Potential ecological effects of cyprinid reduction fishery in Pikkala Bay

Transcription

Potential ecological effects of
cyprinid reduction fishery in
Pikkala Bay
2011
Tvärminne zoological station
Henri Jokinen & Marko Reinikainen
Project report
Henri Jokinen
and
Marko Reinikainen
ESKO Fishery group
Tvärminne Zoological Station
University of Helsinki
Project report
41 pp. + appendices
2011
Authors: Henri Jokinen, Marko Reinikainen
Tvärminne Zoological Station
J.A. Palménin tie 260
10900 HANKO
University of Helsinki
Faculty of Biological and Environmental Sciences
Cover photo: Breams, Abramis brama, in reduction catch (Henri Jokinen)
The authors are responsible for the content of this report and it is not an official statement representing Tvärminne
Zoological Station or the University of Helsinki
Summary
The stocks of cyprinid fish, such as roach, bream and white bream have increased in the Finnish
coastal waters as a probable consequence of eutrophication. The large amounts of cyprinids have
caused bothersome work for the fishermen due to the unwanted big by-catches. The increased
cyprinid populations might also compete with other economically more important fish species and
affect the whole ecosystem in several ways. In order to enhance the utilisation of cyprinids and
simultaneously decrease the stocks, some commercial cyprinid reduction fishery projects have been
launched at the Finnish coast. This study focuses on the cyprinid reduction fishery conducted in
Pikkala Bay, where about 160 tons of cyprinids (mostly bream) have been reduced in 2009–2010.
The main objective of this investigation was to look for possible environmental changes in the study
area of Pikkala Bay based on available data, and further to evaluate the changes and identify
potential ecological effects from the recent cyprinid reduction in the area. Firstly, the purpose was
simply to search for all possible existing and available environmental information from the Pikkala
Bay area, and to evaluate the quality and usefulness of these data for studying the effects of the
cyprinid reduction. The second aim was then to analyse the data for changes, possibly related to the
cyprinid reduction fishery. The study was mainly focused on fish, benthic fauna, and water quality.
In addition to the search and analysis of existing data, a test fishing effort was also conducted in
September 2011 in Pikkala Bay.
The search for environmental data and information about the Pikkala Bay area resulted in a
considerable amount of material consisting of literature, database findings, statistics and documents,
from the 1960’s to present, generating a good picture of the existing background information from
the area. Despite the fairly large amount of found environmental data, no clear indications of any
ecological effects caused by the bream reduction were found. The fish community was dominated
by perch and roach. Bream comprised a considerable proportion of the total biomass, and no signs
of a decrease were observed. The water quality in the bay showed no indication of effects from the
bream reduction, but instead seemed to have developed in accordance with the general
eutrophication. The lack of observable effects from the bream reduction can either imply that the
data were poor or insufficient for revealing potential effects, or that the bream reduction has not
caused any observable changes.
Experiences of cyprinid reduction in the coastal areas are few. If cyprinid reduction fishery projects
are implemented, more research is needed on their mechanisms and desired impacts as well as on
the unintentional ecological effects. The cyprinid reduction might have a potential to support the
improvement of the coastal waters alongside with the fundamentally important reduction of the
external nutrient loading.
Keywords:
biomanipulation, bream, coastal fish community, cyprinids, eutrophication, nutrients,
reduction fishery, water quality, zoobenthos
Särkikalojen poistokalastuksen mahdolliset ekologiset vaikutukset Pikkalanlahdella
Tiivistelmä
Särkikalakannat (varsinkin särki, lahna ja pasuri) ovat kasvaneet Suomen rannikolla todennäköisesti
vesien rehevöitymisen seurauksena. Nämä suuret särkikalamäärät ovat aiheuttaneet haittaa
ammattikalastajille suurien ei-toivottujen sivusaaliiden muodossa. Kasvaneet särkikalapopulaatiot
kilpailevat muiden, taloudellisesti tärkeämpien, kalalajien kanssa ja vaikuttavat monin tavoin koko
ekosysteemin tilaan. Tietyillä rannikkoalueilla on ryhdytty toteuttamaan kaupallista poistokalastusta
vajaasti hyödynnettyjen kalalajien käytön edistämiseksi sekä samanaikaisesti kasvaneiden
särkikalakantojen pienentämiseksi. Tämä tutkielma keskittyy Pikkalanlahdella tehtyyn
laajamittaiseen särkikalojen poistokalastukseen, jossa kahden ensimmäisen vuoden aikana (2009–
2010) saaliiksi saatiin 160 tonnia särkikalaa (suurimmaksi osaksi lahnaa).
Tämän työn päämääränä oli, käytettävissä olevaan tietoaineistoon perustuen, löytää ja arvioida
mahdolliset muutokset Pikkalanlahden vesiympäristössä sekä lisäksi tunnistaa potentiaaliset
poistokalastuken vaikutukset alueella. Ensimmäiseksi, tarkoituksena oli kattavasti etsiä
Pikkalanlahden aluetta koskevat olemassa olevat tietoaineistot sekä arvioida niiden laatu ja
käytettävyys särkikalojen poistokalastuksen vaikutusten tutkimisessa. Toiseksi, tarkoituksena oli
analysoida käytettävissä olevaa tietoaineistoa mahdollisten muutosten löytämiseksi sekä tutkia
poistokalastuksen mahdollista yhteyttä näihin muutoksiin. Tutkielmassa on keskitytty pääosin
kaloihin, pohjaeläimiin ja vedenlaatuun. Olemassa olevan tietoaineiston hakemisen ja analysoinnin
lisäksi toteutettiin koeverkkokalastus Pikkalanlahdella syyskuussa 2011.
Pikkalanlahden aluetta koskeva tietoaineistojen ja informaation haku tuotti huomattavan määrän
kirjallisista teoksista, tietokantalöydöistä, tilastoista ja muista dokumenteista koostuvaa materiaalia
1960-luvulta nykypäivään saakka, luoden hyvän kuvan alueen olemassa olevasta
taustainformaatiosta. Huolimatta varsin suuresta määrästä Pikkalanlahtea koskevaa tietoaineistoa,
merkkejä lahnan poistokalastuksen ekologisista vaikutuksista ei voitu löytää. Kalaston valtalajeja
olivat ahven ja särki. Lahna muodosti merkittävän osuuden kalaston kokonaisbiomassasta, eikä
merkkejä lahnan vähentymisestä havaittu. Vedenlaatu ei myöskään antanut mitään merkkejä
lahnojen poiston vaikutuksesta, vaan sitä vastoin vastasi yleisen rehevöitymiskehityksen kulkua.
Lahnan poistokalastuksen havaittavissa olevien vaikutusten puuttuminen tarkoittaa joko sitä, että
käytettävissä oleva aineisto oli laadultaan riittämätöntä mahdollisten vaikutusten paljastamiseksi, tai
sitä että poistokalastus ei ole tuottanut tai aiheuttanut mitään havaittavia vaikutuksia.
Kokemuksia rannikkoalueilla tapahtuvasta särkikalojen poistokalastuksesta on tähän mennessä
niukasti. Mikäli särkikalojen poistokalastusprojekteja tullaan toteuttamaan, tarvitaan enemmän
tutkimusta mekanismeista ja toivotuista vaikutuksista, kuin myös tahattomista ja ennalta
odottamattomista ekologisista seurauksista. Särkikalojen poistokalastuksella saattaa olla potentiaalia
rannikkovesien tilan parantamisen tukemiseksi perustavanlaatuisen tärkeän ulkoisen
ravinnekuormituksen vähentämisen ohessa.
Avainsanat: biomanipulaatio, lahna, pohjaeliöstö, poistokalastus, rannikon kalasto, ravinteet,
rehevöityminen, särkikalat, vedenlaatu
Potentiella ekologiska följder av reduktionsfiske på karpfisk i Pickalaviken
Sammandrag
Karpfisk, såsom mört, braxen och björkna, har ökat i de finländska kustvattnen, sannolikt till följd
av övergödningen. De stora mängderna karpfisk har orsakat betungande tilläggsarbete för
yrkesfiskare på grund av oönskade bifångster och kan också konkurrera med andra, ekonomiskt
viktigare, fiskarter samt även påverka hela ekosystemet på flera sätt. För att öka användningen av
karpfisk och samtidigt minska på dessa stammar, har man vid den finska kusten startat några
kommerciella reduktionsfiskeprojekt. Den här studien fokuserar på karpfiskreduktionen som utförts
i Pickalaviken, där ca 160 ton karpfisk (mest braxen) har reducerats under åren 2009–2010.
Huvudsyftet med den här undersökningen var att på basis av tillgängligt datamaterial söka möjliga
miljöförändringar i undersökningsområdet Pickalaviken, samt att vidare evaluera dessa förändringar
och identifiera potentiella ekologiska effekter från karpfiskreduktionen i området. För det första var
meningen att leta reda på all existerande och tillgäng data från Pickalavikens område, samt att
evaluera kvaliteten och användbarheten av materialet för studerandet av reduktionsfiskets effekter.
För det andra var målsättningen sedan att analysera data på förändringar, möjligtvis relaterade till
reduktionsfisket.
Data- och informationssökningen riktat på miljön i Pickalavikens område resulterade i en betydande
mängd material, bestående av litteratur, databasresultat, statistik samt andra dokument från 1960talet framåt, som skapade en bra bild av den existerande bakgrundsinformationen från området.
Trots att information och datamaterial hittades rätt rikligt, kunde inga tydliga indikationer på
braxenreduktionens ekologiska effekter hittas. Fisksamhället i Pickalaviken dominerades av abborre
och mört. Braxen utgjorde en betydande del av den totala fiskbiomassan och inga tecken på en
minskning av braxen kunde observeras. Vattenkvalitetsdata från Pickalaviken antydde inte på några
effekter från braxenreduktionen, men utvecklingen verkade i stället ha följt det allmänna
övergödningsförloppet. Avsaknaden av observerbara effekter från braxenreduktionen kan antingen
tyda på att uppgifterna var dåliga eller otillräckliga för att avslöja potentiella effekter, eller att
braxenreduktionen inte har förorsakat observerbara effekter.
Erfarenheterna av karpfiskreduktion i kustområden är få. Om karpfiskreduktionsprojekt
implementeras, behövs mera forskning kring mekanismerna och de önskade verkningarna såväl som
kring de oavsiktliga ekologiska effekterna. Karpfiskreduktionen kan ha potential att stöda
förbättrandet av kustvatten vid sidan av den fundamentalt viktiga minskningen av extern
näringsbelastning.
Nyckelord: biomanipulation, bottendjur, braxen, karpfiskar, kustfisksamhälle, näringsämnen,
reduktionsfiske, vattenkvalitet, övergödning
Preface
This is a final report of the first one-year ecological evaluation project for the Pikkala Bay cyprinid
reduction fishery. The project belongs to Tvärminne zoological station (University of Helsinki) and
was funded by an appropriation from the ELY-centre of Uusimaa (Centre for Economic
Development, Transport and the Environment) granted via the ESKO (in Finnish: “Etelä-Suomen
Kalatalousohjelma”) fishery group. The leader of the project is PhD Marko Reinikainen, director of
Tvärminne zoological station. The work has been conducted by project researcher MSc Henri
Jokinen under the management of Marko Reinikainen. Collaboration has been done with fisherman
Klaus Berglund, ELY-centre of Uusimaa and with LUVY (the Association for Water and
Environment of Western Uusimaa).
The basis for this project is the large-scale commercial cyprinid fishing in Pikkala Bay starting in
year 2009, conducted by the local fisherman Klaus Berglund. The landings of cyprinid fish during
the last years has been considerably larger compared to the years before 2009. This kind of
reduction of cyprinids, through targeted fishing efforts and a consequent increase of the landings,
may affect the ecosystem in different ways. The general aim of this project is therefore to
investigate the potential ecological effects of the cyprinid reduction fishery in Pikkala Bay.
The cyprinid reduction fishery in the coastal waters is a fairly new phenomenon, but a growing
interest is directed towards it. Studies concerning cyprinid reduction in coastal areas are scarce and
therefore little is known about its environmental effects. Besides the clear economically positive
aspect of enhancing the utilisation of the previously valueless cyprinid resource, the usefulness and
effectiveness of the cyprinid reduction for the expected environmental improvement, as well as the
possible side effects of the reduction, are still unknown. In order to be able to plan further
improvement measures in the coastal waters, evidence of the potential ecological effects from the
cyprinid reduction fishery is needed.
Table of contents
1 Introduction .................................................................................................................................................... 1
2 Backgrounds ................................................................................................................................................... 1
2.1 Eutrophication and the fish community................................................................................................... 1
2.2 Biomanipulation ...................................................................................................................................... 3
2.2.1 Theory............................................................................................................................................... 3
2.2.2 The Pikkala Bay cyprinid reduction fishery ..................................................................................... 4
2.2.3 Possible environmental effects of coastal cyprinid reduction .......................................................... 6
3 Features of the study ....................................................................................................................................... 7
3.1 The objective ........................................................................................................................................... 7
3.2 The study area – Pikkala Bay .................................................................................................................. 7
3.3 Materials and methods ............................................................................................................................. 9
3.3.1 Data search ....................................................................................................................................... 9
3.3.2 Test-fishing 2011 .............................................................................................................................. 9
3.3.3 Numerical analyses ......................................................................................................................... 10
4 Results and discussion .................................................................................................................................. 10
4.1 Existing environmental data .................................................................................................................. 10
4.1.1 Fish data.......................................................................................................................................... 11
4.1.2 Benthos data ................................................................................................................................... 12
4.1.3 Water quality data........................................................................................................................... 13
4.1.4 Other environmental data ............................................................................................................... 14
4.2 Test-fishing 2011 – the structure of the fish community ....................................................................... 14
4.3 Ecological changes in Pikkala Bay – lack of cyprinid reduction effects ............................................... 18
4.3.1 Fish ................................................................................................................................................. 18
4.3.2 Benthos ........................................................................................................................................... 24
4.3.3 Water quality .................................................................................................................................. 26
5 General points and conclusions .................................................................................................................... 33
Acknowledgements ......................................................................................................................................... 35
Literature ......................................................................................................................................................... 36
Appendices A–B
1 Introduction
The stocks of cyprinid fish, such as roach (Rutilus rutilus), bream (Abramis brama) and white
bream (Blicca bjoerkna), have increased in the Finnish coastline as a probable consequence of
eutrophication in the inshore and archipelago waters (Bonsdorff et al. 1997a, Lappalainen et al.
2001, Ådjers et al. 2006). Cyprinid fish have been valueless by-catch for professional fishermen
(due to the lack of consumer interest), only causing bothersome work. Additionally these fish
species might compete for food and space with other economically more important species and they
may also aggravate the state of eutrophication by e.g. recycling nutrients from the sediment and the
water column. Large-scale reduction or removal of cyprinids has been used in many lakes as a
restoration measure for counteracting the effects of eutrophication, i.e. to restore the natural balance
in the fish community, reduce internal nutrient loading and improve water quality (e.g. Meijer et al.
1999, Olin et al. 2006). The experiences from biomanipulated lakes vary considerably (see e.g.
Søndergaard et al. 2007), but have often proved the attempts to be successful (e.g. Horppila et al.
1998). Similar measures have seldom been used in sea areas and no reported results of cyprinid
reduction exist from the Baltic Sea so far. However, biomanipulation as a possible method for
improving water quality and restoring natural balance has recently gained interest and a few
projects have been launched in some Baltic Sea coastal areas. At the east coast of Sweden, a largescale pikeperch stocking project is carried through in Himmerfjärden (Anon. 2011a, b), a
planktivore management project is running in Kalmarsund (Anon. 2011c) and cyprinid reduction
fishery in combination with piscivore stocking is conducted in Östhammar (Anon. 2011d). In
Finland, similar projects are running in Mynälahti and in Pikkala Bay (Setälä 2011). In Mynälahti
cyprinids are reduced as by-catch in the regular commercial fishery and in Pikkala Bay a targeted
commercial reduction fishery for cyprinids has been started.
This study focuses on the cyprinid reduction fishery in Pikkala Bay. First, the backgrounds are
given, dealing with the general state of the coastal environment and fish communities as well as
with the cyprinid reduction as a mean of biomanipulation, both concerning the theoretical concepts
and the current practical attempts. Next, the features of the study are described, including an
explanation of the objectives, a characterisation of the study area, and a description of material and
methods used. Thereafter the results are presented and discussed. Finally the conclusions of the
study are viewed in relation to future needs and challenges.
2 Backgrounds
2.1 Eutrophication and the fish community
Eutrophication (i.e. excess of nutrients, mainly phosphorous (P) and nitrogen (N)) is a well known
phenomenon both in freshwater systems and in many marine areas (e.g. de Jonge et al. 2002) and
has been identified as a major threat for marine ecosystems globally (Nixon 1990). In the Baltic Sea
eutrophication has been a problem for several decades (Larsson et al. 1985) and is still considered
to be perhaps the single greatest threat to the Baltic Sea environment, causing severe changes
throughout the ecosystem (HELCOM 2009). Eutrophication affects different parts of the ecosystem
through complex interactions within and between the abiotic and biotic compartments, all based on
the increased primary production of the system. Given that the nutrient load to the sea consists to
the most part of freshwater runoff from surrounding land areas, inshore and coastal waters therefore
1
tend to be more eutrophicated and more locally influenced than open sea areas (Pitkänen 1994).
Severe coastal eutrophication and its consequences have been apparent in the Baltic Sea in general
(Cederwall & Elmgren 1990) as well as in the Finnish coastal waters (Bonsdorff et al. 1997a,
1997b, Lundberg et al. 2005). Eutrophication affects coastal ecosystems in several ways, directly and
indirectly, and causes, for instance, increasing primary production (e.g. cyanobacterial blooms and
increased growth of annual filamentous algae), decreased transparency, increasing coastal hypoxia,
and changes in the benthic fauna and fish communities (Bonsdorff et al. 1997b).
Fish as an organism group constitutes a central part of the aquatic ecosystem, both ecologically, e.g.
by being both prey and predators for other organisms, and economically, as an important human
food resource through the commercial fisheries (Worm et al. 2002, Pauly et al. 2005). In the Baltic
Sea the eutrophication process has been reflected in the fish communities as changes in production
and abundances in both pelagic and coastal species (Hansson & Rudstam 1990). Some species have
declined, while other species have gained advantages from the ongoing development. Cyprinid fish,
mostly roach, bream, and white bream, has generally increased in the coastal areas of Finland as a
probable consequence of the past and ongoing eutrophication (Bonsdorff et al. 1997a, Lappalainen
et al. 2001, Ådjers et al. 2006), now dominating the fish community in many areas (Lappalainen et
al. 2000, HELCOM 2006). Roach is generally the dominating cyprinid species (Lappalainen 2002)
but bream and white bream tend to be even more favoured than roach in extremely eutrophicated
areas (Lappalainen & Pesonen 2000). The true mechanisms behind the shift towards cyprinid
dominance are complex but likely connected to changes in habitats and alterations in competitive
and predatory relationships between fish species. Similar eutrophication induced “cyprinidification”
(i.e. a increase in cyprinids) has been well documented from temperate lakes, where the
development has been related to competitive advantages for cyprinids in foraging in turbid and
structurally less complex (i.e. lack of submerged macrophytes) habitats (Diehl 1988, Persson et al.
1991), which prevail in eutrophicated waters. Cyprinids are able to forage effectively in low light
intensities, whereas visual hunters, e.g. perch, depend on sufficient light conditions (Diehl 1988).
Roach is a generalist feeder and an opportunist, flexibly switching between zooplankton and benthic
invertebrates and also capable of utilising plant material (e.g. Vinni et al. 2000). Adult bream are
benthivorous using their large mouth protrusions to “vacuum” the sediment for invertebrates,
making them efficient foragers on bare sediments and in sparse vegetation, not dependent on vision
(e.g. Diehl 1988). White bream is a close relative to bream, but not as strictly dependent on the
benthic foraging (e.g. Brabrand 1984). Increased cyprinid populations will also compete for food
with predatory fish during the juvenile zooplanktivorous (and benthivorous) phase of these species
(e.g. Persson 1983). This competition can reduce the growth and survival of young piscivores,
leading to a recruitment bottleneck and an out-competition of the future predators for cyprinids
(Persson & Greenberg 1990). The mechanisms behind the cyprinidification in the coastal areas
could be assumed to be similar to those in lakes, as the fish assemblages in the inshore and
archipelago areas mainly consist of freshwaters species (Lappalainen 2002). However, the
advantages related to the effective feeding abilities might not be the single most important reason
for the increase of cyprinids in coastal waters. The ongoing expansion of reed-covered shores in the
coastal areas, coupled to eutrophication (Roosaluste 2007), has increased the availability of suitable
breeding habitats for cyprinids (Kallasvuo 2010). The reproduction of roach, white bream and
bream has shown to be sensitive to salinity, which makes the reproduction of these species strongly
dependent on sheltered, low-saline (preferably < 4 psu), reed-covered shores of the innermost bayareas (Kallasvuo et al. 2011). Juvenile cyprinids are also confined to these types of areas (Snickars
et al. 2009) and have been shown to benefit from eutrophication (Sandström & Karås 2002). The
improved reproductive and juvenile success has led to a dispersal of adult cyprinid fish from
inshore areas to the middle and outer archipelago (Lappalainen et al. 2001). Adult cyprinids can
thrive freely especially in the outer areas in the absence of large predatory fish like pike
2
(Esox lucius) (see Lehtonen et al. 2009), which can further affect the ecosystem in these areas, e.g.
through the effective roach predation on the blue mussel (Mytilus edulis) populations (e.g.
Lappalainen et al. 2005). The observed increase of cyprinids in the coastal waters is mainly
attributed to eutrophication, but other factors such as favourable changes in water temperature and
salinity, or targeted fishing pressure on predatory fish species (and a concurrent low fishing
pressure on cyprinids), may also have strengthened the ongoing development (Lappalainen 2002,
Ådjers et al. 2006). Eutrophication has changed the fish community towards a cyprinid domination
and the cyprinid-dominated fish community may in turn maintain, or even increase, the
eutrophication problems through internal feedback processes (e.g. Horppila & Kairesalo 1990),
which in lakes have been seen even as ecosystem shifts from a less eutrofied clear-water state
dominated by predatory fish to a eutrofied, turbid, cyprinid-dominated state (Scheffer et al. 1993).
In order to comprehend and to take successful actions against coastal eutrophication and its effects
on the ecosystem, understanding the mechanisms behind cyprinidification, including the biology
and ecology of the cyprinid species in the coastal waters, would be of decisive importance.
2.2 Biomanipulation
2.2.1 Theory
Ecosystems can exist in different stable states or regimes, maintained by internal feedback
processes (Scheffer et al. 2001, Scheffer & Carpenter 2003). Gradual changes in conditions, due to
e.g. human-induced eutrophication or continuous fishing pressure, may alter the internal feedback
processes and consequently cause ecosystems to change from one alternative stable state to another
(i.e. dynamic regime shifts). Generally such changes are often undesirable, e.g. due to losses in
production and conservation values, and have thus made large-scale ecosystem restoration
increasingly urgent (Hobbs & Norton 1996). Ecological restoration is the process of improving
ecosystem recovery by means of artificial manipulations (Dobson et al. 1997) and involves forcing
an ecosystem back to a desired regime (Palik et al. 2000). Founded on ecological theory (Hairston
et al. 1960, Palmer et al. 1997), manipulations have proven to be an effective tool in restoring
degraded terrestrial, limnic and marine coastal ecosystems (e.g. Shapiro and Wright 1984, Hawkins
et al. 1999, Gomez-Aparicio et al. 2004).
Biomanipulation is a restoration method originally defined as a food web modification in order to
improve the lake water quality (Shapiro et al. 1975), but has as an expression recently also
expanded into the context of restoration of marine fish stocks (see Lindegren et al. 2010). The
continued development of the biomanipulation concept is firmly connected with the trophic cascade
hypothesis (Carpenter et al. 1985), the top-down : bottom-up theory (McQueen et al. 1986), and in
the holistic food-web model (Persson et al. 1988). Biomanipulation is typically conducted by mass
removal of dominating planktivorous and benthivorous fish (e.g. Drenner & Hambright 1999) or by
addition of piscivorous fish (e.g. Shapiro and Wright 1984). According to the trophic cascade
hypothesis (Carpenter et al. 1985), effects at a higher trophic level cascade downwards. Thus
theoretically, a reduction of zooplanktivory, either through manual removal or through increased
predation, is followed by an increase in the abundance and the size of zooplankton, which results in
increased grazing pressure on phytoplankton and ultimately in improved water quality (e.g. Mehner
et al. 2002). According to the general view, biomanipulation has a much higher success rate in
shallow than in stratified deep lakes due to the advantageous potential of macrophytes to
(re)colonise large bottom areas, which might promote a shift to an alternative clear-water state
through e.g. effective competition of nutrients (McQueen 1998, Scheffer 1998). However,
successful biomanipulations have been conducted also in deep lakes with sparse vegetation
(Horppila et al. 1998, Olin et al. 2006). Contrary to the traditional view, biomanipulation can work
3
in the bottom-up direction as well, in addition to the top-down mechanism. Zooplanktivore
reduction can affect the water quality, via the decrease of phytoplankton, through reduced nutrient
recirculation from excretion and re-suspension (Havens 1991, Horppila et al. 1998, but see Attayde
& Hansson, 2001). However, there are still uncertainties and doubts about the real relative role of
the changed nutrient recirculation by the zooplanktivores (Tarvainen et al. 2002). On the contrary,
benthivorous and omnivorous fish species stir up the bottom sediments effectively during feeding
and thus increase re-suspension and internal nutrient loading (Breukelaar et al. 1994, Søndergaard
et al. 2003). Hence, it has been suggested that the reduction of benthivorous fish determines the
outcome of biomanipulation in shallow lakes even more strongly than the removal of
zooplanktivorous fish (Lammens et al. 1990, Drenner & Hambright 1999). Prerequisites for a
successful biomanipulation are, according to Hansson et al. (1998), a significantly large (> 75 %)
and rapid (1–3 years) fish reduction, targeted efforts on planktivores and benthivores, effective
reduction of the recruitment of young-of-the-year fish, improved conditions for establishment of
macrophytes, and importantly a bearable external load of nutrients. Zooplanktivore and benthivore
cyprinids are generally the most abundant fish groups in eutrophicated north temperate lakes
(Persson et al. 1991, Jeppesen et al. 2000, Rask et al. 2002). While percids are less harmful than
cyprinids in zooplanktivory and nutrient cycling (Persson 1987, Andersson et al. 1988), the
practical target of biomanipulation is usually to reduce the cyprinid density and to increase the
proportion of percids and other piscivores (Olin 2005). Hence, biomanipulation projects have
frequently been carried through, by the means of extensive cyprinid reduction, in order to improve
the water quality in lakes (e.g. Riemann et al. 1990, Horppila et al. 1998, Bergman et al. 1999, Olin
et al. 2006).
Many restoration projects have been carried out since the 1980’s, and the varying results of these
have been repeatedly reported and reviewed (e.g. Benndorf 1990, Jeppesen et al. 1990, Hansson et
al. 1998, Meijer et al. 1999, Søndergaard et al. 2000, 2007, Gulati & Van Donk 2002). As reviewed
by Mehner et al. (2002), about 60 % of the biomanipulation attempts have succeeded. Many
zooplanktivore or benthivore reduction projects have also been conducted in Finland, with varying
results (Horppila et al. 1998, Kairesalo et al. 1999, Sarvala et al. 2000a, 2000b, Leppä et al. 2003,
Rask et al. 2003, Olin et al. 2006, Ventelä et al. 2007). In the Baltic Sea, biomanipulation has not
been an employed method for restoration, probably because of the difficulties in controlling
ecological processes on vast spatial scales (Lindegren et al. 2010). Recently some projects have
though been launched (Anon. 2011a, 2011b, 2011c, 2011d). Due to the lack of empirical
experiences of fish reduction (if not the unintentional over-fishing of cod and the consequent
ecosystem effects (e.g. Österblom et al. 2007) are counted), no literature exists concerning effects of
fish reduction in the Baltic Sea, except of a few project reports (Anon. 2010, Setälä 2011).
2.2.2 The Pikkala Bay cyprinid reduction fishery
Since the beginning of the 1990’s fisherman Klaus Berglund has fished in the Pikkala Bay at the
south coast of Finland and is at present the only actively fishing professional fisherman in the area.
According to his experiences, the unusable share of cyprinids (especially bream) in the net fishing
catches grew, during the last decades, to a limit where the fishing was not profitable anymore (pers.
comm.). Over 90 % of the total catch could consist of non-target cyprinid species. In 2008,
Berglund had the idea of replacing the inshore net fishing with fish traps, which was followed by a
successful pilot project of developing seal-safe fish traps for inshore fisheries. The specialised fish
traps gave good catches of pikeperch and perch, but still also great amounts of bream (maximum
catch in a single fish trap: > 10 tons). This eventually led to the targeted reduction fishery of
cyprinids, connected to and subsidised by a pilot project in the regime of RKTL (Finnish Game and
Fisheries Research Institute). This RKTL pilot project (in Finnish: “Piloottihanke vajaasti
4
hyödynnetyn kalan käytön edistämiseksi”) has been carried out in 2010–2011, in order to
investigate the prospects of enhancing the utilisation of cyprinid fish through producing either
human or animal food and through the production of biofuel (Setälä 2011).The general background
target for the RKTL project was to create prerequisites for a large-scale nutrient removal from the
eutrophicated coastal waters. Some useful investments have been carried out at Berglund’s fishing
harbour in Kopparnäs (Inkoo) in order to improve the facilities for handling the increased landings
of cyprinids. One such investment is the fish processing container for the production of acidpreserved fish mass, targeted to various end-uses, for the share of the catch that has not been sold as
food. A growing share of the cyprinid catch is, however, being sold for export to Russia and the
Baltic countries.
The cyprinid reduction in Pikkala Bay started in 2009 and has been carried out first with only two
fish traps but later with up to 9 traps in 2010, situated at different spots around the bay. The total
amount of cyprinids reduced by the end of 2010 was c. 160 tons (2009: c. 45 tons, 2010: c. 117
tons), comprising over 83 % of the total commercial catch (Figure 1). The cyprinid catches have
increased considerably compared to the time before 2009, when the annual catches of cyprinids
were approximately less than 5 tons (no reliable statistics of the cyprinid catch from this time exists
though). The reduction catch with fish traps has been clearly dominated by bream (2010: > 84 % of
the commercial catch), but has also included other commercial species, of which pikeperch has been
the most important (Table 1). Other cyprinids that have been caught are e.g. roach, white bream,
vimba bream (Vimba vimba) and ide (Leuciscus idus), many of which not have been recorded in the
commercial catch statistics. No statistics on size distribution of the bream catch are unfortunately
yet available, but the breams have generally been rather small, in average about 600 g, in 2010.
total
perch
fishing net (10 pcs.)
bream
pike
fish trap
roach
pikeperch
140000
2000
1800
120000
1600
1400
1200
80000
1000
60000
800
Effort unit
Catch (kg)
100000
600
40000
400
20000
200
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
0
1992
0
Year
Figure 1. The development of the fishing effort and the commercial catch of fisherman Klaus Berglund in
Pikkala Bay from 1992 to 2010. The unit of the fishing effort is one fishing day with one fish trap or with ten
fishing nets, and the annual effort was calculated based on the monthly average of fishing days with a certain
type of gear.
5
Table 1. The commercial catch of different species in Pikkala Bay during the cyprinid reduction fishery in 2009 and
2010, given as the percentual proportions of the total catch
Proportion of the total catch (%)
Year
Bream
Roach
Ide
Tench
2009
71.71
6.21
0.51
0.21
Pikeperch
12.34
2010
84.34
3.74
0.23
0.00
5.21
Perch
Pike
3.78
2.45
Whitefish
0.64
2.34
2.85
0.21
0.14
Rainbow
Burbot
trout
0.13
0.79
0.00
0.00
Trout
0.28
Eel
Cod
Flounder
0.93
0.12
0.04
0.75
0.05
0.00
2.2.3 Possible environmental effects of coastal cyprinid reduction
A strongly increased fishing pressure might reduce the cyprinid fish stocks. This possible reduction
can have different environmental impacts, directly via top-down and bottom-up mechanisms or
more indirectly though changes in competition and predation. The impacts can consist of biotic
changes at different trophic levels from predatory fish to primary producers, and of abiotic changes,
e.g. regarding nutrient concentrations. Many of the effects of biomanipulation and cyprinid
reduction are intentional and desired, but these primary changes can further cause even unexpected
impacts e.g. via biotic interactions. A multitude of studies exists from biomanipulated lakes, serving
a solid background of experiences concerning effects of cyprinid reduction. However, closed lake
systems might differ greatly from the open coastal areas, and thus the potential effects of coastal
cyprinid reduction are not necessarily similar to those from lakes and hence highly speculative.
The reduction fishery of bream in Pikkala Bay should naturally, as a primary effect, reduce the adult
bream stock. For the bream population this would imply a release of intraspecific competition,
which could increase the potential for a higher growth rate and production (Persson & Hansson
1999). The reduction of adult bream could further affect positively other benthivorous fish species,
such as perch and ruffe through reduced competition and improved feeding conditions (e.g. Olin
2005). As bream and other cyprinids have a great reproductive potential (Backiel & Zawisza 1968,
Nielsen & Svedberg 2006), a reduction of the adult breeding stock will necessarily not reduce the
fry production of the target species. A reduction of large cyprinids may also lead to a general
explosion of young-of-the-year fish, often mostly cyprinids, due to the successive release of
competition (Bergman et al. 1999, Olin et al. 2006), which could in this case theoretically lead to an
unwanted increase of roach for example. The increased proportion of piscivores could eventually,
however, start to regulate the bream and other cyprinid populations through improved predation
control due to the smaller average size of the cyprinid prey (Lammens 1999). In the long-term the
fish community could shift back towards a structure dominated by predatory fish and by species
favoured of lesser eutrophication in general, as a possible response to normalised trophic
relationships and to a generally improved state of water quality.
Soft-bottom zoobenthos might be improved (i.e. change towards a more diverse and abundant
benthic community) through decreased predation and disturbance by bream (Svensson et al. 1999,
Leppä et al. 2003). This could, in addition to the positive effects regarding the improved food
availability for other benthivorous fish, further affect the important bioturbation functions of the
benthic fauna and consequently improve sediment oxygen conditions and nutrient retention (see
Middelburg & Levin 2009). The possible effects of a bream reduction on hard-bottom benthic
animals is not clear, as it is unknown to what extent bream might utilise these kind of habitats for
feeding. Roach as a close relative to bream has been shown to effectively prey on blue mussels in
hard bottom areas in coastal waters (Lappalainen et al. 2004, 2005, Westerbom et al. 2006). If
bream utilises a same kind of ability, a reduction of bream should favour blue mussels through the
decreased predation (if not the reduced predation by bream is then compensated with an increased
predation by some other species, e.g. roach). A potential large-scale improvement of blue mussel
6
populations could then further enhance e.g. the declined common eider (Somateria mollissima, an
obligate blue mussel predator) populations and improve the water quality through increased filter
feeding by blue mussels.
The bream reduction could potentially lead to a final decrease of zooplanktivory, as an direct (but
unlike) effect of reduced fry production or as a secondary effect of a shift to predator domination,
which then could improve the water quality through the cascading top-down effects on
phytoplankton (see e.g. Riemann et al. 1990, Olin et al. 2006). A more likely way for the bream
reduction to improve the water quality, is through the decreased recirculation of nutrients from the
bottom to the water column by the means of sediment re-suspension and excretion (see e.g.
Horppila et al. 1998). A reduction of bream removes naturally also nutrients bound to the fish, but
the effects of this in relation to e.g. the external nutrient load are unclear.
3 Features of the study
3.1 The objective
The main objective of this investigation was to look for possible environmental changes in the study
area of Pikkala Bay, based on available data, and further to evaluate the changes and identify
potential ecological effects from the recent cyprinid reduction in the area. The work was divided
into two subparts: first the search and collection of data, and then data analysis for potential effects.
The purpose of the first part was simply to search for all possible existing and available
environmental data from the Pikkala Bay area, and to evaluate the quality and usefulness of the data
for studying effects of the cyprinid reduction. The second aim was then to analyse these data for
possible changes. When any changes were found, their relation to the reduction fishery was
examined. The study was focused on three main sections, i.e. fish, benthic fauna, and water quality,
where potential effects of the cyprinid reduction were most likely to be found.
3.2 The study area – Pikkala Bay
The Pikkala Bay is situated on the south coast of Finland, to the west from Helsinki, in western
Uusimaa region, in the sea areas of Siuntio and Kirkkonummi (Figure 2). The bay is surrounded by
the mainland from west, north and east, and is connected to the open sea in south. The area is not
clearly characterised by the typical zonation in inner, middle and outer archipelago (see Häyrén
1900), even if features of such zones are present in a geographically smaller scale. Pikkala Bay has
a surface area of c. 25 km2 (depending on the definition of the bay), including the islands of
Klobben and Svinö as well as some smaller islets and skerries. The littoral types present in the bay
are sand, gravel and stone, but also reed-covered muddy soft bottom areas are found in the inner
parts as well as deep rocky shores in the eastern parts. The depth of the bay is mainly around 5–7 m,
but shallower (0–5 m) parts are found in the innermost areas and nearer to the shores in the northern
and western parts. The eastern and southeast parts of the bay are generally deeper (7–10 m),
including a > 9 m deep vessel rout to the Kantvik harbour. The depth still increases southwards
against the open sea steadily without any clear thresholds.
7
Figure 2. The study area of Pikkala Bay.
The hydrography of the bay is influenced by the freshwater flow from the Pikkala River (Siuntio
River) and by the occasional deepwater upwelling from the open sea. Therefore the water salinity in
the bay can fluctuate between c. 4 and 6 psu in the central parts, declining to near freshwater at the
entrance of Pikkala River and increasing to > 6 psu closer to the open sea. The oxygen
concentration in the near-bottom water in the Pikkala Bay is generally good all the year round, even
if some temperature stratification may occur in the deeper parts in late summer. The entire Pikkala
Bay can be classified as an eutrophicated area, based on both high surface water (0–3 m and 0–2 m)
nutrient and chl-a (chlorophyll-a) concentrations (total-P c. 30–50 µg/l, total-N c. 380–500 µg/l and
chl-a c. 9–21 µg/l: average June–September values in 2009 and 2010) during the growth season
(Suonpää & Mettinen 2010, Suonpää 2011). Pikkala Bay is affected by loadings from industries,
municipal wastewater and the runoff especially from the Pikkala River. The point sources of
effluents (nutrients, organic matter, etc.) to the Pikkala Bay are: Nordic Aluminium Plc and
Prysmian Cables and Systems Oy, Upinniemi garrision (Finnish defence administration), Pikkala
central water purification plant (municipality of Siuntio), and Kantvik water purification plant
(Suomen Sokeri Oy) (Suonpää 2011). The central water purification plant in Pikkala was taken in
use in 1996 and it replaced the former sewage treatment plant located along the Siuntio River. The
former water purification plant of Kirkkonummi was closed in 2005, which implied a clear decrease
of point source loading to the bay. Despite the possible local influence of the point sources, the
8
clear majority of the total external loading to the Pikkala Bay originates from the Pikkala River,
consisting mainly of diffuse runoff caused by agriculture and forestry (Mettinen 2009a). The
riverine nutrient load (both P and N) has comprised c. 90–99 % of the total external loadings to
Pikkala Bay every year from 2005 to 2010 (Suonpää & Mettinen 2010, Suonpää 2011). The river
enters Pikkala Bay in the northwest with the runoff from a c. 483 km2 catchment area, discharging
an average (for years 2003–2010) annual nutrient load of c. 14 tons P and 250 tons N (Mettinen
2009b, Valjus 2011). Decisive for the relevance of the riverine load to the nutrient state in Pikkala
Bay, is the fact that the nutrient concentrations are clearly higher in the river water than in the bay
(see Suonpää & Mettinen 2010, Suonpää 2011).
In the northern and the central parts of the bay, two areas around groups of small islands have been
protected as natural reserves, and a fish route, for breeding migrations of the endangered
anadromous sea trout (Salmo trutta) from the open sea throughout the bay towards the river
entrance, has also been protected from fishing with passive gears. Details and more precise
descriptions of the characteristics of the Pikkala Bay are available in the reports for the obligatory
monitoring program in the area, provided by LUVY ry (e.g. Mettinen 2009a, Suonpää & Mettinen
2010, Suonpää 2011).
3.3 Materials and methods
3.3.1 Data search
Information and environmental data concerning the Pikkala Bay area have been searched for widely
in different sources and the aim has been to comprehensively find all the surveys, reports and
monitoring results available. Databases, libraries and different archives were the main potential
sources of information. Searches were conducted e.g. in the union catalogue of Finnish university
libraries, “LINDA” (http://linda.linneanet.fi), in the library and information service of the Finnish
Environment Institute, “SYKE” (http://kirjasto.ymparisto.fi/eng), and as Google-searches from the
internet. Additionally some information and data have been searched through personal contacts to
different institutes, bureaus, agencies and consulting firms as well as to researchers and other
persons with relevant knowledge about the Pikkala Bay area. The main effort in the search for data
has been targeted to the two most probable sources of information: the environmental database
“OIVA” (http://wwwp2.ymparisto.fi/scripts/oiva.asp) maintained by the Finnish environmental
administration, and the reports of obligatory monitoring programs published by environmental
consulting firms.
3.3.2 Test-fishing 2011
Since the available material concerning fish and the fish community in Pikkala Bay were found to
be relatively poor, some resources of the project were able to be allocated for conducting an intense
test-fishing survey. The purpose of the test fishing was to compensate for the lack of recent data on
the fish community, providing a fresh picture of the current state, making comparisons with older
data possible, and composing a solid ground for future studies.
The test fishing was conducted during four nights in autumn 2011 (5.9–9.9.2011). Nordic coastal
multi-mesh gillnets (also named coastal Nordic nets or COASTAL nets) were used for sampling the
fish community. This multi-mesh gillnet type is 45 m long, 1.8 m deep, and is composed of nine
(5 m long) panels with different mesh sizes (10 mm, 12 mm, 15 mm, 19 mm, 24 mm, 30 mm,
38 mm, 48 mm and 60 mm, knot-to-knot). The sampling strategy was, with some modification,
based on depth-stratified random sampling, developed for coastal fish monitoring in the Baltic Sea
(Appelberg et al. 2003). However, due to many restricting factors (e.g. near-shore settlements,
9
harbours, boat routes, stationary professional fishing gears, and fishing limitations due to
prohibitions or the confined areas encompassed in the test-fishing permit), some net locations had to
be subjectively chosen. The fishing was conducted in four different subareas (Figure 2, Appendix
A), with the fishing effort of six net-nights per area, giving a total effort of 24 net-nights. All nets
were set as bottom nets and the direction of the nets was initially randomised but in most cases later
determined by the prevailing wind direction, water depth and other practical factors. The nets were
set in the evening, to fish over the night (12–14 hrs), and were lifted the following morning. The
catch was recorded separately for every net and mesh size. All caught fish were determined to the
species level. The total length (1 mm accuracy) and weight (0.1 g accuracy) of every individual fish
was measured and recorded. The principal methodologies used in this survey were adopted from
different test-fishing and fish monitoring advices (Kurkilahti & Rask 1999, Appelberg et al. 2003,
Anon. 2008).
Although the multi-mesh gillnet fishing is selective sampling method, suffering from different
problems (e.g. uneven catchability due to fish size and morphology, passiveness of the gear, net
saturation and problems linked to varying fish behaviour), it can be used as a robust, practical and
cost effective method for sampling the fish community (Kurkilahti 1999, Appelberg et al. 2003) and
suits also to roughly follow the responses in the fish community after biomanipulation attempts
(Olin 2005).
3.3.3 Numerical analyses
Statistical tests were performed in order to analyse data for possible changes or trends. Parametric
tests were generally preferred and all data were tested for the terms of normal distribution
(Kolomogorov-Smirnov test) and for the homogenity of variances (Levene’s test) before conducting
the tests. If the terms for parametric tests were not fulfilled, corresponding non-parametric test were
used instead, unless the problems could be solved with data transformations (ln(x+1)). Parametric
Independent samples t-test or One-way ANOVA (analysis of variance) with Bonferroni-corrected
post hoc test was used for testing differences between groups (e.g. Dytham 2003). The
corresponding non-parametric tests used were the Mann-Whitney U-test and the Kruskal-Wallis
test. To analyse trends over time, parametric linear regression was used. The significance level of
0.05 was generally applied throughout the tests. The statistical software package PASW Statistics
18.0 was used for the analyses.
4 Results and discussion
4.1 Existing environmental data
The search for environmental data and other relevant information about or related to the Pikkala
Bay area resulted in a considerable amount of material, consisting of both literature, database
findings, statistics and documents from the 1960’s to present. Earlier material was not found and is
unlikely to exist, while the area belonged to the Soviet Union from 1944 to 1956 as consequence of
the terms of peace after the war.
The found literature numbered c. 100 items in all, of which 58 pcs. were accessed. The literature
consisted mainly of so called grey literature including different kinds of reports and surveys. The
most abundant type of literature was the regular reports of the obligatory monitoring programs,
which the industries and the sewage water treatment plants that affect the area are bound to produce
10
(usually through an environmental consulting firm), as dictated in the terms of the environmental
permissions for these activities. Obligatory monitoring reports for the Pikkala Bay area have been
produced since the 1970’s and they include information about water quality, primary production,
benthic fauna, sediments, fish, fishery and the environmental quality in general. A list of all the
found literature is presented as Appendix B in this report.
The search in the environmental database OIVA (during the period 1.2.–20.5.2011) gave many hits.
The data consisted of sampling results of monitoring and other studies concerning water quality and
benthos from year 1962 onwards (OIVA 2011). The main producers of the data have been the
former Uusimaa Regional Environmental Centre and now the ELY-centre of Uusimaa,
environmental consulting agencies (e.g. LUVY ry and Oy Vesi-Hydro Ab) and the former Finnish
Institute of Marine Research (FIMR). Some of the results found in the database were the same as
found in the printed reports.
4.1.1 Fish data
Data concerning fish have been found in obligatory monitoring reports, in some other reports, as
well as in an academic thesis (see Appendix B). Additionally commercial catch statistics and fish
stocking figures have been obtained. The obligatory monitoring reports included results from gillnet
test fishing, fishing inquiries and the bookkeeping of catches of some private household fishermen.
Gillnet test-fishing has been conducted in 1982, 1987, 1991, 1995, 1996 and 2000 (Sauvonsaari
1982, 1988, Sauvonsaari & Vaajakorpi 1991, 1996, 2001, Ranta 1996, Kukkonen et al. 2002). The
fishing was carried out once (i.e. during one night) in the spring and once in the autumn, using
gillnet series consisting of eight nets with different mesh sizes (see references for more detailed
methodologies). Data from the test-fishing surveys consisted of abundance and biomass results of
each species separately for the different mesh-sizes. There are some problems regarding the
usefulness of the test-fishing results. Firstly, some of the test-fishing occasions have consisted of a
fairly small fishing effort (only one net series) and have lacked replication, and in addition the
location of the nets has been (intentionally) close to a wastewater discharge, probably influencing
the dynamics in the fish assemblage (Ranta 1996, Kukkonen et al. 2002). Secondly, even if the
results from the other test-fishing occasions could be more usable, as the monitoring has reached
over a longer period of time and while the total fishing effort has been bigger (one net series in 6–7
locations), problems still occur due to the lack of replication (a pooled total catch is given and
separate raw data for the different locations do not exist anymore (pers. comm. Otso Lintinen,
Ramboll Finland Oy)), and because of the placing of the net sites in the vicinity of industrial
discharges or partly outside the bay area as defined in this study (Sauvonsaari 1982, 1988,
Sauvonsaari & Vaajakorpi 1991, 1996, 2001). The lack of available replicates disables the
performance of quantitative statistical analyses in order to find differences in fish populations
between years.
Fishing inquires have been sent every 4–5 years since 1990 to the private people who fish in the
area (members of fishing clubs, water owners, etc.), the last results being from year 2007
(Sauvonsaari & Vaajakorpi 1991, 1996, 2001, Wikström & Kamppi 2004, Valjus 2008). The
bookkeeping fishery has been continuous since 2003, but the last available results are from 2007
(Wikström & Kamppi 2004, Suhonen 2007, Valjus 2008). Information from bream tagging studies
for investigating migration patterns in bream in Pikkala Bay are found in an early report and in a
MSc thesis (Dahlström et al. 1968, Hildén 1986). The official catch statistics for 1992–2010 of
fisherman K. Berglund have been obtained from himself, and have been important and useful.
11
Figures of the fish stocking in Pikkala Bay have been obtained from the Fisheries Services group (in
Finnish: “Kalatalouspalvelut-ryhmä”) at the ELY-centre of Uusimaa.
4.1.2 Benthos data
Data concerning benthic invertebrate macrofauna have been found mainly in the OIVA database
and in obligatory monitoring reports, and additionally in one academic MSc thesis (see Appendix
B), all consisting of results from bottom sampling with grab-samplers (for general methodology see
e.g. Parkkonen 1978, Mettinen 2002a, 2010). The results in the OIVA database originate mostly
from different national or regional monitoring programs performed by the environmental
authorities, or from the obligatory monitoring programs for Pikkala Bay carried through by
environmental consulting firms.
Results from 60 separate sampling sites with a total of 148 sampling occasions in Pikkala Bay from
the period 1969–2007, had been recorded in the database at the time of the search (OIVA 2011). Of
these 60 sites, 42 were soft-bottom locations (essential for the applicability of the grab-sampling
method). Many of the results registered in OIVA are also found in the obligatory monitoring
reports. Results that exist in these reports and have been accessed, originate from samplings
conducted every 3–5 years from 1982 to 2007 (Sauvonsaari 1982, 1988, Sauvonsaari & Vaajakorpi
1991, 1996, 2001, Mettinen 1997, 2002a, 2010, Wikström & Kamppi 2004). No yearly monitoring
or any longer time-series do exist. Some of the sampling sites did, however, have results from years
1978, 1982, 1987, 1991, 1995, 2000, 2003 and 2007. Sampling has been conducted at bottoms with
different depths (2–13 m) and sampling sites have been situated all around the bay area. For many
sites earlier data exist for both spring and autumn, but since 2003 sampling has been done solely in
autumn. The data consist of abundance and biomass results separately for different benthic species.
Despite the comparatively large amount of available benthos data from Pikkala Bay, there are some
problems concerning the applicability of these results due to inconsistency in sampling
methodologies, replication issues and due to the location of sampling sites. The majority of the
samples have been taken with an Ekman sampler, but some of the earlier samples have been taken
with a larger van Veen sampler. Even if the results are calculated per unit area, a greater sample
volume (or area) increases the possibility to encounter more species. The methodologies vary also
regarding the sieve sizes. Mesh diameters of 1 mm, 0.6 mm and 0.5 mm have been used, which is a
factor possibly affecting the results (Aarnio et al. 2011a). Most of the data before 2003 include no
replicate samples for each sample site, and consists of either single sample results or results from
three (or more) pooled grab-samples (Sauvonsaari 1982, 1988, Sauvonsaari & Vaajakorpi 1991,
1996, 2001, OIVA 2011). The only replicated biomass results are from 2003 (Wikström & Kamppi
2004). The lack of replication hinders the performance of quantitative statistical analyses for finding
differences between years. A so called single sample design (i.e. using non-replicated samples from
several sites in an area) could perhaps be used in the analyses (Aarnio et al. 2011b), but the
locations of many of the sample sites near the wastewater discharges preclude this alternative as the
sites have been unevenly disturbed. The most suitable data for the purposes of this study were found
from the six, still active obligatory monitoring transects (named “Pe1–Pe6”), of which five are
situated in the bay and one outside as a reference area (Sauvonsaari 1982, 1988, Sauvonsaari &
Vaajakorpi 1991, 1996, 2001, Mettinen 1997, 2002a, 2010, Wikström & Kamppi 2004, OIVA
2011). All the samples from sites along these lines have been sieved either through 0.5 or 0.6 mm
meshes. The most results and the longest time series are also found from sites at these sampling
transects. Many of these sites as well are situated close to point load sources, intentionally in order
to monitor the local effects of the discharges, thus being poorly suitable for revealing more general
changes in the benthic faunal community. Three sites at different depths (2 m, 5 m and 6 m) along
12
the monitoring transect Pe1 have abundance results for replicate samples (3 or 5 replicates) from
autumn 1996, 2000, 2003 and 2007. The results of the site “Pe1_6 m” could additionally be filled
with the pooled, non-replicate results from two nearby sites at similar depth from the year 1969.
The other monitoring transects in the bay (Pe2–Pe5) have non-replicate data from at least 1987,
1991, 1995 and 2000 as well as data with five replicates from 2003 and 2007.
At present the zoobenthos sampling for the obligatory monitoring program is carried out in autumn
every fourth year at fixed sites along the monitoring transects. The sampling is conducted by LUVY
ry as a consulting assignment. The last sampling was made in autumn 2011, but the results became
unfortunately not available to this report.
4.1.3 Water quality data
Data concerning water quality in Pikkala Bay have been found in the OIVA database, in obligatory
monitoring reports, in other reports and in one scientific publication (see Appendix B). The data
consist of water sampling results on different variables, discharge figures from point sources, and
information about riverine loading. The OIVA database comprises most of the existing water
sampling results from the area. These data originate mainly from different national or regional
monitoring programs performed by the environmental authorities, or from the obligatory monitoring
programs for Pikkala Bay carried through by environmental consulting firms. Hence, the majority
of the water sampling results presented in the literature overlap with the material in the database.
The water sampling results consisted of different physical and chemical variables as well as
variables for eutrophication monitoring.
At the time of the database search, water sampling results were found for 23 sampling sites and
2786 sampling occasions from the period 1962–2010 (OIVA 2011). Nine water sampling sites
covered the time before and after the onset of the cyprinid reduction and are still actively monitored
by LUVY ry and Uusimaa ELY-centre. Eight of these sites had the longest time series with yearly
results at least since 1973. These results have been obtained from samples taken at different
occasions around the year but covers most consistently the summer months. The applicability of the
water sampling results might be affected by problems related to the locations of the sampling sites.
Many of the sites have intentionally been situated near discharge sources in order to provide
information about the effects of the pollution on the water quality. Hence, changes in water quality
variables at such sites could possibly reflect only the variations in the local pollution load, instead
of revealing the general state and trends, which are important for studying potential bay-scale
effects of the cyprinid reduction. The sampling site “UUS-6 Pikkalanlahti 20” is situated quite in
the middle of the bay at a depth of c. 10 m and appears to be suitable and usable for this study, as it
is not located close to any discharge sources (Figure 2). The water quality variables searched for
and obtained at this site were: temperature, salinity, pH, oxygen concentration and saturation
(O-conc., O-%), turbidity, total nutrient concentration for phosphorous and nitrogen (tot-P and totN), and chlorophyll-a (chl-a) concentration. This sampling site had results from 1962 to 2010 and
most of the variables have been measured several times every year (with some gaps).
Point source discharge data as well as water quality data recorded in OIVA could be found in many
obligatory monitoring reports since the 1970’s. The latest figures were found in Mettinen 2002b,
2003a, 2004, 2005a, 2007a, 2008a, 2009a, Holmberg & Mettinen 2006, Suonpää & Mettinen 2010,
Suonpää 2011. Riverine loading data have also been found in obligatory monitoring reports
concerning the Siuntio River, since the 1990’s. The latest data could be found in Ranta & Jokinen
2000, Mettinen & Jokinen 2001, Mettinen 2002c, 2003b, 2005b, 2006, 2007b, 2008b, 2009b,
Valjus 2010, 2011.
13
4.1.4 Other environmental data
In addition to the fish, benthos and water quality data, some other data on the water environment in
Pikkala Bay have also been found. Phytoplankton sampling has been included in the obligatory
monitoring program and the results were found in the reports (Mettinen 2003a, 2004, 2007a, 2008a,
2010, Holmberg & Mettinen 2006). Data regarding the macrophyte vegetation have additionally
been found in one report (Luttinen 1989). No data on the zooplankton community in the Pikkala
Bay have been found.
4.2 Test-fishing 2011 – the structure of the fish community
The total catch from the test-fishing in 2011 comprised 2736 fish with a weigh of c. 167.7 kg (Table
2). The average total catch for one COASTAL-net and night (CPUE) was c. 114 (± SD 37) ind. and
c. 6989 (± SD 2444) g. In the test-fishing a total of 14 species were caught, of which 9 were
freshwater species. Marine species occurred in considerably low numbers. The lowest number of
species caught per net was 5 and the highest was 10, while the average number of species per net
was c. 7 (± SD 1). The catch was dominated by percids (perch, ruffe and pikeperch) and cyprinids
(roach, white bream and bream) and perch, ruffe, roach and white bream were caught in every
single net. The greatest proportion of the catch consisted of perch both regarding the abundance
(c. 46 %) and biomass (c. 38 %) (Figure 3) and the CPUE values of perch were significantly higher
than those of roach (Independent samples t-test, ln-tranformed values (ln(x+1)): abundance
t(46) = 4.78, p < 0.0001; biomass t(46) = 2.39, p = 0.021), the species accounting for the next
greatest proportions of the catch. The composition of the catches from the different areas (A–D)
was roughly similar, consisting of the same dominating species (Figure 4). There were however
statistically significant differences in the CPUE values between the areas (Table 3), e.g. concerning
the total abundance and biomass (One-way ANOVA: abundance F3,20 = 3.68, p = 0.029; biomass
F3,20 = 5.18, p = 0.008). Area C, with the highest CPUE values, differed significantly from areas B
and D, which had the lowest CPUE values for abundance and biomass respectively (Bonferroni post
hoc: abundance p = 0.033; biomass p = 0.013). Some differences between areas existed also
separately for the CPUEs of different species (Table 3). The bream catch in the test-fishing
consisted of 90 individuals with a total weight of c. 21.3 kg (Table 2) and the CPUE values were
c. 3.8 (± SD 3.6) ind. and c. 502.7 (± SD 497.5) g regarding abundance and biomass respectively.
Bream constituted only a small proportion of the total catch regarding the abundance (c. 3.3 %) but
a more considerable proportion of the total biomass (c. 12.7 %). The breams ranged in size from
9.7 cm to 44.5 cm in length and 9.1 g to 1005.5 g in weight, with the average values of 25.7
(± SD 8.0) cm and 237.0 (± SD 194.0) g for length and weight respectively. Only a few small
(< 11 cm) as well as big (> 38 cm) individuals were caught during the test-fishing, while the
intermediate-sized (22–34 cm) breams dominated (Figure 5). The only potential piscivores caught
in the test-fishing were adult perch and pikeperch. The proportion of piscivores (i.e. perch > 15 cm
and pikeperch > 10 cm) was 17.9 % of the total abundance and 36.3 % of the total biomass. The
test-fishing results are given as a whole in Appendix A.
14
Table 2. The test-fishing catch from Pikkala Bay in September 2011
Species
Scientific nam
Perch
Perca fluviatilis
Number of fish
Biomass (kg)
CPUE-abu. ± SD (ind.)
CPUE-bio. ± SD (g)
1259
64.39
52.46 ± 27.37
2682.75 ± 1553.14
Roach
Ruffe
Rutilus rutilus
479
42.44
19.96 ± 14.38
1768.14 ± 1272.64
Gymnocephalus cernua
418
8.74
17.42 ± 10.54
364.25 ± 315.25
White bream
Blicca bjoerkna
272
15.94
11.33 ± 5.60
663.98 ± 498.31
Pikeperch
Sander lucioperca
118
12.06
4.92 ± 4.92
502.65 ± 497.53
Bream
Abramis brama
90
21.33
3.75 ± 3.60
888.58 ± 1017.44
Bleak
Alburnus alburnus
72
1.18
3.00 ± 7.80
48.83 ± 115.55
Sprat
Sprattus sprattus
14
0.73
0.58 ± 1.97
30.25 ± 135.35
Straightmouthed pipefish
Nerophis ophidion
4
<0.01
0.17 ± 0.64
0.09 ± 0.32
Flounder
Platichthys flesus
3
0.82
0.13 ± 0.34
34.08 ± 93.46
Herring
Clupea harengus
2
<0.01
0.08 ± 0.41
0.22 ± 1.06
Rudd
Scardinius erythrophthalmus
1
0.05
0.04 ± 0.20
2.22 ± 10.86
Vimba bream
Vimba vimba
1
0.01
0.04 ± 0.20
0.60 ± 2.92
Black goby
Gobius niger
1
<0.01
0.04 ± 0.20
0.23 ± 1.14
2734
167.7
113.92 ± 36.96
6986.86 ± 2443.83
Proportions of total catch (%)
Total
50
45
40
35
30
25
20
15
10
5
0
abundance
biomass
Species
Figure 3. The percentual proportions of different species in the testfishing catch from Pikkala Bay 2011.
The average total CPUE in Pikkala Bay regarding the abundance was quite high compared to the
results from coastal monitoring at the Finnish coast (HELCOM 2006). However, many of these
coastal monitoring sites are located in more exposed outer archipelago areas, which make the
results not entirely comparable. Compared to test-fishing results from the intermediate archipelago
zone along the Finnish coast (Lappalainen et al. 2000), the total biomass CPUE from Pikkala Bay
was still considerably high, but the results were quite similar when compared to previous studies
from nearby inner bay areas (Lappalainen & Pesonen 2000). The total species count (14) in Pikkala
was somewhat smaller than in the Finnish coastal monitoring areas in average (17) (HELCOM
2006, Ådjers 2006) and than in other test-fishing studies in Finnish coastal waters (16–20)
(Lappalainen & Pesonen, Lappalainen et al. 2000). This could be due to the smaller number of
samples in Pikkala (as the probability of catching more species grows with the sample number) or
due to the inshore location of the bay, causing a lack of some marine and some anadromous species.
The differences in the number of species in different test-fishing results can often be explained with
the varying amount of marine species as the number of freshwater species is usually quite stable
(Lappalainen et al. 2000) and similar to the results from Pikkala Bay as well. The reasons for the
observed differences in the catch between the test-fishing areas (A–D) in Pikkala Bay are not
15
investigated, but are likely linked to differences in the suitability of the areas and to the moving
patterns and routes of the fish (see e.g. Fréon & Misund 1999). The generally higher catch at site C
and the differences in its composition compared to the other sites might be a reason of the more
exposed location nearest to the entrance of the bay.
The species composition and the clear domination by the six species of the most abundant percids
and cyprinids (Figure 3) resembled strongly the results from other studies in the coastal areas
(Lappalainen & Pesonen 2000, Lappalainen et al. 2000, 2001). However, the pronounced
domination by perch was not found in all of those studies, as roach instead was dominating. In fact,
as high CPUE values for perch have not been reported from any of the monitoring sites along the
Finnish coast were the same type of Nordic COASTAL nets have been used, even if the catches
from these areas also have been strongly dominated by perch (HELCOM 2006, Ådjers et al. 2006).
Herring has been a common marine species in the coastal monitoring and in some other studies
(Lappalalainen et al. 2000, HELCOM 2006, Ådjers et al. 2006) but occurred only in a few
specimens in Pikkala. Adult herring can be found in the inner archipelago areas during the
spawning migration in spring or in autumn (Parmanne et al. 1994), while juvenile herring can be
considerably abundant in late summer (Axenrot & Hansson 2004). The low number of adult herring
in Pikkala Bay can be due to the lack of any spawning migration at the time of the test-fishing, even
if herring spawning is known to occur in the area (e.g. Valjus 2008). Juvenile herring, as well as
other small juvenile fish or small sized littoral species, cannot be caught with the COASTAL type
of multi-mesh gillnets because of the lack of sufficiently small meshes (see Kurkilahti 1999), and
thus remains outside of the sampling range of this methodology. The methodology is suitable for
sampling fish generally from their second summer onwards (Appelberg et al. 2003) and is focused
on sampling foremost the adult fish community. In order to study the juvenile fish community, e.g.
for possible effects from cyprinid reduction, other methods such as echo-sounding, trawling or
seining have to be employed.
The bream catch in Pikkala was quite high compared to other studies at the Finnish coast
(Lappalainen et al. 2000, 2001, HELCOM 2006, Ådjers et al. 2006) and the biomass CPUE values
resembled the corresponding values from a eutrophicated inner bay in the Helsinki area (cf. 889 g
and 615 g) (Lappalainen & Pesonen 2000). The bream catch as weight in Pikkala was also high in
the sense of the relative proportion of the total catch compared to other studies (cf. 12.7 % and
< 5 %) (Lappalainen & Pesonen 2000, Lappalainen et al. 2001). The comparably high CPUE values
and weight proportions of bream do not indicate any clear effect of the reduction fishery, even if
this interpretation is only speculative as long as the pre-reduction values are unknown. Anyhow,
despite the relatively high proportion of bream in the test-fishing, the catch did not correspond to
the picture obtained from the recent commercial catch in Pikkala Bay (from fish traps), where
bream accounted for nearly 85 % of the total catch (in weight) and over 95 % of all cyprinid fish.
Even if the fish traps are now used for the cyprinid reduction, they still are passive gears placed
around the Pikkala Bay and could theoretically catch any fish over 8 cm (i.e. the same range as for
the COASTAL nets) that swims into the trap and is retained there. Obviously there are big
differences in the catchability between fish traps and multi-mesh survey nets. These differences
concerning bream depend either on an effective selectiveness by the fish trap or poor catchability by
the COASTAL net. In studies from lakes comparing multi-mesh gill nets and trawling, the
proportion of adult bream was regularly underestimated in the gillnet catch, while perch, roach, and
white bream catches were higher in the gill net than in trawling (Olin & Malinen 2003, Olin et al.
2009). The underestimation of the bream catches in gillnets might be an effect of their body shape,
as the catchability of deep-bodied species is in general relatively poor in gillnets (Hamley 1975).
The length distribution of the bream catch peaked at intermediate length classes, even if smaller fish
16
usually are more abundant in a population. This could though have been an effect of
underestimation due to the generally lower catchability by multi-mesh gillnets of small fish
compared to bigger fish (Kurkilahti 1999, Olin & Malinen 2003, Olin et al. 2009). Another possible
explanation would be that the small breams are moving more in the middle of the bay than nearer to
the shores where the fishing was conducted, as juvenile breams are known to feed on zooplankton
in the pelagic zone (Persson & Brönmark 2002). The current mean weight of bream in Pikkala was
considerably higher than in a study from another nearby bay area (cf. 237 g and 101 g)
(Lappalainen & Pesonen 2000).
A
B
Figure 4. The abundance (A) and biomass (B) CPUE values for different species in the test-fishing in Pikkala Bay
2011, separated for the different test-fishing areas.
Table 3. The abundance (A) and biomass (B) CPUE values for different species in the test-fishing in Pikkala Bay 2011
separated for the different test-fishing areas. Differences between areas have been tested primarily with One-way
ANOVA. Statistically significant (p < 0.05) differences are marked with an asterisk (*). Statistically significant
(p < 0.05) Bonferroni-corrected pairwise differences are indicated with the superscript letters (x, y, z). The superscript
K-W indicates that the non-parametric Kruskal-Wallis test has been used
Abundance (ind.)
CPUE
Species
Area A
Area B
Area C
Area D
F
p
Perch
56.7 ± 17.0
38.7 ± 25.3
75.0 ± 26.6
39.5 ± 27.2
F3,20 = 2.98
0.056
Ruffe
10.0 ± 5.8
16.0 ± 6.9
21.3 ± 12.5
22.3 ± 12.5
F3,20 = 1.95
0.154
Pikeperch
2.2 ± 1.9
6.5 ± 2.6
6.5 ± 8.6
4.5 ± 3.5
Roach
14.0 ± 13.4
White bream
12.5 ± 1.9
Bream
3.5 ± 2.3
Total
Biomass (g)
ANOVA
x
12.2 ± 5.8
x
37.3 ± 12.3
11.8 ± 7.4
xy
7.0 ± 3.8
109.3 ± 29.8
xy
Perch
3548.7 ± 1557.8
Ruffe
89.5 ± 53.2
Pikeperch
321.4 ± 296.0
Roach
645.3 ± 529.2
White bream
395.8 ± 59.1
x
1.5 ± 1.0
x
1443.8 ± 659.7
460.2 ± 322.3
Bream
773.6 ± 998.8
Total
6049.3 ± 1917.7
1366.7 ± 663.9
y
x
6507.0 ± 2154.9
296.6 ±143.2
y
457.7 ± 277.6
9683.0 ± 1317.4
17
yz
xy
0.002*
F3,20 = 2.46
0.093
F3,20 = 3.23
0.044*
F3,20 = 3.68
0.029*
F3,20 = 8.35
0.001*
F3,20 = 4.33
0.017*
x
0.236
x
K-W
F3,20 = 7.19
247.6 ± 320.3
433.2 ± 362.0
xy
xy
1688.8 ± 1039.2
y
3365.2 ± 1205.4
1467.0 ± 960.2
xy
103.8 ± 41.4
x
651.5 ± 682.5
938.6 ± 762.8
xy
3.0 ± 4.3
310.7 ± 387.2
790.0 ± 489.4
x
y
4049.8 ± 992.4
xy
x
14.3 ± 2.9
149.8 ± 28.5
y
0.212
16.3 ± 9.6
6.7 ± 6.3
x
92.7 ± 25.2
xz
y
K-W
F3,20 = 11.89
< 0.001*
888.3 ± 353.3
F3,20 = 2.39
0.099
856.0 ± 1457.4
F3,20 = 1.04
0.397
F3,20 = 5.18
0.008*
1695.4 ± 709.2
5708.2 ± 2323.6
y
In addition to the two piscivore species (perch and pikeperch) in the test-fishing catch, pike would
have been expected to be caught as well, while it is commonly found in the commercial catches
from the area. The weight proportion of piscivorous fish, including perch > 15 cm and pikeperch >
10 cm, was quite high in Pikkala Bay and resembled the situation from a biomanipulated lake basin
with an increased piscivore proportion five years after the reduction (cf. c. 36 % and c. 40 %)
(Bergman et al. 1999). If the weight proportion of piscivores was calculated using perch > 25 cm
and all pikeperch as in the study of Lappalainen et al. (2000) from different areas in the coastal Gulf
of Finland, it would still be quite high in comparison (cf. c. 21 % and 5–22 %). The proportion of
piscivores (perch > 20 cm and pikeperch > 10 cm) regarding the abundance was somewhat
intermediate compared to the highly varying values from the Finnish coastal fish monitoring sites
(cf. c. 11 % and c. 5–40 %) (HELCOM 2006).
Number of fish
25
20
15
10
5
0
Length class (cm)
Figure 5. The length distribution of the bream catch
in the test-fishing in Pikkala Bay 2011.
4.3 Ecological changes in Pikkala Bay – lack of cyprinid reduction effects
4.3.1 Fish
In order to study possible changes and trends in the fish community and to find potential indications
for effects of the bream reduction, the available old data from previous test-fishing surveys were
combined with the new results from the test-fishing in 2011. The autumn results from test-fishing in
1982, 1987, 1991, 1995 and 2000 (Sauvonsaari 1982, 1988, Sauvonsaari & Vaajakorpi 1991, 1996,
2001) were chosen to be used. Down to the fact that the catches have been recorded separately for
different mesh-sizes both in the old and the recent test-fishing, it was possible to calculate the
results just for the mesh-sizes comparable between the gillnet-series and the COASTAL multi-mesh
gillnet, hence making the comparison more accurate. Thus catches from the mesh-sizes 10 mm and
30 mm was excluded from the COASTAL gillnets and correspondingly the catches from the 75 mm
nets in the net series were not included. The comparable mesh-sizes taken into account for the
COASTAL nets and in the gillnet series were then 12, 15, 19, 24, 38, 48 and 60 mm and 12, 15, 20,
25, 35, 45 and 60 mm respectively and all the following results are based on the recorded catches
from these mesh-sizes if nothing else is stated. As mentioned before, the quality of the old data in
respect of the current study purposes was not at all optimal, which should be borne in mind when
interpreting the results.
The recorded total number of species in the test-fishing results from 1982 to 2011 was 22. The
species number before the bream reduction varied between years from 13 to 16 species with an
18
average of 14.8 (± SD 1.3), and the species number in the 2011 test-fishing, after the beginning of
the reduction, was 9 species (14 if all mesh-sizes were included). Perch, pikeperch, ruffe, roach,
bream, white bream and flounder were present in the catch from all the test-fishing years. Smelt
(Osmerus eperlanus) and herring were caught all the years before the reduction but not in 2011 (a
few specimens of herring were caught in the excluded mesh-sizes), while rudd was the only species
caught in 2011 but not the other years. Perch, pikeperch, ruffe, roach, white bream, bream and
herring dominated the catch by accounting for over 89 % of the total catch (both for abundance and
biomass) during almost the entire study period (Figure 6, Table 4). Year 1982 was an exception
regarding the biomass proportions, as the group “others” dominated, mostly due the catches of big
cods and pikes. During the time before the bream reduction, the abundance values of the total catch
were dominated by perch, ruffe, roach and herring in different proportions, but together accounting
for over 80 %. The total biomass before the reduction was not as clearly dominated by certain
species, even though roach accounted steadily for at least > 24 %. The catch in 2011 was clearly
dominated by perch both for abundance (c. 44 %) and biomass (c. 38 %). The following three
dominating species in 2011 were roach, ruffe and white bream regarding abundance, and roach,
bream and white bream regarding biomass. The most prominent changes in the dominating
proportions between the last test-fishing year before the reduction (year 2000) and year 2011 was,
regarding abundance, an increase in perch (from 18.2 % to 44.3 %) and a decrease in ruffe (from
37.4 % to 15.9 %), and, regarding biomass, an increase in perch (from 27.3 % to 38.2 %) and bream
(from 2.0 % to 13.9 %) as well as a decrease in ruffe (from 12.5 % to 5.4 %). When the proportions
are studied separately for the most important species over the entire study period, some changes and
trends appear (Figure 6). Abundance and biomass proportions for perch were lowest in 1982 (< 10
%) and highest in 2011 and there seemed to have been a rising trend since 1995, measured as both
abundance and biomass proportions. Pikeperch has not had particularly big proportions during the
study period (generally under 10 %), but seemed to have increased in 2000 and 2011 compared to
the earlier years. The abundance proportion of ruffe increased steadily from the lowest value (6.8
%) since 1982 until 2000 and then decreased, while the biomass proportion increased from the
lowest value in 1982 (6.9 %) to 1995 (18.0 %) and thereafter decreased. The proportions of roach
have not shown any clear overall trend but the abundance proportions have varied between 61.5 %
(1982) and 9.8 % (2000) and decreased since 1991 until 2000 and then again increased, while the
biomass proportions have varied between 23.1 % (2011) and 37.3 % (1987) and decreased from
1995 to 2011. Bream has steadily had low (< 2 %) proportions until the increase in 2011, especially
regarding biomass. White bream abundance proportion has increased since 1995 up to 10.9 % and
the biomass proportion has increased from 1987 (4.4 %) to 2000 (10.0 %) and then again slightly
decreased. The proportion of herring has varied quite much, but was greatest in 1987 (46.1 % and
29.2 % for abundance and biomass respectively) and then again totally absent in 2011. The
proportions of other fish species combined have been around 10 % at highest, with the exception of
the biomass proportion in 1982 (33.0 %) affected by the big cod catches that year. The proportions
of the group “others” have decreased since 1995.
19
Figure 6. The percentual proportions of different species in the test-fishing catches from different years between
1982 and 2011 in Pikkala Bay. Notice the differences in scales.
It is convenient to use proportions (%) when investigating the composition of test-fishing catches
from different years, especially if different sampling methods have been used. However, the use of
proportions is not optimal for revealing potential changes or trends in the catches or populations of
single species, as proportions are always dependent on each other. Therefore, in order to further
study the changes and possible trends for the main species in the test-fishing catches, figures for
catch per unit net area and night (CPUE/m2) were calculated (Table 4) thus making the old and the
recent results comparable (see Appelberg et al. 2003). Perch catches regarding both abundance and
biomass were over two times higher in 2011 compared to the next highest values in the 90’s and
there was a significant increase for biomass over the study period (Linear regression: r = 0.847,
p = 0.033) (Figure 7). Pikeperch had also the largest catch values in 2011, and showed a
significantly increasing trend over the study period both for abundance and biomass (Linear
regression: abundance r = 0.847, p = 0.034; biomass r = 0.887, p = 0.018). For ruffe, the abundance
value increased significantly from 1982 to the highest value in 2000 (Linear regression: r = 0.921,
p = 0.027) and the biomass value increased significantly until 1995 (Linear regression: r = 0.956,
p = 0.044), after which the value decreased. Roach abundance decreased significantly from the high
value in 1982 to the lowest value in 2000 (Linear regression: r = 0.891, p = 0.042) and biomass
decreased significantly from 1987 to 2000 (Linear regression: r = 0.971, p = 0.029), after which it
increased to the highest value in 2011. Both the abundance and biomass values of bream were
20
steadily low until they increased over a tenfold in 2011. White bream increased significantly from
the lowest values in 1987 to the highest values in 2011 (Linear regression: abundance r = 0.943,
p = 0.016; biomass r = 0.994, p < 0.001). The abundance values for the total catch have varied quite
much during the study period without any clear trends. The total biomass has been on a steady level
until 2000, after which it increased markedly in 2011 (from c. 45 – 55 cpue/m2 to c. 93 cpue/m2).
Figure 7. The CPUE/m2 values for the total catch and for the different species from the test-fishing catches in Pikkala
Bay between 1982 and 2011. Statistically significant linear trends (Linear regression: p < 0.05) during the study period
are marked with trendlines and with the corresponding equations and R 2-values.
To further look at the possible changes in fish populations after the beginning of the bream
reduction, the test-fishing results (CPUE/m2) from the years before the reduction have been treated
as replicates and compared statistically to the results from 2011 (Table 5). According to the these
results, perch abundance and biomass were significantly higher after the reduction than before
(One-Way ANOVA: abundance F1,27 = 7.708, p = 0.010; biomass F1,27 = 7.024, p = 0.013). Higher
abundances in 2011 than before were also found for bream (Mann-Whitney U-test: p = 0.020) and
white bream (One-way ANOVA: F1,27 = 8.105, p = 0.008), and higher biomass values after the
beginning of the reduction were found for total fish biomass (Mann-Whitney U-test: p = 0.008).
21
Table 4. The CPUE/m2-values and the percentual proportions of different species in the test-fishing occasions in Pikkala
Bay between 1982 and 2011
1982
Biomass (g)
Abundance (ind.)
Species
1987
1991
1995
%
catch/m2
%
catch/m2
%
catch/m2
%
catch/m2
%
catch/m2
%
Perch
0.16
9.8
0.27
15.5
0.24
29.2
0.11
13.9
0.16
18.2
0.66
44.3
Pikeperch
0.02
1.2
0.01
0.7
0.02
2.9
0.01
1.3
0.04
4.8
0.07
4.4
Ruffe
0.11
6.8
0.23
13.2
0.19
23.2
0.27
32.5
0.32
37.4
0.24
15.9
Roach
1.01
61.5
0.39
22.3
0.22
26.4
0.14
17.2
0.08
9.4
0.27
18.1
Bream
0.00
0.3
0.00
0.1
0.00
0.3
0.00
0.6
0.00
0.6
0.05
3.3
White bream
0.11
6.7
0.03
1.6
0.04
4.8
0.03
3.8
0.07
8.2
0.16
10.9
Herring
0.13
7.6
0.81
46.1
0.07
8.4
0.17
20.8
0.13
15.2
0.00
0.0
Other
0.10
6.2
0.01
0.5
0.04
4.6
0.08
10.1
0.05
6.2
0.05
3.1
Total
1.65
100
1.76
100
0.83
100
0.82
100
0.87
100
1.50
100
Perch
5.17
9.5
7.90
16.1
17.39
35.2
6.58
14.5
13.62
27.3
35.48
38.2
Pikeperch
2.63
4.8
1.18
2.4
2.01
4.1
2.43
5.4
5.18
10.4
7.69
8.3
Ruffe
3.79
6.9
4.23
8.6
6.23
12.6
8.17
18.0
6.25
12.5
5.00
5.4
Roach
13.35
24.4
18.32
37.3
15.83
32.0
15.51
34.3
12.68
25.4
21.42
23.1
Bream
1.20
2.2
0.21
0.4
1.01
2.1
0.70
1.5
1.01
2.0
12.88
13.9
White bream
6.67
12.2
1.20
2.4
2.17
4.4
2.92
6.5
5.00
10.0
8.71
9.4
Herring
3.77
6.9
14.32
29.2
1.98
4.0
4.34
9.6
3.74
7.5
0.00
0.0
Other
18.03
33.0
1.75
3.6
2.80
5.7
4.62
10.2
2.43
4.9
1.68
1.8
Total
54.61
100
49.11
100
49.42
100
45.27
100
49.92
100
92.86
100
Catch/m2
Statistical test for
difference
Perch
Before
(1982–2000)
0.19 ± 0.07
After
(2011)
0.66 ± 0.37
Pikeperch
0.02 ± 0.01
0.07 ± 0.08
ns
Ruffe
0.23 ± 0.08
0.24 ± 0.16
ns
Roach
0.37 ± 0.38
0.27 ± 0.22
ns
Bream
< 0.00 ± < 0.00
0.05 ± 0.05
0.020
White bream
0.06 ± 0.03
0.16 ± 0.08
0.008
Total
1.18 ± 0.47
1.50 ± 0.55
ns
Perch
10.13 ± 5.17
35.48 ± 20.97
0.013
Pikeperch
2.69 ± 1.50
7.96 ± 7.88
ns
Ruffe
5.74 ± 1.77
5.00 ± 4.46
ns
Roach
15.14 ± 2.24
21.42 ± 18.64
ns
Bream
0.83 ± 0.39
12.88 ± 14.76
ns
White bream
3.59 ± 2.22
8.71 ± 6.61
ns
Total
49.66 ± 3.33
92.86 ± 36.61
0.008
Species
Abundance (ind.)
2011
catch/m2
Table 5. The CPUE/m2-values (± SD) of the total catch and of different
species, before and after the beginning of the bream reduction in Pikkala
Bay, based on the results from the test-fishing occasions between 1982 and
2011. Differences between ”before” and ”after” have been tested
statistically with One-way ANOVA and with the non-parametric MannWhitney U-test (indicated with the superscript M-W U). Statistically nonsignificant differences are marked with ns
Biomass (g)
2000
p
0.010
22
M-W U
M-W U
M-W U
M-W U
To investigate changes or trends in fish species and the fish community, based on the available testfishing results, was difficult and highly uncertain because of the lack of yearly data in addition to
the other problems mentioned earlier. A great number of possible variations remain unrevealed as
results exist only from 6 years during a period of 30 years. Trends that seem apparent from the
current data, with results from every four to five years, may not exist in reality. The available data
are also poorly suitable for revealing recent changes and possible effects of the bream reduction, as
the situation in fish populations is unknown for the time just before the reduction. When the last
test-fishing data before the reduction are from 2003, with a five-year gap to the reduction in 2009, a
true picture of the fish populations and the community at the beginning of the reduction does not
exist, which makes assessment of potential effects difficult. These results provide at best only a
picture of the relative state of the fish community at certain times and possibly a light indication of
the direction of the changes.
The lower total species number in 2011 compared to previous years, could theoretically indicate a
loss of diversity, e.g. due to a result of the ongoing general eutrophication or possible local
eutrophication effects, as seen in other studies (Lappalainen & Pesonen 2000). The more likeable
explanation is the differences in total net area used, as the probability of catching a new species
increases with sample size. Bream seemed to have increased in Pikkala Bay instead of decreased,
which would have been expected as a result from the reduction fishery. An increase (especially
regarding abundance) in a target species could occur, despite the mass removal, if the release of
competition induces an explosive increase of young-of-the-year fish (e.g. Romare & Bergman 1999,
Olin 2006). Such explanation is however not credible in this case, while the bream catch seemed to
consist mainly of adult fish (Figure 5) and because a possible increase in young fish would not yet
even be seen in the net catches due to the limitations in catchability caused by the mesh sizes used.
Immigration of adult fish from other coastal areas (see Hildén 1986) could on the other hand be the
cause of the increase, thus confounding altogether the potential changes of the reduction. It could of
course also be possible that a reduction indeed has occurred compared to the state just before the
beginning of the project, as the available test-fishing data do not cover that time. According to the
last available obligatory monitoring report concerning fish and fishery in Pikkala Bay, the bream
stock is estimated to have been steadily large from 2000 to 2007, and the 2007 results from the
bookkeeping fishery showed that bream accounted for 33 % of the total annual catch in weight
(Valjus 2008). Anyhow, as the recent test-fishing catches of bream are quite high even in
comparison to other coastal areas these results give thus no indication of a reduction in the bream
population.
Perch seemed to have increased, which could be interpreted as a possible effect of the bream
reduction through diminished competition. In that case the increase in abundance would
hypothetically have had to consist of an increase of the recruitment to the adult population from a
pool of small sized fish, trapped by competition forced growth suppression, as a potential increased
number of young-of-the-year fish would not yet have been seen in the net catches due to
catchability limitations of the used mesh sizes. The increased biomass could, however, at least
partly originate from the enhanced feeding conditions and a consequently higher growth rate. If an
explosive increase of young-of-the-year cyprinids has hypothetically occurred, it would have also
further enhanced the availability of food. The observed increase of perch could also have started
already before the reduction, in that case e.g. as a possible result from the decreasing trend of roach
and a consequently reduced juvenile competition (Persson 1986). However, great natural variations
are also common in the perch stocks (e.g. Böhling et al. 1991), and might be the most likely
explanation for the observed development, at least when no indications of bream reduction were
seen.
23
The supposed increase of pikeperch can as well be only a result of natural variation, but could also
be linked to a hypothetical increase of small sized cyprinid prey fish (e.g. Olin 2005), as pikeperch
becomes early an obligate piscivore. Pikeperch is also known to be competitively favoured by the
ongoing eutrophication due to its good vision in low light intensities (e.g. Sandström & Karås
2002), which could also explain an increase. The observed decrease of ruffe after a longer
increasing trend could be a combined or separate effect of increased predation by perch and
possible pikeperch, and enlarged competition for benthic food due to the supposed increase of
bream. The increase of white bream could have been caused by a reduced competition with bream
after the start of the reduction fishery or, more likely, by the general prevailing environmental
condition that favours white bream.
4.3.2 Benthos
In the latest obligatory monitoring benthos survey in Pikkala Bay, in autumn 2007, a total of 44
different zoobenthic taxons were recognised in the samples from the whole monitoring area
(Mettinen 2010). The most frequent taxons in 2007 were the bivalve Macoma baltica, polychaete
and oligochaete worms and the Hydrobidae gastropods, while the most abundant taxons were
oligochaetes and the amphipod Leptocheirus pilosus. The benthic community was most diverse at
the shallow near shore sampling sites representing a good or a slightly affected bottom quality,
changing towards the deeper sites where only few species dominated expressing a passable or even
a poor quality in places.
Due to the fact that the last available data on zoobenthos in Pikkala Bay are from 2007, i.e. before
the start of the cyprinid reduction, no conclusions can be drawn regarding potential effects of the
reduction on the benthic faunal community. However, in order to roughly demonstrate the temporal
development of the benthic community until 2007, the results from the monitoring site “Pe1_6 m”
are presented. The sampling site is situated in the middle of the bay in a common depth zone for the
area and has data from five different years between 1969 and 2007. The total number of species
encountered during sampling at “Pe1_6 m” varied between one and eight, being lowest in 1996 and
highest in 2003 (Figure 8). The average number of species per replicate varied also between years
from one species in 1996 to 4.4 (± SD 0.55) in 2003 (Figure 8) and there was a significant overall
difference between years (One-way ANOVA: F4,12 = 10.82, p < 0.001) caused by the differences
between year 1996 and all other years (Bonferroni post hoc test: p < 0.05). The total abundance
changed over time (One-way ANOVA: F4,12 = 34.01, p < 0.0001) as the mean values varied
between 65.1 (± SD 22.6) ind./m2 in 1996 and 1226.8 (± SD 166.9) ind./m2 in 2003 (Figure 9).
Statistically significant increase in the total abundance occurred from the low values in 1969, 1996
and 2000 to the higher values in 2003 and 2007 (Bonferroni post hoc test: p < 0.05). The yearly
abundances for the main species or taxonomic groups are shown in Figure 9. The abundance of
oligochaete worms varied over time (One-way ANOVA: F4,12 = 12.71, p < 0.0005) increasing from
total absence and low values (48.1 ± SD 41.4 ind./m2) in 1969, 1996 and 2000 to the highest value
(544.0 ± SD 83.0 ind./m2) in 2007 (Bonferroni post hoc test: p < 0.05). Chironomid larvae
abundance changed over time (One-way ANOVA: F4,12 = 17.97, p < 0.0001) from low numbers
(83.6 ± SD 80.8 ind./m2) and total absence in 1969, 1996 and 2000 to the highest number in 2003
(758.6 ± SD 213.7 ind./m2) followed by a statistically significant decrease in 2007 (Bonferroni post
hoc test: p < 0.05), although the chironomids still was dominating together with oligochaetes in
2007. The abundance of the Macoma clam did not show any significant changes over time during
the sampling years in site “Pe1_6 m” (Kruskal-Wallis test: p > 0.05).
24
Number of species
9
8
7
6
5
4
3
2
1
0
Total
Average
1969
1996
2000
2003
2007
Year
Figure 8. The total and average (± SD) number of species
in the zoobenthos sampling from different years between
1969 and 2007 at the sampling site "Pe1_6 m" in Pikkala
Bay.
A
B
Figure 9. The average total abundance values (ind./m2 ± SD) (A) and the average abundance values (ind./m2) for the
different zoobenthos species (B) from samplings in different years between 1969 and 2007 at the sampling site "Pe1_6
m" in Pikkala Bay.
Benthivorous fish have the potential to regulate the structure of the benthic invertebrate community
(Mattila 1992), which has been shown in experiments (Bonsdorff et al. 1986, Mattila & Bonsdorff
1989, Diehl 1992, Persson & Svensson 2006) and in some large-scale studies (Svensson et al. 1999,
Leppä et al. 2003). The results concerning the impact of fish predation on zoobenthos have,
however, been inconsistent as some field experiments and large-scale studies have not found any
effects (Bonsdorff et al. 1986, Mattila & Bonsdorff 1989, Riemann et al. 1990). Bream as a
particularly effective benthivorous feeder has been shown to be able to affect the benthic
invertebrate community (Leppä et al. 2003, Persson & Svensson 2006). Then, assuming that the
bream population in Pikkala Bay had grown (at least until the reduction) and was strong, effects on
the zoobenthos could have been expected. Against this background, the total abundance of
zoobenthos would have been expected to decrease over time instead of increase as observed at the
example site “Pe1_6 m”. However, compensatory responses might mask the effects on zoobenthos
abundance through interactions between the fish, intermediate invertebrate predators and infaunal
prey (Mattila 1992, Diehl 1995). For example, results from field enclosure experiments have shown
that chironomids may increase when their benthic invertebrate predators are suppressed by fish
25
predation (Diehl 1992, Bergman & Greenberg 1994). Also at site “Pe1_6 m” chironomids had
increased considerably over time and clearly dominated the community together with oligochaetes.
In fact, the observed increase in total abundance was almost entirely a consequence of the increase
of chironomids and oligochaetes. This development has, however, most likely not been a response
to an increased fish predation on any intermediate predator, as the abundance of the only possible
observed invertebrate predator, Hediste diversicolor, did not show any dramatic changes over time.
Thus, the observed changes in the zoobenthos at “Pe1_6 m” appear not to be a result from an
increased bream population, but might instead be reflecting the bottom quality affected by the
variation in the load of nutrients and organic matter.
The increase in the number of species and in the total abundance could indicate an improvement of
the bottom quality as a possible recovery response to decreased loading (e.g. Kraufvelin et al.
2001), even if the developed chironomid and oligochaete domination still represented a strongly
affected bottom quality (Leppäkoski 1975). A suitable explanation for the exceptionally poor
situation in 1996 would be that the Pikkala central water purification plant was taken in use that
same year, becoming the closest point load source for the sampling site. Even if the pollution from
the water treatment plant was larger in 1996 than in the following years, the importance of the local
loading is difficult to interpret but likely small as the loading from the Pikkala River is several
magnitudes greater (Wikström & Kamppi 2004). However, the loading (especially of organic
matter) from the river was, as well, considerably higher in 1996 compared to 2003 and 2007, which
could thus be reflected as the observed improvement in zoobenthos towards the last sampling years
(Mettinen 2010). The increase in the average species number could also further have been affected
by an improvement of the determination accuracy, and the increase of the total number of species
might additionally have been an effect of a larger amount of samples taken.
4.3.3 Water quality
Water quality data were analysed for the sampling site “UUS-6 Pikkalanlahti 20”, which was
considered to be representative for the study area and relatively unaffected by local wastewater
discharges. Water quality might be affected by cyprinid reduction through the top-down effect of
reduced phytoplankton turbidity, or through the bottom up effect of internal nutrient recirculation.
Changes in coastal water quality might, however, also result from variations in riverine runoff, from
occasional intrusions of nutrient rich open sea bottom water due to upwelling, or from large-scale
changes in local wastewater discharges, thus making the observation of potential effects from a
biomanipulation attempt difficult.
The surface water (0–3 m) tot-P concentration in Pikkala Bay has been measured since 1967. The
yearly average of all these results varied considerably between the highest value of 75.0 (± SD 54.5)
µg/l (in 1970) and the lowest value of 25.6 (± SD 5.9) µg/l (in 1977). The total average tot-P
concentration of all observations was 40.0 (± SD 18.9) µg/l. The average tot-P concentration from
the years 2009–2010 was 45.5 (± SD 11.8) µg/l and the annual mean values from these years were
among the six highest values since 1975. The grand average tot-N concentration (based on all
surface water records since 1974) was 515.0 (± SD 271.4) µg/l and the yearly mean values varied
between 1110.0 (± SD 1117.2) µg/l (in 1974) and 360.0 (± SD 62.0) µg/l (in 1975). The average
tot-N concentration from the years 2009–2010 was 469.2 (± SD 108.1) µg/l. Due to some
inconsistency in the amount and timing of sampling between different years, a more accurate way
of analysing the annual nutrient concentrations is perhaps to include only the summer observations
(June–August), which are available for all years since 1975. The annual summer mean values for
tot-P varied also quite much, but still showed a slightly increasing trend from 1975 to 2010 (Linear
regression: r = 0.492, p = 0.002) (Figure 10). The development in the tot-P concentrations during
26
the last years (2009–2010), since the beginning of the reduction fishery, showed no signs of
deviation from the general increasing trend. The annual summer average values for the tot-N
concentrations showed also a considerable variation between years, and high values in 1976–1979,
but then an increasing trend from 1982 to 2010 (Linear regression: r = 0.529, p = 0.003). The 2009–
2010 tot-N values did not show any signs of a decrease. Nutrient concentrations for the deeper
water (> 3 m) seemed not to have been sampled as thoroughly as for the surface water, and hence,
consistent monthly results covering the summer season did not exist. However, the annual average
values of all observation showed roughly a similar kind of development as for the nutrient
concentrations in the surface water, and no indications of a decrease since the beginning of the
reduction fishery could be seen.
A
B
Figure 10. The annual average summer (June–August) surface water (0–3 m) total-P (A) and total-N (B) values (µg/l)
at the sampling site ”UUS-6 Pikkalanlahti 20" in Pikkala Bay from 1975 to 2010. Statistically significant linear trends
(Linear regression: p < 0.005) are marked with trendlines and with corresponding equations and R 2-values.
30
500
25
400
20
300
15
200
10
100
5
0
Tot-N riverload (ton)
Tot-P riverload (ton)
The river tot-P loading between 2003 and 2010 had an average yearly value of 13.9 (± SD 7.0) tons,
but varied considerably between the lowest loading of 4.0 ton/a (in 2003) and the highest loading of
25.9 ton/a (in 2008) (Figure 11). The tot-N river load during 2003–2010 was in average 254.9
(± SD 115.2) ton/a, and had a minimum value of 74.1 ton/a in 2003 and a maximum value of 418.0
ton/a in 2004 (Figure 11). Trying to elucidate the importance on the riverine nutrient load for the
nutrient concentrations in the Pikkala Bay, the dependency of the total nutrient concentrations
(surface values) to the river loading was tested both on a monthly and on an annual basis (Figure
12). However, no significant relationships (Linear regression: ns) between the river nutrient loads
and the water nutrient concentrations were found, neither when the total annual loadings nor when
monthly average loadings were tested against the corresponding concentrations in the bay.
Tot-P
Tot-N
0
2003
2004
2005
2006
2007
2008
2009
2010
Year
Figure 11. The annual total-P and total-N riverine load (ton) to Pikkala Bay in 2003–2010.
27
A
B
C
D
Figure 12. The dependency relationships between the nutrient concentrations in Pikkala Bay and the
riverine nutrient loads. Charts A and B present the relationships between the annual average surface
water (0–3 m) nutrient (tot-P and tot-N) concentrations (µg/l) and the annual riverloads (ton) of the
nutrients for the period 2003–2010. Charts C and D present the relationships between available
monthly average surface water (0–3 m) nutrient (tot-P and tot-N) concentrations (µg/l) and the
corresponding monthly average nutrient riverloads (kg/d) from the period 2008–2010. No statistically
significant linear dependencies were found (Linear regression: ns).
The average yearly chl-a concentration in Pikkala Bay, calculated on all available observations
(generally monthly samplings from 0–2 m depth in May to September or October since 1975),
varied between the lowest value, 2.2 (± SD 1.5) µg/l, in 1975 and the highest value, 21.8 (± SD
32.5) µg/l, in 1993. The grand average value of all observations was 9.2 (± SD 9.5) µg/l. The
average concentration from 2009–2010 was 14.5 (± SD 8.3) µg/l and the annual mean values from
these years were among the eight highest values since 1975. When analysing the yearly average
summer (June–August) chl-a values (which existed consistently for all years), a clear and
significant increase was apparent from 1975 to 2010 (Linear regression: r = 0.724, p < 0.0001)
(Figure 13). The development in the chl-a concentrations during the last years (2009–2010), since
the beginning of the reduction fishery, showed no signs of deviation from the general increasing
trend. On the contrary, the average summer chl-a value in 2010 was the second highest since 1975.
The timing of the chl-a maximum seemed to have shifted from the spring towards the late summer
(Figure 14). During the period 1975–2000 the chl-a maximum has occurred in some other month
than in may only seven times, while it since 2000 onwards has most often taken place in the late
summer months and only once in may. The chl-a maximum values in 2009 and 2010 were observed
in August. However, it has to be noticed that the September observations have gaps during some
years and that no results from May exist from 2007 and onwards, thus making the interpretation of
these results somewhat uncertain. The seasonal dynamics of chl-a concentrations, based on five
year periods (with few exceptions) since 1975, revealed the same development towards higher
values in the late summer months (Figure 15). However, it seemed that the spring values could still
be high even if the summer concentrations also had risen. The average monthly values from 2009–
2010 showed no indications of any changes against the general development in the seasonal
dynamics of the chl-a concentrations.
28
25
Chl-a (µg/l)
20
15
y = 0.3015x - 592.99
R² = 0.5248, p < 0.0001
Annual June-August
mean values
10
Linear (Annual JuneAugust mean values)
5
0
1975 1980 1985 1990 1995 2000 2005 2010
Year
Month (May-September)
Figure 13. The annual average summer (June–August) chlorophyll-a
concentration (µg/l) at the sampling site ”UUS-6 Pikkalanlahti 20" in
Pikkala Bay from 1975 to 2010. The statistically significant linear trend
(Linear regression: p < 0.0001) is marked with a trendline and with the
corresponding equation and R2-value.
9
8
7
max chl-a
6
5
1975
1980
1985
1990
1995
2000
2005
2010
Year
Figure 14. The occurance month of the chlorophyll-a maximum
concentrations at the sampling site ”UUS-6 Pikkalanlahti 20" in Pikkala
Bay during the period 1975–2010. Note that there have been gaps in the
sampling in September during years 1982–84, 1987, 1992–93, 1999, and
2003–05, as well as in May during 2007–10.
30
Monthly average 1975-79
Chl-a (µg/l)_0-2 m
25
20
15
10
5
0
May
June
July
August
September
Month
Figure 15. The average monthly (May–September) chlorophyll-a values (µg/l) for five-year periods
(except 1975–79, 2005–08 and 2009–10) at the sampling site ”UUS-6 Pikkalanlahti 20" in Pikkala Bay
during the period 1975–2010. Note that there have been gaps in the sampling in September during years
1982–84, 1987, 1992–93, 1999, and 2003–05, as well as in May during 2007–10.
29
The average yearly water transparency, measured as the Secchi depth, based on all available values
since 1973, varied between the highest value, 2.5 (± SD 1.1) m, in 1974 and the lowest value, 1.0
(± SD 0.5) m, in 2010. The grand average of all observations was 1.7 (± SD 0.8) m. The average
value from 2009–2010 was 1.1 (± SD 0.5) m and the annual mean values from these years were
among the three lowest values since 1973. When analysing the annual average summer (June–
August) Secchi values (which existed consistently for all years since 1975, except from 2001), a
significant decrease was apparent throughout the period (Linear regression: r = 0.645, p < 0.0001)
(Figure 16). The development in the transparency during the last years (2009–2010), since the
beginning of the reduction fishery, showed no signs of deviation from the general decreasing trend.
Instead the average summer Secchi value in 2010 was the lowest since 1975.
3
Secchi depth (m)
2.5
2
Annual June-August
mean values
1.5
1
Linear (Annual JuneAugust mean values)
y = -0.0207x + 42.807
R² = 0.4165, p < 0.0001
0.5
0
1975 1980 1985 1990 1995 2000 2005 2010
Year
Figure 16. The annual average summer (June–August) Secchi depth (m)
at the sampling site ”UUS-6 Pikkalanlahti 20" in Pikkala Bay from 1975
to 2010. The statistically significant linear trend (Linear regression:
p < 0.0001) is marked with a trendline and with the corresponding
equation and R2-value.
The bottom water oxygen condition has generally been quite good during the monitoring period
from 1962 to 2010 (Figure 17). The average oxygen concentration of all observations was 9.3 mg/l,
and near-bottom hypoxia (< 4 mg/l) has occurred only at few occasions.
16
O2-concentration (mg/l)
14
12
10
8
6
Border
value for
hypoxia
4
2
2010
2008
2006
2004
2002
2000
1998
1996
1994
1992
1990
1988
1986
1984
1982
1980
1978
1976
1974
1972
1970
1968
1966
1964
1962
0
Time
Figure 17. All observations of the oxygen concentration (mg/l) in the bottom water at the sampling site ”UUS-6
Pikkalanlahti 20" in Pikkala Bay from 1962 to 2010.
30
Nutrients and especially the elements P and N are essential for the primary production. The relative
importance of these two nutrients for production limitation might vary temporarily and spatially due
to the accessibility of the nutrients to the primary producers (e.g. HELCOM 2009). In the Baltic Sea
N is generally the limiting nutrient, but in the coastal and inshore waters N often exists richly thus
making P concentration most crucial for the production. Fish can affect the nutrient concentration in
the water by recycling and storing nutrients (e.g. Olin et al. 2006). Many studies from lakes have
shown that the role of fish for the recirculation of nutrients is important in relation to the total
external and internal nutrient load (Brabrand et al. 1990, Horppila & Kairesalo 1992, Breukelaar et
al. 1994, Persson 1997). The P release by fish can be of the same order of magnitude than the
external and the other internal loading and consists mostly of inorganic compounds, which are
directly available for primary producers (Brabrand et al. 1990, Persson 1997). Adult breams have
been shown to effectively recycle nutrients from the sediments, through their feeding on benthic
animals and the re-suspension of sediments caused by their foraging activity (Breukelaar et al.
1994, Persson 1997). Additionally cyprinids might also affect the nutrient concentrations in the
water indirectly through their predation effect on the benthic faunal community and its impact on
the nutrient fluxes, i.e. the balance between the re-suspension and the oxygenation induced retention
of nutrients caused by the burrowing activity of the zoobenthos (e.g. Svensson et al. 1999).
As an effect of a successful cyprinid reduction nutrient concentrations would be expected to
decrease, which has also been observed from e.g. many Finnish lakes (Olin et al. 2006). In those
lakes the role of the fish assemblage may have turned from nutrient recycler to nutrient storage as
the proportion of juveniles and the growth rate of fish has increased. This kind of development or
even any indications of a nutrient decrease were absent from the current results from Pikkala Bay,
where both P and N have instead increased in accordance with the general eutrophication
development also seen elsewhere (Bonsdorff et al. 1997a, HELCOM 2009). The latest P and N
concentrations in Pikkala Bay represented an obvious state of eutrophication (Suonpää & Mettinen
2010, Suonpää 2011). The absence of a nutrient decrease and a concurrent nutrient increase as a
response to cyprinid reduction has though been reported also from some eutrophicated lakes with a
high external nutrient loading (e.g. Benndorff et al. 1988, Riemann et al. 1990), suggesting that the
riverine nutrient runoff from Pikkala River could be high enough to mask any decrease in the
internal nutrient circulation. However, the concentration of P and N in the bay did not seem to
directly depend on the corresponding river load, which again could indicate that the internal loading
would have a greater importance. This should though be interpreted with some carefulness, as no
recorded nutrient concentrations in the bay water for the time of the spring and autumn high flows
(accounting for the largest nutrient runoff) were available. In the Gulf of Finland in general, internal
nutrient loading (especially P), i.e. the release of nutrients from sediments, has been considerably
high and at times even larger than the external loading (Pitkänen et al. 2001, Conley et al. 2002).
This basin-scale internal load has been coupled to the vast hypoxia, which causes nutrient release
from the sediment. However, the oxygen conditions in the bottom water of Pikkala Bay seemed to
have been quite good, with hypoxia occurring only rarely, thus referring to some other nutrient
releasing mechanism, e.g. recirculation by fish, in the case internal loading has been important. The
bream reduction in Pikkala Bay could of course also have been simply too small, thus explaining
the lack of observable effects on the nutrient concentration.
Some early studies have shown that up to 50 % of a P pool in lake water can be stored as fish
biomass (Kitchell et al. 1975), suggesting that a fish reduction could remove a large part of the
nutrients in the system. However, in reality both most eutrophic lakes and the Baltic Sea coastal
areas have large quantities of nutrients stored in the sediments, providing a long-term internal
supply, even if the external loading would be reduced (Conley et al. 2002, Jeppesen et al. 2005),
hence probably counteracting the short-term effects of nutrient removal by fish reduction biomass.
31
In Pikkala Bay in 2010 the reduction catch of bream (c. 110 ton) removed about 10 % and 1.5 % of
the annual riverine load of P and N respectively, as calculated based on published nutrient content
values for bream (Schreckenbach et al. 2001). Nutrients removed as fish biomass are, however, not
comparable to and cannot directly compensate for the external loading, because the external loading
is still first available for the primary production regardless of the fish biomass. Nutrients bound to
fish have, so to say, already been used by phytoplankton, zooplankton and/or zoobenthos, and
would sedimentate when the fish dies. This will of course add some nutrients to the internal pool,
but the effect of removing this addition is likely to be minimal due to the large storage of previously
sedimentated nutrients. Even if the direct nutrient removal as bream reduction biomass seems to be
of less importance, the reducing effect on the nutrient recycling by the bream can potentially be
significant. Anyhow, no impacts on nutrient concentrations in Pikkala Bay could be seen as a
potential result of the bream reduction.
The chl-a concentration in the water can be used as a measure of the phytoplankton biomass (e.g.
HELCOM 2009). The amount of phytoplankton is principally dependent on the availability of
nutrients and light (e.g. Anderson et al. 1996, Kuosa et al. 1997, Olenina et al. 2006), but can also
be affected by zooplankton grazing (e.g. HELCOM 2009). Cyprinid reduction can thus potentially
affect the phytoplankton community and hence the chl-a concentration either through decreased
zooplanktivory and a consequent increase of zooplankton grazing on phytoplankton, or through
decreased nutrient availability due to the reduced nutrient recycling effects of the fish (e.g.
Horppila et al. 1998, Mehner et al. 2002). In the current study in Pikkala Bay the latter mechanism
is more probable, as bream foraging is mostly confined to the bottoms and concentrated on benthic
invertebrates instead of zooplankton. Moreover, possible top-down impacts on phytoplankton via
zooplankton would have been difficult to distinguish, while no data on the zooplankton community
existed. The observed increase in the annual average summer chl-a concentration in Pikkala Bay
gave no indications of any effects of the bream reduction, but instead resembled roughly the general
increasing trend in the Gulf of Finland as an obvious effect of the eutrophication development (see
HELCOM 2009). The latest chl-a values in Pikkala Bay represent eutrophicated coastal waters
(Suonpää & Mettinen 2010, Suonpää 2011). The observed change in the seasonal dynamics of the
chl-a concentration towards higher late summer values has probably been caused by the increasing
amount of cyanobacteria that have been shown to dominate the recent late summer phytoplankton
assemblage in Pikkala Bay (Mettinen 2010). Many cyanobacteria can fixate gaseous N to
bioavailable inorganic compounds and consequently high concentrations of cyanobacteria occur
generally later in the summer after the N-limited spring phytoplankton bloom, when unutilised P
still remains available (e.g. Larsson et al. 2001). Results from some biomanipulated Finnish lakes
have shown a shift in the cyanobacterial bloom towards the autumn, as a possible effect of a
decreased amount of available nutrients (Olin et al. 2006). This delay in the cyanobacterial peak
could reflect that the nutrient shortage in the lakes was not replenished until the fall turnover.
However, the observed development in Pikkala Bay is likely not caused by the bream reduction,
while the nutrient concentrations in the bay have not shown any decrease and because the seen
seasonal change in the chl-a concentration has begun already many years before the bream
reduction. A similar development of a bias toward the late summer in the seasonal chl-a
concentration since the 1990’s has been reported from other coastal areas along the Gulf of Finland,
and has been explained by a probable decrease in N availability, which limits the magnitude of the
spring bloom, saving greater P reserves for the late summer (Raateoja et al. 2005).
Water transparency is influenced by the amount of light-absorbing matter in the water, such as
chlorophyll and other suspended particles, and is thus impaired by eutrophication and turbid runoff
(Schiewer 2008). Transparency in the water is a detrimental factor for the light-demanding primary
production of both phytoplankton and macrophytes (e.g. Andersson et al. 1996, Bäck & Ruuskanen
32
2000) and also affects, for example, visual predatory fish (Sandström & Karås 2002). The bream
reduction in Pikkala Bay could theoretically have improved the transparency, through the
decreasing of phytoplankton (and chl-a) and perhaps through the reduced re-suspension of bottom
sediments by foraging breams. No improvement in the Secchi depth was however seen, but instead
a clear declining trend has prevailed, similar to the general development in the northern Baltic Sea
and many coastal areas, representing the past and ongoing eutrophication (e.g. Bonsdorff et al.
1997a, HELCOM 2009). The dynamics of the water transparency in Pikkala Bay might also be
affected by the riverine discharge of clay and humic substances.
5 General points and conclusions
An important part of this work was to search for environmental data regarding Pikkala Bay, which
successfully resulted in a vast collection of literature and other data sources generating a good
picture of the existing background information from the area. Despite the fairly large amount of
found environmental data, no clear indications of any ecological effects caused by the bream
reduction were found. The lack of observable effects can either imply that the data were poor or
insufficient for revealing potential effects, or that the bream reduction has not caused any
observable changes.
Generally the majority of the existing data from Pikkala Bay have been collected as a part of
environmental monitoring and the samplings have thus not been explicitly designed for the study of
bream reduction effects. Problems in the quality of the data have included e.g. issues with
replication, sample size, sampling frequency, sampling methodology and location of the sample
sites. A decisive deficiency in some cases was the fact that the data did not cover the time after the
beginning of the bream reduction. The data concerning the fish assemblage in the bay suffered from
many of the problems mentioned above, thus making the interpretation of the results difficult and
filled with uncertainty. Zoobenthos data were not available for the time after the reduction start,
making the assessment of potential bream reduction effects impossible. The best data existed for the
water quality variables, but any possible effects might not yet have become visible at this level, as
these results covered only the first two years of the bream reduction of which only the second year
included a considerably large bream removal. Finally, a general deficit in the available data and the
design of this study was the lack of control areas for Pikkala Bay.
If the bream reduction has not caused any true changes in the ecosystem, it fundamentally implies
that the reduction has been too small (or alternatively that breams have not had any major role or
negative impact at all on the ecosystem before the reduction, hence also making an improvement
attempt impossible to succeed). The target catch for a successful cyprinid reduction, according to
experiences from lake restorations, should be over 75 % of the initial biomass (Hansson et al. 1998,
Meijer et al. 1999). The initial biomass of bream in Pikkala Bay was however unknown. According
to the biomanipulation advice for European lakes given by Jeppesen & Sammalkorpi (2002), the
target catch can also be estimated based on the tot-P concentration in the water (catch need (kg ha-1
yr-1) = 16.9 × tot-P0.52). This calculation would give a target catch between 200 and 300 tons per
year for Pikkala Bay with an area of 20 km2, depending on which average tot-P values are used.
According to this, the bream reduction catch would have been clearly too small. However, it must
be borne in mind that these advice are given for lake biomanipulations and the coastal ecosystem
might function differently in many respects. Another important aspect concerning the
successfulness of coastal cyprinid reduction in general is the fact that the target areas are not closed
systems similar to lakes. This involves the possibility for fish populations to migrate in and out
33
from the areas, thus perhaps reducing the impact of the reduction fishery. The results from an early
bream tagging study from Pikkala Bay showed that the bream migration area was vast, reaching
along the southern Finnish coast from the Archipelago Sea in west to the Pellinki archipelago in
east, although the majority of the tag-returns came from the nearby areas (Dahlström et al. 1968). If
the bream populations are not confined to a certain bay, but instead move from bay to bay along the
coast, a reduction attempt in a single bay would then most likely be effectless. A general
prerequisite for successful effects of biomanipulation is a low or moderate external nutrient loading
(e.g. Hansson et al. 1998). The nutrient load from Pikkala River to the bay might be too high, thus
hindering any potential effects by the bream reduction on the water quality. However, the high
external nutrient loading would not be able to affect the primary changes that should have been seen
in the structure of the fish community if the reduction would have been large enough.
Due to the deficiency in the originally existing data on the fish community in Pikkala Bay, a new
test-fishing effort was carried through. The results of the test-fishing provided an updated picture of
the fish assemblage and enabled comparisons with the older data. The current test-fishing results
also provide a solid background for continued studies in the area, regarding future changes in the
fish community. Test-fishing together with the oncoming echo-sounding study for assessment of
coastal cyprinid biomasses (Anon. 2011e) will be useful to conduct in order to follow up the effects
of the cyprinid reduction on the fish community. Additionally a continued monitoring of water
quality and zoobenthos, as well as the implementation of zooplankton sampling in Pikkala Bay and
in potential reference areas would be important for a successful and a more comprehensive way of
studying the effects of the bream reduction. As stated for lakes, restorations are often conducted
primarily to improve water quality and are not designed as a scientific experiment (Mehner et al.
2002). This is partly true also for the Pikkala Bay bream reduction, which is understandable but as
well somewhat unfortunate because of the lost potential to investigate and clarify the hitherto
unknown mechanisms, effects and potentials of the reduction fishery in coastal areas. It would
hence be desirable and highly useful if future coastal cyprinid reduction projects would include well
planned environmental monitoring of the kind mentioned above. From a more scientific
perspective, experiments and modelling could additionally enhance the understanding of how
biomanipulation works in coastal areas.
Recently a rising amount of new ideas have been presented for a rapid counteraction and
remediation against the eutrophication effects in the Baltic Sea, including e.g. the use of large-scale
ecological engineering for improving water quality (Stigebrand & Gustafsson 2007). These ”quick
fix” solutions have gained increasing attention, even if most of the proposed methods seem
somewhat unrealistic or not viable (Conley et al. 2009). Biomanipulation and cyprinid reduction
fishery can also be seen as such a ”quick fix” solution. It has been stated that biomanipulation could
be a cost-effective measure for directly removing nutrients from the sea and for improving water
quality through cascading food-web mechanisms (Hansson et al. 1997, Setälä 2011). Both
biomanipulation and other ecological engineering solutions have been faced by scepticism, based
on the uncertainty of the true large-scale effectiveness e.g. due to the enormous size of the Baltic
Sea, and by the reasonable opinion that persistent long-term water quality improvement can only be
achieved by a reduction of external nutrient loads to the sea (Conley et al. 2009). If, however, new
ideas are tested and implemented, they should be well planned and assessed, thus providing real
evidence of the usefulness and by that reducing the need for speculation.
The coastal cyprinid reduction fishery will continue at a larger scale along the Finnish coast due to a
new governmentally financed support system for commercial fishermen (Anon. 2011f). Fishermen
will be guaranteed a certain minimum price for their cyprinid catch, which probably will attract
them to target for bream, roach and other previously valueless cyprinid species. Generally it is
34
useful to thoroughly clarify the targets of this kind of reduction fishery effort. Is the state-aided
cyprinid reduction implemented in order to employ coastal fishermen and enhance the utilisation of
previously unused fish resource, to remove nutrients from the sea, or in order to shift back the
coastal ecosystem to a state characterised by better water quality and the domination of predatory
fish? All of these targets have been mentioned as motives behind this nation-wide cyprinid
reduction program. The enhanced employment of coastal fishermen is a good and important aspect,
and the increased commercial utilisation of cyprinids alongside of the other economically more
important species seems sensible. However the term “reduction fishery” sounds somewhat strange
together with the mentioned target of enhancing the use of cyprinid fish. Is the target really to
reduce cyprinids, or is it to develop a sustainable utilisation of these species? Cost effective nutrient
removal from the sea, has also been used as a common argument for cyprinid reduction. It has been
calculated that the nutrients removed with the reduced fish biomass could cover a considerable part
of the national external nutrient load reduction obligations set by HELCOM. The nutrients removed
as fish biomass are however not strictly comparable to the external nutrient loading. The
bioavailable amount of nutrients will not necessarily diminish with the removal of fish-bound
nutrients, as the externally introduced amount of nutrients remains unchanged. So, even if reduced
fish biomass removes effectively nutrients (i.e. bound to fish biomass), it should be investigated if
this removal has any importance. The fish-bound nutrients will not become bioavailable until the
fish is dead and decomposed and even then only a part of the nutrients will probably be recycled as
the other part will be remained in the sediments. Hence, the nutrients removed with fish biomass
will affect the nutrient state in the water only through the eliminated input of fish-bound nutrients to
the internal pool, of which the majority is probably bound in the sediments. The much more
important aspect, than the removal of the fish-bound nutrients, would presumably be the removal of
the nutrient recycling function of the cyprinids. It should be investigated how big the internal
nutrient loading is and how much it will decrease through the reduction of cyprinids. The target of
shifting back the ecosystem toward a more “normal” state by the means of cyprinid reduction might
not be that unrealistic, as fish communities world-wide have also previously been changed as a
consequence of human fishing pressure. However, to achieve the desired changes the reduction has
to be big enough and probably has to cover large coastal areas, in order to induce a shift between
the predatory fish and cyprinids, and to mitigate the compensating effects of fish migration
respectively. Forcing an ecosystem to shift from one state to another is often a nonlinear process,
implying that it may require a larger amount of time, effort, and resources than expected (Mayer &
Rietkerk 2004). As a conclusion can be said that much more high-quality research is needed on the
coastal cyprinid reduction and its ecological effects, but the reduction fishery might have a potential
to support the improvement measures of the coastal waters, which fundamentally should though
consist of the reduction of the external nutrient loading.
Acknowledgements
Regarding this project I want to thank the following persons and instances: fisherman Klaus
Berglund; personnel at the Uusimaa ELY-center (Markku Marttinen, Mikko Koivurinta and
Mikaela Ahlman); researchers at LUVY ry (Aki Mettinen, Anu Suonpää and Ralf Holmberg); Gabi
Lindholm, the representative for Kirkkonummi-Porkkala fishing area; the test-fishing assistants
Fredrik Gripenberg and Jason Selvarajan; the water-area owners Siuntio and Kirkkonummi
municipalities, Nokia Asset Management, Asuntosäätiö and Erävesi; and additionally Harry
Dahlström, Mats Westerbom and Hannu Lehtonen.
35
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Appendix A. Test-fishing 2011
Table A 1. Practical background information about the test-fishing survey in Pikkala Bay in September 2011
Area
A
B
C
D
Date
(fishing morning)
Site
Coordinates
(WGS 84: hddd°mm.mmm')
Net
direction
Depth
(m)
06/09/2011
A1
N 60 04 787 E 24 18 300
NW
2.0
06/09/2011
A2
N 60 04 892 E 24 18 300
N
2.5
08/09/2011
A3
N 60 04 599 E 24 18 373
SE
3.0
08/09/2011
A4
N 60 04 744 E 24 18 379
S
2.0-2.5
09/09/2011
A5
N 60 04 627 E 24 18 499
S
3.0
09/09/2011
A6
N 60 04 460 E 24 18 392
NW
3.0
06/09/2011
B1
N 60 04 584 E 24 20 484
W
6.5
06/09/2011
B2
N 60 04 452 E 24 21 054
W
4.0
07/09/2011
B3
N 60 04 473 E 24 20 577
W
4.0
07/09/2011
B4
N 60 04 652 E 24 20 775
SW
7.0-8.0
07/09/2011
B5
N 60 04 373 E 24 20 870
SW
2.5-3.5
09/09/2011
B6
N 60 04 503 E 24 20 902
SE
3.5
06/09/2011
C1
N 60 03 652 E 24 22 228
NW
4.0-7.0
06/09/2011
C2
N 60 03 385 E 24 22 229
SW
10.0
07/09/2011
C3
N 60 03 867 E 24 22 353
SW
4.0-6.0
07/09/2011
C4
N 60 03 465 E 24 22 163
NW
7.0-10.0
09/09/2011
C5
N 60 03 552 E 24 22 199
SW
3.0-9.0
09/09/2011
C6
N 60 03 746 E 24 22 319
SE
7.0
06/09/2011
D1
N 60 03 737 E 24 19 511
SW
3.0
07/09/2011
D2
N 60 03 728 E 24 19 410
W
3.5
07/09/2011
D3
N 60 03 213 E 24 19 263
W
3.0
08/09/2011
D4
N 60 03 771 E 24 19 817
W
4.5-5.5
08/09/2011
D5
N 60 03 835 E 24 19 347
wind
3.0
08/09/2011
D6
N 60 03 660 E 24 19 155
wind
3.0
09/09/2011
09/09/2011
09/09/2011
09/09/2011
09/09/2011
09/09/2011
09/09/2011
09/09/2011
09/09/2011
09/09/2011
09/09/2011
09/09/2011
09/09/2011
09/09/2011
09/09/2011
09/09/2011
09/09/2011
09/09/2011
08/09/2011
08/09/2011
08/09/2011
08/09/2011
08/09/2011
08/09/2011
08/09/2011
08/09/2011
08/09/2011
08/09/2011
08/09/2011
08/09/2011
08/09/2011
08/09/2011
08/09/2011
08/09/2011
08/09/2011
08/09/2011
06/09/2011
06/09/2011
06/09/2011
06/09/2011
06/09/2011
06/09/2011
06/09/2011
06/09/2011
06/09/2011
Date
06/09/2011
06/09/2011
06/09/2011
06/09/2011
06/09/2011
06/09/2011
06/09/2011
06/09/2011
06/09/2011
A
0 0.0
0 0.0
SD
3 270.2
2 113.8
17
57
1557.8
3548.7
6
10
53.2
89.5
2
2
296.0
321.4
13
14
529.2
645.3
2
13
59.1
395.8
14
9
203.4
152.3
2
4
998.8
773.6
8.9
0 21.7
0
0
0
0.0
0.0
0
0
0.0
0.0
0
0
0.0
0.0
0 0.0
0 0.0
30
109
1917.7
6049.3
herring
sprat
perch
ruffe
pikeperch
roach
white bream
bleak
bream
rudd
vimba
flounder black goby pipefish
TOTAL
abu bio abu bio
abu bio
abu bio
abu bio
abu bio
abu bio
abu bio
abu bio
abu bio abu bio abu bio
abu bio
abu bio abu bio
0 0.0
2 17.5
9
47.0
4
29.2
0
0.0
2
18.6
0
0.0
7
82.7
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
24
195.0
0 0.0
0
0.0
9
125.3
0
0.0
0
0.0 10
93.8
0
0.0 30 402.1
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
49
621.2
0 0.0
0
0.0
15
318.8
3
44.1
0
0.0
5
118.2
5
91.6
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
28
572.7
0 0.0
0
0.0
8
413.2
0
0.0
0
0.0 11
433.7
7
181.7
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
26
1028.6
0 0.0
0
0.0
11 1110.8
0
0.0
0
0.0
3
238.6
1
106.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
15
1455.4
0 0.0
0
0.0
2 1052.0
0
0.0
0
0.0
1
150.5
0
0.0
0
0.0
2
85.1
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
5
1287.6
0 0.0
0
0.0
2
442.3
0
0.0
0
0.0
2
572.6
0
0.0
0
0.0
1
161.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
5
1175.9
0 0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
0
0.0
0 0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
0
0.0
0 0.0
2 17.5
56 3509.4
7
73.3
0
0.0 34 1626.0 13
379.3 37 484.8
3
246.1
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0 152
6336.4
0 0.0
0
0.0
6
39.3
0
0.0
0
0.0
0
0.0
0
0.0
2
13.6
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
8
52.9
0 0.0
0
0.0
4
62.3
1
13.0
0
0.0 18
211.5
2
26.8
7 103.4
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
32
417.0
0 0.0
1 10.8
9
450.3
1
11.8
0
0.0
1
14.5
4
75.4
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
16
562.8
0 0.0
0
0.0
6
302.0
0
0.0
3
775.4
2
142.9
7
216.0
0
0.0
0
0.0
1 53.2
0 0.0
0
0.0
0
0.0
0 0.0
19
1489.5
0 0.0
7 654.4
0
0.0
0
0.0
0
0.0
1
67.0
1
44.5
0
0.0
1
54.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
10
819.9
0 0.0
0
0.0
4
862.8
0
0.0
0
0.0
1
153.5
0
0.0
0
0.0
2
189.7
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
7
1206.0
0 0.0
0
0.0
4 1540.9
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
3 1217.9
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
7
2758.8
0 0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
0
0.0
0 0.0
0
0.0
1
111.1
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
2 1180.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
3
1291.1
0 0.0
8 665.2
34 3368.7
2
24.8
3
775.4 23
589.4 14
362.7
9 117.0
8 2641.6
1 53.2
0 0.0
0
0.0
0
0.0
0 0.0 102
8598.0
0 0.0
0
0.0
24
140.6
6
23.4
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
30
164.0
0 0.0
0
0.0
9
230.9
1
14.5
1
13.2
0
0.0
0
0.0
0
0.0
1
15.5
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
12
274.1
0 0.0
0
0.0
8
168.1
3
42.0
0
0.0
0
0.0
2
52.4
0
0.0
2
32.5
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
15
295.0
0 0.0
0
0.0
8
426.2
1
27.4
0
0.0
2
109.3
4
113.1
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
15
676.0
0 0.0
0
0.0
3
152.4
0
0.0
2
420.9
3
202.4
3
150.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
11
925.7
0 0.0
0
0.0
3
724.3
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
3
724.3
0 0.0
0
0.0
1
269.4
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
1
269.4
0 0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
0
0.0
0 0.0
0
0.0
1
507.3
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
1
507.3
0 0.0
0
0.0
57 2619.2 11 107.3
3
434.1
5
311.7
9
315.5
0
0.0
3
48.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
88
3835.8
0 0.0
0
0.0
21
109.1
6
20.8
3
28.3
1
7.2
0
0.0
3
23.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
34
188.4
0 0.0
0
0.0
3
35.1
6
57.7
0
0.0
3
34.4
0
0.0
2
25.6
1
9.1
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
15
161.9
0 0.0
0
0.0
21
470.8
4
68.3
0
0.0
5
108.0
3
67.2
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
33
714.3
0 0.0
0
0.0
6
501.6
0
0.0
0
0.0
8
311.2
8
215.6
1 263.2
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
23
1291.6
0 0.0
0
0.0
7
589.9
0
0.0
2
261.0
1
97.8
3
180.6
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
13
1129.3
0 0.0
0
0.0
3
421.4
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
3
421.4
0 0.0
0
0.0
3
757.4
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
1
144.1
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
4
901.5
0 0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
0
0.0
0 0.0
0
0.0
0
0.0
0
0.0
0
0.0
1
260.7
0
0.0
0
0.0
1
441.4
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
2
702.1
0 0.0
0
0.0
64 2885.3 16 146.8
5
289.3 19
819.3 14
463.4
6 311.8
3
594.6
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0 127
5510.5
0 0.0
0
0.0
4
20.9 10
47.7
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
14
68.6
0 0.0
0
0.0
8
228.3
4
59.3
0
0.0
0
0.0
2
29.2
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
14
316.8
0 0.0
0
0.0
35
779.7
3
40.4
0
0.0
0
0.0
3
41.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
41
861.1
0 0.0
0
0.0
8
281.2
0
0.0
1
214.8
1
55.6
5
148.1
0
0.0
1
23.5
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
16
723.2
0 0.0
0
0.0
10 1193.3
0
0.0
1
215.0
1
188.2
3
169.3
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
15
1765.8
0 0.0
0
0.0
12 1837.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
12
1837.0
0 0.0
0
0.0
6 1931.6
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
6
1931.6
0 0.0
0
0.0
1
322.1
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
1
322.1
0 0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
0
0.0
0 0.0
0
0.0
84 6594.1 17 147.4
2
429.8
2
243.8 13
387.6
0
0.0
1
23.5
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0 119
7826.2
0 0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
0
0.0
0 0.0
0
0.0
10
101.9
7
37.3
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
17
139.2
0 0.0
0
0.0
21
619.4
0
0.0
0
0.0
0
0.0
3
65.4
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
24
684.8
0 0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
0
0.0
0 0.0
0
0.0
11
917.8
0
0.0
0
0.0
0
0.0
8
300.4
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
19
1218.2
0 0.0
0
0.0
1
146.2
0
0.0
0
0.0
0
0.0
1
100.6
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
2
246.8
0 0.0
0
0.0
2
530.1
0
0.0
0
0.0
1
281.5
0
0.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
3
811.6
0 0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
3 1088.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
3
1088.0
0 0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
0
0.0
0 0.0
0
0.0
45 2315.4
7
37.3
0
0.0
1
281.5 12
466.4
0
0.0
3 1088.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
68
4188.6
0 0.0 10 682.7 340 21292.1 60 536.9 13 1928.6 84 3871.7 75 2374.9 52 913.6 21 4641.8
1 53.2
0 0.0
0
0.0
0
0.0
0 0.0 656 36295.5
AVERAGE
Site Mesh
A1
10
A1
12
A1
15
A1
19
A1
24
A1
30
A1
38
A1
48
A1
60
A1
tot
A2
10
A2
12
A2
15
A2
19
A2
24
A2
30
A2
38
A2
48
A2
60
A2
tot
A3
10
A3
12
A3
15
A3
19
A3
24
A3
30
A3
38
A3
48
A3
60
A3
tot
A4
10
A4
12
A4
15
A4
19
A4
24
A4
30
A4
38
A4
48
A4
60
A4
tot
A5
10
A5
12
A5
15
A5
19
A5
24
A5
30
A5
38
A5
48
A5
60
A5
tot
A6
10
A6
12
A6
15
A6
19
A6
24
A6
30
A6
38
A6
48
A6
60
A6
tot
TOTAL
Table A 2. Results from area A in the test-fishing survey in Pikkala Bay in September 2011
09/09/2011
09/09/2011
09/09/2011
09/09/2011
09/09/2011
09/09/2011
09/09/2011
09/09/2011
09/09/2011
07/09/2011
07/09/2011
07/09/2011
07/09/2011
07/09/2011
07/09/2011
07/09/2011
07/09/2011
07/09/2011
07/09/2011
07/09/2011
07/09/2011
07/09/2011
07/09/2011
07/09/2011
07/09/2011
07/09/2011
07/09/2011
07/09/2011
07/09/2011
07/09/2011
07/09/2011
07/09/2011
07/09/2011
07/09/2011
07/09/2011
07/09/2011
06/09/2011
06/09/2011
06/09/2011
06/09/2011
06/09/2011
06/09/2011
06/09/2011
06/09/2011
06/09/2011
Date
06/09/2011
06/09/2011
06/09/2011
06/09/2011
06/09/2011
06/09/2011
06/09/2011
06/09/2011
06/09/2011
B6
B
0 0.0
0 0.0
0 0.0
0 0.0
TOTAL
AVERAGE
SD
2
0
1
0
19.5
3.3
5.3
0.0
232
39
25
41
8662.9
1443.8
659.7
1894.5
96 2761.1
16 460.2
7 322.3
24 1039.2
39
7
3
6
4740.2
790.0
489.4
606.8
73
12
6
14
8200.0
1366.7
663.9
2120.7
71
12
7
11
5631.3
938.6
762.8
626.1
0
0
0
0
0.0
0.0
0.0
0.0
42
7
4
9
8802.0
1467.0
960.2
2029.8
0
0
0
0
0.0
0.0
0.0
0.0
0
0
0
0
0.0
0.0
0.0
0.0
0.0
1 225.1
0 37.5
0 91.9
0
0
0
0
0
0.0
0.0
0.0
0.0
0 0.0
0 0.0
0 0.0
0 0.0
556
93
25
105
39042.1
6507.0
2154.9
8317.1
herring
sprat
perch
ruffe
pikeperch
roach
white bream
bleak
bream
rudd
vimba
TOTAL
abu bio abu bio
abu bio
abu bio
abu bio
abu bio
abu bio
abu bio
abu bio
abu bio
abu bio abu bio
0 0.0
1
7.0
6
61.7
0
0.0
1
14.0
0
0.0
0
0.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
8
82.7
0 0.0
0
0.0
2
27.0
1
21.4
3
146.6
0
0.0
0
0.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
6
195.0
0 0.0
0
0.0
15
412.3 11 173.3
2
125.9
0
0.0
2
36.8
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
30
748.3
0 0.0
0
0.0
4
226.8
5 151.3
1
66.6
0
0.0
1
75.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
11
519.7
0 0.0
0
0.0
4
265.6
2 123.7
2
310.7
3
571.0
4
279.6
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
15
1550.6
0 0.0
0
0.0
0
0.0
0
0.0
0
0.0
3
448.3
3
408.7
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
6
857.0
0 0.0
0
0.0
2
352.1
0
0.0
0
0.0
3
761.5
0
0.0
0
0.0
2
383.4
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
7
1497.0
0 0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
1
291.7
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
1
291.7
0 0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
0
0.0
0 0.0
1
7.0
33 1345.5 19 469.7
9
663.8
9 1780.8 10
800.1
0
0.0
3
675.1
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
84
5742.0
0 0.0
0
0.0
1
6.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
1
6.0
0 0.0
0
0.0
3
48.5
1
9.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
4
57.5
0 0.0
0
0.0
13
222.4
4
61.3
1
58.8
1
83.4
1
20.3
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
20
446.2
0 0.0
0
0.0
9
511.1
1
41.0
0
0.0 11
467.6
0
0.0
0
0.0
1
22.5
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
22
1042.2
0 0.0
0
0.0
1
56.4
1
46.6
4
379.9
5
351.5
6
376.8
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
17
1211.2
0 0.0
0
0.0
0
0.0
0
0.0
1
242.7
1
145.8
2
207.9
0
0.0
1
115.8
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
5
712.2
0 0.0
0
0.0
2
486.8
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
3
771.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
5
1257.8
0 0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
0
0.0
0 0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
1
525.7
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
1
525.7
0 0.0
0
0.0
29 1331.2
7 157.9
6
681.4 18 1048.3
9
605.0
0
0.0
6 1435.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
75
5258.8
0 0.0
0
0.0
5
27.3
4
63.9
1
18.1
0
0.0
1
39.4
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
11
148.7
0 0.0
1 12.5
4
60.8
8
86.7
3
62.6
0
0.0
0
0.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
16
222.6
0 0.0
0
0.0
19
388.8
8 144.3
0
0.0
5
142.0
2
39.5
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
34
714.6
0 0.0
0
0.0
6
249.8
0
0.0
0
0.0
2
87.6
6
261.7
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
14
599.1
0 0.0
0
0.0
2
116.4
0
0.0
1
154.4
4
604.7 11
662.5
0
0.0
1
51.3
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
19
1589.3
0 0.0
0
0.0
2
358.4
0
0.0
0
0.0
3
640.3
2
223.5
0
0.0
5
814.2
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
12
2036.4
0 0.0
0
0.0
0
0.0
0
0.0
2 1291.3
0
0.0
0
0.0
0
0.0
4
682.8
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
6
1974.1
0 0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
4 1133.3
0
0.0
1
387.3
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
5
1520.6
0 0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
2 1173.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
2
1173.0
0 0.0
1 12.5
38 1201.5 20 294.9
7 1526.4 14 1474.6 26 2359.9
0
0.0 13 3108.6
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0 119
9978.4
0 0.0
0
0.0
0
0.0
0
0.0
0
0.0
1
20.8
0
0.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
1
20.8
0 0.0
0
0.0
0
0.0
8 129.6
1
97.2
0
0.0
0
0.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
9
226.8
0 0.0
0
0.0
3
88.7
5 116.0
3
286.2
0
0.0
0
0.0
0
0.0
1
18.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
12
508.9
0 0.0
0
0.0
1
30.7
1
30.1
4
439.0
0
0.0
1
49.2
0
0.0
1
57.1
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
8
606.1
0 0.0
0
0.0
3
353.2
4 294.2
1
329.7
1
199.1
4
293.1
0
0.0
3
246.6
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
16
1715.9
0 0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
3
308.8
0
0.0
3
361.5
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
6
670.3
0 0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
0
0.0
0 0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
3
447.6
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
3
447.6
0 0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0 0.0
0 0.0
1 225.1
0
0.0
0 0.0
1
225.1
0 0.0
0
0.0
7
472.6 18 569.9
9 1152.1
2
219.9 11 1098.7
0
0.0
8
683.2
0 0.0
0 0.0
1 225.1
0
0.0
0 0.0
56
4421.5
0 0.0
0
0.0
29
166.9
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
29
166.9
0 0.0
0
0.0
11
116.0
4
48.6
1
14.0
0
0.0
1
13.4
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
17
192.0
0 0.0
0
0.0
23
445.0
4 180.9
0
0.0
4
83.6
1
22.1
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
32
731.6
0 0.0
0
0.0
11
426.7
0
0.0
1
95.7
1
35.7
1
55.9
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
14
614.0
0 0.0
0
0.0
6
473.4
0
0.0
0
0.0
8
744.4
1
50.1
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
15
1267.9
0 0.0
0
0.0
2
199.5
0
0.0
0
0.0
2
457.2
0
0.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
4
656.7
0 0.0
0
0.0
2
590.1
0
0.0
0
0.0
1
234.8
0
0.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
3
824.9
0 0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
2
503.4
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
2
503.4
0 0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
1
366.9
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
1
366.9
0 0.0
0
0.0
84 2417.6
8 229.5
2
109.7 16 1555.7
4
141.5
0
0.0
3
870.3
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0 117
5324.3
0 0.0
0
0.0
10
58.6
3
36.3
2
30.9
0
0.0
0
0.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
15
125.8
0 0.0
0
0.0
4
38.4
7 112.5
3
48.2
0
0.0
0
0.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
14
199.1
0 0.0
0
0.0
11
392.1 11 176.2
0
0.0
0
0.0
3
55.7
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
25
624.0
0 0.0
0
0.0
11
536.5
1
32.6
0
0.0
3
464.8
4
220.1
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
19
1254.0
0 0.0
0
0.0
2
78.6
0
0.0
0
0.0
9 1267.0
0
0.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
11
1345.6
0 0.0
0
0.0
2
384.4
2 681.6
0
0.0
2
388.9
0
0.0
0
0.0
1
194.4
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
7
1649.3
0 0.0
0
0.0
1
405.9
0
0.0
1
527.7
0
0.0
4
350.3
0
0.0
4
289.7
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
10
1573.6
0 0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
1
250.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
1
250.0
0 0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
3 1295.7
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
3
1295.7
tot
Site Mesh
B1
10
B1
12
B1
15
B1
19
B1
24
B1
30
B1
38
B1
48
B1
60
B1
tot
B2
10
B2
12
B2
15
B2
19
B2
24
B2
30
B2
38
B2
48
B2
60
B2
tot
B3
10
B3
12
B3
15
B3
19
B3
24
B3
30
B3
38
B3
48
B3
60
B3
tot
B4
10
B4
12
B4
15
B4
19
B4
24
B4
30
B4
38
B4
48
B4
60
B4
tot
B5
10
B5
12
B5
15
B5
19
B5
24
B5
30
B5
38
B5
48
B5
60
B5
tot
B6
10
B6
12
B6
15
B6
19
B6
24
B6
30
B6
38
B6
48
B6
60
Table A 3. Results from area B in the test-fishing survey in Pikkala Bay in September 2011
60
C
48
09/09/2011 C 6
C6
tot
TOTAL
AVERAGE
SD
Site Mesh
C1
10
C1
12
C1
15
C1
19
C1
24
C1
30
C1
38
C1
48
C1
60
C1
tot
C2
10
C2
12
C2
15
C2
19
C2
24
C2
30
C2
38
C2
48
C2
60
C2
tot
C3
10
C3
12
C3
15
C3
19
C3
24
C3
30
C3
38
C3
48
C3
60
C3
tot
C4
10
C4
12
C4
15
C4
19
C4
24
C4
30
C4
38
C4
48
C4
60
C4
tot
C5
10
C5
12
C5
15
C5
19
C5
24
C5
30
C5
38
C5
48
C5
60
C5
tot
C6
10
C6
12
C6
15
C6
19
C6
24
C6
30
C6
38
09/09/2011 C 6
09/09/2011
09/09/2011
09/09/2011
09/09/2011
09/09/2011
09/09/2011
09/09/2011
09/09/2011
09/09/2011
09/09/2011
09/09/2011
09/09/2011
09/09/2011
09/09/2011
09/09/2011
09/09/2011
07/09/2011
07/09/2011
07/09/2011
07/09/2011
07/09/2011
07/09/2011
07/09/2011
07/09/2011
07/09/2011
07/09/2011
07/09/2011
07/09/2011
07/09/2011
07/09/2011
07/09/2011
07/09/2011
07/09/2011
07/09/2011
06/09/2011
06/09/2011
06/09/2011
06/09/2011
06/09/2011
06/09/2011
06/09/2011
06/09/2011
06/09/2011
Date
06/09/2011
06/09/2011
06/09/2011
06/09/2011
06/09/2011
06/09/2011
06/09/2011
06/09/2011
06/09/2011
0
0
0
0
0
0.0
0.0
0.0
0.0
0.0
0 0.0
0
0
1
0
0
0
0.0
0.0
11.3
1.9
4.6
0.0
0.0
0
0.0
0
0.0
0
0.0
116 5763.2 27 530.0
450 24298.6 128 3664.4
75 4049.8 21 610.7
27
992.4 13 387.2
0
0
1
39
7
9
0
1
125.3
0.0
0
0.0
125.5 46 3980.2
3909.1 224 20191.1
651.5 37 3365.2
682.5 12 1205.4
0.0
0
3
40
7
6
1
0.0
351.4
2599.2
433.2
362.0
181.0
0
0
5
1
2
0
0.0
0.0
80.0
13.3
22.4
0.0
0
3
9
2
1
2
0.0
644.7
2746.2
457.7
277.6
624.7
0
0
0
0
0
0
0.0
0.0
0.0
0.0
0.0
0.0
0
0
0
0
0
0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0
0.0
0
0.0
2 592.7
0 98.8
1 154.6
0
0
0
1
0
0
0
0.0
0.0
5.6
0.9
2.3
0.0
0
0
0
0
0
0.0
0.0
0.0
0.0
0.0
0 0.0
0
196
899
150
28
4
0.0
11395.0
58098.2
9683.0
1317.4
931.0
herring
sprat
perch
ruffe
pikeperch
roach
white bream
bleak
bream
rudd
vimba
TOTAL
abu bio abu bio
abu bio
abu bio
abu bio
abu bio
abu bio
abu bio
abu bio
abu bio
abu bio abu bio
0 0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
0
0.0
0 0.0
0
0.0
2
33.0
4
98.6
1
80.2
0
0.0
1
42.4
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
8
254.2
0 0.0
0
0.0
35 1107.4
8 168.3
2
150.0
3
69.9
6
137.1
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
54
1632.7
0 0.0
0
0.0
16 1311.6
4 130.9
7
797.9
2
132.7
0
0.0
0
0.0
1
751.7
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
30
3124.8
0 0.0
0
0.0
4 1135.5
1
66.2
0
0.0 10
916.0
5
301.6
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
20
2419.3
0 0.0
0
0.0
1
149.3
0
0.0
0
0.0
5
724.6
1
107.9
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
7
981.8
0 0.0
0
0.0
2
440.1
0
0.0
0
0.0
4
796.5
2
262.3
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
8
1498.9
0 0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0 0.0
0 0.0
1 331.5
0
0.0
0 0.0
1
331.5
0 0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
0
0.0
0 0.0
0
0.0
60 4176.9 17 464.0 10 1028.1 24 2639.7 15
851.3
0
0.0
1
751.7
0 0.0
0 0.0
1 331.5
0
0.0
0 0.0 128 10243.2
0 0.0
0
0.0
2
13.5
6
90.2
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
8
103.7
0 0.0
1 11.3
3
93.5
9 142.8
2
179.4
0
0.0
0
0.0
1
26.4
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
16
453.4
0 0.0
0
0.0
21
475.0 20 420.7
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
41
895.7
0 0.0
0
0.0
8
334.5
5 162.2
2
156.2
4
269.7
0
0.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
19
922.6
0 0.0
0
0.0
8
806.4
0
0.0
1
234.3 17 1796.9
0
0.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
26
2837.6
0 0.0
0
0.0
1
131.0
0
0.0
0
0.0
6
851.7
1
176.2
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
8
1158.9
0 0.0
0
0.0
5 1424.2
1
26.5
1
865.5
0
0.0
0
0.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
7
2316.2
0 0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
0
0.0
0 0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
0
0.0
0 0.0
1 11.3
48 3278.1 41 842.4
6 1435.4 27 2918.3
1
176.2
1
26.4
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0 125
8688.1
0 0.0
0
0.0
11
61.6
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
1
5.6
0 0.0
12
67.2
0 0.0
0
0.0
3
290.5
0
0.0
0
0.0
3
97.4
1
10.1
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
7
398.0
0 0.0
0
0.0
28
517.2
1
16.4
0
0.0 16
350.8
1
17.7
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
46
902.1
0 0.0
0
0.0
10
340.1
2
62.9
0
0.0 17
819.9
0
0.0
0
0.0
1
15.2
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
30
1238.1
0 0.0
0
0.0
5
549.4
0
0.0
0
0.0 17 1357.7
0
0.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
22
1907.1
0 0.0
0
0.0
3
410.0
0
0.0
0
0.0
1
104.2
0
0.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
4
514.2
0 0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
0
0.0
0 0.0
0
0.0
3
734.5
0
0.0
0
0.0
2 2604.6
0
0.0
0
0.0
1
414.6
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
6
3753.7
0 0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0 0.0
0 0.0
1 261.2
0
0.0
0 0.0
1
261.2
0 0.0
0
0.0
63 2903.3
3
79.3
0
0.0 56 5334.6
2
27.8
0
0.0
2
429.8
0 0.0
0 0.0
1 261.2
1
5.6
0 0.0 128
9041.6
0 0.0
0
0.0
3
41.7
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
3
41.7
0 0.0
0
0.0
8
172.5
2
34.3
3
200.7
1
134.2
0
0.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
14
541.7
0 0.0
0
0.0
35 1005.7 11 210.8
0
0.0
3
60.8
1
19.8
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
50
1297.1
0 0.0
0
0.0
0
0.0
9 278.1 18
974.9
3
174.7
3
218.1
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
33
1645.8
0 0.0
0
0.0
11 1535.4
0
0.0
1
144.5 17 1900.5
9
581.9
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
38
4162.3
0 0.0
0
0.0
2
479.3
0
0.0
0
0.0
6
960.2
1
84.7
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
9
1524.2
0 0.0
0
0.0
4
682.0
0
0.0
0
0.0
1
230.5
0
0.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
5
912.5
0 0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
1
250.4
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
1
250.4
0 0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
1
373.2
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
1
373.2
0 0.0
0
0.0
63 3916.6 22 523.2 22 1320.1 31 3460.9 14
904.5
0
0.0
2
623.6
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0 154 10748.9
0 0.0
0
0.0
5
26.3
0
0.0
0
0.0
0
0.0
0
0.0
3
34.6
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
8
60.9
0 0.0
0
0.0
17
331.8 13 157.0
0
0.0
2
87.2
0
0.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
32
576.0
0 0.0
0
0.0
36
796.2
0
0.0
0
0.0 16
343.4
0
0.0
1
19.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
53
1158.6
0 0.0
0
0.0
27 1316.6
0
0.0
0
0.0 12
548.7
0
0.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
39
1865.3
0 0.0
0
0.0
13 1215.4
0
0.0
0
0.0
9
686.0
5
288.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
27
2189.4
0 0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
0
0.0
0 0.0
0
0.0
0
0.0
5 1068.5
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
5
1068.5
0 0.0
0
0.0
1
399.6
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
1
296.4
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
2
696.0
0 0.0
0
0.0
1
174.6
0
0.0
0
0.0
1
192.1
0
0.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
2
366.7
0 0.0
0
0.0 100 4260.5 18 1225.5
0
0.0 40 1857.4
5
288.0
4
53.6
1
296.4
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0 168
7981.4
0 0.0
0
0.0
10
79.8
1
13.0
0
0.0
1
44.5
0
0.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
12
137.3
0 0.0
0
0.0
29 1018.0
6
56.8
0
0.0
2
72.7
0
0.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
37
1147.5
0 0.0
0
0.0
47 1709.3 18 394.0
1
125.5
1
107.0
1
128.8
0
0.0
1
20.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
69
2484.6
0 0.0
0
0.0
22 1389.1
1
28.3
0
0.0 15 1005.6
1
41.6
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
39
2464.6
0 0.0
0
0.0
3
233.1
1
37.9
0
0.0 22 1988.9
0
0.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
26
2259.9
0 0.0
0
0.0
2
439.0
0
0.0
0
0.0
4
636.2
0
0.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
6
1075.2
0 0.0
0
0.0
3
894.9
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
3
894.9
Table A 4. Results from area C in the test-fishing survey in Pikkala Bay in September 2011
38
48
60
D
30
08/09/2011 D 6
08/09/2011 D 6
08/09/2011 D 6
D6
tot
TOTAL
AVERAGE
SD
Site Mesh
D1
10
D1
12
D1
15
D1
19
D1
24
D1
30
D1
38
D1
48
D1
60
D1
tot
D2
10
D2
12
D2
15
D2
19
D2
24
D2
30
D2
38
D2
48
D2
60
D2
tot
D3
10
D3
12
D3
15
D3
19
D3
24
D3
30
D3
38
D3
48
D3
60
D3
tot
D4
10
D4
12
D4
15
D4
19
D4
24
D4
30
D4
38
D4
48
D4
60
D4
tot
D5
10
D5
12
D5
15
D5
19
D5
24
D5
30
D5
38
D5
48
D5
60
D5
tot
D6
10
D6
12
D6
15
D6
19
D6
24
08/09/2011 D 6
08/09/2011
08/09/2011
08/09/2011
08/09/2011
08/09/2011
08/09/2011
08/09/2011
08/09/2011
08/09/2011
08/09/2011
08/09/2011
08/09/2011
08/09/2011
08/09/2011
08/09/2011
08/09/2011
08/09/2011
08/09/2011
08/09/2011
08/09/2011
08/09/2011
08/09/2011
08/09/2011
07/09/2011
07/09/2011
07/09/2011
07/09/2011
07/09/2011
07/09/2011
07/09/2011
07/09/2011
07/09/2011
07/09/2011
07/09/2011
07/09/2011
07/09/2011
07/09/2011
07/09/2011
07/09/2011
07/09/2011
07/09/2011
Date
06/09/2011
06/09/2011
06/09/2011
06/09/2011
06/09/2011
06/09/2011
06/09/2011
06/09/2011
06/09/2011
0
0
0
0
2
0
1
0.0
0.0
0.0
0.0
5.2
0.9
2.1
0 0.0
0
0
0
0
1
0
0
0
0.0
0.0
0.0
0.0
12.6
2.1
5.1
0.0
0.0
0
0.0
0
0.0
0
0.0
2
549.0
0
0.0
0
0.0
0
0.0
10
877.6 10 140.4
237 10132.5 134 1779.7
40 1688.8 22 296.6
27 1039.2 13 143.2
0
0
0
0
1
27
5
4
0
0.0
0.0
0.0
12.5
1485.8
247.6
320.3
0.0
1010.1
0
0.0
1
213.3
0
0.0
22 1810.4
98 10172.5
16 1695.4
10
709.2
6
0
0
0
12
86
14
3
0
0.0
0.0
0.0
496.5
5330.0
888.3
353.3
0.0
0
0
0
0
15
3
4
0
0.0
0.0
0.0
0.0
178.3
29.7
43.6
0.0
0
0
0
1
18
3
4
0
0.0
0.0
0.0
76.9
5135.8
856.0
1457.4
0.0
0
0
0
0
0
0
0
0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0 0.0
0 0.0
0 0.0
0 0.0
1 14.3
0 2.4
0 5.8
0
0
0
0
0
0
0
0
0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0
0
0
0
0
0
0
0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0
0
0
0
4
1
1
0.0
0.0
0.0
0.0
2.2
0.4
0.6
0 0.0
0
3
0
56
623
104
41
6
0.0
762.3
0.0
3414.3
34248.9
5708.2
2323.6
1010.1
herring
sprat
perch
ruffe
pikeperch
roach
white bream
bleak
bream
rudd
vimba
TOTAL
abu bio abu bio
abu bio
abu bio
abu bio
abu bio
abu bio
abu bio
abu bio
abu bio
abu bio abu bio
0 0.0
0
0.0
34
185.2
1
5.2
2
14.8
0
0.0
0
0.0
5
56.8
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
1 0.8
43
262.8
0 0.0
0
0.0
10
162.2 23 267.1
2
40.3
0
0.0
1
8.8
3
30.1
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
39
508.5
0 0.0
0
0.0
27
513.6 12 165.2
0
0.0
1
24.0
1
15.0
1
13.6
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
42
731.4
0 0.0
0
0.0
3
121.1
0
0.0
4
392.6
0
0.0
2
53.6
1
13.4
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
10
580.7
0 0.0
0
0.0
4
273.0
0
0.0
2
315.1
6
835.2
8
585.2
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
20
2008.5
0 0.0
0
0.0
4
615.5
0
0.0
0
0.0
3
453.3
2
208.6
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
9
1277.4
0 0.0
0
0.0
4
888.7
0
0.0
0
0.0
1
231.4
1
139.8
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
6
1259.9
0 0.0
0
0.0
2
359.5
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
2
359.5
0 0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
0
0.0
0 0.0
0
0.0
88 3118.8 36 437.5 10
762.8 11 1543.9 15 1011.0 10 113.9
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
1 0.8 171
6988.7
0 0.0
0
0.0
14
111.2
4
34.2
4
33.3
0
0.0
0
0.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
22
178.7
0 0.0
0
0.0
1
12.0 18 198.2
2
23.3
2
22.0
2
26.6
3
38.3
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
28
320.4
0 0.0
0
0.0
16
273.2 16 247.4
0
0.0
3
54.9
0
0.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
35
575.5
0 0.0
0
0.0
7
274.7
2
19.8
0
0.0
5
501.8
8
509.8
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
22
1306.1
0 0.0
0
0.0
2
112.8
0
0.0
0
0.0
1
63.7
0
0.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
3
176.5
0 0.0
0
0.0
1
86.6
0
0.0
0
0.0
3
557.9
0
0.0
0
0.0
1
83.2
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
5
727.7
0 0.0
0
0.0
2
461.7
0
0.0
1
476.4
0
0.0
0
0.0
0
0.0
2
586.3
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
5
1524.4
0 0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
2
787.7
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
2
787.7
0 0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
0
0.0
0 0.0
0
0.0
43 1332.2 40 499.6
7
533.0 14 1200.3 10
536.4
3
38.3
5 1457.2
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0 122
5597.0
2 5.2
1 12.6
4
21.9
1
11.5
2
21.4
0
0.0
0
0.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
10
72.6
0 0.0
0
0.0
3
186.3
9
88.9
1
20.1
0
0.0
1
12.0
0
0.0
0
0.0
0 0.0
1 14.3
0
0.0
0
0.0
0 0.0
15
321.6
0 0.0
0
0.0
22
626.3
6 106.3
0
0.0
0
0.0
4
70.2
1
15.3
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
33
818.1
0 0.0
0
0.0
6
707.7
0
0.0
0
0.0
4
152.7
1
61.2
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
11
921.6
0 0.0
0
0.0
5
563.6
1
11.3
0
0.0
4
425.3
6
309.7
0
0.0
2
174.4
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
18
1484.3
0 0.0
0
0.0
3
798.2
0
0.0
0
0.0
5
841.6
1
123.2
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
9
1763.0
0 0.0
0
0.0
0
0.0
0
0.0
0
0.0
1
280.0
2
249.0
0
0.0
2
383.6
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
5
912.6
0 0.0
0
0.0
0
0.0
0
0.0
1
66.8
1
200.5
0
0.0
0
0.0
4 1296.9
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
6
1564.2
0 0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
3 1734.8
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
3
1734.8
2 5.2
1 12.6
43 2904.0 17 218.0
4
108.3 15 1900.1 15
825.3
1
15.3 11 3589.7
0 0.0
1 14.3
0
0.0
0
0.0
0 0.0 110
9592.8
0 0.0
0
0.0
1
4.6
2
14.0
2
22.7
0
0.0
0
0.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
5
41.3
0 0.0
0
0.0
1
15.0
6
73.0
2
29.0
0
0.0
0
0.0
1
10.8
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
10
127.8
0 0.0
0
0.0
9
162.8
7 125.6
0
0.0
0
0.0
1
16.1
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
3 1.4
20
305.9
0 0.0
0
0.0
3
98.6
3
79.1
0
0.0
0
0.0
2
93.1
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
8
270.8
0 0.0
0
0.0
4
419.8
0
0.0
0
0.0
0
0.0 10
605.3
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
14
1025.1
0 0.0
0
0.0
1
231.0
0
0.0
0
0.0
4
824.9
5
732.3
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
10
1788.2
0 0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
0
0.0
0 0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
0
0.0
0 0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
0
0.0
0 0.0
0
0.0
19
931.8 18 291.7
4
51.7
4
824.9 18 1446.8
1
10.8
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
3 1.4
67
3559.1
0 0.0
0
0.0
5
26.3
4
44.4
0
0.0
3
26.4
0
0.0
0
0.0
1
12.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
13
109.1
0 0.0
0
0.0
5
90.3
7
84.0
1
17.5
3
29.9
2
18.8
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
18
240.5
0 0.0
0
0.0
18
355.4
0
0.0
0
0.0
4
73.1
4
88.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
26
516.5
0 0.0
0
0.0
3
102.8
2
64.1
0
0.0
8
413.0
5
229.4
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
18
809.3
0 0.0
0
0.0
2
247.0
0
0.0
0
0.0
9
930.2
3
364.2
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
14
1541.4
0 0.0
0
0.0
1
146.3
0
0.0
0
0.0
2
515.4
0
0.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
3
661.7
0 0.0
0
0.0
0
0.0
0
0.0
0
0.0
2
684.7
2
313.6
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
4
998.3
0 0.0
0
0.0
0
0.0
0
0.0
0
0.0
1
220.2
0
0.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
1
220.2
0 0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
0
0.0
0 0.0
0
0.0
34
968.1 13 192.5
1
17.5 32 2892.9 16 1014.0
0
0.0
1
12.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
97
5097.0
0 0.0
0
0.0
3
21.7
4
62.0
1
12.5
3
60.2
2
39.4
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
13
195.8
0 0.0
0
0.0
1
13.7
4
50.9
0
0.0
1
15.5
2
22.7
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
8
102.8
0 0.0
0
0.0
0
0.0
2
27.5
0
0.0
4
83.3
0
0.0
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
6
110.8
0 0.0
0
0.0
3
131.0
0
0.0
0
0.0
4
176.0
5
182.8
0
0.0
0
0.0
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
12
489.8
0 0.0
0
0.0
1
162.2
0
0.0
0
0.0
3
252.0
3
251.6
0
0.0
1
76.9
0 0.0
0 0.0
0
0.0
0
0.0
0 0.0
8
742.7
Table A 5. Results from area D in the test-fishing survey in Pikkala Bay in September 2011
Appendix B.
Table B 1. List of literature concerning Pikkala Bay
Chronology
1960’s
1970’s
1980’s
Reference
Dahlström, H. & Sormunen, T., 1968. Strömsbynlahden
makeanvesiallashankkeeseen liittyvä kalatalousselvitys. Kalataloussäätiö,
Helsinki, 6 pp.
Dahlström, H., Korhonen, M. & Sormunen, T., 1968. Lausunto
Pikkalanjoen padon vaikutuksesta kalatalouteen. Kalataloussäätiön
monistettuja julkaisuja n:o 22, 33 pp.
Anttila, R. & Niinimäki, J., 1971. Selvitys Kirkkonummen kunnan
jätevesien johtamisesta Suomenlahteen aiheutuvasta kalataloudellisesta
vahingosta sekä arvio rantavahingoista. Kala- ja Vesitutkimus Oy, 48 pp.
Imatran Voima Oy, 1976. Tutkimustuloksia Vikträskin ja Pikkalanjoen
seudun laadusta 1974–1976.
Keskuslaboratorio, 1970. Oy Nokia Ab:n tilaama kalataloudellinen
tutkimus Pikkalanlahden alueelta.
Oy Vesi-Hydro Ab, 1972. Lausunto Porkkalan tehtaan jätevesien
purkualueen tilasta. (Suomen Sokeri Oy).
Type of source
Information
Access
report
fish, fishery
yes
expert’s report
bream migration,
fishery
yes
report
fish, fishery, littoral
quality
no
survey
environmental
condition
no
survey
fish, fishery
no
expert’s report
Oy Vesi-Hydro Ab, 1974. Jäteveden, jäähdytysveden sekä merialueen
tarkkailu vuonna 1973. (Suomen Sokeri Oy).
obligatory
monitoring report
Oy Vesi-Hydro Ab, 1974. Pikkalanlahden tarkkailu 1974. (Kirkkonummen
kunta).
obligatory
monitoring report
Oy Vesi-Hydro Ab, 1975–2000. Pikkalanlahden yhteistarkkailu.
obligatory
monitoring report
Oy Vesi-Hydro Ab, 1975. Jäteveden, jäähdytysveden ja Pikkalanlahden
tarkkailu vuonna 1974. (Suomen Sokeri Oy).
obligatory
monitoring report
environmental
condition
sewage,
environmental
condition
environmental
condition
water quality,
environmental
condition
sewage,
environmental
condition
Oy Vesi-Hydro Ab, 1975. Selvitys Vikträskin ja Pikkalanjoen
kalataloudellisesta nykytilasta. (Imatran Voima Oy).
Oy Vesi-Hydro Ab, 1977. Selostus Kirkkonummen kunnan
jätevesikuormituksesta vuosina 1969–1977 sekä arvio jätevesien
johtamisesta aiheutuneista vahingoista.
Oy Vesi-Hydro Ab, 1978. Lausunto Pikkalanlahden kalastosta ja
kalastuksesta. (Oy Nokia Ab, Suomen Sokeri Oy).
Parkkonen, L., 1978. Pikkalanselän pohjaeläimistö. Pro gradu-tutkielma,
Helsingin yliopisto, 70 pp. + appendices.
Oy Vesi-Hydro Ab, 1979. Pikkalanlahden kalataloudellinen
tarkkailututkimus 1978–1979. (Kirkkonummen kunta).
Ryhänen, R. & Voipio, A., 1971. Vesistöjen suojelun ja käytön ekologinen
tutkimus. Osa b: Rannikkomeri, liite n:o 10: Vesialueen tila Porkkalan
lahdella. Merentutkimuslaitoksen sisäinen raportti 25.5.1971, Moniste, 8
pp.
Bruun, J.-E., Forsskåhl, M., Grönlund, L., Leppänen, J.-M., Niemi, Å. &
Tamelander, G., 1980. Environmental condition and biological production
in the sea off Kopparnäs, a projected power plant site (S coast of Finland)
in 1975–77. Meri 6, p. 8–38.
Hildén, M. 1986, Braxens, Abramis brama (L.), vandringar och årliga
överlevnadsgrad i finska kustvatten enligt märkningsresultat.
Examensarbete, Helsingfors universitet., 63 pp.
Langi, A., 1986. Pikkalanlahden vedenlaatu (1974–1984) ja sen
parantamismahdollisuudet. Moniste 15.1.1986, 4 pp.
Länsi-Uudenmaan vesiensuojeluyhdistys, 1983. Lausunto Pikkalanjoen
säännöstelyn aiheuttamista vaikutuksista kalakantoihin.
Leppänen. J.-M., Bruun, J.-E. & Tamelander, G., 1976. Kopparnäsin
saaristo- ja merialueen tarkkailu 1975. Merentutkimuslaitos, moniste, 33
pp.
Luttinen, R., 1989. Makrofyyttikasvillisuus Pikkalanlahden tilan
indikaattorina.Vesi- ja ympäristöhallituksen monistesarja nro 198, 87 pp. +
appendices.
Marttinen, M. & Wessman, H., 1987. Siuntionjoen vesistöalueen
kalatalousselvitys. Uudenmaan kalastuspiirin kalastustoimisto, Tiedotus
nro 3
Oy Vesi-Hydro Ab, 1980. Porkkalan tehdas. Jätevesien purkuvesistön
veden laatu ja limnologinen tila vuosina 1973–1979. (Suomen Sokeri Oy).
Oy Vesi-Hydro Ab, 1980. Pikkalan tehdas. Jätevesien purkualueen
pohjalietetutkimus v. 1980. (Oy Nokia Ab).
no
no
no
no
no
report
fish, fishery
no
report
sewage load, water
quality
no
expert’s report
fish, fishery
no
academic thesis
benthos
yes
obligatory
monitoring report
fish, fishery
no
internal report
environmental
condition
no
scientific
publication
environmental
condition
yes
academic thesis
bream migration
yes
advisory report
water quality
yes
expert’s report
fish stocks
no
report
environmental
condition
yes
survey
macrophyte
vegetation
yes
survey
fish, fishery
yes
report
water quality
no
report
sediment
no
1980’s
1990’s
2000’s
Oy Vesi-Hydro Ab, 1983. Pikkalan tehdas. Pohjalietetarkkailu 1982. (Oy
Nokia Ab).
Reinikainen, T. Leskinen, E. & Villa, L., 1986. Perifytonin kasvu ja veden
ravinnepitoisuus Pikkalanlahden kuormituksen ilmentäjänä kesällä 1984.
Vesi- ja ympäristöhallituksen monistesarja nro 3, 23 pp. + appendices.
Sauvonsaari, J., 1982. Pikkalanlahden kalataloudellinen tarkkailu v. 1982.
Oy Vesi-Hydro Ab, 21 pp. + appendices.
Sauvonsaari, J., 1984. Tarkkaliuohjelma säännöstelyn vaikutuksista
Pikkalanjoen vesistön kalastoon. Oy Vesi-Hydro Ab.
Sauvonsaari, J., 1988. Pikkalanlahden kalataloudellinen yhteistarkkailu
1987. Oy Vesi-Hydro Ab.
Mettinen, A., 1997. Pikkalanlahden pohjaeläintutkimus vuonna 1996
Siuntion kunnan Pikkalan keskuspuhdistamon kalataloudellisen tarkkailun
osana. Länsi Uudenmaan Vesi ja Ympäristö ry., Julkaisu 70,11 pp. +
appendices.
Ranta, E., 1996. Pikkalan keskuspuhdistamon kalataloudellinen tarkkailu
vuonna 1996. Länsi Uudenmaan Vesi ja Ympäristö ry., Julkaisu 71,15 pp.
+ appendices.
Ranta, E., 1996. Siuntionjoen vesistön yhteistarkkailu 1995. Länsi
Ranta, E. & Jokinen, O., 1992. Siuntionjoen vesistön yhteistarkkailun
yhteenveto vuodelta 1991. Länsi Uudenmaan Vesi ja Ympäristö ry.,
Julkaisu 15.
Julkaisu 26.
Julkaisu 35.
Julkaisu 44.
Julkaisu 50.
Julkaisu 68.
Julkaisu 82.
Sauvonsaari, J., 1992. Pikkalanjoen ja Vikträskin säännöstelyä koskeva
kalaloudellinen tarkkailuvelvoite. Oy Vesi-Hydro Ab.
Sauvonsaari, J. & Vaajakorpi, H., 1991. Pikkalanlahden kalataloudellinen
yhteistarkkailu 1991. Oy Vesi-Hydro Ab, 34 pp. + appendices.
yhteistarkkailu 1995. Oy Vesi-Hydro Ab, 37 pp. + appendices.
Enckell, E., Airola, H., Tornivaara-Ruikka, R., Villa, L. & Salasto, R.,
(eds.) 2002. Ympäristön tila muuttuu: Uudenmaan ympäristökeskuksen
seurantaraportti. Alueelliset ympäristöjulkaisut 269, 96 pp.
Holmberg, R. & Mettinen, A., 2006. Pikkalanlahden yhteistarkkailun
Julkaisu 163.
Kukkonen, J., Mettinen, A. & Muttilainen, A., 2002. Pikkalan
keskuspuhdistamon kalataloudellinen tarkkailu vuonna 2000. Länsi
Uudenmaan Vesi ja Ympäristö ry., Julkaisu 122, 17 pp. + appendices.
LUVY, 2007. Pikkalanlahden yhteistarkkailuohjelma vuodesta 2007
lähtien. Osa A Vesistötarkkailu, Osa B Pikkalanlahden kalataloudellinen
tarkkaliu. Länsi-Uudenmaan vesi ja ympäristö ry 9.5.2007, part A 13 pp. +
appendices, part B 13 pp. + appendices.
Mettinen, A., 2002. Pikkalanlahden pohjaeläintutkimus vuonna 2000
Siuntion kunnan Pikkalan keskuspuhdistamon kalataloudellisen tarkkailun
osana. Länsi Uudenmaan Vesi ja Ympäristö ry., Julkaisu 123, 11 pp. +
appendices.
Mettinen, A., 2002. Siuntionjoen vesistön yhteistarkkailun yhteenveto
vuodelta 2001. Länsi Uudenmaan Vesi ja Ympäristö ry., Julkaisu 128.
report
sediment
no
survey
periphyton, nutrients
yes
obligatory
monitoring report
fish, fishery, benthos
yes
monitoring plan
fish, fishery
yes
obligatory
monitoring report
yes
obligatory
monitoring report
benthos
yes
obligatory
monitoring report
fish, fishery
yes
obligatory
monitoring report
riverine discharge
yes
obligatory
monitoring report
riverine discharge
yes
obligatory
monitoring report
riverine discharge
yes
obligatory
monitoring report
riverine discharge
yes
obligatory
monitoring report
riverine discharge
yes
obligatory
monitoring report
riverine discharge
yes
obligatory
monitoring report
riverine discharge
yes
obligatory
monitoring report
riverine discharge
yes
fish, fishery
yes
yes
yes
riverine discharge
yes
obligatory
monitoring report
water quality,
environmental
condition,
phytoplankton
yes
obligatory
monitoring report
fish, fishery
yes
obligatory
monitoring
program plan
monitoring
yes
obligatory
monitoring report
benthos
yes
obligatory
monitoring report
riverine discharge
yes
obligatory
monitoring report
obligatory
monitoring report
obligatory
monitoring report
environmental
authorities
puplication
Mettinen, A., 2002. Pikkalanlahden yhteistarkkailun yhteenveto vuodelta
2001. Länsi Uudenmaan Vesi ja Ympäristö ry., Julkaisu 126
obligatory
monitoring report
2002. Länsi Uudenmaan Vesi ja Ympäristö ry., Julkaisu 136, 30 pp. +
appendices.
obligatory
monitoring report
water quality,
environmental
condition
water quality,
environmental
condition,
phytoplankton
yes
yes
2000’s
obligatory
monitoring report
appendices.
obligatory
monitoring report
appendices.
vuosilta 2003 ja 2004. Vesistön tila vuosina 1989–2004. Länsi Uudenmaan
Vesi ja Ympäristö ry., Julkaisu 153, 80 pp. + appendices.
vuodelta 2006. Länsi Uudenmaan Vesi ja Ympäristö ry., Julkaisu 175, 55
pp. + appendices.
2010’s
obligatory
monitoring report
water quality,
environmental
condition,
phytoplankton
water quality,
environmental
condition
yes
yes
yes
obligatory
monitoring report
riverine discharge
yes
obligatory
monitoring report
riverine discharge
yes
obligatory
monitoring report
riverine discharge
yes
appendices.
obligatory
monitoring report
appendices.
obligatory
monitoring report
pp. + appendices.
appendices.
pp. + appendices.
Mettinen, A. & Jokinen, O., 2001. Siuntionjoen vesistön yhteistarkkailun
Ranta, E, & Jokinen, O., 2000. Siuntionjoen vesistön yhteistarkkailun
Julkaisu 96.
yhteistarkkailu v. 2000. Oy Vesi-Hydro Ab, 21 pp. + appendices.
Suhonen, V., 2007. Pikkalanlahden kalataloudellinen yhteistarkkailu.
Kalastuskirjanpidon tulosten yhteenveto vuosilta 2003–2006.
Suunnittelukeskus Oy, 20 pp. + appendices.
Valjus, J., 2008. Pikkalanlahden kalataloudellinen yhteistarkkailu vuonna
appendices.
Wikström, M. & Kamppi, K., 2004. Pikkalanlahden kalataloudellinen
yhteistarkkailu vuonna 2003. Suunnittelukeskus Oy, 29 pp. + appendices.
Långström, S. & Sanberg-Kilpi, E., 2010. Vård- och nyttjandeplan
Kyrkslätt-Porkkala fiskeområde. förslag till stämman 26.4.2010.
Yrkeshögskolan Novia, 52 pp. + appendix.
Mettinen, A., 2010. Pikkalanlahden pohjaeläin ja kasviplanktontutkimus
vuonna 2007. Pistekuormittajien yhteistarkkailututkimus. Länsi
Uudenmaan Vesi ja Ympäristö ry., Julkaisu 203, 50 pp. + appendices.
Setälä, J., 2011. Piloottihanke vajaasti hyödynnetyn kalan käytön
edistämiseksi. Vuosiraportti 2010. RKTL:n työraportteja 5/2011, Riista- ja
kalatalouden tutkimuslaitos, Helsinki, 33 pp.
Suonpää, A., 2011. Pikkalanlahden yhteistarkkailun yhteenveto 2010.
Länsi Uudenmaan Vesi ja Ympäristö ry., Julkaisu 218, 30 pp. +
appendices.
Suonpää, A. & Mettinen, A., 2010. Pikkalanlahden yhteistarkkailun
Valjus, J., 2010. Siuntionjoen vesistön yhteistarkkailun yhteenveto. Laaja
tarkkailuvuosi 2009. Länsi Uudenmaan Vesi ja Ympäristö ry., Julkaisu
Valjus, J., 2011. Siuntionjoen vesistön yhteistarkkailun yhteenveto. Suppea
tarkkailuvuosi 2010. Länsi Uudenmaan Vesi ja Ympäristö ry., Julkaisu
riverine discharge
water quality,
environmental
condition,
phytoplankton
water quality,
environmental
condition,
phytoplankton
yes
yes
obligatory
monitoring report
riverine discharge
yes
obligatory
monitoring report
water quality,
environmental
condition
yes
obligatory
monitoring report
riverine discharge
yes
obligatory
monitoring report
riverine discharge
yes
obligatory
monitoring report
riverine discharge
yes
obligatory
monitoring report
yes
obligatory
monitoring report
fishery
yes
obligatory
monitoring report
fish, fishery
yes
obligatory
monitoring report
yes
plan
fishery
yes
obligatory
monitoring report
benthos,
phytoplankton
yes
report
cyprinid utilisation,
reduction fishery
yes
obligatory
monitoring report
obligatory
monitoring report
water quality,
environmental
condition
water quality,
environmental
condition
yes
yes
obligatory
monitoring report
riverine discharge
yes
obligatory
monitoring report
riverine discharge
yes

Potential ecological effects of cyprinid reduction fishery in Pikkala Bay

Transcription

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