LIMNOLOGICAL STUDY OF MALILANGWE RESERVOIR IN THE

Transcription

LIMNOLOGICAL STUDY OF MALILANGWE RESERVOIR IN THE SOUTH-EASTERN LOWVELD
OF ZIMBABWE
By
TATENDA DALU
Thesis submitted in the partial fulfilment of the degree of
MSc Tropical Hydrobiology and Fisheries
Department of Biological Sciences
University of Zimbabwe
Harare, Zimbabwe
JANUARY 2012
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ABSTRACT
The study provides a nine month record of the limnological investigation of the Malilangwe reservoir between
February to October 2011. Malilangwe reservoir is large (211 ha), and shallow (mean depth 4.54) reservoir
situated in the south-eastern lowveld of Zimbabwe. The reservoir has not spilled in nearly 11 years which
makes it a unique system as most reservoirs of comparable size spill annually. This is the first limnological
study of the reservoir, where the physicochemical quality of the water body was examined. The reservoir was
not strongly stratified during the hot-wet and –dry season with oxygen depletion being observed in the bottom
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layers (< 6m depth) of <2 mgl DO concentrations. Nutrients concentrations varied throughout the seasons.
The reservoir exhibits marked seasonal fluctuations in water level and water level decreased by over 149 cm
(February – October). The N: P ratio ranged from 0 – 10.9 and generally reflect higher levels of phosphorus in
the reservoir. There were significant differences (p < 0.05) between the study sites and secchi depth
transparency. Differences observed in the water quality were due to water level fluctuations with low water
quality conditions being experienced during the hot-dry season and the cool-dry season, when water levels
were low. The reservoir was classified as being mesotrophic. Current loadings indicate that nitrogen and
phosphorus concentration in both water and sediment will continue to increase using the 1-Layer PAMOLARE
model. Therefore the risk of eutrophication is a possibility since the reservoir is now just a sink for nutrients.
Seasonal variations of plankton expressed in terms of species composition, cell density and biomass in relation
to a selected physicochemical water parameters, were investigated. A total of 98 phytoplankton species; 2
Dinophyta, 4 Euglenophyta, 14 Bacillariophyta, 50 Chlorophyta, 13 Desmids and 15 Cyanophyta and 68
zooplankton species; 2 others (Chaoborus sp. and Hydracarina), 13 Cladocerans, 7 Calanoids/Cyclopoids and 46
Rotifers were recorded. The Chlorophyta, Dinophyta and Cyanophyceae comprised the bulk of the
phytoplankton, while the Rotifera and Cladocera comprised the bulk of the zooplankton. Seasonal variations in
plankton species composition, density and biomass were high. A typical seasonal succession of plankton
species occurred from February to October. Algal blooms were observed during May to July dominated by
Anabeana sp., Nostoc sp., Anabeana circinalis, Zygenema sp., Anabeana sporiodes, Ceratium hirudinella and
Perinidium sp. Redundancy Analysis (RDA) showed that water level, conductivity, pH, dissolved oxygen,
temperature, reactive phosphorus and macrophyte cover accounted for most of the variations in the plankton
species. The major conclusion is that the plankton community of Malilangwe reservoir was not dominated by
Cyanophyta algae and cladocerans during the entire study period but showed a typical successional pattern.
However, Malilangwe reservoir is an example of a poorly-flushed, nutrient-rich reactor which could perpetuate
the dominance by Cyanophyta algae and cladocerans in the future. Variation in species composition,
distribution and abundance of macrophytes was investigated at 4 sites on three occasions; March (hot-wet
season), June (cool-dry season) and September (hot-dry season) over a 9 month period. Thirteen macrophyte
species representing eight families were recorded during the study period. Submerged macrophytes had a
patchy distribution and mean transect cover per species was below 3% with the exception of Ceratophyllum
demersum and Potamogeton pusillus. Canonical Correspondence Analysis (CCA) identified four distinct
macrophyte groups closely associated with the three seasons; hot-wet, cool-dry and hot-dry and
environmental factors; pH, dissolved oxygen, phosphorus and water level. Change of seasons and subsequent
fluctuations in water levels resulted in successional changes in macrophyte community structure from the
dominant emergent macrophytes (Cyperus sp., Panicum repens, Ludwigia stolonifera, Phragmites mauritianus
and Schoenoplectus corymbosus) in the hot-wet season to submerged macrophytes (Najas sp., Potamogeton
crispus, Potamogeton pusillus, Potamogeton tricarinatus and Persicaria decipiens) in the hot-dry season.
Although changes in water level variations seemed to influence successional macrophyte structure and
composition changes, further research is needed to evaluate to what extent water level fluctuations interact
with other seasonal factors acting independently. A Macroinvertebrates community assessment was carried
out at five sites in Malilangwe reservoir. The main aim was to investigate macroinvertebrate communities so
as to understand factors and processes structuring communities in the reservoir. Forty-two macroinvertebrate
families were identified. Thiaridae and Physidae (Mollusca) were the dominant and most abundant taxa with
Mollusca constituting 57.71 % of the total sample and Hemiptera (27.31 %). Redundancy Analysis revealed
that environmental factors water level, conductivity and macrophyte cover had a strong influence on
macroinvertebrate distribution. It was concluded that macroinvertebrates in the reservoir are unevenly
distributed in space and time, and that they respond strongly to hydrologically linked parameters such as
water level and macrophyte cover and less to water quality variables. Modelling the sedimentation rates with
the aid of remote sensing to assess land degradation was carried out. Using NDVI, the catchment showed
progressive decline of the vegetation over the years as shown by the decrease in cover. An analysis of NDVI
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values using ANOVA identified significant differences between the years and sites (p < 0.05). The reservoir
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capacity to inflow ratio was estimated at 0.8 with a sedimentation rate of 120.1 tkm yr . Calculated
probability of the dam filling is 26.8%. The reservoir is expected to lose 16% of its storage capacity in 100 years
at current sedimentation rates according to the Wallingford method. With such a high capacity-inflow ratio for
the dam, the reservoir is expected to have a short economic life mainly because it has a sediment trap
efficiency of 100%. While acknowledging the limitations of techniques used, this study demonstrates in part
the effectiveness of sedimentation modelling and remote sensing as a tool for the production of baseline data
for assessment and monitoring of levels of land degradation in the Malilangwe reservoir catchment. A fish
diversity fauna survey of the Malilangwe reservoir was conducted taking into account fish surveys done in
Malilangwe reservoir, Save, Chiredzi and Runde Rivers, Hippo Valley swamp and irrigation channels between
February 2009 - 2011. Gill, seine and fyke nets were used to catch fish within the Malilangwe reservoir. Thirtysix fish species belonging to 11 families were recorded in the Malilangwe reservoir, Save, Chiredzi and Runde
Rivers, Hippo Valley swamp and irrigation channels with 8 species from 5 families being recorded from the
reservoir. Ten species recorded were introduced species including four exotics and with six species;
Glossogobius giuris, Hydrocyanus vittatus, Micropterus salmoides, Oreochromis macrochir, Oreochromis
placidus and Labeo altivelis being found in the reservoir. Tilapia rendalli species was of conservation
significance as its habitat was being severely affected by water level fluctuations. Fish diversity differed
between the water systems. An assessment of the impact of Lernaea cyprinacea on fish populations ten years
after its first outbreak was also carried out. Eight fish species from the reservoir were examined for
ectoparasite prevalence and intensity. Two parasite species, L. cyprinacea in Oreochromis mossambiccus,
Oreochromis placidus, Oreochromis macrochir, Labeo altivelis and Tilapia rendalli and trematode cysts
(Clinostomoides brieni) in Clarias gariepinus were found. Lernaea cyprinacea prevalence was 100% amongst all
cichlids but varied for L. altivelis. Parasite intensity increased during the cool-dry season (May – July) with
greatest mean intensity being observed amongst the cichlids. There was a significant relationship between
parasite intensity and environmental factors; dissolved oxygen (r > 0.5, P < 0.05), temperature (r < 0.5, P <
0.001) and pH (r > 0.5, P < 0.001). The continuous spread of L. cyprinacea in the reservoir has potential adverse
implications on fish biodiversity and has the potential to wipe out host populations resulting in loss of
biodiversity and causing an imbalance to the ecosystem. Length-weight relationships and condition factors (K)
for the eight fish species was calculated. The length-weight relationship had a significant positive correlation (r
> 0.5) for the eight species. The growth exponent (b) indicated a negative allometric growth for seven species
(b range = 1.52 – 6.7) with Tilapia rendalli showing positive allometric growth (b = 6.7). Condition factor (K)
values were greater than one (1.34 – 9.29) for O. macrochir, O. mossambicus, C. gariepinus, O. placidus, L.
altivelis and G. giuris while it was less than one for some H. vittatus (0.82 – 3.09) and T. rendalli (0.36 – 4.44)
fishes. The value of K varied with seasons. The Lake Habitat Survey method was developed to assess the
ecological integrity of the physical habitat around lake and reservoir ecosystems and can be used to determine
the magnitude of human pressure on a lake system. The LHS method has not been applied to tropical lakes but
could potentially be a useful tool. The LHS approach was applied on a tropical African lake, Malilangwe
reservoir, in March 2011. The LHS methods that include Lake Habitat Metric Survey (LHMS) and Lake Habitat
Quality Assessment (LHQA) were used to assess the habitat quality and the magnitude of human impact.
Results show that although Malilangwe reservoir is coming under increasing human pressure, it does not
appear to suffer from a major invasion of alien plants. The LHQA score (76 out of 112) and LHMS score (16 out
of 42) are indicative of relatively few human pressures (e.g. water pumping structures and residential areas);
hence the system can be considered natural. We conclude that the use of LHS can directly enhance quality and
reliability of lake assessments and can lead to better lake conservation and rehabilitation. It is clear that for
conservation management, a holistic assessment of naturalness, representativeness and species rarity needs
to be made in conjunction with scoring systems.
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ACKNOWLEDGEMENT
First of all, a special thanks goes to Dr. Tamuka Nhiwatiwa (University of Zimbabwe) and Dr.
Bruce Clegg (Malilangwe Wildlife Reserve) for supervising and guiding this project. Thank
you for the constant confidence and support in me, you are more than the best supervisors
and the encouragement source I could possibly have had.
Secondly, I am especially grateful to my aunt Dr. Vimbainashe Dalu, Dr. Maxwell
Barson, Lightone Marufu, Vincent Maposa (Frost and Sullivan, South Africa), Esther Jairos
(University of Pretoria, South Africa), Gerald Moyo (UNISA, South Africa), Lenin D Chari,
Edwin Tambara and Gregory Dowo whose creative ideas and ability to sniff out
inconsistencies saved me from countless hours of fumbling and potential embarrassment. A
special thank you also goes Godfrey Pachavo of the Department of Geography and
Environmental Studies, University of Zimbabwe for assisting with remote sensing.
Huge thanks also goes to all the Malilangwe Wildlife Reserve staff especially the
Management led by Mark Saunders, the research staff; Philemon Chivambu, Pandeni
Chitimela and Pamushana guides and Kwali staff for diverse help, cooperation and very nice
working environment. The warmest thoughts and hugs goes to my dearest friends;
Thandiwe C Kehle (NUST), Buhleni Henrietta Ncube (University of Free State, South Africa)
Yemurai Chikwangura (University of Porto, Portugal), Zanele Mswela (Witwatersrand
University, South Africa), Edwin Zingwe and Willias Tagwirei for been a constant source of
support and joy in the dark and bright periods during the course of my studies. Strong hugs
also go to my classmates of the Tropical Hydrobiology and Fisheries, Tafadzwa Mahere,
Farnwell Arizhibowa and Michael Tiki for being there all this time and for keeping the
thought that science can and must make this a better world and for trying it despite all
material limitations.
My deepest gratitude to my family, which has been extremely supportive in all my
enterprises, and inspired me to always go further; my parents Christopher and Roselyn,
brothers (Tapiwa, Farai, Dennis, Donald and Christopher), cousins (Shepherd Ruzvidzo,
Jethro, Tendai and Brian Ngwendere) and my unstoppable uncle Job Dalu.
I greatly acknowledge the financial support of the DAAD Scholarship (A/10/02914)
for financing studies and the Malilangwe Postgraduate Research Grant for providing me
with a place to carry out my research studies. My appreciation also goes to Elizabeth
Munyoro and the technical staff; Patrick Mutizamhepo, Clemence Chakuya, Charity
Mupamhanga, Simbarashe Hatidani and Gerald Ashley of the Department of Biological
Sciences, University of Zimbabwe, for all their technical support during the study.
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TABLE OF CONTENTS
ABSTRACT ............................................................................................................................................... 2
ACKNOWLEDGEMENT ............................................................................................................................ 4
GENERAL INTRODUCTION .................................................................................................................... 10
Justification of study ......................................................................................................................... 12
General objective .............................................................................................................................. 12
Thesis structure................................................................................................................................. 13
Study area ............................................................................................................................................. 15
Introduction ...................................................................................................................................... 15
Rainfall .............................................................................................................................................. 17
Temperature ..................................................................................................................................... 18
Relief and drainage ........................................................................................................................... 19
Catchment and runoff ....................................................................................................................... 19
Lake geology ..................................................................................................................................... 20
Water volumes .................................................................................................................................. 21
THE PHYSICOCHEMICAL LIMNOLOGY AND STRATIFICATION OF A SMALL TROPICAL AFRICAN
RESERVOIR AND THE APPLICATION OF A 1-LAYER PAMOLARE MODEL FOR EUTROPHICATION
MANAGEMENT ..................................................................................................................................... 25
INTRODUCTION .................................................................................................................................... 26
METHODS ............................................................................................................................................. 28
Study area ......................................................................................................................................... 28
Stratification...................................................................................................................................... 29
Basic water quality measurements ................................................................................................... 30
Laboratory Procedures ..................................................................................................................... 30
Chemical Oxygen Demand (COD) ..................................................................................................... 30
Nitrate – nitrogen ............................................................................................................................. 30
Ammonia ........................................................................................................................................... 30
Total suspended solids (TSS) ............................................................................................................. 31
Total Nitrogen (TN) ........................................................................................................................... 31
Reactive phosphorus (RP) ................................................................................................................. 31
Total phosphorus (TP) ....................................................................................................................... 31
Nutrient loading ................................................................................................................................ 32
One-layer PAMOLARE model ............................................................................................................ 32
RESULTS ................................................................................................................................................ 33
Stratification...................................................................................................................................... 33
Seasonal variation in dissolved oxygen and temperature ............................................................ 33
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Diurnal stratification in temperature and dissolved oxygen ............................................................ 35
Hot-wet season ............................................................................................................................. 35
Cool-dry season ............................................................................................................................. 35
Hot-dry season .............................................................................................................................. 35
Water chemistry ............................................................................................................................... 38
Nutrients ....................................................................................................................................... 42
One-Layer model for eutrophication management.......................................................................... 44
DISCUSSION .......................................................................................................................................... 46
THE ECOLOGY OF THE PHYTOPLANKTON AND ZOOPLANKTON COMMUNITIES OF A SMALL
TROPICAL RESERVOIR (MALILANGWE, ZIMBABWE) ........................................................................... 50
INTRODUCTION .................................................................................................................................... 51
Study area ......................................................................................................................................... 53
METHODS ............................................................................................................................................. 53
Plankton sampling............................................................................................................................. 53
Chlorophyll (chl-a) ............................................................................................................................. 55
Environmental parameter measurements ....................................................................................... 55
Redundancy Analysis (RDA) .............................................................................................................. 56
Hierarchal Cluster analysis (HCA) ...................................................................................................... 56
RESULTS ................................................................................................................................................ 56
Environmental variables ....................................................................................................................... 56
Phytoplankton....................................................................................................................................... 59
Species composition and seasonal variation .................................................................................... 59
Hierarchal cluster analysis ................................................................................................................ 63
Redundancy analysis ......................................................................................................................... 63
Zooplankton .......................................................................................................................................... 66
Species composition and seasonal variation .................................................................................... 66
Redundancy Analysis (RDA) .............................................................................................................. 69
DISCUSSION .......................................................................................................................................... 71
AQUATIC MACROPHYTES IN A TROPICAL AFRICAN RESERVOIR: DIVERSITY, COMMUNITIES AND
THE IMPACT OF LAKE-LEVEL FLUCTUATIONS ...................................................................................... 77
INTRODUCTION .................................................................................................................................... 78
METHODS ............................................................................................................................................. 81
Study area ......................................................................................................................................... 81
Basic water quality and morphometric measurements ................................................................... 82
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Macrophyte and substrate sampling ................................................................................................ 83
Sediment analysis ............................................................................................................................. 83
Data analysis ..................................................................................................................................... 84
Canonical Correspondence Analysis (CCA) and Hierarchal Cluster analysis (HCA)........................... 84
RESULTS ................................................................................................................................................ 84
Littoral zone substrate characteristics .............................................................................................. 84
Environmental variables ................................................................................................................... 85
Macrophyte distribution ................................................................................................................... 87
Canonical cluster analysis (CCA) ....................................................................................................... 90
DISCUSSION .......................................................................................................................................... 93
THE MACROINVERTEBRATE COMMUNITIES ASSOCIATED WITH LITTORAL ZONE HABITATS OF A
SMALL RESERVOIR AND THE INFLUENCE OF ENVIRONMENTAL FACTORS......................................... 99
INTRODUCTION .................................................................................................................................. 100
Study area ....................................................................................................................................... 102
METHODS ........................................................................................................................................... 102
Basic water quality measurements ................................................................................................. 102
Macroinvertebrate sampling .......................................................................................................... 103
Data analysis ................................................................................................................................... 104
Assessment of similarity among sampling sites.............................................................................. 104
Assessment of taxa dominance and diversity................................................................................. 104
Assessment of the influence of environmental factors on macroinvertebrate communities ....... 105
RESULTS .............................................................................................................................................. 105
Environmental variables ................................................................................................................. 105
Macroinvertebrate diversity ........................................................................................................... 106
Assessment of similarity among sampling sites.............................................................................. 109
Macroinvertebrates species rank dominance analysis ................................................................... 110
Influence of environmental factors on macroinvertebrate communities ...................................... 111
DISCUSSION ........................................................................................................................................ 114
MODELLING SEDIMENTATION RATES OF MALILANGWE RESERVOIR, WITH THE AID OF REMOTE
SENSING TO ASSESS LAND DEGRADATION IN THE CATCHMENT...................................................... 118
INTRODUCTION .................................................................................................................................. 119
Impacts of sedimentation ............................................................................................................... 121
Study area ....................................................................................................................................... 122
METHODS ........................................................................................................................................... 123
Assessment of changes in vegetation cover using remote sensing................................................ 123
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Storage capacity losses due to siltation .......................................................................................... 127
RESULTS .............................................................................................................................................. 127
NDVI Analysis .................................................................................................................................. 127
Sedimentation rates and reservoir capacity - inflow ratios ............................................................ 131
DISCUSSION ........................................................................................................................................ 132
A STUDY OF THE ICHTHYOFUANA OF A SMALL TROPICAL RESERVOIR IN SOUTH-EASTERN
ZIMBABWE.......................................................................................................................................... 138
INTRODUCTION .................................................................................................................................. 139
Study area ....................................................................................................................................... 141
METHODS ........................................................................................................................................... 142
Fish surveys ..................................................................................................................................... 142
RESULTS .............................................................................................................................................. 143
Fish communities, abundance and diversity................................................................................... 143
Reproductive (gonad) state ............................................................................................................ 148
Regional species diversity assessment ........................................................................................... 149
DISCUSSION ........................................................................................................................................ 151
IMPACT OF LERNAEA CYPRINACEA LINNAEUS 1758 (CRUSTACEA: COPEPODA) ALMOST A DECADE
AFTER AN INITIAL PARASITIC OUTBREAK IN FISHES OF MALILANGWE RESERVOIR, ZIMBABWE ... 156
INTRODUCTION .................................................................................................................................. 157
Study area ....................................................................................................................................... 158
METHODS ........................................................................................................................................... 158
Fish surveys ..................................................................................................................................... 158
RESULTS .............................................................................................................................................. 160
Environmental variables ................................................................................................................. 160
Parasite prevalence and intensity ................................................................................................... 161
DISCUSSION ........................................................................................................................................ 164
LENGTH-WEIGHT RELATIONSHIPS AND CONDITION FACTOR OF 8 FISH SPECIES CAUGHT USING GILL
NETS IN A TROPICAL AFRICAN RESERVOIR, ZIMBABWE ................................................................... 167
INTRODUCTION .................................................................................................................................. 168
METHODS ........................................................................................................................................... 169
Statistical analysis ........................................................................................................................... 170
RESULTS .............................................................................................................................................. 171
DISCUSSION ........................................................................................................................................ 174
THE FEEDING HABITS OF AN INTRODUCED PISCIVORE, HYDROCYNUS VITTATUS (CASTELNAU 1861)
IN A SMALL TROPICAL AFRICAN RESERVOIR ..................................................................................... 177
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INTRODUCTION .................................................................................................................................. 179
Study area ....................................................................................................................................... 180
METHODS ........................................................................................................................................... 181
Fish survey and analysis .................................................................................................................. 181
RESULTS .............................................................................................................................................. 182
DISCUSSION ........................................................................................................................................ 185
APPLICATION OF THE LAKE HABITAT SURVEY (LHS) METHOD IN A TROPICAL AFRICAN LAKE: A CASE
STUDY OF MALILANGWE RESERVOIR, SOUTH-EAST LOWVELD, ZIMBABWE ................................... 188
INTRODUCTION .................................................................................................................................. 189
METHODS ........................................................................................................................................... 190
Study area ....................................................................................................................................... 190
LHS survey method ......................................................................................................................... 191
Lake Habitat Quality Assessment (LHQA) ....................................................................................... 193
Lake Habitat Modification Score (LHMS) ........................................................................................ 194
RESULTS .............................................................................................................................................. 194
Index site ......................................................................................................................................... 194
LHS survey ....................................................................................................................................... 197
LHQA and LHMS .............................................................................................................................. 201
Vegetation....................................................................................................................................... 201
Remote sensing and aerial imagery ................................................................................................ 203
DISCUSSION ........................................................................................................................................ 206
REFERENCES ........................................................................................................................................ 211
APPENDIX I ......................................................................................................................................... 231
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GENERAL INTRODUCTION
Small water bodies are broadly defined and represent a variety of aquatic systems. These
include reservoirs and/or lakes less than 10 km2 (1000 ha), ponds, canals, rivers less than
100 km long and small seasonal floodplains (Marshall and Maes 1994; Potts 2003). In
southern Africa alone, the total number of small water bodies is estimated between 50 000
and 100 000 (Verheust 1998), of which most are reservoirs. Zimbabwe has particularly a
large number of small dams estimated at 14 000, constituting about 86% of the number of
small dams in Southern Africa excluding South Africa. Most of the small dams are built
across seasonal rivers which dry up during the dry season (Nhiwatiwa 2004). The dynamics
of river systems of Zimbabwe and their fishes changed completely in 1902 with completion
of the Matopos Dam built by Cecil Rhodes. Since then, dams have been built on almost
every river in the country (Marshall 2010). The large number, uneven distribution and oftenremote locations of these water bodies complicate the development and management of
small reservoir (Jackson and Ssentongo 1988, Potts 2003, Mustapha 2009).
Reservoirs are structures designed to store or divert water with the intension to alter
the natural distribution and timing of stream flows in order to meet human needs. As such,
they also alter essential natural ecosystem processes and functions (Mustapha 2009,
Bergkamp et al. 2000). Reservoirs constitute obstacles for longitudinal exchanges along
rivers thus by altering the pattern of downstream flow in terms of intensity, timing and
frequency; they change sediment and nutrient regimes and alter water temperature and
chemistry (Bergkamp et al. 2000). Storage reservoirs flood terrestrial ecosystems, killing
terrestrial plants and displacing animals. As many species prefer valley bottoms, large scale
impoundment may eliminate unique wildlife habitats and extinguish entire populations of
endangered species (Bergkamp et al. 2000).
Most of the small water bodies experience wide fluctuations in water level from one
year to another due to annual rainfall variation and water management regimes. Some
organisms inhabiting such water bodies have developed mechanisms for dealing with
periodic droughts such as immigration or aestivation but plankton have low mobility and are
therefore unable to avoid environmental changes imposed by fluctuating water levels which
cause variations in physicochemical variables (Nhiwatiwa 2004). Water quality studies have
shown large and reproducible 24 hour diurnal variations in temperature, dissolved oxygen,
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pH, conductivity and nutrients for large dams (Baxter et al. 1965, Arcifa et al. 1990, Gonzalez
et al. 2004, Nhiwatiwa and Marshall, 2006, Graham et al. 2008). Diurnal variations in
nutrients and physicochemical variables have been observed to fluctuate significantly on a
daily cycle.
Reservoirs are not constant systems, a phenomenon reflected by the distribution of
fishes within them (Janjua et al. 2009, Marshall 2010). Creation of reservoirs may change
the basic limnological characteristics of water bodies. This in turn has a profound effect on
fish populations, mainly due to creation of new micro-habitats. Reservoirs also affect rivers
and their fish fauna downstream, with their characteristic walls acting as impenetrable
barriers to fish movements (Bergkamp et al. 2000, Marshall 2010). As a result, this
disruption of fish migratory patterns may lead to species decline or speciation (Marshall
2010). Marshall and Minshull (2004) highlighted that damming is among the main causes of
decline in many of Zimbabwe’s fish riverine species.
Small reservoirs are generally characterised by a low number of species (Marshall
and Maes 1994). Due to low diversity level and small sizes, these small reservoirs are
relatively less studied. For this reason there is very little information available for African
small water bodies and this makes management of small reservoirs difficult. The study of
shallow reservoirs limnology and fisheries potentials is scanty despite their high potentials
for fish production as compared with large reservoirs (Mustapha 2009; Nhiwatiwa 2004).
A conservationist view argues that dams, even when designed to minimise
environmental impacts, result in significant negative impacts to a wide range of natural
ecosystems and to the people that depend upon them for their livelihood (Bergkamp et al.
2000). At a time when pressures upon diversity and productivity of the world’s natural
resources continue to rise, it is argued that firm action is required to prevent loss of these
resources through further dam construction (Bergkamp et al. 2000, Mustapha 2009).
Small reservoirs have been largely neglected in hydrological and water resource
research because of the combination of several characteristics such as their small size and
widespread distribution. Adequate ground-based data on small reservoir storage volumes
are commonly not available. Conducting ground-based surveys and measurements on a
regional scale is prohibitively expensive and also time consuming (Andreine et al. 2009).
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Management of reservoirs requires a multifaceted approach in order to have
baseline information for managers to make the right decisions. Malilangwe reservoir can be
classified as a small reservoir but it has not spilled in nearly 10 years because of its raised
dam. This is most unusual for a reservoir of its size as most small dams have short retention
times (Nhiwatiwa and Marshall, 2006). It is therefore an ideal case study on reservoir
management but at the same time there is need for a scientific investigation into the
limnology of this reservoir as a first step towards a sustainable dam management strategy. A
major challenge of Integrated Water Resources Management (IWRM) is to balance water
allocation between different users or stakeholders that includes the environment. While
economically and/or politically powerful users have relatively well developed methods for
quantifying and justifying their water needs, this is not the case for ecosystems – the silent
water user. The main of this research was to study the limnological and ecological features
of Malilangwe reservoir.
Justification of study
Small reservoirs in Zimbabwe are often neglected though they support a number of
activities and provide ecosystem services in many parts of the country. This is shown by the
fact that very little information exist on their limnology. Nhiwatiwa (2004) noted that there
is a historical bias in limnological investigations towards larger water bodies like Lake Kariba
and Chivero that has resulted in small reservoirs being studied less. The knowledge we have
about the limnology of small reservoirs is still not adequate, and hence further
investigations into this topic are still warranted. As a result of lack of basic limnological and
hydrological knowledge, and the potential for water quality to change as a result of
anthropogenic activities, it is important to assess limnological conditions of small reservoirs
that exist in Zimbabwe. Knowledge of changes in water quality as well as the responses of
the biota in small reservoirs could constitute an important tool that can be used by water
managers to continuously and rapidly assess the water quality.
General objective
An investigation of the limnological characteristics of Malilangwe reservoir in the southeastern Lowveld of Zimbabwe with an overall objective to present management
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recommendations for this reservoir. Specific research objectives are given in more detail for
the research topics in each chapter. To achieve this objective the study will be divided into
seven chapters.
Thesis structure
The physicochemical limnology, diurnal and seasonal stratification of Malilangwe
reservoir and IETC-UNEP management for shallow lakes. This chapter deals with water
quality, thermal and dissolved oxygen regimes, associated circulation and stratification
patterns and IETC-UNEP management of shallow Lakes. The main objective is to investigate
water level fluctuation and its influence on physicochemical characteristics. Since changes in
the water and sediment chemistry determines water quality and has immediate effects on
the general productivity of the dam and its suitability as habitats for aquatic communities.
The understanding of seasonal and diurnal stratification is important in the development
and implementation of appropriate management strategies. It also defines management
plan for the reservoir using the IETC-UNEP Pamolare software.
The composition and abundance of plankton communities in a tropical freshwater
reservoir. This research topic looks at the plankton communities. The main objective is to
assess the plankton community structure in relation to the dam water quality and
hydrology.
Aquatic macrophytes in a tropical African lake: diversity, communities and the impact of
lake-level fluctuations. The objective was to determine the macrophyte species cover,
composition, species richness and succession in Malilangwe reservoir, as well as try to
determine how the macrophyte communities respond to water level fluctuations in
different seasons.
The macroinvertebrate communities associated with littoral zone habitats of a small
reservoir and the influence of environmental factors. The aim was to determine freshwater
macroinvertebrates communities found in the littoral and sediment zones of the reservoir.
The role of environmental factors on taxon richness, diversity, relative abundance,
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distribution and dominance of invertebrates was also investigated at selected sites during
the study period.
Modelling the sedimentation rates of Malilangwe Reservoir, with the aid of remote
sensing to assess land degradation in the catchment. The main aim of this chapter was to
assess changes in land use and model the impacts this would have on sedimentation rates in
the Malilangwe reservoir.
The ichthyofuana of a tropical African Reservoir (Malilangwe, Zimbabwe). The chapter
look at the fish communities with the main objective being the assessment of the fish
communities and their diversity. Changes in fish species abundance and how they cope with
seasonal changes and water quality were looked at.
Impact of Lernaea cyprinacea Linnaeus 1758 (Crustacea: Copepoda) almost a decade after
an initial parasitic outbreak in fishes of Malilangwe reservoir, Zimbabwe. The purpose of
this topic was to assess the current status of L. cyprinacea infestation, about nine years
following its initial appearance on fishes of the Malilangwe reservoir. The topic aimed at
investigating the distribution within the different seasons and assesses the general
prevalence and intensity of fish parasitism within the reservoir.
Length-weight relationships of 8 fish species caught using gill nets in a tropical African
reservoir, Zimbabwe. This chapter was initiated to fill this gap in information and also
provide useful information for fish management and conservation in Malilangwe reservoir
by looking at the length-weight relationships and condition factors of fish caught using
gillnets.
The feeding habits of an introduced piscivore, Hydrocynus vittatus (castelnau 1861) in a
small tropical African reservoir. This topic considers the food composition of H. vittatus in
Malilangwe reservoir in an attempt to determine how much dietary overlap there is
between different size-classes. It aims to fill the gap on feeding ecology of introduced
tigerfish in small lakes and reservoirs.
14
Application of the Lake Habitat Survey (LHS). The chapter aims to analyse and determine
the current state of the Malilangwe reservoir habitat using LHS. Secondly, to provide a
method for characterizing and assessing the physical habitat of a lake through quantitative
descriptions of canopy, macrophytes, amount of shoreline affected by human activities and
the determine the dominant littoral substrate.
General discussion. The final chapter presents a general discussion of experimental findings,
highlights future research opportunities and concludes with a summary of contributions
made by this thesis and management recommendations.
Appendices are numbered sequentially and are included with the references at the end of
the thesis.
Study area
Introduction
Malilangwe Wildlife Reserve formerly known as Lone Star is a wildlife reserve located in the
Chiredzi District, south-eastern lowveld region of Zimbabwe (20°58’ - 21°02’ S, 31°47’ 32°01’ E) (Figure 1). The Chipimbi, Chiredzi and Runde Rivers demarcate the western
boundary between Maranatha Ranch, Hippo Valley Game Reserve and Matibi II Communal
Land respectively. The reserve is bounded to the south by Gonarezhou National Park, to the
east by Chizvirizvi Communal Land, and to the north by resettlement land (Clegg 2010).
The Malilangwe reservoir (altitude 360 m) on the Nyamasikana River is a gravity
section masonry dam. It was designed by the Department of Water Development and was
constructed in 1964 by Ray Sparrow and his family. The wall was initially built to a height of
10 metres and the dam first filled in 1965. In 1965 the wall was raised to a height of 19
metres, in 1984 to 22 metres and finally to 24 metres in 1988. Most recently by another
1.75 metres in late 1999 to the current height of 25.75 metres. At full supply level the
maximum depth is 25.75 metres and the volume of water is 1.25 x 107m3.
Malilangwe reservoir has an area of 211 hectares and is located on the Nyamasikana
River, a tributary of the Chiredzi River which in turn flows into the Runde River. Flanked by
15
rocky hills on most of its sides, the impoundment has a rocky substrate with few sandy bays.
It is poorly vegetated with few marginal plants including Azolla fuculoides, grass, Ludwigia
stolonifera, Potamogeton sp., Schnoeplectus corymbosus and sedges (Cyperus sp. and
Phragmites mauritanus). The fish communities comprises of predators, omnivores,
detritivores, micro amd macrophages (Barson et al. 2007). Shore line development (DL) is
important because it reflects the potential for development of littoral communities, which
are usually of high biological productivity. A larger ratio means the shoreline is more
crenulated and hence the potential for littoral community development is greater and
Malilangwe reservoir has a DL of 1.83 (Table 1).
Five sampling points were selected along the dam. Site 1 is located in the deepest
part and next to the dam wall. Site 2 is located at a point between the hill, site 3 is located in
the middle of the lake (open waters), site 4 is the point when the dam narrows and site 5 is
where the Nyamasikana River enters the Lake (Figure 1; Table 2).
Table 1: Some morphometric characteristics of Malilangwe reservoir, calculated according
to Huntchinson (1957).
Volume (x 106 m3)
Surface area (ha)
Maximum depth (Z)
Mean depth (Zm)
Volume development (Dv)
Maximum length (m)
Shoreline length (m)
Shoreline development (DL)
12
211
14.30
4.54
0.95
3187
9415
1.83
Table 2: Coordinates for the different study site locations in Malilangwe reservoir.
Site
1
2
3
4
5
S
021 03' 25.6"
021 03' 01.6"
021 02' 41.2"
021 02' 26.2"
021 02' 10.4"
E
031 52' 34.5"
031 52' 27.2"
031 52' 27.6"
031 52' 42.3"
031 52' 59.8"
16
Rainfall
Mean annual rainfall collected at Malilangwe Headquarters is approximately 562 mm, but is
very variable both within and between seasons. The average annual rainfall for Malilangwe
is extremely erratic and the lowveld area is prone to drought (Davy, 2005). The rainy season
extends from November to March, when most precipitation (80%) is in the form of local
heavy downpours of short duration, although spells of up to two weeks of widespread cloud
and light drizzle ('guti' weather) also occur (Davy 2005; Kelly and Walker 1976). Temporal
pattern of wet season rainfall is characterized by sequences of approximately 9 years above
or below the long term mean although a number of years are well out of phase. Four years
(1964, 1972, 1982 and 1991) are conspicuously drier than the rest and mark the occurrence
of severe drought (Figure 3) (Davy 2005; Traill 2003). May – September are the driest
months and in times of drought, January is known as almost rainless and although this
month is in fact the wettest month. The pattern of rainfall during the month is such that it
appears as if this month is the driest month during the rainy season (Figure 2) (Clegg 2010;
Booth 1980).
Figure 1: Malilangwe reservoir in the south-eastern lowveld region of Zimbabwe.
17
Figure 2: Mean monthly rainfall calculated from a 56 year record (1951 - 2010) collected at
Malilangwe Head Quarters. Approximately 84 % of rainfall occurs between
November and March.
Figure 3: Seasonal mean rainfall deviation from the September - August calculated for a 56
year record (1951 - 2007) collected at Malilangwe Head Quarters. Adapted from
Clegg (2010).
Temperature
Temperatures are high with most daily maxima in excess of 32 oC throughout the year and
peak temperatures during hot spells in the summer often over 45 oC. Winters are generally
cool, with temperatures ranging from 5 oC – 26 oC with frost virtual absent (Traill 2006). The
annual average evaporation has been estimated at c. 2000 mm (Kelly and Walker 1976). The
climate is characterised by a hot wet season from November to March, a cool dry season
from March to August, and a hot dry season from September to October (Clegg 2010).
18
Figure 4: Average monthly maximum and minimum temperatures calculated for a 10 year
record (2001 - 2010) collected at Malilangwe Head Quarters.
Relief and drainage
The land surface of the reserve slopes gently downwards in a south-westerly direction
towards the Chiredzi and Runde Rivers, with altitudes of 510 m (Hunyungwe in Malilangwe)
to 300 m at the Chiredzi – Runde River confluence. The Chipimbi, Gananda and
Nyamasikana Rivers which flow into the Chiredzi River, drain the west, north and central
regions of the reserve. The eastern and southern parts are drained by the Nyamsaan,
Mulovele, Mahande and Chiloveka Rivers which flow into the Runde River in the South. The
Chiredzi and Runde are the only perennial rivers. The Nyamasikana River only carries water
during the rainy season after heavy rains (Clegg 2010).
Catchment and runoff
Runde catchment has an 41 000 km2 and is one of the three catchments that lie in the driest
parts of the country covering natural regions III, IV and V and major districts and towns,
stretching from Gweru to Gonarezhou. It constitutes 22% of the country area and 40% of
this catchment is in communal lands (Mugabe et al. 2007). The Department of Water
19
Development divided Zimbabwe into 6 hydrological zones, A to F, and the Runde catchment
falls within the Hydrological zone E, which comprises areas drained by Runde, Tokwe,
Mutirikwi and Chiredzi Rivers and finally draining into the Limpopo River (McCartney et al.
1998). Its mean annual rainfall is about 684 mm and droughts are frequent (Mugabe et al.
2007).
Malilangwe reservoir lies in the Lower Runde sub-catchment with an area 1700 km2
and a mean runoff of 50.03 mm (max 199 mm and min 0.3 mm runoff) using rainfall - runoff
relationship for the Lower Runde catchment (R = 0.0019P + 48.966, R2 = 4 x 10-5, where P =
rainfall and R = run-off ) from Mugabe et al. (2007). Nyamasikana River mean monthly flows
vary greatly between 0 mm in the dry months and 71 mm in the wet months and mean daily
flows at severe rain event may be much larger. The mean annual total runoff for the
Malilangwe catchment (200km2) is 1 x 107 m3yr-1. The estimated theoretical water residence
time for Malilangwe reservoir was calculated by dividing maximum volume by mean annual
inflow rate to give:
12496259.92 m3 / 7615.35838 m3 day-1 = 1607 days (4.4 years)
The water level fluctuations are more severe for Malilangwe reservoir over a 10 year
period. Water level fluctuations are more severe for Malilangwe reservoir over a 10 year
period as shown by the dam water levels (Figure 5).
Figure 5: Malilangwe reservoir level measured as meters below spill.
Lake geology
Classification of the dam bottom types undertaken by the simultaneous interpretation of
the side scan sonar mosaic and bathymetric data showed ten major bottom types, as well as
numerous submerged trees and high relief boulders (Figure 6). The main channel appears to
20
be generally filled with sandy fluvial sediment including the spit which is incised and some
minor channels, but the southern neck region has boulders extending into the channel. The
main channel basin is also flanked by steep alluvial banks which are also incised by gully
features which may have been produced by animals accessing the river prior to the area
being dammed. Areas with boulders including boulder piles of possible anthropogenic origin
and numerous submerged trees occur within these alluvial deposits. A ridge structure
striking east-west could be the surface expression of an igneous dyke and boulders
associated at the top of the ridge may have originated from this intrusive rock? The southeastern and south-western margins of the central basin are composed mainly of rock and
boulders. The southern neck region of the dam is constricted by sandstone cliffs and hills
and the geology of the bottom reflects this with the rocks and boulders being the dominant
bottom type. The alluvial deposits have high densities of boulders dispersed throughout
(Thackeray and Leuci 2008).
Water volumes
Water volumes for the Malilangwe reservoir (Table 3, Figure 7) calculated only for the area
covered by the hydrographic survey with the upper portions of the main tributary leading in
to the dam not being surveyed and therefore this area not forming part of the water volume
estimates. The reservoir volumes calculated was slightly less than the actual reservoir
volume. The difference between the calculated volumes for the survey area and the actual
reservoir capacity will become progressively less as the dam water level drops. This is
because as the water level recedes the contribution from the upper tributary will decrease
rapidly (Thackeray and Leuci 2008).
21
Figure 6: Geological classification map of Malilangwe reservoir. Adapted from Thackeray
and Leuci (2008).
22
Table 3: Malilangwe reservoir different water levels. Modified from Thackeray and Leuci
(2008).
Ellipsoidal Height
369.67
369.17
368.67
368.17
367.67
367.17
366.67
366.17
365.67
365.17
364.67
364.17
363.67
363.17
362.67
362.17
361.67
361.17
360.67
360.17
359.67
359.17
358.67
358.17
357.67
357.17
356.67
356.17
355.67
355.17
354.67
Relative to Spillway level (m)
0
-0.5
-1
-1.5
-2
-2.5
-3
-3.5
-4
-4.5
-5
-5.5
-6
-6.5
-7
-7.5
-8
-8.5
-9
-9.5
-10
-10.5
-11
-11.5
-12
-12.5
-13
-13.5
-14
-14.5
-15
Volume (m3)
12496259.92
11823553.29
11285784.34
10714717.67
10282575.88
9910174.22
9589578.54
8728982.48
7919958.52
7160960.63
6450442.75
5786858.84
5168662.83
4594308.69
4062250.35
3570941.78
3118836.92
2704389.72
2326054.13
1982256.52
1671538.58
1392256.52
1142906.87
921938.58
727805.60
558961.87
413861.36
290958.00
188705.76
105558.57
39970.39
23
Figure 7: Contour map of Malilangwe reservoir with depths corrected to water level height
at time of survey (zero datum = water level). Adapted from Thackeray and Leuci
(2008).
24
THE PHYSICOCHEMICAL LIMNOLOGY AND STRATIFICATION OF A SMALL TROPICAL
AFRICAN RESERVOIR AND THE APPLICATION OF A 1-LAYER PAMOLARE MODEL FOR
EUTROPHICATION MANAGEMENT
25
INTRODUCTION
Limnology in the tropics has only recently developed past the stage of exploration (Lewis
2000). Despite the large number of small storage reservoirs and lakes, baseline limnological
information is available for relatively few (Hart 1999, Nhiwatiwa and Marshall 2007,
Quarcoopome et al. 2008). The baseline limnological information that exists on small
reservoirs and lakes is often insufficient, and is often based on once-off or short term
studies, while the limnology of large and medium sized African reservoirs has been
extensively studied (Moss and Moss 1969, McLachlan 1974, Dӧrgeoloh et al. 1993,
Mustapha 2008). Seasonally comprehensive data are seldom available for a complete year,
let alone spanning sufficient time to encompass the inherent hydrological variability of the
region (Hart 1999). The large density per unit area of the small reservoirs in most part of the
continent, with Zimbabwe having about 14000 small reservoirs (Nhiwatiwa and Marshall
2007), has significant impacts on the aquatic ecosystems. These impacts include changing
seasonal flow patterns of streams and rivers that in turn affect aquatic species migration
(Jackson and Marmulla 2001, McCartney and Sally 2005) and water level fluctuations which
influence physicochemical characteristics of reservoirs and lakes (McLachlan 1969,
Nhiwatiwa and Marshall 2007).
Water quality deterioration in reservoirs and lakes usually comes from excessive
nutrient inputs and organic pollution causing eutrophication, acidification and heavy metal
contamination (Djukic et al. 1994, Mustapha 2008). The effects of these inputs into the
reservoir do not only affect the socioeconomic functions of the reservoir negatively, but also
bring loss of structural biodiversity of the reservoir. The changes in physicochemical
characteristics provide valuable information on water quality, variation sources and impacts
on the functions and biodiversity of the reservoirs (Mustapha 2008).
Various models have been introduced for the management of eutrophic lakes and
wetlands, which are based on physical, chemical and biological properties of water
resources. These include mechanistic eutrophication models such as CE-QUAL-W2-WASP5
(Ambrose et al. 1993, Bowen 1997, Lung 2003), Total Maximum Daily Load (TMDL) (Ernst et
al. 1994), BATHTUB model (Kennedy 1995, Dye 2006), Phosphorus Budget Model
(Mukhopadhyay and Smith 2000) and Environmental Fluid Dynamics Code (EFDC) and
26
ECOSED (Lung 2003). The Planning And Management Of Lakes And Reservoirs
focusing on Eutrophication (PAMOLARE) was introduced for the first time at the third
International Workshop on Regional Approaches for the Development and Management of
Reservoirs in the La Plata Basin in Posadas, Argentina. This method was produced at
University of Kyoto after a request by IETC and IUCN (Jørgensen 1994). PAMOLARE is used
for management and control of eutrophication in eutrophic wetlands and lakes (UNEP-DTIEIETC and ILEC 2001). The PAMOLARE model is useful for predicting the outcomes from lake
and wetland management strategies and thereby aiding decision making for water
resources managers (Jørgensen and de Rast 2007).
The majority of reservoirs in tropical Africa are shallow and polymitic and are found
in regions where evaporation approaches or exceeds precipitation with water typically
derived from rivers (Mustapha 2009). These reservoirs are usually filled up with water in the
rainy season, but become greatly reduced during the dry season as a result of evaporation,
sedimentation, water withdrawal and municipal water usage. These tropical African
reservoirs have short water residence time, small size, with large watershed, high shoreline
development ratio and large water fluctuations due to seasonal influences. They are often
not properly managed (Mustapha 2009).
The most important input quantities during daytime in natural shallow water is the
incoming short and long wave radiation, air temperature and wind speed (Kastev et al.
2010, Jacobs et al. 1997). Long wave radiation is absorbed at the top of the water body, as
well as a large part of the incoming short wave radiation. During the day this leads to a
stable stratification in small natural water bodies. High wind speed may cause a strong
forced mixing to occur which leads to more or less to an isothermal water temperature.
During night time, the most important forcing term is the long wave radioactive cooling, this
triggers the growth of a mixing layer starting from the water-atmosphere interface.
Depending on the weather regime, the water temperature behaviour in shallow waters is
very dynamic and complex (Jacobs et al. 1997). Given the advances in understanding of the
structure and energetics of mixed layers, it is surprising that in tropical lakes even the most
fundamental information, such as persistent thermocline depth and stability of
stratification, is so limited (Nhiwatiwa and Marshall 2006).
27
Water quality is the sum total of its physicochemical properties and generally gives
information of the nutrient status, productivity and sustainability of a water body. Largescale blooms of cyanobacteria in Malilangwe reservoir have raised concerns about water
quality problems. The aim of this study was to investigate the the physical and chemical
characteristics of the water of Malilangwe reservoir to assess the water quality and also
determine impacts of water level fluctuations on water quality. Finally, the application of a
one-layer model of PAMOLARE 3 software (UNEP-DTIE-IETC and ILEC 2001) was used to
determine a management plan for the reservoir.
METHODS
Study area
Malilangwe Wildlife Reserve is located in the Chiredzi District of the south-eastern lowveld
of Zimbabwe (20°58’ 21°02’ S, 31°47’ 32°01’ E) (Figure 1). Malilangwe Reservoir is an
impounded river formed in 1964 and is used for water supply in the reserve. It is situated on
the Nyamasikana River, a tributary of the Chiredzi River which in turn flows into the Runde
River. It is a gravity section masonry dam with a surface area of 211 hectares with maximum
volume of 12 x 106 m3 at full capacity. Flanked by rocky hills on most of its sides, the
impoundment has a rocky substrate with few sandy bays. It is poorly vegetated with few
marginal plants including Azolla filiculoides (Lam), Ludwigia stolonifera (Guill and Perr)
Raven, Panicum repens (Lam), Schoenoplectus corymbosus (Roth ex Roem and Schult)
Raynal, Potamogeton sp. and sedges (Phragmites mauritianus (Kunth) and Cyperus sp.). The
fish communities include predators, omnivores, detritivores, micro amd macrophages
(Barson et al. 2008).
Sampling was carried out in the Malilangwe reservoir throughout the three seasons
(hot-wet, cool-dry and hot-dry) between February – October 2011. All water samples were
collected around midday so as to standardize sampling and reduce diurnal biases according
to Nhiwatiwa (2004). Five sites were selected along the reservoir length and sampling was
done during the last week of each month. A 10 litre Rutner sampler was used to collect
water samples through the water column at 1 m intervals from the bottom of the lake to
the water surface. The collected water samples were stored in 500 ml polythene bottles and
stored in ice before being analysed within 24 hrs in the laboratory.
28
Figure 1: Location of littoral zone sampling sites around Malilangwe Reservoir (shaded
area).
Stratification
Measurements were done once a month throughout the three seasons (hot-wet, cool-dry
and hot-dry) (February to October) from the deepest point of the lake (Site 1) and it should
be noted that the sampling strategy did not consider spatial variations due to time
limitations, hence one site was selected. The seasonal pattern of stratification was
determined by measuring temperature and dissolved oxygen at 1 m intervals using an
oxygen meter (LDO HQ20, HACH). The diurnal variations in temperature and dissolved
oxygen were determined by taking readings at 2 hour (hr) intervals over a 24 hr period for
the three different seasons; February (hot-wet), June (cool-dry) and October (hot-dry).
29
Basic water quality measurements
Water was collected at each site with measurements of pH, conductivity, total dissolved
solutes, temperature and dissolved oxygen (DO) was done using a pH, Conductivity and DO
meter (HACH, LDO, Germany). Water transparency was measured using a Secchi disk.
Chemical oxygen demand (COD), Nitrogen, nitrates, total and reactive phosphorus were
determined using standards methods from EPA, Hach and Standard Methods.
Laboratory Procedures
Chemical Oxygen Demand (COD)
COD was determined by the closed-reflux digestion (EPA Method 410.4, Hach Method 8000
and Standard Method 5520D). The first step was digestion, where concentrated sulphuric
acid (H2SO4) provided the primary digestion catalyst and the secondary catalyst, Silver
Sulphate (AgSO4), assists oxidization of straight-chain hydrocarbons such diesel fuel and
motor oil. The heat from the digestion block (150 °C) also acts as a catalyst. During digestion
the sample’s organic carbon (C) material is oxidized with the hexavalent dichromate ion
(Cr2O7 2-) found in potassium dichromate (K2Cr2O7). The dichromate readily gives up oxygen
(O2) to bond with carbon atoms to create carbon dioxide (CO2). The oxygen transaction from
Cr2O72- to CO2 reduces the hexavalent Cr2O72- ion to the trivalent Cr3+ ion. The Cr6+ remaining
were then determined by measuring absorbance at 420 nm (O'Dell, 1993). In essence a COD
test determines the amount of carbon based materials by measuring the amount of oxygen
the sample will react with. The precision is at standard deviation of ± 2.7 mgl-1 COD.
Nitrate – nitrogen
Nitrate – nitrogen was determined by the chromotropic acid method (Hach method 10020).
The nitrate in the sample reacted to give a yellow product with maximum absorbance at 410
nm. The precision is at standard deviation ± 0.2 mgl-1 N.
Ammonia
Ammonia was determined by the salicylate method (Hach method 10023). Ammonia
compounds combine with chlorine to form monochloramine. Monochloramine reacts with
salicylate to form 5-aminosalicylate. The 5-aminosalicylate is oxidized in the presence of a
30
sodium nitroprusside catalyst to form a blue coloured compound. The blue colour is masked
by the yellow colour from the excess reagent present to give a green-coloured solution. Test
results are measured at absorbance of 655 nm. The precision levels are at standard
deviation of ± 0.03 mgl-1 N.
Total suspended solids (TSS)
TSS was determined by the photometric method (Hach method 8006). A 500 ml of sample is
blended at high speed for exactly two minutes. The blended sample is then poured into a
600-mL beaker and stirred immediately and sample poured into a 10 ml sample cell. Test
results are measured at absorbance 810 nm.
Total Nitrogen (TN)
TN was determined by the persulphate digestion method (Hach method 10071). An alkaline
persulphate digestion converts all forms of nitrogen to nitrate. Sodium metabisulphite is
added after the digestion to eliminate halogen oxide interferences. Nitrate then reacts with
chromotropic acid under strongly acidic conditions to form a yellow complex with an
absorbance maximum at 410 nm. The precision levels are at standard deviation of < 1 mgl-1
N.
Reactive phosphorus (RP)
RP was determined by the PhosVer 3 method (Hach method 8048, USEPA Method 365.2
and Standard Method 4500-P E). Orthophosphate reacts with molybdate in an acid medium
to produce a phosphomolybdate complex. Ascorbic acid then reduces the complex, giving
an intense molybdenum blue colour. Absorbance was measured at 890 nm and the
precision is at a standard deviation of ± 0.02 mgl-1 PO43-.
Total phosphorus (TP)
TP was determined by PhosVer 3 with acid persulphate digestion method (Hach method
8190 and Standard Methods 4500 P-E). Phosphates present in organic and condensed
inorganic forms (meta-, pyro- or other polyphosphates) were converted to reactive
orthophosphate before analysis. Pretreatment of the sample with acid and heat provided
31
the conditions for hydrolysis of the condensed inorganic forms. Organic phosphates were
converted to orthophosphates by heating with acid and persulphate. Orthophosphate
reacts with molybdate in an acid medium to produce a mixed phosphate / molybdate
complex. Ascorbic acid then reduces the complex, giving an intense molybdenum blue
colour. Absorbance was measured at 880 nm. The estimated detection limit for the test is
0.04 mgl-1 PO43- and the precision level is ± 0.09 mgl-1 PO43-.
A Kruskall Wallis ANOVA test (p < 0.05) is a non-parametric test was carried out to
test the differences in physicochemical characteristics between sampling stations (H0: no
difference between five sampling points). The analysis was done for the whole study period,
February – October 2011 using SysStat ver. 12.
Nutrient loading
Nitrogen and phosphorus loadings from the catchment were estimated using the formulae
(Jørgensen 1994);
Where L = nutrient loading (g m2),
Q = flow rate in (m3 s-1),
C = nutrient concentration (mg l-1),
A = surface area of the Lake (m2).
One-layer PAMOLARE model
A One-layer model of PAMOLARE 3, a UNEP-DTIE-IETC and ILEC developed software (2001),
was used for analysis. The 1-layer model consists of a combination of two kinds of models: a
causal dynamic model which integrates the pools of nitrogen and phosphorus in water and
sediment in time as functions of the mass flows and a set of associated empirical models
which are simple regressions made from data of simple physical and chemical characteristics
of a number of lakes. The dynamic model is a modification of the Vollenweider model. Lake
morphology features (depth, water residence and sedimentation rate) and nutrient
concentrations (phosphorus and nitrogen) were measured in field with other features
required being calculated.
32
The parameters that are most related to the eutrophication problem were selected
for the PAMOLARE model and these include nitrogen and phosphorus in water (mg l-1),
phosphorus and nitrogen in sediments (g m2), chl-a (mg l-1) and secchi depth (m). The model
is expected to project the period required by the reservoir improvement in water quality
and also the expected range of the trophic status of Malilangwe reservoir. Given a water
management goal and an array of feasible control techniques, the probability that
rehabilitation efforts will be successful can be determined.
RESULTS
Stratification
Seasonal variation in dissolved oxygen and temperature
Thermal stratification was established during the hot-wet, hot-dry and part of the cool-dry
season (June – August) (Figure 2c). During the hot-wet season (February), the mean water
temperature at the water surface was 31.2oC but in cool-dry season (July), mean water
temperature was 20.1 oC with bottom mean water temperatures of 26.9 oC and 18.6 oC for
February and July respectively. Oxygen stratification pattern was almost similar to that of
thermal stratification. Oxygen concentrations dropped to >4 mgL-1 at 5 m depth during the
February – March and August – October period (Figure 2b). As the air temperature gets
cooler and the solar radiation input decreases in the cool-dry season, the surface water
begins to cool which results in surface water and thermocline cooling down to the
temperature of the hypolimnion. The reservoir at this point is no-longer stratified. In this
state the reservoir can easily be mixed, even by a light wind hence this resulted in complete
mixing or turnover during the beginning of the cool-dry season. This gave the bottom water
an opportunity to aerate with the atmospheric air. As the surface water heated up again
towards the end of the cool-dry season, the reservoir reached a state of thermal
homogeneity and stratification set in with the reservoir returning to the summer
stratification state (Figure 2c). The changes which occurred were related to air temperature
and wind speed. Air temperature increased from 25.2oC in February to 27.3oC in March
before decreasing to a low of 16.8 oC in July. Air temperature then increased from July to
October (26.5 oC). Wind speed followed a similar trend as temperature recording a value of
33
1.1 kmhr-1 in February and decreased to a low of 0.5 kmhr-1 in May and June. Wind speed
then increased to a high value of 2.3 kmhr-1 (Figure 2a).
a
b
c
Figure 2. Seasonal variation in (a) water temperature (oC) and wind speed (kmhr-1) (b)
dissolved oxygen (mgL-1) (c) temperature (oC) in the Malilangwe reservoir
(February – October 2011).
34
Diurnal stratification in temperature and dissolved oxygen
Hot-wet season
The first 24-hour sampling was carried out on the 24th of February 2011 (hot-wet season)
when the water level was high and there was inflow of water into the reservoir. The
reservoir was thermally stratified during the day (10h00 – 18h00) and stratification broke
down at night (20h00 – 08h00) (Figure 3c). Thermal stratification was characterised by very
small temperature gradients. Stratification followed the air temperature trend, where air
temperature decreased from 16h00 (30.8oC) to a low of 20 oC at 04h00 before increasing to
a high of 32.8 oC at 16h00 the next day (Figure 3a). Dissolved oxygen stratification pattern
was more pronounced and the concentration of oxygen fell to <2 mgl-1 (depth = 8 m) from
about 9 mgl-1 (depth = 0 m). Oxygen concentration in the whole water column fell after the
breakdown of stratification (22h00 – 08h00) for short period (Figure 3b). Below a 5m depth,
the reservoir was anoxic (<4 mgl-1).
Cool-dry season
The next 24-hour sampling was carried out on 15 June 2011 (cool-dry season). The reservoir
water level was low as a result of evaporation and drawdown. There was weak thermal
stratification in the reservoir during the day (10h00 – 16h00). Surface water temperatures
decreased from a peak of 28oC during the day (10h00 – 16h00) to a low of 19 oC during the
night (Figure 4b). Lower air temperatures were observed during the cool-dry season (10 –
24oC) compared to February. Low air temperatures of up to 10oC were recorded during the
early morning hours (04h00 – 06h00) (Figure 4a). Stratification broke down after 16h00 to
10h00. There was no oxygen stratification in the reservoir and oxygen concentrations
ranged between 8 and 9 mgl-1 meaning that the water was oxygen saturated (Figure 4b).
Hot-dry season
The last 24-hour sampling was carried on 27 October 2011 (hot-dry season) when the water
was now very low and there was no inflow into the reservoir. The reservoir was thermally
stratified during the day (11h00 – 17h00) with stratification breaking down during the night
(18h00 - 10h00). The water was warmer during the day with surface water temperatures in
the range of 34 – 35oC and the water was cooler during the night with surface water
35
temperatures ranging from 25 – 26oC (Figure 5c). This pattern was related to air
temperatures which reached 30.4oC around midday with lower air temperatures being
observed during the morning (22 – 24oC) between 02h00 and 06h00 (Figure 5a). There was a
weak oxygen stratification pattern during the same period and very low oxygen
concentration (<3 – 6 mgl-1) were recorded during the hot-dry season. Oxygen
concentration levels were below 4 mgl-1 between 16h00 and 18h00 whilst at 5m depth, the
oxygen concentration was <4 mgl-1 for the rest of the study time (Figure 5b).
a
b
c
Figure 3. Diurnal variation in (a) air temperature (oC) (b) dissolved oxygen (mgL-1) (c) water
temeprature (oC) in the Malilangwe reservoir (24 February 2011).
36
a
b
c
Figure 4. Diurnal variation in (a) air temeprature (oC) (b) dissolved oxygen (mgL-1) (c) water
temeprature (oC) in the Malilangwe reservoir (15 June 2011).
37
a
b
c
Figure 5. Diurnal variation in (a) air temeprature (oC) (b) dissolved oxygen (mgL-1) (c) water
temeprature (oC) in the Malilangwe reservoir (27 October 2011).
Water chemistry
Table 1 summarizes the mean values of environmental variables in the Malilangwe reservoir
for study period. Water level decreased at an average of 18.63 cm a month for all sites with
the greatest decreased being recorded for all study sites in March (25 cm) and least
38
decrease in June (9 cm). From February to October a total of 149 cm of water had lost due
to drawdown and evaporation.
Table 1. Physicochemical variables (mean ± sd) measured at 5 sampling sites in Malilangwe
Reservoir, February – October 2011. (Significant differences between the sampling
sites at significance level at p < 0.05 denoted by *).
Variable
-1
Reactive Phosphorus (mg l )
-1
Ammonia (mg l )
-1
Total phosphorus (mg l )
-1
Nitrogen (mg l )
-1
Nitrate (mg l )
pH
-1
Total dissolved solutes (mg l )
-1
Conductivity (μS cm )
-1
Chemical oxygen demand (mg l )
Secchi disk depth (m)
-1
Dissolved oxygen (mg l )
o
Temperature ( C)
-1
Alkalinity (mg l )
Site 1
0.4 ± 0.4
0.1 ± 0.2
0.9 ± 0.9
0.9 ± 0.8
0.07 ± 0.2
7.9 ± 0.6
271.6 ± 37.8
347.5 ± 60.8
33.6 ± 27.2
1.4 ± 0.4
6.1 ± 1.9
24.5 ± 3.3
16.4 ± 1.4
Site 2
0.3 ± 0.3
0.1 ± 0.1
0.7 ± 0.7
0.7 ± 0.3
0.02 ± 0.02
8.1 ± 0.5
273.5 ± 38.5
350.2 ± 63.5
36.5 ± 29.1
1.3 ± 0.3
6.6 ± 1.1
24.87 ± 3.6
16.4 ± 1.5
Site 3
0.3 ± 0.3
0.1 ± 0.1
0.8 ± 0.7
0.6 ± 0.4
0.03 ± 0.03
8.1 ± 0.5
273.2 ± 36.7
349.6 ± 68.1
36.7 ± 27.5
1.1 ± 0.2
7.2 ± 1.2
25.2 ± 3.8
16.9 ± 2.0
Site 4
0.3 ± 0.3
0.1 ± 0.1
1.1 ± 1.6
0.8 ± 0.8
00.2 ± 0.02
8.0 ± 0.5
274.2 ± 37.5
351.8 ± 66.8
36.8 ± 26.2
1.1 ± 0.2
6.6 ± 1.3
25.3 ± 3.7
16.2 ± 1.5
Site 5
0.4 ± 0.4
0.2 ± 0.2
1.1 ± 1.6
1.7 ± 1.3
0.02 ± 0.02
8.2 ± 0.5
275.7 ± 40.6
352.5 ± 75.2
49.4 ± 30.0
0.7 ± 0.4
6.7 ± 1.4
25.6 ± 4.5
17.6 ± 1.1
p value
0.91
0.92
0.88
0.65
0.98
0.92
0.99
0.85
0.50
0.01*
0.69
0.98
0.43
The pH displayed a fluctuating trend during the 9 months of sampling. At the start of
the sampling campaign in February (hot-wet season), pH measured at all the 5 sites were in
the range of 7.32 - 8.18. There was not much difference in March and April but there was a
peak increase in July at all the study sites (pH 8.84 - 9.04). The values of pH dropped again in
August as the cold season ended measuring in the range 7.72-7.82 before increasing in
September to around 8.00 – 8.52. The pH dropped once again to record the lowest values
for the entire study at 4 of the sites and pH was in the range 7.10 - 7.56 (Figure 6).
Ionic conductivity also showed a fluctuating trend throughout the sampling period.
In February, conductivity ranged from 308.91 μScm-1 (site 1) to 346.00 μScm-1 (site 5). For
some reason, there was a sudden drop in March to range between 180.33 μScm-1 (site 5) to
208.64 μScm-1 (site 1). This was followed by a significant increase in April to within the range
of around 352 – 367 μScm-1. From that time, conductivity levels continued to rise reaching
the higest concentrations in October when all sites recorded above 400 μScm-1 (S1 = 427.63
μScm-1; S2 = 427.67 μScm-1; S3 = 433.00 μScm-1; S4 = 437.33 and S5 = 441.00 μScm-1) (Figure
6c). Total dissolved solutes (TDS) concentrations initally followed exactly the same trend as
conductivity as these two variables are correlated up to April when the highest
39
concentrations for the study period were recorded (TDS = 342.75 - 352.91 mg l-1).
Thereafter, TDS concentrations decreased in May to around 275 – 280 mg l-1 for all study
sites before rising slightly from June to July to around 290 – 295 mg l-1. Concentrations
dropped again in August to 230 -233 mg l-1 in August before increasing to 251 – 254 mg l-1
in October. Site 1 recorded of lowest values of total dissolved solutes whilst site 5 recorded
the highest concentrations during the study (Figure 6b).
Chemical oxygen demand (COD) concentrations were constant during first two
months (February and March) and increased slightly in Aprilbefore decreasing to lowest
concentrations in July (S2 = 18.00 mg l-1, S3 = 13.40 mg l-1, S4 = 31.75 mg l-1 and S5 = 9.50
mg l-1) while S1 had low levels in June (19.20 mg l-1). COD concentrations then increased for
all the study sites in August (S1 = 79.22 mg l-1, S2 = 110.00 mg l-1, S3 = 104.00 mg l-1, S4 =
97.74 mg l-1 and 100.87 mg l-1) before decreasing in October. Site 1 recorded lowest
concentrations while S5 recorded highest concentrations of COD for the entire study.
Secchi disk transparency (SD) was lowest in site 5 (below 1m) and highest in site1 for
the study period. Secchi disk transparency increased from February to a peak in May (S1 =
2.00 m, S2 = 1.80 m and S3 = 1.50 m) before decreasing in October (Figure 6e). Secchi disk
readings were relatively constant for S4. Highest SD water transparency levels were
recorded in August (Figure 6e). Total suspended solids (TSS) increased from February to
August decreasing to a low in October for site 1 – 4 (Figure 6g). Tubridity levels were high
for site 2 (114.67 mg L-1) and the lowest was recorded for site 3 (4.6 mg L-1). Turbidity levels
decreased in August before increasing in September and finaling decreasing in October
(Figure 6h).
40
a
b
c
d
e
f
a
b
-1
Figure 6. Changes in (a) pH (b) TDS (mg l ) (c) conductivity (μS cm-1) (d) chemical oxygen
demand (mg l-1) (e) secchi disk (m) (f) alkalinity (mg l-1) (g) total suspended solids
(mg l-1) (h) turbidity (mg l-1) in Malilangwe reservoir from February – October 2011.
41
Nutrients
Site 1 recorded the highest values of reactive phosphorus (RP) concentrations whilst site 3
recorded the lowest concentrations. RP concentrations increased from February to March
before dropping to lowest concentrations in April. RP concentrations increased in June
before decreasing in July. RP concentrations increased from July to October, to record the
highest RP concentrations (S2 = 0.90 mg l-1, S3 = 0.77 mg l-1, S4 = 0.83 mg l-1 and S5 = 0.76
mg l-1) while S1 recorded a highest RP concentrations of 1.28 mg l-1 in September (Figure
7a). Total phosphorus (TP) concentrations were constant between February and March (S1 –
S4), decreasing in April then increasing in June before decreasing in July (S1 = 0.19 mg l-1, S2
= 0.18 mg l-1, S3 = 0.12 mg l-1, S4 = 0.09 mg l-1 and S5 = 0.10 mg l-1). Ammonia concentrations
increased from July to October for S2 (2.07 mg l-1), S3 (1.77 mg l-1) and S5 (2.13 mg l-1) while
S1 and S4 increased to a high in September (S1 = 2.94 mg l-1 and S4 = 1.67 mg l-1) before
decreasing in October (Figure 7c).
The highest ammonia concentrations for site 1 were recorded in February (0.46 mg l1
) while the rest of the sites recorded lowest concentrations (S2 = -0.43 mg l-1, S3 = -0.41 mg
l-1, S4 = -0.41 mg l-1 and S5 = -0.48 mg l-1). Ammonia concentrations for site 1 – 4 increased
from February to a high in March. Site 1 recorded the lowest ammonia concentrations of 0
mg l-1 in April. Ammonia concentrations ranged between 0 – 0.20 mg l-1 form April to
October for S1 – S3 while ammonia concentrations increased for S5 in July (0.29 mg l-1).
Ammonia concentrations for site 4 increased in April (0.06 mg l-1) to 0.40 mg l-1 in May
before decreasing in June (0.05 mg l-1) (Figure 7b). Nitrate concentrations decreased from
42
a
b
c
d
e
f
Figure 7. Changes in (a) reactive phosphorus (mg l-1) (b) ammonia (mg l-1) (c) total
phosphorus (mg l-1) (d) nitrogen (mg l-1) (e) nitrogen (mg l-1) (f) N: P ratio in
Malilangwe
reservoir
from
February
–
October
2011.
43
February to March and then increased in April (S1 = 0.07 mg l-1, S2 = 0.06 mg l-1, S3 = 0.08
mg l-1, S4 = 0.07 mg l-1 and S5 = 0.06 mg l-1). Nitrate concentrations decreased in July (all
sites = 0.00 mg l-1) and then increased in October (S1 = 0.03 mg l-1, S2 = 0.04 mg l-1, S3 = 0.02
mg l-1 and S5 = 0.03 mg l-1) (Figure 7e).
Total nitrogen concentrations increased from February to March before becoming
nearly constant. Site 5 recorded decreases in June (0.00 mg l-1) and August (0.33 mg l-1) and
increases in July (2.56 mg l-1) and September (2.96 mg l-1). Site 4, S1 and S2 recorded high N
concentrations in May (2.58 mg l-1), June (1.22 mg l-1) and September (1.21 mg l-1)
respectively (Figure 7d). A slight variation in N: P ratio was observed for all the study sites
and N: P ratios were below 1 for all sites except for S5 (1.37) in September and October. Site
5 recorded a high of 56.96, S2 = 6.37 and S1 = 2.18 while low ratios of 0 (S4 and S3). During
the cool-dry season, S4 recorded N: P ratio of 2.96 (May), S5 = 24.73 (July), S4 = 6.84 (July)
and S3 = 5.52 (July) (Figure 7f).
One-Layer model for eutrophication management
If the current land use activities are changed, nitrogen levels in water will continue increase
to about 11.9 mg l-1 in 5 years and then to 15.7 mg l-1 in 45 years. Nitrogen in sediment will
increase linearly with time to about 233.6 g m2 in the next 45 years. Nitrogen sediment
levels are expected to increase to about 18.3 mg l-1 in 5 years (Figure 8). Phosphorus levels
in water will increase to about 2.3 mg l-1 in 5 years and then 3.2 mg l-1 in 45 years.
Phosphorus in sediment will increase linearly with time to about 5.4 g m2 in the next 5 years
and it’s expected to increase to about 51.2 mg l-1 in 45 years (Figure 9). Chlorophyll-a will
increase to 3.9 mg l-1 within the 5 years and then to about 5.7 mg l-1 in 45 years. Secchi
depth will decrease from about 0.28 m to 0.25 m in 5 years. The secchi depth is expected to
decrease to 0.24 m in 25 years and remain constant at that rate (Figure 10).
44
a
b
c
Figure 8. PAMOLARE projections for (a) nitrogen (b) phosphorus (c) secchi depth and
chlorophyll-a levels in Malilangwe reservoir under the current land use.
45
DISCUSSION
The study area falls within the sub-tropical region where rainfall is defined by seasonality.
This affects water levels in small water bodies resulting in large decreases during the long
dry season (April – October) mainly through evaporation and drawdown. Mixing in the
shallow and stratified reservoir varied daily and seasonally depending on solar irradiance
and wind regimes. Nhiwatiwa & Marshall (2006) and Graham et al. (2008) showed that daily
discontinuities of solar radiation and wind regimes are the main causes of stratification
changes. The pronounced daily variations of the atmospheric heat content, evaluated
through the range of air temperature values, promote nocturnal heat loss of the water, so
that the instantaneous heat content of the water does not reflect the reality of heat
exchanges (Arcifa et al. 1990). Temperatures were naturally higher in the hot-dry season
during daytime than in the cool-dry season. Weak diurnal thermal and oxygen stratification
were observed during the cool-dry season mainly as a result of low temperatures.
Deoxygenation of bottom waters was observed during the hot-wet and hot-dry
season while the whole water column was well oxygenated during the cool-dry season. The
spatial variability of the oxygen depletion (<2 mgl-1) that the reservoir exhibited could be
partly due to respiration as a result of decomposing organic matter and the nature of the
soils (Chapman et al. 1998). Seasonal importation of allochthonous organic material during
the rainy season is a characteristic feature of most tropical reservoirs, and Malilangwe
reservoir is not an exception. The absence of dissolved oxygen depletion during the cool-dry
season is mainly due to complete mixing of the water column. In addition, the processing of
organic matter could occur rapidly and bacterial activity declines during the cool-dry season
or it could be due low temperatures lowering bacterial activity during the cool-dry period.
Temperature is a major determinant of the rates of biological and biochemical processes
such as decomposition (Nhiwatiwa and Marshall 2006).
Dissolved oxygen depletion during the hot-wet and –dry season is a result of demand
exceeding supply due to the increase in aquatic animals, plants and decaying organic matter
which consume DO. Large fish populations in the reservoir experience a faster metabolic
rate as water temperature increase due to change of seasons (cool-dry to hot-dry season)
which increases their oxygen requirements. As a result, more oxygen is needed by the fish
during the hot-wet and –dry season. Another factor for low DO levels during the hot-dry
46
season could be due to decomposition by bacteria, a process that further reduces DO in the
water column. The development of hypolimnetic anoxia reduces the biologically available
habitat and severely impacts on benthic organisms. Fish usually avoid water layers
containing <2-3 mgl-1 oxygen concentration (Abd El-Monem 2008) and the same is true for
other aquatic organisms. About 40% of the Malilangwe reservoir volume (oxygen deficient
depth of up to 4 m) creating condition of oxygen stress during the hot-wet and –dry season
and greatly reducing habitat.
Thermal and oxygen stratification has implications on nutrient exchange between
sediments and water. Cowan and Boynton (1996) observed that sediment oxygen
consumption rates increase with increasing temperature until bottom DO concentrations
fell below <3 mgl-1 thereby apparently limiting sediment oxygen consumption rates. This
partly explains the depletion of oxygen that occurred in Malilangwe reservoir. With regards
to nutrient cycling, high DO in the hypolimnion inhibits sediment release of ammonia by
enhancing nitrification of ammonia to nitrate and thus nitrogen assimilation into bacterial
biomass. However, fluxes of ammonia are elevated at high temperatures and when coupled
with low bottom DO concentrations (<5 mgI-1), very large releases occur (Beutel et al. 2008).
Phosphate fluxes are small except in areas of hypoxic and anoxic bottom waters. It’s likely
that nutrient exchange is rapid and frequent in small reservoirs even though they are
characterized by vertical gradients that are caused by thermal and oxygen stratification
(Nhiwatiwa and Marshall 2004). In Malilangwe reservoir, there were short-term fluctuations
of some isopleths of temperature and dissolved oxygen indicating there is dynamism among
the different layers even during stratification. This likely result in partial mixing in the water
column and this may allow nutrient exchanges between the epilimnion and the
hypolimnion.
Seasonal changes in water quality were also investigated. Conductivity was
characterised by fluctuations between the cool-dry season, hot-dry and -wet season. The
lower concentrations during the wet season occur because rainfall occurs in a few
contiguous months of the year and this results in a high dilution factor as river inflows come
in. Later in the year after inflows have ceased, ionic concentrations increased as water levels
dropped. This concentration effect has been observed and reported in other studies
elsewhere (Nhiwatiwa and Marshall 2007, Moss and Moss 1969, Mclachlan et al. 1972,
47
Osborne et al. 1987). The temporal and vertical patterns of pH in the reservoir were
mediated through the processes of photosynthetic consumption and respiration. The high
pH observed during the cool-dry season (June – July) could be attributed to photosynthetic
uptake of CO2 by prolific algal blooms observed during the same period while
decomposition and respiration tended to decrease pH during the hot-wet and hot-dry
seasons.
Secchi disk transparency is an important feature of water quality and has ecological
implications. Secchi disk transparency ranged from 0.2 – 1.8 m in Malilangwe reservoir and
was comparable to the characteristic modal range of 0.1 - 1.6 m recorded in two small
reservoirs in the Manyame catchment (Nhiwatiwa and Marshall 2007) and Oyun reservoir,
Nigeria (Mustapha 2008). Secchi disc transparency was low in the rainy season (February –
March) and in particular at Site 5, throughout the study. The rainfall season is naturally
characterised by high runoff resulting in sediment laden inflows into the reservoir. Site 5
had riverine characteristics and was at the point of where the major inflows came in and
thus the observed low water transparency. High water transparency observed in the dry
season water transparency improved as suspended particles settled at the bottom of the
reservoir. The range of water transparency (0.2 - 1.8m) reflects that depth of light
penetration is good for aquatic organisms (plankton and fish) to thrive in the pelagic regions
of Malilangwe reservoir (Mustapha 2008).
The river inflows were obviously linked to higher phosphorus concentrations during
the hot-wet season. These higher concentrations are most likely linked to the production of
algal blooms during the cool-dry season which brought about high productivity of the
reservoir. Additional nutrients were also released during turnover contributing to the overall
increased productivity. The overall decline in phosphorus concentrations are obviously
linked to uptake algae and macrophytes and during the hot-dry season, retention in the
hypolimnion. The fall in water levels in the reservoir corresponded with an increase in
phosphorus concentrations but this relationship is confounded by the effects of turnover at
the same time. Nitrogen concentrations were generally in the low category. This finding
supports the suggestion that nitrogen does not accumulate in tropical lakes and reservoirs
due to the occurrence of anoxic hypolimnia (Bootsma and Hecky 2003). Anoxia and warm
temperatures promote rapid denitrification rates and enhance phosphorus mobilization in
48
tropical lakes, and this explains the greater prevalence of nitrogen limitation in the tropics
(Bootsma and Hecky 2003).
Nitrogen and phosphorus (N:P) ratios observed in the reservoir were relatively
unchanged during the study period. According to Smith (1979) nitrogen is limiting when the
N:P ratio is less than 10:1 and phosphorus is limiting when the ratio N: P is greater than
13:1. Thus, for the Malilangwe reservoir, nitrogen was found to be the limiting factor in the
reservoir as shown by the relatively high N:P ratio of -0.6 to 10.9 for all study sites. The
nutrient status of the reservoir was low and within the recommended range for freshwater
quality by APHA (1998) and WHO (2006). The trophic status of the reservoir is likely to
change in the short to medium term to eutrophic as the reservoir is just a sink for nutrients.
Nutrient loading from the catchment is currently low and this is the reason why the
reservoir has not yet become eutrophic. The PAMOLARE trend indicates that under the
current loadings, both N and P concentrations in water and sediment will continue to
increase with N and P sediments increasing linearly. Such an increase will result in an
increase in phytoplankton biomass (chlorophyll-a concentrations) producing phytoplankton
populations dominated mostly by the blue-green algae (Cyanophyta). Water transparency
will also decline and generally eutrophic reservoirs have low values of Secchi depth values
due to high turbidity related to high concentrations of algae and detritus. It is recommended
that the Malilangwe management takes a special interest in the activities of the
communities situated in the Nyamasikana River headwaters. Overall, the physicochemical
properties of the reservoir reflect still good water quality suitable for domestic use.
49
THE ECOLOGY OF THE PHYTOPLANKTON AND ZOOPLANKTON COMMUNITIES OF A SMALL
TROPICAL RESERVOIR (MALILANGWE, ZIMBABWE)
50
INTRODUCTION
Approaches that look at ecosystem integrity can be used to assess water quality based on
the response of specific biological species to water quality (Arnott et al. 1998). Among
aquatic biota, plankton are generally highly sensitive and their dynamics can be seriously
affected by environmental perturbation (Park and Marshall 2000, Munamati et al. 2007).
Due to their short life-cycles, plankton inhabiting shallow freshwater lakes and reservoirs
and respond quickly to environmental changes. The species composition and frequency of
seasonal abundance fluctuate according to the changing status of the water mass in which
they are found (Chattopadhyay and Barik 2009, Okogwu 2010). Plankton have fast growth
rates thus they therefore can provide meaningful and quantifiable indicators of ecological
change in short timescales (Arnott et al. 1998, Munamati et al. 2007).
Plankton are identified as important components of aquatic ecosystems, with
zooplankton helping in regulating algal and microbial productivity through grazing and in
the transfer of primary productivity to fish and other consumers (Arnott et al. 1998, Sibanda
2005, Okogwu 2010). By grazing on phytoplankton and bacteria, they help in improving
water quality hence zooplankton are considered as indicators of water quality (Munamati et
al. 2007, Okogwu 2010). However, the responses of zooplankton to water quality variations
are ecosystem and species dependent and vary within and between lakes (Arnott et al.
1998, Okogwu 2010). Phytoplankton constitutes an important compound of the diet of
zooplankton organisms, influencing their reproduction and survivorship (Basima 2005,
Perbiche-Neves et al. 2007).
Seasonal succession in zooplankton assemblages in lakes and reservoirs has been
attributed to both biotic and abiotic mechanisms (Rajashekhar et al. 2009). Several
limnological studies in the tropics have shown that the zooplankton of floodplain lakes are
highly responsive to changes in environmental variables which include dissolved oxygen, pH,
flood pulse, environmental morphometry, connectivity, lake width and depth (Masundire
1994, Okogwu 2010). Seasonal flooding of these lakes tends to bring about environmental
changes which ultimately influence the biotic interactions between populations of
floodplains (Okogwu 2010).
River-fed man-made reservoirs normally exhibit a spatial gradient in various
attributes such as sediment and nutrient concentrations (Dejen et al. 2004). Inflowing rivers
51
often carry loads of suspended solids into lakes and reservoirs with horizontal gradients in
turbidity affecting the occurrence and distribution of plankton organisms. This, in turn,
causes a spatial gradient in biological productivity and water quality along the axis of the
reservoirs (Masundire 1997). Food availability for zooplankton tends to decline with
turbidity due to light limitation on the primary production. In addition to reduced
production of algal food resources one can expect interference of silt particles with the filter
feeding processes in zooplankters (Masundire 1997). Suspended sediments reduce light
intensity in the photic zone and reactive distance of visual planktivores, which may lead to
declining foraging rates (Dejen et al. 2004, Olomukoro and Oronsaye 2009).
In Zimbabwe, most investigations into plankton ecology have concentrated on the
plankton of larger dams with a fairly stable hydrology, such as Lake Chivero (Munro 1966,
Elenbaas and Grundel 1994, Magadza 1994, Sibanda 2005, Ndebele-Murisa 2010, Moyo
2011, Ndebele-Murisa 2011) and Lake Kariba (Begg 1976, Masundire 1992, 1994, 1997,
Cronberg 1997, Marshall 1997, Harding and Rayner 2001). Relatively little is known about
plankton in the country’s smaller reservoirs, with some notable studies being carried by
Thornton and Cotterill (1978) who listed phytoplankton and zooplankton species in five
small dams in the eastern highlands, Green (1990) who described the zooplankton
associations in 18 small impoundments, including those in the eastern highlands, Masundire
(1992) ecology of zooplankton in Mazvikadei Dam, Elenbaas and Grundel (1994)
zooplankton composition and abundance in Cleveland Dam, Sibanda (2005) the composition
of the phytoplankton in the five impoundments (Harava Dam, Seke Dam, Lake Chivero, Lake
Manyame and Bhiri Dam), Basima et al. (2006) assessment of Plankton diversity in four
reservoirs in the Mzingwane catchment, Nhiwatiwa and Marshall (2007) plankton ecology of
Mumwahuku reservoirs, Ndebele (2009) phytoplankton and primary production of
Cleveland Dam and Moyo (2011), ecology of zooplankton in Mazvikadei Dam.
There are few records of the dam’s phytoplankton communities in Zimbabwe:
Thornton and Cotterill (1978) and Green (1990) – eastern highlands, Basima et al. (2006) –
Mzingwane catchment, Nhiwatiwa and Marshall (2007) – Mumwahuku, Mhlanga et al.
(2006) – Lake Chivero, Ndebele-Murisa (2007, 2011) – Cleveland dam and Lake Chivero. This
study, therefore, is a baseline survey to ascertain the plankton community of Malilangwe
reservoir, so as to contribute to the pool of knowledge in plankton ecology in Zimbabwe.
52
Such a study has not previously been carried out for this water system. The limnology of
other dams, particularly the small dams scattered across the country on seasonal rivers, has
not been studied in detail and there are therefore gaps in limnological knowledge of
mechanisms that drive change in small dams (Nhiwatiwa 2004, Mhlanga 2011). The aim of
this study is to determine plankton community composition and abundance and also
ascertain the seasonal dynamics of the plankton communities of Malilangwe reservoir. The
study will also relate the plankton population dynamics to physicochemical parameters and
estimate the different chlorophyll-a levels for the lake.
Study area
volume of 12496259.92 m3 at full capacity. Flanked by rocky hills on most of its sides, the
marginal plants which include Azolla filiculoides (Lam), Ludwigia stolonifera (Guill and Perr)
fish communities include predators, omnivores, detritivores, micro amd macrophages
METHODS
Plankton sampling
Sampling was done once a month during the three seasons present in Zimbabwe: (1)
November - April were considered the hot wet season; (2) May – August the cool dry
season; and (3) September – October the hot dry season from the five study sites along the
lake from February to October 2011. Plankton samples were collected using vertical hauls
with a zoo - and phytoplankton net of 40 cm diameter, 62 μm and 20 μm mesh size from the
53
bottom to the surface through the water column at an approximate speed of 0.6 ms-1. The
area).
samples were collected using a standardized method presented in Edmondson and Winberg
(1971). The concentrated samples were collected in small 250 ml bottles that were labelled.
A preservation solution of 70 % alcohol was added to the sample bottles with zooplankton
and Lugol’s iodine solution was added to the bottles containing phytoplankton for fixing
purposes. The volume of sampled water that passed through the net was then estimated by:
V = ∏r2d
Where V = volume of water filtered by the plankton net, r = radius of the mouth of the net
and d = distance the net pulled through (Nhiwatiwa 2004).
54
The samples were taken to the fish laboratory, Biological Sciences Department
(University of Zimbabwe) for identification and scoring under an inverted microscope
OLYMPUS CKX41. The density of zoo- and phytoplankton were determined by counting the
numbers present in five 10 ml sub-samples from each site and the mean value was
recorded. The identification of taxa was done using a dichotomic identification keys
presented by Elenbaas (1994), Fernando (2002) and Cander-Lund and Lund (1995).
Unfortunately it was not possible to identify copepods and calanoids to species level. The
Shannon-Weiner index of diversity (H’) (Krebs 1989) was calculated for phytoplankton and
zooplankton using PAST version 2.0 (Hammer et al. 2001).
Chlorophyll (chl-a)
Chlorophyll was extracted with 90 % acetone using the spectroscopic method (Aminot and
Rey 2000). Five hundred millilitres of the sample was filtered using Whatman GF 47 mm
filters. The filters were then cut to pieces into a 10 ml centrifuge tube and 7 ml of 90 %
acetone was added. The samples were allowed to extract for 3 hours in a refrigerator and
were then centrifuged at 3000 rpm for 10 minutes. The supernatant solution was then
transferred into 2 cm cuvettes. The colour absorbance was then read at 630, 647, 664 and
750 nm. The concentration of chl-a (mgm-3) was calculated according to Aminot and Rey
(2000) equation:
Chl-a = [11.85 (E664 - E750) - 1.54 (E647 - E750) - 0.08 (E630 - E750)] x Ve/L x Vf
Where, L = Cuvette light-path in centimetres, Ve = Extraction volume in millilitres, Vf =
Filtered volume in litres.
Environmental parameter measurements
solutes, temperature and dissolved oxygen (DO) done using a pH, Conductivity and DO
determined using standards methods from EPA, Hach and Standard Methods. Water level
was measured at the dam using a tape measure by measuring from the top of the dam to
the water level point. Macrophyte cover was measured as percentage cover in the littoral
55
zones of the reservoir by observing cover while walking along the shore and driving a boat
were the shore was inaccessible.
Redundancy Analysis (RDA)
Before analysis, all plankton species data were square-root transformed to reduce skewness
in the data. All species included contributed a relative abundance of at least 1%. Thirty-four
phytoplankton taxa and thirty zooplankton taxa were considered for analysis. RDA
Multivariate data analyses were performed on the different plankton datasets to examine
the links between plankton species composition and environmental parameters
(temperature, nitrogen, phosphorus (reactive and total), chemical oxygen demand, secchi
disk transparency, macrophyte cover, water level, dissolved oxygen, ammonia, conductivity
and nitrate). To determine whether to use linear or unimodal methods for the analysis,
Detrended canonical Correspondence Analysis (DCCA) was used. The lengths of gradient
were examined and since the longest gradient was shorter than 3.0, a linear constrained
method was a better choice. Redundancy Analysis (RDA) a constrained linear ordination
method and also called reduced rank regression based on significant (p < 0.05) forward
selected environmental variables using 499 Monte Carlo Permutations was used for
analysis. The software Canoco (ver. 4.5) was used for the analysis. RDA was done to
determine how the environmental parameters possibly influenced plankton species
composition.
Hierarchal Cluster analysis (HCA)
Macroinvertebrate species grouping according to differences in site and season were
assessed. Hierarchal Cluster analysis was performed using PC-ORD for windows 5 (2006).
Hierarchal Cluster Analysis (HCA) is a multivariate method, a technique that defines groups
based on their similarities (McCune and Mefford 2006).
RESULTS
Environmental variables
for the study period. Dissolved oxygen (DO) values were low during February – March,
56
increased between May to August before dropping in September – October. Well
oxygenated water was found throughout the cool-dry season (7 – 9 mg l-1). Low DO levels of
up 2 mg l-1 were recorded during the February – March and September – October for site 1
and 2. The lowest water temperatures occurred from May to September after which there
was rapid increase in temperatures. Temperature decreased through the three seasons
(hot-wet – cool-dry). Temperatures averaged 26.65oC in February before decreasing to a low
of 19.27oC in June. Temperatures then increased from June to September (27.6oC). Highest
temperatures were recorded in October (28.40 oC) for site 5 and lowest in June site 5 (18.80
o
C). Not much differences in temperature between surface and bottom water existed during
the cool-dry season when the reservoir was stratified. A breakdown in stratification
occurred in August. Secchi disk depth readings at site 1 - 4 ranged between 0.9 and 1.7 m
with site 5 ranging from 0.2 – 0.6 m and in August, a secchi depth of 1.15 m (Table 1) was
recorded for site 5.
Ammonia and Nitrogen decreased during the cool-dry season especially during May
– July before increasing again for all study sites. Low levels of Total Nitrogen (TN = 0.68 mg l1
) were recorded in June. Nitrate values were low during the hot-wet season with low
values being observed for all sites. Low values were observed in July for all sites (0 mg l-1)
but increased from August (0.01 mg l-1) to October (0.03 mg l-1). Nitrate was high for
February site1 (0.5 mg l-1), March site 1 (0.07 mg l-1) and June site 4 – 5 (0.04 mg l-1).
Ammonia was high in February (0.17 mg l-1), March site 5 (0.40 mg l-1), August site 4 (0.11
mg l-1) and October (0.26 mg l-1). Low values of ammonia were observed during the hot-wet
57
Table 1. Environmental variables measured in Malilangwe reservoir in February - October 2011 (Significant differences between the months
are denoted by * (K-Wallis Anova p < 0.05).
Feb
Mean SD
Dissolved Oxygen
Temperature
Conductivity
pH
Total dissolved solutes
Reactive phosphorus
Nitrogen
Ammonia
Nitrate
Chemical oxygen demand
Total phosphorus
Secchi depth
Alkalinity
Total suspended solids
Turbidity
-1
mg l
6.6
o
C
29.7
-1
μS cm
333.0
7.8
-1
300.6
mg l
-1
mg l
0.3
-1
mg l
0.7
-1
mg l
-0.2
-1
0.1
mg l
-1
mg l
30.1
-1
mg l
0.6
m
1.1
-1
mg l
-1
mg l
-1
mg l
1.2
0.9
14.1
0.3
12.1
0.1
0.8
0.4
0.2
8.9
0.2
0.1
-
Mar
Mean SD
Apr
Mean SD
May
Mean SD
Jun
Mean SD
Jul
Mean SD
Aug
Mean SD
Sep
Mean SD
Oct
Mean SD
p
value
5.0
30.1
191.6
7.9
235
0.3
1.7
0.4
0.0
27.6
0.8
1.0
17.0
-
7.8
26.9
358
7.9
344.9
0.1
0.8
0.1
0.1
56.8
0.01
1.1
18.7
-
7.0
24.4
358.3
7.9
278.4
0.2
1.1
0.2
0.03
26.1
0.2
1.6
18.6
-
7.9
21.6
367
8.6
284.7
0.6
0.7
0.03
0.03
19.5
1.4
1.0
18.6
-
8.5
19.3
376
8.9
292.2
0.1
1.0
0.1
0.00
27
0.1
1.2
18.1
11.7
16.0
5.6
20.9
338.4
7.5
226.7
0.1
0.4
0.1
0.01
86.6
0.3
1.3
17.8
22.5
44.3
5.6
22.5
360.3
7.8
228.1
0.7
0.9
0.002
0.02
35.1
2.5
1.1
19.1
17.2
34.7
5.3
27.6
433.3
7.5
252.6
0.8
1.2
0.1
0.02
25.2
1.9
0.7
19.4
20.5
37.4
0.69
0.98
0.85
0.21
0.99
0.91
0.65
0.92
0.98
0.50
0.88
0.01*
0.43
0.24
0.21
0.8
0.8
11.2
0.2
3.7
0.2
1.0
0.2
0.1
12.4
0.4
0.3
1.2
-
0.3
0.7
6.2
0.3
1.8
0.1
0.6
0.05
0.01
15.3
0.1
0.5
0.8
-
0.3
0.1
3.4
0.1
1.9
0.1
1.0
0.2
0.02
4.0
0.05
0.4
1.5
-
0.3
0.3
1.3
0.2
0.8
0.1
0.5
0.02
0.01
1.2
0.3
0.3
1.4
-
0.5
0.5
2.2
0.1
1.6
0.02
0.9
0.1
0.002
21.4
0.0
0.5
1.3
2.7
11.4
0.4
2.1
22.5
0.4
8.0
0.03
0.1
0.03
0.0
20.8
0.1
0.2
2.0
26.4
48.9
1.0
2.1
34.1
0.7
19.8
0.3
1.2
0.04
0.01
14.8
1.5
0.1
1.5
11.1
27.9
1.1
0.8
5.9
0.3
1.0
0.1
1.1
0.1
0.01
23.9
0.2
0.3
1.6
11.0
14.4
58
season for all study sites. Alkalinity showed slight seasonal changes across the study sites
and it fluctuated between 15 and 22 mg l-1 for all sites and months. Total dissolved solute
(TDS) was high during April – July (270 – 360 mg l-1). There was an increase in conductivity
from March (191.6 μS cm-1) to September (383.15 μS cm-1) (Table 1). Water level decreased
at an average of 18.63 cm a month for all sites with the greatest decreased being recorded
for all study sites in March (25 cm) and least decrease in June (9 cm). From February to
October a total of 149 cm of water had been lost due to evaporation.
Phytoplankton
Species composition and seasonal variation
A total of 98 phytoplankton species; 2 Dinophyta, 4 Euglenophyta, 14 Bacillariophyta, 50
Chlorophyta, 13 Desmids and 15 Cyanophyta were recorded for Malilangwe reservoir
between February and October 2011. The abundance and composition of Chlorophyta was
greatest during the hot-wet season (February – April) with February having highest
composition of 54.24% of the total chlorophyta composition. The average Chlorophyta
abundance for the hot-wet season was 45.69% (Figure 2a, Table 2). The abundance and
composition of Bacillariophyta was also greatest in the hot-wet season at an average of
19.38% with greatest diversity being recorded in March (23.74%). The Dinophyta abundance
and composition increased from hot-wet season (February – 7.86%) to a peak in the hot-dry
season (October – 45.31%). The composition and abundance of the Cyanophyta was
greatest during the cool-dry season (May – August) with an average of 29.61%. The highest
Cyanophyta composition was observed during the hot-wet season month of August
(36.29%). Desmids had the greatest composition and abundance in August (10.66%) and the
Euglenophyta averaged 1.22% with greatest composition being recorded in February
(2.30%) (Figure 2a, Table 2).
Individual numbers per litre for the phytoplankton were high during the cool-dry
season (May – July average 129428 ind. l-1) and lowest during the hot-dry season
(September – October average 37670 ind. l-1). The cool-dry season month of May recorded
the highest number of phytoplankton (182765 ind. l-1) and August the least (17726 ind. l-1).
The hot-wet season (February – April) recorded an average of 74208 ind. l-1 (Figure 2b, Table
2).
59
a
b
c
Figure 2. Temporal changes in (a) percentage composition (b) total abundance (individual
per litre – ind. l-1) of phytoplankton taxa.
Individual species within the phytoplankton groups that contributed significantly in terms of
abundance namely are; Anabeana sp., Anabeana circinalis, Anabeana sporiodes,
Botryococcus braunii, Ceratium hirudinella, Chlorella sp., Diatom sp., Euglena sp.,
Eutetramorous fotti, E. planctonicus, Melosira sp., Merismopedia sp., Microcystis
60
Table 2. Relative abundance (individual per litre – ind. l-1) of phytoplankton of Malilangwe
reservoir, February – March 2011.
Division
Dinophyta
Ceratium hirudinella
Peridinium sp.
Euglenophyta
Euglena sp.
Phacus caudatus
Tetraedon trigonum
Trachelomonas sp.
Bacillariophyta
Asterionella sp.
Cracticula sp.
Cyclotella sp.
Cymbella sp.
Diatom sp.
Fragilaria sp.
Gonium sp.
Melosira sp.
Pinnularia sp.
Pleurotenium sp.
Stephanodiscus
Surirella capronii
Synedra sp.
Tabellaria sp.
Chlorophyta
Actinastrum hantzschii
Amphora sp.
Anaphocassa elecista
Ankistrodesmus spiraliformis
Asterococcus
Botryococcus baunii
Chlorella sp.
Chlorococcus sp.
Coelastrum sp.
Crucigena tetrapedia
Dictyosperarium ehrenbergianum
Dictyosperarium pulchellum
Dictyosperarium tetrachonium
Didymosphaearia sp.
Eudorina elegans
Euplates sp.
Eutetramorous planctonicus
Eutetramorus fotti
Frontonia sp.
Gloeocystis sp.
Gomponema sp.
Haematococcus pluvialias
Heleochloris mucosa
Heleochloris sp.
Kirchneriella sp.
Korschpalmella miniata
Lagerheimia sp.
Lepocinclis sp.
M. radians
Micratinium sp.
Monoraphidium arcuatum
Oocystis sp.
Ophiocytium capitatum
Pediastrum boryanum
Pediastrum duplex
Pediastrum simplex
Pediastrum simplex "biwaense"
Pediastrum simplex var 'Sturmii'
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
3701
408
10246
580
17054
2255
24503
6946
22733
7635
17094
3978
3311
571
9174
1452
17136
2138
2483
411
170
1754
2283
91
333
2764
1061
1463
195
37
3972
1078
1310
2103
3180
112
562
425
21
1763
353
21
843
248
634
477
149
1603
541
499
394
483
4104
-
245
75
724
705
1762
8193
2035
203
202
40
6202
-
423
150
46
4835
834
5135
289
603
14
1781
206
16
69
136
12396
11685
79
104
838
-
3
92
2381
373
2725
992
1106
1044
526
14
171
1639
160
767
258
69
554
-
30
36
388
26
17
189
26
3
1
1233
-
166
44
916
16
412
74
1
98
-
7
1858
350
808
3
1324
1030
697
2
223
-
181
750
98
95
140
488
470
74
62
186
287
409
596
592
162
377
458
66
73
614
348
416
274
-
489
4
109
50
448
39
10
964
1226
245
271
321
726
277
57
131
33
232
761
69
93
1249
897
1641
509
825
689
30
3002
37
622
1568
14
114
118
484
674
2816
364
438
1002
451
332
134
74
135
118
507
85
43
5399
6196
2811
11
692
3047
5321
1221
1744
1386
553
2867
418
170
44
552
443
229
127
421
1920
1610
1293
5
29
1026
3242
1365
290
722
594
39
2248
81
18
85
891
368
20
2320
1247
253
13
385
107
771
1450
202
11
304
8
203
20
68
242
53
158
84
57
262
750
2
14
110
17
2
131
225
114
27
20
139
23
45
108
14
774
322
206
7
209
241
1284
448
227
273
590
187
2
66
126
83
92
6
394
643
549
267
458
614
1414
154
385
15
62
26
511
166
36
15
174
0
302
141
41
61
Quadringula closteriodes
Radiococcus nimbatus
Rhodochorton sp.
Scenedesmus sp.
Schroederia setigara
Schroederia sp.
Sclenastrum capricornutum
Synura sp.
Unidentified filamentous green algae
Uroglena sp.
Xanthidium sp.
Zygenema sp.
Desmids
Arthrodesmus sp.
Closterium setaceum
Closterium monoliferum
Closterium toxon
Closteriopsis sp.
Cosmarium sp.
Euastrum evolutum
Micrasterias furcate
Spirogyra sp.
Staurastrum gracile
Staurastrum paradoxum
Staurastrum tetracerum
Stauratrum polymorphum
Cyanophyta
Anabeana circinalis
Anabeana sp.
Anabeana spiroides
Chroococcus sp.
Cylindrospermopsis raciborskii
Dactylococcopsis sp.
Gomphosphaeria sp.
Merismopedia sp.
Microcystis aeruginosa
Microcystis aeruginosa with
pseudoanabeana mucicola
Nostoc sp.
Oscillatoria sp.
Spirulina sp.
Tetrapedia gothica
Unidentified filamentous blue-green algae
Total number of taxa (N)
Shannon-Weaver index (H')
18
56
2208
93
660
18
8790
178
-
221
2691
49
118
4224
69
330
-
177
269
597
37
833
802
238
567
63
3288
3363
1116
200
24
22984
230
5
9312
18
235
426
12
432
617
43
53
49
479
8
56
535
186
236
190
6
482
26
156
322
175
122
37
318
9
551
1656
361
442
349
574
222
605
370
29
15
460
15
24
163
22
-
770
23
259
-
84
130
324
144
125
1062
22
2
273
19
20
33
38
46
108
13
102
278
81
143
482
469
531
1746
605
340
1124
678
37
1134
132
1182
5457
471
1110
306
708
91
499
1720
2379
22
47
1890
2119
29672
752
184
1141
945
2323
21252
17504
3925
4146
1824
140
326
764
3374
14666
2773
110
269
227
2124
37
26
1111
42
10
2174
990
7934
58
110
1344
118
66
542
1426
282
1114
35
71
2.406
66
2.324
770
7303
62
2.249
1133
400
75
577
52
2.092
1411
10023
19
257
52
2.099
184
3286
43
1.958
7
268
56
2.192
59
35
1373
51
1.965
4
600
52
1.918
aeruginosa, Peridinium sp., Trachelomonas sp., Spirulina sp., Synedra sp. and Zygenema sp
(Table 2). Species richness/diversity was greatest during the hot-wet season; Fbebruary (71
species), March (66 sp.) and April (62 sp.). Species richness/diversity was low during the
cool-dry season (May – August) with an average of 51 species and July recorded the least
number of species (43 sp.). The Shannon-Weaver diversity index was high for the hot-wet
season with February recording 2.406, March (H’ = 2.324) and April (H’ = 2.249). The lowest
diversity H’ index was recorded in October (1.918) while the cool-dry season averaged (H’ =
2.085) (Table 2).
Chlorophyll-a (chl-a) levels were generally high during the cool-dry season months of
May – July (average 14.13 mg m-3) and lowest in the hot-wet season months of September –
62
October (average 9.46 mg m-3). The highest chl-a levels were recorded in July (14.66 mg m-3)
and the lowest in August (4.67 mg m-3) (Figure 2c).
Hierarchal cluster analysis
Similarity was based on Bray-Curtis distance as a measure of relative similarity between
sites and seasons. This allowed for the graphic illustration of similarities between sites
making use of hierarchal cluster analysis (Figures 3). As in the RDA analyses, consistent
patterns emerged between the successive surveys seasons and months. From Figure 3, a
total of four groups were formed with the first group consisting of hot-wet season months
(February – March), group 2 consisted of cool-dry season months (May – July), hot-wet
season month (April) and hot-dry season months (September – October). Group 3 consisted
of the cool-dry season month August and cool-dry season month July site 5 formed a
separate individual group 4 (Figure 3).
Table 3. Summary of RDA analysis results for the relationship between zooplankton (zoo)
and phytoplankton (phyto) species and environmental parameters in Malilangwe
reservoir.
Axis
Eigen values
Species-environment correlations
Cumulative percentage variance
of species data
of species-environment relation
Sum of all eigenvalues
Sum of all canonical eigenvalues
1
2
zoo
0.181
0.874
phyto
0.12
0.932
zoo
0.126
0.818
phyto
0.105
0.793
18.1
40.5
12
35
30.7
68.9
22.6
65.6
Total variance
zoo
phyto
1
1
1
0.445
1
0.344
Redundancy analysis
Six environmental factors (macrophyte cover, water level, dissolved oxygen, RP,
conductivity and pH), were identified as significant (p < 0.05, 499 Monte Carlo permutation
tests) to explain the significant proportion of variation in phytoplankton species abundance
(Figure 4). RDA shows that 68.9% of variations in phytoplankton species composition in the
Malilangwe Dam were caused by environmental variables. The first two axis, axis 1 and 2
accounted for 68.9% of the species-environment variation (Table 6, Figure 4). All
63
environmental variables; Conductivity, macrophyte cover, water level, pH, DO and RP were
significant with p < 0.05 and explained 44.5% of the phytoplankton variation (Table 4).
Figure 3. Dendrogram showing results from the hierarchal cluster analysis of the sites in
Malilangwe Reservoir. Key to site names: 1F – 5F (February site 1 – 5), 1M – 5M
(March), 1A – 5A (April site 1 – 5), 1Ma – 4Ma (May site 1 – 4), 1Jn – 5Jn (June site 1
– 5), 1J – 5J (July site 1 – 5), 1Ag – 5Ag (August site 1 – 5), 1S – 5S (September site 1
– 5), 1O – 5O (October site 1 – 5).
64
Table 4. Variation partitioning using the Monte Carlo permutation test for environmental
variables on zooplankton (zoo) and phytoplankton (phyto) communities.
F-ratio
zoo
phyto
4.609
-
P-value
zoo
phyto
0.002
-
9.4
7.3
7.3
4.1
3.3
-
5.393
4.215
4.169
2.367
-
0.002
0.004
0.006
0.042
-
44.5
5.8
5.9
4.6
4.5
4.6
9.2
9.9
4.495
3.842
3.942
3.06
3.021
3.1
6.15
0.002
0.004
0.004
0.004
0.004
0.006
0.002
1.0
All: Temperature, water level, RP, conductivity
All: Conductivity, macrophyte cover, water level,
pH, DO and RP
DO
pH
Temperature
Water level
Reactive phosphorus
Conductivity
Macrophyte cover
Variation (var) explained in common: zoo
phyto
Explained var (%)
zoo
phyto
32.1
-
Water level
Conductivity
RP
C. raciborskii
Pinnularia sp.
Macrophyte cover
H. pluvilias
E. planctonicus
Micractinium sp.
Fragilaria sp.
Euglena sp.
H. mucosa
Chroococcus sp.
Trachelomonas sp.
P. simplex
Ps. simplex "sturmii"
R. nimbatus
Diatom sp.
Scenedesmus sp.
Synedra sp.
-1.0
Diss. oxygen
Merismopedia sp.
Anabeana sp.
Spirulina sp.
pH
Coelastrum sp.
Gloeocystis sp.
A. spiroides
Chlorella sp.
Peridinium sp.
A. circinalis
Zygenema sp.
B. braunii
E. fotti
Gonium sp.
C. hirudinella
Cymbella sp.
M. aeruginosa
-1.0
1.0
Figure 4. Canonical Correspondence Analysis (CCA) ordination showing associations
between zooplankton species and sites sampled at different times and different
seasons. TP – total phosphorus.
65
Zooplankton
Species composition and seasonal variation
A total of 68 zooplankton species; 2 others (Chaoborus sp. and water mites), 13
Cladocerans, 7 Calanoids/Cyclopoids and 46 Rotifers were observed in Malilangwe reservoir.
The population density of zooplankton was greatest during the cool-dry season month of
June (27082 individuals per litre – ind. l-1) with the lowest density being observed in
February (1184 ind. l-1). Generally, low population densities were observed in the hot-dry
season with September having the lowest population density of 5028 ind. l-1. The population
Table 5. Relative abundance (individual per litre – ind. l-1) of zooplankton and other
macroinvertebrate fauna of Malilangwe reservoir, February – March 2011.
Rotifera
Anuraraeopsis fissa
Anuraraeopsis navicula
Ascomorpha ecaudis
Asplancha priodonta
Asplancha sieboldi
Branchionus angularis
Branchionus calyiflorus
Branchionus caudatus
Branchionus dimidiatus
Branchionus falcatus
Branchionus fortificula
Branchionus havanaensis
Branchionus plicatilis
Branchionus quadridentatus
Cephaladella gibba
Conochilus sp.
Epiphananes senta
Euchlaris dilatat macrura
Filinia longiseta
Filinia opoliensis
Filinia peljeri
Filinia peljeri grandis
Filinia terminalis
Gastropus sp.
Hexarthra mira
Horacella brehmi
Keratella cohlearis
Keratella lenzi
Keratella quadrata
Keratella tecta
Keratella tropica
Lecane bulla
Marcochaetus collinsi
Mytilinia mucronata
Polyarthra dilochoptera
Polyarthra remata
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
3
5
34
154
74
6
26
2
6
57
2
18
37
28
54
38
4
14
5
261
821
674
82
33
3
1138
25
137
623
58
72
316
8
23
7
422
198
110
35
87
1998
1264
-
2
102
554
2
211
93
18
561
20
73
1091
414
440
56
3
-
118
1570
172
607
498
1365
23
7322
3166
-
59
305
22236
551
102
1387
364
2993
-
2
9
13
539
38
3
40
48
58
41
9
4
2
21
507
111
7
6
101
3
14
4186
226
4
-
38
6
1194
30
107
18
56
140
10
39
215
253
56
6
312
544
743
33
1
-
6
9
118
49
234
81
25
321
2
5
109
92
270
38
45
9
295
22
2
-
66
Polyarthra vulgaris
Pompholyx complanata
Pompholyx sulcata
Synchaeta pectinata
Trichocera chattoni
Trichocera elongata
Trichocera flagellata
Trichocera similis
Trichocera similis grandis
Unidentified
Copepoda/cyclopoida
Neodiaptomus sp.
Eodiaptomus sp.
Mesocyclops sp.
Ectocyclops sp.
Thermocyclops sp.
Marcocyclops sp.
Nauplii
Cladocera
Alona sp.
Bosmina longirostris
Ceriodaphnia dubia
Ceriodaphnia quadrangula
Ceriodaphnia reticulata
Daphnia gessneri
Daphnia laevis
Daphnia longispina
Daphnia lumholtzi
Daphnia pulex
Daphnia rosea
Diaphanosoma excisum
Moina micrura
Others
Chaoborus sp.
Hydrachnellae
Total number of taxa (N)
Shannon-Weaver index (H’)
2
30
-
31
100
-
170
6
54
-
1068
11
55
2
4
2
482
46
45
440
-
328
68
2
-
232
14
14
3
-
252
283
1
35
2
14
55
-
77
18
-
17
6
9
67
40
12
8
134
87
147
2108
313
2190
621
106
364
1058
922
673
1054
1219
1857
653
412
2340
1193
2602
484
146
290
72
141
454
44
512
58
192
322
86
390
324
342
258
1254
12
202
33
24
35
72
30
48
36
43
699
257
40
30
46
1206
1518
8
624
92
2044
4564
1579
280
180
1508
1023
124
28
282
218
100
142
40
73
8
30
52
70
15
-
1090
1449
203
100
515
104
428
515
772
91
34
38
3.156
158
95
25
2.446
105
27
27
2.524
85
32
31
2.606
167
22
26
2.601
83
14
22
2.305
96
22
41
2.024
7
9
34
2.593
116
37
2.933
67
a
b
Figure 5. Temporal changes in (a) percentage composition (b) total abundance (individual
per litre – ind. l-1) (c) chlorophyll a content of phytoplankton in Malilangwe
reservoir.
density of zooplankton increased from the hot-wet season density of ≈ 10000 ind. l-1 to a
peak during the cool-dry season (Figure 2). Keratella lenzi was the most dominant species in
June (7322 ind. l-1). Rotifers were most dominant in September, cladocerans in October,
nauplii and cyclopoids in March, calanoids in April and other macroinvertebrate fauna
(Chaoborus sp. and water mites) in February (Figure 5a).
Peak population densities of zooplankton in June were dominated by rotifers (K.
lenzi, K. tropica and Filinia opiliensis); calanoids/cyclopoids (Thermocyclops sp.,
Neodiaptomus sp. and Nauplii) and cladocerans (Diaphanosoma excisum and Miona
micrura) (Table 2). Bosmina longirostris and Daphnia lumholtzi were only dominant during
the hot-wet season. During the cool-dry season, Lecane bulla, K. quadrata, Horacella
brehmi, Filinia peljeri grandis, D. excisum, M. micrura, nauplii, Thermocyclops sp., Asplancha
68
priodonta, hexarthra mira, K. lenzi and K. tropica were the most dominant species.
Ceriodaphnia quadringula, C. reticulata, Thermocyclops sp., A. priodonta, K tecta and K. lenzi
were dominant during the hot-dry season (Table 5).
The diversity of zooplankton was greater during the hot-dry season (September and
October) recording 34 and 37 species respectively. The highest and lowest species
diversity/richness was observed in cool-dry season month of August (41 species) and July
(22 species) (Table 5). The Shannon-Weaver diversity index show that the hot-wet season
month of February (H’ = 3.156) had the greatest diversity with August having the least (H’=
2.024). Hot-dry season had H’ diversity of above 2.5 (September = 2.593 and October =
2.933) (Table 5).
Similarity between zooplankton communities for the study sites and seasons was assessed
using hierarchal cluster analysis which allowed for the graphic illustration of similarities
(Figures 6). Three major groups emerged; February sampling (group 1), March – May, June
and September – October (group 2) and July – August (group 3). Between the successive
groups, several smaller groups of zooplankton communities formed that were similar for the
different months (Figure 6).
Redundancy Analysis (RDA)
The results of the RDA showed that the first two RDA axes accounted for 65.6% of the
species-environment relationship whilst also accounting for 22.6% of the variance in the
species data (Table 3). The test of significance of all canonical axes was highly significance
(Trace = 0.321, F-ratio = 4.609, p-value = 0.0020). Most significant variables were water
level, temperature, water level, RP and conductivity (Figure 7, Table 4). All environmental
variables; Conductivity, temperature, water level and RP were highly significant with p <
0.05 and explained 32.1% of the zooplankton variation (Table 4).
69
Figure 6. Dendrogram showing results from the hierarchal cluster analysis of the sites in
Malilangwe Reservoir. Key to site names (Figure 3).
70
M. micru
Marcocyclops sp.
Thermocyclops sp.
K. tropica
B. caudatus
C. dubia
K. lenzi
Chaoborus sp.
F. opoliensis
1.0
Temperature
D. excisum
B. falcatus
Ectocyclops sp.
R.
H. mira
K. tecta
F.peljeri grandis
P. vulgaris
Eodiaptomus sp.
phosphorus
T. similis
D. pulex
L. bulla
-1.0
P. complanata
H. brehmi
F. peljeni
K. cohlearis
C. quadrangula
C. reticulata
K. quadrata
A. priodonta
D. lumholtzi
Nauplii
Conductivity
Water level
-1.0
1.0
Figure 7. Redundancy Analysis (RDA) ordination showing associations between
phytoplankton species and sites sampled at different times and different seasons.
DISCUSSION
The information presented here has historical value for future research on Malilangwe
reservoir and is also unique in that it represents the first survey of plankton composition,
diversity and abundance of Malilangwe reservoir. Plankton communities for the nine study
months (February – October 2011) falling in the three seasons (hot-wet, cool-dry and hotdry) were significantly different. Small and shallow lakes usually exhibit markedly high interannual variability, which shapes their hydrological regime (Nhiwatiwa and Marshall 2007).
The results of study conducted on plankton species at Malilangwe Reservoir, show
there were marked differences in the plankton community composition and also succession
71
in the different seasons. It was also evident that plankton assemblages were closely
associated with environmental parameters and how highly distinct the different plankton
groups were. Changes in seasonal environmental factors which include pH, reactive
phosphorus, dissolved oxygen, macrophyte cover, conductivity and water level were
important in driving or structuring phytoplankton community composition. Our results show
that each species reacts individually to separate environmental variables and they may also
react to other variables that have not been measured. Mcrophyte cover or abundance had
the largest influence on phytoplankton community structure. Most of the phytoplankton
species composition were influenced by pH, DO and macrophyte cover with reactive
phosphorus, water level and conductivity having the greatest influence. Meanwhile,
zooplankton communities was strongly influenced by environmental parameters;
temperature, reactive phosphorus, conductivity and water level.
Highest densities of phytoplankton were recorded during low water levels in the
cool-dry season with least densities being observed during the hot-wet and –dry seasons.
Nhiwatiwa and Marshall (2007) observed similar trends in two small reservoirs where
phytoplankton increased during periods of long water residency. However, water residence
is 100% in Malilangwe reservoir so other processes that include nutrient inflows are also
very important. In that case, high phytoplankton densities could be attributed to the
decrease in destabilising effects of river inflows which increase nutrient input which favours
accelerated plankton growth in the cool-dry season as a result of low total dissolved solutes
and high water transparency. Offem et al. (2011) also observed a similar scenario in Lake
Ikwori where phytoplankton abundance increased with increasing water in transparency. A
low turbidity implies improved light attenuation and this can becomes an important factor
influencing algal productivity. The Cyanophyta were the more abundant taxa during cool-dry
season. This change in species composition followed a substantial increase in phosphorus in
May and this saw a dramatic increase of nitrogen-fixing species such as Nostoc sp. and
Anabaena sp. This could reflect a nitrogen-limitation in the reservoir and this was confirmed
by the by the very low N: P ratio (0.6 – 10.9) for the five study sites.
Algal blooms observed during the cool-dry season were mostly dominated by
Anabeana sp., Anabeana circinalis, Zygenema sp., Anabeana sporiodes, Ceratium hirudinella
and Perinidium sp. Ramberg (1987) showed that the dominant Cyanophyta species in Lake
72
Kariba, Anabaena sp. and Cylindrospermopsis raciborskii, were able to fix atmospheric
nitrogen when inorganic nitrogen concentration in water was low. In another study, it was
noted that the dominance Cyanophyta coincided with low nitrogen concentrations (<0.01
-1
mgl ) (Asiyo (2003). High pH and low levels of nitrate, nitrogen and water transparency in
the reservoir resulted in Cyanophyta abundance. The key attributes of Cyanophyta which
enable them to out-compete other algal species is their superior light capturing capacity in
low light situations and their high affinity to absorbing nitrogen and phosphorus at severe
limiting levels (Harding 1992, Asiyo 2003 and Descy et al. 2005). The Cyanophyta biomass in
Malilangwe reservoir was about 30 – 35% of the total biomass during most of the complete
water mixing period while Ramberg (1987) observed that Cyanophyta biomass ranged
between 70 - 90% for Lake Kariba during the same period. The gradual increase in
Cyanophyta algal biomass in Malilangwe reservoir during the complete water mixing period
was probably related to even distribution of nutrient throughout the water column as the
other environmental factors such as temperature only had small changes during the cooldry season months.
Predation by zooplankton also influences algal dynamics in Malilangwe reservoir as
the rise in phytoplankton biomass also corresponded to an increase in zooplankton biomass.
Therefore, the increase zooplankton explained the decrease in total algal abundance during
end of the cool-dry season. Nhiwatiwa and Marshall (2007) studies on two small reservoirs
on the Munwahuku River and Ivarez et al. (2006) studies in three shallow lakes in Monegros,
Spain observed similar findings where phytoplankton densities were controlled by
zooplankton during the winter period (cool-dry season). It has been observed that
cladocerans, copepods and rotifers feed on a large range of algae with a degree of
selectivity, important influential factors being size, shape, availability and toxicity of the
algae (Nhiwatiwa 2004).
The state of nitrogen depletion and other nutrient requirement of the individual taxa
could be important factors in determining algal species succession in Malilangwe reservoir.
There was an adequate supply of phosphorus hence it is likely that the phytoplankton rarely
experience severe phosphorus limitation. Thus, nitrogen fixers were found in high
abundance among the phytoplankton community in Malilangwe reservoir and there was
clear evidence of seasonality in the abundance of nitrogen-fixing taxa (Cyanophyta) in the
73
reservoir. The ability to adapt quickly to a fairly unstable limnological regime that is typical
of small, shallow waterbodies is an important factor that could affect species succession.
Therefore, taxa such colonial cyanobacteria species (e.g. Microcystis aeruginsa) which are
capable of acclimating to rapidly fluctuating light regimes will tend to dominate the system
(Harding 1992).
The results of this study showed that Bacillariophyta abundance declined reaching its
least abundance and diversity during the cool-dry season. Bacillariophyta development is
usually terminated by depletion of silica suggesting that silica might be a limiting factor
during the cool-dry season in the reservoir (Wetzel, 2001). During the hot-wet season, there
was increased development of Bacillariophyta, Cyanophyta and Dinophyta with Chlorophyta
being dominant. However, the slower growing Cyanophyta genera became dominant during
the cool- and hot-dry season. This sequence is expected to be modified by prevailing
environmental forcing factors as also explained by Harding (1992) on studies on the Lake
Zeekovlei. Therefore, total phytoplankton biomass increased in the dry season, mainly as a
result of greater abundance of Cyanophyta, Chlorophyta and Dinophyta. Movements of
water linked to the tilting of the thermocline in the southern part of the reservoir may have
favoured pulses of nutrients towards the epilimnion, which were best exploited by
phytoplankton with intracellular nitrogen and phosphorus storage capacities such as
Cyanobacteria.
Phytoplankton biomass was estimated using chlorophyll concentrations and the
reservoir biomass ranged between 4 - 16 mgm-3 chl-a with an average of 11 mgm-3 for May October. In contrast to Lake Chivero a polluted and eutrophic lake, Ndebele (2003) reported
average values of 8.8 mgl-1 which is almost in the same range with Malilangwe reservoir but
Mhlanga et al. (2006) reported chl-a values of up to 60 μgl-1 while Cleveland dam had low
average chl-a values of 2.6 mgl-1 (Ndebele 2009). Muggide (1993) observed that chl-a levels
in Lake Victoria ranged from 8.4 – 40.0 μgl-1. The generally high levels of chl-a can be
attributed to high phytoplankton biomass levels. The maximum chl-a (14.66 mgm-3)
measurement coincided with those of minimum water transparency values (1.01 m). This
condition can be explained by an increase in photosynthesis of phytoplankton
The zooplankton assemblages in the Malilangwe reservoir consisted of Cladocerans,
Cyclopoids, Calanoids and Rotifers. Sixty-eight zooplankton species were found, the total
74
Cladoceran species richness (13 species) was higher than most studies elsewhere. Various
studies have shown small reservoirs to be less diverse and comprising between 5 and 10
species lower than what was observed in our study (Green 1990, Masundire 1992, Elenbaas
and Grundel 1994, Basima et al. 2006, Nhiwatiwa and Marshall 2007, Chattopadhyay and
Barik 2009). Within the nine study months, zooplankton composition showed not much
significant differences with the least taxon richness being found during the cool-dry season
and a noticeable absence of most zooplankton species. Species richness of zooplankton
differed significantly among the study sites with higher values being observed for site 1 - 3.
Zooplankton communities were dominated by Nauplii, Macrocyclops sp.,
Thermocyclops sp., Diaphanosoma excisum and Moina micrura. It is possible that predation
by these suppressed the numbers of rotifers while grazing might have reduced the numbers
of most phytoplankton taxa. In May, when the reservoir is stratified, there was a peak in
dissolved oxygen implying increased availability of oxidizable organic matter. Particulate
organic matter (POM) is a component of suspended solids and the suggestion is that if
zooplankton can feed directly on POM as a food source then this would explain the sudden
increase in zooplankton abundance. Among the zooplankton, rotifers respond more quickly
to the environmental changes and used as a change in water quality (Leitão et al. 2006,
Rajashekhar et al. 2009). Rotifers are considered opportunistic organisms, with high capacity
of adaptation to ecological disturbances, some species can be particularly sensible to pH
changes.
Water regime affects the specific composition of zooplankton through changes in the
water quality and phytoplanktonic assemblage, determining different communities
associated to different trophic levels. The temporal variation of planktonic organism density
may be influenced by the reservoir’s operational regime, which determines the magnitude
of change on the water residence time (Leitão et al. 2006). Water duration in reservoirs and
ponds was found to account for significant shifts in zooplankton community structure
(Nhiwatiwa and Marshall 2007) and this is not the case with the Malilangwe reservoir as it
does not spill and other environmental factors such as water level fluctuations come into
play. Frequent variation in water depth may cause changes to the mixing depth-euphotic
depth ratio as well as changes in turbulence which affects phytoplankton succession and
thus impacting on the zooplankton community. Wantzen et al. (2008) and Kuczyńska-Kippen
75
et al. (2009) showed that water level fluctuations affected plankton densities and
composition, a similar situation observed in the reservoir.
Increase of Cladoceran densities has already been recognized as an indicator of
eutrophication in lakes and reservoirs (Magadza 1980, Sendacz 1984, Leitão et al. 2006,
Gülle et al. 2010) with some species presenting different responses associated to trophic
gradients. Diaphanosoma excisum is usually found more abundant in high organic content
water bodies (Rajashekhar et al. 2009). In this present study, Diaphanosoma excisum was
found present throughout the entire study period and can be considered as an indication of
increased organic content in the reservoir, thus suggesting that the reservoir might be
eutrophic.
Fluctuating water levels therefore caused changes in water chemistry and
macrophyte cover which resulted in changes in plankton species composition. The present
study can be used as a comparative base for future plankton studies on Malilangwe
reservoir. The major conclusion is that the plankton community of Malilangwe reservoir was
not dominated by Cyanophyta algae and cladocerans during the entire study period but
showed a typical seasonal successional pattern. Cyanophyta blooms dominated by
Anabeana sp. were only observed during cool-dry season (May – July). Increase in plankton
biomass can be a sign that reservoir is becoming eutrophic as shown by the high densities of
cladocerans.
76
AQUATIC MACROPHYTES IN A TROPICAL AFRICAN RESERVOIR: DIVERSITY, COMMUNITIES
AND THE IMPACT OF LAKE-LEVEL FLUCTUATIONS
Tatenda Dalu, Bruce Clegg and Tamuka Nhiwatiwa. 2012. Aquatic macrophytes in a tropical African
lake: diversity, communities and the impact of lake-level fluctuations. Canadian Journal of Fisheries
and Aquatic Sciences. Submitted for publication. 2012-0031
77
INTRODUCTION
Freshwater bodies are an integral part of tropical ecosystems (Heegaard et al. 2001). Lakes
provide habitats for many plant, bird, fish, insect and other animal species which interact as
a balanced ecosystem, with plants providing food and shelter for other organisms that live
in and close to the water. The influence of plants in a lake is not confined to the aquatic
ecosystem but extends to surrounding areas and a good example is how many insects spend
only part of their lives in water (Thomas et al. 2008), the other life stages being spent in
terrestrial systems. Aquatic plants are in intimate contact with the lake environment
because their roots and leaves are emerged in the water. Consequently, aquatic plants
respond strongly to changes in a lake’s prevailing environmental conditions (Heegaard et al.
2001).
Aquatic macrophytes are common in freshwater lakes, especially in the tropics and
have been used widely to assess water quality or habitat characteristics (Toivonen and
Huttunen 1995). Aquatic macrophytes and epiphytic algae on their stems and leaves
contribute a significant proportion of the sediment particulate organic carbon in small,
shallow lakes (Ficken et al. 2000). Larger lakes generally offer a wide range of habitats for
submerged, emergent and floating-leaved water plants. This is largely due to a broad
variation in littoral geomorphology, exposure to wind and associated wave turbulence,
water level fluctuations and gradients in nutrient availability (Feldman and Noges 2007).
Submerged macrophytes are crucial for the stabilization of the clear water state in shallow,
mesotrophic and eutrophic lakes (Schmieder 1997, van Donk and van de Bund 2002).
Macrophytes are also involved in ecosystem processes such as biomineralization,
transpiration, sedimentation, elemental cycling, materials transformations and release of
biogenic trace gases into the atmosphere (Cronin et al. 2006). Macrophytes directly store
nutrients in their biomass in spring and summer, which otherwise may contribute to
eutrophication of downstream waters (Schulz et al. 2003). However, determining
macrophyte cover and biomass is difficult both at small and large spatial scales because of
the spatial heterogeneity of these communities (Vis et al. 2003). This makes determining the
amount of nutrients stored in a lake difficult.
78
Lakes with a well-developed macrophyte community are usually associated with
more diverse communities of zooplankton, benthos and fish (Brendonck et al. 2003). It is
also well established, that within a single lake vegetated sites often support a greater
diversity of macroinvertebrates than do open water sites (Brendonck et al. 2003). The
presence of submerged aquatic vegetation is an important factor in shallow lake food webs
as the structural complexity of submerged aquatic macrophytes offers protection from
predation of recruiting fishes and provides an increased availability of food resources,
especially for smaller invertebrates (van Donk and van de Bund 2002). This structural
heterogeneity increases available niches resulting in high rates of secondary productivity
and high abundance of fish and invertebrates in submerged vegetation (Duffy and Baltz
1998, Gantes and Caro 2001, van Donk and van de Bund 2002, Schmieder et al. 2006).
Submerged macrophytes may reduce mixing of the water column and re-suspension of
seston and may also influence sinking losses and light climate for phytoplankton.
Macrophytes can produce allelopathic substances affecting phytoplankton and periphyton
and perhaps also higher trophic levels (Gafny and Gasith 1999, van Donk and van de Bund
2002). Rooted macrophytes also serve as a living link between the sediment, water and
atmosphere in wetlands, lakes and rivers. Macrophytes grow between the shoreline and
open waters dominated by plankton, and can potentially intercept or modify material flows
from land to the pelagic zone (Cronin et al. 2006, Carpenter and Lodge 1986).
Some floating aquatic plants have developed a poor reputation in southern Africa
because several alien species have become major problems in lentic systems. The water
lettuce or Nile cabbage (Pistia stratiotes), Kariba weed (Salvinia molesta), water pennywort
(Hydrocotyle sp.) and the water hyacinth (Eichhornia crassipes) have been widely
documented (Chikwenhere 1994, Gratwicke and Marshall 2000, Chikwenhere 2001,
Brendonck et al. 2003), but less is known about Azolla filiculoides Lam which was introduced
in Zimbabwe around 1980. It now infests water bodies throughout the country, although
according to Gratwicke and Marshall (2000), it is not yet officially considered to be a
problem. Floating plants can affect the water beneath them by forming thick mats which
eliminate submerged plants and algae, prevent photosynthesis and block oxygen diffusion
from the air causing the water to become anaerobic as well as reducing or eliminating
79
populations of fish and other animals from the water beneath them (Gratwicke and
Marshall 2000, Schmieder et al. 2006).
The majority of reservoirs in tropical Africa are shallow and polymitic and are found
in regions where evaporation approaches or exceeds precipitation with water typically
derived from rivers (Mustapha 2009). These reservoirs are usually filled up with water in the
rainy season, but become greatly reduced during the dry season as a result of evaporation,
sedimentation and water drawdown. These small African tropical reservoirs have short
water residence time, small size with small watershed, high shoreline development ratio
and large water fluctuations due to seasonal influence (Mustapha 2009; Geraldes and
Boavida 2005). Water level drawdowns in small reservoirs are also often a result of water
abstraction for purposes such as irrigation, and extreme water fluctuations are typical in
sub-tropics (Nhiwatiwa and Marshall 2006). Dam operations releasing water downstream
also account for some of the changes in water levels.
Human activities have altered water-level management regimes in water bodies
along many rivers (van Geest et al. 2005).The immediate effect of any water-level
drawdown is the potential stranding of organisms as the water level recedes. Long-term
effects of drawdowns include shoreline erosion and loss of aquatic macrophytes, which
results in a degraded benthic habitat for fish and invertebrates. Water level drawdowns
have catastrophic effects on aquatic macrophyte communities, the immediate effects being
destruction of above ground biomass for most submerged species (Richardson et al. 2002).
In shallow lakes, water-level fluctuations are often significant, attached periphyton usually
contribute mostly to the primary biomass especially when the littoral zone is extensive.
Macrophytes have the same properties as attached algae and are found at high densities in
shallow water. Macrophytes and periphyton can reduce the flow of mineral nutrients from
the bottom sediment to the water column (Jeppesen et al. 1997, Thomas et al. 2000).
A few studies have been carried out in Zimbabwe that investigate the composition
and succession of macrophytes in small reservoirs such as Chivake, Kaitano and Chakoma
(Chikwanhere 1994). Most studies have been on large water bodies such as Lake Kariba (Du
Toit 1985, Machena and Kautsky 1989, Mhlanga and Siziba 2006), Lake Chivero
(Chikwenhere 2001, Brendonck et al. 2003) and streams (Gratwicke and Marshall 2000),
mostly on invasive species impacts. The objective of the current study was to determine the
80
macrophyte species cover, composition, species richness and succession in Malilangwe
reservoir, as well as try to determine how the macrophyte communities respond to water
level fluctuations in different seasons.
METHODS
Study area
volume of 12 x 106 m3 at full capacity. Flanked by rocky hills on most of its sides, the
impoundment has a rocky substrate with few sandy bays. The fish communities include
predators, omnivores, detritivores, micro amd macrophages (Barson et al. 2008).
Macrophytes were sampled once during each of the three seasons present in Zimbabwe: (1)
November - April were considered the hot wet season and sampling was carried out in
March; (2) May – August the cool dry season, sampling being carried out in June; and (3)
September – October the hot dry season, sampling being carried out in September. Four
sites were selected along the littoral zones of the reservoir as shown in Figure 1.
81
Figure 1. Location of littoral zone sampling sites around Malilangwe Reservoir (shaded
area).
Basic water quality and morphometric measurements
A water sample was collected at each site and measurements of conductivity, total
dissolved solutes, temperature and dissolved oxygen (DO) were taken from each sample
using a pH, Conductivity and DO meter (HACH, LDO, Germany). Water transparency was
measured using a Secchi disk. Nitrogen was determined by the persulphate digestion
method (Hach method 10071) while total phosphorus was determined by PhosVer 3 with
acid persulphate digestion method (Hach method 8190 and Standard Methods 4500 P-E).
Shoreline development (DL) is the degree of shoreline irregularity expressed as ratio of
shoreline length to the circumference of a circle of area equal to the surface area of the
lake. The closer this ratio is to 1, the more circular the lake. A larger ratio means the
82
shoreline is more crenelated and hence the potential for littoral community development is
greater. Shoreline development was calculated as:
DL = L/(2 x sqrt (Ao))
Where DL = shoreline development index
L = shoreline length
Ao = lake surface area
Macrophyte and substrate sampling
A standard length of water, 100 m, was selected at each of the four sites on both sides of
the reservoir and assessed to confirm its suitability for the survey and then marked as
described by Dawson (2002) and Hering et al. (2006). The macrophyte flora and physical
character of the area were then surveyed by wading and by boats. Wading was done in
zigzag manner across the littoral zone length, frequently investigating all the habitat types
present. At sites where the water was too deep to wade, a boat was used. Care was taken to
examine all small niches by setting up 8 (1 m x 1 m) quadrats within the survey area.
Percentage macrophyte cover of all species present within the quadrats was recorded.
Identification of the macrophytes were done up to species level where possible using field
identification guides by Sainty and Jacobs (1988) and also with the help of a local experts
such as Dr Bruce Clegg and Mark Hyde and Bart Wursten of Zimbabwe Flora
(www.zimbabweflora.co.zw). Results were calculated as percentage macrophyte cover of
the different species.
Sediment analysis
Sediment samples were collected for analysis in all the four sites in June 2011 using a mud
grab. The samples were analysed at the Hydrobiology Laboratory, University of Zimbabwe
using standard methods described by Anderson and Ingram (1989) and Keeney (1982).
Variables that were determined were sediment texture (sand, silt, clay content), carbon
content (% C), nitrogen (% N), phosphorus (% P) and organic matter.
83
Data analysis
The differences in physicochemical characteristics between sampling stations were assessed
using Kruskall Wallis analysis. Kruskall Wallis analysis (p < 0.05) a non-parametric test was
carried out to test the differences in physicochemical characteristics between sampling
stations (H0: no difference between five sampling points). The analysis was done for the
whole study period, March, June and September 2011 using SysStat 12 for Windows version
12.02.00 (Systat 2007). Macrophyte cover estimates (as mean transect cover per site,
calculated from all transects estimates taken for that site including transects without
macrophytes) were log(x + 1) transformed prior to analysis according to MacKay et al. (2003)
so that composition data with a few very dominant taxa are down weighted.
Canonical Correspondence Analysis (CCA) and Hierarchal Cluster analysis (HCA)
Canonical Correspondence analysis (CCA) was done in order to get an overall assessment of
the associations between sites, sampling season, environmental factors and macrophyte
species occurrence. The macrophytes composition data was first tested for linearity using
(Detrended Canonical Analysis). The data was non-linear in nature and a unimodal method
was used. The software Canoco (ver. 4.5) was used for the analysis. The similarity in
macrophyte communities of the different sites sampled in different seasons was further
assessed with Hierarchal Cluster Analysis (HCA). Similarity was based on Sorensen (BrayCurtis) distances as a measure of relative similarity between sites and seasons using the
nearest neighbour linkage method. Hierarchal Cluster Analysis is a multivariate method, a
technique that defines groups based on their similarities (McCune and Mefford 2006). The
software PC-ORD for Windows 5 (McCune and Mefford 2006) was used for the analysis.
RESULTS
Littoral zone substrate characteristics
Wave action can be highly effective at sorting littoral zone sediments into distinctive size
patterns depending on site conditions such as sediment type, shore form, fetch and
exposure. The sediment texture was determined as the relative proportions of different
particle size classes in the littoral zone. Site 4 showed a relatively high amount of organic
carbon (1.89%), nitrogen (0.28%), phosphorus (11.45%) and organic matter (3.29%) within
84
the sediment substrate. Site 1, 2 and 3 were characterised by bedrock, boulders and cobbles
on the eastern side of the reservoir and pebbles, sand, silt and clay on the western side. Clay
composition was 30.9% in site 4, while a high proportion of sand (27.25%) and silt (41.85%)
were found in site 4 (Table 2). No bedrock, boulders and cobbles were found at site 4 during
the survey. Substrate was found to influence the composition and distribution of littoral
macrophyte communities. At site 1 - 3 where boulders dominated, L. stolonifera, P. crispus,
P. mauritianus and P. pusillus were found to be dominant. At littoral zones that had
predominantly sand, silt and clay substrates (site 4 and site 3 western side of reservoir), free
floating; A. filiculoides, emergent grass Panicum repens, Marsilea sp. and submerged
macrophyte Persicaria decipiens were dominant.
Table 2. The characteristics of sediment collected at different littoral sites sampled once at
Malilangwe Reservoir (June 2011)
Site
1
2
3
4
% Clay
85.00
87.00
96.80
30.90
% Silt
5.10
4.30
3.20
41.85
% Sand
9.90
8.70
0.00
27.25
% OC
1.73
0.50
1.97
1.89
% OM
3.00
0.88
3.43
3.29
%P
3.10
11.38
12.63
11.45
%N
0.19
0.24
0.23
0.28
for study period. There were no significant differences across the study sites for the three
seasons. Low DO levels were observed in March (mean 5.02 mg l-1) and high levels in June
(mean 7.89 mg l-1). Temperature averaged 30.1oC for all the study sites in the hot-wet
season (March), in the cool-dry season (June) the temperatures dropped for all sites with an
average of 21.6oC. The temperatures then increased slightly in hot-dry season to an average
of 23.9oC. A pH value of 7.88 (September site 4) was recorded as the lowest for all seasons
and pH varied from 8 to 8.9. The highest pH value (8.91) was recorded for June site 3. Total
dissolved solutes (TDS) increased from March (235 mg l-1) to a high in June (284.7 mg l-1)
before decreasing in September (241.4 mg l-1). Conductivity increased from March (191.6
μScm-1) to September (383.15 μScm-1).
Table 1. Limnological variables measured (± standard deviation) in Malilangwe reservoir in
85
March, June and September 2011
Variable
Dissolved oxygen (mg l-1)
Temperature (oC)
Conductivity (μS cm-1)
pH (mg l-1)
Total dissolved solutes (mg l-1)
Reactive phosphorus (mg l-1)
Nitrogen (mg l-1)
Ammonia (mg l-1)
Nitrate (mg l-1)
Chemical oxygen demand (mg l-1)
Total phosphorus (mg l-1)
Secchi disk transparency (m)
Water level (cm)
Maximum Depth (m)
Surface area (ha)
Shoreline length (m)
Shoreline development index
March
5.0 ± 0.9
30.1 ± 0.8
191.6 ± 11.2
7.9 ± 0.2
235.0 ± 3.7
0.3±0.2
1.7 ± 1.0
0.4 ± 0.2
0.0±0.0
27.6 ± 12.4
0.8 ± 0.4
1.0 ± 0.3
44.0 ± 4.2
10.54
186.3
9415
1.94
June
7.9 ± 0.3
21.6 ± 0.3
367.0 ± 1.3
8.6 ± 0.2
284.7 ± 0.8
0.6 ± 0.2
0.7 ± 0.5
0.03 ± 0.02
0.03 ± 0.01
19.5 ± 1.2
1.4 ± 0.3
1.0 ± 0.3
90.0 ± 5.8
9.64
169.5
9231
1.99
September
5.9 ± 0.9
23.9 ± 0.3
383.2 ± 1.0
8.3 ± 0.2
241.4 ± 0.5
0.8 ± 0.3
0.9 ± 1.2
0.02 ± 0.02
0.02 ± 0.01
29.9 ± 12.2
2.5 ± 1.5
1.1 ± 0.1
149.0 ± 4.7
9.05
157.1
8969
2.02
p value
0.69
0.98
0.67
0.94
0.95
0.73
0.65
0.86
0.64
0.66
0.45
0.05
0.37
Highest total nitrogen (TN) values were recorded during the hot-wet season with
March site 4 having the highest TN value of 0.41 mg l-1. The lowest TN values were observed
during the cool-dry season with June site 1 having the least TN value (0 mg l-1). Total
nitrogen values increased slightly in hot-dry season with site 1, 2 and 4 having 0.54 mg l-1
values while site 3 had the highest value of 0.98 mg l-1. Nitrate values were 0 mg l-1 for all
sites in the hot-wet season and increased during the cool-dry (0.03 mg l-1) and hot-dry (0.02
mg l-1) season. Ammonia decreased from the hot wet season (0.36 mg l-1) to hot-dry season
(0.02 mg l-1). High ammonia values for recorded for hot-wet season site 1 (0.41 mg l-1), cooldry season site 2 (0.05 mg l-1) and hot-dry season (0.05 mg l-1).
Total and reactive phosphorus (TP and RP) increased in the reservoir from the hotwet to hot-dry season (September – 2.52 mg l-1). Secchi disk transparency was relatively the
same for March (1.02 m) and June (1.01 m) but was high in September (1.13 m). Water level
decreased at averaged of 18.63 cm a month with the greatest decrease being recorded in
March (25 cm) and least decrease in June (9 cm). From February to October a total of 149
cm of water had been lost due to drawdown and evaporation (Table 1). Lake surface area
decreased from 186.3 hectares (ha) in March to 157.1 ha in September while shoreline
86
length was 8969 m in September, 9231 m (June) and 9415 m (March). Shoreline
development index increased slightly from March (1.94) to September (2.02) (Table 1).
Macrophyte distribution
Thirteen macrophyte taxa representing eight families; Potamogetonaceae (Potamogeton
crispus, P. pusillus and P. tricarinatus), Cyperaceae (Cyperus sp. and Schoenoplectus
corymbosus), Poaceae (Panicum repens and Phragmites mauritianus), Limnocharitaceae
(Ludwigia
stolonifera),
Azollaceae
(Azolla
filiculoides),
Najadaceae
(Najas
sp.),
Ceratophyllum (Ceratophyllum demersum), Polygonaceae (Persicaria decipiens) and
Marsileaceae (Marselia sp.) were recorded during the study period.
At the time of the hot-wet season (March 2011), the water level was high and
measured 4.88 m below dam spill level on the day of sampling. Sites 1 and 2 had similar
macrophyte species composition namely; Cyperus sp., Ludwigia stolonifera, Phragmites
mauritianus, Potamogeton crispus and Schoenoplectus corymbosus. Site 3 had all the
species found in site 1 and 2 but with the exception of P. crispus (species richness = 4).
Meanwhile, site 4 had the highest species richness of 6, but also with the exclusion of P.
crispus. Two species that previously did not occur in the lake, an emergent grass species
(Panicum repens Lam) and the free floating Azolla filiculoides Lam, were all recorded at site
6 (Table 3). At sites 1 - 3, L. stolonifera was the most dominant species in terms of
distribution followed by S. corymbosus and lastly P. crispus. At site 4, A. filiculoides was the
most commonly occurring as well as S. corymbosus, which showed a similar distribution
pattern. Phragmites mauritianus was the least common species and appeared to have a
limited distribution (Table 3). A. filiculoides, Cyperus sp., L. stolonifera, P. crispus, P.
mauritianus, and S. corymbosus were found at depths of 0.0 – 0.7 m and extending a
distance of 0.0 - 1.2 m from the bank lake ward while P. repens 0 – 1.2 m extending up to 11
m lake ward in some areas. Species of Cyperus sp., S. corymbosus and P. mauritianus could
be seen growing on the bank (riparian zone) up to 3 m landward.
Table 3. Vegetation cover (%) of macrophytes occurring in Malilangwe Reservoir during the
hot-wet season (March 2011)
Species
Submerged
Site M1
Site M2
Site M3
Site M4
87
Potamogeton crispus
Emergent
Cyperus sp.
Panicum repens
Ludwigia stolonifera
Phragmites mauritianus
Schoenoplectus corymbosus
Free floating
Azolla filiculoides
No macrophytes
1.5
0.5
-
-
5.8
65.5
3.8
20.4
20.9
44.6
4.9
26.1
21.3
36.9
13.6
25.2
14.6
17.5
15.5
1.9
22.3
3.0
3.0
3.0
25.2
3.0
During the cool-dry season (May - August 2011) the water level had dropped to
5.34m below dam spill level and a larger proportion of the littoral zone had no macrophytes
growing (> 65%) as shown in Table 4. Site 4 lost about 90% of its macrophyte communities
during the drawdown period. There was a decline in the number of species from hot-wet
season (7 species) to the cool-dry season (4 species), and the remaining species were A.
filiculoides, L. stolonifera, P. mauritianus and P. crispus. All sites had macrophytes present
with a minimum of at least 3 species (Table 3). Ludwigia stolonifera had the widest
distribution occurring at all the study sites, whilst P. crispus was found in very low densities
as well as distribution (Table 4). A. filiculoides, L. stolonifera, Potamogeton crispus and
Phragmites mauritianus were found at depths of 0.2 – 0.6 m and extending a distance
ranging from 0.0 - 0.9 m from the bank into the lake. Meanwhile, Cyperus sp., S. corymbosus
and patches of P. mauritianus could be seen growing on the bank (riparian zone) up to 4 m
landward. Most macrophytes which left exposed due to water level declines could be seen
drying out in the riparian zone (bank), a distance ranging from 0.1 – 7.0 m depending on the
site.
During the hot-dry season (September 2011) the water level had dropped to its
lowest of 5.88 m below dam spill level. Six macrophyte species not recorded before were
identified in the study area and these were: Marsilea sp., Ceratophyllum demersum Najas
sp., Potamogeton pusillus, Potamogeton tricarinatus and Persicaria decipiens. At this time,
most of the reservoir had no macrophytes. The dominant macrophyte species at sites 3 and
4 was C. demersum and both sites had 7 and 6 species, respectively. Site 2 had 7 species of
which
88
Table 4. Vegetation cover (%) of macrophytes occurring in Malilangwe Reservoir in the cooldry season (June 2011)
Species
Submerged
Potamogeton crispus
Emergent
Free floating
Azolla filiculoides
No macrophytes
Site J1
Site J2
Site J3
Site J4
0.7
0.3
0.2
-
15.0
2.0
17.0
16.0
18.0
9.0
6.0
1.0
82.3
66.7
72.8
2.0
91.0
P. mauritianus was dominant, while site 1 had the least number of species (5) with the
dominant species being P. Pusillus. No free-floating macrophytes were identified during the
hot-dry season (Table 5). Ceratophyllum demersum, L. stolonifera, Marsilea sp. Najas sp., P.
crispus, P. pusillus, P. tricarinatus, P. mauritianus and P. decipiens were all found at depths
of 0.0 – 1.2 m and extending a distance of approximately 3.0 m from the bank into the lake.
Cyperus sp., S. corymbosus, patches of L. stolonifera and P. mauritianus could be seen
growing on the bank (riparian zone) extending up to 13 m away from the water edge,
depending on the site.
89
Table 5. Vegetation cover (%) of macrophytes occurring in Malilangwe Reservoir in the hotdry season (September 2011) at Malilangwe Reservoir
Species
Submerged
Ceratophyllum demersum
Najas sp.
Potamogeton crispus
Potamogeton pusillus
Potamogeton tricarinatus
Persicaria decipiens
Emergent
Marsilea sp.
No macrophytes
Site S1
Site S2
Site S3
Site S4
17.5
8.5
0.5
2.5
14.5
-
22.0
0.8
3.2
9.5
1.8
-
11.0
2.5
5.0
3.8
9.0
9.5
14.5
41.0
6.5
13.0
43.2
8.0
5.0
64.7
3.5
29.0
24.0
7.5
18.5
Canonical cluster analysis (CCA)
The results of the CCA showed that the first two CCA axes accounted for 83.0% of the
species data. The species – environment correlation was also highly significant (r > 0.9) for
all axes (Table 6). Summary of Monte Carlo test testing significance of the 4 selected
variables pH, DO, Phosphorus and water level showed that the test of all canonical axes was
highly significant (Trace = 1.238, F-ratio = 6.565, p-value = 0.0020). Significant variables were
water level, dissolved oxygen, pH and phosphorus (Figure 2). In March, P. repens and A.
filiculoides were only found in site 4 (Figure 2). Sites S1 – S4 were only associated with P.
decipiens, Marsilea sp., P. pusillus, C. demersum and Najas sp., thus they are grouped
together in the CA plot (Figure 2). Site J4 is closely associated with S. corymbosus and
Cyperus sp. while L. stolonifera, P. crispus and P. mauritianus which were found throughout
the study are grouped together closer to sites M1 – M3 grouping (Figure 2). Site J1 – J3
which are closely associated are grouped together.
90
Table 6. Summary of CCA analysis results for the relationship between macrophyte species
and environmental parameters in Malilangwe reservoir.
Axis
Eigen values
Species-environment correlations
Cumulative percentage variance
of species data
of species-environment relation
Sum of all eigenvalues
Sum of all canonical eigenvalues
1
0. 699
0.995
2
0.329
0.939
3
0.146
0.939
4
0.064
0.762
44.5
56.4
65.5
83.0
74.8
94.8
79.0
100.0
Total variance
1.569
1.569
1.238
This allowed for the graphic illustration of similarities between sites making use of cluster
analysis (Figures 3). As in the CCA analysis, consistent patterns emerged between the
successive surveys seasons (Figure 3). To start with, the macrophyte communities in March
2011 samples were quite distinct from those of June and September 2011 (Figure 3). Then
from Figure 3, M1 – M3 formed a cluster indicating high similarity but site M4 differed from
the other sites. This was for sampling done in March 2011. A similar pattern was noted for
the June 2011 samples, where sites J1-J3 formed a cluster of high similarity but site J4
remained highly distinct. In fact the September samples (S1-S4) were more similar to the
June sites (J1-J3) than J4. It was only in the September sampling that all the sites were
91
clustered
together
showing
high
similarity
in
the
plant
communities.
Figure 2. CCA macrophyte taxa-environmental relations and sites sampled at different times
and seasons. Significant variables water level, pH, dissolved oxygen and phosphorus.
(□ = June sampling, ○ = March sampling, = September sampling).
92
Figure 3. Cluster Analysis diagram of the 2011 site (month) to denote relationships between
sites shown by the red rectangles. Site names; March site (M1 – M4), June site (J1 –
J4) and September site (S1 – S4).
DISCUSSION
The results of study conducted in three distinct seasons at Malilangwe Reservoir, show
there were marked differences in the macrophyte community composition and also
succession. With Canonical Correspondence Analysis (CCA), it was possible to show four
distinct macrophyte assemblages that were closely associated with conditions at the time of
sampling. This relationship strongly suggests that seasonal factors; pH, phosphorus,
dissolved oxygen and water level were important in driving or structuring macrophyte
community composition and succession. Our results show that each species reacts
individually to separate environmental variables and they may also react to other variables
that have not been measured. Most of the macrophyte species composition; Najas sp., P.
tricarinatus, C. demersum, Marsilea sp. and P. pusillus were determined by water level and
was highly distinct. Low water periods allow many macrophyte species and vegetation types
to regenerate from buried seeds. Fluctuating water levels therefore increase the area of
shoreline vegetation and diversity of vegetation types and plant species. Any stabilization of
water levels would likely reduce marsh area, vegetation diversity and plant species diversity
(Keddy and Reznicek 1986, van Geest 2005). The second group; P. crispus and P. mauritianus
93
were influenced by phosphorus and DO but DO had a lesser influence of the distribution of
these macrophytes. The pH level did not have any effect on macrophyte composition as it is
strongly influenced by DO levels.
Emergent macrophytes were most abundant during the hot-wet season (March) but
had the lowest percent cover during the cool-dry season. The low macrophyte cover in cooldry season is attributed to the fall in water level in the reservoir. Emergent and free-floating
macrophytes were found to reproduce and grow well during the hot-wet season while the
submerged macrophytes were successful during the hot-dry season. Competition could be
one of several factors that might have limited the growth and development of submerged
macrophytes during the hot-wet season. Machena (1989) in Lake Kariba showed that
emergent macrophytes which formed canopies at the surface effectively occluded light from
deeper water and non-canopy forming species like Najas sp. and C. demersum were
outcompeted. Observations by Macrophytes have a fairly long generation time which
enables them to respond slowly to changes in environmental factors such as water quality.
However, water level fluctuations have an almost immediate impact on the physiology of
the plant communities. Several studies have now also shown that hydrological factors are
one of the key determinants of macrophyte communities in lentic systems (Ali et al. 2007,
Feldmann and Noges 2007, Heergard et al. 2001). Macrophytes in Malilangwe reservoir are
sensitive to the water- level fluctuation regime.
Differences in the macrophyte communities were observed among the different
sites. Results showed that changes in water level corresponded to changes in the
distribution of macrophyte species in the hot-wet and hot-dry season. Azolla filiculoides was
found only in the site J4 while the dominant L. stolonifera and P. mauritianus were found in
patchy habitats throughout the lake in June. In September, submerged macrophytes began
to dominate most lake habitats with L. stolonifera and P. mauritianus remaining sparsely
distributed. These patterns were due to water level fluctuations influencing zonation
patterns as different species have different degrees of adaptation to stress caused by depth
and drying. Most submerged macrophytes would be immediately affected by exposure
compared to emergent macrophytes. Site 4 which was situated at the lake mouth had a
unique macrophyte community composed mainly of A. filiculoides and the emergent grass,
Panicum repens. Site 4 was different from the other sites and the possible explanations
94
could be that inflow enter the lake from the north (site 4) during the hot-wet period and is
normally expected to bring in higher levels of nutrients from the sub-catchment as shown by
the levels measured in the sediments (3.29% organic matter and 11.45% phosphorus) and
water (1.62 mg L-1 nitrogen). This inflow is likely to be unevenly distributed in the lake
thereby affecting their spatial distribution and massive macrophyte growth could have been
due to increases in nutrients (nitrogen). Studies carried out on factors controlling
macrophyte distribution in Lake Vörtsjärv in Estonia found that inflow contributed to spatial
distribution of macrophytes within a lake (Feldmann and Noges 2007).
Emergent macrophytes showed succession zones between the dry land and
inundated areas with each zone having a dominant macrophyte species influenced by falling
water levels. This dynamic pattern was more pronounced for the sedges in the Malilangwe
reservoir. The differences between sites in macrophyte species composition was also
attributed to differences in the substrate structure at each site. At sites where boulders
dominated (Sites 1, 2 and 3), L. stolonifera, P. crispus, P. mauritianus and P. pusillus were
found to be dominant. Littoral sites that had predominantly sand, silt and clay substrates in
almost equal proportions of 33% were dominated by the free floating, A. filiculoides,
emergent grass Panicum repens, Marsilea sp. and submerged macrophyte Persicaria
decipiens. The influence of habitat structure on the spatial distribution of macrophytes has
been discussed in other studies. Lake morphometry is important since sediment
characteristics such as soil particle size and wave action depend on it, with the area covered
by macrophytes being inversely related to slope (Machena 1989).
In Lake Chivero,
Brendonck et al. (2003) in Lake Chivero found out submerged macrophytes were rare and
restricted to some shallow zones with a sandy bottom. Machena (1989) studies in Lake
Kariba showed that submerged macrophytes Najas sp. and C. demersum occur in deeper
water whereas Potamogeton sp. and Vallisneria occurred in shallow water with extreme
environmental conditions dominated by gravel and bedrock substrate as they have greater
ecological tolerances for these conditions. Observations by Machena (1989) are almost
similar to our study findings, as most of the submerged macrophytes were found to be
associated with extreme environmental conditions (gravel and rocky substrates).The
dominance of submerged macrophytes during the hot-wet season (September) has
ecological significance because they have an important role in the structuring and regulation
95
of aquatic ecosystems. According to Kouamé et al. (2011), they help in the stabilisation of
sediments resulting in reduced turbidity levels and they compete for nutrients with
phytoplankton. The natural growth of submerged species is limited by water transparency
and therefore light limitation (Haller 2009). In Malilangwe, Potamogeton crispus was found
to inhabit depth of 0.2 – 1.2 m. Secchi disk measurements were on average about 1m at all
the sites and they were less variable between sampling periods. The growth of submerged
species such as Potamogeton crispus is limited to waters that range from 0.9 to 1.8 m secchi
depth transparency (Haller 2009). It was therefore conclusive that light limitation controlled
the distribution of the species.
Potamogeton crispus is considered as an indicator of pollution and eutrophication
due to its tolerance of low light and high dissolved nutrients (Haller 2001). The submerged
macrophyte, P. crispus was present throughout the sampling period but with time, other
submerged macrophyte species namely C. demersum, Najas sp., P. pusillus, P. tricarinatus
and P. decipiens became prominent as water levels were declining. The above named
submerged macrophyte species which emerged in the hot-dry season had a colonizable
depth of 0–1.2 m but Machena and Kautsky (1988) and Machena (1989) found out that
Najas sp., C. demersum and Potamogeton sp. had potentially colonizable depth zone of 0-12
m in Lake Kariba with a secchi depth of 6 m. The differences in habitable depth may be due
to water transparency levels and the trophic status of the two lakes, with Malilangwe
reservoir being mesotrophic and having a secchi depth range of 0.6-1.4 m while Lake Kariba
is mesotrophic-oligotrophic with a secchi depth of 0-6m colonisable macrophyte depth.
Feldmann and Noges (2007) showed that low water transparency in Lake Vortsjarv, Estonia
was an important parameter limiting the depth distribution of macrophytes.
Colonisation by submerged macrophytes following a decline in water levels
corresponded with the decline in emergent macrophytes. It is possible that emergent
macrophytes might have had an inhibiting effect on the growth of submerged macrophyte
through competition for resources such a space, nutrients and light. Once emergent
macrophytes were excluded, the submerged community became more successful. Haller
(2009) noted that drawdown is a prerequisite for successful germination and survival of
various submerged macrophytes with water level fluctuations representing a significant
disturbance factor which resulted in increased submerged macrophyte diversity. Several
96
studies have found similar results were water level fluctuations resulted in changes in
macrophyte structure (e.g. Toivonen and Nybom 1989; Murphy et al. 1990; Rorslett (1991;
Van Geest et al. 2005, Hellsten and Dudley 2006). In New Zealand, lakes regulated for
hydropower generation had an increase in biodiversity with increase in range of monthly
water level fluctuation (Riis and Hawes 2002).
The basin morphometry of Malilangwe Reservoir changed as water levels declined
resulting in an increase in the littoral zone area. This increased shallowness extended the
sub-littoral zone to cover the entire water body with maximum depth changing from
10.52m in March to 9.03m September. The water level was decreased and in March, the
water level had decreased by 44 cm, June (90 cm) and September (149 cm). This translated
to a new littoral zone area increase of approximately 15%, and a larger surface area means
increased habitat diversity and the creation of more niches. Shoreline development (DL)
which reflects the potential for development of littoral communities of high biological
productivity, for Malilangwe reservoir DL increased from 1.94 in March, 1.99 (June) and
finally 2.02 in September suggesting an increase in littoral zone area for macrophyte
development. This explains the unusual trend whereby macrophyte cover increased with
declining water levels, which is normally not the case in other reservoirs.
An important factor that could influence macrophyte community structure is grazing
by wild animals. At Malilangwe, hippopotamus (Hippopotamus amphibius), waterbuck
(Kobus ellipsiprymnus) and waterbirds were all found around the reservoir littoral zones
grazing but the extent of observed extensive grazing could not be quantified. Studies
elsewhere showed that reductions in macrophyte biomass by grazers (hippos, ducks,
waterfowl, and insect larvae) can be substantial, with reductions exceeding 50% being
reported for crayfish, insect larvae, snails, hippos, ducks and waterfowl (Lodge 1991,
Schmeider et al. 2006). The high densities of snails present during the cool-dry season in the
dam could have also contributed to decreases in composition of the macrophytes as the
snails were also observed grazing on the macrophytes. This is corroborated by studies
elsewhere showing that large snail populations grazed on submersed macrophytes thereby
causing a significant reduction in macrophyte biomass and species diversity (Sheldon 1984,
Carpenter and Lodge 1986).
97
The hydrological regime of a reservoir has strong spatial and temporal influence on
the macrophyte community. Thus large shallow environments with occasional bottom
exposure within lakes or reservoirs have the highest potential for creating macrophyte-rich
areas/habitats as shown in the study. Water level fluctuations also represent a significant
disturbance to the ecosystem thereby allow other colonizers or dormant species to take
opportunity and establish themselves. However, the dynamics of macrophyte communities
in such systems must also be understood from the perspective that macrophytes play an
important role in lake primary productivity as well as food and habitat to other aquatic
organisms. Therefore the management regime for a small reservoir must be careful to
ensure that ecological components of the ecosystem are not severely affected.
Severe water level drawdowns on the reservoir will have negative impacts on fish
diversity and abundance, including important angling species (tigerfish) and will eventually
lead to the extinction of Tilapia rendalli in the reservoir. Drawdown habitats will be lost
through heavy water level fluctuations, with an associated severe impact on mammal, bird
and reptile biodiversity, including high profile conservation species. Water fluctuations will
results in benefits such as excellent wildlife viewing opportunities as the draw down zone
will attract many more grazing animals when the water level is low than when it is high. The
same applies to the water birds.
98
THE MACROINVERTEBRATE COMMUNITIES ASSOCIATED WITH LITTORAL ZONE HABITATS
OF A SMALL RESERVOIR AND THE INFLUENCE OF ENVIRONMENTAL FACTORS
99
INTRODUCTION
Invertebrates are the most diverse and abundant organisms in freshwater aquatic systems
and are a key component of aquatic ecosystem function (Kratzer 2002). Invertebrate
distribution and assemblage is strongly dependent on the composition and structure of
vegetation and invertebrates are recognized as an essential food source for nesting and
juvenile fish and amphibians in aquatic systems (Takhelmayum and Gupta 2011). Lakes with
a well-developed macrophyte community are characterised by a more diverse communities
of zooplankton, benthos and fish. Some species of the major secondary producers such as
rotifers, cladocerans and insect larvae are commonly found in both pelagic and vegetation
areas, whereas others are found in or in the vicinity of vegetation stands (Kouamé et al.
2011, Rocha-Ramirez et al. 2007, Skoroszewski and de Moor 1999, Curtis 1991).
Invertebrates form a very important part of any ecosystem since they comprise the
major portion of the biomass (Volkmer-Ribeiro et al. 2004, Dallas 2000, Phiri 2000).
Invertebrates are responsible for much of the nutrient cycling in the standing lentic systems
where the detritivores convert decaying organic matter into food for other invertebrates
(Kratzer 2002). Invertebrates form a complex food chain, which in turn provides a food
source for numerous vertebrates, notably fish and birds. Some taxa are confined to the
water for their entire life cycle while others rely on water for the development of their
immature stages (Curtis 1991, Kratzer 2002, Albertoni et al. 2007). Distribution of many
invertebrate taxa is limited by the availability of suitable habitats (Curtis 1991).
Macroinvertebrates are important primary consumers and decomposers of detritus and are
a critical connection between primary producers and the upper trophic levels of lakes and
reservoirs (Kratzer 2001).
Diverse invertebrate communities exist among the submersed vegetation of ponds,
pools and lakes. The abundance of phytophilous invertebrates in an aquatic ecosystem is
defined by many factors some of which may include macrophyte morphology, substrate
texture, epiphytic algal growth and community composition and defensive chemicals
(Albertoni et al. 2007, Kratzer 2002, Skoroszewski and de Moor 1999, Hann 1995). The
invertebrates can consume part of the plant or its associated periphyton. In eutrophic
waters, the grazing invertebrates may prevent algal blooms, thereby allowing submersed
macrophytes to persist (Hann 1995). Different submerged plants within a pond create
100
various microhabitats which should result in different assemblages of invertebrates (Hann
1995).
Benthic macroinvertebrates are amongst the most sensitive components of aquatic
ecosystems and are thus useful for assessing ecosystem integrity (Mackay and Cyrus 1998,
Chakona et al. 2009). They are largely non-mobile and are directly or indirectly involved in
most physicochemical processes in estuaries, ponds, pools and lakes. These invertebrates
are representative of the location being sampled and have a relatively long life cycle, which
allows monitoring of temporal changes in response to perturbation (Chakona et al. 2009a).
The heterogeneity of benthic macroinvertebrate distributions is attributable not only to
water quality but also to natural variations such as seasonal changes in populations or
influences of the substratum. Nevertheless, benthic faunal assemblages are indicators of
relatively small-scale effects of disturbance (Chakona et al. 2009, Mackay and Cyrus 1998).
Water levels fluctuations occur naturally in lakes and reservoirs as a result of
seasonal imbalances between the amounts of water entering via inflow, precipitation,
runoff and/or groundwater and water leaving the lake via evaporation and outflow (Zohary
and Ostrovsky 2011). Lakes and reservoirs fluctuate seasonally between maximum levels,
usually at the end of the rainy season and minimum levels at the end of the dry season.
Extreme or untimely water level fluctuations have undesirable effects on the biota,
ecosystems and man (Bond et al. 2008). Human exploitation of water resources leads to
increased annual and inter-annual water level fluctuations at times far beyond natural
amplitudes. A range of natural features of the water level regime are often impacted, not
only the amplitude of fluctuation but also the timing of the minimum and maximum water
levels and the rates of water level increase and decline (Gasith and Gafny 1990, Zohary and
Ostrovsky 2011).
Aquatic macroinvertebrate assemblages and communities offer a good reflection of
the prevailing hydrological regime and water quality in aquatic systems, furthermore
forming an essential component of the aquatic ecosystem. Several studies on invertebrates,
mainly aquatic insects in different fresh water systems or aquatic insects associated with
individual plant species or communities have been carried out on large water bodies such as
Lake Kariba, whilst no studies on the insects of Lake Malilangwe is on record. The study on
macroinvertebrate is the first to be carried out on the reservoir and the aim was to
101
determine freshwater macroinvertebrates communities found in the littoral and sediment
zones of the reservoir. The role of environmental factors on taxon richness, diversity,
relative abundance, distribution and dominance of invertebrates was also investigated at
selected sites during the study period.
Study area
Malilangwe Wildlife Estate (formerly known as Lone Star Ranch) is a wildlife reserve located
in the Chiredzi District, south-eastern lowveld region of Zimbabwe (20°58’ 21°02’ S, 31°47’
32°01’ E) (Figure 1). Malilangwe Dam is an impounded river, formed in 1964 and is used for
water supply in the wildlife reserve. It is situated on the Nyamasikana River, a tributary of
the Chiredzi River which in turn flows into the Runde River. It is a gravity section masonry
dam with a surface area of 211 hectares. Flanked by rocky hills on most of its sides, the
marginal plants including Azolla fuculoides, Panicum repens, Ludwigia stolonifera,
Potamogeton sp., Schnoeplectus corymbosus and sedges (Cyperus sp. and Phragmites
mauritanus). The fish communities comprise of predators, omnivores, detritivores, micro
amd macrophages (Barson et al. 2008).
METHODS
determined using standards methods from EPA, Hach and Standard Methods. A Kruskall
Wallis ANOVA test (p < 0.05) is a non-parametric test was carried out to test the differences
in physicochemical characteristics between sampling stations (H0: no difference between
five sampling points). The analysis was done for the whole study period, February – October
2011 using SysStat ver. 12.
102
area).
Macroinvertebrate sampling
A survey of macroinvertebrates in the littoral and substrate zones was conducted during
throughout the three seasons (hot-wet, cool-dry and hot-dry) between April and October
2011 and 5 sampling sites were selected based on their differences in vegetation type and
cover, soil type, position in relation to the inflow and outflow points. Sampling was carried
out at the end of each month for the seven selected sites. A tape measure was used to
measure 10 m long transect along the shore and pegs were used to mark the sites.
Macroinvertebrates were sampled semi-quantitatively using a nylon hand net (mesh
size 500 μm, dimension 30 x 30 cm) with an aluminium rim and a handle which could be
extended to allow sampling distance of up to 1.5 m. At each sampling station,
103
macroinvertebrates were collected by submerging the sampling net and sweeping a
demarcated 10 m length for a total sampling time of 5 minutes. This was done to ensure
that in terms of species richness, no taxa were excluded. This involved walking through the
water dragging the net through the macrophyte vegetation. Five drags were made along
each 10 m transect. The kick-net was carefully lifted out of the water to prevent the escape
of agile animals. Benthic macroinvertebrates were collected using a mud grabber from the
lake bottom substrate and this was performed five times at each study site. The benthic
composition was determined by pouring and washing the sample through a 1.5 mm mesh
sieve and removing organisms for identification and counting.
The collected macroinvertebrates from the different subsamples were then pooled
to constitute a single sample of each site. The samples were preserved in a 70 % alcohol
solution in 250 ml plastic containers for analysis to family level several keys which included
Davies & Day (1999), Gooderham and Tsyrlin (2002) and Gerber and Gabriel (2002a, b).
Although species level identification is desirable, family level identification is often the only
achievable for studies in Sub-Saharan Africa region. Even though considerable information is
lost due low taxonomic resolution, several studies have demonstrated that family level
classification for macroinvertebrates can produce meaningful results (Bailey et al. 2001,
Kratzer 2002, Nhiwatiwa et al. 2009, Kouamé et al. 2011).
Data analysis
Assessment of similarity among sampling sites
Macroinvertebrate species grouping according to differences in site and season were
assessed. Hierarchal Cluster analysis was performed using PC-ORD for windows 5 (2006).
Hierarchal Cluster Analysis (HCA) is a multivariate method, a technique that defines groups
based on their similarities (McCune and Mefford 2006).
Assessment of taxa dominance and diversity
Rank abundance is a measure of biodiversity and the curves are important as they are a
measure of evenness. Rank Abundance Analysis for the ten most abundant
macroinvertebrate taxa was carried out using PC-ORD for windows 5 (2006) to assess the
distribution of abundance among species in the samples.
104
Assessment of the influence of environmental factors on macroinvertebrate communities
To determine whether to use linear or unimodal methods for the analysis, Detrended
canonical Correspondence Analysis (DCCA) was used. The lengths of gradient were
examined and since the longest gradient was shorter than 3.0, a linear constrained method
was a better choice. Redundancy Analysis (RDA) a constrained linear ordination method
and also called reduced rank regression based on significant (p < 0.05) forward selected
environmental variables using 499 Monte Carlo Permutations was used for analysis. These
variables were water level, % macrophyte cover and conductivity. The software Canoco
(ver. 4.5) was used for the analysis.
RESULTS
for study period. The lowest water temperature occurred from May to September after
which there was rapid increase. Dissolved oxygen (DO) values were low during February –
March, increased between May to August before dropping in September – October. Well
oxygenated water was found throughout the cool-dry season (7 – 9 mg l-1). Site 1 recorded
the lowest DO values while site 3 the highest. Low DO levels of up 2 mg l-1 were recorded
during the February – March and September – October for site 1 and 2. Temperature
decreased through the three seasons (hot-wet – cool-dry). Temperatures averaged 26.65oC
in February before decreasing to a low in the cool-dry season 19.27oC in June. Temperatures
then increased from June to September (27.6oC). Highest temperatures were recorded in
October (28.40 oC) for site 5 and lowest in June site 5 (18.80 oC). Not much differences in
temperature between surface and bottom water existed during the cool-dry season when
the lake was stratified. A breakdown in stratification occurred in August. Low secchi disk
readings at site 1 - 5 ranged between 0.9 and 1.7 m with site 5 ranging from 0.2 – 0.6 m and
in August, it recorded 1.15 m (Table 1). Low secchi disk (SD) readings at site 1 - 5 ranged
between 0.9 and 1.7 m with site 5 ranging from 0.2 – 0.6 m and in August, it recorded 1.15
m.
105
Table 1. Descriptive statistics of the measured environmental variables in Malilangwe
reservoir (April - October 2011)
Variable
-1
Reactive Phosphorus (mg L )
-1
Ammonia (mg L )
-1
Total phosphorus (mg L )
-1
Nitrogen (mg L )
-1
Nitrate (mg L )
pH
-1
Total dissolved solutes (mg L )
-1
Conductivity (μS cm )
-1
Chemical oxygen demand (mg L )
-1
Dissolved oxygen (mg L )
o
Temperature ( C)
Macrophyte cover (%)
-1
Alkalinity (mg L )
Site 1
0.4 ± 0.4
0.1 ± 0.2
0.9 ± 0.9
0.9 ± 0.8
0.07 ± 0.2
7.9 ± 0.6
271.6 ± 37.8
347.5 ± 60.8
33.6 ± 27.2
1.4 ± 0.4
6.1 ± 1.9
24.5 ± 3.3
62.1 ± 40.5
16.4 ± 1.4
Site 2
0.3 ± 0.3
0.1 ± 0.1
0.7 ± 0.7
0.7 ± 0.3
0.02 ± 0.02
8.1 ± 0.5
273.5 ± 38.5
350.2 ± 63.5
36.5 ± 29.1
1.3 ± 0.3
6.6 ± 1.1
24.87 ± 3.6
63.1 ± 32.1
16.4 ± 1.5
Site 3
0.3 ± 0.3
0.1 ± 0.1
0.8 ± 0.7
0.6 ± 0.4
0.03 ± 0.03
8.1 ± 0.5
273.2 ± 36.7
349.6 ± 68.1
36.7 ± 27.5
1.1 ± 0.2
7.2 ± 1.2
25.2 ± 3.8
60.3 ± 35.0
16.9 ± 2.0
Site 4
0.3 ± 0.3
0.1 ± 0.1
1.1 ± 1.6
0.8 ± 0.8
00.2 ± 0.02
8.0 ± 0.5
274.2 ± 37.5
351.8 ± 66.8
36.8 ± 26.2
1.1 ± 0.2
6.6 ± 1.3
25.3 ± 3.7
47.1 ± 45.2
16.2 ± 1.5
Site 5
0.4 ± 0.4
0.2 ± 0.2
1.1 ± 1.6
1.7 ± 1.3
0.02 ± 0.02
8.2 ± 0.5
275.7 ± 40.6
352.5 ± 75.2
49.4 ± 30.0
0.7 ± 0.4
6.7 ± 1.4
25.6 ± 4.5
47.1 ± 45.2
17.6 ± 1.1
p value
0.91
0.92
0.88
0.65
0.98
0.92
0.99
0.85
0.50
0.01*
0.69
0.98
0.91
0.43
Ammonia and Nitrogen were shown to decrease during the coo-dry season especially during
May – July before increasing again for all study sites. Low levels of Total Nitrogen (TN = 0.68
mg l-1) were recorded during June. Nitrate values were low during the hot-wet season with
low values being observed for all sites. Low values were observed in July for all sites (0 mg l1
) but increased from August (0.01 mg l-1) to October (0.03 mg l-1). Nitrate value was high for
February site1 (0.5 mg l-1), March site 1 (0.07 mg l-1) and June site 4 – 5 (0.04 mg l-1).
Ammonia values were high for February and March site 5 (0.17 mg l-1 and 0.40 mg l-1) while
site 4 in August and October recorded high values (0.11 mg l-1 and 0.26 mg l-1). Low values of
ammonia were observed during the hot-wet season for all study sites. Alkalinity showed
slight seasonal changes in the study sites and it fluctuated between 15 and 22 mg l-1 for all
sites and months. Total dissolved solute (TDS) was high during April – July (270 – 360 mg l-1).
There was an increase in conductivity from March (191.6 μS cm-1) to September (383.15 μS
cm-1) (Table 1). Water level decreased at an average of 18.63 cm a month for all sites with
the greatest decreased being recorded for all study sites in March (25 cm) and least
decrease in June (9 cm). From February to October a total of 149 cm of water had lost due
to drawdown and evaporation.
Macroinvertebrate diversity
A total of 15771 macroinvertebrates belonging to 42 families (10 orders) were collected
from the sites. Average relative percentage abundance of the macroinvertebrates and total
106
number of identified families collected from each sampling site are shown in Table 2. They
were more macroinvertebrate families obtained in sites 1 – 3 compared to site 4 – 5.
Mollusca constituted 57.71 % of the total sample and other common taxa were Hemiptera
(27.31 %), Diptera (4.93 %), Archanida (3.22 %), Odonata (3.12 %), Annelida (1.73 %),
Ephemeroptera (1.07 %), Coleoptera (0.85 %), Lepidoptera (0.01 %) and Trichoptera (0.01
%). The most family taxa were Odonata (7), Hemiptera (8) and Mollusca (7) (Table 2). Eight
family groups; Veliidae (site 1), Pyralidae (site 3), Ancylidae (site 4), Sphaeridae (site 4),
Planorbidae (site 3), Calopterygidae (site 2), Protoneuridae (site 1) and Hydropsyche (site 2)
were only present in one study site and could not be found in other sites. Four family groups
were found the sediment habitats, Chaoboridae, Oligochaetae, Chironomidae and
Hirudinae.
Taxon richness for all the study sites is shown in Figure 2 for the different months.
Site 4 showed a steady decrease in the taxa richness from 16 to 8 while site 1 recorded
highest taxon richness in August (richness = 22) (Figure 2). They was a general increase in
taxon richness in site 1 – 3 in August (Site 1 richness = 22, Site 2 richness = 18 and site 3
richness = 17) and September site 5 (richness = 16).
107
Table 2. Relative percentage abundances of macroinvertebrates at the sampling sites on the
Malilangwe Dam for April – October 2011
Order / Family
Annelida
Hirudinae
Oligochaetae
Arachnida
Hydracarina (Hydrachnellae)
Lycosidae
Tetragnathidae
Pisauridae
Coleoptera
Curculionidae
Dytiscidae
Elmidae
Hydrophilidae
Hydraenidae
Diptera
Culicidae
Chaoboridae
Chironomidae
Ephemeroptera
Baetidae
Teloganodidae
Hemiptera
Belostomatidae
Corixidae
Gerridae
Naucoridae
Nepidae
Notonectidae
Pleidae
Veliidae
Lepidoptera
Pyralidae
Mollusca
Ancylidae
Corbiculidae
Lymnaeidae
Physidae
Planorbidae
Thiaridae
Sphaeridae
Odonata
Aeshnidae
Calopterygidae
Chlorolestidae
Coenagrionidae
Gomphidae
Lestidae
Libellulidae
Platycnemidae
Protoneuridae
Trichoptera
Hydropsyche
Number of taxa
Site
1
2
3
4
5
0.84
-
0.23
-
0.46
1.09
1.47
1.57
2.01
1.53
3.69
0.24
0.03
0.03
5.97
0.03
0.16
0.03
2.98
0.06
-
-
2.65
-
0.27
0.19
0.14
0.10
0.59
0.20
0.36
0.09
0.57
0.29
0.03
0.09
0.03
0.07
0.16
-
0.36
0.08
0.20
0.52
7.00
0.14
6.27
0.46
3.49
0.40
0.03
2.09
1.21
0.08
1.20
1.57
1.33
0.03
2.79
0.03
0.11
-
0.49
-
0.52
-
0.68
9.34
0.08
0.33
0.38
21.55
0.41
0.11
1.18
11.48
0.03
0.69
0.62
19.85
0.20
-
0.86
8.91
0.23
0.77
0.14
17.50
0.09
-
0.13
6.64
0.03
0.07
0.03
7.07
0.13
-
0.32
13.45
0.04
0.84
0.12
10.76
0.04
0.12
-
-
0.03
-
-
0.03
8.44
13.98
26.25
-
0.07
1.38
18.90
24.02
-
0.74
6.24
13.49
3.01
35.11
-
0.07
1.34
5.33
69.21
1.28
0.04
8.03
54.15
-
0.62
1.14
1.95
0.11
0.14
0.27
0.08
0.19
0.20
0.39
0.85
2.40
0.13
0.07
0.13
0.16
-
0.11
0.49
2.18
0.14
0.32
-
1.01
0.16
0.36
-
0.04
1.12
0.16
0.04
-
32
0.03
33
30
24
26
108
Assessment of similarity among sampling sites
Similarity was based on Bray-Curtis distance as a measure of relative similarity between
sites and seasons. This allowed for the graphic illustration of similarities between sites
making use of cluster analysis (Figures 3). As in the RDA analyses (Figure 4), consistent
patterns emerged between the successive surveys months with several small groups of
macroinvertebrates being formed (Figure 3). Two groups emerged from the analysis, with
one smaller group consisting of June site 1 -3 and July site 2. The large second group
consisted of several smaller groups that were similar. April and May site 1 – 4 were similar
and formed a small group which was similar to June site 4 - 5, July, August and September
site 4. August site 1 - 3 formed another group and September site 1 – 3 and October site 1
forming another smaller group. June site 1 and 3 formed another smaller group while the
rest of the sites formed individual groups.
Figure 2. Variation of taxon richness within the sites for the study months, April – October
2011.
109
Figure 3. Dendrogram showing results from the cluster analysis of the sites in Malilangwe
Reservoir. Key to site names: A – O = April – October, 1 – 5 = site 1 – 5 (April site1
= 1A).
Macroinvertebrates species rank dominance analysis
The rank analysis of the 10 most dominant macroinvertebrate families in Malilangwe
reservoir are shown in Figure 4. Overall, Thiaridae was the most dominant taxa and the
Oligochaeta the least dominant. The rank analysis for each site is presented in Table 3. For
sites 1 & 2, the 10 dominant families were the same. Thiaridae family group was the most
dominant with Chlorolestidae begin the least dominant for site 1 and 2 with the rank order
changing from the fifth family to the ninth. Thiaridae was the most dominant family with a
new family group, Oligochaetae being the least dominant group in site 3. At site 4, Thiaridae
was most dominant while Chironomidae was the least dominant. At site 5, Thiaridae was
the most dominant with Coenagrionidae being the least dominant. The Thiaridae, Physidae,
Notonectidae, Corixidae and Chaoboridae were dominant across all the five sites, with the
first four being the top 4 dominant families in the respective sites while Chaoboridae varied
in position in the top 10 rank abundance between 5th and 9th (Table 3).
110
Figure 4. Rank abundance for the 10 dominant macroinvertebrate families in Malilangwe
Reservoir (April – October 2011).
Influence of environmental factors on macroinvertebrate communities
The results of the RDA showed that the first two RDA axes accounted for 82.3% of the
species data (Table 4). Forward selection revealed that from the input environmental
variables, macrophyte cover, water levels and conductivity were significant in explaining
patterns of occurrence and abundance of macroinvertebrate taxa in Malilangwe. Firstly,
Interactive effects between the environmental factors upon the macroinvertebrate
community were assessed. Altogether, the 3 significant variables explained 16.9% of the
variation. The individual effects of the significant environmental variables on the
macroinvertebrate communities were assessed as well (Table 4). All factors significantly
influenced macroinvertebrate community as follows; macrophyte cover 5.9%, water level
5% and conductivity 7%. In April and May, macroinvertebrate communities and abundance
were influenced and positively associated by percentage macrophyte cover while the rest of
the months (July, August and October) macroinvertebrate communities and abundance
were
negatively
associated
and
influenced
by
water
level
and
conductivity.
Macroinvertebrate communities and abundance in June and September was independent of
the three environmental parameters (Figure 5).
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Table 3. Rank abundance of macroinvertebrate taxa for the different study sites (Rel. ab. =
relative abundance)
Family
Site 1
Rank Rel. ab.
Physidae
3
515
Thiaridae
1
967
Coenagrionidae 8
72
Hydrachnellae 7
136
Corixidae
4
344
Notonectidae 2
794
Oligochaetae
Hirudinae
Chironomidae Baetidae
9
49
Chlorolestidae 10 42
Chaoboridae
6
258
Lymnaeidae
5
311
Planorbidae
Sphaeridae
Corbiculidae
-
Site 2
Rank Rel. ab.
3
576
1
732
7
73
6
182
4
350
2
605
8
85
10
26
5
191
9
42
-
Site 3
Rank Rel. ab.
3
471
1
1226
9
76
8
104
4
311
2
611
10
38
6
122
5
218
7
105
-
Site 4
Rank Rel. ab.
5
63
1
2115
3
203
2
216
6
48
7
45
10
37
4
64
9
39
8
41
Site 5
Rank Rel. ab.
4
200
1
1349
10
28
5
66
2
335
3
268
8
38
6
50
7
39
9
30
-
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Table 4. Interactive and individual effects of explanatory variables for macroinvertebrates in
Malilangwe reservoir (April – October 2011)
Explanatory Variables
% species variation
explained
F-ratio
p
All significant variables together
Water level ∩ macrophyte cover ∩ conductivity
16.9
2.027
0.002
Interactive effects
Water level ∩ macrophyte cover
Water level ∩ conductivity
Macrophyte cover ∩ conductivity
7.1
7.1
6.3
2.399
2.442
2.180
0.002
0.002
0.002
Individual effects
Conductivity
Water level
Macrophyte cover
5
7
5.9
1.800
2.517
2.128
0.012
0.002
0.002
113
1.0
% macrophytes cover
Notonectidae
Water
Corixidae
Pisauridae Elmidae
Naucoridae Lestidae
Baetidae
Protoneuridae
Aeshnidae Lycosidae
Hydracarina
Thiaridae
LibellulidaeNepidae
Coenagrionidae
Gerridae
Teloganodae
Platycneidae Sphaeridae
Pyralidae
Pleidae Veliidae
Oligochaeta Corbiculidae
Curculiolidae
Hydraenidae
Tetragnaeidae
Hirudinaea Dytiscidae
Culicidae
Chlorolestidae Gomphidae
Lymnaeidae
Physidae
level
Calopteridae
Planorbidae
Belostomatidae
Chaoboridae
Hydrophilidae
Ancylidae
Conductivity
-1.0
Chironomidae
-1.0
1.0
Figure 5. RDA macroinvertebrate taxa-environmental relations. Significant variables water
level, conductivity and macrophyte cover. (■ = S, ● = Ag, ○ = A, ◊ = Jn, □ = M, =
O, = JL).
DISCUSSION
The main aim of this study was to determine macroinvertebrate communities in a reservoir
greatly affected by water level fluctuations and how these communities respond to changes
in the environment. A total of 42 macroinvertebrate taxa were recorded demonstrating
relatively higher taxa richness when compared to other small reservoir studies in other
regions such as 43 families in Lake Taabo (Kouamé et al., 2011), and 40 families in two lakes
of the Paraná River floodplain (de Neiff and Carignan 1997). Fewer taxa have been recorded
from some reservoirs in Zimbabwe such as 15 taxa in Lake Chivero (Brendonck et al. 2003)
and 11 taxa from Fletcher reservoir (Mwabvu and Sasa 2009). High species coexistence and
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frequency of occurrence contributed to greater diversity within Malilangwe reservoir with
higher taxon affinities occurring between taxa belonging to different orders possibly
suggesting less competition. Nhiwatiwa et al. (2009) showed that resource partitioning
among taxa of the different orders has been advanced as a primary reason why such
coexistence and high affinities are possible.
A high diversity of Mollusca (7 families) in our study could be related to the lake’s
trophic status which could considered to be mesotrophic and calcium levels averaged about
16 mg L-1 for all the study sites. Thiaridae and Physidae were the most dominant and
abundant Mollusca across all the study sites, especially the Thiaridae family group. Both
families (Thiaridae and Physidae) dominance may be attributed to the competitive
advantage they have over the other snails of rapidly increasing their populations (Kouamé et
al. 2011, Pointier et al. 1989). Since the study did not focus in detail on the Mollusca
populations, a mention of schistosomiasis (bilharzia) needs to be made as these two
gastropods groups (Physidae and Thiaridae) could be vectors of this disease. The increases
in abundance of these two gastropods pose a potential health hazard particularly to those
who are always in regular contact with the reservoir water during the cool-dry season.
Macroinvertebrate species composition and abundance in the study sites also
changed from April. Site 1, 2 and 3 had a taxa richness of 32, 33 and 30 while site 4 and 5
had a richness of 24 and 26. The low richness observed in site 4 and 5 could be due to less
macrophyte cover which is used as refugia by macroinvertebrates. Sites 1 and 2 had
macroinvertebrate families only unique to the area; Teloganididae, Pisuaridae and
Platycnemidae. Sites 1–3 had Lymnaeidae, site 2 - Calopterygidae, site 3 - Pyralidae and
Hydrophilidae and site 4 - Ancylidae and Sphaeridae which were unique to the sites. The
differences in species composition, dominance and abundance among the sites indicated
that the macroinvertebrate fauna and the suitability of the habitats maybe strongly
influenced by local environmental parameters.
The relationships between biotic and abiotic factors and the macroinvertebrate
community of Malilangwe reservoir were assessed using RDA multivariate procedures.
Percentage macrophyte cover, conductivity and water level were found to have a significant
effect on the distribution of macroinvertebrates. Water level of the reservoir was found to
be a relevant and important ecologically variable for macroinvertebrate communities
115
through increasing niche separation, thus allowing more species to coexist at higher
abundances (Nhiwatiwa et al. 2009). Changes in water levels also affected environmental
variables such as macrophyte cover around the reservoir (Dalu et al. unpublished data).
During the hot-wet season there was plenty of the macrophyte vegetation in the littoral
zone and water level was high before dropping as the seasons changed. This corresponded
to changes in the macroinvertebrate communities and it explains the differences in taxon
richness and abundance at the sites.
According to the results and analysis, macroinvertebrate communities in the
reservoir were less influenced by most water quality variables with the exception of
conductivity which showed a strong environmental gradient and had a structuring effect on
macroinvertebrate communities. Conductivity was shown to increase throughout the study
three seasons (hot-wet, cool- and hot-dry). Studies by Mwasa and Sasa (2009) also showed a
positive correlation between Physidae (Bulunus africanus) and conductivity (r = 0.56) while
Efitre et al. (2001) reported that the Uganda lakes with higher conductivity and pH showed
greater species richness and abundance of Mollusca. Therefore, high conductivity levels
could have had an effect on Mollusca diversity in the Malilangwe reservoir as it has been
shown to be great importance for Mollusca shells (Mwasa and Sasa 2009).
Macrophyte cover was also identified as an important habitat variable influencing
macroinvertebrate community in Malilangwe Reservoir. Our results indicate that with
decrease in macrophyte cover, taxon diversity increased but the abundance of each
individual families decreased. Macrophyte cover is of great importance as a refuge for
macroinvertebrate taxa from predation, offer a substrate for living on and also for laying
eggs in water medium (Amakye 2001, Kratzer 2002). Substrate type and depth may have
influenced the distribution of species and also the benthic fauna in sites with low
macrophyte cover. However, our findings are similar to findings by Mwabvu and Sasa (2009)
who observed the same scenario in Fletcher reservoir. Kovalenko et al. (2010) showed that
the abundance of certain macrophytes could explain a small proportion of variability in
macroinvertebrate communities, but the effect of this driver was consistent with our study
reservoir Malilangwe, as a decline in macrophyte cover and abundance due to drawdown
resulted in changes in macroinvertebrate communities, abundance and distribution. This is
also shown by Kratzer (2002) studies in the Okefenokee Swamp showed that changes in
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macrophyte cover and abundances affected macroinvertebrate communities and
distribution.
The findings of the study have shown that differences in richness, abundance and
distribution of macroinvertebrates in small reservoirs are influenced by hydrological regimes
and environmental factors associated with strong gradients. Macroinvertebrates are highly
adaptable to a broad range of ecological conditions hence only strong environmental
gradients can have a structuring effect on their communities (Nhiwatiwa 2009, Chakona et
al. 2009a, Lounaci et al. 2000). Therefore, the knowledge of the relationships between
macroinvertebrates and their environment is of crucial importance in the understanding of
the functioning of ecological systems.
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MODELLING SEDIMENTATION RATES OF MALILANGWE RESERVOIR, WITH THE AID OF
REMOTE SENSING TO ASSESS LAND DEGRADATION IN THE CATCHMENT
118
INTRODUCTION
Soil erosion causes many problems such as the filling-up of water reservoirs with sediments
reducing its storage capacity for irrigation, drinking water and capacity to control floods
(WCD 2000). The sediment storage can have large implications for ecosystem development
downstream of large river systems in arid environments resulting in large economical and
environmental consequences (WCD 2000). It is of great importance to predict sediment
yield at the catchment level and understand factors which determine reservoir
sedimentation rates. The knowledge on sedimentation rates will allow for the estimation of
the probable lifespan reservoirs and enable measures to taken against reservoir
sedimentation, watering shortage and river bank erosion.
In Zimbabwe, sediment load has exceeded normal design limits in many reservoirs,
thus reducing storage capacity and shortening their useful life for human benefit. According
to van der Wall Bake (1986) and Mambo & Archer (2007) Africa now stands for rapid land
degradation, declining fertility, soil erosion and drought. Sedimentation of reservoirs, in the
light of man accelerated erosion, is regarded by the Zimbabwean Government a major time
bomb (van der Wall Bake 1986, Mambo and Archer 2007). Within the framework of the
development of a National Master Water Plan for Zimbabwe, a reconnaissance study in
Siltation and Soil Erosion was carried out in May 1984 - January 1985 (van der Wall Bake
1986). It has been reported that over 50% of 132 small dams surveyed in Masvingo Province
in Zimbabwe by Elwell in 1985 were silted (Khan et al. 2007).
Land use change, is listed as the biggest threat to global biodiversity largely due to
deforestation activities (Enters 1998). Land degradation in Zimbabwe has been caused
mainly by the decline of forest areas through cutting down of trees for agriculture and fuel
(van der Wall Bake 1986, Mambo and Archer 2007). The widespread impacts of
deforestation are also reflected at a national and regional level through vastly elevated soil
erosion rates, sedimentation of major waterways and an increased frequency and severity
of floods (Adger 1992, Ewers 2006). Of the major causes of soil degradation; deforestation
and removal of natural vegetation account for 43 % with overgrazing, improper agricultural
practices and over-exploitation of natural vegetation contributing 29 %, 24 %, and 4 %
respectively (Enters 1998). Land degradation is most widespread and severe in communal
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areas which are characterized by deforested landscapes, poor quality pasture and soil
infertility. The recent land resettlement programme that started in 2000 has left most of the
country forests facing serious threat of deforestation increasing from 1.41 % (1990–2000) to
16.4 % (2000–2005). Degradation is mostly manifest as gullies that render large tracts of
land virtually unusable, threatening water supply and quality (Mambo and Archer 2007).
Despite the advances made in understanding several of the factors involved in
reservoir sedimentation, predicting the accumulation of sediment in a reservoir is still a
complex problem (Salas and Shin 1999, Mueller et al. 2010). Empirical models such as
SHETRAN, based on surveys and field observations, have been developed and applied to
estimate annual reservoir sedimentation load, accumulated reservoir sedimentation load
and accumulated reservoir sedimentation volume after a given number of years of reservoir
operation (Salas and Shin 1999, Bathurst 2002). Likewise, several mathematical models such
as GSTAR and WASA-SED for predicting reservoir sedimentation have been developed based
on the equations of motion and continuity for water and sediment (Toniolo and Parker
2003, Yang et al. 2004, Berres et al. 2005, Berres et al. 2007, Mueller et al. 2010). However,
empirical methods are still widely used in actual engineering practice. Several methods of
uncertainty analysis have been developed and applied in water resources engineering. The
most widely used methods are first-order analysis and Monte Carlo simulation. First-order
analysis is based on linearizing the functional relationship that relates a dependent random
variable and a set of independent random variables by Taylor series expansion. This method
has been applied in several water resources and environmental engineering problems
involving uncertainty (Salas and Shin 1999).
Recent ecological studies have highlighted the relevance of the Normalized
Difference Vegetation Index (NDVI) as a tool for assessing changes in vegetation cover
(Pettorelli et al. 2005). Land degradation is believed to be one of the most severe and
widespread environmental problems in Zimbabwe and globally. It is therefore important to
understand spatial and temporal distributions of vegetation in a region in order to assess
changes in land cover. Human-induced land degradation alters the vegetation cover and
function through increasing the extent of soil erosion or changing the local climate through
positive feedbacks. Remotely sensed NDVI may provide the basis for an early warning of
land degradation (Scanlon et al. 2002, Wessels et al. 2004). The method is however not
120
without its limitations and mis-registration of spectral images may lead to a considerable
number of errors and unusable results (Lu et al. 2003). The calculation of NDVI values is
influenced by a number of factors such as clouds, atmospheric, soil, anisotropic and spectral
effects (Crippen 1990, Wessels et al. 2004). Modified indices such as Soil Adjusted
Vegetation Index (SAVI) and Global Environment Monitoring Index (GEMI) have been
developed indices to correct for some of the confounding factors that affect NDVI (Wessels
et al. 2004). Despite its limitations, NDVI remains a valuable quantitative vegetation
monitoring tool.
Impacts of sedimentation
The effect of sedimentation in a dam is that it reduces the dam's water holding capacity,
with decline in capacity; the yield is reduced both in quantity and reliability. The
relationships between reservoir yields under certain risk levels, storage ratios and the
reliability of inflow, have been well established for Zimbabwe by Mitchell (1977). The
depositing of eroded soil sediments in water bodies from either natural or anthropogenic
impacts can result in the destruction of aquatic habitats and a reduction in the diversity and
abundance of aquatic life. Diversity and population size of fish species such as Labeo
altivelis and benthic macroinvertebrates associated with coarse substrates can be greatly
reduced if the substrates are covered with sand and silt. Tomasson and Allanson (1983)
showed that the growth rates of Barbus and Labeo sp. in Lake Le Roux, South Africa were
greatly reduced when transparency of the water decreased due to increased input in the
lake.
Increased sediment in rivers, lakes and reservoirs has an economic impact on public
water systems that use them as a source of drinking water. Suspended sediments cause the
water to be turbid, resulting in reduced light transmission which causes a reduction in
photosynthesis leading to a decline in primary production. Moreover, increased turbidity
decreases the water's aesthetic appeal, human enjoyment of lake and reservoir recreational
activities and interferes with disinfection of the water prior to it being pumped to the endusers. If the river cross-section is sufficiently reduced by sediment build-up, sedimentation
can increase downstream flooding. In addition, some metal ions, pesticides and nutrients
may combine with sediment particles and be transported downstream.
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Information on upstream land use activities and land cover change, sediment yield
within a catchment is required for controlling sediment accumulation in reservoirs.
Presently, there have been very few studies in Zimbabwe that have looked at the problem
of reservoir siltation (ZINWA, 2004). Therefore, there is not much data is available to
establish the correlation between changes in land use and land cover with sedimentation
rates in reservoirs. If this is not addressed, sediment loads could exceed normal design
parameters in some reservoirs, thus reducing storage capacity and a shortened useful
lifespan. The main objective of this research was to assess changes in land use and model
the impacts this would have on sedimentation rates in a small reservoir.
Study area
impounded reservoir formed in 1964 and is used for water supply in the reserve. It is
situated on the Nyamasikana River, a tributary of the Chiredzi River which in turn flows into
the Runde River. It is a gravity section masonry dam with a surface area of 211 hectares and
has a maximum volume of 1.2 x 107 m3 at full capacity, as well as a catchment of about 200
km2. The dam wall was initially built to a height of 10 metres in 1963 and the dam was filled
for the first time in 1965. In 1965 the dam wall was raised to a height of 19 metres, 22
metres in 1984, and finally to a height of 24 metres in 1988. The dam wall was raised by an
additional 1.75 metres in 1999 and has a current height of 25.75 metres. Malilangwe
reservoir last spilled in hot-wet season of 2000 after the Cyclone Eline induced floods in
2000. The resevoir’s impoundment which is flanked by rocky hills has a rocky substrate with
few sandy bays. It is poorly vegetated with a few marginal plants including Azolla filiculoides
(Lam), Ludwigia stolonifera (Guill and Perr) Raven, Panicum repens (Lam), Schoenoplectus
corymbosus (Roth ex Roem and Schult) Raynal, Potamogeton sp. and sedges (Phragmites
mauritianus (Kunth) and Cyperus sp.). The fish communities include predators, omnivores,
detritivores, micro amd macrophages (Barson et al. 2008).
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Figure 1. Location of Malilangwe Reservoir (shaded black area) and major water supplying
rivers in the catchment (MC).
METHODS
Assessment of changes in vegetation cover using remote sensing
The Normalised Difference Vegetation Index (NDVI) gives a measure of the vegetative cover
on the land surface over wide areas. Dense vegetation shows up very strongly in the
imagery, and areas with little or no vegetation are also clearly identified. NDVI identifies
water and ice with vegetation differing from other land surfaces as it tends to absorb
strongly the red wavelengths and reflect in the near-infrared wavelengths (University of
Reading 2002). The NDVI captures the marked contrast between the strong absorptance in
the visible wavelengths and strong reflectance in the near-infrared wavelengths which
uniquely characterizes the presence of photosynthetically active vegetation (Wessels et al.
2004). The use of NDVI enables the differentiation of savannah, dense forest, non-forest and
agricultural fields. However, it is important to note that non-green vegetation (not in leaf)
will not give a high NDVI and thus may not be measured. NDVI is one of the most widely
123
used vegetation indexes and its utility in satellite assessment and monitoring of global
vegetation cover has been well demonstrated over the past two decades.
The NDVI is also correlated with certain biophysical properties of the vegetation
canopy, such as leaf area index, fractional vegetation cover, vegetation condition, and
biomass. It has been observed that NDVI increases near-linearly with increasing leaf area
index and then enters an asymptotic phase in which NDVI increases very slowly with
increasing leaf area index (Roderick et al. 1996, Wessels et al. 2004, Jiang et al. 2006).
Calculations of NDVI always result in a number that ranges from -1 to +1, however, no green
leaves gives a value close to zero. A zero means no vegetation and close to 1 (0.8 - 0.9)
indicates the highest possible density of green leaves (Crippen 1990, Weier and Herring
2000) with values of the range between −0.2 and 0.05 for snow, inland water bodies,
deserts and exposed soils (Crippen 1990, Roderick et al. 1996, White et al. 1997, Bacour et
al. 2006).
The satellite data used in this study were Normalized Difference Vegetation Index
(NDVI) images downloaded from the United States Geological Survey (USGS), Global
Visualisation Viewer (GloVis) website: www.glovis.usgs.gov. Images from the years 2000 2009 were used to show changes. The images were processed using the Integrated Land and
Water Information System (ILWIS) Version 3.3 GIS software which employed the map-value
function to extract NDVI values from the sample locations. Sampling points were randomly
selected in the catchment area and in the reference sites with the aid of ArcView GIS 3.2a
software. The points demarcated positions of sites whose NDVI values were used analysis.
Coordinates (UTM) of each point were recorded.
NDVI, expressed as a ratio between measured reflexivity in the red and the infra-red
bands was calculated as:
NDVI = (NIR - R) / (NIR + R)
Where NIR (in TM imagery) = near infra-red band 4; and R = red band 3 (N.B. living
vegetation absorbs light in the frequency range of band 3 but shows almost no absorption in
the range of band 4).
The available NDVI data were not enough for a full Time Series analysis to be carried
out but there was need to find out whether there had been any significant changes for
124
Malilangwe wildlife reserve (reference) and catchment. A two-way ANOVA was therefore
carried out on the data set using the Microsoft Excel Data Analysis package (2010).
In this study, Malilangwe wildlife reserve was used as the reference site which
represents a natural functional ecosystem (Figure 1). Reference sites are supposed to occur
in similar biotic zones, in close proximity with the study site, and exposed to similar natural
disturbances (Society for Ecological Restoration 2004).
Estimation of sedimentation rates
Mathematical equations from studies by van der Wall Bake (1986), Wallingford (2004), Khan
et al. (2007) and Mavima et al. (2010) were used in the estimation of sediment rates and the
following procedure using several models was followed;
Gross mean annual reservoir inflow (MAI) (m3yr-1) was calculated by:
MAI = CA x MAR
(i)
where CA = catchment area (km2),
MAR = mean annual runoff (mm).
Annual runoff volume (ARV) (m3) was calculated by:
ARV = Pa x CA x 1000
(ii)
where Pa = annual precipitation (mm),
CA = catchment area (km2).
Sediment trap efficiency (St) as a percentage (the trap efficiency is generally assumed to be
100 % for most reservoirs were the gross storage ratio > 0.1) was calculated by:
St = (0.1 + 9 x SRg) x 100 or St = 0.1116 x In (C / I)
(iii)
where C = reservoir capacity at spillway crest level,
I = inflow volume of water to the reservoir and the relationship predicts the annual
sediment trapping efficiency of a dam from the ratio of the dam capacity to the
annual inflow volume,
SRg = gross storage ratio.
125
Sediment concentration was calculated according to Wallingford (2004) method since
catchment characterisation wasn’t carried out. The method uses the description which best
fitted the catchment and the Malilangwe catchment fell between two descriptions; basin
with low slopes and very well developed conservation (1200 ppm) and basin with moderate
topography and well developed conservation (3600 ppm). The sediment concentrations
were then averaged to give the mean annual sediment concentration of 2400 ppm (2400
mgl-1) for the catchment.
The predictive equation adopted from Wallingford (2004) and Khan et al. (2007) was
used for estimation of sediment yield for the catchment of the Malilangwe Reservoir with
the mean annual Sy then calculated using the formula:
Sy = X x MAR / 1000
(iv)
where Sy = Mean annual sediment yield (t km-2yr-1),
X = sediment concentration/density,
We used the Ministry of Lands and Water of Zimbabwe (MLWZ) (1984) methods, to
correlate the coefficient of variation (CV) of mean annual runoff with MAR were used a
fitted relationship:
CV = (0.00139MAR)2 - 0.7538MAR + 154.5 (R2 = 0.87)
(v)
where CV = coefficient of variance (%),
The probability of a dam filling can be estimated from the coefficient of variation of annual
runoff and the dam capacity to annual inflow ratio, using a procedure developed for dams in
Zimbabwe described in Mitchell (1987). Mitchell argues that given the relatively short
records and other deficiencies in the available data, the use of complex statistical functions
is not justified, and that the Wiebul distribution can be used to represent the distribution of
annual inflows to a dam:
P = e-km
(vi)
where P = probability of a dam filling from empty,
km = (c x V/I)n,
126
V = Dam storage volume (m3),
I = Annual inflow (m3),
c = Constant related to CV (taken as 1.11),
n = Constant related to CV (taken as 0.84).
Storage capacity losses due to siltation
The proportion of the incoming sediment load that is trapped in a dam varies with the sizes
of the sediments transported to the dam, the water velocities or retention time in the dam,
and the proportion of the incoming flows that is passed over the spillway. The
interrelationship between these parameters is too complex to be considered in the design
of small dams (Wallingford 2004). Trap efficiency was assumed to remain constant at 100%
as Murwira et al. (2009) projected decreases in precipitation and runoff for the lowveld
region. The loss in a dam’s storage capacity over a specified time period is estimated using
equation:
Cn = 1 - [n x Sy x CA x St / (C x Den)]
(vii)
Where Cn = proportion of original storage capacity left after n years of siltation,
n = number of years,
Sy = catchment sediment yield (tkm-2yr-1),
CA = catchment area (km2),
St = sediment trap efficiency,
C = dam’s original capacity at full supply level (m3),
Den = settled density of dam sediment deposits (taken as 1.2 tm-3).
RESULTS
NDVI Analysis
Geographical Information Systems (GIS-NDVI) images were used for monitoring vegetation
changes in the Malilangwe catchment (MC). Figure 2 – 3 show vegetation change in the
catchment and Malilangwe Wildlife Reserve (MR) from 2000 - 2009. The catchment showed
progressive decline in NDVI values as shown by the decrease in cover especially along the
Malilangwe wildlife reserve boundary. The catchment showed a more extensive decrease in
127
vegetation cover than the reserve in areas along major rivers supplying Malilangwe reserve.
There was little change in vegetation cover over the Malilangwe wildlife reserve. From the
NDVI images and values, all sites in the wildlife reserve and the catchment between the
years 2000 - 2009 consisted of sparse vegetation as a range of 0.1 to 0.5 represent sparse
vegetation and >0.6 represent dense vegetation (Crippen 1990, Bacour et al. 2006). In 2002
and 2007 vegetation had decreased in both the reserve and catchment as seen by low NDVI
values (Figures 3 and 4). In 2009, the catchment and reserve were still covered by sparse
vegetation except for the southern tip of the reserve which had little patches of vegetation
(Figures 3 and 4).
The ranges of NDVI values are shown in Figure 4. Mean NDVI values were generally
higher for the catchment compared to the wildlife reserve. NDVI values decreased from the
year 2000 up to 2007. The decrease observed in the catchment was much larger compared
to the reserve. Mean NDVI values for Malilangwe Wildlife Reserve (MR) for 2000 were
0.4322 but decreased in 2002 (NDVI = 0.3229); 2005 (NDVI = 0.3729) and 2007 (NDVI =
0.3973). There was an increase in 2009 (NDVI = 0.4411) (Figure 4). Overall mean NDVI value
change for the wildlife reserve from 2000 to 2009 was 0.045. For the Malilangwe catchment
(MC), mean NDVI values showed a generally declining trend although they fluctuated
between the years. In 2000, mean NDVI was 0.4381; 2002 (NDVI = 0.395); 2005 (NDVI =
0.4354) and 2007 (NDVI = 0.3855). Similar to the wildlife reserve, there was an increase in
NDVI values in 2009 (NDVI = 0.4812) (Figure 4). The overall mean NDVI value change for the
catchment from 2000 to 2009 was 0.043.
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Figure 3. Colour composite Landsat satellite images covering Malilangwe study area in the wet season for (A) 2000, (B) 2002, (C) 2005, (D) 2007 and (E)
2009 overlaid with degraded areas mapped by National Land Cover (NLC). Map units are in kilometres, Universal Transverse Mercator (UTM) zone
36 South based on WGS 1984 spheroid
129
Figure 4. Colour composite Landsat satellite images covering Malilangwe study area in the dry season for (A) 2000, (B) 2002, (C) 2005, (D) 2007 and (E) 2009
overlaid with degraded areas mapped by National Land Cover (NLC). Map units are in kilometres, Universal Transverse Mercator (UTM) zone 36
South based on WGS 1984 spheroid.
130
Figure 4. Boxplots of NDVI values for Malilangwe catchment and Malilangwe Wildlife Reserve
(2000, 2002, 2005, 2007 and 2009).
The available NDVI data was not enough for a comprehensive Time Series analysis to be carried
out on the data. There was need to identify if there had been any significant changes in
vegetation cover over the years and also if there were any differences in terms of NDVI
between the catchment and reference sites. ANOVA revealed significant differences between
the years and sites (p < 0.05). However, for the years the trend implied by these differences
could not be established.
Sedimentation rates and reservoir capacity - inflow ratios
The sedimentation rates, capacity inflow ratios are presented in Table 2. The reservoir capacity
or volume was 1.2 x 107 m3 and inflows were determined from the long term data collected
over a 60 year period. The reservoir capacity to inflow ratio was estimated at 0.8. The
131
calculated gross storage ratio was 4 for the reservoir, and the sediment trap efficiency was
assumed to be 100% as the reservoir has no outlet for water. The catchment sediment yield
was estimated at 120.1 tkm-2yr-1 with a mean annual sediment concentration of 2400 ppm.
(Table 1). Using relationship developed by Mugabe et al. (2007), the Malilangwe catchment
area is about 200 km2 and with mean annual rainfall of 562 mm, runoff was calculated at 50
mm and the coefficient of variance of mean annual runoff was 120.3%. The runoff coefficient
for the catchment was calculated as 0.1 (Table 1). The probability of the dam filling with water
was calculated at 26.8%.
Table 1. Results of sedimentation rates for Malilangwe Reservoir.
Reservoir volume
Annual runoff volume
Mean annual runoff (MAR)
Sediment trap efficiency
Runoff coefficient
Mean annual sediment concentration
Catchment sediment yield
Probability of the dam filling
Coefficient of variance of MAR
Capacity – inflow ratio
m3
m3
mm
%
ppm
t km-2yr-1
%
%
1.2 x 107
1 x 107
50.0
100.0
0.1
2400
120.1
26.8
120.3
0.8
Predicted capacity storage losses for the Malilangwe reservoir calculated using the Wallingford
(2004) method is shown in Table 2. It is predicted that the dam will lose 16% of its storage
capacity over 100 years at current levels of sedimentation (120.1 tkm-2yr-1). The reduction in
water yield over the same period is expected to be larger than 16%. It is also projected that 32%
of the storage capacity will be lost over 100 year period with double the sedimentation (Table
2).
DISCUSSION
Remote sensing was used to assess changes in vegetation cover in the study area in a period
covering almost a decade. The interpretation of the NDVI data pointed toward a progressive
132
decline in vegetation cover in the Malilangwe catchment particularly in areas close to the
reserve boundary. We used NDVI values were employed as a surrogate for the assessment of
vegetation (deforestation) change rates in the catchment.
Table 2. Projected capacity storage losses (%) for Malilangwe reservoir for 0, 10, 25, 50, 80 and
100 years for different sediment yield rates.
Years
120.1
0
1.6
4
8
12.8
16
0
10
25
50
80
100
Sedimentation storage loss of reservoir in percentage
150.1
180.1
210.1
0
0
0
2
2.4
2.8
5
6
7
10
12
14
16
19.2
22.4
20
24
28
-2
-1
-2
-1
-2
-1
240.2
0
3.2
8
16
25.6
32
-2
Note: sedimentation rate increases 120.1 tkm yr - 0%, 150.1 tkm yr - 25%, 180.1 tkm yr – 50%, 210.1 tkm yr
-2 -1
– 75% and 240.2 tkm yr – 100%.
-1
Vegetation change thus showed a general decline in the catchment for the period 2000 – 2009
with a mean yearly change of 0.043 NDVI values whilst the wildlife reserve showed a slight
increase in NDVI values of relatively 0.045 NDVI units. The mean NDVI value decrease observed
in 2002 & 2007 in both the wildlife reserve and the catchment could be attributed to the severe
droughts in those years that significantly reduced vegetation cover. In contrast, NDVI increases
observed in 2005 and in 2009 in both the wildlife reserve and the catchment) could be
attributed to good rainfall during the two years. Therefore climatic factors have an important
role in determining vegetation patterns. This variable is of great concern as this can be linked to
protected climatic changes for the region where dry areas are expected to get less and less
rainfall.
The use of statistical tools to analyse NDVI values for the 2000 – 2009 period, identified
a large vegetation change in the catchment closer to the boundary with the communal areas.
The catchment vegetation is facing serious anthropogenic impacts such deforestation, veld fires
and vegetation clearing for farmland and firewood which is changing the vegetation structure
resulting in it being different from that of the wildlife reserve. There was a significant difference
133
found between catchment and wildlife reserve with the latter having higher vegetation cover.
It is evident that the catchment is slowly being degraded from analysis of 2000 – 2009, though
influenced by stochastic setbacks such as cyclone, drought and human-induced anthropogenic
events which are resulting in runoff and soil erosion changes in the catchment. Deforestation
had a significant effect on the runoff and sediment discharge from agricultural catchments
because it brought about a number of interferences such as increased surface runoff in streams
and rivers and soil erosion which resulted in sedimentation of rivers and the reservoir (Dinor et
al. 2007). Murwira et al. (2009) found a strong positive and significant correlation between
rainfall and runoff in the Save mega-basin. They noted that, an increase in rainfall has a
simultaneous increase in runoff and the inverse is also true and they also found a decreasing
but not significant trend in the rainfall and runoff over the years. A deficit of over 5 x 104 mega
litres of water in certain sub-catchments of the Save basin was projected given the worst case
scenario of decreased rainfall were observed (Murwira et al. 2009).
In Ivory Coast, deforestation increased surface runoff and sediment yield by 50 - 1000
times compared to the forested areas. Similar effects of deforestation have been reported from
East Africa, Kenya where sediment yield from agricultural and grazed catchments was
significantly more than from partially or forested catchments. Li et al. (2007) found out that in
deforestation increased both surface and subsurface runoff by about 20% because some of the
water that was formerly vegetation intercepted and evaporated became overland flow. They
also observed that about 80% of the increase was due to an increase in subsurface drainage of
soil moisture that would have been transpired by plants in the control experiment.
The combined use of NDVI, traditional statistical and mathematical tests greatly
improves the ability to analyse the impact of land use on catchment runoff and sediment yield
compared to using only method. Field studies should be carried out to determine the actual
amounts of sediments in the catchment and reservoir so as to provide the actual rate of
sedimentation related to land use change in the catchment. While acknowledging the
limitations of the techniques applied, this study demonstrates in part the effectiveness of
remote sensing as a tool for the production of baseline data for assessment and monitoring of
land degradation in the Malilangwe catchment
134
The annual catchment sediment yield for Malilangwe reservoir was calculated at 120.1
tkm-2 yr-1. The figure of sediment yield (120.1 tkm-2yr-1) obtained is similar to studies done by
van der Wall Bake (1986) where about half of the basins observed in Zimbabwe yielded more
than 100 tkm-2yr-1. The sediment yields for the Malilangwe reservoir of 120.1 tkm-2yr-1was
compared to that of Chikwedziwa (45 tkm-2yr-1) which is in the same geographic region and
area (van den Wall 1987). This could be attributed to little land degradation and low population
density per unit area (70 inhabitants’ per km2) in Chikwedziwa at that time (1987) but the
sediment rate for area is expected to higher than 45 tkm-2yr-1 at present. In the study area, high
rates of degradation and population increase are estimated at 2.68% and 2.2% per year
respectively (Lurop et al. 1998). Population growth and the poorly organised land resettlement
since the year 2000 have been cited major factors contributing to the deterioration of the
environment in the catchment (Mambo and Archer 2007).
The ratio of reservoir capacity to inflow indirectly provides an index of residence time of
sediment laden water in the reservoir (Reddy, 2005). Most sediment enters reservoirs during
high inflow periods and ideally if the capacity – inflow ratio is small, much of it will be
discharged over the spillway (Reddy, 2005). If the capacity-inflow ratio is large much of this
water is retained in the reservoir resulting in high sediment trap efficiency (Reddy, 2005). The
capacity-inflow ratio for the dam was 0.8 which is higher than the recommended ratio of 0.3 for
long economic life of the dam. In highly degraded catchments, where large sediment yield is
expected, the capacity to inflow ratio of about 0.5 is mostly recommended (Wallingford, 2004).
With such a high capacity-inflow ratio for the dam, the reservoir is expected to have high
siltation and shorter economic life.
The calculated gross storage ratio for Malilangwe reservoir was greater than 0.1
(calculated = 4) which according to Khan et al. (2007), a gross storage ratio of greater than 0.1
means the sediment trap efficiency is 100%. Thus, with a sediment trap efficiency of 100%, all
sediments that enter the reservoir are retained and trapped in the reservoir. A total depth of
about 8.6 m or 33.1% of storage capacity has been lost due to the sediment accumulation in the
reservoir over a 48 year period (1963 - 2011) with the current estimated maximum depth at
15.4 m from a previous of 25.75 m. The Save River catchment in Zimbabwe loses an estimated
135
2.6 × 108 m3yr-1 of its storage capacity annually (Marshall and Maes 1994). At current
sedimentation rates, the reservoir is projected to lose 16% of its storage capacity in 100 years.
With increase in land degradation in the Malilangwe reservoir catchment, the reservoir
estimated life span of over 100 years will be drastically reduced unless drastic measures are
taken to address the problem. Khan et al. (2007) showed that, the bigger the reservoir and
catchment, the better the siltation life. All projections on storage capacity, showed that the
reservoir will not lose over 50% of capacity in 100 years.
The coefficient of variation for mean annual runoff was calculated at 120.3% with a
capacity-inflow ratio of 0.8 which indicates a probability of filling of 26.8%. This is less than the
80% sometimes adopted as a target value for conventional water supply and irrigation systems
(Wallingford 2004) as this would probably be acceptable as it is customary to retain some water
in the dam at the end of the dry season (carry-over) to provide insurance against low rainfall in
the following year. Since the probability of the dam filling will be greater than the 26.8%, this is
way less than the recommended level hence measures must be put in place to conserve much
of the water in the reservoir. Other factors such as environmental factors (temperature, rainfall
and evaporation rates), changes in catchment activities such deforestation, poor agricultural
methods and water use and demand will be major determinants of the reservoir lifespan.
The annual runoff volume of 1 x 107 m3 indicates that, a storage volume larger than 0.8
x 1 x 107 = 8 x 106 m3 is required, meaning that an 11 m dam height from the current 15.4 m
dam height should be selected as this gives the best ratio of volume of water stored at any
given year. O’Connor (2007) calculated runoff volume 6.2 x 106 m3 for Malilangwe reservoir
which was lower than the calculated runoff volume of 1 x 107 m3 in this study. Magadza (2002)
projected that mean annual runoff of some major rivers in southern Africa is estimated to
decline by as much as 20 - 45% within the next 50 years meaning that the rate of erosion and
rate of sedimentation also be strongly related to runoff and rainfall.
Many benefits might be obtained from improving the management of the Malilangwe
reservoir catchment so as to reduce siltation rates in the reservoir. These includes addressing
poor land practices leading to low soil productivity and the value of wood and non-wood
products to be obtained from increased tree planting and improved management of natural
136
forest areas. It is strongly recommend that Malilangwe must be geared for increased variability
in the water availability in the reservoir with an increased frequency of droughts and floods as
projected by Murwira et al. (2009). This calls for the use of more dams and groundwater
sources (boreholes) within the wildlife reserve to reduce the negative effects of increased
water fluctuations in the Malilangwe reservoir. This sedimentation problem can only be solved
through wider soil conservation technologies that are readily understood and implemented by
locals and is within their financial reach. These measures require limited labour and require no
foregone benefits but lead to substantially increased benefits within catchment populations.
137
A STUDY OF THE ICHTHYOFUANA OF A SMALL TROPICAL RESERVOIR IN SOUTH-EASTERN
ZIMBABWE
138
INTRODUCTION
Freshwater forms the habitat of a large number of species, and therefore represent a
substantial proportion of the Earth's biological diversity. Of the world’s 44000 fish species
described, an estimated 42 % of the world’s fishes live in freshwater (Welcomme 2004). Dams
are obstacles for longitudinal exchanges along rivers, with nearly 60% of major river basins
fragmented by large dams (Jackson and Marmulla 2001, Burke et al. 2009). By altering the
pattern of downstream flow, dams are changing sediment and nutrient regimes and altering
water temperature and chemistry (Jackson and Marmulla 2001). Despite the negative effects of
dams, they are now very much a part of Zimbabwe’s landscape with over 12000 reservoirs.
Most were constructed before there was much knowledge on the impacts on river ecosystems
and their primary purpose was to store water agriculture, industrial and domestic consumption.
Stream fishes throughout the world are threatened by various human activities that
include physical changes to their environment, alteration of flow regimes, pollution, and alien
species (Zengeya et al. 2011). In southern Africa about 24 species of freshwater fishes are now
considered to be rare or endangered because of dam-building and water abstraction, among
other things (Gratwicke et al. 2003). In Australia, dams have generally resulted in negative
impacts to native riverine fishes while encouraging exotic species. This has been attributed, in
part, to disruption of seasonal flood cycles, and to dams acting as barriers to fish movements
(Jackson and Marmulla 2001). Very little is known about fish communities in small dams and
their ecology in rather unstable environments (Nhiwatiwa 2004) and the current project seeks
to add to this limited database of knowledge.
Fish species inhabiting reservoirs are drawn from the fauna of the impounded river.
However, many riverine species are unable to adapt to the new regime and disappear from the
main body of the reservoir (Jackson and Marmulla 2001). This was also the case for Lake Kariba,
were a total of seven species from the initial 31 species prior to impoundment are now thought
to have disappeared or are now very rare (Zengeya and Marshall 2008). A few migratory
species may persist in the shallow upper end of the reservoir (Welcomme 2004), as that
remains accessible to the river. Other species may adapt well to the new ecosystem often by
139
changing their breeding and feeding habits radically (Welcomme 2004). Typical reservoir faunas
often consist of the minority elements of the river fauna, which take on a new prominence by
occupying the new habitats (Jackson and Marmulla 2001). Where native species have proved
unable to adapt to the new conditions it has proved necessary to introduce exotic lacustrine
species such as the tilapias and carps into the basin to compensate (Welcomme 2004).
The introduction of invasive species and habitat destruction are considered to be among
the leading causes of extirpations and extinctions of species in freshwater systems. The adverse
ecological impacts of the Nile tilapia, Oreochromis niloticus on recipient rivers and reservoir
systems worldwide has drawn attention to the problems associated with fish introductions
(Ogutu-Ohwayo and Hecky 1991, Zengeya et al. 2011). The impact of the Nile perch, Lates
niloticus Linnaeus, 1758 on the haplochromine cichlids of Lake Victoria has drawn attention in
Africa to the problems that can follow introduction of exotic predatory fishes (Johnson et al.
2000). It has led to one of the largest species extinctions of modern times. In southern Africa,
there is concern about the impacts of introduced Oncorhynchus mykiss (rainbow trout) and
Micropterus salmoides (bass) on the populations of indigenous fish and in Zimbabwe the impact
of these introduced predators is generally ignored or overlooked (Gratwicke 2003). Micropterus
salmoides an exotic fish predator is also present in Lake Chivero constituting less than 1% of the
fish catch. It was introduced into Zimbabwe in 1932 and is now widespread throughout the
country (Zengeya 2005).
Small water reservoirs are characterised by fluctuating water regimes (Nhiwatiwa and
Marshall, 2006). It has been shown that seasonal fluctuations in the water level determine the
presence or absence of any fish species in a temporarily inundated area and also provoke
complicated changes in the community structure of the community (Gafny et al. 1992). These
changes thus can become a factor in controlling spatio-temporal distribution of fish species.
Sloman et al. (2002) found that unstable environmental conditions significantly altered
dominance structure of trout population that was stable under constant conditions. Loss of
reed beds at low water levels in Lake Biwa led to reduced survival of larvae of the cyprinid fish
Cyprinus carpio and Carassius sp. In years of strong autumn water level drawdown in Lake
Constance, the young (age 0) of the benthic fish Lota lota Linnaeus, 1758 migrated into pelagic
140
waters at an earlier age than typical for the species, possibly due to shortage of littoral
resources (Zohary and Ostrovky 2011). Gafny et al. (1992) argued that water level fluctuations,
either man made or natural, affect habitat availability in Lakes.
The littoral zones of any standing water body are the most productive region of a lake or
reservoir theoretically. It is an area where two layers of highest productivity, the water surface
or near surface layer and the bottom or near bottom layer overlap (Northcote and Atagi 1997).
It is also here where the greatest habitat complexity and diversity occurs providing a broad
range of differing microhabitats for exploitation of primary producers. The littoral zones are
areas of greatest abundance and diversity of zooplankters, benthic invertebrates and fishes
(Gafny et al. 1992, Northcote and Atagi 1997). The littoral zones of lakes and reservoirs are an
important habitat for most of the life history stages of fishes. Fish species tend to concentrate
in or around the littoral areas as habitat complexity provides refuge from predators with
aquatic macrophytes provide the physical structure used by near shore fish communities (Gafny
et al. 1992, Beauchamp et al. 1994).
There is a lot of literature on fish communities in Zimbabwe, and most studies have
been carried out on Lake Kariba and this body of literature is adequately captured in a recent
book on the fishes of Zimbabwe and their biology (Marshall, 2011). There have not been many
studies on fish communities of small reservoirs except for a few studies (Marshall and Maes
1994, Donnelly and Marshall 2004, Nhiwatiwa 2004). The aim of this study was to assess the
fish community in a small reservoir with an unusual hydrology in that it does not spill. It is
therefore a closed community and how the fish community has evolved will be compared to
similar aquatic systems.
Study area
Malilangwe Wildlife Reserve is located in the Chiredzi District of the south-eastern lowveld of
Zimbabwe (20°58’ 21°02’ S, 31°47’ 32°01’ E) (Figure 1). Malilangwe Reservoir is an impounded
river formed in 1964 and is used for water supply in the reserve. It is situated on the
Nyamasikana River, a tributary of the Chiredzi River which in turn flows into the Runde River. It
is a gravity section masonry dam with a surface area of 211 hectares with maximum volume of
141
12496259.92 m3 at full capacity. Flanked by rocky hills on most of its sides, the impoundment
has a rocky substrate with few sandy bays. It is poorly vegetated with few marginal plants
including Azolla filiculoides (Lam), Ludwigia stolonifera (Guill and Perr) Raven, Panicum repens
(Lam), Schoenoplectus corymbosus (Roth ex Roem and Schult) Raynal, Potamogeton sp. and
sedges (Phragmites mauritianus (Kunth) and Cyperus sp.). The fish communities include
Figure 1. Location of the study area, Malilangwe Reservoir (shaded area), south-east lowveld,
Zimbabwe.
METHODS
Fish surveys
Sampling was carried out monthly for 8 months (February – October 2011). The sampling
program was done using three types of fishing gear: fyke nets, seine net and gill nets. Fyke nets
were used in the shallow parts (< 1 m) while gill nets were set in the deeper sections (> 1.5 m)
of the dam. Three double fyke nets with a stretched mesh size of 24 mm connected by a 12.5 m
142
long net giving a total length of 18 m were set overnight at randomly selected sites. A fleet of
nylon multifilament gill nets with stretched meshes of 12, 20, 30, 40, 50, 72, 100, 128, and 140
mm were used in February and March 2011 and cotton multifilament nets stretched meshes of
7, 12, 20, 30, 40, 50, 60 and 72 mm were used throughout the sampling period and all nets
were set overnight for 12 – 14 hrs. A Seine net with mesh size of 18 mm was also used only in
June 2011. Gill nets were used more extensively compared to the other fishing gears. Fish were
identified using Skelton (2001) and Marshall (2010). Fish standard length were measured to the
nearest cm and weighted in kgs. The gonad maturation was assessed using a simplified scale
(Bagenal and Braum, 1968) as follows:
Inactive (IA) – these are the immature fish and adults in resting stage with sexual products not
yet developed, gonads are very small and eggs indistinguishable to the naked eye.
Active ripe (AR) – the eggs become distinguishable to the naked eye and testes change from
transparent to a pale white colour.
Ripe - running (RR) – eggs are clearly distinguishable to the naked eye and are big and testes
are white coloured. The sexual products can be discharged in response to very light pressure on
the fish belly.
Spent (S) – sexual products have been discharged and gonads appear deflated. The ovaries may
contain a few left over eggs or testes may have residual sperm.
RESULTS
Fish communities, abundance and diversity
Four seine net hauls, three sets of fyke nets and eight gill nets captured a total of 2170
individuals representing 8 species from 5 families; Cichlidae (Oreochromis macrochir,
Oreochromis mossambicus, Oreochromis placidus and Tilapia rendalli), Gobiidae (Glossogobius
giuris), Cyprinidae (Labeo altivelis), Characidae (Hydrocynus vittatus) and Clariidae (Clarias
gariepinus). Labeo altivelis was the most abundant species caught comprising 38.3% of the total
catch followed by Oreochromis placidus (20.3%), Oreochromis mossambicus (13.4%),
Oreochromis macrochir (12.4%), Hydrocynus vittatus (8.2%), Clarias gariepinus (6.682 %),
juvenile Glossogobius giuris (0.5%) and Tilapia rendalli (0.3%) (Table 1). The total fish biomass
143
was 2175kg. Labeo altivelis was the dominant species with an icthyomass comprising 41.1% of
the overall biomass, followed by Clarias gariepinus (15.5%), Oreochromis placidus (14.5%),
Oreochromis mossambicus (12.4%), Oreochromis macrochir (11.1%), Hydrocynus vittatus
(5.2%), Tilapia rendalli (0.3%) and juvenile Glossogobius giuris (< 0.1%) (Table 2).
Table 1. Relative numerical abundance (% n) of fishes captured in all 3 types of fishing gear
(seine (S), fyke (F) and gill (G) nets) in Malilangwe Dam (February - October 2011).
Species
Clarias gariepinus Burchell 1822
Glossogobius giuris Hamilton-Buchanan 1822
Hydrocynus vittatus Castelnau 1861
Labeo altivelis Peters 1852
Oreochromis macrochir Boulenger 1912
Oreochromis mossambicus Peters 1852
Oreochromis placidus Trewavas 1941
Tilapia rendalli Boulenger 1897
Total individuals
Number of species (n)
S
1
3
6
9
1
20
5
F
31
14
2
2
12
6
2
69
7
G
114
9
160
830
266
272
426
4
2081
8
%n
6.7
0.5
8.2
38.3
12.4
13.4
20.3
0.3
Species richness did not vary much during the study period. Six species, H. vittatus, C.
gariepinus, L. altivelis, O. placidus, O. mossambicus and O. macrochir were the most common
throughout the study months with T. rendalli and G. giuris being the least common species.
Differences are largely attributed to the effectiveness of fishing gear at each sampling occasion.
The distribution and abundance of eight fish species occurring in Malilangwe reservoir are
illustrated in Figure 2. The distribution and abundance of L. altivelis was closely associated with
the rocky areas of the reservoir. Hydrocynus vittatus juveniles were found abundant on the
western side, while the cichlids (tilapias) were evenly distrubuted in the resevoir with numbers
varying depending on sites.
Size distributions (length frequency analysis)
Length frequency distributions of H. vittatus, C. gariepinus, L. altivelis, O. placidus, O.
mossambicus and O. macrochir from gill net catches was plotted (Figure 3 and 4) while the
144
analysis of the other two species, T. rendalli and G. giuris was not done due to the small sample
size. Labeo altivelis captured during this survey measured between 23 and 42 cm with the
majority being mature individuals, which are estimated to reach a size of 40 cm
Table 2. Relative biomass (% kg) of fishes captured in 3 types of fishing gear in Malilangwe
reservoir (February - October 2011).
Species
Clarias gariepinus
Glossogobius giuris
Hydrocynus vittatus
Labeo altivelis
Oreochromis macrochir
Oreochromis mossambicus
Oreochromis placidus
Tilapia rendalli
Total weight (kg)
Seine nets
< 0.1
1.1
5.9
7.2
0.9
15.1
Fyke nets
84.4
7.9
0.8
1.2
10.1
2.5
2.4
109.2
Gill nets
253.2
0.1
103.5
892.5
239.1
254.1
306.2
2.6
2051.2
%n
15.5
< 0.1
5.2
41.1
11.1
12.4
14.5
0.3
145
Figure 2. The distribution and relative abundances of differences fish species in the Malilangwe
Reservoir (February – October 2011).
standard length (SL) (Skelton 2001). In February – March most species were in the 30 – 35 cm
SL size class but from April – October most of the species were in the 35 – 40 cm SL size class
(Figure 4). Glossogobius giuris species caught fell in the 0 – 10 cm SL size class whilst T. rendalli
fell into the 20 - 30 cm category.
Hydrocynus vittatus ranged in size from 18 - 48 cm SL. Most of the species were spread
across all the size classes with most falling into the 30 – 35 cm SL size class (Figure 3).
Oreochromis mossambicus ranged in size from 21 - 41 cm SL. Most of the O. mossambiccus
species fell into the 30 – 35 cm SL size class (April –October) whilst in February – March most of
the species were in the 25 – 30 cm SL size class (Figure 4. Clarias gariepinus ranged in size from
34 to 83 cm SL. Two catfish fell below the 50 cm SL and both measured 34 cm in February and
May. In February, May and June, age groups can clearly be distinguished using size classes.
Most the catfish were in the 55 – 60 cm category (Figure 3). Oreochromis placidus SL size
classes ranged from 15 – 35 cm with most of the fish falling into the 25 -30 cm category (Figure
2). Oreochromis macrochir had two dominant size cohorts; 25 – 30 cm (February – June) and 30
– 35 cm (July - October).
146
Figure 3. Length frequency distribution of H. vittatus, O. placidus and C. gariepinus in the
Malilangwe reservoir, relative abundance is given next to the month.
147
Figure 4. Length frequency distribution of L. altivelis, O. macrochir and O. mossambicus in the
Malilangwe reservoir (relative abundance is given next to the month).
Reproductive (gonad) state
The IA, AR, RR and S of 8 fish species; Clarias gariepinus, Hydrocynus vittatus, Labeo altivelis,
Glossogobius giuris, Tilapia rendalli, Oreochromis macrochir, O. mossambicus and O. placidus
for the nine study months in relation to rainfall are shown in Figure 6. Oreochromis placidus fish
bred throughout the nine study months with a peak in gonad activity being observed during the
winter period (April – August). Five fish species (Clarias gariepinus, Hydrocynus vittatus, Labeo
altivelis, Oreochromis macrochir and O. mossambicus) showed a decline in gonad activity from
February to July and an increase from August to October (Figure 6). The gonad activity of
Glossogobius giuris and Tilapia rendalli could not show a proper trend as few fish specimens
148
were caught; G. giuris (n = 10) and T. rendalli (n = 7) during the entire study period. Gonad
activity was related to rainfall patterns as for most fish species it declined with the onset of the
dry season (Figure 5).
Figure 5. Percentage AR, RR and S of 6 species excluding Glossogobius giuris and Tilapia rendalli
in Malilangwe reservoir (February - October 2011) and relationship with rainfall.
Regional species diversity assessment
A total of 36 fish species from 8 families were collected within Malilangwe reservoir, Save,
Chiredzi and Runde Rivers, Hippo Valley swamp and irrigation channels in fish surveys from
2009 – 2011. There 20 fish species from the reservoir, rivers and swamp while only eight
species were only found in the Save River (Table 3). Twelve species from Cyprinidae, 9 species
from the family Cichlidae, 3 species each from Alestidae and Mormyridae, 2 species each form
Poecilidae and Anguillidae, 1 species each for Centrarchidae, Clariidae, Gobiidae, Schilbeidae
and Machokidae respectively were collected in Malilangwe reservoir, Save, Chiredzi and Runde
Rivers, Hippo Valley swamp and irrigation channels. During the 2009 – 2011 fish survey, a total
of six fish species were recorded in the Malilangwe reservoir with the exception of C. gariepinus
and G. giuris but the two species were recorded during the 2011 fish survey bringing the total
number of species to 8 for the reservoir. The Save River had highest species richness of 28
species, Hippo Valley swamp recorded 11 species, Chiredzi and Runde Rivers had 13 species
149
each. Pollution-tolerant species Barbus paludinosus and Poecilia reticulata were recorded in
Hippo Valley channels, Save and Runde Rivers.
Table 3. The fish species from Chiredzi River (C), Runde River (R), Save River (S), Malilangwe
reservoir (M), irrigation channels (IC) and Hippo Valley swamp (Sw), sampled during a 2year survey that involved 4 sampling campaigns (2009 - 2011).
Fish family
Alestidae
Centrarchidae
Cichlidae
Clariidae
Cyprinidae
Gobiidae
Poecilidae
Mormyridae
Anguillidae
Schilbeidae
Machokidae
Genus and species
Micralestes acutidens
Hydrocynus vittatus
Brycinus imberi
Micropterus salmoides
Astatotilipia calliptera
Oreochromis niloticus
Pseudocrenilabrus philander
Pharyngochromis acuticeps
Tilapia rendali
Serranochromis robustus
Clarias gariepinus
Barbus afrohamiltoni
Barbus paludinosus
Barbus toppini
Barbus trimaculatus
Barbus radiatus
Barbus sp. (viviparous?)
Labeobarbus marequensis
Labeo altivelis
Labeo congoro
Labeo cylindricus
Labeo rosae
Mesobola brevianalis
Glossogobius giuris
Gambusia affinis
Poecilia reticulata
Marcusensis macrolepidotus
Petrocephalus catastoma
Cyphomyrus discorhynchus
Anguilla bicolor
Anguilla mossambica
Schilbe intermedius
Synodontis zambezensis
Common name
Silver robber
Tigerfish
Imberi
Bass
Eastern bream
Greenhead tilapia
Tilapia
Tilapia
Black tilapia
Southern mouthbrooder
Happy
Redbreast tilapia
Nembwe
African catfish/barbel
Hamilton’s barb
Straightfin barb
East coast barb
Three-spot barb
Beira barb
Occurrence
indigenous
indigenous
indigenous
exotic
indigenous
introduced
indigenous
exotic
indigenous
indigenous
introduced
indigenous
introduced
indigenous
indigenous
indigenous
indigenous
indigenous
indigenous
Largescale yellowfish
Manyame labeo
Purple labeo
Redeye labeo
Red-nosed labeo
River sardine
Tank goby
Mosquito fish
Guppy
Zambezi bulldog
North Churchill
Zambesi parrotfish
African mottled eel
African long fin eel
Silver catfish
Plain squeaker
indigenous
indigenous
indigenous
indigenous
indigenous
indigenous
indigenous
exotic
exotic
indigenous
indigenous
indigenous
native
indigenous
indigenous
indigenous
Locality
C, S
M, S
S, R
C, M
R
M, S
C, M, R, Sw, IC, S
C, Sw, S
M, S
C, Sw, IC, S, R
C, S, R
C, R, Sw, IC, S
IC
C, R, Sw, IC, S
C, M, S
Sw, IC
Sw, IC, S, R
Sw, IC, S
S
S
C, Sw, S
M, S, R*
S
C, R
S
C, R, S
C, M, R, S
Sw, IC
C, Sw, IC
S, R
S
S
C, R
S
S
S
150
DISCUSSION
A total of eight species belonging to five families; Cichlidae (Oreochromis macrochir,
Oreochromis mossambicus, Oreochromis placidus and Tilapia rendalli), Gobiidae (Glossogobius
giuris), Cyprinidae (Labeo altivelis), Characidae (Hydrocynus vittatus) and Clariidae (Clarias
gariepinus) were recorded in Malilangwe reservoir. A regional survey found a total of 24 species
belonging to 8 families; Cichlidae, Poecilidae, Alestidae, Cyprinidae, Centrarchidae, Clariidae,
Gobiidae and Anguillidae (Table 3). Barson et al. (2008) recorded six of the eight species caught
during reservoir survey; C. gariepinus, H. vittatus, T. rendalli, L. altivelis, O. mossambicus and O.
placidus during the fish parasite surveys in the reservoir while a regional survey recorded a total
of 6 species; O. macrochir, H. vittatus, M. salmoides, L. altivelis, O. mossambicus and O.
placidus. The number of species recorded for the reservoir is almost the same as 7 species that
were recorded by Nhiwatiwa (2004) in a study in two small water reservoirs in the Manyame
catchment.
A total of 10 species are known to have been introduced in the lowveld region; H.
vittatus, Micropterus salmoides, O. macrochir, O. placidus, L. altivelis, G. giuris, Gambusia
affinis, Poecilia reticulata, Pharyngochromis acuticeps and Serranochromis robustus with the
first six species have been introduced in the Malilangwe reservoir (Barson and Nhiwatiwa 2010,
Marshall 2010). The introduced species have been very successful and are now widespread
with the exception of Micropterus salmoides. Micropterus salmoides (bass) which was
introduced in the year 2000 for the angling purposes is now rare and could be possibly extinct
in the reservoir. Anglers have not caught the bass (M. salmoides) in the reservoir since
November 2009 (Philemon Chivambu, Personal communication). According to Marshall (2010),
the presence of large numbers and abundance of the large goby (G. giurus) species which feeds
mainly on fish, aquatic insects and other small animals may have affected the breeding and
recruitment of bass. Two species found in the reservoir can be considered to be local species
which are common in the Save-Runde system (Marshall 2010).
Malilangwe reservoir ideally should release water into the Chiredzi River in compliance
with ecological flow requirement but that is currently not the case. This has led to differences in
the number of species between the Chiredzi River and reservoir observed as noted by Barson
151
and Nhiwatiwa (2010) who recorded a total of 13 species belonging to 8 families in the Chiredzi
River. The complete isolation of fishes in the Malilangwe reservoir has led to differences in the
species observed as both fish groups never mix except during times of extreme floods such as in
the year 2000 (Cyclone Eline) when the reservoir spilled. The Malilangwe reservoir is acting as a
barrier for the migration of fishes upstream of the Nyamasikana River from the Chiredzi River.
The fish fauna of Malilangwe reservoir is that Nyamasikana River is one of the smaller
tributaries of the Chiredzi River and is a seasonal river and when the river was dammed, it is
most likely it was during the dry season hence a few species were confined upstream in few dry
season pools.
It is therefore likely that an extinction of less abundant resident fish species of
Nyamasikana River may have occurred with the introduction of predatory species in the
reservoir such as Mesobola brevianalis, Anguilla bicolor and Pharyngochromis acuticeps have
completely disappeared. However, the barrier represented by the dam has also been beneficial
in preventing some introduced fish species in lowveld rivers such as Oreochromis niloticus, from
entering the Malilangwe Reservoir.
In Zimbabwe O. macrochir occurs naturally in the Zambezi River above Victoria Falls but
has been widely translocated into many parts of the country and was especially imported in
Lake Chivero, Manyame River system and Lake Mutirikwi (Marshall 2010). The appearance of O.
macrochir way outside its home range in the Malilangwe reservoir could have been due fish
introductions. In most cases fish introductions are done using juveniles but the taxonomy of
juvenile tilapia is difficult and this has become a common way of introducing exotic species.
Oreochromis placidus observed and collected in Malilangwe reservoir in great abundance but
none were recorded in the Chiredzi and Runde Rivers, Hippo Valley swamp and irrigation
channels. The absence of the species in nearby water bodies is perhaps evidence that after its
introduction into Malilangwe reservoir it has not escaped into the river region above Chipinda
Pools. Oreochromis placidus occurs in the Lower Save-Runde River system, one of its natural
habitats (Barson et al. 2009, Marshall 2010). The absence of Labeo altivelis and Hydrocyanus
vittatus from nearby water bodies after extensive surveys can also be due their confinement to
Malilangwe.
152
There is no pre-impoundment data for Malilangwe reservoir but it is likely that most of
the indigenous fishes species (14 species), used to thrive in the Nyamasikana River. Forty-seven
years after impoundment, most of the fish species are no longer being found in the reservoir
with the exception of only C. gariepinus and O. mossambicus. Mesobola brevianalis, a river
sardine reported to be present by O’Connor (2007) and Marshall (2010) appears to have
completely disappeared from the reservoir and to date there are no catch records or
observations for the species. Tilapia rendalli is now very rare and is rarely caught as the results
of this study confirmed. The decline in species richness after dam construction is not new in the
history of reservoirs in Zimbabwe. In a recent study, Zengeya and Marshall (2008) noted that
prior to impoundment of Lake Kariba, the middle Zambezi River had 31 fish species but 7
species are now very rare or have gone extinct while at least 5 species were introduced.
High abundances of L. altivelis (38.34%) were caught in the inshore areas characterized
by rocky substrates of Malilangwe reservoir and less in open waters. According to the biology of
this species, they scrap periphyton from rock surfaces and therefore this section of the
reservoir is their ideal habitat (Marshall 2010). This observed scenario in Malilangwe reservoir
where labeo fishes were dominant in the inshore areas is in direct contradiction to observations
made by Begg (1974) who reported that labeo species were generally sparse in the inshore
areas of the Lake Kariba, making up 0.11 - 0.17% of the total numbers and less than 1% of the
biomass. High water level drops especially in times of drought can result in a drop or decrease
of labeo species populations as a result of failure to spawn as the species are potamodromous
and they move up swollen rivers to spawn (Marshall 2010). Marshall (1978) reported that in
Lake Chivero, severe droughts of 1967 – 1968 resulted in decline of the labeo species from 12%
to 1% in 1971 due to failure to spawn but population recovered rapidly making up 23% of total
catch between 1972 and 1977 after heavy rains.
All the three fishing gears had different fish species richness, gillnets (species richness =
8), fyke nets (sp. richness = 7) and seine net (sp. richness = 5). These differences in sampling
gear and effort were at least partly responsible for differences in the numbers of species
recorded during the different sampling periods. Changes in species assemblages may also be a
reflection of patio-temporal changes in habitat in response to factors such as water level
153
fluctuations. There was a decline of macrophytes density and composition in the reservoir
during the cool- and hot-dry seasons as a result of drawdown and with a healthy predator
population (H. vittatus) in the reservoir, this can have catastrophic effects. When most of the
macrophyte cover was severely reduced from the reservoir due to drawdown, forage fish such
as T. rendalli and small fish juveniles lost their refuge and were subjected to intensive
predation. The decline in macrophyte cover could have coincided with the migration of most of
the tigerfish adults and juveniles back into reservoir from breeding sites up the Nyamasikana
River and this resulted in large population declines of other fish juveniles in the reservoir. The
decline in tigerfish catches observed in July can be attributed to change in gillnet mesh size to
only 100, 128, and 140 mm so as to conserve the tigerfish populations for sport fishing.
The reproductive status of fish species in Malilangwe reservoir was low during the
winter months (cool-dry season) as they time their breeding to coincide with rains and the river
floods. This is true for most of the observed species such as H. vittatus, C. gariepinus, L. altivelis,
O. mossambicus, T. rendalli and O. macrochir (Skelton 2001, Marshall 2010). Reproduction and
breeding of most in the reservoir seems to start in September in anticipation of the summer
rains. Since most fish tend to coincide their breeding or reproduction with the onset rains so
that the juveniles can have plenty of food and protection. Oreochromis placidus was found to
breed throughout the three seasons with peak reproduction in June (Figure 5). No studies have
been carried out on the breeding of O. placidus in Zimbabwe (Marshall 2010) and this study is
the first observation on the breeding behaviour for the species. It also appears that breeding
outside the peak period common for tilapias (October - February) and there was no clear
explanation for this.
The 2-3 size cohorts being observed (Figure 3 - 4), suggests there is regular recruitment
and utilisation of the system. Schools of juvenile fishes which were observed during the hot-wet
season decreased with decline in macrophyte cover as they were left exposed to predators. It is
possible that a great number of fish breed during the hot-wet season period (November –
February). Predation of juvenile fishes in the reservoir was presumed to be almost 100% from
observations made around the littoral zones in cool- and hot-dry seasons. Mulonga (2004)
suggested this could be due to heavy predation pressure on juveniles or parasite (Lernaea
154
cyprinacea) induced mortalities as the reason for declines but most fish species are well
adapted to high predation levels and therefore fish populations were unlikely to collapse. Lake
Chivero showed a broad relationship between the relative abundance of tiger fish, T. rendalli
and O. macrochir, when the tiger fish catch was low that of the cichlids was high and vice-versa
(Marshall 2010).
The case study of Malilangwe reservoir has provided new insights into the fish
communities of small reservoirs and especially one with an unusual hydrological regime i.e. it
does not spill and has not spilled in more than 10 years. The prevailing population has been
shaped by community interactions and human interventions such as fish introductions. It will
be interesting for future assessments to be done to investigate how this closed community
continues to evolve. This study is very important because it provides an important benchmark
for future studies.
155
IMPACT OF LERNAEA CYPRINACEA LINNAEUS 1758 (CRUSTACEA: COPEPODA) ALMOST A
DECADE AFTER AN INITIAL PARASITIC OUTBREAK IN FISHES OF MALILANGWE RESERVOIR,
ZIMBABWE
156
INTRODUCTION
Fish parasites are very common throughout the world and are of particular importance in the
tropics (Moyo et al. 2009). Parasites affect fish health, growth and survival (Barson and
Marshall 2003). Lernaea cyprinacea Linnaeus 1758 (Crustacea: Copepoda), commonly known as
‘anchor worm” is an important crustacean parasite of freshwater fish that has a wide
geographic range (Silva-Souza et al. 2000, Nagasawa et al. 2007).
Lernaea species have nine stages in the life cycle including three free living naupliar
stages, five copepodid stages and one adult stage. After mating on the fish host, the males die
and females metamorphose and insert their anterior body into the host tissue and then
produce eggs (Mulonga 2007, Nagasawa et al. 2007). Anchor worm infections usually result in a
single parasite per host fish in flowing rivers and streams causing a little damage but in closed
environments severe infestations often result (Demaree 1967).
The complex life cycles that parasites possess makes them extremely valuable
information units on aquatic environmental conditions since their presence or absence tells us
a great deal about not only their host ecology but also food web interactions, biodiversity and
environmental stress (Madanire-Moyo and Barson 2010). Combining different species based on
shared patterns of transmission provides a potentially more powerful indicator of prevailing
environmental conditions (Moyo et al. 2009, Madanire-Moyo and Barson 2010).
Knowledge on the fish parasites in Zimbabwe is limited to studies that were done in
Lake Kariba (Chishawa 1991, Douellou 1992), in the upper Manyame catchment including Lake
Chivero (Barson and Marshall 2003, Barson 2004, Madanire-Moyo and Barson 2010, Taruvinga
2011) and the south-eastern lowveld rivers (Barson et al. 2008a). No meaningful work has been
done on fish parasites in small dams except work carried out by Barson et al (2008b) in
Malilangwe Reservoir, Moyo et al. (2009) in Insukamini Dam and Taruvinga (2011) in Harava
and Seke Dams.
In 2002, a parasitic infestation of L. cyprinacea was observed on several Oreochromis
species in Malilangwe Dam (Bruce Clegg, personal observation). This parasite being a one-host
parasite had to be introduced either via infected fish from the surrounding Runde catchment or
from human introductions of infested fish. At the time water levels in the dam were very high
157
following the tropical cyclone Eline in 2000, and it is possible that the prevailing flood
conditions could have brought the infested individuals into the otherwise isolated Malilangwe
Dam. Subsequent investigation by Barson et al. (2008b) revealed that the parasite had affected
almost 100% of the population of concerned species, with little or no apparent seasonal
variation, somehow suggesting that the parasite was trapped in a more or less isolated system.
The purpose of this study was to assess the current status of L. cyprinacea infestation,
about nine years following its initial appearance on fishes of the Malilangwe reservoir. We also
aimed to investigate its distribution within the different seasons and assess the general
prevalence and intensity of fish parasitism within the reservoir.
Study area
Malilangwe Wildlife Reserve is located in the Chiredzi District of the south-eastern lowveld of
Zimbabwe (20°58’ 21°02’ S, 31°47’ 32°01’ E) (Figure 1). It arises from an impounded river
formed in 1964 and is used for water supply in the reserve. It is situated on the Nyamasikana
River, a tributary of the Chiredzi River which in turn flows into the Runde River. It is a gravity
section masonry dam with a surface area of 211 hectares with maximum volume of 1.2 x 107 m3
at full capacity. Flanked by rocky hills on most of its sides, the impoundment has a rocky
substrate with few sandy bays. It is poorly vegetated with few marginal plants including Azolla
filiculoides (Lam), Ludwigia stolonifera (Guill and Perr) Raven, Panicum repens (Lam),
Schoenoplectus corymbosus (Roth ex Roem and Schult) Raynal, Potamogeton sp. and sedges
(Phragmites mauritianus (Kunth) and Cyperus sp.). The fish communities include predators,
omnivores, detritivores, micro and macrophages (Barson et al. 2008b).
METHODS
Fish surveys
Sampling was carried out monthly for 9 months (February – October 2011). The sampling
program was done using three types of fishing gear: fyke nets, seine net and gill nets. Fyke nets
were used in the shallow parts (<1 m) while gill nets were set in the deeper sections (>1.5 m) of
the dam. Three double fyke nets with a stretched mesh size of 24 mm connected by a 12.5 m
158
long net giving a total length of 18 m were set overnight at randomly selected sites. A fleet of
nylon multifilament gill nets with stretched meshes of 12, 20, 30, 40, 50, 72, 100, 128, and 140
mm were used in February and March 2011 and cotton multifilament nets stretched meshes of
7, 12, 20, 30, 40, 50, 60 and 72 mm were used throughout the sampling period and all nets
were set overnight for 12 – 14 hrs. A Seine net with mesh size of 18 mm was also used only in
June 2011. Gill nets were used more extensively compared to the other fishing gears. Fish were
identified using Skelton (2001) and Marshall (2010). Fish standard length were measured to the
nearest cm and weighted in kgs.
Figure 1. Location of littoral zone sampling sites around Malilangwe Reservoir (shaded area).
A method used by Barson et al. (2008b) was used for L. cyprinacea parasite
identification. The external body surfaces as well as the gill chamber and mouth cavities of each
fish were examined for the presence of adult female L. cyprinacea. Fish intensity was
determined by counting the number of adult female L. cyprinacea with cutaneous lesions about
159
4mm in diameter were included. The lesions were assumed to be sites of L. cyprinacea
attachment as parasites are sometimes dislodged during fish handling.
meter (HACH, LDO, Germany). Water transparency was measured using a Secchi disk. Chemical
oxygen demand (COD), Nitrogen, nitrates, total and reactive phosphorus were determined
using standards methods from EPA, Hach and Standard Methods. A Kruskall Wallis ANOVA test
(p < 0.05) was carried out to test the differences in physicochemical characteristics between
sampling stations (H0: no difference between five sampling points). The analysis was done for
the whole study period, February – October 2011 using SysStat ver. 12.
RESULTS
Table 1 summarizes the mean values of environmental variables in the Malilangwe reservoir for
study period. Dissolved oxygen (DO) values were low during February – March, increased
between May to August before dropping in September – October. Well oxygenated water was
found throughout the cool-dry season (7 – 9 mg l-1). Low DO levels of up 2 mg l-1 were recorded
during the February – March and September – October. Lowest water temperature occurred
from May to September after which there was rapid increase. Temperature decreased through
the three seasons (hot-wet – cool-dry). Temperatures averaged 26.65oC in February before
decreasing to a low of 19.27oC in June. Temperatures then increased from June to September
(27.6oC). Highest temperatures were recorded in October (28.40 oC) and lowest in June (18.80
o
C). Secchi disk readings ranged between 0.2 – 1.7 m (Table 1).
Ammonia and Nitrogen were shown to decrease during the coo-dry season especially during
May – July. Low levels of Total Nitrogen (TN = 0.68 mg l-1) were recorded during June.
Ammonia values were high for February and March (0.17 mg l-1 and 0.40 mg l-1) while in August
and October recorded high values (0.11 mg l-1 and 0.26 mg l-1). Low values of ammonia were
160
observed during the hot-wet season. Nitrate was low during the hot-wet season with low
values being observed in July (0 mg l-1) but increased from August (0.01 mg l-1) to October (0.03
mg l-1). Nitrate was high in February (0.5 mg l-1), March (0.07 mg l-1) and June (0.04 mg l-1).
Alkalinity showed slight seasonal changes and it fluctuated between 15 and 22 mg l-1 for the
study months. Total dissolved solute (TDS) was high during April – July (270 – 360 mg l-1). There
was an increase in conductivity from March (191.6 μS cm-1) to September (383.15 μS cm-1)
(Table 1).
Parasite prevalence and intensity
Eight fish species; Oreochromis macrochir, Oreochromis mossambicus, Oreochromis placidus,
Tilapia rendalli, Glossogobius giuris, Labeo altivelis, Hydrocynus vittatus and Clarias gariepinus
caught in the Malilangwe reservoir were examined for parasites (Table 2). All the four cichlids
and one cyprinid (L. altivelis) were infected with Lernaea cyprinacea and had different parasite
intensities across the months (Table 2). The parasite prevalence was low in Tilapia rendalli
(small sample size, n = 4) and Labeo altivelis but much higher in the other three cichlids (O.
macrochir, O. mossambicus and O. placidus). Parasite prevalence was 100 % throughout the
nine study months amongst the cichlids whilst it varied across the study months for cyprinidae
(Table 2). Parasite intensity differed greatly amongst host species with the Oreochromis sp.
being the most infected. Parasite intensity increased during the winter period (May – July) as
algal blooms formed in the reservoir (Table 2). Eight individuals of catfish, C. gariepinus were
found to be heavily infected with trematode cysts (Clinostomoides brieni) in the skin during the
hot-wet (sp. = 7) and early months of the cool-dry season (sp. = 2). No further catfish species
were observed that infected by the cysts. No infections were found in the tigerfish (H. vittatus)
and the goby (G. giuris).
A Pearson correlation of physicochemical variables with parasite intensity showed that
parasite intensity was significantly correlated to dissolved oxygen, temperature and pH.
Parasite intensity was significantly and negatively correlated to temperature whilst significantly
and positively correlated to dissolved oxygen and pH (Table 3).
161
Table 1. Descriptive statistics of the measured environmental variables in Malilangwe reservoir (April - October 2011)
Dissolved Oxygen
Temperature
Conductivity
pH
Total dissolved solutes
Reactive phosphorus
Nitrogen
Ammonia
Nitrate
Chemical oxygen demand
Total phosphorus
Secchi depth
Alkalinity
-1
mg l
o
C
μS cm
mg l-1
-1
mg l
-1
mg l
-1
mg l
-1
mg l
-1
mg l
-1
mg l
m
-1
mg l
-1
Feb
Mean
6.6
29.7
333.0
7.8
300.6
0.3
0.7
-0.2
0.1
30.1
0.6
1.1
-
SD
1.2
0.9
14.1
0.3
12.1
0.1
0.8
0.4
0.2
8.9
0.2
0.1
-
Mar
Mean
5.0
30.1
191.6
7.9
235
0.3
1.7
0.4
-0.02
27.6
0.8
1.0
17.0
SD
0.8
0.8
11.2
0.2
3.7
0.2
1.0
0.2
0.1
12.4
0.4
0.3
1.2
Apr
Mean
7.8
26.9
358
7.9
344.9
0.1
0.8
0.1
0.1
56.8
0.01
1.1
18.7
SD
0.3
0.7
6.2
0.3
1.8
0.1
0.6
0.05
0.01
15.3
0.1
0.5
0.8
May
Mean SD
7.0 0.3
24.4 0.1
358.3 3.4
7.9 0.1
278.4 1.9
0.2 0.1
1.1 1.0
0.2 0.2
0.03 0.02
26.1 4.0
0.2 0.05
1.6 0.4
18.6 1.5
Jun
Mean
7.9
21.6
367
8.6
284.7
0.6
0.7
0.03
0.03
19.5
1.4
1.0
18.6
SD
0.3
0.3
1.3
0.2
0.8
0.1
0.5
0.02
0.01
1.2
0.3
0.3
1.4
Jul
Mean
8.5
19.3
376
8.9
292.2
0.1
1.0
0.1
0.00
27
0.1
1.2
18.1
Aug
SD Mean
0.5 5.6
0.5 20.9
2.2 338.4
0.1 7.5
1.6 226.7
0.02 0.1
0.9 0.4
0.1 0.1
0.002 0.01
21.4 86.6
0.0 0.3
0.5 1.3
1.3 17.8
SD
0.4
2.1
22.5
0.4
8.0
0.03
0.1
0.03
0.0
20.8
0.1
0.2
2.0
Sep
Oct
Mean SD Mean SD
5.6 1.0 5.3 1.1
22.5 2.1 27.6 0.8
360.3 34.1 433.3 5.9
7.8 0.7 7.5 0.3
228.1 19.8 252.6 1.0
0.7 0.3 0.8 0.1
0.9 1.2 1.2 1.1
0.002 0.04 0.1 0.1
0.02 0.01 0.02 0.01
35.1 14.8 25.2 23.9
2.5 1.5 1.9 0.2
1.1 0.1 0.7 0.3
19.1 1.5 19.4 1.6
162
Table 2. Prevalence and intensity of Lernaea cyprinacea in susceptible fish species present in
Malilangwe reservoir.
Species present
N
Prevalence (%)
Labeo altivelis
Labeo altivelis
Tilapia rendalli
Labeo altivelis
Labeo altivelis
Labeo altivelis
Labeo altivelis
Labeo altivelis
Labeo altivelis
Tilapia rendalli
Labeo altivelis
Tilapia rendalli
15
4
13
32
98
16
27
1
95
22
28
35
116
30
55
37
112
50
27
47
91
49
27
50
82
25
24
34
93
29
37
37
2
127
26
41
30
1
26.67
100.00
100.00
100.00
17.35
100.00
100.00
100.00
32.63
100.00
100.00
100.00
38.79
100.00
100.00
100.00
45.54
100.00
100.00
100.00
34.07
100.00
100.00
100.00
24.39
100.00
100.00
100.00
17.02
100.00
100.00
100.00
100.00
20.31
100.00
100.00
100.00
100.00
Intensity
mean
range
3
1-5
21
12 - 31
20
2 - 41
16
3 - 40
7
1 - 16
26
5 - 44
25
9 - 62
8
8
12
2 - 31
33
18 - 64
32
9 - 59
28
5 - 61
34
7 -89
42
2 - 88
42
5 - 91
40
8 - 90
37
3 - 89
78
4 - 153
71
10 - 152
74
9 - 158
30
12 - 71
75
19 - 175
69
10 -153
78
18 -192
16
3 - 21
31
5 - 82
29
9 - 78
40
8 - 101
16
3 - 21
22
2 - 56
27
8 - 78
26
8 - 67
5
2-8
12
3 - 31
29
9 - 67
30
9 - 56
20
5 - 36
13
13
Month
February
March
April
May
June
July
August
September
October
163
Table 3. Pearson correlation coefficients and significance levels between the
physicochemical variables and parasite intensity (* = P < 0.05, ** = P < 0.001).
Parameter
Dissolved Oxygen
Temperature
Conductivity
pH
Total Dissolved Solutes
Nitrogen
Ammonia
Nitrate
Chemical Oxygen Demand
Total Phosphorus
Secchi Depth Transparency
Correlation Coefficient
0.727*
-0.801**
0.262
0.683**
0.192
-0.237
-0.144
-0.378
-0.307
0.013
0.188
DISCUSSION
The presence of L. cyprinacea on some fish species (O. placidus, O. mossambiccus, O.
macrochir, L altivelis and T. rendalli) and not others (C. gariepinus, G. giuris and H. vittatus)
in Malilangwe reservoir suggest that L. cyprinacea is host-specific. Whitaker & Schlueter
(1975) and Barson et al. (2008b) suggested that the differences in susceptibility of fish
species to the parasite could be due to differences in ecological, behavioural, physiological
mechanisms and morphological variations. Some fish species such as the scale-less C.
gariepinus might produce hormones or secrete mucous which might be make them
unacceptable to the copepod or make them immune. The structure and arrangement of
scales in some fish species such as H. vittatus might not allow for easy implantation of the
parasite’s anchor as they are tightly packed.
The most abundant fish species Labeo altivelis was found to have the lowest rates of
Lernaea infestation. Whitaker and Schlueter (1975) suggested that abundant species seem
to have had more opportunity to evolve such defence mechanism devices, particularly if
they had been abundant over rather long periods of time. Such mechanisms would seem
more likely to have evolved if the parasite tended to cause severe harm to the host. Clarias
gariepinus and Labeo altivelis which are associated with muddy habitats were found to be
the least infected species. These findings are in contradiction with Demaree (1967) who
164
reported that fish collected from muddy water and muddy bottom were most frequently
infected with L. cyprinacea.
In our study, the copepod parasite infection in O. placidus was very high during the
cool-dry season and when most of the reservoir was covered in algal blooms. The high
parasite infection in the smaller cichlid of the four species found in Malilangwe is supported
by Amin et al. (1973) who found that smaller host fish to be more heavily infested. Whitaker
& Schlueter (1975) and Barson et al. (2008b) found that higher parasite intensity in smaller,
younger fish could be that these fish are easily accessible to the parasite or that their
defence mechanisms are less well developed compared to larger, older fish. Smaller fish live
in the littoral zones of the reservoir as they seek refuge from predators in the macrophytes
and substrates but these warm littoral zone areas are also the preferred habitats of L.
cyprinacea as noted by Paperna (1996). Therefore chances of juvenile fish infection are very
high. Clarias gariepinus was found to be affected by trematode cysts (Clinostomoides)
during the hot-wet and cool-dry season. The cysts covered the whole fish body and also
changed the skin colour of fish to a light grey. The number cysts per host were higher during
the rainy season which may suggest a link with climatic and environmental factors.
Water quality in the Malilangwe reservoir could be contributing to the high parasite
prevalence observed in the fishes. Malilangwe reservoir has not overflowed in the last 12
years since Cyclone Eline of 2000 and the reservoir only outflows when it is at full capacity
thus the biota is essentially isolated. The pH was very highly positively correlated to parasite
intensity (p < 0.001, r = 0.727) while temperature was very highly negatively correlated to
parasite intensity (p < 0.001, r = -0.801). Barson et al. (2008b) showed that high water
temperatures contributed to fast development of the copepod parasite but our study seem
to suggest otherwise, during the cool-dry season, parasite intensity increased with mean
temperatures of 19°C suggesting that temperature only is not a major factor in the increase
of parasite intensity. The temperature and water level fluctuations observed in Malilangwe
reservoir during the cool-dry season could have contributed to the increased infestation by
L. cyprinacea in the reservoir. The studies by Kupferberg et al. (2009) and Idris and Amba
(2011) demonstrated the influence of climatic factors on parasite outbreaks. The outbreak
of L. cyprinacea in the SF Eel was associated with periods of warm water temperatures,
declining discharge and shrinking pool sizes, conditions which are typical for infestations on
165
fish in other rivers (Kupferberg et al. (2009). Idris and Amba (2011) showed that
temperature fluctuations during monsoon season may contribute to parasitic outbreaks.
Dissolved oxygen was significantly correlated to parasite intensity and DO levels increased
during the turn-over period (complete mixing of the water body). Increases in DO levels
coincided with an increase in parasite intensity and high levels of DO content in the water
are considered desirable for the proliferation of L. cyprinacea (Mulonga 2007). In addition to
the fluctuating environmental factors, host densities (fish populations) were high in the cool
dry season as most fish species were coming out of the breeding season in Malilangwe
reservoir.
The continuous spread of L. cyprinacea in the reservoir has potential adverse
implications on fish biodiversity and has the potential to wipe out host populations resulting
in loss of biodiversity and causing an imbalance to the ecosystem. The effect of the parasite
on fish populations can then cascade to other biota. More studies on host parasites need to
be investigated as shown by Kupferberg et al. (2009) that L. cyprinacea can have devastating
impacts on amphibian populations. A major flood like the one experienced in 2000 (Cyclone
Eline) is required to help flush out the reservoir and reduce the L. cyprinacea infestations.
The parasite is showing no sign of declining. Although the infected fish are generally
considered safe to eat (Mulonga 2007), heavily infested ones are unsightly for anglers who
patronise the dam as a touristic and recreational activity.
166
LENGTH-WEIGHT RELATIONSHIPS AND CONDITION FACTOR OF 8 FISH SPECIES CAUGHT
USING GILL NETS IN A TROPICAL AFRICAN RESERVOIR, ZIMBABWE
Tatenda Dalu, Bruce Clegg and Tamuka Nhiwatiwa. 2012. Length-weight relationships of 8 fish
species caught using gillnets in a tropical African reservoir, Zimbabwe. Pan-American Journal of
Aquatic Sciences. Submitted for publication.
167
INTRODUCTION
Length–weight relationships are an important tool in fish biology, physiology, and ecological
assessment because they can be used to compare growth in different environments (Cherif
et al. 2008, Kumolu-Johnson and Ndimele 2010). In the application of the length-weight
relationship to define a population, fish length is measured and predicted average weight is
assigned to all fish in a given length group (Oscoz et al. 2004, Shakir et al. 2008). This is often
faster and more convenient than weighing fish individually, especially when large numbers
of live fish are sampled.
Knowledge of the relationship between length and weight of a fish species in a given
geographic region is useful for at least three reasons (Petrakis and Stergiou 1995, Can et al.
2002, Cherif et al. 2008, Ak et al. 2009, Laghari et al. 2009, Kumolu-Johnson and Ndimele
2010, Awong et al. 2011);
1. Estimation of weight at age from total reported catch weight and length-frequency
distributions and use in stock assessment models.
2. As a practical index of the condition of fish. Length-weight relationships are used to
compute the departure from the expected weight for length of the individual or a
group fish of fishes as indications of fatness or degree of wellbeing of fish known as
the condition factor (Ayoade and Ikulala 2007, Shakir et al. 2008, Kumolu-Johnson
and Ndimele 2010). It is based on the hypothesis that heavier fish of a particular
length are in a better physiological condition (Kumolu-Johnson and Ndimele 2010).
3. Life history and morphological comparisons of populations. It is also a useful index
for monitoring of feeding intensity, age, and growth rates in fish. It is strongly
influenced by both biotic and abiotic environmental conditions and can be used as
an index to assess the status of the aquatic ecosystem in which fish live and for
further purposes of new stocking (Shakir et al. 2008, Kumolu-Johnson and Ndimele
2010).
Length–weight relationships are only known for a restricted number of species, which
hampers efforts to model aquatic ecosystems where observations are typically obtained as
the number of specimens by length class that have to be transformed into estimates of the
biomass. The length-weight relationships are very important for proper exploitation and
management of the fish species populations (Kumolu-Johnson and Ndimele 2010, Awong et
168
al. 2011). Length-weight relationships and condition factors have been used in fisheries
research since the beginning of the 20th century and appear simple enough, yet there has
been ongoing confusion about their correct interpretation and application (Froese 2006).
Length and weight data are useful standard results of fish sampling programs and in fish,
size is generally more biologically relevant than age, mainly because several ecological and
physiological factors are more size-dependent than age-dependent. Consequently,
variability in size has important implications for diverse aspects of fisheries science and
population dynamics (Kalaycı et al. 2007).
Most studies on length-weight relationships in Zimbabwe have been done for large
water bodies such as Lake Chivero (Minshull 1978, Clay 1984), Mturikwe (Clay 1984) and
Kariba (Kolding et al. 1992, Torres 1992) whilst a few have been done for small water bodies
(Nhiwatiwa 2004). Information about the length-weight relationships and condition factors
of fish species in small reservoirs is very limited. This study was initiated to fill this gap in
information and also provide useful information for fish management and conservation in
Malilangwe reservoir. It will also allow for future comparisons between populations of the
same species. The parameters of the length-weight relationships are reported for 8 fish
species caught in the Malilangwe reservoir, south-eastern, Zimbabwe using gill nets of
various mesh sizes.
METHODS
Fish data were collected during the monthly surveys (March - October 2011) using gill nets
at Malilangwe reservoir in the south-eastern lowveld of Zimbabwe (Figure 1). From the fresh
samples, standard length (SL) and body weight (W) were measured to the nearest 0.1 cm
and 0. 1 g. The length-weight relationships were estimated from the allometric formula:
W = aLb
And this expression can be transformed logarithmically; log W = log a + b log L. Where W is
weight, L = total length, a = constant and parameter b is the exponent of the arithmetic
form of the weight–length relationship and the slope of the regression line in the
logarithmic form. If b = 3 the fish grows isometrically, then small fish in the sample under
consideration have the same form and condition as large fish. If b > 3, the fish shows
positive allometric growth, then large fish have increased in height or width more than in
169
length, either as the result of a notable ontogenetic change in body shape with size, which is
rare or most large fish in the sample were thicker than small fish, which is common.
Conversely, if b < 3 the fish shows negative allometric growth, then large fish have changed
their body shape to become more elongated or small fish were in better nutritional
condition at the time of sampling (Abdallah 2002, Wigley et al. 2003, Froese 2006, Shakir et
al. 2008).
A condition factor (K) was calculated using the formula (Froese 2006):
K = 100 x W x L-3
Figure 1. Location of the study area, Malilangwe Reservoir (shaded area), south-east
lowveld, Zimbabwe.
Statistical analysis
Prior to regression analysis of log W on log L, log-log plots of length and weight values were
performed for visual inspection of outliers (Froese, 2006). Only extreme outliers attributed
to data error were omitted from analyses. In order to confirm whether b values obtained in
the linear regressions were significantly different from the isometric value (b = 3), t-tests
with appropriate degrees of freedom were used. The comparison between obtained values
of t statistics and respective tabled critical values allowed for the determination of
170
(statistical significance) the b-values, and their inclusion in the isometric range (b = 3) or
allometric ranges (negative allometric b < 3 or positive allometric b > 3). Box-Whisker plots
were drawn using SysStat 12 for Windows version 12.02.00 (Systat 2007). T-test was applied
as expressed by the equation according to Sokal and Rohlf (1987):
ts = (b - 3) / SE
Where ts = t-test value, b = slope and SE = standard error of the slope b. All the statistical
analyses were considered at significance level of 5% (p < 0.05).
RESULTS
A total of 580 individuals representing 8 species from 5 families; Cichlidae (Oreochromis
macrochir Boulenger 1912, Oreochromis mossambicus Peters 1852, Oreochromis placidus
Trewavas 1941 and Tilapia rendalli Boulenger 1897), Gobiidae (Glossogobius giuris
Hamilton-Buchanan 1822), Cyprinidae (Labeo altivelis Peters 1852), Characidae (Hydrocynus
vittatus Castelnau 1861) and Clariidae (Clarias gariepinus Burchell 1822). Labeo altivelis was
the most abundant species (631 individuals) with T. rendalli and G. giuris having 7 and 4
individuals respectively. The descriptive statistics, estimated parameters of the lengthweight relationship species and growth type (allometric or isometric) are presented in Table
1 and Figure 3. Correlations were found to be higher than 0.5 showing that the length was
positively correlated to weight. The t-tests showed that all the fish species had negative
allometric growth except T. rendalli which had positive allometric growth. G. giuris, L.
altivelis, O. macrochir, O. mossambiccus and O. placidus had b values lower than 2, two
species (H. vittatus and C. gariepinus) had b values in the range of 2.5 – 3 and T. rendalli had
b value greater than 3 (Table 1).
The condition factor results for each species are shown in Table 1. High condition
factor value ranges were observed in O. mossambiccus (9.29), O. placidus (5.49) and O.
macrochir (5.30). On average, O. placidus (mean K = 3.41), O. macrochir (K = 3.11), G. giuris
(K = 3.09) and H. vittatus (K = 3.09) were found to be in slightly better condition than T.
rendalli (K = 1.05) and L. altivelis (K = 1.55). The temporal changes for the eight species are
shown in Figure 3. This shows that seasonal variation occurred in K factor of the eight fish
species and the highest mean K factor were recorded during the hot-wet season for L.
altivelis (mean K = 2.735), O. macrochir (K = 3.839), O. mossambiccus (K = 4.088), O. placidus
171
(K = 4.046) and T. rendalli (K = 4.441) while for H. vittatus (K = 2.687), G. giuris (K = 2.736)
and C. gariepinus (K = 1.266) were recorded during hot-dry season. Condition factor (K)
values during the hot-dry season were high before decreasing in April. K values increased
between May and August (cool-dry season), then decreased in September (hot-dry season)
before rising again in October (Figure 2).
The weight of the fish increased logarithmically with an increase in length and viceversa (Figure 4). The b values calculated showed that all fish were growing negatively
allometrically as shown in Figure 4. The values of b increased from 1.52 for G. giuris to 6.7
for T. rendalli (Figure 3, Table 1). The median value of b was 2.684, whereas 62.5% of the
values of b ranged between 1.52 and 2.684.
Figure 2. Changes in condition factor of 8 fish species in Malilangwe reservoir (February –
October 2011). Redlines indicate the different seasons; A – hot-wet, B – cool-dry
and C – hot-dry.
Figure 3. Box-Whiskers plots of the exponent b of the weight-length relationships (W=aLb)
for 8 species caught in the study area. The vertical line shows the median and the
horizontal line represents the range of the values.
172
Table 1. Descriptive statistics and estimated parameters of the length-weight relationship for 8 fish species from Malilangwe reservoir
(February – October 2011).
Species
N
Length characteristics
Mean Min Max SD (mean)
Parameters of the relationship
a
b
r
r2
T-test value
Type of
growth
K range
SD (K)
C. gariepinus
G. giuris
H. vittatus
L. altivelis
O. macrochir
O. mossambiccus
O. placidus
T. rendalli
53
4
78
131
92
96
119
7
59.9
7.3
34.6
36
30.4
31
27.5
24
0.02
0.46
0.03
0.30
2.34
1.86
1.06
0.00*
(-) allometric
(-) allometric
(-) allometric
(-) allometric
(-) allometric
(-) allometric
(-) allometric
(+) allometric
0.70 - 2.14
1.65 – 2.92
0.82 – 3.09
1.34 – 4.71
1.85 – 5.30
1.83 – 9.29
2.10 – 5.49
0.36 – 4.44
0.29
1
0.31
0.39
0.55
0.79
0.66
1.39
46
6
19
28
20.5
23.3
18
15
75
12
48
43
38
38
33
29
5.57
1.71
5.99
2.22
2.54
3.06
2.33
5.93
2.81
1.52
2.81
2.32
1.75
1.81
1.96
6.70
0.94
0.97
0.97
0.97
0.96
0.96
0.96
1.00
0.89
0.94
0.94
0.95
0.93
0.93
0.92
1.00
-0.57
-1.65
-0.23
-20.9
-7.94
-6.74
-13.93
1.57
* = 0.000000158, Min – minimum, max – maximum, SD – standard deviation, SE - standard error, N - sample size, a - intercept of the
relationship, b - slope of the relationship, r - coefficient of correlation, r2 – coefficient of determination, (-) - negative and (+) - positive.
173
The monthly obtained data for nine months was pooled and obtained the following
regression equation:
Log W = -1.651 + 2.806 Log L
Log W = -0.3404 + 1.521 Log L
Log W = -1.529 + 2.810 Log L
Log W = -0.529 + 2.321 Log L
Log W = 0.373 + 1.746 Log L
Log W = 0.570 + 1.598 Log L
Log W = 0.024 + 1.957 Log L
Log W = -6.797 + 6.698 Log L
r = 0.893
r = 0.943
r = 0.940
r = 0.951
r = 0.934
r = 0.931
r = 0.921
r = 0.996
C. gariepinus
G. giuris
H. vittatus
L. altivelis
O. macrochir
O. mossambiccus
O. placidus
T. rendalli
(Figure 4a – h).
DISCUSSION
In this study all the fish species showed allometric growth, that is, fish grew with weight
increasing at a slower rate (b < 3) compared to length. Three fish species; C. gariepinus
(2.81), T. rendalli (6.7) and H. vittatus (2.81) b values were within an ideal fish range of
between 2 and 4 (Saha et al. 2009, Ayoade and Ikulala 2007 and Bayhan et al. 2008) with
the rest of the species below b value less than 2. The b values obtained for C. gariepinus and
H. vittatus are different from those observed by Torres (1992) in Lake Kariba for C.
gariepinus (b = 3.013) and H. vittatus (b = 2.98) and Nhiwatiwa (2004) in two small
reservoirs who reported b = 2.75 and 2.99 of C. gariepinus.
The calculated coefficient of correlation (r) for length-weight relationship is high (r >
0.5) for all the eight species, more importantly it suggests that weight can be reasonably
accurately predicted from length. This is supported by several studies done on lengthweight relationships such as Ayoade and Ikulala (2007) studies on Hemichromis bimaculatus,
Sarotherodon melanotheron and Chromidotilapia guentheri in Lake Eleiyele, south-western
Nigeria and Shakir et al. (2008) studies on Sperata sarwari from Lake Mangla, Pakistan.
The length-weight relationship parameters (a and b) of the different fishes seem to
be affected by a series of factors such as season, gonad maturity, diet, health and
environmental parameters. Such differences in values b can be ascribed to one or a
combination of most of the factors including differences in the number of specimens
examined, season effects and distinctions in the observed length ranges of the specimens
caught, to which duration of sample collection can be added as well.
174
a
b
c
d
e
f
g
h
Figure 4. Length- weight relationship in (a) C. gariepinus (b) O. placidus (c) L. altivelis (d) O.
mossambicus (e) H. vittatus (f) O. macrochir (g) T. rendalli (h) G. giuris in Malilangwe
reservoir (February 2011 – October 2011).
175
The condition factor (K) reflects the physiological state of the fish in relation to its
welfare. From a nutritional point of view, there was the accumulation of fat and gonad
development from a reproductive point of view in the hot-wet season; this resulted in the
highest K values recorded in all fish species during the hot-wet season. The condition factors
(K) of the 8 fish species ranged between 0.36 - 9.29 and a closer examination of the
condition factors revealed that 4 fish species; C. gariepinus, L. altivelis, O. mossambiccus and
T. rendalli had their K values outside the 2.9 - 4.8 recommended range for matured
freshwater fish according to Bagenal and Tesch (1978). This could have been caused by
environmental factors as result of change of seasons. Froese (2006) reported that seasonal
variation of K value in plaice of the south-eastern North Sea could be related to better the
nutritional condition which resulted in higher K value and also that differences in K are
directly proportional to differences in weight.
The mean K for the eight fish species are greater than one, and this show that these
fish species are above average condition within the Malilangwe reservoir as according to
Bayhan (1992). The variation in mean K values (Figure 1) observed during different months
for the three species showed that very high K values were obtained for fish during the
breeding season (hot-wet season). Thus, K values are appearing to be related to the
breeding activities of the fish and also abundance of food reserves during the hot-wet
season. Condition factor has also been closely linked with reproductive cycle for fishes in
other water bodies as shown by Mortuza and Rahman (2006) studies on Rhinomugil corsula
from Rajshahi, Bangladesh, Saha et al. (2009) studies on Thenus Orientalis along East Coast
of India and Kumolu-Johnson and Ndimele (2010) studies on twenty-one fish species in
Ologe Lagoon, Nigeria.
In conclusion, the observed results for eight fish species presented in this study
contribute to the knowledge about the weight-length relationships of eight freshwater
fishes in small reservoirs and it will provide useful information for the fish management and
conservation in Malilangwe reservoir.
176
THE FEEDING HABITS OF AN INTRODUCED PISCIVORE, HYDROCYNUS VITTATUS
(CASTELNAU 1861) IN A SMALL TROPICAL AFRICAN RESERVOIR
177
Abstract
The diet of the tigerfish, Hydrocyanus vittatus (Castelnau 1861) from a small impoundment
(Malilangwe reservoir) was investigated. The tigerfish is an introduced piscivorous fish in
this reservoir. Stomach contents analysis indicated that the adult size classes were almost
entirely piscivorous and showed diet shifts with size changes. Approximately 35% of the
tigerfish diet consisted of cichlid fishes and also included large numbers of gobiidae (31%),
cyprinidae (29%) and clariidae (28%). Small size classes of tigerfish fed heavily on
macroinvertebrates, in particular, the taxa Pleidae (18%), Chironomidae (13%), Chaoborus
sp. (11.5%), Corixidae (7.7%), Baetidae (4%) and Notonectidae (7%). They later shifted to a
diet of cichlids. Hydrocyanus vittatus predator-prey length ratio averaged approximately
0.21. The study showed that H. vittatus has a varying food composition perhaps in response
to changes in food abundances and distributions within the reservoir.
Keywords: Hydrocynus vittatus, piscivorous, cichlid, macroinvertebrates, introduced
178
INTRODUCTION
The tigerfish, Hydrocynus vittatus is a common carnivorous species in Malilangwe reservoir
and is one of the most abundant species, constituting about 8.2% of the fish biomass
(unpublished data Dalu et al. 2011). For any fish species, its habitat as well as its feeding
habit influences growth, behaviour and other ecological characteristics (Ogbe et al. 2008).
The tigerfish Hydrocynus vittatus (Castelnau 1861) is a piscivorous fish and a pelagic
predator that is widely distributed in Zimbabwean inland waters (Marshall 2010). The
tigerfish is one of the most familiar and distinctive of fishes in Zimbabwe. It has a
streamlined, fusiform body and a large head with bony cheeks and strong jaws, each having
eight sharply-pointed, canine-like teeth that are visible even when the mouth is shut.
Tigerfish can grow to 70 cm fork length and 15 kg in weight, although such large specimens
are rare (Marshall 2010). Although widespread in Africa and still common in certain areas,
tigerfish have declined in many rivers due to pollution, water extraction and migration
barriers, such as weirs and dams (Skelton 2001). Tigerfish is also one of the most popular
angling species and was introduced into the Malilangwe reservoir for that sole purpose. This
species is a member of the Characidae, which is one of the largest families of freshwater
fishes found in Africa (Thorstad et al. 2002).
The introduction of Lates niloticus into Lake Victoria in the 1950s led to extinction of
hundreds of endemic haplochromine species (Ogari 1988, Warui and Arnason 2007). Lates
niloticus demonstrates a natural ontogenic change in diet but also has the capability of
adjusting its feeding habits to take advantage of the most abundant food source (Warui and
Arnason 2007). In southern Africa, concern has been expressed about the impacts of
introduced trout (Salmonidae) and bass (Centrarchidae) on indigenous fish populations with
South Africa having about 14 freshwater fish species believed to be threatened by exotics.
Largemouth bass Micropterus salmoides (Lacepede) and Serranochromis robustus
(Boulenger) were introduced into Zimbabwe in 1932 and early 1960s respectively and they
are now widespread throughout the country (Gratwicke and Marshall 2001, Marshall 2010).
These two species have caused a decline in Barbus sp. diversity and abundance in streams.
This is of great concern because this group of fluvial fishes is threatened throughout
179
southern Africa by dam-building, pollution and other factors (Gratwicke and Marshall 2001).
In Zimbabwe, the impact of these introduced predators is generally ignored or overlooked.
Little is known about the feeding ecology of introduced tigerfish in small lakes and
reservoirs with most studies having been done in large lakes such as Lake Kariba (Matthes
1968, Marshall 1987, Ogari 1988, Mhlanga 2003). This paper considers the food composition
of H. vittatus in Malilangwe reservoir in an attempt to determine how much dietary overlap
there was between different size-classes. It was hypothesised that the greatest overlap
would be amongst small individuals and the juveniles of adults because they were likely to
be feeding on the same resources, but the overlap would decrease amongst larger
individuals because of a tendency to specialise on certain food items (Zengeya and Marshall
2007).
Study area
of Zimbabwe (20°58’ 21°02’ S, 31°47’ 32°01’ E) (Figure 1). It arises from an impounded river
formed in 1964 and is used for water supply in the reserve. It is situated on the
Nyamasikana River, a tributary of the Chiredzi River which in turn flows into the Runde
volume of 1.2 x 107 m3 at full capacity. Flanked by rocky hills on most of its sides, the
marginal plants including Azolla filiculoides (Lam), Ludwigia stolonifera (Guill and Perr)
fish communities include predators, omnivores, detritivores, micro and macrophages
Mean annual rainfall collected for Malilangwe is approximately 562 mm, but is very
variable both within and between seasons. Temperatures are high with most daily maxima
in excess of 32 oC throughout the year and peak temperatures during hot spells in the
summer often over 45 oC. Winters are generally cool, with temperatures ranging from 5 oC –
26 oC with frost virtual absent (Davy, 2005, Traill 2006). The annual average evaporation has
180
been estimated at c. 2000 mm (Kelly and Walker 1976). Classification of the dam bottom
types undertaken by the simultaneous interpretation of the side scan sonar mosaic and
bathymetric data by Thackeray and Leuci (2008) showed ten major bottom types, as well as
numerous submerged trees and high relief boulders.
Figure 1. Location of littoral zone sampling sites around Malilangwe Reservoir (shaded area).
METHODS
Fish survey and analysis
Sampling was carried out monthly for 6 months (May – October 2011). The sampling
program was done using three types of fishing gear: fyke nets, seine net and gill nets. Fyke
nets were used in the shallow parts (<1 m) while gill nets were set in the deeper sections
(>1.5 m) of the dam. Three double fyke nets with a stretched mesh size of 24 mm connected
by a 12.5 m long net giving a total length of 18 m were set overnight at randomly selected
sites. A fleet of cotton multifilament nets stretched meshes of 7, 12, 20, 30, 40, 50, 60 and
72 mm were used throughout the sampling period and all nets were set overnight for 12 –
14 hrs. A Seine net with mesh size of 18 mm was also used only in June 2011. Gill nets were
used more extensively compared to the other fishing gears. Fish were identified using
181
Skelton (2001) and Marshall (2010). Fish standard lengths (SL) were measured to the
nearest centimetres (cm).
Fish stomachs were dissected out and preserved in 70% alcohol for 24 hrs to allow
fixation of tissues. The contents of each stomach were suspended in 100 ml of water per
gram of stomach contents and examined under an inverted microscope. Each item in the
diet was identified to the lowest possible taxonomic level and counted. The diet was first
determined by the frequency of occurrence method, which records the percentage of
stomachs containing a particular food item out of the total stomachs containing food
(Zengeya and Marshall 2007). The food items were then combined into broader taxonomic
categories for quantitative comparisons. The percentage of empty stomachs was
determined for tigerfish species for the study period.
In order to determine whether there was a change in food composition among the
different size groups, the fish were separated into several standard length (SL) size classes.
The dietary overlap between size classes for the tigerfish was calculated according to
Colwell and Futuyma (1971):
where Cih = overlap coefficient of length groups i and j, Pij = proportional occurrence of prey
type j in length group i and Phj = proportional occurrence of prey type j in length group h. For
the index, values may range near 0 (specialized diet or almost no overlap) to 1.0 (even use
of food resources or complete overlap)
RESULTS
A total of 155 tigerfish specimens were collected during the survey. The number of tigerfish
caught decreased from May (68 specimens) to September and October (3 specimens each).
Out of 155 stomachs examined, only 34 (21.9%) had food in the stomach. The trend for the
proportion of empty stomachs increased from May (76.5%) to September and October
(100%) (Figure 2).
182
Tigerfish in the 15 – 19.9 SL size class feed predominantly on macroinvertebrates (food
proportion = 1) while those from the 20 – 44.9 SL size group fed mostly on fish (65%);
Oreochromis placidus, O. mossambicus, Glossogobius giuris, Clarias gariepinus and Labeo
altivelis. Tigerfish in the 35 – 39.9 SL size group feed mostly on fish (78%); Glossogobius
giuris, Labeo altivelis and Oreochromis placidus. Macroinvertebrates formed a small
proportion of the diet of tigerfish in the 35 – 39.9 SL (0.24) and 40 – 44.9 SL (0.16). Tigerfish
in the 40 – 44.9 SL size group feed mostly on fish Glossogobius giuris, Clarias gariepinus and
Oreochromis mossambiccus (Figure 3, Table 1). Tigerfish in the 25 – 29.9 and 30 – 34.9 SL
Figure 2. Incidence of empty stomachs in 155 specimens of Hydrocynus vittatus in
Malilangwe reservoir from May - October 2011 varied from 76.5 - 100%.
Figure 3. Frequency occurrence of prey items in stomachs of Hydrocynus vittatus sampled in
Malilangwe reservoir from May to October 2011.
183
size group also fed mostly on fish (0.64 & 0.37) and macroinvertebrates (0.35 & 0.58
respectively). The distribution of prey items by size class (SL) of H. vittatus shows that
Chaoborus sp. and cichlids were the major prey items (Table 1).
The prey length in relation to the predator length for H. vittatus is shown in Figure 4.
For 20 tigerfish with measurable prey in their stomachs, the predator length to prey length
ratio ranged from 10.4 to 46.1% with a mean of 20.5%. The graph shows that small tigerfish
consumed prey (fish) from small size SL classes but larger predators took a wider range of
prey sizes and most of the prey items consumed were 3 – 17 cm SL (Figure 4).
Table 1. Frequency of occurrence (%) of different prey items by standard length size class in
stomachs of Hydrocynus vittatus sampled in Malilangwe reservoir from May to
October 2011.
Standard length (cm)
Weight range (g)
Number (n)
Fish scales/vertebra
Baetidae
Chaoborus sp.
Pleidae
Corixidae
Chironomidae
Notonectidae
Aeshnidae
Glossogobius giuris
Oreochromis mossambiccus
Clarias gariepinus
Labeo altivelis
Relative fullness (%)
15 - 19.9
0.11
1
100
20
20 - 24.9
0.15
1
100
2
25 - 29.9
30 - 34.9
0.23 - 0.37 0.36 - 0.62
7
10
1
5
7
23
7
25
5
6
13
7
47
22
17
15
38.3
36.5
35 - 39.9
0.32 - 0.8
7
1
11
12
32
29
17
57.4
40 - 44.9
0.92 - 1.22
8
1
1
15
3
25
28
45
Size related dietary shift among different standard length (SL) size classes are shown
in Table 2. Stomach contents analyses by standard length size class indicated a high degree
of dietary overlap over all standard length size classes. Juveniles or fry were absent in the
catch survey due to the selective nature of the sampling gear that was used.
184
Table 2. Size related dietary shift among the different standard length size classes of
Hydrocynus vittatus sampled in Malilangwe reservoir (May – October 2011).
SL group (cm)
15 - 19.9
20 - 24.9
25 - 29.9
30 - 34.9
35 - 39.9
20 - 24.9
0.92
25 - 29.9
0.85
0.93
30 - 34.9
0.85
0.93
1.00
35 - 39.9
0.89
0.98
1.00
1.00
40 - 44.9
0.92
1.00
1.00
1.00
1.00
Figure 4. Relationship of prey standard length and predator standard length of Hydrocynus
vittatus.
DISCUSSION
The results of the stomach analyses indicated a low incidence of full stomachs (21.9%) and a
very high incidence of empty stomachs (78.9%). It was noted that all fish caught in
185
September and October had empty stomachs. These observations are similar to H. vittatus
studies done by Matthes (1968) and Mhlanga (2003) in Lake Kariba were they observed high
percentage incidences of empty stomachs ranging between 50% and 90%. The high
percentage incidence of empty stomachs can be attributed to post-capture digestion which
resulted in 5% of stomachs analysed to contain fish scales or vertebra. The empty stomachs
during September and October can be attributed to high temperatures (mean 30oC) which
resulted in low dissolved oxygen levels (≤ 4.5 mgl-1) throughout the water column. This
might have resulted in the tigerfish feeding less as they slowed down their metabolism with
decline in dissolved oxygen levels causing a significant reduction in food conversion and
growth amongst the species. A similar scenario was observed in Gambusia affinis fry
(Wurtsbaugh and Cech 1983) and Handeland et al. (2008) in the Atlantic salmon postsmolts. The type of fish gear; gillnets and fyke nets that was employed had an effect on the
high frequency of individuals with empty stomachs in the Malilangwe reservoir. Reyjol et al.
(2010) and Vinson & Angradi (2011) showed that the mean percentage of individuals with
empty stomachs varied significantly among fish collection gear types, trophic groups,
feeding behaviours and habitats and with species length at maturity. Paradis et al. (2008)
suggested that a high frequency of individuals with empty stomachs in northern pike, Esox
lucius may reflect a strongly piscivorous behaviour while low frequency of individuals with
empty stomachs could reflect a higher utilization of invertebrates.
The tigerfish in the reservoir were shown to undergo ontogenetic diet shifts during
early life-history stages. These shifts had large implications for the individuals, populations
and communities which eventually resulted in piscivory as observed with the tigerfish in the
reservoir. This switch to piscivory is viewed as favourable to individuals because of the
associated increase in growth and survival (Jensen et al. 2004, Graeb et al. 2005). Most of
the tigerfish caught fed primarily on fish with macroinvertebrates forming a smaller
percentage of their diet and this can be explained by optimal foraging theory which suggests
that early switching to piscivorous diet result in faster growth because they derive higher
energetic returns from fish prey than alternative prey such as macroinvertebrates (Graeb et
al. 2005).
186
Stomach content analysis of Hydrocynus vittatus fish specimens showed that it feeds
extensively on fish and the results observed in this study agree with other previous studies
on the nature of its diet. The study show also showed that cichlids (35%) are currently the
major prey item in the diet of H. vittatus with gobiidae (31%), cyprinidae (29%) and clariidae
(28%) being consumed in different proportions. Mhlanga (2003) studies in Lake Kariba
showed that tigerfish fed primarily on Limnothrissa miodon (55%), cichlids (20%), others
including catfish, squeaker fish and macroinvertebrates (12%) and Brycinus sp. (<5%) while
Winemiller and Kelso-Winemiller (1994) showed that Hydrocynus forskahlii fed primarily on
cichlids (over 50%) in the Zambezi River floodplain. Therefore cichlids are the preferred prey
even in Lake Kariba without the introduced Kapenta. Tigerfish fed primarily on fish less than
20 cm SL, a similar finding to that of Winemiller and Kelso-Winemiller (1994) where tigerfish
fed on fish <25 cm SL. In this study the prey was <50% predator length and only in
exceptional cases was the ratio greater than 40%.
Diet overlap was higher for the different SL size groups (>0.85) and this suggests that
food resource partitioning may occur as environmental conditions and resource densities
change with season. We observed a diet shift in tigerfish with the primary differences being
the greater consumption of cichlids during May - June and a shift to cyprinidae, gobiidae
and clariidae during July – August. Within the different age groups a diet shift was also
observed. These seasonal diet differences could be more derived from differences in
relative prey availability in the resident habitats rather than prey selection by the tigerfish.
The predation on juvenile fish species by tigerfish has a significant impact on
population natural mortality, at is an important parameter in stock assessment models
(Mhlanga 2003). A follow-up study investigating interactions between the different prey and
predator groups is recommended to better understand the long-term effects of introducing
exotic species into a closed ecosystem such as Malilangwe reservoir. The decline in Tilapia
rendalli in the reservoir could be linked to the introductions of tigerfish but more studies are
required to confirm this.
187
APPLICATION OF THE LAKE HABITAT SURVEY (LHS) METHOD IN A TROPICAL AFRICAN
LAKE: A CASE STUDY OF MALILANGWE RESERVOIR, SOUTH-EAST LOWVELD, ZIMBABWE
Tatenda Dalu, Bruce Clegg and Tamuka Nhiwatiwa. 2011. Application of the Lake Habitat Survey
(LHS) method in a Tropical African Lake: a case study of Malilangwe Reservoir, South-East Lowveld,
Zimbabwe. African Journal of Aquatic Ecology. Submitted for publication. AJAS-2011-0073.R1.
188
INTRODUCTION
Aquatic habitats are detrimentally affected by the growing demand for water supply which
has resulted in an array of impacts across several spatial scales, from the global scale down
to the local habitat level (Hughes 2005). Over the past 30 years human activities have
caused freshwater biodiversity to decline at a faster rate than in either terrestrial or marine
habitats (Riain et al. 2008). To curb this trend, countries and regions have put in place
legislative measures. The European Union (EU) established a Water Framework Directive
(2000/60/EC) in December (2000), which has become a landmark for integrated, sustainable
water management (Hughes 2005). The Water Framework Directive was an important driver
in the development of the Lake Habitat Survey (LHS) method, which can systematically
characterise and assess the physical habitat of lakes and reservoirs. LHS can also play an
important role in condition monitoring, systematising environmental impact assessment
and supporting restoration programmes for degraded lake ecosystems (Rowan et al. 2004;
2006, McGoff and Irvine 2009). The LHS protocols were developed to create the foundations
of a European standard for assessing the hydromorphology of standing waters under the
aegis of Comité Européen de Normalisation (CEN) (Rowan et al. 2004).
The LHS approach is based on a combination of a small number of detailed plot
observations, analysed together with several whole-lake metrics. The scheme builds upon
lake habitat characterisation techniques developed in the United States by the
Environmental Mapping and Assessment Program (EMAP) as well as those developed in the
River Habitat Survey (RHS) in the UK (Rowan et al. 2004). The LHS method includes
quantitative descriptions of canopy, macrophyte communities, impact of human activities
on the shoreline and the dominant littoral substrate. The Lake Habitat Survey method is
done through surveys within the ecotone (the transitional area between terrestrial and
aquatic systems), which is normally the area incorporating the riparian and the littoral zone
of a lake. The littoral zone of lentic water bodies is functionally important because it
provides shelter against predation and wave action, feeding zones, and habitat; hence it is
the zone of highest productivity in a lake (McGoff 2008; McGoff and Irvine 2009).
Consequently, LHS provides a functionally relevant description of the lake ecosystem
189
(Wetzel 2001), which is necessary for sound conservation and management decision
making.
By incorporating suites of lake habitat features for survey, the LHS method is capable
of serving a range of operational needs. For example result might be used to describe the
hydromorphological reference conditions for lakes, and determine the characteristics of
hydromorphology that support the biological elements for varying levels of ecological
status. This will certainly aid in the identification of remediation needs where the ecological
status of a lake system is already compromised. The LHS also has potentially important
applications as a legislative tool in tropical countries where there is generally inadequate
information and criteria for assessing human impacts on lake ecosystems. Much of the
research effort in lakes and reservoirs in Zimbabwe has been directed at long-term
descriptive and ecological studies on theoretical and applied issues (e.g. Marshall 1981,
Mutsekwa 1989; Magadza 1994; Nhiwatiwa and Marshall 2006 & 2007; Chifamba and
Marufu 2011). However, habitat structure and ecological effects of flow and other
modifications to reservoirs are poorly understood and difficult to assess because of lack of
contemporary and historical ecological data.
The essence of the LHS approach is that it is a technique that will provide an
integrated assessment of the physical habitat of standing waters. The main aim of this study
was to analyse and determine the current state of the physical habitat of Malilangwe
reservoir and the applicability of the LHS method as an assessment tool on a tropical
system. A comprehensive picture on the range of habitats and the intensity of human
activities that may be affecting the lake should emerge from this study. It should also be
possible to capture and separate influences that encroach directly on the lakeshore from
those that are present in the wider catchment, but whose effects may be buffered by any
intervening areas.
METHODS
Study area
of Zimbabwe (20°58’ 21°02’ S, 31°47’ 32°01’ E) (Figure 1, Table 1). Malilangwe Reservoir is
190
an impounded river formed in 1964 and is used for water supply in the reserve. It is situated
on the Nyamasikana River, a tributary of the Chiredzi River which in turn flows into the
Runde River. It is a gravity section masonry dam with a surface area of 211 hectares with
maximum volume of 12496259.92 m3 at full capacity. Flanked by rocky hills on most of its
sides, the impoundment has a rocky substrate with few sandy bays. It is poorly vegetated
with few marginal plants including Azolla filiculoides (Lam), Ludwigia stolonifera (Guill and
Perr) Raven, Panicum repens (Lam), Schoenoplectus corymbosus (Roth ex Roem and Schult)
Raynal, Potamogeton sp. and sedges (Phragmites mauritianus (Kunth) and Cyperus sp.), the
plant nomenclature follows Mapaura and Timberlake (2004). The fish communities include
Table 1: Details of Malilangwe reservoir used for comparative testing of the LHS method.
Location
Maximum depth (m)
South-east Lowveld, Zimbabwe
14.3
Altitude (m)
360
Lake size (ha)
211
Catchment area (km2)
200
Shoreline perimeter (km)
9.415
Water body type
Impoundment
Pressures
Angling, Nuisance species, Water supply
LHS survey method
The LHS method is a tool for characterizing and assessing the physical habitat of a lake
through quantitative descriptions of canopy, macrophytes, amount of shoreline affected by
human activities and the dominant littoral substrate. The Lake habitat survey of Malilangwe
reservoir was carried out in March 2011 using a boat and on foot. There are basically two
versions of the LHS method, a simple version for rapid and extensive use, and a more
comprehensive version for intensive use on a limited number of lakes (Rowan et al. 2006). A
comprehensive version of the LHS was applied as the LHS survey was only being carried out
191
in one reservoir. The boat was launched from Pamushana Harbour and Kwali Lodge on the
eastern side of the reservoir, near the dam. A single survey was adequate to capture most of
the reservoir’s limnological features with some observations being carried out from late
April through to July as vegetation conditions around the lake zones (littoral and riparian)
changed which could probable have an influence habitats characteristic and the water level
was lower during this time of year so the bank/beach zones were exposed and could be
examined easily.
Figure 1: Location of hab-plots around Malilangwe Reservoir (shaded area), labelled A – J.
192
The LHS method was carried out in summer (March) because during this period
physicochemical data collected from the index site (deepest point) were considered to be
most representative of the lake conditions as a whole (Rowan et al. (2004, 2006, 2008)).
When a survey is conducted in mid- to late-summer, temperature and dissolved oxygen
profiling is conducted at the index site because almost all stratifying lakes will have a
detectable thermocline at this time.
The first hab-plot (15m x 15m) was chosen randomly and the other nine hab-plots
were approximately evenly spaced around the lake perimeter. The plots extended from the
riparian to littoral zone, and included the main characteristics of the lake shore. A detailed
LHS field survey questionnaire version 4 (Appendix I) (Rowan et al. 2008) was filled out for
each hab-plot. The following features were recorded at each hab-plot in the different zones:
littoral zone, shore zone, riparian zone (15 m and 50 m zones landward from the bank top)
and characterization of the water body perimeter (including shoreline pressure). Visual
interpretation of raw and remotely sensed data from June 2000 obtained using Landsat 7
+ETM satellite image were also used to complete Malilangwe Reservoir LHS survey form.
Summary metrics of the LHS termed the Lake Habitat Modification Score (LHMS) and
the Lake Habitat Quality Assessment (LHQA) were calculated using the survey data. Please
note that these metrics are still provisional and subject to change and further investigations
are still required to determine the relationships and thresholds between biology and hydromorphological disruption (Rowan et al. (2004).
Lake Habitat Quality Assessment (LHQA)
The Lake Habitat Quality Assessment (LHQA) method produces an index of lake habitat
quality based on diversity, physical structure and the presence of habitat features
considered to be of ecological value (Rowan et al., 2004, 2006). The LHQA is based mainly
on proportional scoring over the hab-plots. The LHQA scoring system is outlined in Table 2
and more detail is given in Rowan et al. (2004, 2006). Since this study was confined to one
lake, the LHQA scoring method, which was designed for comparison across lakes, was
adjusted according to McGoff and Irvine (2009) and Rowan et al. (2006). A minor
modification of score ranges was made so as to incorporate nuisance or exotic species. The
modified criteria were based firmly on the original LHS approach and philosophy (Table 2).
193
Aquatic and terrestrial plant species were identified with help of Dr Bruce Clegg, Mark Hyde
and Bart Wursten (www.zimbabweflora.co.zw).
Lake Habitat Modification Score (LHMS)
The LHMS metric is useful for classification purposes, especially in the identification of lakes
with high ecological status and those at risk of not attaining good ecological status due to
hydromorphological alteration from human activities. Human pressure as part of the whole
lake assessment, were assessed at each hab-plot up to 50m away from the waterline Rowan
et al. (2004, 2006), Skocki et al. (2008) and McGoff and Irvine (2009). Therefore it enables a
comparison of hydromorphological and related pressures between different sites. The full
array of features included in the LHMS scoring system is shown in Table 3. The LHMS has a
score from 0 to 42, where the zero end of the scale means that the habitat is natural and
has not been modified in any way.
Water was collected at each depth (0.5, 1, 1.5, 2, 3, 4 – 10 m) for the full vertical profile
using a 10 - litre Ruttner sampler at the index site (the deepest point). Measurement of
temperature and dissolved oxygen (DO) was done using a pH, Conductivity and DO meter
(HACH, LDO, Germany). Water transparency was measured using a Secchi disk.
RESULTS
Index site
The physicochemical data recorded at the index site are summarised in Table 4. The lake
was shallow with a depth of 10.1 m (volume = 8195599.04 m3) at the deepest point but
depth can reach 15.4m (12496259.92 m3) at full capacity. High water temperatures were
recorded for the two days of sampling, with a temperature of 27.5oC being recorded at 10m.
Thermal and dissolved oxygen profiles (Figure 2) showed that the lake was stratified. No
algal blooms were observed. Dissolved oxygen deficits and odours indicative of hydrogen
sulphide were evident at depths > 6 m.
194
Table 2: Lake Habitat Quality Assessment scores and criteria for the LHS per hab-plot adopted from
Rowan et al. (2006) and McGoff and Irvine (2009) used in this study with maximum LHQA =
112. (The “equals sign represents ‘for’)
Lake
zone
Riparian
Shore
Characteristic
measured
Vegetation
structural
complexity
Vegetation
longevity/ stability
Extent of natural
land cover types
Diversity of natural
land cover types
Diversity of banktop features
Shore structural
habitat diversity
Bank naturalness
bank habitat
Beach naturalness
Littoral
Whole
Lake
Vegetation
structure
beach habitats
Hypsographic
variation
Extent of natural
littoral zones
littoral zone types
Extent of
macrophyte cover
Diversity of
macrophyte
structural types
Extent of littoral
habitat features
Diversity of littoral
habitat features
Diversity of special
habitat features
Introduced
species
Measurable feature
Proportion of hab-plots with complex
or simple riparian vegetation structure
Proportion of hab-plots with >10%
cover of trees with DBH > 0.3m
Proportion of hab-plots with either
natural / semi-natural woodland,
wetland, moorland heath or rock,
scree and dunes
Number of natural cover types
recorded
Number of bank-top features recorded
Proportion of hab-plots with an earth
or sand bank > 1m
Proportion of hab-plots with trash-line
Number of natural bank materials
recorded
Proportion of hab-plots with natural
beach material
Number of natural beach materials
recorded
Coefficient of variation for depth at
10m from shore over all plots
Proportion of hab-plots with natural
littoral substrate
Number of natural littoral substrate
types recorded
Average of total macrophyte cover
over all hab-plots
Number of hab-plots where
macrophyte cover extends lake wards
Number of macrophyte cover types
recorded (not including filamentous
algae)
Average of total cover for fish over all
plots
Number of littoral habitat feature
types recorded
Number of special habitat features
(excl. diseased alders)
Number of islands
Number of deltaic depositional
features recorded (excl. un-vegetated
sand and silt deposits)
Number of non-native species
Whole lake LHQA
score
1 = 1 – 3, 2 = 4 – 6, 3
= 7 – 8, 4 = 9 – 10
Max
score
4
2 = 1 – 3, 2 = 4 – 6, 3
= 7 – 8, 4 = 9 – 10
3 = 1 –3, 2 = 4 – 6, 3 =
7 – 8, 4 = 9 – 10
4
1 for each type,
maximum of 4
1 for each type,
maximum of 4
1 = 1 – 3, 2 = 4 – 6, 3
= 7 – 8, 4 = 9 – 10
1 = 1 – 3, 2 = 4 – 6, 3
= 7 – 8, 4 = 9 – 10
1 for each type,
maximum of 4
1 = 1 – 3, 2 = 4 – 6, 3
= 7 – 8, 4 = 9 – 10
1 for each type,
maximum of 4
1 for > 25, 2 for > 50,
4 for > 75
1 = 1 – 3, 2 = 4 – 6 3 =
7 – 8, 4 = 9 – 10
1 = 1 – 3, 2 = 4 – 6, 3
= 7 – 8, 4 = 9 – 10
1 for a ‘1’, 2 for a ‘2’
3 for a ‘3’, 4 for a ‘4’
1 = 1 – 3, 2 = 4 – 6 3 =
7 – 8, 4 = 9 – 10
1 for each type,
maximum of 4
1 for a ‘1’, 2 for a ‘2’
3 for a ‘3’, 4 for a ‘4’
1 for each type,
maximum of 4
5 for each type,
maximum score of 20
2 = 1, 5 = 2 – 4, 10 ≥ 5
2 for each type
0 = 0 – 1, 2 = 2 – 3,
4 = ≥ 4 recordings
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
20
10
6
4
195
Table 3: Scoring system for Lake Habitat Modifications Score (LHMS) adopted from Rowan
et al. (2004).
Pressure
Scores 0
Shore zone
<10% shoreline
modification affected by hard
engineering AND
Shore reenforcement
recorded at 0-1
hab-plots
(0 for core)
Shore zone
< 10% shoreline
intensive use non-natural landcover AND Nonnatural land-cover
recorded at 0-1
hab-plots (0 for
core)
In-lake use
Hydrology
No in-lake
pressures
(excl. litter or
odour)
0-1 hydrological
structures
Scores 2
≥ 10%, < 30%
shoreline affected by
hard engineering OR
Shore reenforcement
recorded at 2 habplots (1 for core) OR
Poaching recorded at
3 or more hab-plots
(2 for core)
≥ 10%, < 30%
shoreline nonnatural land-cover
OR Non-natural landcover recorded
at 2 hab-plots (1 for
core)
1 in-lake pressure
(excl. litter or
odour)
2 hydrological
structures OR
Presence of an
upstream
impoundment
Sediment
regime
< 25% shore
affected by
erosion AND < 25%
in-lake area
affected by
deposition (excl.
veg islands)
≥ 25%, < 50%
affected by
erosion OR ≥ 25%,
< 50% lake area
affected by
deposition (excl.
veg islands) OR
Sedimentation over
natural substrate
recorded at 3 - 4
hab-plots (2 for
core)
Nuisance
Species
0 - 1 recordings
(not 2
recordings of 1
species)
2 - 3 recordings
(may be
1 or more species)
Scores 4
≥ 30%, < 50%
shoreline
affected by hard
engineering OR
Shore
modification
recorded at 3-4
hab-plots (2 for
core)
Scores 6
≥ 50%, < 75 %
shoreline
affected by hard
engineering OR
Shore
modification
recorded at 5-7
hab-plots (3 for
core)
Scores 8
≥ 75% shoreline
affected by hard
engineering OR
Shore modification
recorded at 8 or
more hab-plots (4
for core)
≥ 30%, < 50%
shoreline
non-natural landcover OR Nonnatural landcover recorded at
3-4 hab-plots (2
for core)
2 in-lake
pressures (excl.
litter or odour)
≥ 50%, < 75%
shoreline
non-natural landcover OR Nonnatural landcover recorded at
5-7 hab-plots (3
for core)
3 in-lake
pressures
≥ 75% shoreline
non-natural land
cover OR Nonnatural land-cover
recorded at 8 or
more hab-plots (4
for core)
3 or more
hydrological
structures
≥ 50%, < 70%
shore affected by
erosion OR ≥
50%, < 70% lake
area affected by
deposition (excl.
veg islands) OR
Sedimentation
over natural
substrate
recorded at 5 - 6
hab-plots (3 for
core)
≥ 4 recordings
(may be 1 or
more species)
Principal use
hydropower,
flood control,
water supply OR
Raised or
lowered by > ± 1
m
> 3 in-lake
pressures
1 dam (no fish pass)
OR
Principal use
hydropower, flood
control, water
supply
AND Annual
fluctuation > 5m or
< 0.5m
≥ 70% shore
affected by
erosion OR ≥
70% lake area
affected by
deposition (excl.
veg islands)
196
Figure 2: Temperature and dissolved oxygen profiles for Malilangwe reservoir recorded in
March 2011.
Table 4: Summary data for the index site for Malilangwe reservoir, March 2011.
Measurements at index site
Results
Water depth (m)
10.1
pH
7.9
Clear to bottom
No
1.3
Temperature (oC) range
27.5 – 31.3
Dissolved oxygen (mgl-1) range
7.0 - 1.9
LHS survey
The data summary for shoreline pressures recorded at each hab-plot is presented in Table 5.
Figure 3 shows pictures of the two hab-plots E and J, showing the different zones namely:
197
the littoral zone - extends 10 m lake-wards from waterline; beach - variable width and may
not be present; bank face - variable height and may not be present; bank top - extends 1 m
shore wards from back of bank; and riparian zone - extends 15 m shore wards from back of
bank. Hab-plots C, E and J were recorded as having the largest number of different
pressures (2) within the 0 – 15 m and >15 - 50 m, followed by hab-plots B, G, H and I (1
pressure) and lastly hab-plots A, D and F which scored zero. There were four instances (habplot B, H, I and J) where pressures extended into the landward >15 – 50 m perimeter band.
There was only one site (hab-plot J) that had one pressure type and results showed that the
lake-ward pressure extent exceeded the land-ward extent by more than one category. This
indicates that when shoreline pressures exist, they are more likely to extend to within 15m
of the water edge than to be detached by a more natural buffer zone.
Figure 3: Two examples of hab-plots E (picture a) and J (picture b) to illustrate the
boundaries between hab-plot zones, where: A = lake, B = Littoral zone, C = Bank
face, D = Bank top and E = Riparian zone.
198
Table 5: Summary data for shoreline pressures within 15 m and between > 15 - 50 m for Malilangwe Reservoir (March 2011) expressed as
extent of total perimeter length
Pressures and non-natural land-use
Hab-plots
A
Commercial activities
Residential areas
Roads or railways
Parks and gardens
Recreational beaches
Educational activities
Litter, dump, landfill
Quarrying or mining
Coniferous plantation
Evidence recent logging
Pasture
Observed grazing
Tilled land
Orchard
Erosion
Number of pressures
15
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
B
50
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
15
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
C
50
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
1
15
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
2
D
50
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
15
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
E
50
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
15
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
1
F
50
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
1
15
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
G
50
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
15
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
1
H
50
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
15
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
I
50
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
1
15
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
J
50
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
1
15
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
50
0
2
0
1
0
0
0
0
0
0
0
0
0
0
0
2
Note: (i) 15 = 0 – 15 m and 50 = > 15 – 50 m
(ii) 0 (0 – 1 %), 1 (> 1 – 10 %), 2 (> 10 – 40 %), 3 (> 40 – 75 %), 4 (> 75 %)
199
Table 6: Summary data for natural land cover and meso-habitats within 15 m and between 15 - 50 m for Malilangwe Reservoir (March 2011)
expressed as extent of total shoreline length. Overall diversity of land-cover types was considered per hab-plot.
Natural land cover and meso-habitat type
A
Broadleaf/mixed woodland
Broadleaf/mixed plantation
Coniferous woodland
Scrub and shrubs
Moorland/heath
Open water
Rough grassland
Tall herb/rank vegetation
Rock, scree or dunes
Fringing reed banks
Wet woodlands
Alders (ring if diseased)
Bogs
Quaking banks
Other (e.g. fen, marsh)
Extent of predominant cover
Diversity of land-cover types
15
3
0
0
0
0
0
1
0
2
0
0
0
0
0
0
3
B
50
4
0
0
0
0
0
1
0
3
0
0
0
0
0
0
3
3
15
0
0
0
0
0
0
2
0
3
2
0
0
0
0
0
3
C
50
3
0
0
0
0
0
1
0
2
0
0
0
0
0
0
2
3
15
0
0
0
0
0
0
2
1
1
2
0
0
0
0
0
4
D
50
3
0
0
1
0
0
1
1
1
0
0
0
0
0
0
5
15
0
0
0
0
0
0
1
0
0
3
0
0
0
0
0
2
6
50
0
0
0
0
0
0
2
0
0
2
0
0
0
0
0
2
2
Hab-plots
E
F
15 50 15
0
2
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
1
2
3
0
1
0
0
1
0
2
1
2
1
2
1
0
0
0
0
0
0
0
0
0
0
0
0
3
6
3
6
7
G
50
1
0
0
0
0
0
2
1
0
2
2
0
0
1
1
7
15
2
0
0
1
0
0
2
0
2
1
0
0
0
0
0
5
H
50
1
0
0
2
0
0
2
0
3
0
0
0
0
0
0
4
5
15
1
0
0
1
0
0
4
0
3
2
0
0
0
0
0
5
I
50
3
0
0
2
0
0
3
0
4
0
0
0
0
0
0
4
5
15
4
0
0
3
0
0
3
0
3
2
0
0
0
0
0
5
50
4
0
0
2
0
0
3
0
3
0
0
0
0
0
0
4
5
J
15 50
1 3
0 0
0 0
2 3
0 0
0 0
3 3
1 1
2 2
1 1
0 0
0 0
0 0
0 0
0 1
6 7
7
Note: (i) 15 = 0 – 15 m and 50 = > 15 – 50 m
(ii) 0 (0 – 1 %), 1 (> 1 – 10 %), 2 (> 10 – 40 %), 3 (> 40 – 75 %), 4 (> 75 %)
200
Table 6 summarises data for natural shoreline data for both 0 – 15 m and >15 – 50 m
perimeter bands. Hab-plot F and J recorded the most diverse shoreline with respect to
natural land cover types (7 different types), followed by hab-plot C and E (6 types each). The
lake is dominated by broadleaf/mixed woodland with cover exceeding 40% and 75% for the
0 – 15 and >15 – 50 m bands respectively, for almost all the hab-plots.
LHQA and LHMS
The LHQA score calculated for the reservoir was 76 out of 112 (Table 7). Table 8 shows the
results for the LHMS showing how the final score was generated. Malilangwe Reservoir
achieved a much lower score of 16 out of 42 as it experiences relatively few pressures,
except for water pumping structures and residential areas (lodges) otherwise the system
can be considered natural. They are no tarred roads except for earth roads running at least
part way along the park and which are associated with the lodges and game viewing.
Vegetation
The vegetation in the areas surrounding Malilangwe Reservoir is mainly comprised of shrub
woodlands. Dominant species included Acacia welwitschii (Harms) Ross and Brenan,
Adansonia digitata (Adanson), Androstachys johnsonii (Prain), Brachystegia glaucescens
(Hutch and Davy), Spirostachys africana (Sond) and Gyrocarpus americanus (Stock), (Figure
4). The aquatic plants found were Azolla filiculoides (Lam), Cyperus sp., Ludwigia stolonifera
(Guill and Perr) Raven, Panicum repens (Lam), Phragmites mauritianus (Kunth),
Potamogeton sp. and Schoenoplectus corymbosus (Roth ex Roem and Schult) Raynal
(Mapaura and Falconer 2004).
Substrates in the drawdown zone varied from silts/clay on lower gradient areas to
rocks/boulders on steeper slopes. Areas off the lake mouths had silt/clay substrates.
Bedrock outcrops were frequent along the eastern shoreline and western shoreline closer to
the dam, while fine organic substrates were found throughout the whole lake. High gradient
areas for littoral zones with high macrophyte frequency were located along the eastern and
western shorelines moving towards the dam. Cover for fish and invertebrates were found to
be abundant due to the presence of macrophytes in the littoral zone in traditional nursery
201
habitats, which is important because of the predation pressure from the large population of
introduced tiger-fish (Hydrocynus vittatus) and bass (Micropterus salmoides).
Table 7: Scores for Lake Habitat Quality Assessment (LHQA) in Malilangwe reservoir in
March 2011
Zone
Measurable LHS feature
Riparian
Complex or simple veg.
> 10% large trees
Natural/semi natural
veg.
No. natural types
No. bank top features
Earth/sand bank
Trash line
Natural bank material
No. natural types
Natural beach material
No. natural types
Coefficient variation
Natural littoral substrate
No. natural types
Total macrophyte cover
Extend lake wards?
No. macrophyte types
Total fish cover
No. littoral features
No. wetland habitats
No. islands
No. deltaic deposits
Shore
Littoral
Whole lake
Vegetation
structure
Total
Introduced species
Counts of features across lake, or
number of hab-plots with a
feature
6
9
Score
allocated
10
2
4
5
4
4
3
4
1
0
10
3
10
10
5
10
5
3
1
0
4
2
4
2
2
4
3
4
1
0
4
1
4
4
4
4
4
15
2
0
3
2
76
2
4
Water level (r = 0.915) and substrate composition (r = 0.586) had a significant influence on
macrophyte composition (p < 0.05). Pearson and Kendall correlations showed a
significant relationship between water level, substrate composition and macrophyte species
communities (R2 = 0.842 and 0.324). This suggested that changes in water level had a
significant effect influence on the macrophyte species distribution and densities.
202
Table 8: LHMS component values and total score of Malilangwe reservoir (March 2011).
Pressure
Shore zone modification
Shore zone intensive use
In-lake use
Hydrology
Sediment regime
Nuisance Species
LHMS total score
Score
0
0
6
8
0
2
16
Figure 4: Remotely sensed image of Malilangwe Reservoir describing the land cover types.
Remote sensing and aerial imagery
Remotely sensed data showed good agreement with the observed field data for estimating
the aerial coverage of trees, tall herbs and grasses. The presence of herbs and grasses was
observed at most of the habitat plots. There were also limits in the spatial resolution of the
data as 25 m resolution was used hence small vegetation types were not easily
distinguishable with the required terrain resolution of better than 0.5 m being required to
preserve the recognition of vegetation features. There was considerable disagreement
203
between multispectral data and ground observations regarding the dominant land cover
within the riparian zone and shore zone at each hab-plot. It was noted that remotely sensed
data failed to show the presence of overhanging vegetation in the littoral zone.
Figure 5 shows some of the different riparian zones found around the reservoir,
mainly the thick to open riparian zones distinguished by different vegetation and substrate
types. In hab-Plot B, C, I and J (Figure 6), lodges and a residential area impose minimum
anthropogenic pressures on the lake as noted by the dense vegetation surrounding the
areas. Other smaller anthropogenic pressures on the lake included the small Pamushana
harbour, water extraction/drawing points (3) and Kwali lodge viewing point (Figure 7). The
use of aerial photography (Figure 6) enabled the precise identification and interpretation of
the various land use categories around Malilangwe reservoir.
Figure 5: Thick Acacia trees in the riparian zone very close to the waterline on the eastern
part of the lake between hab-plot I – J (picture a). Hab-plot I riparian zone
characterised by huge boulders and arrow indicates a nuisance tree species,
Albizia lebbeck (picture b). The riparian and littoral zones of hab-plot H (picture c)
and D (picture d).
204
Figure 6: Hab-plot A, B, C, I and J – Pamushana lodge uphill between hab-plot B and C,
Sparrow’s House next to hab-plot J and Kwali lodge (next to the dam) close to
hab-plot J. Water extraction points shown by the stars / crosses.
205
Figure 7: Kwali lodge viewing point next to the dam (hab-plot J) (picture a), hab-plot C –
Pamushana harbour (picture b) and hab-plot I - water extraction / drawing point for
Malilangwe (picture c).
DISCUSSION
Shallow lakes such as Malilangwe reservoir, typically do not develop a stable thermal
structure because shallow depths mean they can be easily disturbed by wind or wave action
resulting in full-water column mixing. In the current study dissolved oxygen (DO) levels
dropped from about 7 mgl-1 (6m depth) to 2 mgl-1 (10 m depth) which was an indicator of
oxygen depletion. Consequently, this probably means that the stratification that is occurring
is sufficient to limit water exchange between the surface and bottom waters during
summer. The results of this study are well in accordance with the assertion made by
Nhiwatiwa and Marshall (2006) that significant amounts of energy are still required to
disrupt thermal stratification even in shallow water-bodies, such as the Malilangwe
206
reservoir. In addition, microbial decomposition of organic matter falling from relatively
productive epilimnion (top layer) could have contributed to the low level of dissolved
oxygen in the hypolimnion (bottom layer). It is known that DO levels below 4 mgl-1 cause
acute mortality of the early life stages of fish, macroinvertebrates and plankton
communities (Chick et al. 2004), and therefore these results indicate that there is a problem
with the lake although it is relatively unpolluted. Deoxygenation of bottom waters and the
resultant changes in redox at the sediment-water interface can lead to rapid release of
nutrients and contaminants resulting in significant water quality deterioration especially at
turnover.
According to Kaufmann and Whittier (1997) distribution profiles are useful in
characterizing the pelagic habitats by determining the depths of the top (calculated at 5 m
depth) and bottom (6 m) of the metalimnion and the extent of oxygen depletion
operationally defined to be less than 2 mgl-1 DO. This information is very useful in selecting
gill net (maximum depth for fishing gear) and benthic sampling sites. At the index site, no or
very few organisms are expected to live at depths of 8 m and below as the DO levels are less
than 2 mgl-1 hence cannot sustain life and this study provided evidence for maximum depth
where fish could be caught.
Malilangwe reservoir does not appear to suffer from major problems of alien species
introductions as in the case of Lake Victoria (Verschuren 2002), Kariba (Mhlanga 2011),
Chivero (Marshall 1981, Magadza 1994), Mutirikwi (Mhlanga 2011) and most urban
reservoirs where the introduction of exotic species have led to the extinction of indigenous
ones. An exotic plant species, Calotropis procera (Aiton), was found on the western shore
(Pamushana Harbour) in low abundance but Albizia lebbeck (Lam) Benth another exotic
plant species appeared to be rapidly invading the eastern shores of the lake. Unfortunately,
the LHS appears to be useful for describing habitat quality but it seems to have a major
shortcoming when it comes to evaluating alien species. Incorporating alien species and/or
rare species, into conservation assessment of lakes was important in identifying possible
impacts on lake ecosystem functioning. Thus incorporation of such important information as
alien species data proved to certainly contribute to the development of a sound
conservation assessment based on community assemblages.
207
The LHQA is configured to express naturalness and diversity as proxies for the
conservation value of a site and Malilangwe reservoir’s score of 76/112 suggests that the
lake still has a more natural environment that is not heavily impacted by anthropogenic
effects. It ranks higher than most lakes surveyed in the UK by Rowan et al. (2004) such as
Lake Llyn Tegid (LHQA = 48/108), Brandy (62/108) and Lindores (59/108). The conservation
efforts by The Malilangwe Trust should therefore be commended.
Substrate size and characteristic is one of the most important determinants of
habitat characters for fish and macroinvertebrates along with bed form (Kaufmann and
Whittier 1997). Substrate influences the hydraulic roughness and consequently water
velocities and interstices size ranges that provide living space and cover for
macroinvertebrates (Kaufmann and Whittier 1997). Decreases in the mean substrate size
and increases in the percentage of fine sediments may destabilize water systems and
indicate changes in the rates of upland erosion and sediment supply as noted in hab-plots D
– F consisting of sand (> 10 – 75 %) and silt/clay (> 75 %) whilst Hab-plot H consisted of sand
(> 10 – 40 %) and silt/clay (> 40 – 75 %). These substrate characteristics changes are often
sensitive indicators of the effects of human activities on streams in the catchment hence
this in turn affect reservoirs.
The presence of different kinds of substrates (clay to boulders) and high density of
macrophytes in all hab-plots offers protection from predation for recruiting fishes and
provides an increased availability of food resources, especially for smaller organisms such as
macroinvertebrates and plankton. Other studies have also noted that an increased
complexity of macrophytes contributes to the relatively high secondary productivity and
high abundance of fishes and invertebrates (van Donk and van de Bund 2002; Schmieder et
al. 2006). The current study showed that various benthic littoral substrates have enabled
the development of diverse habitats for aquatic fauna in the reservoir, thereby enhancing
biodiversity in the littoral zone.
Many of the habitats in Malilangwe reservoir littoral zones are seasonal due to high
evaporation rates and drawdown which results in yearly water depth decreases of up to
about 6 metres or more. This usually results in decreases in macrophyte communities and
densities which harbour macroinvertebrates and fish resulting in changes in the aquatic
208
ecosystem. It is also well established that within a single lake, vegetated sites often support
a greater diversity of macroinvertebrates than do open water sites (Brendonck et al. 2003).
In this study, macrophytes were found to offer protection from predation for recruiting
fishes and provide an increased availability of food resources, especially for smaller
organisms. Due to drawdown, most of the macrophytes remain exposed and die, but a few
sedge species (Cyperus sp., P. mauritianus and S. corymbosus) remain exposed along the
reservoir banks/shores with L. stolonifera regenerating after initial drying up. There is
speculation that water-level drawdowns resulting in the depletion of macrophytes might be
contributing to the overall decline of Tilapia rendalli (macrophyte feeder), but more detailed
studies are required to confirm this.
From the remotely sensed data, major land-cover classes and landform features such
as urban development and islands could be easily identified, but the detail of vegetation
structure and cover recorded at hab-plot scale was not easily represented. Many pressures
relevant to LHS could not be identified, including those that are likely to change seasonally
such as boating, angling and related visitor pressures. The study is the first test of the
relevance of LHS as a descriptor of ecological quality in a tropical African lake but it is
important to recognize the limitations of the study on one water-body. It would be highly
informative to extend such detailed work across a number of reservoirs for better
comparison as little information is known about the hydrological regimes of reservoirs in
Africa particularly in Zimbabwe except for large water bodies such as Lake Kariba and
Chivero.
The study also highlighted a potential limitation of using LHQA as a metric of
conservation status in a reservoir where macrophytes are naturally sparse. McGoff and
Irvine (2009) showed that small low alkaline upland lakes generally have less emergent
macrophytes and habitat diversity than large higher alkaline lakes, hence scoring lower for
LHQA, despite their naturalness which can be considered to be the case of Malilangwe
reservoir, a small alkaline reservoir with less emergent macrophytes but scored lower for
LHQA despite their natural state. Results of this study show that the LHS method has
potential as an ecological monitoring and management tool that integrates several variables
related to human pressures on aquatic ecosystems. However, like other biological
209
monitoring tools, this method faces the challenge of establishing baseline conditions that
define “naturalness”. For example, the application of LHQA as a metric of conservation
status on a reservoir where macrophytes are naturally sparse is potentially problematic.
In this study, 10 hab-plots were found to be very useful in describing lake habitat
characteristics since a comprehensive perimeter survey was carried out which included
intensive shoreline observations in 15m x 15m wide plots. Similarly, Rowan et al. (2006),
reported that relatively little information is gained if more than 10 hab-plots are sampled; it
also increases the survey time and introduces undesirable redundancy in the data collected.
For large water bodies it is thus recommended to increase the number of hab-plots so as to
cover all features as this is influenced by the size and complexity of the lake, with larger and
more complex sites exhibiting a more diverse set of features.
There is still much to be done in demonstrating the suitability of the LHS approach as
a potential contribution to the development of standards on the hydro-morphological
assessment of African standing waters. However, present understanding indicates that no
standard lake monitoring protocol is available in Africa, Europe and most parts of the world
(Rowan et al. 2004) hence adopting the full development of the LHS into a standard
approach is required by all stakeholders. This study shows LHS may be a suitable hydromorphological and conservation tool in Zimbabwe and other southern African countries.
More experience through other field case studies here in Africa will strengthen the LHS
concept. Future studies could also model water quality and LHS results to determine if there
is a direct relationship for African waters.
210
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APPENDIX I
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LIMNOLOGICAL STUDY OF MALILANGWE RESERVOIR IN THE

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