A Conservation Value Index to facilitate coral reef evaluation and

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A Conservation Value Index to facilitate coral reef evaluation and
A Conservation Value Index to facilitate coral reef evaluation and
assessment
A thesis submitted for the degree of Doctor of Philosophy,
Department of Biological Sciences,
University of Essex,
November 2007
c
Steven M Mellor
Dedicated to my parents,
Don & Eve
II
“A coral reef cannot be properly described, it must be seen to be truly appreciated”
-
III
Hickson (1889)
Summary
Due to the importance of coral reefs to local communities and the increasing level of
natural and anthropogenic impacts upon them, accurate monitoring and assessment of reef
condition is necessary to allow the management and sustainable use of these resources. This
study tests and compares several commonly utilised benthic sampling techniques and
whether they can be implemented by semi-skilled volunteers to provide data to assess reef
condition and help prioritise areas for conservation. The study identified line transects as the
most suitable benthic data collection method along with time restricted belt transects for the
fish assemblage. Data collected by volunteers after a week long training period was found
not to be significantly different from that collected by experienced reef surveyors. Twenty
four commonly recorded reef assessment attributes were identified to show differentiation
between sites of varied condition and combined into a two part multi-metric Conservation
Value Index (CVI). This index was then tested and used to assess the condition of several
reefs in two Marine Protected Areas. Reefs in the Wakatobi Marine National Park, Sulawesi,
Indonesia were found to be in decline with both univariate attributes and CVI scores showing
reductions from 2002 to 2007. Although both methods did highlight that a No Take Area
within the park showed the slowest rate of decline. The reefs of the Ras Mohammed National
Park, Sinai, Egypt were found by both univariate and the CVI method to be showing signs of
benthic recovery after a COTs outbreak at the turn of the century, while the fish assemblage
remained in a stable condition between 2005 and 2006. The proposed CVI meets the
requirements of a readily understood assessment method that can be use to disseminate
complex biological data to managers, politicians, funding bodies and other stakeholders.
IV
Acknowledgements
Dr. David J. Smith for continued support, advice, constructive criticism and encouragement
throughout the study period and beyond
Dr. James Morison and Professor Chris Mason for constructive criticism and advice
Dr. James Bell (University of Wellington, New Zealand) for an alternate viewpoint that was
always constructive.
Ras Mohammed National Park, Egypt
(Mr) Ben Farrar, Gerban Post and Steve Oliver for logistical support with Egyptian fieldwork
All Bedouin at camp in Ras Mohammed, Egypt
Joe Taylor and Sebastian Hennige for field support and assistance in Egypt.
Dr.Essam Saadalah Khalil (EEAA) for use of research facilities at Nature Conservation
Centre in Ras Mohammed.
Dr. Osama al-Gpely (EEAA) for access to closed areas in Ras Mohammed
All EEAA Park Rangers involved with monitoring program
Wakatobi Marine National Park, Indonesia
Jessica Hyypka, David Sanderson for assistance with Indonesian data collection
Femmy Hukom & Agus Budianto (LIPI) for assistance with Wakatobi Monitoring
Programme
All Operation Wallacea staff in Indonesia
Dr. Tim Coles & Operation Wallacea for providing travel funds and research facilities
University of Essex Poulter studentship award for PhD funding
Seb, Dan, Mark and Ben Cong at the CRRU
Rich & Leanne, Layla, and Sal for my sanity through the Winter months at Essex
Mum, Dad, Karen, Samantha & Chloe for love and unconditional support always
V
Table of Contents
Summary
IV
Acknowledgements
V
Table of Contents
VI
List of Figures
XII
List of Tables
XX
List of Abbreviations
XXII
Chapter 1 General Introduction
1
1.1
Importance of coral reefs
1
1.2
Threats to coral reefs
1
1.3
Monitoring coral reef condition
4
1.4
Current reef assessment methods
6
1.5 Multi-metric Indexes of Biotic Integrity
12
1.6
Performance criteria and management
16
1.7
Survey methodologies
18
VI
1.8 Study sites
19
1.8.1 Wakatobi MNP, Sulawesi, Indonesia
19
1.8.2
26
Ras Mohammed NP, Sinai, Egypt
Chapter 2 Optimised reef survey methodology
2.1
Abstract
34
2.2 Introduction
2.2.1
2.3
2.4
34
35
Sample size and replication
36
2.2.2 Benthic data collection
37
2.2.3
Fish community survey
39
2.2.4
Survey data accuracy
40
2.2.5 Survey data consistency
42
2.2.6
42
Minimum detectable change
Methodology
45
2.3.1
45
Sample size and replication
2.3.2 Benthic data collection
46
2.3.3
47
Survey data accuracy
2.3.4 Survey data consistency
48
2.3.5
49
Minimum detectable change
Results
2.4.1
49
Sample size and replication
49
2.4.2 Benthic data collection
53
2.4.3
54
Survey data accuracy
2.4.4 Survey data consistency
55
2.4.5
58
Minimum detectable change
VII
2.5
Discussion
59
2.5.1
59
Sample size and replication
2.5.2 Benthic data collection
61
2.5.3
62
Survey data accuracy
2.5.4 Survey data consistency
63
2.5.5
Minimum detectable change
64
2.5.6
Conclusions
64
Chapter 3 A multi-attribute Conservation Value Index
3.1
Abstract
66
66
3.2 Introduction
67
3.3
Methodology
71
3.4
Results
74
3.5
3.4.1
Site ordination
74
3.4.2
Benthic attributes
76
3.4.3
Fish attributes
79
3.4.4 Scoring attributes
83
3.4.5
87
Modelling attribute values
3.4.6 Final Index
92
Discussion
98
3.5.1
Site ranking
98
3.5.2
Benthic attributes
99
3.5.3
Fish attributes
100
3.5.4
Scoring attributes
101
3.5.5
Modelling attribute values
102
3.5.6
Final Index
103
3.5.7
Conclusion
104
VIII
Chapter 4 Case Study I. Wakatobi Marine National Park, Indonesia
4.1
Abstract
106
4.2 Introduction
4.3
4.4
107
4.2.1
Background
107
4.2.2
Monitoring Program
107
Methodology
109
4.3.1
Benthic assemblage
109
4.3.2
Fish assemblage
110
4.3.3
Data analysis
111
4.3.4
CVI assessment
111
Results
4.4.1
4.5
106
112
Benthic assessment
112
4.4.2 Fish assessment
117
4.4.3 Wakatobi MNP assessment
121
4.4.4
Large interval monitoring
126
4.4.5
CVI assessments
128
Discussion
136
4.5.1
136
Benthic assessment
4.5.2 Fish assessment
137
4.5.3 Wakatobi MNP assessment
138
4.5.4
Large interval monitoring
139
4.5.5
CVI assessment
140
4.5.6
Conclusions
142
IX
Chapter 5 Case Study II. Ras Mohammed National Park, Egypt
144
5.1
Abstract
144
5.2
Introduction
146
5.3
5.4
5.5
Chapter 6
5.2.1 Background
146
5.2.2 Threats to the Ras Mohammed National Park
146
5.2.3 Monitoring program rationale
148
5.2.4 CVI assessment
151
Methodology
152
5.3.1
Benthic assemblage
152
5.3.2
Fish assemblage
153
5.3.3
Threats to Ras Mohammed
154
5.3.4
CVI
154
Results
155
5.4.1
Benthic assemblage
155
5.4.2
Fish assemblage
161
5.4.3
Threats to Ras Mohammed
164
5.4.4
CVI assessment
166
Discussion
168
5.5.1
Benthic assemblage
168
5.5.2
Fish assemblage
172
5.5.3
Threats to Ras Mohammed
175
5.5.4
CVI assessment
177
General Discussion
178
6.1
Optimised survey methods
178
6.2
Validity of Conservation Value Index
180
X
6.3
CVI as a management tool
182
6.4
Status of the Wakatobi Marine National Park
184
6.5
Status of the Ras Mohammed National Park
185
6.6
Further study
186
6.7
Aims of this thesis
187
References
189
Appendix I
211
XI
List of Figures
Chapter 1
Introduction
Figure 1.1 Location of the Wakatobi Marine National Park, Indonesia and
the position of the three study sites within the park
22
Figure 1.2 Location of the Ras Mohammed National Park, Egypt
28
Chapter 2
Optimised reef survey methodology
Figure 2.1 Coral genera-Distance curve for the Wakatobi MNP. (a) Indicates
the distance required to identify 95% of the coral genera present. (b)
Indicates that 50m transects are able to identify >75% of the coral
genera present. (c) The transect distance necessary to identify 50%
of coral genera present
50
Figure 2.2 Survey effort (distance) versus time taken to complete benthic
survey for six different techniques including data entry and analysis.
[1m, 0.5m and 0.25m point count techniques, continuous line
intercept technique, photo quadrat and video frame techniques]
52
Figure 2.3 In-water time taken to complete multiple 50m transects using the
six different sampling techniques. Dashed line indicates average dive
time. [1m, 0.5m and 0.25m point count techniques, continuous line
intercept technique, photo quadrat and video frame techniques]
52
Figure 2.4 MDS plot to show the similarity between the different survey
methodologies [S=Sampela, R=Ridge and N=NTA] (P=Point
transects at 1m, 50cm and 25 cm intervals, P=Photo quadrat,
L=continuous LIT and V=Video)
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53
Figure 2.5 Mean (±s.e.) benthic category values surveyed by non-expert
volunteers compared with experienced surveyors data
55
Figure 2.6 Benthic categories recorded by six volunteers along the same
continuous line transect (Volunteers a-f) [mean(±s.e.) % cover; n=6]
56
Figure 2.7 Further benthic parameters recorded by six different volunteers
along the same continuous line transect (Volunteers a-f) [mean(±s.e.)
% cover; n=6]
57
Figure 2.8 Dendrogram to show percentage similarity between benthic
composition recorded by six volunteers (a-e) along the same
continuous line transect (Square root transformed Bray-Curtis Group
average)
57
Figure 2.9 Power curve to identify required sample size at α=0.05 to detect
small (0.1), medium (0.25) and large (0.40) effects
58
Figure 2.10 Power curve to illustrate the trade off necessary between α
(Type I error) and 1-β (Type II error) to detect three levels of Effect
size, [n=108]
Chapter 3
59
A multi-attribute Conservation Value Index
Figure 3.1 PCA co-variance ordination plot of components 1 & 2 to identify
site classifications. Arrow indicates direction of perceived reef health
(low to high) [Site key:1-Hoga NTA, 2-Ridge 1, 3-Kaledupa, 4-Pak
Kasims, 5-Kaledupa Double Spur, 6-Sampela]
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76
Figure 3.2 Dendrogram of Bray-Curtis (Group average) cluster analysis of
all summary attributes at all six study sites [site key; 1. Ridge,
2.Kaledupa Double Spur, 3. Kaledupa, 4. Pak Kasims, 5. Hoga
NTA, 6. Sampela]
77
Figure 3.3 PCA plot to identify site classifications, PC1 & PC2 of
summary benthic data overlaid with vectors indicating influence of
each individual attribute [site key; R1- Ridge, KDS-Kaledupa
Double Spur, KAL- Kaledupa, PK-Pak Kasims, NTA-Hoga NTA,
SAM-Sampela][Benthic categories:HC-Hard Coral, SC-Soft Coral,
SPG-Sponge, CR- Coral Rubble, ALG- Macro-alge, S-Sand, DCRecently Dead Coral, RK –Bare Rock, OTH- Other]
79
Figure 3.4 PCA plot to identify site classifications, PC1 & PC2 of
summary fish assemblage data overlaid with vectors indicating
influence of each individual attribute. [Site key; R1- Ridge, KDSKaledupa Double Spur, KAL- Kaledupa,PK-Pak Kasims, NTAHoga NTA, SAM-Sampela]
81
Figure 3.5 Proportion of the fish community belonging to the six trophic
classes identified in (a)2002 and (b)2005 [n=6]
82
Figure 3.6 Regression modelled benthic attribute values (%) over ten year
period
89
Figure 3.7 Regression modelled fish community attribute values over ten
years following current trends. (Family richness 1250m-3 on left
axis, abundance per 1250m3 on right axis)
91
Figure 3.8 Comparison of modelled regression data (2002 +5 years) and
surveyed park mean (±s.e.) data from 2007
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91
Figure 3.9 Flow diagram of the CVI procedural steps
95
Figure 3.10 Output for Conservation Value Index classification of sites
within the Wakatobi Marine National Park (2002 Site means).
Image courtesy LandSAT Millenium coral reef archive
96
Figure 3.11 Output for Conservation Value Index classification of sites
within the Wakatobi Marine National Park (2005 Site means).
Image courtesy LandSAT Millenium coral reef archive
97
Figure 3.12 Grid style output of CVI values [2002 solid, 2005 open], xaxis shows benthic component (A-E), y-axis shows fish component
(1-5)
Chapter 4
98
Case Study I. Wakatobi Marine National Park, Indonesia
Figure 4.1 Percentage cover of five benthic attributes at the six study sites
within the Wakatobi MNP over six years. (a) Hard coral cover, (b)
total live benthic cover, (c) Mean hard coral colony size in
centimetres, (d) percentage coral rubble cover, (e) percentage
macro-algal cover.
113
Figure 4.2 Association between hard coral cover and coral rubble cover
within the Wakatobi MNP
116
Figure 4.3 Linear regression showing changes in hard coral cover at the
six study sites within the Wakatobi MNP
117
Figure 4.4 Mean(±s.e.) fish abundance 1250 m-3 at each of the six study
sites in the Wakatobi MNP over six years[n=9]
XV
118
Figure 4.5 Mean(±s.e.) fish species richness 1250m-3 at each of the six
study sites in the Wakatobi MNP over six years [2002=White bars
-2007=Black bars][n=9]
119
Figure 4.6 Mean (±s.e.) number of Serranidae and Epinephelidae species
present at each of the six study sites in the Wakatobi MNP over six
years [2002=White bars -2007=Black bars][n=9]
120
Figure 4.7 Mean (±s.e.) number of Scaridae species present at each of the
six study sites in the Wakatobi MNP over six years [2002=White
bars -2007=Black bars][n=9]
120
Figure 4.8 Mean(±s.e.)hard coral cover within the Wakatobi over the six
year period[n=54]
122
Figure 4.9 Mean (±s.e.) values for four benthic attributes within the
Wakatobi MNP over the six study years[n=54]. (a) percentage
coral rubble, (b) percentage cover of macro-algae, (c) percentage
total live cover,(d) number of hard coral colonies per transect
123
Figure 4.10 Mean(±s.e) fish abundance 1250m-3 within the Wakatobi
MNP over the six study years [n=54]
124
Figure 4.11 Mean (±s.e.) values for four fish Family richness attributes
within the Wakatobi MNP over the five study years [n=54]. (a)
Scarid richness, (b) Serranid/ Epinephelid richness, (c)Pomacentrid
richness, (d) Labrid richness
126
XVI
E
Figure 4.12 Change in percentage cover of four benthic attributes at the
three West Kaledupa sites over the five year study period[n=9].
[Sites: SOM-Sombano, MON-Montigola, TAO-Taou] [HC-Hard
coral, SC-Soft coral, CR-Coral rubble, ALG-Macro-algae]
126
Figure 4.13a. Conservation Value Index output for six sites around
Kaledupa island 2002
131
Figure 4.13b. Conservation Value Index output for six sites around
Kaledupa island 2007
132
Figure 4.14 Grid style CVI output to show direction of change in index
scores for the six study sites within the Wakatobi MNP(a)Ridge 1,
(b)Kaledupa Double Spur, (c)Kaledupa, (d)Pak Kasims,(e)Hoga
NTA, (f)Sampela [2002-closed circle, 2003-closed square, 2004closed triangle, 2005-open circle, 2006-open triangle, 2007-closed
circle]
134
Figure 4.15 Grid style output representing mean (±s.e.) CVI values
throughout Wakatobi MNP from 2002 to 2007
Chapter 5
135
Case Study II. Ras Mohammed National Park, Egypt
Figure 5.1. Mean (±s.e., n=8) hard (hermatypic) coral cover on upper[5]
and lower[10] reef slopes at the study sites. Mean site values for
2005 are shown for comparison where available [ Site Key; SOShark Observatory, NB-North Bereika,SB-South Bereika, VCMarsa Ghozlani, OQ-Old Quay, RUS-Ras Umm Sid]
XVII
156
Figure 5.2 Variation in mean (±s.e., n=8) total live benthic cover between
sites [Site Key; SO-Shark Observatory, NB-North Bereika,SBSouth Bereika, VC-Marsa Ghozlani, OQ-Old Quay, RUS-Ras
Umm Sid]
158
Figure 5.3 Breakdown of dominant benthic cover by category [Benthic ke;
RK-Bare Rock, ALG-Macro-algae,DC-RecentlyDead Coral,CRCoral Rubble,SC-Soft Coral,HC-Hard Coral] [ Site Key; SO-Shark
Observatory, NB-North Bereika,SB-South Bereika, VC-Marsa
Ghozlani, OQ-Old Quay, RUS-Ras Umm Sid]
158
Figure 5.4 Mean(±s.e., n=8) hard coral Generic richness [Site Key; SOShark Observatory, NB-North Bereika,SB-South Bereika, VCMarsa Ghozlani, OQ-Old Quay, RUS-Ras Umm Sid]
159
Figure 5.5 Mean (±s.e., n=8) hard coral colony size [ Site Key; SO-Shark
Observatory, NB-North Bereika,SB-South Bereika, VC-Marsa
Ghozlani, OQ-Old Quay, RUS-Ras Umm Sid]
159
Figure 5.6 Mean(±s.e., n=8) number of hard coral colonies at each site
[Site Key; SO-Shark Observatory, NB-North Bereika,SB-South
Bereika, VC-Marsa Ghozlani, OQ-Old Quay, RUS-Ras Umm Sid]
160
Figure 5.7 PCA plot of fish assemblage attributes overlaid with vectors
indicating influence of individual attributes
162
Figure 5.8 Dendrogram of cluster analysis (Bray-Curtis, group average
linkage) of fish assessment metrics
Figure 5.9 Incidence of mean(±s.e.) physical damage to hard corals
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163
165
Figure 5.10 Satellite image of Ras Mohammed National Park with
overlaid 2006 CVI values for the study sites (Source: Landsat
millennium coral reef archive)
166
Figure 5.11 Grid style output indicting changes in CVI scores between
2005 and 2006
168
XIX
List of Tables
Chapter 1
Table 1.1 Common reef assessment techniques
Chapter 2
Optimised reef survey strategy
Table 2.1 Benthic classification categories
Chapter 3
7
47
Development of a multi-attribute Conservation Value Index
Table 3.1 Varied ranking of sites according to uni-variate methods of
assessment (values in parentheses) [Site key: NTA-Hoga NTA,
R1-Ridge1, KDS-Kaledupa Double Spur, Kal-Kaledupa, PK-Pak
Kasims, SAM-Sampela]
74
Table 3.2 Scoring criteria for benthic attributes
86
Table 3.3 Scoring criteria for fish assemblage attributes
88
Table 3.4 Regression values used to model changes in attribute values
according to current trends [nd= no data]
90
Table 3.5 CVI values for hypothetical sites modelled from regression data
for -5, +5 and +10 years from 2002 data
92
Table 3.6 Classification of sites within the Wakatobi Marine National Park
with the proposed Conservation Value Index (2002) [Site key: R1Ridge 1, KDS-Kaledupa Double Spur, KAL-Kaledupa, PK-Pak
Kasims, NTA-Hoga NTA, SAM-Sampela]
93
Table 3.7 Classification of sites within the Wakatobi Marine National Park
with the proposed Conservation Value Index (2005) [Site key:R1Ridge 1, KDS-Kaledupa Double Spur, KAL-Kaledupa, PK-Pak
Kasims, NTA-Hoga NTA, SAM-Sampela ]
XX
93
Chapter 4
Case Study I. Wakatobi Marine national Park, Indonesia
Table 4.1 Conservation Value Index scores and classification of the six
Wakatobi MNP study sites by year
Table 4.2 Further outputs to aid clarity for varied audience
Chapter 5
129
135
Case Study II. Ras Mohammed National Park, Egypt
Table 5.1 Scleractinian coral cover at the six study sites in the Ras
Mohammed National Park (n=4) in 2006 [c=Reef crest; s=Upper
reef slope] Mean (±s.e.) values with maximum and minimum
values shown
156
Table 5.2 Mean(±s.e.) fish abundance per 1000m3 with minimum and
maximum counts for each study site on the reef crest(c) and
upper reef slope (s) [ Site Key; SO-Shark Observatory, NBNorth Bereika,SB-South Bereika, VC-Marsa Ghozlani, OQ-Old
Quay, RUS-Ras Umm Sid]
162
Table 5.3 CVI benthic and fish values with final CVI codes [C-Reef
Crest, S-Upper Reef Slope]
167
XXI
List of Abbreviations
AIMS – Australian Institute of Marine Science
ALG – Macro algae
ANOVA – ANalysis Of VAriance
CAP – Community Analysis Package
CCA- Crustose Coralline Algae
COREMAP – World bank funded Indonesian COral REef MApping Program
COTs – Crown Of Thorns starfish (Acanthaster planci)
CR – Coral Rubble
CRRU – Coral Reef Research Unit, University of Essex
CVI – Conservation Value Index
DC – Recently Dead Coral
EEAA – Egyptian Environmental Affairs Agency
EIA – Environmental Impact Assessment
GCRMN – Global Coral Reef Monitoring Network
GIS – Geographic Information System
GPS – Global Positioning System
HC – Hard Coral
IBI – Index of Biotic Integrity
IUCN – International Union for the Conservation of Nature
KAL – Kaledupa (Indonesian study site)
KDS – Kaledupa Double Spur (Indonesian study site)
XXII
LC – Total Live Cover
LIPI – Lembaga Ilmu Pengetahuan Indonesia (Indonesian Institute of Sciences)
LIT – Line Intercept Transect
MDS – Multi-Dimensional Scaling
MON – Montigola (Indonesian study site)
MNP – Marine National Park
NB – North Bereika (Egyptian study site)
NGO – Non-Governmental Organisation
NP – National Park
NTA – No Take Area
OQ – Old Quay (Egyptian study site)
OTH – Other benthic cover
PCA – Principal Component Analysis
PERSGA - The Regional Organization for the Conservation of the Environment of the Red
Sea and Gulf of Aden
PIT – Point Intercept Transect
PK – Pak Kasims (Indonesian study site)
PRIMER – Plymouth Routines in Multivariate Ecological Research software package
R1- Ridge 1 (Indonesian study site)
RK – Bare rock substratum
RUS – Ras Umm Sid (Egyptian study site)
SAM – Sampela (Indonesian study site)
SB – South Bereika (Egyptian study site)
XXIII
SC – Soft Coral
SCUBA – Self Contained Underwater Breathing Apparatus
SO – Shark Observatory (Egyptian study site)
SOM – Sombano (Indonesian study site)
SPG – Sponge
SPSS – Statistical Package for the Social Sciences software
SST – Sea Surface Temperature
TAO – Taou (Indonesian study site)
TNC – The Nature Conservancy
UVC – Underwater Visual Census
VC – Marsa Ghozlani/ Visitor Centre (Egyptian study site)
WMNP – Wakatoni Marine National Park
WWF – World Wildlife Fund
XXIV
Chapter 1. Introduction
CHAPTER 1. Introduction
1.1 The importance of coral reefs
Coral reefs are by definition, three dimensional, shallow water structures
dominated by Scleractinian corals and are the most biologically diverse of shallow
water marine ecosystems. It is believed that although coral reefs represent less than
0.2% of total ocean area, they contain more species per unit area than any other
ecosystem (Ahmed et al., 2004). Estimates of the total number of people reliant on
coral reefs for their food resources, range from 500 million (Wilkinson, 2004) to over
one billion (Whittingham et al., 2003). Some 30 million of the worlds’ poorest and
most vulnerable people in coastal and island communities are totally reliant on reefbased resources as their primary means of food production, sources of income and
livelihoods (Gomez et al., 1994; Wilkinson, 2004). As well as providing direct food
resources, coral reefs provide coastal protection and sustain valuable tourism
industries (Moberg & Folke, 1999; Spalding et al., 2001). Due to increasing
population size, the reliance on reef resources is set to increase over the coming
decades.
Due to the importance of coral reefs to local communities and the increasing
level of natural and anthropogenic impacts upon them, accurate monitoring and
assessment of reef condition is necessary to allow the management and sustainable use
of these resources.
1.2
Threats to coral reefs
Most coral reefs around the world are over-exploited and damaged by over-
extraction, pollution, excess sediment and inappropriate development. Coral reef
1
Chapter 1. Introduction
scientists also predict massive destruction of coral reefs in coming decades due to the
effects of global climate change. Their loss will destroy the social fabric of many
coastal communities and ruin the massive tourism industry that supports many of the
developing tropical countries (Wilkinson, 2004). The current State of the Reefs report
(Wilkinson, 2004) states that some 20% of the worlds coral reefs have already been
destroyed and show no prospect of recovery, while a further 24% are under imminent
risk of collapse through human induced pressures and a further 26% are under a
longer term threat of collapse. Bryant et al., (1998) classified the threat to coral reefs
worldwide according to a number of common factors such as coastal development,
over-exploitation and destructive fishing practices, impacts of inland pollution and
soil erosion and from marine based pollution. The study observed that of the worlds’
reefs, 27% were at high risk, 31% at medium risk and just 42% were considered to be
at a low level risk from the combined factors. A report by Hughes (1994) showed that
many Caribbean coral reefs have shown a dramatic decline over the last few decades
with reductions in coral cover of up to 80%. He noted that in Jamaica a dramatic
phase-shift had occurred, producing a system dominated by fleshy macro algae, often
with over 90% cover.
Coral reefs around the world continue to decline due to both natural and
anthropogenic influences. Threats are becoming more serious because of the high
demand for marine sourced products and weak enforcement of existing laws in many
regions (Hidayati, 2003). McLanahan et al., (2002) noted that despite the potential
long term stability of coral reefs in the face of many disturbances, concern was
increasing that anthropogenically induced environmental changes may be beginning to
exceed the limits of tolerance of reef organisms to factors such as UV radiation, water
temperature and human predation. Humans may be affecting the frequency, intensity,
2
Chapter 1. Introduction
distribution and duration of many types of disturbance. By fishing out keystone
predators and increasing nutrient concentrations, humans may be inadvertently
contributing to outbreaks of coral predators such as Acanthaster planci and
coralivorous gastropods (e.g. Drupella spp.). Such fishing activity is now pervasive
throughout the tropics and now extends further offshore than in the past.
Unsustainable fisheries reduce the abundance of many target species and can also
remove whole functional groups, such as grazing Scaridae which can lead to phase
shifts from coral to algal dominated systems. Predicting such shifts, because of the
increasing instability of coral reef ecosystems before their collapse, has often been
unrecognised, even on heavily studied reefs. These phase shifts of tropical reefs to less
desirable states can have devastating economic effects on maritime developing nations
(Bellwood et al., 2004). Hodgson (1997) reported that pollution is often diffuse and
that many tropical watersheds are heavily influenced by human activity. This
extensive deterioration again highlights the need for efficient monitoring and
assessment methods (McKenna et al., 2001; Bellwood et al., 2004).
Many coral reef countries lack the resources of trained personnel, equipment
and finances to effectively conserve coral reefs, establish MPA’s and enforce existing
regulation. This lack of resources is often exacerbated by a poor awareness of
problems facing coral reefs and their significance to local economies, and inadequate
political will to tackle difficult environmental problems (Wilkinson, 2004).
Recently studies have focussed on the predicted impacts of global climate
change, mainly in the form of increasing temperatures and acidification of the worlds’
oceans. These changes are predicted to cause further decline of coral reefs, from shifts
in community composition to complete loss of reef systems (Hoegh-Guldberg, 2005;
Kleypass et al., 2005).
3
Chapter 1. Introduction
Marine Protected Areas are increasingly being established and used to protect
valuable marine resources, such as coral reefs and their associated biodiversity. These
areas restrict exploitation and usage of marine resources to allow the sustainable use
of the resource (see Ward et al, 2001 for a review). However, the science of MPA
design and management is complex and still being investigated (PISCO, 2002).
1.3
Monitoring coral reef condition
Grigg (1999) stated that monitoring programs are a pre-requisite for any sort of
competent management, i.e. before management decisions can be made, it is
necessary to know what is there and in what condition, as well as the level of threat
faced. With the aforementioned limited resources of many tropical nations, coupled
with the increasing rates of over-exploitation and degradation, finding an effective and
methodical way to prioritise areas for conservation efforts is critical (McKenna and
Allen, 2000). In addition to the identification of sites for MPA’s and other
conservation efforts, a systematic monitoring programme also generates a number of
other beneficial information including; baseline data to assess the impact of
management actions and success of MPA after establishment; to determine the
biological effects of pollution; to monitor the presence of introduced or alien species
and to monitor their impacts. The data may also be useful to monitor the long term
effects of climate change (Edgar et al., 1996).
Although coral reef monitoring programs around the world generate important
volumes of data and information on various coral reef parameters, standardised and
easily accessible data from these programs is often lacking (Noordeloos et al., 2004).
The same report from the 2004 International coral reef monitoring workshop also
recommended that the structure of national status reports for the Global Coral Reef
4
Chapter 1. Introduction
Monitoring Network (GCRMN) be standardised and contain more visually
represented summary information to benefit non-expert decision makers. Tun and
Wilkinson (2004) also suggested the adoption of standardised monitoring and
reporting protocols suggested by the GCRMN as coral reefs have been , and continue
to be, a difficult ecosystem to monitor and assess.
Karr and Chu (1999) suggest that the first step toward effective biological
monitoring and assessment of fresh waters is to realise that the goal is to measure and
evaluate the consequences of human actions on biological systems. The relevant
measurement endpoint for biological monitoring is biological condition, detecting
change in that endpoint, comparing the change with a minimally impacted baseline,
identify the causes of change and communicate all of this to policy makers and
stakeholders, these are the combined tasks of biological monitoring programs. This
view was contrary to that of Gomez et al., (1994) who noted that reef condition is
greatly affected by changes in both biotic and abiotic factors, whether due to natural
or anthropogenic influence. Natural changes also constitute a stress, bringing about
deleterious effects on reef condition if extreme or frequent, and hence require
monitoring to avoid problems associated wth shifting baselines (Sheppard, 1995).
In summary, biological monitoring studies must measure present biological
condition and compare that condition with what would be expected in the absence of
stress. Biological monitoring documents any divergence from expected baseline
conditions and associates divergences with knowledge of human or natural activity in
the area. Karr and Chu (1999) also suggest that communicating the consequences of
human activity to all parts of society is perhaps ‘the greatest challenge facing modern
ecology’.
5
Chapter 1. Introduction
1.4
Current assessment methods
The first attempt to introduce quantitative methods for the survey of benthic coral
reef habitats was published in 1953 by Fosberg and Sachet (cited in Loya, 1979). It
wasn’t until the early seventies when the likes of Loya and Slobodkin (1971, cited in
Loya, 1972) identified the similarity between benthic coral reef communities and
terrestrial plant communities. This led them to adopt the use of concepts and
techniques used by plant ecologists to study coral reefs. After considering several
terrestrial techniques for studying plant communities, the line transects of Greig-Smith
(1983) were adopted for a comparative study of different reef zones by Loya and
Slobodkin (1971, cited in Loya, 1972).
The selection and monitoring of sites for representative MPA’s first requires
classification of the environment in question. Edgar et al., (1996) suggested that
although costs are substantial, a biological survey programme is unavoidable when
formulating an integrated MPA strategy and that the benefits of such surveys far
outweigh the costs.
Integrated with the debate about, and co-evolving with, different survey
methods, has been the method of habitat assessment once the survey data has been
collected (Table 1.1). Coral cover was found by Porter (1972a, 1974, cited in Loya,
1976) to positively correlate with species diversity on Caribbean reefs, however, the
correlation between the two was found to be negative on Indo-Pacific reefs (where
cover was high, diversity was low and vice versa), (Grigg and Maragos,1974; Loya
1972, 1976). Loya’s early studies in coral reef zonation measured species richness,
number of colonies, percentage of live coral cover and diversity. Loya used Shannon’s
diversity index (Shannon and Weaver, 1949) to measure species diversity. The notion
of diversity was described by Hill (1973) to be the effective number of species present
6
Chapter 1. Introduction
in a sample, as did Mason (1977) in suggesting species richness alone was a better
indicator of differences in communities than other measures of diversity. Of the many
proposed measures of diversity, Simpson’s and Shannon’s are the two most widely
used (Zahl, 1977). A review by Magurran (1988) noted that diversity indices are often
seen as indicators of the wellbeing of ecosystems. She identified the usefulness of
information theory indices for this function. The study reiterated the advantages of
each of the most well known and used. It has been reported by many that no single
diversity index is universally superior (Routledge, 1979; Magurran, 1988; Pennisi,
1997; Ben-Tzvi et al., 2004).
Table 1.1 Common reef assessment techniques
Technique
Uni-/multivariate
Units
Reference
Coral cover
Univariate
%
Loya, 1976
Coral Species richness
Univariate
Number
Loya, 1976
Coral diversty
Bivariate
No unit
Loya, 1976
Reef Condition Index
Univariate
Category
Gomez & Alcala, 1979
Coral Mortality Index
Multivariate
Ratio
Gomez et al., 1994
Conservation Class
Multivariate
Graphical
Edinger & Risk, 2000
Deterioration Index
Bivariate
Ratio
Ben-Tzvi et al., 2004
Mulitvariate
No unit
Hodgson 1999
ReefCheck Coral Reef
Health Index
These diversity indices are heavily influenced by sampling effort and sample
size must realistically reflect the diversity of an ecosystem, as was noted by Shannon
and Weaver (1949) in their original publication, as well as in a study by Taylor (1986).
7
Chapter 1. Introduction
Magurran (1988) identified the strength of Shannon’s Index to be the best
discriminator between sites and samples, as well as noting the value of diversity
measures to conservation and monitoring the wellbeing of an ecosystem.
As well as species diversity, Shannon’s index can be used as a measure of
topographic diversity by using growth form data in the formula instead of species
(Loya, 1979), a factor which it is now realised exerts a major influence in the
community structure of coral reefs (Roberts and Ormond, 1987).
Values of diversity have been calculated from data of many taxonomic levels
(see Hughes, 1978 for review) and the same patterns are detectable at each level
although values are lower at higher taxonomic levels (Bouchon, 1981). Hughes (1978)
data showed no significant difference in diversity values when calculated from species
or Genera. This was supported by Krebs (1999) who also stated that there was no
reason why Generic data could not be analysed. Standardisation of surveys to Genera
would reduce problems in survey comparison from data of different taxonomic groups.
Identification of corals to genus is relatively simple compared with classification by
species.
It is only with the advent of new molecular techniques that definitive
classifications and doubts about coral speciation can be established, whereas Generic
identification can be achieved in the field by non-specialists with relatively little
training, a point which is vital in many developing countries.
That living corals themselves are highly productive and account for the net
production of a coral reef (Yap et al., 1994), as well as being the actual reef building
organisms, means that they are of vital importance to reefs and should be central to
any form of assessment of coral reef health. On Caribbean reefs macro-algal
communities can often dominate reefs (Klumpp and McKinnon,1992) and so their role
is also important to any form of overall assessment. Inter-regional differences in reef
8
Chapter 1. Introduction
community structure mean that direct comparison of studies assessed using univariate
indices is difficult.
Other indices have been specifically developed to survey coral reefs, such as
the Reef Condition Index, the Coral Mortality Index (Gomez et al., 1994),
Conservation Class (Edinger and Risk, 2000), and most recently Deterioration Index
(Ben-Tzvi et al., 2004). These methods utilise multivariate assessment techniques that
encompass several factors into the outcome as opposed to measures of diversity or
percent cover which are measures of single factor univariate indices. The Reef
Condition Index (RCI) developed by Gomez and Alcala (1979) simply converts the
measured percentage cover of hermatypic corals into one of four categories (Excellent,
Good, Fair, and Poor). This was the method of reef classification used by LIPI
(Indonesian Institute of Ocean Science) as stated by Suharsono at a Coral Reef
Assessment workshop (see Harger, 1995), drawing the response from both Tomascik
and Johannes that high coral cover on a reef does not necessarily represent good
health such as a site with a high percentage cover of a monospecific stand of a single
species. Contrary to this, a reef may have low cover of hermatypic corals but be very
diverse and provide habitat for many other organisms or be in ‘good health’. These
differences may be due to regional factors and not simply reef condition. At the same
meeting, Done suggested that use of qualitative terms such as ‘good or bad’ should be
avoided, while Suter (1993) criticised the general use of terms such as ecosystem
‘health’ as it is not a scaler operational property.
Gomez et al., (1994) then replaced the RCI with the Coral Mortality Index
(CMI), a simple ratio between the proportions of live and live plus dead coral on a
reef. This was developed as they believed that coral cover per se is not a reliable
indicator of reef health, since large areas of the reef may be unavailable to corals even
9
Chapter 1. Introduction
in unspoilt systems. However, this can lead to huge variation in the outcome
dependent upon what is classified as dead coral. The COREMAP (2001) report
questioned the usefulness of this mortality index and suggested it had no statistical
value and should not be used for reef assessment. The COREMAP study
recommended the use of live coral cover as the best indicator of reef condition.
Another addition to the reef assessment ‘toolbox’ was suggested by Edinger
and Risk (2000). They suggested that coral morphology could predict the conservation
value of a reef, and that this could be achieved with the use of non-specialist survey
teams as no taxonomy was involved. This method would allow the bridging of the gap
between scientists and managers by allowing the direct comparison between studies as
well as increasing social capital. The method is based on r-K-s life history triangles,
adapted from the work of Grime (2001) on plant communities. Although, this method
is simplistic, some of the categorisation of coral life strategies is questionable, and
Moore (1978, cited in Endean and Cameron, 1990) states that the use of r-K-s
selection for marine invertebrates is misguided. It is however, valuable to note the
assertion that to be useful in South-East Asia, where very little taxonomic expertise
exists (Wilkinson and Chou, 1997), measures of coral reef conservation value should
not be based at the species level. This point was also identified by Bouchon (1981)
who cited the main problems in comparison of studies were the inconsistent
methodology and the uncertainties of Scleractinian taxonomy.
The Deterioration Index (DI) proposed by Ben-Tzvi et al., (2004) is a ratio
between mortality and recruitment of branching corals. Knowlton (2001) as well as
Edinger and Risk (2000) suggest the usefulness of functional groups for monitoring,
as utilised by the DI. Due to the nature of the ratio, when a system is stable, a low DI
10
Chapter 1. Introduction
score will always occur, regardless of live cover or diversity, so any deviation
indicates a perturbance within the system.
As previously mentioned, the only truly global survey effort and hence data set
is that of ReefCheck (Hodgson, 1999). Once gathered, the data is entered into a Coral
Reef Health Index (CRHI) which is scored according to the abundance of indicator
organisms. The highest abundance for each indicator worldwide was used as a
maximum possible value to allow the determination of lower, middle and upper thirds.
Then for each site a value of zero to three was assigned to each indicator score
dependent upon the level of mean abundance in comparison with the cut off level for
each third. The overall index is a sum of the different indicator scores for a site.
Hodgson (1999) also suggested a Distance-Population Index (DPI) calculated by
assigning scores for the distance of a site to the nearest city and its population size.
As reported by Ben-Tzvi et al., (2004) and Ablan et al., (2004), and is also
apparent from the proliferation of different indicator methods available, there are no
well-accepted reliable means of indication for a ‘healthy reef’ and none of the
commonly used parameters is accepted as an indication that reliably represents reef
community status. McClanahan et al., (2002) identified the great need to monitor
coral reef resources and develop a scientific infrastructure and a conceptual platform
for the interpretation of the collected data. Eakin et al., (1997) had also previously
identified a particular need for the ability to quickly and accurately assess the health of
ecosystems and the level of threat that they face, and called for further research to
develop criteria and cost-effective procedures for the assessment of coral reef health.
11
Chapter 1. Introduction
1.5
Multimetric Index of Biotic Integrity
To provide stakeholders with the information necessary for successful
management of the fisheries and reefs within an area, as well is to increase social
capital (Pretty, 2003), it is necessary to have a method of reef assessment that can be
understood by the local community, many of whom are poorly educated. According to
Karr and Chu (1999), policy makers, citizens and scientists faced with making
decisions about complex systems need multiple levels of information. Ablan et al.,
(2004) identified the similarity between biological metrics and economic metrics used
in economic analysis (e.g. FTSE100, retail price index).
Therefore, there is the need for a simple non-specialist means of transferring
information about reef and fisheries quality to the stakeholders. This also allows an
easily understandable overview to be given to policymakers and funding agencies.
Several studies have identified problems with classifying habitats by the use of
a single factor index (Loya, 1972; Pielou, 1972; Hughes 1978). The development of a
single readily understood multivariate/ multimetric index would be of greater use than
the reporting of numerous or single factor indices (Extence et al., 1987). In his
publication ‘Ecological evaluation for conservation’, Spellerberg (1981) defined
ecological evaluation as “finding a mathematical numeric expression based on
ecology which can be used to determine the conservation requirements of a species or
habitat or to assess the impact of an action on that species or habitat”. Mumby and
Harbourne (1999) stated that habitat classification schemes should be determined
objectively and have an intuitively understandable structure, when classifying the
marine habitats of Belize. Any index produced should fit the seven requirements of an
index for everyday use as defined by Extence et al., (1987).
12
Chapter 1. Introduction
Margules and Usher (1981) stated that indices derived from the combination
of heterogeneous data have been proposed but their general applicability was yet to be
shown, although Maloney (1974) combined multiple attribute outcomes into an
overall index of illness. Margules and Usher (1981) also suggested that the
development of such indices were necessary for effective conservation and predicted
that integrating several criteria into a single index would become commonplace by the
1990’s. In fact Sokal and Rohlf (1973, cited in Green, 1979) and Pikul (1974) both
described an index as “a mathematical combination of two or more factors which has
utility in an interpretive sense”. Indicators can also be used as static measures to
assess the instantaneous state of ecosystems.
Bellwood and Hughes (2001) also identified the need to shift focus from
individual taxa to a broader, habitat based management strategy. McKenna and Allen
(2000) suggested the use of indicator groups along with other variables such as threat
level and socio-economic issues. The development of indicators of ecosystem health
was called for in Chapter 40 of Agenda 21 (Ablan et al., 2004).
The work of Karr (1981, 1991, and Karr and Chu, 1999) has lead the way in
the development of multimetric indexes of biotic integrity in their extensive work on
freshwaters. Their work identified that multimetric biological indexes calculated from
ambient biological monitoring data provide a similar integrative approach for
measuring condition and diagnosing causes in complex ecological systems. The
resulting multimetric approach to biological monitoring is dependent upon the
selection of suitable metrics that reflect diverse responses of biological systems to
human activities. Multimetric biological indexes incorporate levels of organisation
from individuals to landscapes and the best multimetric indices are more than a
13
Chapter 1. Introduction
community assessment as they contain measures of condition in individuals,
populations, communities, ecosystems and landscapes (Karr and Chu, 1999).
Some critics of multimetric indexes counter that such metrics combine and
thus lose information however, the individual metrics are not lost when combined into
a multimetric index. Each numeric value and the overall multimetric score can be
translated into words or figures suitable for a variety of audiences (Karr and Chu,
1999). The indexes are also statistically versatile, with the values of multimetric
indexes assuming a normal distribution and hence can be tested with familiar statistics.
In addition, since multimetric indexes produce a single, integrating number, it also
serves as a yardstick to rank and compare sites according to their relative condition.
However, although there have been repeated calls for the development of
multimetric IBI, supported by suitable dose response values, the successful creation of
such metrics is still proving elusive. Almost a decade has passed since the publication
of a review of biological criteria by Jameson et al., (1998) and yet little progress has
been made, meanwhile the world’s coral reefs continue to decline at alarming rates.
Those that have been developed, along with dose-response data have been difficult to
interpret or difficult to reproduce in developing countries with limited resources (e.g.
Stomatopod isotopic Nitrogen composition indicator of Risk & Erdmann, 2000).
These factors suggest that more easily interpretable attributes or measurable
ecosystem properties that vary over a range of reef conditions are needed for
implementation into multi-attribute indexes now.
Bellwood et al., (2004) identified the need for ecosystem metrics to move
beyond simply coral cover and counts of target species to include functional groups,
functional redundancy and response diversity. They identified this need to cope with
the uncertainty in a biosphere increasingly shaped by human influence.
14
Chapter 1. Introduction
Costanza et al., (1998) both defined and proposed three main components of
ecosystem health as resilience, vigour and organisation. Vigour being a measure of
system activity or productivity, organisation was defined as the number and diversity
of interactions between components while resilience refers to the ability of a system to
maintain structure and function in the presence of stress.
Jameson et al., (1998) provided a complete review of biological criteria for
coral reef ecosystem assessment and noted that the high level of natural variation on
such systems means that multiple species assemblages must be monitored. Assessing
the health of ecosystems requires the measurement of a number of indicators, but for
the assessment to have real value, they must not just address status, but also evaluate
the level of risk of the status changing to a less desirable state (Whitford, 1998). This
same study noted that, contrary to that of Jameson et al., (2001), indicator metrics
need not only involve single measurements and that combined measurements and
ratios emerge as the most sensitive indicators. Whitford takes a more complex
approach to development of metrics suggesting that mean values may not be the most
appropriate indicators and that often changes in variance are more informative and
sensitive to change.
The report from the international workshop on coral reef monitoring data
(Noordeloos et al., 2004) adopted some similar ideas suggesting that ranking various
reef scores into a summary index was desirable. The workshop also suggested that the
inclusion of summary indices on a five point scale was desirable along with a set of
text descriptors for each. Such a five point scale would provide a basis for site
comparison, promote management and the setting/ meeting of targets, be effective for
trend analysis and have a strong probability of being scientifically sound. The
workshop also suggested a two part summary statistic to describe the health of a reef:
15
Chapter 1. Introduction
the status of the reef health and a vigour or resistance index to indicate a reefs capacity
to recover from stress. Several possible metrics were also put forward, such as
summary coral cover, general abundance and richness counts, pest abundance and
metrics to assess stress or physical damage. McClanahan et al., (2002) and Bellwood
et al., (2004) both point out that functional groups and functional diversity/
redundancy are necessary metrics for modern reef health monitoring, rather than
simple abundance measures. McClanahan et al., (2002)
suggest other possible
indicators such as soft coral abundance, predator and secondary consumer abundance,
herbivorous fish diversity, while Bellwood et al., (2004) suggest that the functional
diversity of herbivores in the form of grazers, scrapers and bioeroders is vital to
identify possible phase shifts.
Karr and Chu (1999) state that the majority of their freshwater indexes contain
eight to twelve metrics, with complex ecosystems involving more metrics.
1.6
Performance criteria and management
Science and research play a major role in providing the information required to
plan and decide on management actions for coral reefs (Ablan et al., 2004). Spurgeon
(2003) reports that accurate environmental valuation is integral to the development of
appropriate pricing and charging policies, which are vital to the emerging science of
environmental economics. Fabricius and De’ath (2004) go further in stating that the
successful management of ecosystems depends on the early detection of change and
the causes of such change. Management also depends upon the communication of
scientific results to the broader public, and this can fail if the evidence of change and
causality is not synthesised in a transparent manner. Their study suggests that the most
16
Chapter 1. Introduction
appropriate way to identify ecological change should be focused on the responses of a
wide range of ecological groups rather than individual species or factors.
The wide-ranging responsiveness of multimetric biological indexes makes
them an ideal tool for judging the effectiveness of management actions. Graphs of
index values can be quickly and easily interpreted by policymakers, researchers and
citizens (Karr and Chu, 1999). They also infer that the use of a combination of
numeric and narrative descriptions that come from a multimetric index make
communication possible with virtually all levels of audience; thus education is part
and parcel of the multimetric approach. This is vital as although there have been some
local successes, current management of reefs has failed to achieve the sustainable use
of ecosystem services upon which so many are dependent at both regional and global
scales (Bellwood et al., 2004). Noordeloos et al., (2004) also remind us that the key
objective of status reporting is to provide managers, policymakers and other
stakeholders with a reliable but simple indication of whether the reefs within their
own area are in good condition, whether they are at risk from threats that may alter
reef condition and whether effective management actions are in place to deal with the
threats.
There is a wealth of studies that call for the development of such management
tools if we are to successfully protect coral reefs (Wilkinson and Chou, 1997; Bryant
et al., 1998; Edinger and Risk, 2000; Ahmed et al., 2004).
Currently the only global program to attempt this is ReefCheck, but Jameson
et al., (2001) point out that due to the non-diagnostic nature of programs such as
ReefCheck, policymakers, governments and stakeholders are not equipped to
communicate reef condition to the public or politicians, the causes of such declines,
and in turn cannot suggest remedial action. The ReefCheck WRAS website has
17
Chapter 1. Introduction
recently attempted to do this, but due to the non-diagnostic nature of the ReefCheck
data and suitability of the indicators used, incorrect conclusions and solutions are
proposed for some sites (e.g. Using ReefCheck data for the Indonesian Sampela site
suggests it is impacted by industrial pollution, when it is remote from any possible
industrial pollution source).
1.7
Survey methodologies
The community structure of coral reefs is a result of the interaction between
many complex factors and the identification of which factors to survey has a direct
effect on the assessment of reef condition. However, different scientists and managers
of Marine Protected Areas (MPA’s) go about their survey and assessment of the coral
reef environment in many different ways. Attempts have previously been made to
introduce standardised survey and assessment techniques, which would allow the
comparison of different areas of reef environment, such as those suggested by the
Global Coral Reef Monitoring Network (GCRMN), Caribbean Coral Monitoring
Program (CARICOMP), Atlantic and Gulf Rapid Reef Assessment (AGGRA) and
ReefCheck. Some of these have been region specific (AGGRA and CARICOMP),
while others have been designed only to be carried out by an organisations own highly
experienced scientists (AIMS/GCRMN). The only truly global survey technique is
that of ReefCheck. This technique does allow comparison of reef condition around the
world using a standardised technique; however the resolution of the data collected by
ReefCheck volunteers is low. The adoption of standardised methodologies for reef
survey and assessment is vital to allow the comparison of studies and reef condition
within protected areas.
18
Chapter 1. Introduction
Unfortunately, the lack of a standardised, widely accepted, protocol for reef
survey has led to the proliferation of different methods, surveyed variables and varied
definitions, making comparison between sites impossible (Oliver et al., 2004). The
GCRMN provides a selection of protocols, but again no preferred method has been
adopted (Tun and Wilkinson, 2004).
Grigg (1999) reviewed the merits and pitfalls of data collection on coral reefs
and identified that sample ‘quality’ is directly proportional to the area it covers. The
number of samples needed to make valid statistical comparisons depend on the
variance of abundance. The higher the variance (and more complex the system), the
more samples are required. The simplest way to identify the correct sample size is to
generate a species-area curve. Grigg recommends that in order to test for significance,
the variance produced by the impact must be compared to natural variability or noise.
Survey stations must be representative of the study area and be of a relevant scale.
Data collected at each site should be replicated and sampled at random. Bias can be
avoided by taking many small rather than a few large samples. The best way to
achieve these recommendations is to adopt a stratified random sampling design, where
random samples are collected within random strata (Grigg, 1999).
1.8
Study sites
1.8.1
Wakatobi Marine National Park, Indonesia
2
Sulawesi is the fourth largest island in Indonesia with an area of 159,000km
and lies between Borneo to the west and the Mollucas Islands to the east. Sulawesi
also lies on the theoretical division between fauna and flora characteristic of Asia and
Australia (The Wallace Line) and is consequently an extremely important area for
global biodiversity, evolutionary biology and biogeography (Tomascik et al., 1997).
19
Chapter 1. Introduction
Sulawesi has four provinces, including Sulawesi Tenngarra (Southeast Sulawesi)
which encompasses the Southeast peninsula of the island and the large islands of
o
o
Buton, Muna and the Tukang Besi archipelago. It lies between latitudes 3 – 6 S and
o
o
120 45’ – 124 06’ E.
The Tukang Besi archipelago is believed to have been formed in the late
Tertiary when a shallow undulating plateau subsided by several hundred metres
(Tomascik et al., 1997). Continued subsidence of the land and reef growth on the
highest points led to the formation of atolls. Escher (1920, cited in Tomascik et al,
1997) was first to describe the reefs and atolls of the Tukang Besi group.
The geology of the region is better studied than the ecology, with Best et al.,
(1989) only finding some 129 species of Scleractinian coral during the Snellius II
expedition.
The Tukang Besi islands had been subject to very little research and before
1996 research had been limited to a Dutch expedition in 1985 largely to investigate
the topography and geology of the area, although some coral identification was
conducted at some sites during this survey (Best et al., 1989). Further ecological work
in the islands has been sparse. Prior to 1996 there was no data available. Since then
surveys have been conducted by the UK based organisation Operation Wallacea from
a research centre on Hoga Island (Figure 1.1).
Operation Wallacea were invited to the Tukang Besi Archipelago to carry out
a baseline survey of the reefs and associated communities. The reefs, which fall
almost central to the coral triangle region of high diversity, were found to have both
diverse fish and benthic communities and as such were identified as an important
region, worthy of conservation.
20
Chapter 1. Introduction
Coral reefs are abundant within the Wakatobi MNP (WMNP) and to date some
396 species of hermatypic coral belonging to 68 genera and 15 families have been
recorded within the WMNP, whilst 590 species of fish have so far been officially
recorded (Pet-Soede & Erdmann, 2003).
The Wakatobi Marine National Park is the second largest MPA in Indonesia at
13900km2. The park was established in July 1996 after petitioning from the British
NGO Operation Wallacea (and its Indonesian counterpart charity the Wallacea
Development Institute), WWF, TNC and LIPI. The park is classified as IUCN
Category II, a National Park managed mainly for ecosystem protection and recreation.
The park consists of four main islands, Wangi Wangi, Kaledupa, Tomia and Binongko,
giving the area the Wakatobi acronym. There are also two large atolls to the west of
the main island chain, Karang Kapota and Karang Kaledupa. The park also includes
the smaller atolls of Lintea, Ndaa, Koromaha, Cowocowo, Koka, Runduma and
Moromaho, along with numerous smaller islands and atolls. The park contains a
population of over 90000 people who belong to two distinct ethnic groups. The
Butonese people are land based farmers, traders and craftsmen and comprise about
95% of the local population. The Bajo people are traditional fishermen, living mostly
in semi permanent villages erected on the reef flats. They are sometimes referred to as
‘sea gypsies’ as many still spend part of the year, living on their boats during fishing
excursions. Fish is the most important protein source for local people and the Bajo
provide the largest part of fish for local markets (Cullen, 2007).
In 2002 after consultation by Operation Wallacea the communities of the
island of Kaledupa formed an island level committee comprising representatives from
each of the 22 villages. The committee has been empowered to manage the Kaledupa
Stakeholder Area, with scientific advice offered by Operation Wallacea scientists.
21
Chapter 1. Introduction
This method of ‘bottom up’ management has been little tried in Indonesia, where
management has traditionally been ‘government down’, and the World Bank through
the COREMAP program have provided funds to make this model the basis for the
management of all of Indonesia’s reefs (COREMAP, 2004). For this method to be
successful, then the methods of assessment need to be transparent and be able to be
understood by a wide range of stakeholders.
The Tukang Besi archipelago is situated almost central to the ‘coral triangle’,
the Indo-Pacific region of highest coral and fish diversity situated between the north
of Papua, the Philippines and Borneo which is defined as having over 500 coral
species (Veron, 1993). The park falls within the Banda Sea ecoregion of fish diversity
within the coral triangle (Green and Mous, 2004).
Green and Mous (2004) also cite the south-east Sulawesi region as being of
high connectivity with complex currents suggesting good mixing of waters giving a
high density of high diversity reefs of different types.
22
Chapter 1. Introduction
Wangi
Wangi
N
4km
Kaledupa
Double
Spur
INDONESIA
Ridge 1
Pak Kasims
Hoga
NTA
Kaledupa
Sampela
Sombano
Buton
Montigola
Kaledupa
Wakatobi Marine
National Park
Taou
Figure 1.1 Location of the study sites within the Wakatobi Marine National Park,
southeast Sulawesi, Indonesia
1.8.1.1 Site descriptions
1.8.1.2 Hoga No Take Area
The Hoga No Take Area is off the west coast of Pulau Hoga (GPS: 05°28.40S
123°45.45E) and falls within a voluntary No Take Area that is 500m long and extends
from 30m off the reef crest to the shore, which was established in 2001 (Unsworth,
2007). The reef crest is about 150m offshore, adjacent to sea grass beds. The reef
drops vertically from the crest to a depth of just over 30metres, from where a sandy
slope forms into slightly deeper waters. The site is characterized by many overhangs
and small caves. Limited fishing does occur at this site as compliance with the no-take
area is not total, although fishing is generally artisanal and by single hook and line.
23
Chapter 1. Introduction
1.8.1.3 Pak Kasim’s
This site is located around 500 metres to the north of the No Take Area along
the same stretch of the west Hoga fringing reef (GPS: 05°27.569S 123°45.179E). The
reef crest is almost 200 metres offshore, again adjacent to seagrass beds. The reef
aspect is not as vertical as within the NTA, and slopes at between 40 and 70 degrees.
The reef bottoms out at around 50 metres into a sandy slope. There are some spur and
groove formations with sandy gullies in between. Although this site is outside the
NTA, it is not believed to be subject to extensive fishing. There is some evidence of
fish traps and limited gleaning at low tide.
1.8.1.4 Ridge 1
This site is one of the least impacted within the area, situated to the north west
of Hoga island on a barrier over one kilometre offshore (GPS: 05°26.565S
123°45.138E). The ridge runs from north to south with the outer slope dropping to
over 100 metres and the inner slope somewhat shallower. The reef slopes at around 70
degrees on both sides with the crest remaining under several metres of water at all
tides, with effectively no reef flat. This means no gleaning occurs at this site. Some
artisanal line fishing occurs here and there is increasing evidence of bomb fishing
along lengths of the ridge.
1.8.1.5 Kaledupa
The Kaledupa site is on the north eastern side of the island of Pulau Kaledupa
(GPS: 05°28.22S 133°43.47E). The reef is around 300 metres offshore across a
seagrass bed, with some areas of mangrove along the shoreline. There is an extensive
well developed reef flat community that extends for tens of metres back from the reef
crest. The reef slopes at an angle of around 50 degrees and descends past the 50 metre
24
Chapter 1. Introduction
mark to a sloping sandy bottom. The reefs in this area are exposed to moderate levels
of subsistence fishing, but again there is evidence of bomb fishing in the form of
rubble craters.
1.8.1.6 Sampela
This site is adjacent to the Bajo village of Sama Bahari (Sampela) which is
built on the reef flat (GPS: 05°28.975S 123°44.95E). The site is also subject to large
sediment loads of unknown origin which remain suspended for long periods due to the
sites sheltered location (Crabbe and Smith, 2005). The mangroves on shore have
mostly been removed, while the seagrass beds here are probably the most heavily
exploited site in terms of reef gleaning. The reef itself has a flat that shows a lot of
bare substratum, while the reef slopes at 45 degrees own to a depth of around twelve
metres, from where a sand bottom extends out to numerous small patch reefs offshore.
1.8.1.7 Kaledupa Double Spur
This site is located near the northern most tip of Pulau Kaledupa (GPS:
05°27.432S 123°42.412E) and has a very varied topography. There are steep walls
with high benthic cover, interspersed with shallow, often rubble strewn, sandy slopes.
Several spurs stick out from the main reef and descend past 50 metres seawards.
Again this site experiences moderate levels of subsistence fishing, usually with hook
and line gears, while there is also evidence of previous bomb fishing.
1.8.1.8 Sombano
The reefs at Sombano are on the western side of Kaledupa island at the
northern end (GPS: 05°30.117S 123°42.008E). There is a small settlement on the
mainland of Kaledupa at this location separated from the reefs by extensive seagrass
25
Chapter 1. Introduction
beds that extend for over 300m towards the steeply sloping reef that drops of into deep
water. As with the Kaledupa Double Spur site, the area is known to local fisherman as
a spawning ground and the villagers glean the reefs heavily at low tide, but leave other
areas aside for the farming of Agar agar, which also covers large areas of the reef flat
here.
1.8.1.9 Montigola
The reefs at Montigola are adjacent to a Bajo village on the western side of
Kaledupa island (GPS: 05°32.939S 123°44.600E), but of a much smaller scale than
that at Sampela. The reefs are several hundred metres offshore separated from the
village on the reef flat. The reefs are heavily gleaned as at Sampela and exploited in
an artisanal manner with hook and line from small dugout canoes. The reefs are fairly
steep slopes with areas of gentle sandy slope in between, often strewn with coral
rubble. The reefs descend past 30m and then drop steeply into the depths.
1.8.1.10 Taou
The reefs at Taou are similar in structure and distance from shore as those to
the north at Montigola. The village of Taou is on the south western side of Kaledupa
island (GPS: 05°35.238S
123°45.320E), and is exploited locally using artisanal
methods. There are more extensive rubble strewn areas at this site, while the reef flat
is covered with seagrass beds. There are some small areas of mangrove forest along
the shoreline. As at Montigola the reefs decline fairly steeply to over 30 metres in
depth and then descend almost vertically into the depths.
26
Chapter 1. Introduction
1.8.2 Ras Mohammed National Park, Egypt
The Red Sea is a relatively ‘new’ sea formed in the Eocene some 40 million years
ago when a fault developed between what is now the Arabian peninsula and North Africa
and is a continuation of the fault which developed the east African rift valley. The modern
Red Sea was formed some five million years ago when Sinai uplifted, cutting the water
body off from the Mediterranean (formerly Tethys Sea) and opened a shallow channel to
the Indian Ocean, allowing entry of Indo-Pacific organisms to the water body (Lieske &
Myers, 2004). Subsequent isolation from the Indian Ocean led to speciation and the
current situation with so many endemic species, unique to the Red Sea. The Red Sea was
again linked to the Indian Ocean some 15000 years ago at the end of the last Ice age
(Lieske & Myers, 2004). Lieske & Myers, (2004) report that between 210 and 270 species
of Scleractinian coral are found within the Red Sea, and around 1000 species of fishes,
some 15% of which are endemic.
The
Ras
Mohammed
National
Park
was
established
in
1983
as
Egypt’s first national park, although it is generally agreed (Shehata, 1998) to have existed
as a ‘paper park’ until 1988, when the Egyptian government handed the task of
management to the EEAA in response to the areas growing popularity as a dive tourism
destination.
The Ras Mohammed National Park (Figure 1.2) exists at the southernmost tip of
the Sinai peninsula, protruding into the Red Sea, its is bordered its western side by the
Gulf of Suez and on the other buy the Gulf of Aqaba (Frouda, 1984). The coastal plain is
narrow with granitic mountains descending almost directly into the sea (Shehata, 1998).
To the North and the West are large alluvial plains, the northern of which has undergone
rapid and constant development since the mid-eighties and now forms the city of Sharm
el-Sheikh.
27
Chapter 1. Introduction
The cape of Ras Mohammed consists of a large bay and inlet with cliffs of
raised fossilised corals backed by low undulating barren hills (Samuel, 1973). In the
East and in the West there are clear water creeks with sandy shores. The high bluffs of
Ras Mohammed itself are connected to the mainland by a narrow land bridge, 3.5km
long and 1km wide. The southern tip of the headland is an island separated from the
mainland by a shallow channel filled with mangroves. Exposed coral reefs are found
adjacent to open water areas of over 100m in depth. The fringing reef encircles the
entire headland and ends in cliff-like ledges at 70m and 100m water depth. By the
headland there is an extensive terrace at approximately 15m depth (Wells, 1987).
Nearly all areas of shoreline within the park have well developed fringing reefs, often
with steep walls dropping thousands of metres in places.
Water temperatures in the park range from 21°C in January to almost 30°C in
August, salinity is elevated above 40‰ due to high levels of evaporation and slow rates of
water exchange between the Red Sea and the main Indian Ocean basin due to the shallow
water connection between the two bodies. Lack of riverine inputs and associated run off
and sedimentation gives rise to the world renowned visibility of the regions waters.
1.8.2.1 Study sites
Logistical constraints meant that the preliminary study in 2005 was restricted
to four study sites and in 2006 the study was extended to a total of six sites;
1.8.2.1 South Bereika
Located at the southern side of Marsa Bereika bay (GPS: 27°46.447’N
34°12.760’E), South Bereika has a very narrow reef crest only a few metres in width.
The reef then drops vertically to approximately six to eight metres and then slopes at
around 45° down past the 50m mark. Below a depth of 10m spur and groove
28
Chapter 1. Introduction
formations of coral and sandy areas are evident. The large bay is sheltered from the
prevailing conditions and hence the site can be considered a low energy site. The area
has previously been closed for a approximately ten years to all activities, but has
recently been opened in 2005 for boat diving and snorkelling; however, shore diving
is still prohibited. The site is popular with day safari boats and liveaboards, especially
as a mooring site for lunch, mainly due to its sheltered location. This site is also the
only location in Marsa Bereika bay that is open to visitors. Four moorings have been
provided by the park authorities that are regularly full, holding between eight to
twelve boats.
ISRAEL
1
2
Ras
Mohammed
National Park
3
4
5km
6
5
Figure 1.2. Map of the Ras Mohammed National Park
[Key to sites: 1.Ras Umm Sid, 2.Marsa Golan, 3.North Bereika, 4.South Bereika, 5.Shark
Observatory, 6.Old Quay]
29
Chapter 1. Introduction
1.8.2.2 Marsa Ghozlani (Visitor centre)
This site is located between Sharm el Maya and Marsa Bereika (GPS:
27°49.319’N 34°15.862’E) a small bay is overlooked by the Ras Mohammed Visitor
Centre. The reef flat in this area extends from a few metres at the sides of the bay to
approximately 15m in the centre where a small sandy channel also exists. The bay has
a sandy central area which slopes down to approximately ten metres where the reef
begins. At the sides of the bay the reef crest drops vertically to approximately four to
five metres and then a narrow terrace extends for ten to twelve metres. The deeper reef
is a mixture of slope and steep wall dropping to approximately 35 metres, getting
deeper as the reef extends out of the bay. This small bay is relatively sheltered from
the prevailing conditions. The site is extremely popular with snorkelling day boats and
the four moorings within the bay are often fully occupied, possibly due to the sites
proximity to Sharm el Maya, where the majority of the boats depart from. Shore
diving occurs at this site as well as diving from boats.
1.8.2.3 Old Quay
The Old Quay site is on the western side of the Ras Mohammed headland
(GPS:27°44.257’ N 34°14.282’E) and is technically in the Gulf of Suez. This side of
Ras Mohammed is characterised by several kilometres of extensive, shallow reef flat.
However, the area around the Old Quay site has a small sandy lagoon about 50-70m
wide, with patchy seagrass beds occurring within the lagoon. The reef crest rises from
the sandy bottom by approximately 1.5 metres and is approximately five metres wide.
On the seaward side the reef drops as a wall to approximately six metres. This part of
the reef is characterised by spur and groove formations and many large overhangs and
caves. Below this depth, the reef slopes gently at approximately 45° to below 50m.
30
Chapter 1. Introduction
There are two park provided moorings at this site and one or two dive boats are
usually present. The majority of visitors to this site arrive in tourist buses and
generally consist of snorkellers and swimmers. It is not unusual to witness over ten
buses at this site. Visibility at this site was often observed to be relatively poor at less
than 10 metres. Mixing of waters is visible, as is the sediment load coming onto the
reef itself from the reef flat, particularly at low tide when sediment can be seen
flowing out through the reef.
The site is considered sheltered due to its geography, and the settled sediment
load present suggests that it is a low energy site.
1.8.2.4 Shark Observatory
This is the most exposed of the study sites facing south east from the tip of the
Ras Mohammed peninsula (GPS: 27°43.903’N 34°15.592’E). It is adjacent to the
popular Shark and Yolanda Reefs and hence receives a large number of divers, often
as an alternative dive when the moorings for the aforementioned sites are
full(PERSGA, 2005). The site is also popular with shore divers and jeep safaris as
well as with snorkelling tour buses. The site is entered through a narrow bay less than
ten metres wide, and access to the reef is through a cavern approximately 20 metres
wide which slopes from six metres to over 30 metres. Either side of the small bay
there is no reef flat and the reef descends vertically as a steep wall almost straight
down from the terrestrial cliffs which surround this site. The reef descends straight
down to several hundred metres in depth and is dotted with small caves and overhangs.
The site is often subject to moderate to fast currents and as such attracts many pelagic
species such as Tuna, Trevally and several shark species.
31
Chapter 1. Introduction
1.8.2.5 North Bereika
This site is on the north side of the sheltered Marsa Bereika bay (GPS:
27°47.127’N 34°12.920’E). The site is adjacent to one of the three closed areas within
the park and receives very few divers each year (less than 100). The reef begins with
small network of patch reefs and bommies on a sandy slope to approximately 8m
depth. The reef crest ‘proper’ begins at approximately 10-12m and slopes down at a
45º angle to 50m and deeper to 500m in the middle of Marsa Bereika bay. There are
several areas of mini inlets and bays within this area of reef and the slope becomes
steeper in some areas to almost a 70º slope. This site is adjacent to a military
checkpoint and it is understood that this site is closed to boats but open to a small
volume of shore diving.
1.8.2.6 Ras Umm Sid
Ras Umm Sid (GPS: 27º50.852’ N 34º18.826’ E) is one of the most popular
and heavily dived sites within the Ras Mohammed National Park. The site is located
off the steep cliffs of Hadaba and is a popular location for boats to moor between
dives and stopovers on both the way to and return from the Tiran reefs. The reef flat
ranges from 20-60m wide and has several buoyed channels as well as a floating
pontoon to help keep visitors off the reef flat. The reef drops down vertically to
approximately 10m and then slopes gently into depths of over 500m with several
large outcrops and bommies approximately the 30m mark. The site is exposed to the
prevailing conditions with strong currents occurring at peak stages of the tidal cycle.
32
Chapter 1. Introduction
Consequently the aims of this thesis are to;
1. Develop a statistically robust standardised methodology to survey coral reef benthic
and fish communities that can be achieved by non-specialists without the need
for expensively prohibitive equipment, which will give a realistic representation
of reef condition.
2. Develop a multi-attribute index comprising justifiable measures of reef condition
that can be used to represent overall reef condition to a wide variety of audience
from scientist to the general public.
3. Ensure that the developed index will allow the setting of performance goals and
monitoring the success of management actions in Marine Protected Areas
containing coral reef ecosystems.
4. Produce a status report on the condition of the reefs and associated communities of
the Wakatobi Marine National Park in South Sulawesi, Indonesia that will be of
use to community stakeholders and resource managers.
5. Produce a status report on the condition of the coral reefs and associated
communities of the Ras Mohammed National Park, South Sinai, Egypt that will
be of use to the Egyptian Environmental Affairs Agency, Nature Conservation
Sector and will also contribute to the GCRMN Status of the Reefs report.
33
Chapter 2. Optimised reef sampling strategy
CHAPTER 2. Optimised reef survey strategy
2.1 Abstract
This aims of this study where to develop a fully justifiable sampling protocol
that is statistically robust enough to allow informed management action to be taken to
protect the Worlds’ coral reef resources. The ability of any monitoring effort to allow
informed management action to be made is directly related to the reliability of the data
collected (and its interpretation) and hence controlled by the sampling design. Many
papers have suggested that basic facets of sampling design, standard to all ecological
studies are often omitted when studying coral reefs. Sample size and replication were
determined by cost benefit analysis and found to vary dependent on the data collection
method used. The point intercept technique was most time efficient but required more
replication, while the photo quadrat and video techniques were very time efficient in situ,
but were very expensive in terms of subsequent laboratory analysis required. The use of
volunteers to collect coral reef monitoring data has been well documented and this study
also supports the view that volunteers can prove useful in establishing large scale coral
reef surveys. Coral reef survey data collected by volunteers at the genus and family level,
after an initial week long training period, was found to be similar to that collected by
experienced surveyors and also consistent between different volunteers. Finally the
sampling design used for the studied reef monitoring programs established in Indonesia
and Egypt were shown to be capable of detecting medium to large annual changes in
percentage cover (i.e. over 10% total cover) using statistical power analysis, and hence
emphasises the problems with the majority of reef survey designs that utilise smaller
sample size and fewer samples than this study.
34
Chapter 2. Optimised reef sampling strategy
2.2 Introduction
Numerous monitoring and environmental impact methods have been developed
globally for the analysis of coral reef communities, such as ReefCheck, CARICOMP, and
AGGRA, as well as general ecological sampling techniques used by many individual
researchers. Each of these has its own merits, but few, if any adhere to all of the
necessary statistical and ecological criteria to provide reliable, high quality data in an
efficient manner. It is most likely that no standardised monitoring protocol will either be
adopted or widely accepted, because of the varied data needs set by the objectives of
different programs. Due to the many trade-offs necessary to collect the data, temporal and
financial considerations often override statistical ones. Although trade-offs between data
quality and quantity are necessary, the neglect of many basic statistical principles means
that monitoring program data is more likely to be misinterpreted and hence lead to
inappropriate management actions.
One of the problems with monitoring coral reef communities is the large natural
variation both within and between habitats (Lewis, 2004). The target of monitoring
should be to determine natural variation and be able to distinguish this from
anthropogenically induced variation; it is vital to be able to distinguish between the two.
Although the likes of Greig-Smith emphasise the necessity of random sampling
and replication, both of which are, more often than not are neglected in coral reef
monitoring programs (Lewis, 2004). Green (1979) highlighted the fact that putting
transects in “typical” or “representative” places, is not random. Without random sampling
at some stage in the survey, most statistical tests are invalid and hence, we cannot be
confident in the outputs of such programs. Furthermore, Lewis (2004) pointed out that
35
Chapter 2. Optimised reef sampling strategy
without randomisation comparisons cannot be made between reefs and errors can be
made interpreting changes in reef condition. The preferred method for sampling coral
reef benthic communities was described by Loya (1978) was stratified random sampling.
Although the positioning of transects may be representative or systematic, the subsampling of these by use of random quadrats (or images) satisfies the need for
randomisation (Lewis, 2004).
2.2.1 Sample size and replication
The majority of monitoring programs and reef surveys throughout the world are
failing to account for another vital factor in sampling design; sample size. There are
numerous reports in the literature of programs utilising ten or 20 metre long transects to
survey the reef benthos. Transects of such length are not likely to give a realistic estimate
(‘a sample’) of reef composition, unless many replications are considered. The basic
design principles cited in many of the texts (Green, 1979;Hill & Wilkinson, 2004; Krebs,
1999); suggest a pilot study, to generate species area curves to identify the ideal sample
size or area. If the actual sample size or area is small, then replication is vital to allow a
realistic assessment of the reef to be made. Grigg (1999) assessed the ‘merits and pitfalls
of data collection on coral reefs’ and stated that the number of samples needed to make
valid statistical comparisons depends on the variance of the mean abundance or
variabilty. The higher this variability, the more samples are required to give a realistic
estimation of the reef. The simplest method to achieve this is to plot the number of
samples against the number of species present.
36
Chapter 2. Optimised reef sampling strategy
Ideally transect length or the number of quadrats should be set to the number
indicated by a pilot study which identifies around 95% of species present, while
replication should continue until the within site variance is minimal. However, most coral
reef ecosystems can only be sampled using SCUBA, so surveyors are limited by the
inherent safety margins involved with the use of SCUBA and in turn, sampling effort is
often greatly limited. This has often meant a trade-off between the effort involved in
sampling and the quality of data required, often with the outcome of providing data
lacking in spatial scale and/ or statistical rigour (Rogers, 1999).
2.2.2 Benthic Data collection
Loya (1978) suggested the use of species versus transect length curves to
quantify the ideal transect length. Mundy (1991), however, suggested that transects 30m
in length would be representative of the community, which contradicted the findings of
Montebon (1992) who suggested a line transect should always be at least 50m to be
sufficiently representative on Indo-Pacific reefs.
Olhorst et al., (1988) produced a review of published reef census techniques,
and assessed the quality of the data collected, time efficiency and the effects of spatial
heterogeneity on data collected. In terms of benthic survey that study found the point
intercept technique produced the highest quality data in the shortest period of time,
although the line transect method was equally good with a slight increase in effort. The
study also identified the tendency of quadrats to underestimate coverage, while a PCA
plot showed that both the point and line intercept techniques produced cover estimates
close to the true values. The overall conclusion of this review supported Loyas
37
Chapter 2. Optimised reef sampling strategy
conclusion that plotless methods were most efficient. The results of Harding et al., (2001)
showed similar results when using the point and line intercept techniques.
Nadon & Stirling (2006) tested the repeatability, cost-efficiency, precision and
accuracy of belt, line and point techniques on a modelled reef, and suggested that all
three methods were highly repeatable, with low observer error. They found the optimum
number of point samples to be between 80-100, and that increases in precision tailed off
above this number. They also identified that precision and accuracy of all the methods
increased with between five and ten replicate transects, but again began to plateau above
ten.
Weinberg (1981) suggested that the point method be discarded, in favour of
photo quadrats, which he demonstrated to also be superior to line transects in terms of
effort and accuracy. It was also deemed photo quadrats were impractical due to the length
of lab time needed to analyse the pictures, although the rapid advancement in digital
photography has reduced this significantly.
The use of the video transect technique was assessed by Aronson & Swanson
(1997) and also by Vogt et al., (1997). Vogt showed that the video method produced
reliable benthic cover data and that this method could be a fast tool to obtain quantitative
data on the reef benthos, while Aronson and Swanson demonstrated that an independent
sampling strategy (i.e. random transects) using video, could be statistically powerful in
comparing both single and multiple reef attributes. Their study also highlighted the
advantages of using an independent design over traditional fixed methods as it
encompasses a larger reef area and so accounts for more of the within reef variance,
giving greater confidence in results when change is detected. Carleton & Done (2004)
38
Chapter 2. Optimised reef sampling strategy
suggested that for broad taxonomic categories of coral reef benthos, the video method
was ideal to record abundance over large areas of reef, which would give more power to
studies.
Lam et al., (2006) compared the video technique with traditional in situ point
counts and found that the point method overestimated percentage cover in areas where
corals were not extensive, which was contrary to the findings of Olhorst et al., (1988)
whom suggested the point method would underestimate cover where corals showed a
patchy distribution. They identified that the video method was much more efficient in the
field, but like the photo quadrats, proved very costly in terms of lab time to analyse the
images, although this may be attributable to their method of taking 5000 points per
transect. The study also noted equipment costs and maintenance as the main drawbacks
with the video method, but these need to be weighed up against the creation of a
permanent record, which could be reassessed at a later date, to meet different objectives.
2.2.3 Fish Community Survey
There appears to be more of a consensus in the literature with regard to fish
census techniques and many published techniques show similarities. These are all based
on the Australian Institute of Marine Science (AIMS) method of underwater visual
census (Halford & Thompson, 1994). A good justification of Underwater Visual Census
(UVC) can also be found in Labrosse et al., (2002).
Williams et al. (2006) identified a certain degree of bias in non-experts
collecting fish data by UVC, but other studies have shown this soon changes with
experience. While Allen and Werner (2002) suggested surveying reef fish populations
39
Chapter 2. Optimised reef sampling strategy
with indicator families. They suggest that monitoring should focus on the richness of the
Chaetodontidae,
Pomacanthidae,
Pomacentridae,
Labridae,
Scaridae
and
the
Acanthuridae families, as they are the most common species that usually account for at
least 50% of fish surveyed. These six families are also identified as being constantly in
the ten most speciose groups throughout the Indo-Pacific (Allen & Werner, 2002).
Another widespread speciose indicator family is the Serranidae, which is often seen as an
indicator of fishing pressure on a reef (Shakeel & Ahmed, 1997). The use of these
common and easily identifiable family groups can help avoid bias due to
misidentification of cryptic or rare species.
The commonly used AIMS method (English et al., 1997) employs 50m long by
5m wide by 5m high box transects which are surveyed over a restricted time to
standardise effort. Due to the standardised nature of fish community surveys on coral
reefs in the form of UVC, this method will be adopted as the standardised methodology
used with the CVI.
2.2.4 Survey data accuracy
With regard to volunteer collected data, Mumby et al., (1995) defined accuracy
as the similarity of volunteer collected data to scientific data. Both Darwell & Dulvy
(1996) and Pattengill-Semmens & Semmens (1998) identified the usefulness of using
non-experts to collect data for monitoring programs. The use of volunteers reduces labour
costs, while increasing manpower and hence survey area, as well as increasing the
participation and awareness of the public. There are several examples in the literature
describing the usefulness of data collected by non-expert volunteers (e.g. Mumby et al.,
40
Chapter 2. Optimised reef sampling strategy
1995; Erdmann et al., 1997; Harding et al., 2001; Foster-Smith & Evans, 2003; Bell
2007). The majority of studies suggest that with training, non-expert volunteers can
collect valid data, the accuracy of which improves with time. Although Mumby et al.,
(1995) found no such relationship with time, other studies suggest improved accuracy
after some initial overestimation of parameter values due to mis-identification. The
recommended training period necessary for non-experts to collect accurate data varies
from six days for benthic organisms (Erdmann et al., 1997; IOC/UNEP/SPREP, 1994) to
two weeks for reef fish (Darwell & Dulvy, 1996), with all highlighting the importance of
ongoing learning throughout the survey period. There will also be differences in the
length of training time needed for volunteers on programs in different reef environments,
for example learning to identify common coral genera in the Caribbean will take
significantly less time than in the Indo-Pacific region due to the lower number of genera
present. Harding et al., (2001) along with Fore et al., (2001) both identified that nonexpert volunteers could quite easily be trained to accurately identify fish at the higher
taxonomic levels (e.g. family). Although the majority of studies suggest that volunteer
assisted reef monitoring is potentially a valuable management tool, Erdmann et al.,
(1997) highlighted the need for standardisation of both survey techniques and training
programs for volunteers to ensure a reliable standard of data.
2.2.5 Survey data consistency
Mumby et al., (1995) defined consistency as the similarity of data collected by
different volunteers on the same transect. If the selected sample size is representative of
the habitat, then it follows that different researchers should be expected to produce
41
Chapter 2. Optimised reef sampling strategy
similar results when surveying the same transect, using the same method. However,
Mundy (1991) showed that reef scientists using the line intercept technique methodology
often showed significant variance within and between observers, obscuring temporal
changes. It is vital to management to be able to detect temporal change in coral reef
communities. Therefore it is essential to determine whether volunteer and expert data is
consistent enough to allow the identification of change and not mask any change with
observer variation.
2.2.6 Minimal detectable change
Statistical power analysis is another widely suggested, but little used tool in
monitoring program design. Peterman (1990) suggested that the minimal detectable effect
obtained by a given number of samples is a vital component when interpreting
monitoring results. Pattengil-Semmens & Semmens (1998) stated that given a sample
size (n), power analysis could be used to estimate the accuracy of the mean, in terms of
percent deviation from the true mean or simply the minimum detectable change in a
parameter.
A power analysis considers four inter-dependent parameters;
(i) Significance level (Į)
(ii) Power (1-ȕ)
(iii) Effect Size (f)
(iv) Sample size (n)
Significance level is the likelihood of making a Type I error usually set at 95%,
while Power is the likelihood of making a Type II error, and the Effect Size is a measure
of departure from the null hypothesis (Cohen, 1988). By knowing any three of its four
42
Chapter 2. Optimised reef sampling strategy
components, the fourth can be calculated. This should allow the number of samples to be
adjusted so that the detectable levels of community change (i.e. Percent coverage) can be
set, for example to five per cent change per year.
It is only by either incorporating or taking account of all of these aforementioned
factors that we can be confident that a sampling design is likely to provide data that we
can base informed management decisions upon. The selection of methods will remain
dependent upon the programs objectives and the limitations of each method must be
considered when interpreting results.
A recent publication by Leujak and Ormond (2007) also provides a good
comparison of the different survey methods discussed here, including a description of the
strengths and weaknesses of each survey method.
Consequently the aims and subsequent objectives of this chapter are to develop a
statistically robust standardised methodology to survey coral reef benthic and fish
communities that can be achieved by non-specialists, which will give a realistic
representation of reef condition.
(a) To assess the effect of sample size and replication on reef survey results.
(b) Compare methods of benthic data collection on survey results.
(c) Identify an accepted method of fish assemblage survey.
(d) Assess the accuracy of data collected by non-expert volunteers.
(e) Assess the consistency of data collected by non-expert volunteers.
(f) Use power analysis to identify the level of minimum detectable change of
monitoring program designs.
43
Chapter 2. Optimised reef sampling strategy
2.3 Methodology
2.3.1 Sample size and replication
To generate genera-distance curves continuous line intercept transects were
carried out to a total length of 120 metres at three sites of varied condition within the
Wakatobi Marine National Park, South Sulawesi, Indonesia. Hard corals were recorded to
genus and separated into the distance categories where they were first observed. These
data were combined to find the mean number of hard coral genera at various distance
intervals. The plotted curve was intersected to identify the distance at which 95, 75 and
50 per cent of the coral genera present could be identified.
To assess the cost effectiveness of each different survey method, the in situ data
recording time was added to pre defined times for data entry and analysis (to a level of
providing percentage cover data for various benthic categories e.g. 30 minutes data entry
and analysis per transect). The adjustment for the point and line intercept method
techniques was simply the time taken to enter the data into a spreadsheet and sum the
categories. With the photo quadrat method the adjustment included time taken to analyse
the photos, using the CPCe Coral Point Count software (Kohler & Gill, 2006), adapted
for use in the Indo-Pacific (by simply using the image software but entering the data into
MS Excel for analysis), as well the time required to enter the resulting values into a
spreadsheet. The Video transect technique was similarly adjusted in terms of time taken
to randomly select frames and calculate cover values from random points on those
frames.
With in-water time, being the greatest limiting factor in sampling design (due
to the associated safety precautions involved with the use of SCUBA), the time taken to
44
Chapter 2. Optimised reef sampling strategy
complete the survey of one site (multiple replicate transects) needs to be known. The time
taken to complete nine 50m long transects was calculated for each of the different data
collection methods.
2.3.2 Benthic data collection
To compare the reliability of the different data collection methods, three 50m
long line transects were laid on the reef crest (4-6m) and on the upper reef slop (9-12m).
The methods of benthic data collection were assessed in the Wakatobi Marine National
Park, Sulawesi, Indonesia. Transects were laid at three sites of varied perceived quality
(pers. obs). One site (Ridge 1) was in relatively good condition, characterised by high
hard and soft coral cover, with little obvious sign of human impact, one site was within a
protected no take area (NTA) and the third site was heavily impacted (Sampela), being
adjacent to a Bajou fishing village (Figure 1.1).
Data were collected using three point intercept methods, recording the benthos
intercepting points at every 25cm, 50cm and 1m respectively along the transect. These
gave coverage of 200, 100 and 50 points along the transect respectively. The benthos was
divided into ten categories (Table 2.1). Along the same 50m long transect, data were also
collected by the same observer using the continuous line intercept method (after English
et al. 1996), recording everything intercepted by the complete distance of the transect.
For the photo-quadrat method, five 1m2 quadrats were placed randomly along the 50m
transect and photographed. The images were analysed using the CPCe v3.3 Point count
software (NCRI, 2006). The software was used to generate 25 random points within the
1m2 quadrat, and these were used to calculate mean cover values per transect, giving a
total of 125 points per transect. For the video method, the transects were videoed using an
45
Chapter 2. Optimised reef sampling strategy
underwater camera and housing and still frames were selected using the time code and
random numbers and analysed for percent cover, in a similar manner to the photo-quadrat
method. Each frame identified the benthic category under ten random points after
Aronson & Swanson, (1997), and fifteen frames were randomly selected giving a transect
total of 150 points.
Table 2.1 Benthic classification categories
Abbreviation
Substratum category
HC
Hard Coral
SC
Soft Coral
SPG
Sponge
DC
Dead Coral
CR
Coral Rubble
S
Sand
ALG
Macroalgae
RK
Bare Substratum
CCA
Crustose Coralline Algae
OTH
Other
2.3.3 Survey data accuracy
To identify the usefulness of non-expert volunteer collected data, volunteer data
was compared to that collected by experienced reef surveyors. This part of the work was
carried out in the Ras Mohammed National Park in Egypt (Figure 2.2) during August
2006. Line intercept transects of 50m were again used on the reef crest (4-6m) and the
upper reef slope /wall (9-12m), with three replicates at each depth. The data collected by
six volunteers was assigned to the same ten benthic categories as used in Indonesia and
values were statistically compared to those collected by the experienced reef surveyors
(McMellor & Smith, 2006). The volunteers had all received a weeks training in benthic
46
Chapter 2. Optimised reef sampling strategy
identification in the ten categories and identification of fish to Family level, with at least
two in water practicals daily along with two lectures and a feedback session. The
volunteers were tested on their coral and invertebrate identification skills which they
were required to pass at 80% prior to the surveys. The group of six study volunteers had a
range of reef survey experience from one volunteer who had previously carried out
volunteer reef surveys, two volunteers who had completed two weeks of reef survey post
training and three who had just completed the identification training.
The volunteers surveyors each carried out three 50m point intercept transects at
two depths on the reef crest (4-6m) and the upper reef slope /wall (9-12m), with three
replicates at each depth.
Data were arcsine square root transformed to ensure data met normality
assumptions and analysed using ANOVA in SPSS v11.5. Multi Dimensional Scaling was
carried out on the transformed data using PRIMER v6 statistical software to identify
similarities in the datasets collected by different methods and different volunteers.
2.3.4 Survey data consistency
Line intercept transects of 50m were again used on the reef crest (4-6m) and the
upper reef slope /wall (9-12m), with three replicates at each depth. The volunteer
collected data was collected for the same ten benthic categories and values were
statistically compared to those of the other volunteers. All volunteers carried out their
surveys on the same transects on the same day within the Ras Mohammed National Park.
Data were arcsine square root transformed to meet normality and variance assumptions
and compared using ANOVA in SPSS v11.5.
47
Chapter 2. Optimised reef sampling strategy
2.3.5 Minimal detectable change
Statistical power analysis was carried out for a repeat measures design on the
Indonesian monitoring program data, with a significance level (Į) set at 0.05, power was
set to both high (0.8) and low (0.2) as defined by convention, while sample size (n) was
108. This allows the detectable Effect Size to be calculated, i.e. the percentage annual
change in a measured attribute that can reliably be detected.
2.4 Results
2.4.1 Sample size and replication
The three 120 metre long transects identified 23 hard coral genera and the
distance-genera curve levelled off after an average of 20 different hard coral genera. The
distance-genera curve (Figure 2.1) identified a suitable transect length of 80m to be able
to identify 95 percent of the genera present. A transect of 50m in length would only be
able to identify 75 per cent of coral genera, while a 20m transect would be able to
identify 50 percent of the hard corals present.
48
Chapter 2. Optimised reef sampling strategy
100
25
90
No. Genera
70
60
15
50
10
40
30
5
% of Total Genera
80
20
20
10
0
0
0
20
40
60
80
100
120
Distance (m)
Figure 2.1 Coral genera-Distance curve for the Wakatobi MNP. [Left y-axis indicates
number of Genera found, Right y-axis indicates percentage of total Genera identified]
The time taken to complete transects of a set length varies with the method of
data collection used, as does the quality of data collected. The continuous line intercept
technique was shown to take the longest, with survey time increasing at a greater rate
than other methods, with greater transect length (Figure 2.2), when including time taken
to collect the data and analyse it to the point of calculating cover values for various
benthic parameters. The point intercept technique, with data points every metre was the
most time efficient at all transect lengths, closely followed by the point intercept
technique with points every 50cm. The point technique with 25cm spacing was the third
most time efficient method at shorter transect lengths, but became more costly once
transects in excess of 70 metres were used. The video technique showed a steady increase
in survey time with increased transect length, as the transect is recorded at a standard
49
Chapter 2. Optimised reef sampling strategy
speed. The photo quadrat method was slightly less time efficient than the video
technique, with both being rapid in situ, but effort increasing greatly when the time taken
to analyse the images was taken into account.
The video survey method proved to be the most efficient method of carrying out
multiple surveys in realistic dive times (Figure 2.3). Due to the remote location of the
field studies single dives have time restrictions of 50 minutes, and so the following
numbers of transects were completed within this timeframe; Up to five video transects
could be completed within one 50 minute dive, while at the other end of the scale, it
would take around 45 minutes to complete a single 50m continuous line intercept
transect. Within the 50 minute timeframe along a 50m transect, the three point transect
methods all allowed for two transects to be completed per dive, while the photo quadrat
method could complete three 50 metre transects.
50
Chapter 2. Optimised reef sampling strategy
140
-1
)
1m Pt
0.5mPt
0.25mPt
LIT
Photo
Video
Total Time (mins tranesct
120
100
80
60
40
20
0
0
20
40
60
Distance (m)
80
100
Figure 2.2 Survey effort (distance) versus time taken to complete benthic survey for six
different techniques including data entry and analysis. [1m, 0.5m and 0.25m point count
techniques, continuous line intercept technique, photo quadrat and video frame
techniques]
450
1m P
Time (mins)
400
0.5mP
350
0.25mP
300
LIT
250
Photo
200
Video
150
100
50
0
0
2
4
6
No. 50m transects
8
10
Figure 2.3 In water time taken to complete multiple 50m transects using the six different
sampling techniques. Dashed line indicates average dive time. [1m, 0.5m and 0.25m
point count techniques, continuous line intercept technique, photo quadrat and video
frame techniques]
51
Chapter 2. Optimised reef sampling strategy
2.4.2 Benthic data collection
When the different survey methods were carried out at the three sites of varied
quality in the Wakatobi MNP, similar patterns were observed in a MDS plot (Figure 2.4).
Transform: Square root
Resemblance: S17 Bray Curtis similarity
2D Stress: 0.07
SV
Similarity
70
80
90
SL
S50
S1 S25
NL
N1
RL
N25
N50
R50
R25
R1
SP
RV
NV
RP
NP
Figure 2.4 MDS plot to show the similarity between the different survey methodologies
[S=Sampela, R=Ridge and N=NTA] (P=Point transects at 1m, 50cm and 25 cm
intervals, P=Photo quadrat , L=continuous LIT and V=Video)
All the survey methods show a data similarity above 70%. The impacted Sampela
sites show a clustering of the point and line technique data, with the photo quadrat data
being over 80% similar to the other methods. Yet for the two higher quality sites it can
again be seen that the data collected using the photo method is somewhat separated from
the data collected by the other methods.
52
Chapter 2. Optimised reef sampling strategy
It was noted that all of the methods are capable of separating the sites, and depths
within sites from one another in a consistent way, with the possible exception of the
photo quadrat data at the higher quality sites. It is worth noting that the least impacted
sites, the reef crests at the Ridge and within the NTA, show the highest degree of
similarity between the different transect methods.
2.4.3 Survey data accuracy
The accuracy of the non-expert volunteer collected data when compared to the
data collected by experienced reef surveyors was not significantly different for most
parameters (Figure 2.5), including hard coral cover, soft coral cover, coral rubble, total
live cover and percentage bare rock. The mean (±s.e.) volunteer measured hard coral
cover within the Ras Mohammed National Park was 25.9 (±4.6)%, while the experienced
surveyors estimated the hard coral cover at 25.7 (±1.5)%, however, there was larger
variability in the volunteer collected data. Significant differences were found between
volunteer and experienced surveyors data for the macro-algae (F2,8=3.54;p<0.01), generic
richness (F2,8=2.84;p<0.05), mean hard coral colony size (F2,8=3.01;p<0.05), and for the
number of colonies per transect (F2,8=3.75;p<0.01).
Volunteer estimates were significantly higher for mean colony size, and
significantly lower for the macro-algae, hard coral generic richness and number of
colonies per transect.
53
Chapter 2. Optimised reef sampling strategy
% Cover
80
70
Volunteer surveyors
60
Experienced surveyors
50
40
30
20
10
No
Co
ls
siz
e
Co
l
RK
AL
G
DC
LC
CR
SC
HC
0
Figure 2.5 Mean (±s.e.) benthic category values surveyed by non-expert volunteers
compared with experienced surveyors data. [Categories: HC-Hard Coral,SC-Soft
Coral,CR-Coral Rubble,LC-Live cover,DC-Dead Coral, ALG-Macro-algae,GenRichGeneric richness of HC,Colsize-mean HC colony size, NoCols-Number HC colonies per
transect]
2.4.4. Survey data consistency
The results for consistency between different reefs surveyors (of limited, though
varied experience), on the same transect, showed similarity between the majority of
surveyors. However there was often error by one observer that showed a significant
difference to the other estimates (Figure 2.6). For the hard corals, there was a significant
difference in the levels of cover estimated (F5,4=6.84;p<0.01). Tukey post hoc tests
identified that observer b estimated a mean level of cover in excess of ten per cent of all
other observers(p<0.01), while observer e, the most experienced of the volunteer
surveyors estimated the lowest mean coverage(p<0.001). Again for the soft corals, the
majority of the surveyors’ estimated similar levels of cover, while one observer under
54
Chapter 2. Optimised reef sampling strategy
estimated by around ten per cent and a second observer overestimated by a similar
margin. Levels of coral rubble and macro-algae were not high enough to allow the
identification of any significant differences
There were no significant differences in the mean number of hard coral colonies
estimated per transect by the six volunteers (Figure 2.7). For total live cover, there was a
significant difference (F5,4=4.69;p<0.05), with observer b overestimating the cover, as
they had with soft coral cover. There was also a significant difference in the mean hard
coral colony size (F5,4=3.13;p<0.05), with observer b over estimating size, as they did
cover, there was no difference between the other observers.
70
a
60
b
c
d
e
f
% Cover
50
40
30
20
10
0
HC
SC
CR
DC
Benthic category
ALG
RK
Figure 2.6 Benthic categories recorded by six volunteers along the same continuous line
transect (Volunteers a-f)[mean(±s.e.) % cover; n=6] [Categories: HC-Hard Coral,SCSoft Coral,CR-Coral Rubble,LC-Live cover,DC-Dead Coral, ALG-Macroalgae,GenRich-Generic richness of HC,Colsize-mean HC colony size, NoCols-Number
HC colonies per transect]
55
Chapter 2. Optimised reef sampling strategy
100
90
80
% Cover
70
a
60
b
c
d
e
f
50
40
30
20
10
0
No. cols
LC
Benthic category
Col size(cm)
Figure 2.7 Further benthic parameters recorded by six different volunteers along the
same continuous line transect (Volunteers a-f)[mean(±s.e.) % cover; n=6][Categories:
NoCols-Number HC colonies per transect. LC-Total Live Cover, Colsize-mean HC
colony size]
Group average
Transform: Square root
Resemblance: S17 Bray Curtis similarity
a
c
Samples
b
f
d
e
85
90
95
100
Similarity
Figure 2.8 Dendrogram to show percentage similarity between benthic composition
recorded by six volunteers (a-e) along the same continuous line transect
(Square root transformed Bray-Curtis Group average)
56
Chapter 2. Optimised reef sampling strategy
The similarity in the data collected by the six observers can be seen in the
Dendrogram (Figure 2.8); there was over 86 % similarity for all the benthic categories
recorded. The majority of the parameter estimates are some 92% similar to those of the
most experienced volunteer (e).
2.4.5 Minimum detectable change
The results of the power analysis for the Wakatobi MNP monitoring program
design (Figure 2.9) suggest that to achieve a high power (1-ȕ), as well as low error
probability (Į) then sample sizes (or number of transects) need to be over 500 to be able
to identify a small effect size (i.e. a change in percentage cover less than 10%). At the
medium effect size (a 25% change in cover), a smaller sample size, is required to achieve
higher power, while at the large effect size (a change in cover over 40%), less than 50
samples will allow the power to be estimated above 0.8.
Figure 2.9 Power curve to identify required sample size at Į=0.05 to detect small (0.1),
medium (0.25) and large (0.40) effects.
57
Chapter 2. Optimised reef sampling strategy
Figure 2.10 Power curve to illustrate the trade off necessary between Į (Type I error)
and 1-ȕ (Type II error) to detect three levels of Effect size, [n=108]
The trade-off between low error probability (Į) and high power (1-ȕ) at a sample
size of n=108 (nine transects at 12 sites) indicates that relatively high power can be
achieved with a low error probability for large and medium effect size, but at the smallest
effect size, error probability must be increased to achieve higher power (Figure 2.10).
2.5 Discussion
2.5.1 Sample size and replication
The results of the generic-area curve suggest that transect lengths necessary to be
truly representative of the sampled area of reef, would be too long to carry out in practice,
due to the limitations imposed by the use of SCUBA. Therefore a trade-off between data
quality and survey effort is required. The majority of published studies use transects of
lengths less than 30m, which was suggested by Mundy (1991) as a minimum size;
58
Chapter 2. Optimised reef sampling strategy
however, in the present study a 30m transect identifies less than 50% of the coral genera
present. A transect of 50m length provides a reasonable trade-off, as 75% of genera
present can be found and meets the suggested 50m minimum size identified by Montebon
(1992). The length of the transect can also be influenced by the survey method used. The
point count technique was the most time efficient method, supporting previous studies
(Olhorst et al., 1988; Nadon & Stirling, 2006), while the line intercept technique was
least time efficient method per transect. Nadon & Stirling (2006) suggested that increases
in precision decline once more than 80-100 points are counted, therefore a 50m transect
point sampled every 0.50 metres should prove sufficient. A smaller transect sampled
more frequently would produce similar precision, but then the transect length may not be
representative of the benthic community as defined by the genera-area curve.
The photo and video techniques are more time efficient in situ, but the analysis of
the images in the laboratory requires a considerable amount of post-dive time. If the
number of frames to be analysed is set regardless of transect distance, then time costs for
analysis do not vary significantly with transect length. Although Weinberg (1981)
dismissed the photo-quadrat method as too time consuming, it was found to be more
efficient than the continuous line transect technique. There are also implications of
equipment cost and maintenance involved with these two ‘high technology’ methods. For
example, a broken camera could mean the suspension of survey efforts until an expensive
replacement can be sourced.
The use of a stratified random sampling design, as suggested by Aronson &
Swanson (1997), eliminates the need for permanently marked transects, which are both
difficult to locate and maintain, as well as difficult to re-establish in exactly the same
59
Chapter 2. Optimised reef sampling strategy
position as previously used. Stratified random sampling was also identified as desirable
by Lessios (1996).
2.5.2 Benthic data collection
The similarity in the data collected by all of the methods supports previous studies
by Weinberg (1981), Dodge et al. (1992) and Nadon & Stirling (2006), who all found no
significant difference in data collected using the point or continuous techniques when
samples of sufficient size were collected. More recently, Leujak and Ormond (2007)
found no significant difference in the data collected between photo, video, line intercept
and point intercept methods. For broad categories such as percentage cover of hard
corals, it makes sense to use the most time efficient method of data collection as there is
no difference in the data quality.
However, Lam et al., (2006), suggested that the point method overestimates
percentage cover where corals are not extensive, whereas in this study the point method
was found not to be significantly different from the continuous method where coral
distribution was patchy. The second problem with the point technique is the lack of
ability to record diversity or richness measures. The data from this study suggests that
differences between the methods become more apparent at the degraded sites, as
highlighted by the difference in the photo method. The photo quadrat data was shown to
be less representative than the transect methods, and this suggests that more quadrats are
needed along the fixed transect length. This is also an issue with the video method,
suggesting the selection of more frames would give a more representative sample.
Previous studies have increased the number of frames sampled from the transect, yet such
60
Chapter 2. Optimised reef sampling strategy
increases are pseudo-replication as the frames are not independent of one another (see
Lam et al., 2006). The similarity between the point techniques and between the point and
continuous techniques was shown to be very high, suggesting minimal difference
between these techniques. The results of the Leujak and Ormond (2007) study reports
that only ten metres of continuous line transect could be completed in an hour long dive,
whereas this study found it was possible to complete a 50m continuous LIT to the genus
level within a 50 minute dive. This shows a bias in the reported study towards a method
that the authors had used previously, i.e. the video transect method, as an experienced
reef surveyor should be able to complete more than ten metres of continuous LIT in a
single dive (pers. obs.).
2.5.3 Survey data accuracy
The accuracy of volunteer collected data showed no significant difference from
data collected by experienced reef surveyors for the majority of attributes at the category
level. The majority of the surveyed parameters showed no significant difference between
surveyors, however, it should be noted that there was greater variability between nonexpert collected data when compared to the experienced surveyors. Differences were
identified in the number of individual colonies and in the size of coral colonies, which
can be explained by observer inexperience. Colonies now separated by areas of bare rock
or dead skeleton are considered separate colonies by the experienced surveyors, whereas
it seems likely that they were still considered to be a single larger colony by non-experts.
This explains both the underestimation of hard coral colonies and also the overestimation
of mean colony size. This study offers support to previous works suggesting that
61
Chapter 2. Optimised reef sampling strategy
volunteers can be a useful tool to increase the survey effort of monitoring programs
(Mumby et al., 1995; Foster-Smith & Evans, 2003; Bell 2007).
2.5.4 Survey data consistency
The consistency of data collected by different volunteers working on the same
transect showed similar high levels between observers and these high levels support the
results of Mumby et al. (1995). Harding et al. (2001) also showed that the results of
volunteers are consistent with different point and continuous methodologies. The
between observer variation needs to be monitored to identify if one observer is
consistently over or under estimating cover. Where differences for various parameters
were observed, it was usually only one observer that was finding significantly different
from the others. Monitoring of observer performance would reduce observer error, and
therefore with ongoing education, observer performance should increase with time and
effort (Darwell & Dulvy, 1996; Erdmann et al., 1997; Foster-Smith & Evans, 2003).
Discussions of volunteer use of the photo and video techniques are sparse in the
literature, probably due to the expense of the equipment involved. Direct in water survey
methods appear more suited to volunteers as several people can be utilised on a transect,
maintaining interest and helping to avoid bias by using mean observed results rather than
the observations of a single individual, although these methods would still provide plenty
to occupy volunteers out of the water, in terms of data entry and basic analysis.
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Chapter 2. Optimised reef sampling strategy
2.5.5 Minimum detectable change
The power analysis of the sampling design identified that the methods are only
capable of detecting medium to high levels of change between surveys, due to the high
levels of variability both within and between sites. To identify small changes annually in
the benthic parameters, much larger, unrealistic sampling effort would be required. This
raises the question of the validity of the majority of monitoring program and survey
designs.
In science in general, the error probability is set to 95% confidence interval, or a
one in twenty chance of making a Type I error and rejecting a null change hypothesis.
Although it could be argued that in ecological monitoring studies, the avoidance of a
Type II error in accepting a no change hypothesis when there is in fact change, would
have more serious consequences. Sticking to this 95% confidence interval means that
power is low for achievable survey effort. This means a trade off is needed between
sample size, error probability and power. To keep sample size achievable, the level of
error probability needs to be sacrificed to allow higher levels of power in the study.
Reducing the level of error probability will be dependent upon the goals of the study or
monitoring program. The observers will need to identify the relative importance of Type I
and Type II errors, and what they would mean to the interpretation of results
2.5.6 Conclusions
The data and subsequent analysis suggest that a transect length of 50 metres is the
most appropriate sample size to provide a realistic estimate of cover while being
achievable within the limitations imposed by the safe use of SCUBA. Replicates at three
63
Chapter 2. Optimised reef sampling strategy
depths on the reef flat, the reef crest and upper reef slope allow for much of the variation
between depths and zones to be accounted for. Three replicate transects at each of these
depths will provide total transect coverage of 150m per zone and a total of 450m per site,
well above the minimum value of 135m proposed by Leujak and Ormond (2007). Belt
transects for analysing the fish community will also be 50m in length to match the
benthic data and also to follow well established AIMS UVC methods.
The majority of the data collected for this study was by continuous line intercept
technique, which is shown to be similar to point techniques in efficiency, but does not
suffer from the shortcomings of the point technique in low cover areas or in terms of
assessing richness and diversity. The video method would be most ideal, but is not
entirely appropriate for studies using volunteers, due to financial costs and excessive ex
situ effort needed for analysis. The line intercept method also removes any doubts about
pseudo-replication that may be levelled at photo or video frames selected from a single
transect as suggested by Lam et al., (2006).
The data collected by volunteers was not dissimilar to that collected by experts at
the category level and hence the study can be given more power by an increased
sampling effort utilising volunteers. The variability in data collected by volunteers needs
to be monitored to ensure consistency between different volunteers, but will allow the
reduction of observer bias by providing mean values of abundance and cover for each
transect.
The power of any study is proportional to the sample size. This suggests that the
majority of coral reef monitoring programs have such little power, that Type II errors
become a problem. To identify minimal change, sample sizes prove unrealistic, and as
64
Chapter 2. Optimised reef sampling strategy
such the sample design should either be adjusted to sample many more sites or the error
probability needs to be reduced to give increased power. The current survey methods
using 54 transects at an error probability of 0.05 can only reliably show a medium to
large effect size (>20% cover) at a high power level.
The recommended standardised sampling strategy for use with the Conservation
Value Index, as devised from this study, is shown in full in Appendix I.
65
Chapter 3. Conservation Value Index
CHAPTER 3. A Multi-Attribute Conservation Value Index
3.1 Abstract
This chapter aims to develop a Conservation Value Index to allow the assessment
of the condition of coral reef communities using numerous attributes, rather than a single
univariate factor, which may mot represent the true condition of a reef. Survey data from
the Wakatobi Marine National Park, Indonesia was collected in 2002 and used to rank six
study sites in order of reef condition. Principal Component Analysis was used to identify
reef attributes that varied between sites, for both the benthic and fish assemblages. A total
of 24 attributes were then combined into two parts, a benthic index containing twelve
coral reef benthic attributes and a fish assemblage index also consisting of twelve
attributes. The benthic index was converted into five categories and scored from A-E,
while the fisheries index is divided into five categories labelled 1-5, giving a two part
index (e.g. a top quality site would score A1). Data from a 2005 survey of the six sites
were used to generate regression equations which were used to model both high and low
extremes of attribute values, which were than combined to test the index. A literature
search and baseline data was used to score the attributes. The final index was presented
both graphically and in tabular format to allow the dissemination of complex biological
data sets to a wide range of stakeholders from local communities to scientists and
managers. This type of multi-attribute index can allow the informed management of coral
reefs and marine protected areas, and be used to monitor rates of change and the
effectiveness of management actions, which is vital if these valuable ecosystems are to be
preserved. This method also retains the detailed univariate survey information collected.
66
Chapter 3. Conservation Value Index
3.2 Introduction
With the aforementioned limited resources of many tropical nations, coupled with
the increasing rates of over-exploitation and degradation, finding an effective and
methodical way to prioritise areas for conservation efforts is critical (McKenna and
Allen, 2000). Although coral reef monitoring programs around the world generate
important volumes of data and information on various coral reef parameters, standardised
and easily accessible data from these programs is often lacking (Noordeloos et al., 2004).
The relevant measurement endpoint for biological monitoring is biological condition;
detecting change in that endpoint, comparing the change with a minimally impacted
baseline, identify the causes of change and communicate all of this to policy makers and
stakeholders, these are the combined tasks of biological monitoring programs as defined
by Karr and Chu (1999). Living corals should be central to any form of assessment of
coral reef health. They are highly productive, as well as being the actual reef building
organisms, meaning that they are of vital importance to reefs and account for the net
positive production of a coral reef (Yap et al., 1994). However, coral reef ecosystems are
highly diverse and complex environments and cannot be adequately quantified according
to Scleractinian coral cover alone, the method that is currently most prominent. For
example, a monospecific stand of fragile Acropora with 60% cover would not necessarily
indicate a reef in better condition than one with a mixed coral community with 45%
cover. As reported by Ben-Tzvi et al., (2004) and Ablan et al., (2004), and is also
apparent from the proliferation of different indicator methods available, there are no wellaccepted reliable means of indication for a ‘healthy reef’ and none of the commonly used
parameters is accepted as an indication that reliably represents reef community health.
67
Chapter 3. Conservation Value Index
McClanahan et al., (2002) identified the great need to monitor coral reef resources and
develop a scientific infrastructure and a conceptual platform for the interpretation of the
collected data. Eakin et al., (1997) had also previously identified a particular need for the
ability to quickly and accurately assess the health of ecosystems and the level of threat
that they face, and called for further research to develop criteria and cost-effective
procedures for the assessment of coral reef health.
To provide stakeholders with the information necessary for successful
management of the fisheries and reefs within an area, as well as to increase social capital
(Pretty, 2003), it is necessary to have a method of reef assessment that can be understood
by the local community, many of whom are poorly educated. According to Karr and Chu
(1999) policy makers, citizens and scientists faced with making decisions about complex
systems need multiple levels of information. Ablan et al., (2004) identified the similarity
between biological metrics and economic metrics used in economic analysis (e.g.
FTSE100, retail price index).
Therefore, there is the need for a simple non-specialist means of transferring
information about reef and fisheries quality to the stakeholders. This also allows an easily
understandable overview to be given to policymakers and funding agencies. Several
studies have identified problems with classifying habitats by the use of a single factor
index (Loya, 1972; Pielou, 1972; Hughes 1978). The development of a single readily
understood multivariate/ multimetric index would be of greater use than the reporting of
numerous or single factor indices (Extence et al., 1987). The work of Karr and Chu
(1999) identified that multimetric biological indexes calculated from ambient biological
monitoring data provide a similar integrative approach for measuring condition and
68
Chapter 3. Conservation Value Index
diagnosing causes in complex ecological systems. The resulting multimetric approach to
biological monitoring is dependent upon the selection of suitable metrics that reflect
diverse responses of biological systems to human activities.
To compile a multimetric index, each metric must be converted to a common
scoring base. Typically metrics are quantified with different units and have different
absolute numerical values. Some metrics will increase in response to disturbance whereas
some will decline. To resolve this, each metric is assigned a score based on expectations
for that metric at a minimally impacted site for that region, either from direct survey or
from a historic baseline. The metrics that are not significantly different to the regional
expectation (control) are awarded the top score with those sites that do differ, receiving
progressively lower scores dependent on the scale of difference from the controls. The
final multimetric index is simply a sum of all these scores.
Jameson et al., (1998) provided a complete review of biological criteria for coral
reef ecosystem assessment, but also noted that the high level of natural variation on such
systems means that multiple species assemblages must be monitored. The study noted
that such multimetric assessment will also aid management as well as giving a snapshot
of reef condition. This form of bio-assessment will allow the identification of causative
factors, if not from the multimetric score, and then from the individual attribute values
which are also retained from the survey. The same report noted that well constructed
indices from other ecosystems typically examine two or more assemblages because
different groups of organisms respond differently to different impacts (e.g. benthic
lifeforms and fish). Therefore, the more diverse the measures used, the more robust the
index and hence more confidence can be placed in the results. In their continuing review
69
Chapter 3. Conservation Value Index
of coral reef attributes, Jameson et al., (2001) identified the need for the development of a
coral reef classification system as well as selection and sampling of representative
minimally disturbed sites to define regional expectations. They also noted the advantage
of measuring biological condition with a continuous yardstick such as a multimetric
index which puts a site along a continuum of condition in comparison with other sites (or
times). This also permits the ranking of many sites, which would simply be labelled as
degraded by traditional assessments, so that priorities may be set for budget-constrained
protection and restoration efforts. This same study of Jameson et al., (2001) noted that
the wide-ranging responsiveness of multimetric biological indexes makes them ideal
tools for assessing the effectiveness of management decisions. They point out that if the
individual metrics are correctly calibrated, it is possible to compare sites across different
class of reef and also to use the index as an effective early warning system, although they
note that to diagnose the exact stressor(s) requires focus on the individual metrics.
Noordeloos et al., (2004) also remind us that the key objective of status reporting is to
provide managers, policymakers and other stakeholders with a reliable but simple
indication of whether the reefs within their own area are in good condition, whether they
are at risk from threats that may alter reef condition and whether effective management
actions are in place to deal with the threats. A multi-attribute index would also allow the
auditing of management actions and their effectiveness by setting desirable outcomes that
could be monitored.
There are wealth of studies that call for the development of such management
tools if we are to successfully protect coral reefs (Wilkinson and Chou, 1997; Bryant et
al., 1998; Edinger and Risk, 2000; Ahmed et al., 2004).
70
Chapter 3. Conservation Value Index
The aim of this chapter was to develop a justifiable multi-attribute assessment
method that will give a clear indication of reef condition that can be interpreted by
stakeholders without a specialist scientific background. The index should be based upon a
statistically sound sampling methodology that will allow the calculated attributes to be
true estimates of reef condition. The index should however maintain enough complexity
to generate and maintain data that is of value to scientists and reef managers in terms of
MPA management.
To meet this aim the objectives for this chapter are to;
(a) Ordinate the survey sites using multivariate attributes.
(b) Identify suitable attributes to assess the benthic assemblage.
(c) Identify suitable attributes to assess the fish assemblage.
(d) Develop a system to score the selected attributes and combine them into a two
part index.
(e) Test the responsiveness of the resulting index and ensure that the developed
index will show appropriate variation in output with changes in reef condition
3.3 Methodology
The data used to construct the conservation value index was collected from 2002
to 2005 in the Wakatobi Marine National Park, Sulawesi, Indonesia (Figure 1.1) by a
team of taxonomic experts in the fields of corals and fish in conjunction with the
Indonesian institute of sciences (LIPI). Benthic data was collected using a 50m long line
intercept transects, and all lifeforms intercepting each transect were recorded to genus
level (after English et al., 1996). This was deemed the most appropriate method,
71
Chapter 3. Conservation Value Index
considering the trade off in effort and data quality discussed in Chapter 2. This method
allowed the calculation of various coral health attributes such as percentage cover of
various benthic categories, various diversity measures, mean colony size and species
richness. A 25 minute time restricted 50m x 5m x 5m box transect was used to assess the
abundance and diversity of the fish assemblage, the richness of seven fish families while
the trophic structure of the community was identified using the FishBase online database
(URL http://www.fishbase.org/home.htm).
The data from the six Operation Wallacea biodiversity monitoring program sites
collected in 2002 (see Chapter 4), was used as a baseline to rank the study sites in an
order of overall reef health, using a number of different reef attributes, such as hard coral
cover, diversity, total live cover for the benthic section and total fish abundance, fish
diversity, fish species richness and equitability, for the fish component. The statistical
packages PRIMER and SPSS were used to detect trends in the data and to allow
ordination of the sites using Principal Component Analysis(PCA). PCA and Bray-Curtis
cluster analysis were used to identify potential indicator metrics which showed a
correlation with the varied site qualities. The selection of individual attributes was
supported by an extensive literature search to identify commonly reported and called for
reef attributes.
Regression analyses were carried out on the four year series of Indonesian data
collected between 2002 and 2005, and the formulas generated were used to predict
extreme values five years previously, as well as both five and ten years in the future for
each of the individual attributes. This generated both high and low values which allowed
the testing of the index at extremes of condition, but based on realistic values for each
72
Chapter 3. Conservation Value Index
attribute. The output of the five year future predictions were compared to actual data
from 2007 to assess their validity using a Ȥ2 contingency test in the program XLStat.
Once the data sets were complete, the tested metrics were combined into a multiattribute index consisting of two parts, a benthic index containing 12 coral reef benthic
attributes and a fish assemblage index consisting of 12 attributes. The benthic index is
converted into five categories and scored from A-E, while the fish index is divided into
five categories labelled 1-5, giving a two part index (e.g. a top quality site would score
A1).
The individual attributes were scored according to methods or values established
for that region from the literature. For example the commonly used reef condition index
dividing coral cover into four categories (<25%, 26-50%, 51-75% and 76-100%) was
used to score the hard coral cover attribute. For each individual attribute a regional
control value was set after consultation to the literature available for the region. If the
sites were not significantly different from the control values, they were awarded a top
score of five points for that metric. The measured attributes were then scored on a
declining scale as either three, one or zero depending on the difference from the control.
The overall index score is a sum of all the possible attribute scores, with a theoretical
maxima of 60 for each part.
The generated index scores were then presented in both tabular and graphic
formats. Outputs of the index values were plotted on satellite images of the survey area to
allow easy interpretation by non-specialists. The data was also presented in a grid style
format so that trends in changing reef condition can be easily identified.
73
Chapter 3. Conservation Value Index
3.4 Results
3.4.1 Site Ordination
Before the new Conservation Value Index can be compiled or tested, the study
sites needed to be ranked definitively according to their current state of health. This also
allowed the identification of potential indicator metrics which change in value across the
gradient of study sites. Initially several different reef assessment techniques were used,
and it was found that the ranking of the sites varied with the assessment method used
(Table 3.1).
Table 3.1 Varied ranking of sites according to univariate methods of assessment (values
in parentheses) [Site key: NTA-Hoga NTA, R1-Ridge1, KDS-Kaledupa Double Spur, KalKaledupa, PK-Pak Kasims, SAM-Sampela]
Rank
1
2
3
4
5
6
Hard
Coral %
cover
NTA (56.8)
R1 (53.3)
PK (46.6)
KAL (45.8)
KDS (45.5)
SAM (32.6)
Macroalgal %
cover
KDS (7.0)
R1 (7.2)
NTA (12.3)
PK (15.4)
KAL (18.0)
SAM (29.3)
Coral
Rubble %
cover
KAL (1.9)
R1 (3.8)
NTA (6.2)
PK (7.4)
KDS (10.0)
SAM (11.7)
Mean Fish
abundance
(1250m-3)
NTA (1604)
R1 (1216)
KAL (944)
PK (777)
KDS (648)
SAM (366)
Fish
diversity
(H’)
R1 (3.17)
KDS (3.13)
PK (2.79)
KAL (2.76)
SAM (2.56)
NTA (2.43)
Using these univariate assessments, different sites were ranked highest dependent
upon the attributes used. When using hard coral cover the Hoga NTA site was ranked
highest, but when recording macro-algal cover the NTA site ranked lower and the
Kaledupa Double Spur site was ranked highest (low algal cover). Again with fish
abundance the Hoga NTA site came out top, but fish diversity (Shannon-Weiner) was
highest at the Ridge 1 site and the NTA site scored lowest of all six sites.
74
Chapter 3. Conservation Value Index
The ordination technique Principal Component Analysis (PCA) was used from
site summary data for both the benthic and fishery components. Using the first two
principal components, 82.9% of the variation between sites can be explained, while this
increases to over 93.7% when component three is incorporated (Figure 3.1). A general
trend from low quality to higher quality sites has been overlaid on this figure. The
technique ranks the sites along principal component one, with the Hoga NTA site ranked
highest, ahead of the Ridge 1 site. This was followed by the Kaledupa site, then Pak
Kasims and Kaledupa Double Spur and last in the ranking was Sampela.
The multivariate techniques also aided in the identification of suitable indicator
metrics as individual attributes could be overlaid on the PCA plot as vectors to show that
the attributes vary with the established order of sites. Sampela was consistently ranked as
the poorest quality site, with Ridge 1 and Hoga NTA being the best sites. Although there
was separation between sites it is worth noting that cluster analysis using Bray-Curtis
similarity (group average linkage) indicated that all of the study sites within the Wakatobi
MNP showed a similarity in community composition, both fish and benthic of over 84%
(Figure 3.2). The sites did show differences at the higher levels of similarity, with
samples clustering together based on site.
75
Chapter 3. Conservation Value Index
PK
SAM
NTA
R1
KAL
KDS
10
PC2
5
0
-5
-10
-8
-6
-4
-2
0
2
4
6
8
PC1
Figure 3.1 – PCA co-variance ordination plot of components 1 & 2. Arrow
indicates direction of perceived reef health (low to high) [Site key: PK-Pak Kasims,
SAM-Sampela NTA- Hoga NTA, R1-Ridge 1, KAL-Kaledupa, , KDS-Kaledupa Double
Spur]
3.4.2 Benthic Attributes
A separate PCA was carried out for the benthic and fishery attributes, with the
benthic PCA (Figure 3.3) identifying that PC1&2 explained 76.6% of the variance,
inclusion of PC3 accounted for a cumulative 90.0% of the between site variance. All of
these attributes showed a variation with the perceived site quality, yet the variance of
individual attributes showed a range of variation that was attribute dependent, ( i.e. the
sponge category showed a very low level of inter-site variation, while the soft coral cover
showed a high inter-site variation as indicated by the length of the vector line).
76
Chapter 3. Conservation Value Index
80
Similarity
85
90
95
4
4
4
3
3
3
2
3
3
2
3
3
3
3
2
2
2
2
2
2
2
1
1
1
1
1
1
6
6
6
6
6
6
6
6
6
5
5
5
5
5
5
5
5
5
4
4
4
4
4
4
100
Figure 3.2 Dendrogram of Bray-Curtis (Group average) cluster analysis of all summary
attributes at all six study sites [site key; 1. Ridge, 2.Kaledupa Double Spur, 3. Kaledupa,
4. Pak Kasims, 5. Hoga NTA, 6. Sampela]
The attributes represented by vectors that run parallel to the change in reef
condition are thus supported as indicators of reef health. For example the hard coral cover
vector (HC) runs parallel to the variation in site quality from Sampela to Hoga NTA,
increasing in a positive direction along principal component one with higher cover. This
change in attribute value along the same axis as PC1 suggests that hard coral cover is an
ideal indicator metric. The other attributes which make suitable indicators include dead
coral which also showed a positive correlation with PC1, algal cover which showed a
negative correlation with PC1 and PC2, and coral rubble which also showed a negative
correlation with PC1 and PC2 (i.e. values increased at the sites with negative PC1
scores).
77
Chapter 3. Conservation Value Index
The categories for sponge, bare rock and other substratum did not show
significant between site variation to justify inclusion in the final index. Although dead
coral cover is recorded in the survey methodology (as are the cover of bare substratum
and sponges), and as such can be called upon if necessary The level of dead coral cover
found within the Wakatobi was also deemed too small to show inter-site variance and as
such was discarded from the final index.
The abundance of coral disease, coral bleaching, Acanthaster planci (COTs)
abundance and abundance of Drupella Gastropods was deemed ecologically important
enough to include in the overall monitoring programme. The levels of disease, bleaching
and COTs correlated strongly with the levels of hard coral cover and hence varied in a
similar direction across the range of sites. The abundance of Drupella gastropods
followed the same negative pattern as algal cover and coral rubble.
As well as variation across the range of sites, the cross products from the PCA
analysis also identified the following correlations between attributes; hard coral cover
and hard coral generic richness (r=0.69), coral rubble and total live cover (r=0.72),
generic richness of corals and total live cover (r=-0.65) also showed significant
correlation. Hard coral cover was also correlated with abundance of COTs, coral disease
and coral bleaching.
78
Chapter 3. Conservation Value Index
2
SC
KAL
1
R1
PC2
S
ALG
PK
RK
SAM
0
SPG
OTH
KDS
DC
HC
CR
-1
NTA
-2
-3
-2
-1
0
1
2
PC1
Figure 3.3 PCA plot to identify site classifications, PC1 & PC2 of summary benthic data
overlaid with vectors indicating influence of each individual attribute [site key; R1Ridge, KDS-Kaledupa Double Spur, KAL- Kaledupa, PK-Pak Kasims, NTA-Hoga NTA,
SAM-Sampela][Benthic categories:HC-Hard Coral, SC-Soft Coral, SPG-Sponge, CRCoral Rubble, ALG- Macro-algae, S-Sand, DC- Recently Dead Coral, RK –Bare Rock,
OTH- Other]
3.4.3 Fish Attributes
A similar PCA analysis carried out on the fishery attributes (Figure 3.5) identified
that PC 1-3 identified 87.4% of the variation between the sites. The attributes that varied
along the same gradient as perceived site quality were total fish abundance, total fish
species, the richness of the Scaridae, Chaetodontidae, Pomacentridae, Labridae,
79
Chapter 3. Conservation Value Index
Serranidae and Pomacanthidae families. The Acanthuridae richness and Shannon-Weiner
index of fish diversity showed variation along PC2 rather than PC1 gradient. All of these
attributes showed a similar level of between site variation as indicated by the length of
the vectors.
Cross products identified relationships between several of the fishery attributes
including total fish species and total fish abundance (r=0.72), Scaridae and
Chaetodontidae richness (r=0.86), Scaridae and Pomacentridae (r=0.86), Chaetodontidae
and Pomacentridae (r=0.79). The Scaridae also showed a relationship with the richness of
Acanthuridae(r= 0.78).
Work by Allen & Werner (2002) suggests that Indo-Pacific coral reef fish
assemblages can be represented by seven main fish families, the Scarridae, Serranidae/
Epinephelidae,
Labridae,
Pomacentridae,
Chaetodontidae.
80
Pomacanthidae,
Acanthuridae
and
Chapter 3. Conservation Value Index
4
p(Herivore)
2
NTA
Abundance
KAL
Chaetodont
P'canthid
No.Spp.
Scarid
P'centrid
PC2
PK
0
Serranid
Labrid
SAM
R1
Shannon
Acanthurid
p(Corallivore)
-2
KDS
-4
-4
-2
0
PC1
2
4
Figure 3.4 PCA plot to identify site classifications, PC1 & PC2 of summary fish
assemblage data overlaid with vectors indicating influence of each individual attribute.
[Site key; R1- Ridge, KDS-Kaledupa Double Spur, KAL- Kaledupa,PK-Pak Kasims,
NTA-Hoga NTA, SAM-Sampela]
The classification of the fish species into trophic groups with the use of the online
database Fishbase identified the proportion of the overall community in each trophic
group remained constant temporally (Figure 3.5).
81
Chapter 3. Conservation Value Index
(a) 2002
5%
12%
zooplanktivore
9%
herbivore
31%
carnivore
invertivore
19%
omnivore
corallivore
24%
(b) 2005
4%
14%
9%
31%
20%
22%
Figure 3.5 Proportion of the fish community belonging to the six trophic classes
identified across all six Indonesian sites in (a)2002 and (b)2005 [n=6]
The two groups included in the index were corallivores (4-5%) and herbivores
(9%) as these groups remained constant throughout the study period. The inclusion of
these two important groups can be used to identify change from this normal proportion
and hence be used as indicators of change in community composition.
82
Chapter 3. Conservation Value Index
3.4.4 Scoring attributes
The final index to be tested was compiled from twelve benthic and twelve fish
assemblage attributes. These are factors that as well as being identified to vary with reef
condition in the study area, have also been reported elsewhere as individual attributes of
reef condition (Tables 3.2 & 3.3). Some of these have set scoring criteria, for example the
reef condition index of Gomez et al. (1994) ranks reef condition by placing a reef into
four categories based on levels of hard coral cover. Here this has been adapted to the four
scoring levels of the CVI index, where less than 25% cover scores zero, 25-50% scores
one. 50-75% scores three and over 75% gets the maximum score of five. Other attributes
have been set intuitively such as coral rubble cover. Although the literature suggests that
increasing coral rubble cover on a reef is a negative factor (Perry, 2001), little
quantitative information exists to score this attribute. The scoring needs to take into
account intermediate disturbance, where occasional increases in rubble will occur
naturally and weigh this against increases due to anthropogenic disturbance, such as blast
fishing.
Soft coral is included as it is a known competitor of the reef building
scleractinia and will often replace the slower growing hard coral after a disturbance
(Bowden & Coll, 1983) and it is also known to vary along a gradient of water quality
(Fabricius & McCorry, 2006). Macro-algae is also known to compete spatially with the
scleractinia, and is again seen as a negative factor on coral reefs as high levels of algal
cover can out compete corals and lead to a phase shift to an algal dominated state
(McCook, 1999). The generic richness of hard corals was identified as a factor influenced
by both local and regional factors (Cornell & Karlson, 1996), and as such will vary with
83
Chapter 3. Conservation Value Index
changes in local reef condition. The diversity of the Scleractinia will also be affected by
interaction with the soft corals and macro-algae. The coral colony size has been shown to
be important in terms of reproductive output and hence local recruitment of new colonies
(Sakai, 1998), but again, quantitative values are scarce for coral maturity or reproductive
output rates related to colony size. The density distribution of corals has been identified a
important to reef condition and accretion in Australia by van Woesik and Done (1997)
and in Indonesia by Sukarno (1977). Although these two studies suggest density of coral
colonies will vary with reef condition, again no quantitative values are given for healthy
and impacted communities. Bellwood et al. (2006) described the effects of coral
bleaching on reef community composition and related effects to increased macro algae
and phase shifts to non-coral dominated states. The importance of monitoring for signs
and effects of coral bleaching is highlighted by Jokiel (2001). Goldberg and Wilkinson
(2004) associated bleaching with coral disease and predation in terms of monitoring for
impacts and Bruckner (2004) identified the need to monitor for signs of disease and
predation. The impacts caused by infestations of Acanthaster planci was identified by
Goreau et al. (1972) and later by Endean (1977), highlighting the need to monitor the
abundance of these coral predators. While Cumming (1999), did the same for infestations
of the corallivorous Gastropod, Drupella spp.
The abundance of fish is a widely reported attribute of coral reef communities
and has been suggested as an indicator of reef condition by McField & Kramer (2006),
while protocols exist for the collection of fish abundance data (Hill & Wilkinson, 2004).
Scoring values could be set from established regional MPA’s that are free from over
fishing and other impacts, while lower range scores can be established from exploited
84
Chapter 3. Conservation Value Index
reefs. Mundy & Allen (2000) used both abundance and fish diversity to assess the reef
fish assemblage of Papua New Guinea, while Jennings et al.(1995) recorded reductions in
diversity of reef fish with increased exploitation. Both Alcala & Luchavez (1993) and
Gratwicke & Speight (2005) related species richness to fish abundance. Values for
scoring species richness can be set from known species numbers in different regions,
although they would need to account for the likelihood of recording rare species. Allen
(2000) suggested that certain reef fish could be used as indicators of conservation
hotspots. Allen & Werner (2002) then suggested an index of reef fish assemblages could
be calculated by just including the seven most representative families of reef fish,
Chaetodontidae, Serranidae, Scaridae, Labridae, Pomacentridae, Pomacanthidae and
Acanthuridae. Their proposed index simply used the number of species present from each
of the seven families, and incorporated these into their index. With regard to the trophic
structure of the fish community, several papers have recently highlighted the importance
of monitoring the trophic structure of fish assemblages (Bellwood et al., 2003; Nyström,
2006), to identify changes in functional redundancy which could identify a phase shift.
This functional redundancy in the trophic structure was also found to be related to the
diversity of the assemblage. No quantitative values for these fish family attributes
currently exist.
The scoring criteria were established using searches of the literature and
analysis of the baseline data for the Wakatobi MNP in 2002. The levels were set either as
an established standard or in ranges that would allow the detection of changes in that
attribute.
85
Chapter 3. Conservation Value Index
Table 3.2 Scoring criteria for benthic attributes
Attribute/
Score
Score
Score
Score
Score
‘5’
‘3’
‘1’
‘0’
Hard coral (%)
76-100
51-75
26-50
0-25
References
Gomez et al., 1994;
Wilkinson, 2002
Soft coral (%)
>30
>20
>10
<10
Bowden & Coll, 1983
Fabricius & McCorry, 2006
Coral rubble(%)
<2
<5
<10
>10
Perry, 2001
Reigl, 2001
Macro-algae(%)
<5
<10
<20
>20
Lirman, 2000
McCook, 1999
Live cover(%)
>85
>70
>55
<55
McField & Kramer, 2006
Generic
>20
>10
>5
<5
Borel-Best et al., 1989
Cornell & Karlson, 1996
richness
Mean colony
>25
>15
>10
<10
Sakai, 1998
size (cm)
Number of
>100
>75
>50
<50
Sukarno, 1977
van Woesik & Done, 1997
colonies
Bleached (%)
Birkland, 1999
<0.1
<1
<2
>2
Bellwood et al., 2006
Jokiel, 2001
Diseased (%)
<1
<2
<5
>5
Bruckner, 2004
Goldberg & Wilkinson, 2004
COTs
<1
<2
<5
>5
Endean, 1977
Goreau et al., 1972
Drupella (%)
<1
<2
<5
86
>5
Cumming, 1999
Chapter 3. Conservation Value Index
3.4.5 Modelling Attribute values
The data from the Wakatobi MNP from 2002 to 2005 was used to generate the
linear regression equations shown in Table 3.4. Also shown are r2 values along with the F
and p values from ANOVA tests for significant relationships. Only the richness of the
Chaetodontidae, Serranidae and Pomacanthidae families, showed no linear temporal
relationship over the study period. Data for hard coral generic richness and the
proportions of the various trophic groups were not available for the entire study period
and so were not tested.
The equations were used to generate extreme values for all of the attributes to test
the index for sensitivity to change and robustness at extreme values. Values were
generated from the regression equations to simulate data from five years previous to this
study, as well as both five and ten years post this study. The trends and rates of change in
the benthic attribute data can be seen in Figure 3.6.
The equations generated for the fish community were also used to generate
extreme values (Figure 3.7), which were again modelled for five years prior to this study
and both five and ten years post study. The Conservation Value Index scores were
calculated from these modelled data (Table 3.5) and used to test the indexes viability
using extreme high and low values.
To confirm the usefulness of these extrapolated values from the regression
equations, the forecast ‘+ 5 years’ data was compared to that collected from reef surveys
in 2007 (Figure 3.8). No significant difference was found between the observed and
expected values when performing a Ȥ2 test of contingency.
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Chapter 3. Conservation Value Index
Table 3.3 Scoring criteria for fish assemblage attributes (1250m-3)
Attribute/
Score
Score
Score
Score
Score
‘5’
‘3’
‘1’
‘0’
References
Fish abundance
>1000
>500
>250
<250
Hill & Wilkinson, 2004
McField & Kramer, 2006
Shannon-
>3.00
>2.50
>2.00
<2.00
Weiner index
Species
Munday & Allen, 2000
>100
>75
>50
<50
>8
>6
>4
<4
Richness
Serranidae
>4
>2
>1
<1
>6
>4
>2
<2
>15
>10
>5
<5
>4
>2
>1
<1
Allen, 2000
Allen & Werner, 2002
>15
>10
>5
<5
Richness
Acanthuridae
Allen, 2000
Allen & Werner, 2002
Richness
Pomacentridae
Allen, 2000
Allen & Werner, 2002
Richness
Pomacanthidae
Allen, 2000
Allen & Werner, 2002
Richness
Labridae
Crosby & Reece, 1997
Allen & Werner, 2002
Richness
Scaridae
Alcala & Luchavez, 1993
Gratwicke & Speight, 2005
Richness
Chaetodontidae
Jennings et al. 1995
Allen, 2000
Allen & Werner, 2002
>8
>4
>2
<2
Richness
Allen, 2000
Allen & Werner, 2002
Proportion
0.10-
0.08-0.09
0.06-0.08
<0.06
Bellwood et al., 2003
Herbivores
0.12
0.13-0.14
0.14-0.16
>0.16
Nyström, 2006
Proportion
0.04-
0.03-0.04
0.02-0.03
<0.02
Bellwood et al., 2003
Corallivores
0.05
0.05-0.06
0.06-0.07
>0.07
Nyström, 2006
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Chapter 3. Conservation Value Index
HCC
90
SC
% Cover
80
CR
70
ALG
60
LC
50
40
30
20
10
0
1
2
3
4
5
6
Year
7
8
9
10
Figure 3.6 Linear Regression modelled benthic attribute values (%) over ten year
period[Categories: HCC-Hard coral cover,SC-Soft Coral,CR-Coral rubble,ALGMacroalgae,LC-Live cover]
The modelled CVI scores generated from the regression values performed as
would be expected (Table 3.5). The values for five years prior were higher than current
values, as would be expected from the linear trend. The benthic component scored 55 out
of a possible 60 rating the theoretical site A. The fisheries component scored 48 out of
60, giving a rating of 2. The two modelled values from five years and ten years post study
showed lower scores than present, again as would be expected with a linear decrease with
time. The five year benthic score was 23, with the ten year score just 13, ranking both
sites as D. For the fish component, the five year score was 32 with the ten year score at
just 15. These gave the theoretical sites scores of 3 and 4 respectively.
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Chapter 3. Conservation Value Index
Table 3.4 Regression values used to model changes in attribute values according to
current trends [ nd= no data]
ANOVA
Equation
2
Attribute
(y=mx+c)
R
F
df
p
Hard coral
-5.42x + 53.28
0.19
37.00
163
<0.001***
Soft coral
2.07x + 10.65
0.06
8.10
136
<0.01**
Coral rubble
1.82x + 3.42
0.07
9.95
136
<0.01**
Macro-algae
-5.46x + 30.53
0.31
61.58
136
<0.001***
Total live cover
-6.46x + 91.44
0.19
32.13
136
<0.001***
nd
nd
nd
nd
nd
Mean colony size
3.55x + 16.73
0.17
27.91
136
<0.001***
Fish Abundance
-57.21x + 1054.48
0.02
2.36
151
<0.05*
Shannons Fish diversity
0.151x + 2.55
0.12
20.36
151
<0.001***
Total fish species
6.64x + 44.57
0.23
44.27
151
<0.001***
Margalefs sp. richness
1.10x + 6.21
0.35
82.55
151
<0.001***
Chaetodontidae richness
-0.37x+ 7.750
0.02
3.61
149
>0.05
Serranidae richness
0.14x + 1.36
0.02
2.43
149
>0.05
Labridae richness
1.6x + 6.95
0.16
28.48
149
<0.001***
Scaridae richness
0.55x + 1.49
0.14
24.56
149
<0.001***
Pomacanthidae richness
0.08x + 1.93
0.01
1.03
149
>0.05
Pomacentridae richness
1.21x + 12.54
0.12
20.46
149
<0.001***
Acanthuridae richness
0.81x + 2.28
0.29
61.71
149
<0.001***
Proportion of herbivores
nd
nd
nd
nd
nd
Proportion of corallivores
nd
nd
nd
nd
nd
Coral Generic richness
[* - significant, ** - highly significant, ***very highly significant]
90
Chapter 3. Conservation Value Index
30
1200
25
1000
20
800
15
600
10
400
5
200
0
0
Chaetodontidae
Serranidae
Labridae
Scarridae
Pomacanthidae
1
2
3
4
5
6
Year
7
8
9
Pomacentridae
Acanthuridae
ABUNDANCE
10
Figure 3.7 Regression modelled fish community attribute values over ten years following
current trends. (Family richness 1250m-3 on left axis, abundance per 1250m3 on right
axis)[Years 1-4 measured, remainder predicted]
100
Predicted +5yr
80
Recorded 2007
60
40
20
So
ft
Ha
rd
co
ra
l
co
Co
ra
l
ra
lr
ub
M
bl
ac
e
ro
al
ga
HC
e
Li
ve
ge
ne
co
ve
r ic
r
ric
HC
hn
es
co
s
lo
No
ny
.H
siz
C
e
co
lo
ni
%
es
Bl
ea
ch
%
ed
D
ise
as
e
No d
%
.C
w
O
ith
Ts
Dr
up
el
la
0
Figure 3.8 Comparison of modelled regression data (2002 +5 years) and surveyed park
mean (±s.e.) data from 2007
91
Chapter 3. Conservation Value Index
Table 3.5 CVI values for hypothetical sites modelled from regression data for -5, +5 and
+10 years from 2002 data.
3.4.6
Benthic
Fish
CVI
Score
Score
Score
-5 years
55
48
A
2
+5 years
23
32
D
3
+10 years
13
15
D
4
Final Index
After summing the attributes to give benthic and fish scores they can be
separated into five categories to give the A-E and 1-5 rankings. (e.g. top quintile
scores A). From the attributes selected for the initial 2002 index, the sites were ranked as
shown in Table 3.6. Ridge 1 was clearly the highest quality site ranked as B2. The sites at
Kaledupa Double Spur and Kaledupa, Pak Kasims and the Hoga NTA also attained the
rank of C for their benthic component, with all scoring 3 for their fish component, with
the exception of Kaledupa which scored a 4 for the fish component. Although these sites
all scored C for benthic components, there are sight variations in the underlying scores,
with Kaledupa Double Spur scoring highest at 33 out of 60, with Pak Kasims scoring just
25 from 60. The Sampela site is ranked last in 2002 with a CVI score of D4.
There had been some improvements in some scores by 2005, but decline in others
(Table 3.7). The sites at Ridge 1 were still the highest scoring, remaining classed as B2
by the CVI although both the benthic and fish components did show improvements in
their underlying index scores. The Kaledupa Double Spur site had improved from C to B
with an actual score increasing from 33 in 2002 to 41 in 2005.
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Chapter 3. Conservation Value Index
Table 3.6 Classification of sites within the Wakatobi Marine National Park with the
proposed Conservation Value Index (2002) [Site key: R1-Ridge 1, KDS-Kaledupa Double
Spur, KAL-Kaledupa, PK-Pak Kasims, NTA-Hoga NTA, SAM-Sampela ]
CVI
Site
R1
KDS
KAL
PK
NTA
SAM
score
Benthic
Fishery
40
40
B
2
33
30
C
3
29
23
C
4
25
25
C
3
29
32
C
3
23
15
D
4
Table 3.7 Classification of sites within the Wakatobi Marine National Park with
the proposed Conservation Value Index (2005) [Site key:R1-Ridge 1, KDS-Kaledupa
Double Spur, KAL-Kaledupa, PK-Pak Kasims, NTA-Hoga NTA, SAM-Sampela ]
CVI
Site
R1
KDS
KAL
PK
NTA
SAM
score
Benthic
Fishery
44
42
B
2
41
32
B
3
28
36
C
3
33
40
C
2
27
38
C
2
24
22
D
4
93
Chapter 3. Conservation Value Index
The benthic categories for the other four sites also remained constant over the
study period, though it is worth noting that the only site of these four to show
improvement was that in the Hoga NTA. The NTA, Pak Kasims and Kaledupa also
showed improved fish component scores improving to 2, 3 and 2 respectively. The
underlying fisheries scores showed improvement at all of the sites, with Kaledupa and
Pak Kasims showing significant improvements. Sampela remained ranked as the lowest
quality site for both categories.
Once the initial index values had been calculated, the index values for a particular
reef or site were then be plotted geographically on maps or satellite images and viewed as
an overall management tool (Figure 3.10). Temporal changes can be monitored using this
method (Figure 3.11) by simply comparing before and after images/scores. This also
allows the identification of areas for further detailed biological study, possibly using the
already existing data from the surveys that was not utilised by the Conservation Value
Index.
The procedural steps necessary to undertake a Conservation Value Index
assessment of a reef is shown in Figure 3.9. Collect attribute data as per survey protocol
(Appendix I), then calculate mean values. Score these according to values in tables 3.2
and 3.3 (this can be automated using a simple MS Excel spreadsheet). Sum the attribute
scores to get the two part index values for the benthic and fish components of the index.
The type of output can then be created dependent upon the level of stakeholders
knowledge. The CVI score can then be represented graphically either as a map or a grid
display, or in tabular format. Underlying attribute scores can also be presented as
necessary.
94
Chapter 3. Conservation Value Index
Reef Flat
3 Replicate
transects as per
survey protocol
Reef Crest
Reef Slope
3 Replicate
transects as per
survey protocol
3 Replicate
transects as per
survey protocol
Calculate
mean
values for
all benthic
attributes
Written
report
Calculate
mean
values for
all fish
attributes
Score + sum
attributes
(spreadsheet)
Score + sum
attributes
(spreadsheet)
Benthic
score (A-E)
Fish score
(1-5)
Map
output
Grid
output
Tabular
output
Figure 3.9 Flow diagram of the CVI procedural steps
95
Chapter 3. Conservation Value Index
500m
N
R1 [B2]
KDS [C3]
PK [C3]
KAL [C4]
NTA [C3]
SAM [D4]
Figure 3.10 Output for Conservation Value Index classification of sites within the
Wakatobi Marine National Park (2002 Site means). Image courtesy LandSAT Millenium
coral reef archive
96
Chapter 3. Conservation Value Index
500m
N
R1 [B2]
KDS [B3]
PK [C2]
KAL [C3]
NTA [C2]
SAM [D4]
Figure 3.11 Output for Conservation Value Index classification of sites within the
Wakatobi Marine National Park (2005 Site means). Image courtesy LandSAT Millenium
coral reef archive
Temporal changes in the index scores can also be presented in the form of a grid
(Figure 3.12) that can clearly show changes in site condition from the top right (green
area indicating high scores) and the bottom left (red area indicating low scores). For
example it can be seen that there is little change in the Ridge 1 sites (blue diamonds),
while the improvement in the Kaledupa (yellow triangles) fish scores discussed earlier
are clearly visible in moving from a 4 in 2002 to a high 3 in 2005. These can be plotted as
park mean values or for individual sites so changes in condition can be followed
temporally over longer periods.
97
Chapter 3. Conservation Value Index
Pristine habitat
Priority habitat
for conservation
R1
R102
02
KDS
KDS02
02
11
KAL
KAL02
02
PK
02
PK 02
22
NTA
NTA02
02
SAM
02
SAM 02
Good habitat
Degraded habitat
33
R1
R105
05
KDS
KDS05
05
Severely
degraded habitat
44
KAL
KAL05
05
PK05
PK05
5
5
NTA05
NTA05
SAM05
SAM05
E
D
C
B
A
Figure 3.12 Grid style output of CVI values [2002 solid, 2005 open], x-axis shows
benthic component (A-E), y-axis shows fish component (1-5).
The grid output sown in Figure 3.12 can be further sub-divided to allow the
simple characterisation of overall reef condition. Those reefs in the top-right portion
could be labelled ‘pristine’, then declining towards the bottom-left to ‘severely
degraded’.The upper middle portion could be deemed ‘prioriy habitat for conservation’,
the mid-section deemed as ‘good’. The final lower section could be deemed as
‘degraded’. Therfore the Sampela site would be rated as degraded habitat, while the
Ridge site should be deemed ‘Priority habitat for conservation’.
3.5 Discussion
3.5.1 Site ranking
The ordination of sites was shown to vary with the assessment metric used, and as
such highlighted the problems in current assessments that utilise a single univariate
technique to differentiate between reefs of varied condition. A multivariate approach as
98
Chapter 3. Conservation Value Index
suggested by Extence et al. (1987), is more suited to providing an ordination of sites
based on numerous metrics. The site ranking achieved with the PCA analysis ranked the
sites according to numerous metrics from both the benthic and fish communities. Using a
multivariate technique allowed the ordination of the sites in a similar way to perceived
condition and allowed the identification of reef attributes that also varied in this same
direction or order. The two extremes tie in with local knowledge of the area with the
Sampela site being the most exploited due to its location adjacent to the Bajou village of
Sampela, this site is also subject to high levels of sedimentation (Crabbe and Smith,
2005). The Ridge 1 site is the least impacted site as the lack of a reef flat and the offshore
location mean no gleaning occurs there. As the crest is several metres below the surface,
it is also minimally impacted by the artisanal fishing techniques used by local fishers.
The PCA ranked the sites along principal component one with the Hoga NTA site first,
closely followed by Ridge 1, then Kaledupa and Pak Kasims and Kaledupa Double Spur,
which scored similar values, with the Sampela site scoring lowest on PC1. These scores
agree with the output of the cluster analysis that shows the Kaledupa, Pak Kasims and
Kaledupa Double Spur sites to be most similar to each other.
3.5.2 Benthic attributes
The PCA plots overlaid with the vectors representing the individual attributes
allowed the identification of those attributes which varied across the range of site
conditions. This also identified the attributes that showed the greatest and least variation
between sites. The benthic attributes identified from the individual PCA represent a
number of important groups of reef biota as well as many of the commonly used reef
99
Chapter 3. Conservation Value Index
condition reporting attributes. The PCA provides evidence to support the common use of
hard coral cover as a method of reef assessment as it clearly varies across the range of
reef condition. The direction of influence of the various attributes again supported the site
ordination results with factors such as coral rubble and algal cover working in the
direction of the poorest quality Sampela site. The length of the vector also suggested
significant inter-site variance in these attributes. It is also interesting to note the effect of
soft coral on the ordination of sites as this works on PC2 rather than PC1, allowing the
separation of some of the sites that are similar on PC1. The recently dead coral measure
showed influence in the same direction as hard coral, but was excluded due to the
minimum observations at most sites within the Wakatobi.
Several threat indicator metrics were included as these will allow the reporting as
to whether the reefs within their own area are in good condition, whether they are at risk
from threats that may alter reef condition and whether effective management actions are
in place to deal with the threats, which Noordeloos et al., (2004) identified as one of the
key objectives of status reporting. It is worth noting the relationship that exists between
the bleaching, disease and COTs attributes and hard coral cover.
3.5.3 Fish attributes
The fish community attributes also ordinated the sites along PC1. The abundance
of fish, species richness and species richness in families such as the Serranidae, Scaridae,
Labridae and Pomacentridae all showed variation across the range of sites, with their
vectors influencing the assemblage in the same direction as perceived condition.
Abundance and richness are also commonly used in reef assessment, while the inclusion
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Chapter 3. Conservation Value Index
of the richness of certain family groups should allow a more detailed assessment of reef
fish stocks to be carried out, without the need for taxonomic expertise to identify fishes to
species level. The work of Allen and Werner (2002) suggested this method of assessing
coral reef fish assemblages using just these seven families and is supported by the PCA
output as these seven indicator families all vary in species richness in line with perceived
reef condition. The inclusion of the trophic proportions of the fish community in the
form of corallivores and herbivores, shows that these two groups work in opposition to
one another with both showing variation across PC2, but in different directions. The fact
that the proportions of the fish assemblage adopting these trophic positions remain
constant both between sites and temporally means that monitoring these proportions
should provide a useful early warning system to identify shifts in community structure,
such as those which have occurred with overfishing in the Caribbean (Bellwood et al.,
2004; Mumby et al., 2007).
3.5.4 Scoring attributes
The scoring of the attributes within the index proved to be the most complex part
of the index development as literature providing values to support the set levels was
scarce. Some did exist such as the reef condition index of Gomez et al., (1994), but the
majority had to be set by making informed decisions, which though subjective, referred
to the baseline data from the first year of the monitoring program. The setting of the
scoring values and thresholds will be dependent upon the aims of the assessment and the
level of change deemed necessary for the study. Such a method of assigning qualitative
scores to quantitative data will always be subjective, but can still be useful to allow the
combination of attributes into a multi-attribute index. In this case, where quantitative data
101
Chapter 3. Conservation Value Index
for attributes did not exist, the values were set by comparing values to the baseline values
from the initial Wakatobi surveys, and as such allow changes from this baseline condition
to be monitored. The individual scores could be set by consultation with stakeholders in
terms of quantifying levels of change that should affect the scoring system. Such a
method is utilised in EU based Environmental Impact Assessments (Glasson et al., 2003)
where impact attributes are weighted for importance by a panel of consultants, who
decide which attributes show impacts of importance and also decide upon levels of
acceptable impact or change in the measured variables.
The scoring of the threat attributes was again subjective and adjusted for the
Wakatobi baseline. Although a wealth of literature exists about the causes and effects of
bleaching and disease, very little quantitative data exists as to what should be considered
a bleaching event in terms of proportion of reef corals affected.
Ideally, dose-response curves for each attribute would be beneficial as called for
by Jameson et al. (2001), but here it is difficult to establish the effects of a single factor
on coral reef attributes that show complex interactions between multiple attributes which
all react in different ways to different impacts.
3.5.5 Modelling attribute values
The index classifies the sites current condition, but the modelled data from the
linear regressions was needed to identify whether the index will hold true if dramatic
changes were to occur on the reefs. Although the relationships and changes in the
measured attributes may not follow a linear relationship in reality, this was deemed an
appropriate way to generate values at either end of the scale, both very good and very
poor condition. These values have been produced, from the regression equations and
102
Chapter 3. Conservation Value Index
were shown to indicate a good condition reef (-5years) and a very poor condition reef
(+10years) when classified using the Conservation Value Index. It is useful to note that
the plus five year predicted value were not significantly different from the actual values
surveyed after five years, suggesting that the linear model used was appropriate to give
realistic scores for the different quality reefs. In reality it is more likely that an
exponential decline would be occurring and once the values of cover and abundance get
to a certain low threshold value, they will persist at this low level for some time. The
example of hard coral cover at the Sampela site supports this view (see Chapter 4). For
other attributes, such as macro-algae, it is likely that the relationship would follow a
positively skewed distribution, where the ideal, high scoring values are low percentage
cover and the majority of values with high percentage cover (or very low) gain the lowest
score.
3.5.6 Final Index
The current index scores the sites within the park in an appropriate order,
providing some separation between sites of different quality with different levels of
impact. The index values do not change significantly over the three years of this study,
yet the underlying scores do show trends in changes in condition.
This baseline can be compared to ongoing monitoring data and used to identify
future changes. The majority of the reefs are in average to poor condition, with the odd
exception (see Chapter 4 for a full assessment). The fish community status also appears
relatively poor for such a diverse region. The visual outputs of the LandSat images and
also the grid style output are ideal for disseminating this data to managers and local
stakeholders as they are easily interpretable by many levels of audience. The overlaying
103
Chapter 3. Conservation Value Index
of scores and the underlying surveyed attribute values has obvious application in GIS
projects, which again would allow the dissemination of complex data sets to a wide range
of audience.
The 24 included attributes could be fully interchangeable for different parks or
regions of the world. For example in Ras Mohammed Egypt, where fishing is not a major
threat, but large numbers of tourists are believed to be degrading the reefs (Hawkins &
Roberts, 1992), then some fish attributes could be replaced by attributes to monitor
physical damage to the reef. Attributes could be extended to account for coral growth
and recruitment rates, to monitor for the effects of climate change and acidification.
The outputs of the CVI can be used to monitor management actions and their
effectiveness, for example the usefulness of closing areas to the public can be assessed by
monitoring changes in the CVI score over the course of the management action. If the
scores improve the action can be judged successful, whereas if there is no change or a
decline in values, then alternative management strategies may be necessary. The
inclusion of such a wide range of attributes as suggested by Jameson et al. (2001) can
reassure managers that the reef community is responding to action, where the monitoring
of a single factor such as hard coral cover may not.
3.5.7 Conclusion
The proposed Conservation Value Index has been shown to be an accurate and
effective way to rapidly assess the health of a coral reef system as called for by Eakin et
al. (1997). The index ordinates sites in a comprehensive manner that cannot be achieved
using the traditional univariate assessment methods. It also meets the requirements of
104
Chapter 3. Conservation Value Index
Jameson et al. (2001) in providing a classification of reef condition along a continuum
which allows the ranking of sites in order to allow prioritisation of conservation efforts.
The varied methods of reporting the index with graphical based output will be of
use to stakeholder groups in many developing countries where understanding of complex
biological data sets can be problematical to management. Although as the survey data has
been collected to generate the CVI, the underlying data is also available should a more in
depth scientific assessment be required. The index also has great potential for use as a
tool to monitor the effectiveness of management actions.
The proposed Conservation Value Index is used in the case studies in the
Wakatobi Marine National Park, Sulawesi, Indonesia in Chapter 4 and the Ras
Mohammed National Park, Sinai, Egypt in Chapter 5, where it is compared to traditional
univariate methods of reef assessment.
105
Chapter 4. Case Study I Wakatobi Marine National Park, Indonesia
CHAPTER 4. Case Study I: Wakatobi Marine National Park, Indonesia
4.1
Abstract
This chapter uses the Operation Wallacea monitoring program data collected
in the Wakatobi MNP from 2002 to 2007 to assess changes in the condition of the
parks reefs over this six year period. It then uses the CVI developed in Chapter 3 to
also assess changes in reef condition and compares the two methods of reef
assessment. Twenty four attributes of the benthic and fish assemblages were recorded
and assessed for temporal change using univariate and multivariate techniques.
Univariate techniques such as ANOVA show that the percentage cover of many
benthic attributes is declining. For individual sites the monitoring identified that the
Sampela site changed little but was already of reduced condition compared to the
other five sites. This data also identified that the protected Hoga NTA site showed the
slowest decline in hard coral cover. For the park as a whole, the hard coral cover
declined by 52.5% over the study period from 46.7(±3.4)% in 2002 to 22.2(±4.0)% by
2007, the coral rubble cover increased from 6.8(±1.5)% to 14.6(±3.0)% over the same
period. There were also significant reductions in mean fish abundance which declined
from 925.7(±178.6) in 2002 to 597.7(±94.6) in 2007. The monitoring data showed
significant declines in many important classes of reef attribute, with declines recorded
for almost all attributes in 2006. The CVI assessment also showed declines in benthic
scores at all sites except Pak Kasims and declines in the fish assemblage scores. The
attenuation in the 2006 data recorded in the monitoring program showed large
declines in CVI scores, suggesting the index is a good indicator of reef condition that
will vary with changes in reef condition, allowing the presentation of complex data
sets to non-experts. The CVI scores also differentiate between the sites as they show
spatial variability, even when they do not show clear temporal change.
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4.2
Introduction
4.2.1 Background
Information included within this chapter represents a report of the scientific
monitoring program implemented by Steve McMellor for the Coral Reef Research
Unit, University of Essex and Operation Wallacea, in collaboration with The
Indonesian Institute Of Science (LIPI) and The Wallacea Development Institute, over
a six year period from 2002 to 2007.
4.2.2 Monitoring Program
This Operation Wallacea monitoring program was established in 2002 to;
1. Understand how the abundance and diversity of scleractinian corals
change annually in different areas of the study area subjected to
varying management practices and pressures.
2. Understand how the characteristics of benthic biological and nonbiological features change annually in different areas of the study area
subjected to varying management practices and pressures.
3. Understand how the abundance and diversity of fish associated with
coral reefs change annually in different areas of the study area
subjected to varying management practices and pressures.
The coral reef monitoring program was first established in 2002 when 108
permanent transects were laid at 12 sites around the study area in replicates of three at
the reef flat (10 m horizontal distance on the landward side from the reef crest), reef
crest and upper reef slope (defined by habitat type and a depth of 10 m)(Figure 1.1).
For the six north-east Kaledupa sites (Ridge 1, Kaledupa Double Spur, Kaledupa, Pak
Kasims, Hoga NTA and Sampela), surveys were repeated annually for six years,
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Chapter 4. Case Study I Wakatobi Marine National Park, Indonesia
whereas for the west Kaledupa sites (Sombano, Montigola and Taou), the surveys
were repeated after a five year interval. Specifically the following data was collected
as part of the monitoring program;
a. The percentage cover, diversity and community structure of hard corals
as assessed by a 50 m continual line intercept transect.
b. The percentage cover of soft corals as assessed by a 50m continual line
intercept transects.
c. The percentage cover of macro algae as assessed by a 50m continual
line intercept transect.
d. The percentage cover of dead coral and coral rubble as assessed by a
50m continual line intercept transect.
e. The density, diversity and the community and functional structure of
coral reef fish as assessed by a 50 m by 5 x 5 m 25 minute restricted
effort belt transect.
f. The abundance of threats present in the form of bleaching, disease and
predators, such as Crown Of Thorns starfish (COTs) and Drupella.
This chapter aims to provide an assessment of both the benthic assemblage
and fish assemblage of the reefs of the Kaledupa sub-region of the Wakatobi MNP.
The assessment will be carried out by site and also for the park as a whole to identify
any changes occurring over the six years of the Operation Wallacea monitoring
program, both in terms of univariate assessments and also using the Conservation
Value Index described in Chapter 3. A comparison in the response of the univariate
data was made to changes in the CVI scores and values to ensure the CVI responded
to change in an appropriate manner.
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Chapter 4. Case Study I Wakatobi Marine National Park, Indonesia
To meet these aims, the objectives of this chapter are to;
(a) Produce a site specific assessment of the benthic assemblages within the
Wakatobi MNP using multiple univariate attributes from 2002-2007.
(b) Produce a site specific assessment of the fish assemblages within the
Wakatobi MNP using multiple univariate attributes from 2002-2007.
(c) Produce an assessment of the reefs of the Wakatobi MNP using multiple
univariate attributes from 2002-2007.
(d) Classify the reefs of the Wakatobi MNP using the Conservation Value Index
from 2002-2007.
4.3
Methodology
4.2.1 Benthic assemblage
The main group studied were the hermatypic corals (Order Scleractinia), other
groups of sessile reef organisms monitored included the soft corals (Alcyonacea),
sponges (Porifera), macro algae and Crustose Coralline Algae. The area of coral
rubble, dead corals and area of bare substratum available for recruitment was also
recorded.
The annual monitoring program was carried out at nine sites within the park at
three depths; on the reef flat, (1-2m depth), the reef crest (2-6m depth) and upper reef
slope (9-12m depth). Surveys were undertaken between June and September annually.
A combination of several survey methods were used to quantify spatial and temporal
changes in the benthic community. The principal technique used was the continuous
Line Intercept Transect (English et al., 1996), combined with belt transects (Loya,
1978). After generating species-area curves, three 50 metre long transect tapes were
laid along depth contours parallel to the shoreline for each depth at each site, giving a
total of nine transects per site with total length 450m. All life forms intercepting the
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Chapter 4. Case Study I Wakatobi Marine National Park, Indonesia
transect line were recorded to genus with the length intercepting the transect tape
recorded to the nearest centimetre. An individual was defined as any colony/
individual growing independently from its neighbours. In cases where a colony is
divided into multiple parts by the death or overgrowth of intermediate parts, each part
is considered a separate colony. The area intercepting the transect tape was classified
according to the benthic category system from the methodology of English et al.,
(1996). The percentage cover of each category was then calculated by dividing by the
total transect length.
4.3.2 Fish Assemblage
The following section outlines the procedure for undertaking underwater
visual census surveys at the monitoring sites after the AIMS fish monitoring protocol
(adapted from Halford and Thompson, 1994).
Two divers entered the water at the mooring buoy marking each site. One
observer laid a 50m long transect tape parallel to shore along the contours of the reef.
After laying the tape, the transect was given a wide berth and left alone for a
minimum of 10 minutes to allow the fish behaviour to settle after the disturbance
caused by the surveyors presence.
The first observer conducted the 50 metre long by 5 metre wide by 5 metre
high box survey by swimming along the centre line of the transects over a 25 minute
period. The observer counted all fish sighted within the area 2.5 metres either side of
and up to five metres above the centre line, recording species and number of
individuals.
Nine of these 50m belt transects were completed at each site, three at each of
the three depths on the flat, crest and upper reef slope, as per the benthic survey, with
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Chapter 4. Case Study I Wakatobi Marine National Park, Indonesia
a horizontal gap of at least 20m between transects at the same depth. This gave a total
survey area of 11250m3 per site (each belt giving 1250m3).
In an attempt to reduce variability in fish densities (due to diurnal influences
on behaviour) sampling excludes the high activity periods of early morning and late
afternoon. A preliminary study in 2002 identified no significant differences in fish
abundance between morning and afternoon. Sampling was been limited to between
0900 and 1600.
4.3.3 Data analysis
All transect data were square root transformed to satisfy the distribution and
variance assumptions for repeat measures ANOVA. Data was analysed using the
statistical computer package SPSS using both one- and two-way ANOVA. Tukey
post-hoc tests were used to identify changes between sites and years were differences
were found by ANOVA.
4.3.4 CVI methodology
Data collected from the nine transects at each site were then used to generate
CVI scores for the twelve benthic and twelve fish assemblage attributes. These were
scored according to the methods described in full in Chapter 3. The combined scores
were then represented in graphical and tabulate format to allow easy interpretation of
the data collected at each site over the six years of the study.
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4.4
Results
4.4.1
Benthic assessment
The percentage hard coral cover has shown significant declines for all of the study
sites within the park (Figure 4.2a) over the study period from 2002 to 2007. A
significant difference in cover between the years of the study (F5,260=60.8;p<0.001)
and also significant differences in cover between sites (F5,260=30.1;p<0.001) was
identified by the two-way ANOVA. There was also a significant interaction in coral
cover between year and site (F25,260=3.0;p<0.001). The hard coral can be seen to
decline significantly between 2004 and 2005 at all sites with the exception of the
NTA site, which showed no significant decline in hard coral cover over the study
period. Tukey post-hoc tests found that there was no significant difference in hard
coral cover from 2002 to 2004, but the cover data from 2005 was different to all other
years (p<0.01). No significant difference was found in coral cover between 2006 and
2007, but for these years cover was significantly lower (p<0.001) than for the first
three years of the study. In terms of between sites within years, Sampela was found to
have significantly lower coral cover than all the other sites (p<0.001), while the
Kaledupa site was also shown to be significantly different to all the other sites
(p<0.01), showing the largest decline.
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2002
(a) Hard Coral Cover
70
2003
2004
60
2005
2006
50
% Cover
2007
40
30
20
10
0
R1
KDS
KAL
(b)Live cover (%)
100
Site
NTA
PAK
SAM
(c)Mean Colony Size (cm)
50
40
80
30
60
20
40
10
20
0
0
R1
KDS
KAL
NTA
PAK
50
(d)Coral Rubble (%)
50
R1
SAM
KDS
KAL
NTA
PAK
SAM
(e)M acro Algae (%)
40
40
30
30
20
20
10
10
0
0
R1
KDS
KAL
NTA
PAK
SAM
R1
KDS
KAL
NTA
PAK
SAM
Figure 4.1 Percentage cover of five benthic attributes at the six study sites within the
Wakatobi MNP over six years. (a) Hard coral cover, (b) total live benthic cover, (c)
Mean hard coral colony size in centimetres, (d) percentage coral rubble cover, (e)
percentage macro-algal cover.
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Chapter 4. Case Study I Wakatobi Marine National Park, Indonesia
The total live cover (including hard corals, soft corals and sponges) showed a
similar pattern to the hard coral (Figure 4.1b), with no significant difference over the
first three years of the study, but then a steep decline and then no difference for the
remaining three years. Significant declines were observed between the years
(F25,257=69.2;p<0.001), with Tukey post-hoc tests finding no significant difference
between the first three years, then finding that 2005 and 2007 were similar with no
significant difference between them, but significantly lower cover than the first three
years (p<0.001), whereas the cover from 2006 was found to be significantly lower
than all other years (p<0.01). Significant differences between sites were identified
(F5,257=25.3;p<0.01) with Sampela showing significantly lower total live cover than
all other sites for all years of the study (p<0.001). The NTA site showed lower cover
than the Ridge 1 (p<0.001) and Kaledupa (p<0.01) sites, and higher cover than
Sampela (p<0.001), but was not significantly different to Kaledupa Double Spur and
Pak Kasims sites. The total live cover has declined from a mean of 83.7(±1.3)% in
2002 to just 51.3(±5.0)% in 2007.
The mean hard coral colony size (Figure 4.1c) was found to be significantly
different between the study years (F5,257=54.0;p<0.001), with post-hoc tests
identifying that the mean colony size for 2005 was significantly larger at all sites
(p<0.001), while the mean colony size in 2006 was significantly smaller at all sites
(p<0.001). There was no significant difference in mean colony size between the first
three years of the study and the final year when the mean colony size was
20.0(±0.8)cm across all sites. There were significant between site differences in mean
hard coral colony size (F5,257=19.2;p<0.001). Post-hoc tests showed no significant
difference between sites for the first three years, except Pak Kasims which was found
to have a significantly larger mean coral colony size (p<0.001) than the other sites.
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The mean hard coral colony size was originally recorded at 22.2(±1.9)cm, in 2002,
and is currently 23.2(±1.3)cm in 2007.
The percentage cover of coral rubble increased across the period of the study
at all sites (Figure 4.2d). There was a significant difference between the study years
(F5,257=34.5;p<0.001), with no significant difference in rubble cover over the first
three years, nor between 2005 and 2007, although these two years showed higher
cover than the first three years (p<0.001). The rubble cover in 2006 showed a
significant difference to all other years (p<0.01) with the highest values recorded at all
sites during that year. With regard to between site differences, Sampela consistently
showed the highest coral rubble cover (p<0.01), with the exception of the 2006 value
for Pak Kasims, while Kaledupa and Ridge 1 were not significantly different to one
another, they both had significantly lower coral rubble cover than did all the other
sites (p<0.001). There was a significant interaction between site and year identified by
the two-way ANOVA (F25,257=2.0;p<0.001). The negative association between hard
coral cover and coral rubble cover can be seen clearly in Figure 4.2, where samples
with high coral cover tend to have low coral rubble cover and vice versa. A significant
relationship between hard coral cover and coral rubble cover (rs=0.71;p<0.001) was
found. The coral rubble cover was originally recorded at 5.6(±1.4)% in 2002, and has
increased to currently 14.6(±1.9)% in 2007.
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Chapter 4. Case Study I Wakatobi Marine National Park, Indonesia
% Hard Coral Cover
80
60
40
20
0
0
10
20
30
% Coral Rubble
40
50
60
Figure 4.2 Association between hard coral cover and coral rubble cover within the
Wakatobi MNP
The Macro-algal cover (Figure 4.1e) varied significantly between years
(F5,257=81.9;p<0.001) and also between sites (F5,257=8.1;p<0.001), a significant
interaction between site and year was also recorded (F25,257=3.8;p<0.001). As with all
of the other factors reported, there was no significant difference in macro-algal cover
across the sites over the first three years of the study from 2002 to 2004. There was no
significant difference either in the data from 2005 and 2006, although the algal cover
from these years found to be significantly lower (p<0.001) than that for the first three
years. The data for 2007 suggests that the macro-algal cover is still significantly lower
than for the first three years (p<0.001), but significantly higher than for the 2005 and
2006 surveys (p<0.01). The mean macro-algal cover was originally recorded at
22.7(±2.4)% in 2002, and has declined to 9.3(±2.6)% in 2007.
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Chapter 4. Case Study I Wakatobi Marine National Park, Indonesia
2002
2003
2004
2005
2006
Figure 4.3 Linear regression showing changes in hard coral cover at the six study
sites within the Wakatobi MNP
There was a significant decline in hard coral cover over the study period, and
this can be seen in Figure 4.3, where regression lines have been plotted from the cover
data, the Sampela site starts off lowest, and all of the sites show a similar rate of
decline with the exception of the NTA site (F6,254=52.2;p<0.001), which shows a
slower rate of decline as identified by an ANCOVA analysis on the slope of the
regression lines.
4.4.2 Fish assemblage
The mean fish abundance (Figure 4.4) was significantly different both between
years (F5,253=24.0;p<0.001) and between sites (F5,253=20.7;p<0.001). Tukey post-hoc
tests found that there was no significant difference in mean fish abundance over the
first four years of the study from 2002 to 2005, nor between data collected in 2006
and 2007. There was however a significant difference in mean fish abundance
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Chapter 4. Case Study I Wakatobi Marine National Park, Indonesia
between these two groups (p<0.001). Sampela had significantly lower abundance of
fish than all other sites (p<0.001), while the NTA site had a significantly higher
abundance of fish than all other sites (p<0.001), with the exception of the Ridge 1 site.
There was also an interaction between the year and site (F25,253=2.5;p<0.01) with the
NTA site having higher mean fish abundance for the first four years of the study, but
showing no significant difference to the other sites (except Sampela) for the final two
years.
For the mean fish species richness (Figure 4.5), there were significant
differences identified between years (F5,253=60.2;p<0.001) and between sites
(F5,253=18.4;p<0.001). There was no significant interaction between year and site. The
Ridge 1 site showed no significant difference in fish species richness over the first
four study years, but then, like all of the sites showed a significant decline between
2005 and 2006( p<0.001). All the other sites were shown to have increasing fish
species richness over the study period. The Sampela site consistently had the lowest
species richness.
2002
2000
2003
1800
2004
2005
Mean fish abundance
1600
2006
1400
2007
1200
1000
800
600
400
200
0
R1
KDS
KAL
NTA
PK
SAM
Site
Figure 4.4 Mean(±s.e.) fish abundance 1250 m-3 at each of the six study sites in the
Wakatobi MNP over six years[n=9]
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Chapter 4. Case Study I Wakatobi Marine National Park, Indonesia
100
Fish species richness
80
60
40
20
0
R1
KDS
KAL
NTA
PK
SAM
Site
Figure 4.5 Mean(±s.e.) fish species richness 1250m-3 at each of the six study
sites in the Wakatobi MNP over six years [2002=White bars -2007=Black bars][n=9]
The species richness of the grouper family (Figure 4.6) did not show any
significant difference over the study period, but did show significant differences
between sites (F5,251=10.8;p<0.001), with the NTA site showing significantly more
species of grouper than Ridge 1 (p<0.01) and also more species than the four other
sites (p<0.001).
There were found to be significant differences in the species richness of the
Butterflyfish (Chaetodontidae) both between years (F5,251=9.6;p<0.001) and between
sites (F5,251=28.2;p<0.001), but there was no significant interaction between the two
factors. Over the six years of the study there was a decline in the number of
Butterflyfish species at Ridge 1(p<0.001), NTA(p<0.05) and Sampela(p<0.05),
whereas the number of species remained constant at the other sites.
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Chapter 4. Case Study I Wakatobi Marine National Park, Indonesia
4
No of species
3
2
1
0
R1
KDS
KAL
NTA
PK
SAM
Site
Figure 4.6 Mean (±s.e.) number of Serranidae and Epinephelidae species present at
each of the six study sites in the Wakatobi MNP over six years [2002=White bars 2007=Black bars][n=9]
20
No of species
15
10
5
0
R1
KDS
KAL
NTA
PK
SAM
Site
Figure 4.7Mean (±s.e.) number of Scaridae species present at each of the six study
sites in the Wakatobi MNP over six years [2002=White bars -2007=Black bars][n=9]
Ridge 1 showed the highest number of Butterflyfish species per transect
starting at 11.0(±1.2) in 2002 which declined to 8.2(±1.4) in 2007. The Sampela site
had 5.6(±1.3) in 2002 which reduced to 4.2(±0.7) by 2006, but returned to 5.0(±1.1)
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Chapter 4. Case Study I Wakatobi Marine National Park, Indonesia
in the 2007 survey. There was no significant difference in numbers of Chaetodont
species between the other sites.
The number of parrotfish species (Scaridae) varied between both year
(F5,251=66.2;p<0.001) and site (F5,251=33.7;p<0.001), and there was also significant
interaction between the two (F5,251=2.4;p=0.001). All sites showed a large decline in
the richness of the Scaridae between 2005 and 2006. Before this time there was no
significant difference in Scarid richness at the Ridge 1, Kaledupa Double Spur or the
NTA sites. For Kaledupa and Pak Kasims there was a peak in Scarid richness in 2005,
and for Sampela where the richness was lowest (p<0.001), the peak richness occurred
in 2004 (Figure 4.7).
The number of wrasse species (Labridae) also showed significant variation
between both year (F5,251=33.0;p<0.001) and site (F5,251=29.2;p<0.001), again there
was also significant interaction between the year and site (F5,251=9.9;p=0.001). For the
richness of the Labridae, the opposite happened with richness remaining constant for
the first four years from 2002 to 2005, and then increasing significantly in 2006 at the
Ridge 1, Kaledupa and NTA sites (p<0.001) and at the other three sites increased
significantly in 2007(p<0.001).
4.4.3 Wakatobi MNP assessment
Over the six years of the study the mean value of hard coral cover for the
Wakatobi MNP (Figure 4.8) declined from 46.7(±3.4)% in 2002 to 22.2(±4.0)% in
2007. The hard coral cover varied significantly between the six years of the study
(F5,35=13.7;p<0.001), with there being no significant difference between the 2002,
2003 and 2004 data, then a significant decline (Tukey p<0.001) to the values for
2005, 2006 and 2007 between which there was no significant difference.
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Chapter 4. Case Study I Wakatobi Marine National Park, Indonesia
There was no significant difference in the mean percentage cover of soft
coral within the park over the study period, which was recorded at 20.5(±5.2)% in
2002 to 25.2(±6.0)% in 2007. A significant increase in the mean percentage of coral
rubble (Figure 4.9a) found within the park was identified from the One-way ANOVA
(F5,35=4.8;p<0.01). Tukey post-hoc tests revealed that there was no significant
difference between the value for the first four years of the study, then a significant
increase (p<0.001) in 2006, which then reduced back to a level not significantly
different from the first four years values. The mean value of coral rubble cover for the
Wakatobi MNP increased from 6.8(±1.5)% in 2002 to 21.0(±4.3)% in 2006, and then
declined slightly to 14.6(±3.0)% in 2007.
70
60
% Cover
50
40
30
20
10
0
2002
2003
2004
2005
2006
2007
Figure 4.8 Mean(±s.e.)hard coral cover within the Wakatobi over the six year
period[n=54]
The macro-algal cover also showed significant change over the study period
(F5,35=5.7;p<0.001), with no significant difference in the first three years (Figure 4.9b)
with a 2002 value of 14.9(±3.4)%, then a steep decline in 2005 (p<0.001) to
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Chapter 4. Case Study I Wakatobi Marine National Park, Indonesia
6.4(±1.3)%, no significant change in 2006 and then a slight increase to 9.3(±2.6)% in
2007, that was significantly lower than at the start of the study (p<0.05).
There was a significant decline in the total live cover (Figure 4.9c) recorded
throughout the study period (F5,35=9.6;p<0.001). There was no significant difference
in total cover over the first five years, with 80.5(±3.2)% recorded in 2002. The last
two years values were not significantly different from one another, with a value of
51.3(±5.0)% in 2007, but there was a difference between these two groups (p<0.001).
There was no significant difference in the number of hard coral colonies per
transect or in the generic richness of the Scleractinian corals or the mean hard coral
colony size over the study period.
30
(a) Coral Rubble
(b) Macro-algal cover
25
25
20
20
15
15
10
10
5
5
0
0
2002
2003
2004
2005
2006
2007
2002
(c) Total live cover
140
90
2003
2004
2005
2006
2007
(d) Number of Colonies
120
80
70
100
60
50
40
30
20
10
0
80
60
40
20
0
2002
2003
2004
2005
2006
2007
2002
2003
2004
2005
2006
2007
Figure 4.9 Mean (±s.e.) values for four benthic attributes within the Wakatobi MNP
over the six study years[n=54]. (a) percentage coral rubble, (b) percentage cover of
macro-algae, (c) percentage total live cover,(d) number of hard coral colonies per
transect
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Chapter 4. Case Study I Wakatobi Marine National Park, Indonesia
1400
Mean fish abundance 1250m
-3
1200
1000
800
600
400
200
0
2002
2003
2004
2005
2006
2007
Figure 4.10 Mean(±s.e) fish abundance 1250m-3 within the Wakatobi MNP over the
six study years [n=54]
The mean fish abundance within the Wakatobi MNP (Figure 4.10) showed
significant variation over the study period (F5,35=4.3;p=0.005). Post-hoc tests
identified that there was no significant difference between the data from the 2002,
2003, 2004, 2005 and 2007 data, there was however a significant reduction in mean
fish abundance in 2006. In 2002 the mean abundance was 925.7(±178.6), this reduced
to 320.4(±70.4) in 2006, but was at 597.7(±94.6) by 2007.
The mean number of species identified per transect was found to be
significantly different across the study years (F5,35=13.8;p<0.001). No significant
difference was found between the first three years data and that from 2007, but the
2005 richness data was found to be higher than all other years (p<0.01), with the
exception of 2004, to which there was no significant difference. The species richness
data for 2006 showed a significantly lower value than all other years in the study
(p<0.001). The fish species richness was originally recorded at 51.4(±4.5) in 2002,
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Chapter 4. Case Study I Wakatobi Marine National Park, Indonesia
this increased to 71.7(±2.3) in 2005, reduced to 36.2(±3.4) in 2006 and increased to
52.5(±2.2) in 2007.
No significant change was recorded in the mean richness of either the Scaridae
(Figure 4.11a), nor the Serranidae (Figure 4.11b) in the Wakatobi MNP over the six
year study period. Over the six year period there was a mean Scarid richness of
2.7(±0.2), and a mean Serranid richness of 1.6(±0.1). Nor was there a significant
difference in the species richness of the Pomacanthid over the same period, with a
mean species richness of 2.1(±0.1). However there was a significant difference in the
species richness of the Pomacentridae (Figure 4.11c) over the six annual surveys
(F5,35=30.2;p<0.001). There was significantly fewer species recorded in 2006
(p<0.001) and 2007 (p<0.05) than in all other years between which there was no
significant difference. The mean number of Pomacentrid species in 2002 was
13.6(±1.3), this reduced to 3.2(±1.2), in 2006 and increased to 11.1(±0.9) in 2007.
There was also a significant difference in the species richness of the Labridae (Figure
4.12d) over the study period (F5,35=4.9;p=0.002). There was no significant difference
in Labrid richness in 2002, 2003, 2004, 2005 and 2007, but the value for 2006 was
significantly lower than for 2003, 2004 and 2005 (p<0.01), but was not significantly
different from the values for 2002 and 2007. In 2002 a mean Labrid richness of
8.7(±1.2) was recorded, this reduced to 5.1(±1.4) in 2006, but increased again to
8.3(±1.1) in 2007. Finally, there was a significant difference in the species richness of
the Acanthuridae over the study period (F5,35=5.5;p=0.001). 2002 showed a lower
mean species richness than did 2004, 2005, 2006 and 2007. The recorded richness in
2002 was 3.3(±0.4), which increased to 4.8(±0.3) in 2007.
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Chapter 4. Case Study I Wakatobi Marine National Park, Indonesia
(a) Scarid richness
(b) Serranid richness
5.0
2.5
4.0
2.0
3.0
1.5
2.0
1.0
1.0
0.5
0.0
0.0
2002
2003
2004
2005
2006
2007
2002
(c) Pomacentrid richness
2003
2004
2005
2006
2007
(d) Labrid richness
16
14
12
10
8
6
4
2
0
20
16
12
8
4
0
2002
2003
2004
2005
2006
2007
2002 2003 2004 2005 2006 2007
Figure 4.11 Mean (±s.e.) values for four fish Family richness attributes within the
Wakatobi MNP over the five study years [n=54]. (a) Scarid richness, (b) Serranid/
Epinephelid richness, (c)Pomacentrid richness, (d) Labrid richness
4.4.4 Large interval monitoring
70
HC
SC
60
CR
ALG
50
40
30
20
10
0
SOM 02 SOM 07 MON 02 MON 07
TAO 02
TAO 07
Figure 4.12 Change in percentage cover of four benthic attributes at the three West
Kaledupa sites over the five year study period[n=9]. [Sites: SOM-Sombano, MONMontigola, TAO-Taou] [HC-Hard coral, SC-Soft coral, CR-Coral rubble, ALGMacro-algae]
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Chapter 4. Case Study I Wakatobi Marine National Park, Indonesia
Over the longer five year interval between surveys (Figure 4.12), a two-way
ANOVA showed that the hard coral cover at all three west Kaledupa study sites
declined significantly (F1,35=223.7;p<0.001). Although there was no significant
difference in hard coral cover between the three sites, there was a significant
interaction between the two years of the study and site (F2,35=27.1;p<0.001). The
Sombano site showed a 70% decline in hard coral cover, the Montigola site declined
by over 52% and the Taou site declined by 12%. For soft coral cover there was a
significant difference between the three sites (F1,35=38.5;p<0.001) with the Taou
(p<0.001) and Montigola (p<0.001) sites showing significantly more soft coral than
the Sombano site. There was a significant increase in soft coral cover over the five
year period (F1,35=16.2;p<0.001), but only at the Montigola and Taou sites. Sombano
showed no significant change, meaning no significant interaction between year and
site as Montigola showed an increase from 10.2(±2.4)% to 19.8(±2.0)%, while Taou
showed an increase in soft coral cover from 11.5(±2.3)% to 16.0(±2.6)%. The coral
rubble cover showed significant increases between years (F1,35=102.7;p<0.001) with
the Sombano site showing a five fold increase to 40.8(±6.4)% , Montigola increased
by three times to 12.4(±2.3)% and the rubble cover at Taou almost doubled from
6.8(±2.7)% to 12.7(±1.9)%. Significant differences were identified between sites
(F1,35=28.7;p<0.001) and a significant interaction between site and year was also
found (F2,35=17.0;p<0.001). Finally for the benthic components, the macro-algal cover
showed no significant difference between sites or years.
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Chapter 4. Case Study I Wakatobi Marine National Park, Indonesia
4.4.5 CVI assessment
The Conservation Value Index proposed in Chapter Three was used to assess
the six sites around the Wakatobi MNP and identify change over the six year study
period. This data can be presented in numerous ways, either by site, by year as a mean
for the Wakatobi MNP, in tabular format, map style or as graphical grids.
The CVI scores and classification values for each site over the six study years
can be seen in Table 4.1. For the Kaledupa site the benthic component score shows a
decline from 29 to 22 ranking the site originally as a C, but by 2007 as D, suggesting
a decline in the condition of the benthic assemblage. The fish component score
increases from 23 in 2002 to 30 in 2007, ranking the site originally as a 4, but
currently as a 3, suggesting an improvement in the health of the fish assemblage. The
Kaledupa Double Spur site fluctuates from 33 in 2002 up to 37 in 2005, then shows a
dramatic reduction to 14 in 2006, finally returning to near the original rating of 31 in
2007. This means that the benthic component was ranked as C, improved to B, then
suddenly declined to D, but by 2007 was again ranked C. The fish component at the
Kaledupa Double Spur site started with a score of 30 which remained relatively
constant, reduced to 17 in 2006, but returned to 30 in 2007. This scored the site as a 3
meaning that both components remained in similar condition over the study period.
The Hoga NTA site also remained relatively consistent in terms of index score
over the six years. In 2002 the benthic component scored 29, which reduced to 26 by
2007. Again a sharp reduction was recorded in 2006. This gave the benthic
component a ranking of a low C which occasionally reduced to a D with a small
reduction in score. The fish component scored 32 in 2002, which increased to 38 in
2005, then declined to just 20 in 2006, with a 2007 score of 26.
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Chapter 4. Case Study I Wakatobi Marine National Park, Indonesia
This ranked the site as a 3 originally which improved to a 2 in 2005, reduced
to a 4 in 2006 and returned to a 3 in 2007. This suggests that the condition of the site
is relatively stable, but small reductions in the underlying scores should be noted.
Table 4.1 Conservation Value Index scores and classification of the six Wakatobi
MNP study sites by year
Site
KALEDUPA
KALEDUPA
DOUBLE
SPUR
HOGA
NTA
PAK
KASIMS
RIDGE 1
SAMPELA
Year
2002
2003
2004
2005
2006
2007
2002
2003
2004
2005
2006
2007
2002
2003
2004
2005
2006
2007
2002
2003
2004
2005
2006
2007
2002
2003
2004
2005
2006
2007
2002
2003
2004
2005
2006
2007
Benthic
29
29
28
31
12
22
33
31
28
37
14
31
29
26
22
31
14
26
25
26
26
37
15
25
40
37
34
40
18
32
23
21
19
27
12
25
129
Fish
23
22
29
36
20
30
30
26
29
32
17
25
32
21
30
38
20
26
25
21
31
40
10
30
40
33
38
42
17
31
15
8
15
22
7
16
CVI
score
C
4
C
4
C
3
C
3
E
4
D
3
C
3
C
3
C
3
B
3
D
4
C
3
C
3
C
4
D
3
C
2
D
4
C
3
C
3
C
4
C
3
B
2
D
5
C
3
B
2
B
3
C
2
B
2
D
4
C
3
D
4
D
5
D
4
C
4
E
5
C
4
Chapter 4. Case Study I Wakatobi Marine National Park, Indonesia
The Pak Kasims site showed an increase in benthic score from 25 in 2002 to
37 in 2005, then the same reduction as other sites in 2006 to just 15, but then returned
to 25 by 2007. This ranked the site at the start and end of the study as a C. The fish
component for Pak Kasims scored the site originally as 25, which increased to 40 in
2005, reduced to 10 in 2006 and returned to 30 in 2007. This gave the site a fish
component ranking of 3 in 2002 which increased to a 2, then declined to 5 in 2006,
but finished ranked as 3 in 2007. This site showed consistent ranking over the six
study years, with similar underlying scores in 2002 and 2007. The Ridge 1 site
originally scored 40 for both benthic and fish components ranking the site B2 in 2002,
this remained constant until 2006 when scores of 18 and 17 for benthic and fish
components respectively gave the site a ranking of D4, this improved again in 2007 to
score the site 32 and 31 for benthic and fish respectively, giving a final rank of C3,
representing a decline in both benthic and fish community status over the six year
study. Finally the Sampela site scored 23 for the benthic component in 2002 which
declined as did the other sites in 2006, but finished at 25, giving the site a rank of a
high D or low C. The fish component for the Sampela site scored 15 in 2002 and 16 in
2007, ranking the site as 4, suggesting little change in reef condition over the study
period.
The CVI rankings can also be presented annually (or as often as the surveys
are carried out). This ranking of the sites is represented graphically in Figure 4.13a
and b in a map format that would be suitable for a GIS database and can be easily
interpreted by non-specialists.
130
131
KDS [C3]
KAL [C4]
SAM [D4]
NTA [C3]
PK [C3]
R1 [B2]
Figure 4.13a. Conservation Value Index output for six sites around Kaledupa island 2002
500m
Chapter 4. Case Study I Wakatobi Marine National Park, Indonesia
132
KDS [C3]
KAL [D3]
SAM [C4]
NTA [C3]
PK [C3]
R1 [C3]
Figure 4.13b Conservation Value Index output for six sites around Kaledupa island 2007
500m
Chapter 4. Case Study I Wakatobi Marine National Park, Indonesia
Chapter 4. Case Study I Wakatobi Marine National Park, Indonesia
A combination of both annual and site specific output can be represented in a
grid style output (Figure 4.14). The scores for each site can be plotted on a five by
five grid based on the A-E and 1-5 ranking system. Trends in the scores for each site
can then be monitored over several years or surveys.
The index scores can also be presented as a summary for the reefs of the
Wakatobi MNP as a whole (Figure 4.15) using the grid method. Means of the scores
from all sites can be calculated and then used to rank the reefs of the park for that
year. This method also allows the plotting of standard errors as an indication of
between site variability. Using this method the scores for 2002 were 30(±2.5) for
benthic component and 28(±3.5) for the fish component, giving an overall ranking of
C3. In 2003 the scores declined slightly to 28(±2.1) for benthic and 22(±2.8) for fish,
ranking the site C4. For 2004 the benthic and fish components scored 26(±2.0) and
28(±2.7) respectively, ranking the site C3. In 2005 the respective scores were
34(±2.0) benthic and 35(±2.7) fish, ranking C3 again. In 2006 there was a significant
decline in scores with the benthic component scoring 14(±2.0) and the fish component
15(±2.8), ranking the site D4. In the final year of the study the benthic and fish
components scored 27(±2.0) and 26(±2.5) respectively, ranking the site C3.
To clarify the outputs and direction of any changes further categories and
simplification can be used dependent upon the target audience (Table 4.2), either the
map
or grid based outputs could be used along with text explanations of the
categories to allow the understanding of the CVI assessment scores.
133
E
Chapter 4. Case Study I Wakatobi Marine National Park, Indonesia
(a) Ridge 1
E
D
C
B
(b) Kaledupa Double Spur
A
E
D
C
D
C
A
2
2
3
3
4
4
5
5
(d) Pak Kasims
B
B
B
1
A
E
D
C
B
A
1
1
2
2
3
3
4
4
5
5
(f) Sampela
(e) Hoga NTA
E
C
1
(c) Kaledupa
E
D
E
A
D
C
B
A
1
1
2
2
3
3
4
4
5
5
Figure 4.14 Grid style CVI output to show direction of change in index scores for the
six study sites within the Wakatobi MNP(a)Ridge 1, (b)Kaledupa Double Spur,
(c)Kaledupa, (d)Pak Kasims,(e)Hoga NTA, (f)Sampela
[2002-closed diamond, 2003-open square, 2004-closed triangle, 2005-open diamond,
2006-open triangle, 2007-closed square]
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Chapter 4. Case Study I Wakatobi Marine National Park, Indonesia
Table 4.2 Further outputs to aid clarity for varied audience
Output
Positive
change
No
change
Negative
change
Arrows
↑
↔
↓
Mathematical
+
/
-
Faces
Traffic lights
Fishery
E
D
C
B
2002
A
2003
1
2004
2005
2006
2
2007
3
4
5
Figure 4.15 Grid style output representing mean (±s.e.) CVI values throughout
Wakatobi MNP from 2002 to 2007
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Chapter 4. Case Study I Wakatobi Marine National Park, Indonesia
4.5 Discussion
4.5.1 Benthic assessment
The hard coral cover data show a significant decline between 2004 and 2005
indicating some sort of impact or disturbance event between these two surveys. The
decline in hard coral cover was observed at all sites with the exception of the
protected Hoga NTA site. The fact that this site showed no decline in coral cover
suggests an anthropogenic impact (or impacts!) affecting the coral cover at the other
sites within the park, as all are subject to similar environmental conditions. The total
live cover also showed this significant decline between two study years, but here it
occurred a year later between 2005 and 2006, suggesting that while the hard coral
declined the year before, a further decline in either soft coral, sponges and/ or CCA
occurred a year later, on top of the hard coral decline. The cause of these declines is
not immediately apparent, there is little tourist activity in the park in the form of
recreational boats and divers, nor do the local subsistence fishermen use anchors (per.
obs.). Destructive fishing techniques are understood to occur within the park (PetSoede & Erdmann, 2003), evidence of blast fishing is visible on the reefs in terms of
coral rubble, which was shown to increase significantly over the study period at all
sites between 2004 and 2005, again suggesting either a storm or some anthropogenic
impact. Personal accounts from members of the local community rule out a
destructive storm over this period and suggest anthropogenic exploitation as a more
likely cause. Distant explosions were often experienced underwater by the Operation
Wallacea survey team, and it is possible that these fishermen who employ destructive
techniques exploit the reefs around the study area at other times of year when there is
no monitoring presence in the region. It is possible however, that other factors such as
coral disease, coral mining and anchor damage from visiting boats may be an
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Chapter 4. Case Study I Wakatobi Marine National Park, Indonesia
important factor in the decline of the benthic cover. Another factor suggesting the
decline is anthropogenically induced is the behaviour of the macro-algal community,
which instead of increasing to exploit the increased substratum availability, has
actually decreased significantly over the study period. It can be shown that there is a
strong association between hard coral cover with the increase in coral rubble cover,
with the damaged coral actually forming the rubble.
4.5.2 Fish assessment
The significant decline in mean fish abundance was recorded to have occurred
a year after the decline in benthic cover, between the 2005 and 2006 surveys. This
decline was only found at the sites which originally had higher levels of coral cover as
the Sampela site which was already significantly degraded showed no reduction in
fish abundance, with values pre-2006 similar to those post-2006 at all other sites.
There is more evidence here for the importance of the Hoga NTA as this site did not
show a significant reduction in mean fish abundance. This also suggests that the
reduction in abundance was anthropogenic in origin, although it also follows that if
the decline was related to habitat decline, then the Hoga NTA site was also the only
site that did not decline significantly the previous year, and hence continued to
support a higher mean fish abundance. As for the fish abundance, the mean fish
species richness also showed a sudden, significant decline between 2005 and 2006.
This reduced significantly at all sites except Sampela, which again began the study at
a significantly lower level than the other five sites. This provides more evidence that
the decline in the fish assemblage was linked to the decline in benthic habitat as
identified in the Caribbean by Friedlander & Parish (1997) and in the Indo Pacific by
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Chapter 4. Case Study I Wakatobi Marine National Park, Indonesia
Ohman (1998). Syms & Jones (2000) also showed that degradation of benthic habitat
had the same effect in lowering both fish abundance and diversity as did fish removal.
The results from the Grouper (Serranidae/ Epinephelidae) species richness
data again show support for the effectiveness of the Hoga NTA with this site having
significantly more Grouper species than all other sites, even in the 2006 survey where
the majority of surveyed attributes were greatly reduced. The Ridge 1 site was the
only site to show very significant declines in Chaetodont species richness, where the
overall abundance and species richness also declined in line with live benthic cover.
This supports the work of Crosby & Reece (1996) who identified these changes as
some species migrate to find food, while those that remain have enlarged territories,
excluding others and meaning fewer individuals will be encountered. Surprisingly the
richness of the Labridae increased over this same period, possibly as a result of a
combination of both the wide ranging trophic status of this family and decreased
resource competition due to the lower abundance and diversity of other family and
functional groups.
4.5.3 Wakatobi MNP assessment
As with the general trend at the individual sites, the hard coral cover showed a
significant decline between the 2004 and 2005 surveys, again suggesting some park
wide disturbance. There was no significant difference in soft coral cover suggesting
that they were not replacing the lost hard corals. In fact the total live cover including
the soft and hard corals showed significant reductions. The significant increases in
coral rubble suggest that the hard coral is remaining at the sites in the form of coral
rubble, which would inhibit the recruitment of other benthic organisms and may take
several decades to centuries to recover (Fox and Caldwell, 2006). The reducing cover
of macro algae suggests that herbivorous fish and invertebrates are currently
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Chapter 4. Case Study I Wakatobi Marine National Park, Indonesia
preventing a shift to an algal dominated state (Done, 1992). This is supported by the
fish data which shows no significant reduction over the six year period, with the
exception of the 2006 data, which shows extreme values for nearly all attributes, both
benthic and fish assemblage. There appears to be some form of observer error for this
year’s survey as the values are so different from both previous and subsequent years
that they are ecologically unlikely. For example the 2006 data showed no
Pomacentridae present at numerous sites, which is ecologically unlikely as they are
one of the most abundant families on Indo-Pacific coral reefs (Allen, 1997). This
highlights a possible shortcoming with the likelihood being that the surveyors did not
follow the prescribed training procedures and survey schedule. This seems likely as
some categories are massively overestimated while other related categories are
massively underestimated. This also highlights the issues raised in Chapter 2 with
different surveyors producing different results that could lead to inappropriate
management action. The species richness data also supports this with fewer species
being recorded during this years surveys at all sites. If this 2006 data is deemed to be
inaccurate then there was no significant difference in the majority of the fish attributes
monitored, again supporting limited decline in the fish community within the park.
The fact that the proportion of the fish communities that were both herbivores and
corallivores remained constant over the study period suggests no changes in the
trophic composition of the fish assemblage.
4.5.4 Large interval monitoring
The data collected at the west Kaledupa sites with the five year interval
between surveys showed large significant changes in both coral cover and coral
rubble cover, with the former declining significantly and the latter increasing
significantly. This follows a similar pattern to the annual monitoring in the park, but
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Chapter 4. Case Study I Wakatobi Marine National Park, Indonesia
the magnitude of the changes of the five year period suggests that monitoring on a
much shorter temporal scale is appropriate within the Wakatobi MNP to allow the
early identification of change.
4.5.5 Conservation Value Index assessment
The CVI scores for the individual sites showed a decline in the conservation
value of Kaledupa, which is similar to that recorded by the various univariate
attributes such as hard coral cover and live cover. The stable fish assemblage at this
site was representative of the park as a whole. Hoga NTA gave constant scores and
classifications across the study period, similarly to the univariate attributes, as did the
Kaledupa Double Spur and Pak Kasims sites, with no clear trend in either direction.
The Ridge 1 site showed a decline in both scores and classifications for both benthic
and fish assemblages The univariate attributes support this decline as there were
significant reductions in hard coral, live cover, fish abundance and species richness,
while coral rubble cover increased significantly. This site has reduced in condition
over the study period and now scores similarly to most other sites within the park
except Sampela. The Sampela site showed slight improvement in the benthic score
which improved the ranking of the benthic category, but the fish score remained
constant and lower than the other sites.
Like the univariate data, the CVI output highlights a decline in the benthic
assemblage between 2004 and 2005, which was followed by a lag of one year before a
decline in the fish assemblage was observed. However, the output of the CVI is much
more easily interpreted by non-specialists as it avoids the reporting of statistics for
numerous univariate attributes, such as in the traditional assessment, which can be
over complicated when trying to report outcomes to stakeholders.
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Chapter 4. Case Study I Wakatobi Marine National Park, Indonesia
Anomalous data seems to have been recorded in 2006, with significant
reductions in scores and classifications from previous and subsequent years, following
the same pattern as the univariate data. This highlights the responsiveness of the CVI
in that the index scores are only as good as the data they are compiled from. This
suggests that the index will provide suitable classification for low quality reefs, but
again highlights the need for a standardised survey procedure to be followed to allow
comparison between years and identification of real change rather than between
observer differences.
The CVI scores can also be used to differentiate between the sites as they
show spatial variability (between sites), even when they do not show a clear temporal
change (within sites).
The annual scores can be clearly represented on maps and plans to provide a
clear representation of individual reef condition. This can be interpreted by all levels
of audience as a single easily understood value associated with a position on a map,
rather than needing to interpret numerous univariate graphs or values which may be
responding to change in different directions or at different scales. However, as all
individual attributes need to be surveyed to calculate the final index scores, if change
is identified at a site, then these univariate values can be analysed, either to identify
stressors or to prioritise areas for further detailed study. Although this map based
presentation method is suitable for disseminating reef condition data, the grid style
outputs are more appropriate to identify change and trends at different sites. Again
these can be easily interpreted, with the high scoring sites plotted towards the top right
of the grid and the poor scoring sites towards the bottom left of the grid. These grids
can also be colour coded to grade from green in the top right for the good quality sites
to red in the bottom left, where the poor scoring sites will occur. The use of the grids
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Chapter 4. Case Study I Wakatobi Marine National Park, Indonesia
as a summary for the Wakatobi MNP as a whole, with points plotted on an annual
basis, again allows for easy interpretation of change and the direction in which it is
occurring. The use of multiple samples and sites to give mean park scores also allows
the generating of error bars which can give a visual indication of the between site
variability for each year. The method of taking the mean scores for each year are
supported by the similarity in benthic and fish assemblage composition of all the
study sites and also by the increased power this gives the outputs with greater
numbers of samples being less likely to produce a Type II error, i.e. change is
occurring but the survey design does not detect it.
4.5.6. Conclusions
This assessment identifies a change in benthic cover within the Wakatobi
MNP. The hard coral cover and live cover are declining while coral rubble cover is
increasing. However, due to limited changes in the fish assemblage, this is not leading
to an increase in algal cover at the impacted sites. It is important to continue the
monitoring of both the benthic and fish assemblages for future change. The study also
identified that annual survey was appropriate as the longer term surveys with a five
year gap identified large changes in some reef attributes. Annual monitoring will
allow the early detection of these changes and may give time to allow management
actions to be applied.
The CVI gave appropriate rankings to the sites and detected changes similar to
those identified by the 24 surveyed attributes in the benthic and fish assemblages.
Therefore the CVI meets its goals of assessing reef condition in a way that can be
disseminated to a wide range of audience, while retaining the underlying data which
allows for more in depth analysis once change has been detected. The CVI scores can
also be used to differentiate between the sites as they show spatial variability
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Chapter 4. Case Study I Wakatobi Marine National Park, Indonesia
(between sites), even when they do not show a clear temporal change (within sites).
Identifying this between site variability can be as important to reef management as the
identification of any temporal trends, which it has been shown, can also be achieved
with the CVI method.
143
Chapter 5. Case Study II Ras Mohammed National Park
CHAPTER 5. Case Study II. Ras Mohammed National Park, Egypt
5.1 Abstract
The aim of this chapter is to report the data collected as part of the ongoing
long-term coral reef monitoring program established for the Egyptian Environmental
Affairs Agency in the Ras Mohammed National Park, South Sinai, Egypt. Study sites
were surveyed using belt and LIT methodologies, with four replicate transects carried
out at the reef crest and upper reef slope at six sites. The percentage cover of live
corals (Scleractinia) did not vary significantly between the six study sites. A 5%
increase in mean cover was observed in 2006 from the 2005 values. The mean
Scleractinian coral cover within the National Park was 25.7(±1.5)%, up from
20.3(±1.8)% in 2005. The use of randomly placed 1m2 quadrats identified a mean
recruitment rate for scleractinian corals of 1.21 (±0.13) new recruits per m2 per year;
there was no significant difference in the number of new recruits between the
different sites. There was a highly significant difference in the total abundance
(1000m-2) of fish observed at each of the study sites(p<0.001). There were also
significant differences in the number of Chaetodontidae, Pomacentridae and
Acanthuridae species found at the different sites, while the other major fish families
studied showed no significant differences. The classification of the surveyed sites
within the park using the CVI showed that the Old Quay upper slope site had the
highest index scores of 49 and 35 for benthic and fishery health respectively, giving a
CVI score of B2. The lowest scoring site was Shark Observatory, with a benthic score
of 44 and a fishery value of 20, giving a CVI rating of C3. These results suggest that
the management of the park is starting to show effectiveness, as the low coral cover is
recovering from the Crown of Thorns starfish outbreak of 2000.
144
Chapter 5. Case Study II Ras Mohammed National Park
This chapter formed the basis of the following paper,
McMellor S. & D.J. Smith (2007).The status of the reefs of the Ras Mohammed
National Park, Proceedings of Red Sea Project III, SAS Monograph, BAR
International Series. Oxford: Archaeopress
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Chapter 5. Case Study II Ras Mohammed National Park
5.2 Introduction
5.2.1 Background
In November 2004 the Nature Conservation Sector of the Egyptian
Environmental Affairs Agency (EEAA) and the UK based NGO Operation Wallacea
signed an eight year agreement to establish and implement a long-term monitoring
program for the coral reef habitats of the Ras Mohammed National Park, South Sinai,
Egypt. The first year (2005) of the agreement was dedicated to establishing links with
EEAA staff, implementing the logistical support required for such a long-term project,
identifying suitable sites for the program, and carrying out a baseline survey of several
reefs within the Ras Mohammed National Park. This was followed up by a more
extensive survey of the parks reefs in 2006. Both years of the survey were undertaken by
Steve McMellor of the Coral Reef Research unit (University of Essex) for Operation
Wallacea and the EEAA.
5.2.2 Threats to Ras Mohammed National Park
The threats to the Ras Mohammed National Park environment fall into two
categories; natural and anthropogenic. (Although it could be argued that there are
links between the two).
Natural threats include predation on the important reef building corals by
Acanthaster planci, the Crown of Thorns Starfish (COTs) and corallivorous
gastropods such as Drupella spp. and Coralliophilla spp. These organisms are natural
components of any reef system and usually occur in small numbers where they feed
directly on hard coral tissues. However, outbreaks or population explosions of these
coral predators are known to occur and have both been recorded over recent years in
and around the Ras Mohammed National Park.
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Chapter 5. Case Study II Ras Mohammed National Park
Feeding aggregations of Drupella spp. have caused considerable coral damage
on reefs across the Indo-West Pacific (Turner, 1994). They usually aggregate in small
clusters of less than ten individuals, but have been recorded in densities from around
200 to over several thousand individuals. These gastropods have adapted radula for
stripping the live coral tissue from the skeleton, leaving behind characteristic white
feeding scars that are quickly colonised by turf algae (Cumming,1999). The
populations tend to exhibit stable periods punctuated by rapid population increases,
often associated with changes in ecological structure. The outbreaks tend to occur in
areas with high coral cover (McClanahan, 1994). They have also been linked to coral
disease outbreaks in the Red Sea (Antonius & Riegl, 1997;1998).
The Ras Mohammed park has recently (1998-2002) suffered a catastrophic
outbreak of Acanthaster planci (Saleh, 2006), with thousands of individuals being
removed from the reefs of the park. Again, the COTs is a predator of the reef building
scleractinia and such outbreaks can lead to a collapse in spatial heterogeneity,
resulting in very slow recovery of the impacted reefs, although recovery can take
around twelve years if the structural integrity of the reef remains intact (Hart &
Klumpp, 1996). The ‘State of the reefs’ (Wilkinson, 2004), reported that coral cover
was reduced from 37% to 13% during the recent outbreak at some sites in the Gulf of
Aqaba. The loss of the hard coral cover often leads to shifts in community structure
resulting in an algal dominated system. This in turn can affect the structure of fish
populations with changes in the abundance of various roving herbivores, such as the
Surgeonfishes (Acanthuridae) and Parrotfishes (Scaridae) (Hart et al., 1996).
Other natural threats to the regions coral reefs include coral bleaching and
coral disease, although again it could be argued that they are anthropogenically
enhanced. Coral bleaching is the loss of symbiotic zooxanthellae due to a number of
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Chapter 5. Case Study II Ras Mohammed National Park
different stresses, the most commonly reported being elevated SST. The incidence of
coral diseases is believed to be increasing worldwide, yet little data exist for the entire
Indo-Pacific region. It has been suggested (Green & Bruckner, 2000) that the
increasing incidence of disease may be linked to declines in marine environmental
health generally due to anthropogenic influences.
Major anthropogenic threats include the continued development of the tourism
industry with direct physical impacts on the reefs caused by the visiting divers and
snorkellers. Tourism activity in and around the Ras Mohammed park is intense with
Kotb et al., (2004) reporting over 75000 divers per year at some sites. The ‘State of
the Reefs report’ (Kotb et al., 2004) also identified major indirect anthropogenic
threats from tourism in the form of land fills, dredging and sedimentation, sewage
discharge and effluent from desalination plants all associated with continued coastal
development.
Anthropogenic impacts on coral reefs can be assumed to be cumulative with
natural impacts, and hence practically there would appear to be little qualitative
difference between anthropogenic and natural stress on coral reefs and both these
sources of stress are important in controlling reef community structure (Grigg &
Dollar, 1990).
5.2.3 Monitoring Program Rationale
Although there appear to have been a number of studies and monitoring
programs attempted in the Ras Mohammed park, the data they produced is
unfortunately lacking (Pilcher & Zaid, 2000). Informed management action requires a
solid foundation on which to base decisions, often in the form of a detailed biological
survey. The hermatypic Scleractinian corals are arguably the most important
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Chapter 5. Case Study II Ras Mohammed National Park
component of the reef as they are the reef builders themselves and without them reef
growth would be very limited. Although important, they are by no means the only
organism important to overall reef health.
Degradation of tracts of reef often involves a ‘phase shift’ from coral
dominated to algal dominated states, which in turn has knock on effects to the fish
abundance and diversity (McCook,1999; McClanahan et al., 2002). A complex
interaction between hard corals, soft corals, algae and levels of fish grazing can lead
to these phase shifts, but it often requires several factors to occur simultaneously, such
as increased eutrophication and removal of important herbivorous fishes, along with
ongoing degradation of hard corals. Many of these other factors need to be recorded
and considered, before any management action can be taken, due to the complex
nature of competition on a coral reef. It is of vital use to stakeholders and managers
that early detection of changes in these interacting factors are monitored, alongside
measures of coral cover, to allow the early identification of possible phase-shifts in
community structure.
The link between the ‘health’ of the benthic and fish assemblage is already
well established in coral reef ecology. Roberts & Ormond, (1987) showed that
substratum biodiversity was positively correlated with overall fish species richness,
although total live cover did not show a significant correlation to fish diversity or
abundance. Friedlander & Parrish (1998) also identified that benthic habitat
characteristics affect fish assemblages. Often these are characteristics which provide
habitat for fish and also for fish prey species. The benthic and fishery components of a
reef system are highly interdependent, with a natural or anthropogenic impact on one
community having a knock-on effect on the other (Chabanet et al., 1997). The
interaction between these components within the coral reef system means that it is of
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Chapter 5. Case Study II Ras Mohammed National Park
vital importance to monitor the changes in cover and abundance of many of these
factors as coral cover alone cannot give any indication of possible phase shifts or
changes in the composition of either community.
The Ras Mohammed National Park was originally designated to protect an
area of important natural resources which was at risk due to the development of the
dive tourism industry. The hermatypic corals provide habitat and resources for a huge
variety of different organisms and the sustainable development of tourist activities
must be based around the protection of the reef builders themselves, (i.e. an
ecosystem approach to conservation).
The benthic component of this study aimed to survey the reef benthos and
classify the abundance and diversity of several categories of biota including the hard
corals (Scleractinia), the soft corals (Alcyonacea), sponges (Porifera), crustose
coralline algae and macro algae. Abiotic categories such as areas of sand, coral
rubble, dead coral and bare rock were also recorded.
Any form of reef assessment must include the fish species present as they
perform vital roles in the maintenance of diversity on a healthy reef system. Many
fish species are important algal grazers and as such help maintain the competition for
substratum between benthic organisms, by keeping the faster growing ruderal algae in
check (Thacker et al., 2001; Sluka & Miller, 2001). Removal or loss of this functional
redundancy (Bellwood, et al., 2004) can lead to phase shifts and changes in
community structure.
Unlike many reef areas throughout the world’s oceans, the Ras Mohammed
park is not subject to adverse fishing techniques and/ or over-extraction of resources,
however, it is still vital to monitor the fish assemblages for signs of impact or change
as other factors, such as nutrient input or inappropriate development may impact the
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Chapter 5. Case Study II Ras Mohammed National Park
fish assemblage. Removal of predators by overfishing is known to deplete both
biomass and diversity of other non-target fish species (Jennings & Polunin, 1997).
Benthic data monitoring efforts have also been targeted at the park previously,
yet the data still remains somewhat lacking in terms of published results. This study
aims to estimate the size and diversity of the fish populations on the studied reefs, to
identify their trophic structure and functional redundancy as well as gaining estimates
of overall abundance and species richness. Once baselines have been established,
these factors can then be monitored temporally for change.
5.2.4 Conservation Value Index assessment
To complement the assessment of the reefs of the Ras Mohammed National
Park, the Conservation Value Index (CVI) described in Chapter 3 was used to make
an assessment of the condition of the reefs within the park.
Consequently the aims and subsequent objectives of this chapter are to produce
a status report on the condition of the coral reefs and associated communities of the
Ras Mohammed National Park, South Sinai, Egypt that will be of use to the Egyptian
Environmental Affairs Agency and;
(a) Produce a site specific assessment of the benthic assemblages within the
Ras Mohammed NP using multiple univariate attributes from 2005-2006.
(b) Produce a site specific assessment of the fish assemblages within the Ras
Mohammed NP using multiple univariate attributes from 2005-2006.
(c) Produce an assessment of the threats to the reefs of the Ras Mohammed NP
using multiple univariate attributes from 2005-2006.
(d) Classify the reefs of the Ras Mohammed NP using the Conservation Value
Index from 2005-2006.
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Chapter 5. Case Study II Ras Mohammed National Park
5.2 Methodology
5.3.1 Benthic assemblage
The main group studied were the hermatypic corals (Order Scleractinia), and
other groups of sessile reef organisms that were monitored included the soft corals
(Alcyonacea), sponges (Porifera), macro algae and crustose coralline algae. The area
of coral rubble, dead corals and area of bare substratum available for recruitment was
also recorded. Regular monitoring of echinoderm populations (particularly
Acanthaster planci), as well as abundance of corallivorous gastropods (particularly
Drupella spp.) were included.
The monitoring program was carried out at a four sites in 2005, and expanded
to six sites in 2006, within the park at two depths on the upper (2-6m) and lower (912m) reef slopes. Several survey methods were used to quantify spatial and temporal
changes in the benthic community. The principal technique used was the continuous
Line Intercept Transect (after English et al., 1996), combined with belt transects
(Loya, 1978). Four 40 metre long transect tapes were laid along depth contours
parallel to the shoreline for each depth at each site. All lifeforms intercepting the
transect line were recorded to Genus with the length intercepting the transect tape
recorded to the nearest centimetre. An individual was defined as any colony/
individual growing independently from its neighbours. In cases where a colony is
divided into multiple parts by the death or overgrowth of intermediate parts, each part
is considered a separate colony. The area intercepting the transect tape was classified
according to the benthic category system as shown in Table 2.1, adapted from the
methodology of English et al., (1996).
Digital photographs were taken of any unknown lifeforms for later
identification using keys. While recording the colony size intercepting the transect
line, coral predator abundance and the presence (area affected) of bleached tissue or
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Chapter 5. Case Study II Ras Mohammed National Park
disease was also be noted. A belt transect extending 2.5m either side of the transect
was used to quantify the abundance of COTs.
All transect data were square root transformed to satisfy the distribution and
variance assumptions of ANOVA. Data was analysed using the statistical computer
packages Community Analysis Package (CAP), SPSS and PRIMER. To carry out
one-way ANOVA between sites and also years, 2-way ANOVA between site and
depth, Bray-Curtis Cluster analysis (Group Average) and Principal Component
Analysis.
5.3.2 Fish assemblage
The following section outlines the procedure for undertaking visual census
surveys at the permanent monitoring sites following the AIMS fish monitoring
protocol (Halford and Thompson, 1994). The sites were located from the surface
using a GPS. Two divers entered the water. The first diver (observer) was equipped
with a slate, pencil and data sheets, the second diver (tape layer) carried the tapes.
Before reaching the first transect the tape layer runs out 2.5m of tape to allow the
observer an initial visualization of the desired transect width.
The observer conducted a 40 metre by 5m by 5m box transect by swimming
along the centre line of the transects over a 25 minute period. The observer counted
all fish sighted within the area 2.5m either side of and up to 5 m above the centre line,
recording species and number of individuals.
Eight 40m belt transects were completed at each site, four at each of the two
depths on the upper and lower reef slopes. This gave a total survey area of 8000m3 per
site (each belt giving 1000m3).
A visual census aims to record an instantaneous estimate of abundance for the
target species present within the bounds of the transect. Unfortunately this theoretical
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Chapter 5. Case Study II Ras Mohammed National Park
goal can never be realised due to factors including the time taken to count and record
each individual, and commonly, the inability to scan the entire transect area at any one
time. Consequently there is a need to employ a sampling technique which best
approximates this ideal. The total transect survey time is standardized at 25 minutes
for the 40m belt transect.
In an attempt to reduce variability in fish densities (due to diurnal influences
on behaviour) sampling excludes the high activity periods of early morning and late
afternoon. Sampling has been limited to between 0900 and 1600. This time window
also excludes periods of poor visibility caused by low sun angle.
5.3.3 Threats to Ras Mohammed
The survey methods were the same as for the general benthic survey, utilising
three 40m long LIT at each depth at each site (eight replications per site). All colonies
recorded by the benthic transect were observed and all those showing signs of disease,
bleaching or predation by COTs or Gastropod (e.g. Drupella spp.) were noted in
terms of presence or absence. This allowed the calculation of proportions of
infected/affected colonies. COTs abundance used the same transects but the belt was
extended 5m either side of the transect to produce a total belt area of 3200m2.
Physical impacts was recorded using five 1m2 quadrats which were placed
randomly along the transects and the number of broken loose coral fragments were
recorded along with the number of damaged colonies with branches missing still
attached to the substratum.
5.3.4 Conservation Value Index
Extra attributes were deemed important for the Ras Mohammed assessment
due to the nature of management and threats present. Surveys were carried out (as
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Chapter 5. Case Study II Ras Mohammed National Park
above) for coral damage and broken fragments, as well as for rates of hard coral
recruitment. These were combined into the CVI referred to in full in Chapter 3.
5.4 Results
5.4.1 Benthic assemblage
There was no significant difference between the percentage cover of
scleractinian coral cover between the six study sites (Figure 5.1). The highest coral
cover was found at South Bereika, with a mean value of 33.3(±2.4)%. The second
highest mean coral cover was found at the upper slope of the Ras Umm Sid site, with
a mean cover of 28.6 (±7.4)%. Shark Observatory had 27.5 (±2.9)% mean coral cover
and the lowest hard coral cover was found at the Marsa Ghozlani site with just 19.7
(±1.1)% cover. The ranges (Max and Min cover) and standard error of the mean can
be seen in Table 5.2.
Although the hard coral cover did not vary significantly between sites, the
total live cover did vary significantly (F5,43=7.43;p<0.001), which can be clearly seen
in Figure 5.2. The live cover was significantly higher at the Old Quay (Tukey;
p=0.001) site when compared with all the other sites, between which there was no
significant difference.
The dominant scleractinian coral genera included, Acropora, Seriatopora,
Pocillopora, Stylophora, Porites and Montipora. There was also significant
abundance of the octocoral Millepora. The Acropora, Seriatopora and Millepora
genera were dominated by branching growth forms, the Pocillopora and Stylophora
were dominated by Sub-massive growth forms, Porites colonies were dominated by
massive growth forms and Montipora generally occurred in the encrusting form.
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Chapter 5. Case Study II Ras Mohammed National Park
Table 5.1 Scleractinian coral cover at the six study sites (n=4)
[c=Reef crest; s=Upper reef slope]
Percentage hard coral cover
Site
Mean
±s.e.
Min
Max
South Bereika (c)
32.8
3.3
26.0
38.9
South Bereika (s)
33.7
3.9
24.3
42.4
North Bereika (s)
24.1
5.8
15.9
37.3
Shark Observatory (c)
27.0
2.8
22.0
34.9
Shark Observatory (s)
28.0
4.6
24.3
38.5
Marsa Ghozlani (c)
19.7
1.1
17.4
22.4
Marsa Ghozlani (s)
21.8
1.8
17.3
26.3
Old Quay (c)
27.2
3.8
16.3
33.0
Old Quay (s)
21.4
7.5
8.6
43.2
Ras Umm Sid (c)
28.6
7.4
13.8
47.2
Ras Umm Sid (s)
18.4
5.8
8.3
34.7
40
% Hard Coral Cover
35
30
25
20
15
10
5
0
5
10 2005 10
SO
NB
5
10 2005
SB
5
10 2005
VC
5
10 2005
5
OQ
10
RUS
Figure 5.1 Mean (±s.e., n=8) hard (hermatypic) coral cover on upper[5] and
lower[10] reef slopes at the study sites. Mean site values for 2005 are shown for
comparison where available [ Site Key; SO-Shark Observatory, NB-North
Bereika,SB-South Bereika, VC-Marsa Ghozlani, OQ-Old Quay, RUS-Ras Umm Sid]
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Chapter 5. Case Study II Ras Mohammed National Park
As there was no significant difference between the hard coral cover at the
sites, the difference in overall live cover can be attributed to the significantly higher
proportion
of
soft
corals
(Alcyonacea)
found
at
the
Old
Quay
site
(F5,43=24.8;p<0.001). Tukey post hoc tests found no significant difference between
the other sites regarding soft coral cover.
This variation in soft coral cover can be seen in Figure 5.3, along with the
proportions of hard corals (Scleractinia) and coral rubble, algae and bare rock
substratum. The proportion of coral rubble varied very significantly between the
original four study sites (F5,43=3.67;p<0.01) of Old Quay, Shark Observatory, Marsa
Ghozlani an South Bereika surveyed in 2005, with the highest proportion of rubble,
10.1(±1.3)% found at the South Bereika site (Tukey; p<0.001). There was no
significant difference in coral rubble cover between the other sites. Although the
majority of the algae was recorded at the Marsa Ghozlani site, there was a significant
difference in algal cover between the Old Quay and all other sites (F5,43=3.98;p<0.01),
with Old Quay showing less than 0.5% cover.
All of the sites, with the exception of Old Quay were also shown to be
dominated by bare rock substrata (Figure 5.3).
There was a significant difference (F5,43=7.45;p<0.001) in the number of hard
coral genera found at the six study sites (Figure 5.4). South Bereika had the highest
number of coral genera (19), which was significantly higher than the number of
Genera recorded at the Shark Observatory(11) site (Tukey p<0.001), as was the
number of Genera found at North Bereika (p<0.001), whereas there was no significant
difference in numbers between the other sites. There was no significant difference in
the generic richness recorded in this study with that observed during 2005 at any of
the sites.
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Chapter 5. Case Study II Ras Mohammed National Park
70
2005
60
2006
% Live cover
50
40
30
20
10
0
SO
NB
SB
VC
OQ
RUS
Figure 5.2 Variation in mean (±s.e, n=8.)total live benthic cover between sites [Site
Key; SO-Shark Observatory, NB-North Bereika,SB-South Bereika, VC-Marsa
Ghozlani, OQ-Old Quay, RUS-Ras Umm Sid]
100%
90%
80%
RK
70%
ALG
60%
DC
50%
CR
40%
SC
30%
HC
20%
10%
0%
5
10
SO
10
NB
5
10
SB
5
10
VC
5
10
OQ
5
10
RUS
Figure 5.3 Breakdown of dominant benthic cover by category [Benthic key; RK-Bare
Rock, ALG-Macro-algae,DC-RecentlyDead Coral,CR-Coral Rubble,SC-Soft
Coral,HC-Hard Coral] [ Site Key; SO-Shark Observatory, NB-North Bereika,SBSouth Bereika, VC-Marsa Ghozlani, OQ-Old Quay, RUS-Ras Umm Sid]
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Chapter 5. Case Study II Ras Mohammed National Park
Hard Coral generic richness
25
20
15
10
5
0
5
10
SO
10
NB
5
10
5
SB
10
5
VC
10
5
OQ
10
RUS
Figure 5.4 Mean(±s.e., n=8) hard coral Generic richness
[ Site Key; SO-Shark Observatory, NB-North Bereika,SB-South Bereika, VC-Marsa
Ghozlani, OQ-Old Quay, RUS-Ras Umm Sid]
0.30
Colony size(m)
0.25
0.20
0.15
0.10
0.05
0.00
5
10
SO
10
NB
5
10
SB
5
10
VC
5
10
OQ
5
10
RUS
Figure5.5 Mean (±s.e., n=8) hard coral colony size [ Site Key; SO-Shark
Observatory, NB-North Bereika,SB-South Bereika, VC-Marsa Ghozlani, OQ-Old
Quay, RUS-Ras Umm Sid]
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Chapter 5. Case Study II Ras Mohammed National Park
There was a significant difference in the mean size of the hard coral colonies
(Figure 5.5) between all the sites (F5,43=2.71;p<0.05), with an overall average size of
0.15m (Range 0.12-0.20m).There was no significant difference in mean colony size
between the two depths. This mean size showed no significant difference to the value
recorded in 2005. There was also a very significant difference in the number of coral
colonies per transect area between the sites (F5,43=3.20;p<0.05) (Figure 5.6). South
Bereika site had a higher mean number of coral colonies, (Tukey p<0.01) than the Old
Quay site, while the Marsa Ghozlani site also showed a significantly higher number of
colonies (p<0.05), than at Old Quay. Again these values did not differ significantly
from those observed during the 2005 study. Again there was no significant difference
in colony abundance between the different depths.
No.colonies transect -1
120
100
80
60
40
20
0
5
10
SO
10
NB
5
10
SB
5
10
VC
5
10
OQ
5
10
RUS
Figure 5.6 Mean(±s.e, n=8.) number of hard coral colonies at each site
[ Site Key; SO-Shark Observatory, NB-North Bereika,SB-South Bereika, VC-Marsa
Ghozlani, OQ-Old Quay, RUS-Ras Umm Sid]
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Chapter 5. Case Study II Ras Mohammed National Park
The use of randomly placed 1m2 quadrats identified a mean recruitment rate
for scleractinian corals of 1.21 (±0.13) new recruits per m2 per year. The number of
recruits ranged from 0.8 m-2 at the Old Quay site to 1.93m-2 at the Marsa Ghozlani
site. There was no significant difference in the number of recruits between all the
different sites.
5.4.2 Fish Assemblage
The survey sites showed significant variation in three of the fish survey
metrics used but not for the richness of Serranidae, Scaridae, Labridae and
Pomacanthidae. The total number of species recorded at each site also showed no
significant difference between sites, which ranged from 93 to 102 species.
With regard to abundance of fishes at the six sites, there was a very significant
difference (F5,43=3.82;p=0.01) between the Old Quay site (Tukey p<0.05) and the
Marsa Ghozlani (Visitor Centre) and North Bereika sites. There was no significant
difference in the mean fish abundance between all other sites. The Old Quay site had
a mean (±s.e. ;n=8) abundance of 3242.9 (±501.5) 1000m-3, while the lowest
abundance was found at the North Bereika site, with 422.0 (±11.1) 1000m-3. The
abundance values varied quite considerably between individual samples with a
minimum value of 125 1000m-3 at the Marsa Ghozlani site to a maximum value of
8075 1000m-3 at the Shark Observatory (Table 5.3).
Both Principle Component Analysis (Figure 5.7) and Bray Curtis (Group
average) cluster analysis (Figure 5.8) identified the degree of similarity between all
sites. The PCA plot suggests that fish abundance is the most influential factor in the
differences between sites. The cluster analysis suggested that the fish assemblages at
all four sites shared a similarity in composition of around 85%.
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Chapter 5. Case Study II Ras Mohammed National Park
Table 5.2 Mean(±s.e.) fish abundance per 1000m3 with minimum and maximum
counts for each study site on the reef crest(c) and upper reef slope (s) [ Site Key; SOShark Observatory, NB-North Bereika,SB-South Bereika, VC-Marsa Ghozlani, OQOld Quay, RUS-Ras Umm Sid]
Mean
s.e.
Min
Max
SO (c)
1213.3
198.5
809
1704
SO (s)
3120.8
1750.7
645
8075
NB (s)
422.0
13.6
392
445
SB(c)
1119.3
580.8
421
2850
SB(s)
453.0
119.1
212
740
VC(c)
968.3
244.4
475
1644
VC(s)
380.5
114.3
125
671
OQ(c)
4339.8
348.1
3490
4969
OQ(s)
2146.0
500.6
1191
3557
RUS(c)
2014.0
997.7
680
4963
RUS(s)
1546.5
712.0
745
3674
4
SOu2
SOl1
SOu1
SOl2
2
Pomacanthid
Abundance
Acanthurid
OQl3
SOu3
RUSl1
OQu1
OQu2
PC2
RUSl2
SOl3
Serranid
OQl1
0
VCl2
ChaetodontRUSl3
VCu1
SBl2
NBl1
NBl3Labrid
Scarid
RUSu3
NBl2
VCu2
SBu1
SBl1
-2
SBl3
Pomacentrid
VCl3
OQu3
RUSu1
OQl2 VCl1
RUSu2
SBu3
VCu3
SBu2
-4
-6
-4
-2
0
2
PC1
Figure 5.7 PCA plot of fish assemblage attributes
162
4
Chapter 5. Case Study II Ras Mohammed National Park
Group average
VCu2
SBu1
NBl3
SBu2
VCl2
NBl1
NBl2
VCl1
SBl2
RUSu3
SOl3
RUSl3
SBu3
SBl3
VCu3
VCu1
VCl3
RUSl1
SOu1
OQl1
SOu2
OQl2
SOu3
RUSu2
SBl1
RUSl2
OQl3
OQu3
SOl1
RUSu1
OQu2
OQu1
SOl2
60
70
80
Similarity
90
Samples
Transform: Square root
Resemblance: S17 Bray Curtis similarity
100
Figure 5.8 Dendrogram of cluster analysis (Bray-Curtis, group average
linkage) of fish assessment metrics [Site codes: SO-Shark Observatory, SB- South
Bereika, MG-Marsa Ghozlani, OQ-Old Quay, NB-North Berika, RUS- Ras Umm
Sid][u-Upper reef slope, l-lower reef slope]
The fish assemblages at all of the sites were dominated by three very abundant
species, the half-and-half chromis (Chromis dimidiata), the Orchid dottyback
(Pseudochromis fridmani) and the Lyretailed anthias (Pseudoanthias squamipinnis).
These three species accounted for over 65% of all fish observed at all sites.
The functional redundancy of the four sites, i.e. the number of different
species present within a family, shows that there were very limited differences
between the different sites in the number of species representing each of the dominant
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Chapter 5. Case Study II Ras Mohammed National Park
seven families. The Chaetodontidae showed a significant difference between sites
(F5,43=3.26;p<0.001), with both South Bereika and Old Quay having a mean of 5.0
(±0.4) species 1000m-3, while the North Bereika site had a mean of just 2.7 (±0.2)
species 1000m-3. The Pomacentridae also showed significant differences in species
richness between sites (F5,43=5.74;p<0.001), with a mean 7.5 (±1.0)species 1000m-3
at the South Bereika site and just 3.0 (±0.6)species 1000m-3 at the Shark Observatory
site. There were no significant differences observed in fish species richness between
the two depths surveyed at any of the sites.
5.4.3 Threats to Ras Mohammed
No observations of A. planci were made on any of the survey transects, only
one individual was seen over the course of this study at the Marsa Ghozlani site. The
individual was a mature specimen at over 50cm diameter. There were several small
patches of recently dead coral in the immediate vicinity.
The corallivorous gastropod Drupella spp. was present on several coral
colonies at the Marsa Ghozlani and South Bereika sites. At South Bereika they were
found to be present in small aggregations (<10) on 1% of colonies intersecting the
line transects, while at Marsa Ghozlani they occurred , again in small aggregations on
0.6% of colonies. All Drupella observed were only found on Acropora spp. corals.
No incidence of coral bleaching was observed either on the transects or in the
park in general during the period of this study. Only one incidence of coral disease
was observed in the park at the Marsa Ghozlani site.
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Chapter 5. Case Study II Ras Mohammed National Park
5.0
Loose coral fragments
4.5
Damaged coral colonies
Number m -2
4.0
3.5
3.0
2.5
2.0
1.5
1.0
0.5
0.0
5
10
SO
10
NB
5
10
SB
5
10
VC
5
10
OQ
5
10
RUS
Figure 5.9 Incidence of physical damage to hard corals
There were a mean number of 1.7 (±0.2) broken coral fragments observed per
metre squared throughout the park in 2006 (Figure 5.9). There was a significant
difference in the number of broken fragments at each site (F5,43=3.36;p<0.05). The
highest occurrence of broken fragments was at the Old Quay site (3.1 ±0.5), where
branching Millepora dominates the substratum. The lowest incidence occurred at the
undived North Bereika site (1.1±0.1) which receive minimal numbers of divers.
There was also a significant difference in the number of broken or damaged
coral colonies at the six sites (F5,43=3.30;p<0.05). Fewest damaged colonies were
observed at the Old Quay site (0.05 ±0.03), while the most damage was observed at
the Shark Observatory site (0.68 ±0.13). The average number of damaged colonies
throughout the park was 0.35 (±0.06) per metre squared.
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Chapter 5. Case Study II Ras Mohammed National Park
5.4.4 CVI Assessment
The CVI scores for the six sites are displayed in Table 5.4 and can also be
seen in Figure 5.10, where they are overlaid on a satellite image as an example of the
easily interpretable output from the CVI.
Figure 5.10 Satellite image of Ras Mohammed National Park with overlaid 2006 CVI
values for the study sites (Source: Landsat millennium coral reef archive)
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Chapter 5. Case Study II Ras Mohammed National Park
Table 5.3 CVI benthic and fish values with final CVI codes
[c-Reef Crest, s-Upper Reef Slope]
Site
Shark Observatory (c)
Shark Observatory (s)
North Bereika (s)
South Bereika (c)
South Bereika (s)
Marsa Ghozlani (c)
Marsa Ghozlani (s)
Old Quay (c)
Old Quay (s)
Ras Umm Sid(c)
Ras Umm Sid(s)
CVI
Benthic
score
CVI
Fishery
score
CVI
code
48
48
51
51
53
49
46
53
52
48
46
48
40
26
66
26
46
22
70
48
66
32
C3
C3
B4
B2
B4
B3
C4
B2
B3
C2
C4
For the benthic component of the index, the South Bereika and Old Quay sites
scored the highest with a score of 53 out of a maximum of 80 points. The second
highest benthic score was found at the North Bereika site at 51. Shark Observatory
and Ras Umm Sid showed the lowest benthic score at 33. The Marsa Ghozlani
(Visitor Centre) site had a score of 49. This meant that North and South Bereika and
Old Quay was classified as ‘B’ ranked sites, while the other three sites were all
ranked as ‘C’.
For the fish assemblage component of the index, the Old Quay site scored
highest with 70 (out of 90), closely followed by the South Bereika and Ras Umm Sid
sites at 66. The Shark Observatory site scored 48, while the Marsa Ghozlani site
scored 46. The North Bereika site rated at just 26, giving a CVI ranking of ‘4’. The
upper slope sites at Ras Umm Sid, Old Quay and South Bereika all scored highly at a
rank of ‘2’. The lower slopes at these sites as well as all other sites scored ‘3’ and four
of the sites scored the lowest with a ranking of ‘4’.
The CVI output can also be represented as a grid style figure to allow
identification of spatial and temporal trends in scores (Figure 5.11).
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Chapter 5. Case Study II Ras Mohammed National Park
E
D
C
B
A
SO - 2006
1
SB - 2006
MG - 2006
2
OQ - 2006
NB - 2006
3
RUS - 2006
SO - 2005
4
SB - 2005
MG - 2005
5
OQ - 2005
Figure 5.11 Grid style output indicting changes in CVI scores between 2005 and 2006
[Site codes: SO-Shark Observatory, SB- South Bereika, MG-Marsa Ghozlani,
OQ-Old Quay, NB-North Berika, RUS- Ras Umm Sid]
5.5 Discussion
5.5.1 Benthic assemblage
The uniformity of coral cover at all sites is somewhat surprising as the sites
were selected for their varied factors such as sheltered and exposed, heavily dived and
minimally dived. This suggests that some other over-riding factor, such as the COTs
outbreak in 1998, has had a more important influence on the benthic assemblage.
The Old Quay site had lowest mean hard coral cover and had 50% lower cover
than other sites in the southern Gulf of Suez as reported by Perkol-Finkel et al.,
(2005), although the high soft coral cover observed at this site corresponds to reported
values for the Gulf of Suez. This study found that the soft coral assemblages were
dominated by the Xenia genus, again in line with the findings of Perkol-Finkel et al.,
(2005). However, the level of hard coral cover is some 10% higher than that reported
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Chapter 5. Case Study II Ras Mohammed National Park
by PERSGA (2005), this difference may be due to different survey methods used in
their study. The South Bereika site also showed the highest levels of coral rubble,
which may be attributable to the number of snorkeller boats observed at this site
during the course of this study. The number of individual hard coral colonies at Old
Quay was lower than the other survey sites, possibly due to the increased levels of
spatial competition, with the high soft coral cover preventing recruitment of coral
planulae (Atrigenio and Aliño,1996; Maida et al.,1995), although no significant
difference in levels of recruitment was observed.
The Shark Observatory site had the second lowest hard coral cover of the
study sites, and this level is only 50% of that reported by the ReefCheck website
(Hodgson, 2005), and is still 30% lower than the reported levels before the 1998
COTs outbreak. It should however be noted that direct comparisons with ReefCheck
data are not suitable due to the different methodology used to collect the information.
Levels of soft coral cover are slightly higher than those currently reported by
ReefCheck although still only around 55% of the pre-1998 cover. The generic
richness of hard corals was the lowest at this site, which would support the
intermediate disturbance hypothesis of Karlson and Hurd (1993),as it is at the very
southern tip of Ras Mohammed and exposed to the prevalent currents from the south.
The lack of richness and cover may be somewhat attributable to the steep ‘walled’
topography of this site. Although the number of divers visiting this site is reported to
be among the lowest in the park (<1000 yr -1) by the PERSGA (2005) report, during
the period of this study, more divers were again observed at this site than at all others,
with the exception of Ras Umm Sid (McMellor, unpublished data), in line with the
observations from 2005. The topography of this site, with its steep vertical walls, may
however, limit impacts from divers who cannot swim directly above the substratum.
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Chapter 5. Case Study II Ras Mohammed National Park
The coral cover at the Marsa Ghozlani site was lower than that estimated by a
2003 ReefCheck survey, but higher than that identified in the PERSGA report (2005).
The soft coral cover identified was only half that reported by ReefCheck, while the
amount of coral rubble at the site was constant. These figures may say more about the
statistical integrity of the ReefCheck method, rather than real changes over time. This
site is one of the most heavily utilised by visitors with some 30000 dives per year
(PERSGA, 2005). There were five boat moorings at this site which were often all
occupied by two or more boats. The majority of visitors were snorkellers, with some
shore diving also noted. The number of coach visitors to the beach at this site was
likely to be responsible for the huge amounts of litter both on shore and on the reef, in
the form of plastic bags, soiled nappies, and plastic water bottles. Further studies into
the nutrient status of the bay would be beneficial as this was the only site with a
significant abundance of turf algal cover. Anthropogenic disturbance may also be
behind the fact that this site also had the lowest mean coral colony size, although it
did support the second highest number of coral colonies.
The recorded cover at the South Bereika site had agreed with the values in
both the PERSGA report (2005) and also the work of Saleh (2006). This site was also
found to contain the highest generic richness of hard corals in this study as well as
largest number of colonies per area. This site has been closed since the mid 1980’s
and has only recently re-opened to divers, although shore diving is still prohibited.
According to the PERSGA records, this site receives over 15000 divers per year. Over
the period of this study, all the moorings at this site were often occupied, yet the
majority of day boats appear to utilise the site as a lunch time mooring, with some
snorkelling, as very little diving was observed.
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Chapter 5. Case Study II Ras Mohammed National Park
The total coral genera found throughout this study comprised just fewer than
50% of the genera known to occur in the Red Sea region (Veron, 2000), with all of
the common genera found, but few of the rarer genera recorded. As the mean coral
colony size is relatively small at all the sites, this seems to suggest that the reefs are
starting to recover from the COTs episode and hence many of the colonies are small
and likely recruited since the COTs problems.
As there is a general lack of published data for the Ras Mohammed National
Park (Wilkinson, pers. com.), the data used for comparison with this study was mainly
from the ReefCheck database. It should be noted that due to the methodology used,
these ReefCheck data may be subjective and not give a reliable estimation of true reef
condition. A discussion on the suitability of ReefCheck method is covered in more
detail in Chapter 2.
There was no significant difference in the mean number of scleractinian coral
recruits to each of the six study sites. This suggests that recruitment is fairly
consistent throughout the park and although the figures are somewhat lower than
other reported studies, the uniformity of the recruitment rates suggests that there is
plenty of available substratum and there are no site specific impacts preventing
recruitment. Further temporal studies are needed to confirm if stable recruitment rates
are ongoing. Grazing by Scaridae may be keeping recruitment rates lower than would
be expected in a region where the fish population was being exploited.
In summary, the benthic assemblage of the Ras Mohammed National Park
appear to be starting to recover from the devastation caused by the COTs outbreak in
1998. Although there was significant coral bleaching in the Red Sea in 1998, this did
not affect the Ras Mohammed region. Although large areas of bare substratum exist,
these are generally free of turf algae and available for recruitment of other benthic
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Chapter 5. Case Study II Ras Mohammed National Park
invertebrates. However, the recruitment rate within the park is relatively low when
compared to other reported rates of recruitment (Kojis and Quinn, 1999). The higher
abundance of soft corals is known to inhibit coral recruitment (Maida et al., 1995) and
a higher number of scraping and grazing Scarids could be inhibiting the success of the
new recruits. Further monitoring over the coming years is vital to monitor this
recovery and identify further problems, from both natural and anthropogenic sources.
Continued monitoring should include completely closed areas which can act as a
control to monitor the rates of change in benthic cover and relate this to the levels of
visitors to the sites. These closed areas and other popular dive sites within the park
were not sampled here due to logistical restraints in terms of access.
5.5.2 Fish assemblage
The abundance of fish varies surprisingly little between the sites, with only the
one significant difference between the Old Quay and the Marsa Ghozlani and North
Bereika sites. This may be due to the protection offered by the no fishing status of the
Ras Mohammed park. Fishing is prohibited in all areas of the park and has been since
its establishment, although it was several years after the parks establishment that
compliance became high (Saleh, pers com.). It appears that the ban is generally
observed and that there are only minor infringements. This lack of fishing pressure
means that natural competitive interactions are occurring and hence most of the fish
assemblage are similar in abundance and composition, with local variations
attributable to natural variations possibly linked to localised reef conditions and
habitat variation.
For the Marsa Bereika (South) and Ras Umm Sid sites, the abundance is
similar to that of Leujak (2005), although due to the use of slightly different methods,
the data are not directly comparable. Unfortunately no abundance data was available
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Chapter 5. Case Study II Ras Mohammed National Park
in the literature regarding the Shark Observatory, Marsa Ghozlani, North Bereika and
Old Quay sites.
The variation in the individual samples (transects) is likely to be attributable to
currents influenced by tidal state, as the fish surveys were carried out at a similar time
of day to avoid any diurnal variation. The greatest variation was recorded at the Shark
Observatory site, attributable to the varied strength of the currents at this very exposed
site located at the point where the Gulfs of Suez and Aqaba part.. When the current
was running at this site it was often moderate to strong and hence larger numbers of
pelagic species were recorded. At the Old Quay site the local conditions varied
considerably with the state of the tide and due to the large expanse of shallow reef flat
adjacent to this site, numbers of pelagic fish may have limited access to the reefs. The
lowest variation between individual samples was found at the North Bereika site
which had the most stable, sheltered conditions, but the lowest overall abundance of
fishes.
The number of reef fish species observed during this study represents
approximately 10% of the reported total 1000 species present in the Red Sea (Lieske
& Myers, 2004) , with the figure from this study being similar to the findings of
Leujak (2005), though again the two methods used mean that the data are not
statistically comparable.
Those sites with high abundance tended to have lower diversity as they were
dominated by vast numbers of several common planktivorous species, such as the
Anthiases (Pseudoanthias squamipinnis); particularly at the Shark Observatory site.
The two low abundance sites did not appear to be dominated by a few species and
hence showed greater diversity. It is also worth noting that the cluster analysis also
confirms that all of the sites have similar fish assemblages.
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Chapter 5. Case Study II Ras Mohammed National Park
With regard to the functional redundancy of the fish populations at the study
sites, there were very limited differences between sites, with similar numbers of
species from each family present. The exceptions being the increased Chaetodont
species richness at the Old Quay and South Bereika sites and lower richness of
Pomacentrids at the Shark Observatory site. The latter may be explained by the
topography at the Shark Observatory site, where the steep wall may not provide a
suitable habitat for some species, along with increased predation from the large
numbers of pelagic predators that congregate there. Similarly, the steep wall at this
site is often in deep shade in the afternoons and hence algal production is likely to be
reduced, as shown in the lack of algal cover at this site, removing the primary food
source for many of the Pomacentrids. Many Pomacentrids also show close
associations with branching Scleractinian colonies, which were limited in number at
this site, possibly helping to explain their reduced abundance there.
The only available data for temporal comparison is that provided by the
ReefCheck database for the Chaetodontidae, Serranidae and Scaridae families. The
species richness and hence a proxy for functional redundancy of the Chaetodontidae
(Butterflyfish) has shown a steady decline at the Shark Observatory site from the mid1990’s to the present survey, with the current richness less than a third of the recorded
levels before the 1998 COTs outbreak, in line with the report of Wilkinson, (2002).
The removal of coral substrata by the COTs, would have impacted the obligate
corallivorous species, which are known to migrate to seek food elsewhere (Crosby &
Reese, 1996), leaving the non-corallivores behind, giving a lower species richness.
The numbers of Chaetodonts has also declined from pre-1998 levels at the Marsa
Ghozlani and South Bereika sites. No comparable data was available for neither Old
Quay, Ras Umm Sid nor North Bereika.
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Chapter 5. Case Study II Ras Mohammed National Park
The species richness of Serranids (Grouper) seems to be increasing at both the
Marsa Ghozlani and Shark Observatory sites, when compared to ReefCheck data from
previous years (Hodgson, 2005). Scarrid (Parrotfish) richness also appears to be
increasing at the same two sites when compared to ReefCheck data, and are above
pre-1998 levels. This may be explained by the removal of coral substrata by the COTs
outbreak, leaving more calcareous substrata and algae, suitable for the Scarrid diet,
which supports a greater diversity of Scarrid species.
In summary, all of the sites in this study have similar fish populations,
although the exposed Shark Observatory, Ras Umm Sid and Old Quay sites are
characterised by low species diversity but high abundance, while the sheltered Marsa
Ghozlani, North and South Bereika sites show low abundance but high diversity.
5.5.3 Threats to Ras Mohammed
The survey results suggest that COTs (A.planci) are no longer a significant
problem on the reefs of the Ras Mohammed park, with no quantitative values for their
abundance. The sighting of a single individual suggests that the reefs within the park
are now back to their normal, non-outbreak state. Although the reefs are appearing to
recover from the devastation the 1998-2002 outbreak caused, future monitoring is
vital to allow immediate action to be taken, should numbers begin to rise significantly
once more. This future monitoring is essential if the reefs of the park are to survive as
studies suggest that if the outbreaks start occurring more regularly than every 15
years, then the reefs will continue to decline and there will not be enough time
between outbreaks for then reef communities to recover (Hart & Klumpp, 1996).
Again, as with the COTs, the population of the corallivorous gastropod
Drupella spp. seems to be in a non-outbreak state with just a few individuals
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Chapter 5. Case Study II Ras Mohammed National Park
aggregating on certain corals especially of the Acropora genus. Again, their presence
in such small densities is no cause for concern and a natural part of the reef
communities. The population needs ongoing monitoring as large increases in their
abundance could have a considerable effect on the coral assemblage of the park,
especially in tandem with other impacts.
No signs of coral bleaching or disease were recorded in any of the surveys,
and only a single incidence of disease was observed while diving within the park in
general. As both bleaching and diseases have previously been identified within the
park, it is again, essential to continue to monitor for either impact.
As the impacts of SCUBA divers and snorkellers are one of the greatest
threats to the health of the parks benthic assemblage, their effects should be included
in the future monitoring program. The number of broken coral fragments throughout
the park seems higher than would be expected from natural disturbance and this can
be linked to rates of anthropogenic damage caused by divers and snorkellers
(Hawkins & Roberts, 1992). The high number of broken colonies at Shark
Observatory may be due to the high number of visitors this site receives, the fact that
more fragments aren’t also found here can be attributed to the wall style topography
meaning fragments sink into the depths and are not recorded as they are at some of the
sites with sloping topographies. In future this can be compared to data from areas
closed to the public to confirm that it is the visitors causing the damage and not some
other factor. Establishment of monitoring in closed areas will also provide data to
monitor the rates of recovery of the reefs from the COTs outbreak. Although the
correlation was not significant for this study, the expansion of the surveys to more
sites in future years may give a more realistic picture of the true effect of the tourist
visitors.
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Chapter 5. Case Study II Ras Mohammed National Park
5.5.4 CVI assessment
The CVI index does rank the sites in a logical order and is supported by the
traditional reporting methods in previous sections (i.e. Total live cover etc.). The
expansion of these baseline CVI values to more sites in future surveys will allow the
monitoring for temporal change, while also giving an early warning about changes in
community composition across a greater area of the park. The CVI output can be
adjusted for any level of audience from community stakeholders, to scientists and
government. For example, if park managers have a scientific background, then the full
survey values for each attribute could be reported in great detail. Whereas if the
stakeholders were for example Bedouin dive boat crews, then the reporting of
declining summary values would be more appropriate, either in geographical map
form of by using some easily understood CVI scores or symbols. Use of the grid style
output allows for the easy identification of trends in changes of reef condition,
although changes over short timescales (such as annually) should be treated with
caution as they may be down to the inherent variability of coral reef systems or
artefacts f an insufficient sampling design and should be monitored longer term to
identify real change.
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Chapter 6. General Discussion
CHAPTER 6. General Discussion
6.1 Optimised Survey Methods
It is vitally important to take account of the necessary statistical and ecological
considerations to allow the provision of reliable, high quality data in an efficient
manner. Sample size and replication are important considerations when designing a
monitoring program and selection of unrepresentative sample size, or too few
replicates can have serious implications for the interpretation of the resulting data.
It is often true that in the collection of reef monitoring data, temporal and
financial considerations often override statistical ones. Although trade-offs between
data quality and quantity are necessary, the neglect of many basic statistical principles
means that monitoring program data is more likely to be misinterpreted. The data and
subsequent analysis in Chapter 2 of this study suggested that a transect length of 50
metres is the most appropriate sample size to provide a realistic estimate of cover
while being achievable within the limitations imposed by the safe use of SCUBA.
Replicates at three depths on the reef flat, the reef crest and upper reef slope allow for
much of the variation between depths and zones to be accounted for. Three replicate
transects at each of these depths will provide total transect coverage of 150m per zone
and a total of 450m per site, well above the minimum value of 135m proposed by
Leujak and Ormond (2007).
In terms of using volunteers to collect coral reef survey data, this study found
that at the category level (i.e. Hard coral, soft coral etc.), the accuracy of volunteer
collected data showed no significant difference from data collected by experienced
reef surveyors. The majority of the surveyed parameters showed no significant
difference between different surveyors, however, it should be noted that there was
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Chapter 6. General Discussion
greater variance between non-expert collected data when compared to the experienced
surveyors.
The consistency of data collected by different volunteers working on the same
transect showed similar high levels between observers and these high levels support
the results of other studies that identify the usefulness of volunteers to monitoring
programs (Erdmann et al., 1997; Harding et al., 2001;Mumby et al., 1995).
Peterman (1990) suggested that the minimal detectable effect obtained by a
given number of samples is a vital component when interpreting monitoring results,
yet statistical power analysis is a little used tool in monitoring program design. The
power of any study is proportional to the sample size. This suggests that the majority
of coral reef monitoring programs have such little power, that Type II errors become a
problem, where real change that is occurring is missed by the sampling design. To
identify minimal change at high power, sample sizes prove unrealistic for surveys
using SCUBA, and as such the sample design should either be adjusted to sample
many more sites or the error probability needs to be reduced to give increased power.
The only global method for reef survey and assessment currently accepted is
Reefcheck. It is becoming increasingly common as a management tool for MPA’s,
and yet it has been shown to be prone to Type II errors and as such will rarely detect
significant changes in hard coral cover, unless large numbers of stations are clustered
for analysis (Leujak and Ormond, 2007). The length of transects has been shown by
this study to be too short to be representative, while the replicates are pseudoreplicates of the same transect as their placement is neither random nor independent
from the previous. It should be of concern to reef managers that the data collected
with the Reefcheck method may not be reliably representing reef condition and could
lead to inappropriate management or no action at all.
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Chapter 6. General Discussion
The importance of following the survey protocol became apparent in some of
the 2006 data, where values recorded were significantly reduced from the two
adjacent years. Following discussions with the surveyors it became clear that the
survey protocol had not been strictly adhered to. A point sampling method had been
adopted to save time and some data was collected by volunteers who had not
completed the training program, but whom had assured prior experience of reef
surveys.
The methodology proposed (Appendix I) has been tested and shown to give
reliable estimates of various a reef attributes, as well as being time efficient and
repeatable. The tested survey protocol has also been shown to generate data of
sufficient quality when collected by trained volunteers. So long as the protocol is
followed, then the data used to generate CVI scores should prove viable, allowing
temporal and spatial comparison of reefs.
6.2 Validity of Conservation Value Index
The ordination of sites was shown to vary with the assessment metric used and
as such highlighted the problems in current assessments that utilise a single univariate
technique to differentiate between reefs of varied condition. A multivariate approach
as suggested by Extence et al. (1987) is more suited to providing an ordination of sites
based on numerous attributes. The PCA plots utilised in Chapter 3 of this study
overlaid with the vectors representing the individual attributes allowed the
identification of those attributes which varied across the range of site conditions. The
benthic attributes identified from the individual PCA represent a number of important
groups of reef biota as well as many of the commonly used reef condition reporting
attributes.
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Chapter 6. General Discussion
The setting of the scoring values and thresholds was dependent upon the aims
of the assessment and the level of change deemed necessary for the study. Such a
method of assigning qualitative scores to quantitative data will always be subjective,
but can still be useful to allow the combination of attributes into a multi-attribute
index. The setting of these scoring values can be adjusted for use in different studies
or regions, where different baselines may exist. For example the four categories f the
Reef Condition Index are appropriate for the Indo-Pacific, but in the Caribbean would
need to be adjusted otherwise all reefs would score poorly. Similarly fish species
richness varies with biogeographic location, and again target scores for one region
may not be attainable in others.
It was useful to note that the plus five year predicted values were not
significantly different from the actual values surveyed after five years, suggesting that
the linear model used was appropriate to give realistic scores for the different quality
reefs. The CVI scores showed appropriate definition by changing significantly when
extremes of data were entered into the index, for both good and poor condition reefs.
Although in reality it is unlikely that all the individual attributes will vary in a linear
manner, this was shown to be appropriate as it allowed extreme values to be entered
into the index which behaved as would be expected for real extreme values.
The inclusion of 24 wide ranging attributes, as suggested by Jameson et al.
(2001) can reassure managers that the reef community is responding to action, where
the monitoring of a single factor such as hard coral cover may not. The index
ordinates sites in a comprehensive manner that cannot be achieved using the
traditional univariate assessment methods. It also meets the requirements of Jameson
et al. (2001) in providing a classification of reef condition along a continuum which
allows the ranking of sites in order to allow prioritisation of conservation efforts.
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Chapter 6. General Discussion
The CVI has been shown to vary with reef condition, both temporally and
spatially, and as such can prove a useful addition to the reef managers ‘toolbox’. Use
of such multi-attribute indexes has become accepted in other fields of ecology, for
example the Habitat Suitability Index of Oldham et al., (2000) takes ten factors
relating to freshwater ponds such as size, degree of shading, location, fish presence
and vegetation cover. By scoring each individually and then combining them into a
single easily understood score the presence of Great Crested Newts (Triturus
cristatus) can be reliably predicted.
6.3 CVI as a management tool
The CVI allows MPA managers to quickly assess reef habitats and prioritise
areas for conservation efforts as called for by McKenna and Allen, (2000). The CVI
allows the reporting of feedback to stakeholders in terms of disseminating complex
data sets to managers, scientists and non-experts, in terms of a readily understandable
format, such as the maps or grids suggested. This meets the needs of such a method
called for by McClanahan et al. (2002) to monitor coral reef resources and develop a
scientific infrastructure and a conceptual platform for the interpretation of the
collected data. It also provides a method to quickly and accurately assess the health of
reef ecosystems and the level of threat that they face in terms of criteria and costeffective procedures for the assessment, as called for by Eakin et al., (1997). The CVI
also provides a single readily understood multivariate index, which Extence et al,
(1987) suggested would be of greater use than the reporting of numerous or single
factor indices. As demonstrated by the case studies in Chapters 4 and 5, the reporting
of numerous attributes and the associated statistics can become over-complicated and
difficult to interpret, especially by non-specialist stakeholders.
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Chapter 6. General Discussion
Noordeloos et al. (2004) reminded us that the aim of monitoring was to
provide managers, policymakers and other stakeholders with a reliable but simple
indication of whether the reefs within their own area are in good condition, whether
they are at risk from threats that may alter reef condition and whether effective
management actions are in place to deal with the threats. The CVI will help to report
status to managers, policymakers, politicians and other stakeholders as the outputs
can be readily understood. Secondly, any threats to a region can be incorporated into
the CVI attributes and the level of risk can be assessed, such as damage to coral
colonies in the index used in Ras Mohammed National Park. The index can also be
used to monitor management action and how it responds to threats. For example
target criteria can be set when a management action is undertaken and then monitored
with the CVI, such as closing an area to fishing and monitoring the CVI scores for
improvement in the fish assemblage with time. If the improvement occurs, the
management action can be judged successful, whereas if no improvement occurs with
time, or declines are ongoing, this suggests that the management action is not
appropriate or that there are further stressors impacting the fish population.
Conversely the index scores and underlying attribute values which are also retained
from the standardised survey methodology, and can be used to guide management
action as well as calculate index scores. If increases in coral rubble or damage are
occurring at a heavily dived area within an MPA such as Ras Mohammed, then the
cause could be isolated by taking appropriate management action such as closing the
area to recreation for a period, and monitoring the index for reductions in rates of
change of the specific attributes.
However, as the cause and effect of a problem may not be so easily identified
from changes in index scores, changes at a specific site or in a specific component of
183
Chapter 6. General Discussion
the index can be used to target more in depth biological survey which may be needed
to identify multiple stressors.
The CVI can act as a valuable tool for reef managers and further testing could
be used to demonstrate its flexibility in utilising varied attributes, targeted at a specific
area and the specific threats it faces.
By adhering to the tested survey protocol, managers can have confidence in
the CVI outputs, as well as the values for individual attributes. This allows them to
take appropriate action secure in the knowledge that this method of monitoring is not
subject to errors caused by insufficient survey effort or randomisation, that commonly
affect most monitoring programs.
6.4 Wakatobi Marine National Park
It was indicated in Chapter 4 that reef condition within the Wakatobi is in
decline. For individual sites the monitoring identified that the Sampela site changed
little and remained in poor condition compared to the other five sites. Both the CVI
and underlying univariate attributes also identified that the protected Hoga NTA site
showed the slowest rates of decline. For the park as a whole, the hard coral cover
declined by over 50% over the study period while the coral rubble cover increased by
over 50% over the same period. Significant reductions in mean fish abundance were
also recorded. In fact, monitoring program data showed significant declines in many
important classes of reef attribute. It is important to continue the monitoring of both
the benthic and fish assemblages for future change. The study also identified that
annual survey was more appropriate than longer interval surveys with a five year gap
identifying large changes in some reef attributes. Annual monitoring is more
184
Chapter 6. General Discussion
appropriate to allow the early detection of these changes and may give time to allow
management actions to be applied.
The CVI gave appropriate rankings to the sites and detected changes similar to
those identified by the 24 surveyed attributes in the benthic and fish assemblages.
Using the CVI method declines in scores were recorded at all sites, with the degraded
Sampela site consistently ranked lowest.
Therefore the CVI meets its goals of assessing reef condition in a way that can
be disseminated to a wide range of audience, while retaining the underlying data
which allows for more in depth analysis once change has been detected. The data for
the six years of the monitoring program to date were used to generate CVI values for
the Parks reefs and these were reported in both written and map format to the
Wakatobi Stakeholders Committee meeting in September 2007 to highlight the
importance and effectiveness of the NTA to local fisherman’s groups.
6.5 Ras Mohammed National Park
The study of reefs in the Ras Mohammed NP covered in Chapter 5 showed
that there was a small improvement in benthic reef condition at the study sites. The
levels of coral cover are increasing from those reported immediately after the COTs
outbreak of several years ago. The fish community showed a high degree of similarity
between all sites and remained temporally consistent, with some variation in
abundance attributable to varied environmental conditions between sites.
The CVI assessment also showed slight improvement in benthic condition and
a large degree of stability among the fish communities over the study period.
Inclusion of threat attributes specific to the region such as COTs abundance and
physical damage, allow the monitoring and reporting of region specific impacts to
185
Chapter 6. General Discussion
park managers as both the CVI scores and the underlying univariate data are
available.
As improvements in CVI scores were recorded, it demonstrates that the CVI
can respond in both positive and negative directions to identify rates of change in
overall scores, as well as in individual attributes.
This work will also help address the gap in knowledge about one of the worlds
best known but little understood (in terms of published literature), coral reef areas as
was identified by Noordeloos et al. (2004) and Wilkinson (pers. comm.).
6.6 Further study
As with any long term monitoring program, it is vital that the monitoring
effort be ongoing in both the Wakatobi MNP and the Ras Mohammed NP. The data
provided by Operation Wallacea volunteers can be used alongside data collected by
experienced teams of surveyors to generate CVI values for the reefs of both regions
and provide essential feedback to the parks respective stakeholders and managers.
Within the Wakatobi MNP the Hoga No Take Area was demonstrated to be
effective at maintaining stocks of important target species such as Grouper, as well as
slowing general reef decline and this evidence must be used to educate local
fishermen and other stakeholders about the need to maintain this area. This could be
combined with assessments of the usefulness of the CVI feedback to stakeholder
groups, in terms of understanding and usefulness to management.
There are numerous opportunities presented in the Ras Mohammed NP in
terms of monitoring the effectiveness of different management actions. The three
totally closed areas can be used as controls to monitor the impact of recreational
186
Chapter 6. General Discussion
divers on rates of reef recovery as well as monitoring the rates of change in the CVI
scores at closed and open sites subject to varied management strategies.
Finally, the CVI survey methodology could be made available to MPA
managers at numerous sites to allow the assessment of reef condition and provide
transparency in feedback to stakeholders. Protocols for the standardised survey
(Appendix I) as well as the index calculators spreadsheets and training packages
would aid in the management of MPA’s with limited resources in terms of expertise,
time and cost.
6.7 Aims of this thesis
This thesis addressed the problems associated with sampling strategies for
coral reefs and how they affect the quality of data collected. Chapter 2 meets the aim
of assessing various sampling strategies and identifying the most appropriate survey
method in terms of data quality and sampling effort. The use of continuous line
transects avoids the problems with point methods associated with questions of
richness. The LIT method also avoids issues of ex situ identification associated with
the photo and video methods. The length of transects and replication suggested at
each site allows for the detection of change in measured attributes with a high level of
confidence in the results. This confidence is vital to allow informed management
action to be taken.
The proposed CVI in Chapters 3 and the case studies in Chapters 4 and 5
meets the needs of an index for everyday use proposed by Extence et al. (1987). The
index allows the assessment of coral reef condition by combining numerous
commonly recorded factors into a single, easily interpretable index. By combining the
standardised survey protocol with this standardised method of assessment, (which has
been shown to be a reliable indicator of both reef condition and changes in that
187
Chapter 6. General Discussion
condition), reef condition can be reported in a reliable, statistically sound manner by
the Conservation Value Index. The index can be used to disseminate complex data
sets to a wide range of audience through several methods of output and hence
facilitate stakeholder MPA management by allowing the reporting of changes in reef
condition to the communities whom such changes will affect most.
The assessment of the Wakatobi MNP in Chapter 4 shows similar trends using
numerous univariate attributes or the proposed CVI. Both show a decline in reef
condition and declines in the fish assemblage. The dissemination of this data back to
the stakeholder decision makers should allow informed management action to be
taken to slow this decline and maintain the reefs and fish communities in this
important region.
The assessment of the Ras Mohammed National Park in Chapter 5 again
shows similar trends using the traditional univariate and CVI approaches. The benthic
reef communities here are showing signs of recovery since the catastrophic COTs
outbreak at the turn of the century, while the fish community remains stable due to the
enforced no-fishing status of the park. The data generated from this study has been
used by the EEAA to support their management strategies and provide data for this
important area, which had been previously lacking.
It is proposed that the CVI method of data collection, assessment and
presentation can act as a complete package to aid the sustainable management of these
important resources, whose survival is vital to so many.
188
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Appendix I. Proposed Survey Methodology for CVI monitoring
(i)Monitoring benthic community structure
The main group studied will be the hermatypic reef building corals (Order
Scleractinia). Other groups of sessile reef organisms to be monitored include the soft
corals (Alcyonacea), sponges (Porifera), macro algae and CCA. The area of coral rubble,
dead corals and area available for recruitment will also be recorded. Regular monitoring
of Echinoderm populations (Acanthaster planci and Diadema sp.) as well as abundance
of corallivorous Gastropods (Drupella spp.) will also be included.
The monitoring program will be carried out at a number of sites within a park to
be defined by a preliminary study, at three depths, the reef flat (0-2m) som 5-10m beck
from the crest running parallel to the shoreline, the reef crest (3-6m) and on the upper
reef slope (8-12m). A combination of several survey methods will be used to quantify
spatial and temporal changes in the benthic community. The principal technique to be
used will be the continuous Line Intercept Transect (English et al., 1996), combined with
belt transects and five 1m2 quadrats in subsets of each transect (Loya, 1978). Three 50
metre long transect tapes will be laid along depth contours parallel to the shoreline for
each depth at each site. All lifeforms intercepting the transect line will be recorded to
Genus with the length intercepting the transect tape recorded to the nearest centimetre.
An individual is defined as any colony/ individual growing independently from its
neighbours. In cases where a colony is divided into multiple parts by the death or
overgrowth of intermediate parts, each part is considered a separate colony. The area
intercepting the transect tape will be classified according to the benthic category system
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as HC-Hard Coral, SC-Soft Coral, SPG-Sponge, DC-Dead Coral, CR-Coral Rubble, SSand, ALG-Algae, CCA-Crustose Coralline Algae, OTH-Other, after the AIMS
methodology of English et al., (1996). Digital photographs will be taken of any unknown
lifeforms for later identification using keys. While recording the colony size intercepting
the transect line, coral predator abundance and the presence (area affected) of bleaching
or disease will also be noted. A belt transect extending 2.5metres either side of the
transect tape and five metres above the substratum will be over swam to quantify the
abundance of A.planci (C.O.T.S.).
(ii)Coral growth and rate of damage
Five 1m2 quadrats will be placed randomly along each LIT to allow for
monitoring of damage rates and coral recruitment rate. The quadrats will be examined for
newly recruited corals in three size classes (<10mm; <20mm; <30mm). Numbers of
broken coral fragments present and number of coral colonies with physical damage will
also be recorded for each quadrat.
(iii) Fish community status
The following section outlines the procedure for undertaking visual census
surveys at the permanent monitoring sites after the AIMS fish monitoring protocol
(Halford and Thompson, 1994).
The site is located from the surface using a GPS. Two divers enter the water. The
first diver (observer) is equipped with a slate, pencil and data sheets, the second diver
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(tape layer) carries the tape. Before reaching the first transect the tape layer runs out 2.5
metres of tape to allow the observer an initial visualization of the desired transect width.
The observer conducts the 50 metre by 5 metre by 5 metre surveys by swimming
along the centre line of the transect. The observer counts all fish sighted within the area
2.5 metres either side of and up to 5 metres above the centre line, recording family,
number of individuals.
The tape layer follows the observer approximately 5 metres behind, laying a tape
measure along the centre line of the transect.
At the end of every transect the observer calibrates their estimation of the transect
width. For the 50 metre by 5 metre transects the observer identifies an object estimated to
be 2.5 metres perpendicular to the centre line of the transect. This distance is measured
and recorded on the data sheet.
A visual census aims at recording an instantaneous estimate of abundance for the
target species present within the bounds of the transect. Unfortunately this theoretical
goal can never be realised due to factors such as the time taken to count and record each
individual, and commonly, the inability to scan the entire transect area at any one time.
Consequently there is a need to employ a sampling technique which best approximates
this ideal. Although it is impossible to census the entire transect in a given instant, it is
possible to treat the transect as a series of instantaneous counts, such that each portion of
the transect area is only viewed once for any given target species. In practice this is
achieved by viewing ahead and counting target species in an area of the transect
contained well within the bounds of visibility. During the first scan of the section the
most mobile target species should be counted and recorded, with progressively less
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mobile species recorded in consecutive counts. Fish entering the transect during, or after,
that area of transect is sampled are not included as they were not present during the initial
count. Once the most mobile species have been counted the observer moves along the
centre of the transect searching for the more cryptic and slower moving target species,
being careful to include individuals of the most mobile species which were obscured
from view by the structure of the reef during the initial count of the area.
In an attempt to reduce variability in fish densities (due to diurnal influences on
behaviour) sampling excludes the high activity periods of early morning and late
afternoon. Sampling has been limited to between 0900 and 1600 hours during winter
months and between 0800 and 1700 hours during summer months. This time window
also excludes periods of poor visibility caused by low sun angle.
(iv) Training
Surveyors will have to be well organised and prepared for the survey work
involved in the monitoring programme. Hence it is recommended that they undergo a six
day training course, confirming underwater ID skills, data recording and working
underwater, buoyancy stabilisation and survey practice, along with data entry procedures.
The course will involve ten one hour lectures on identification of benthic categories, and
fish families, along with survey techniques and methods. Lectures are to be run along
with revision and feedback sessions, two in-water practical sessions per day and a
compulsory ID test on the final day to be passed before surveying.
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