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Functional diversity and assembly rules of the Baltic Sea fish assemblages
PhD projectLaurène Pécuchet
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1st study:Environmental filtering driving the traitscomposition of the Baltic fish community
Laurène Pécuchet, Martin Lindegren and Anna Törnroos
12-02-2015 [email protected]
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Mouillot et al., 2007
Trait-based approach
Species enter and persist in local communities because of their ecological fit to local conditions. Mechanisms influencing patterns of community assembly act on the ecological similarities and/or differences of organisms
Mechanisms influencing patterns of community assembly
12-02-2015 [email protected]
The Baltic Sea – a strong salinity gradient
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Hypothesis: Abiotic control of the biological community
Studied area – bottom salinity contour (PSU) from CTD data, and representations of the ICES squares in the Baltic Sea
12-02-2015 [email protected]
Baltic International Trawl Survey (BITS)
Number of hauls performed from 2003 to 2014
From this dataset we derived the occurence and mean CPUE of Species per ICES square for the period 2003-2014
2003-2014, February - March
For each haul, the species are sorted and counted (CPUE/h) by length class
512-02-2015 [email protected]
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Species and traits database
DIET
MEAN LENGTH
BODY SHAPE
CAUDAL SHAPE
FECUNDITY
AGE AT MATURITY
6 traits characterising the diet, the demography, the habitat and the morphology.
3 traits are categorical. 3 traits are continuous.
Traits values from literature primarily and secondarily through species fact sheet (FAO/FishBase)
42 strictly demersal (10 pelagics eliminated)
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Investigate potential abiotic drivers of the diversity indices:• Salinity• Oxygen• Temperature• Depth• Sediment
Diversity pattern of the Baltic Sea: Species vs Functional richness
Metrics Best gam model Dev.expl
Species Richness Temp.* + Salinity*** + Oxy*** + habitat*** 92.5% Salinity 83.3
Functional Rich. Salinity*** + Oxygen* + habitat*** 67.1% Salinity 51.8
Functional Richness : The amount of niche space filled by species in the community (Convex Hull)
12-02-2015 [email protected]
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Limiting similarity
Niche filtering
Neutral
Species Richness
Fu
nctio
na
l R
ich
ne
ss
Limiting similarity
Functional Dissimilarity
Co
-occu
rre
nce
in
de
x
Niche filtering
Functional Dissimilarity
Co
-occu
rre
nce
in
de
x
Neutral
Functional Dissimilarity
Co
-occu
rre
nce
in
de
x
Functional Richness : The amount of niche space filled by species in the community (Convex Hull)
Investigating the assembly rules- Observed Functional Richness vs null model
Null model : for each species richness level, mean Fric calculated from random assemblages of species from the ecosystem pool
12-02-2015 [email protected]
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Observed Functional Richness vs null model
0.00
0.03
0.06
0.09
10 20 30
Species Richness
Fu
nctio
na
l R
ich
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10 12 14 16 18 20 22
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La
titu
de
F9 G1 G3 G5 G7 G9
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46Environmental filteringNeutralLimiting similarity
0.00
0.03
0.06
0.09
10 20 30
Species Richness
Fun
ction
al R
ich
ne
ss
12-02-2015 [email protected]
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What about the biomass distribution in the communities?
Calculation of communities weighted Functional Dissimilarities
Functional Dissimilarity: Quantify how similar/dissimilar are two species based on their traits
Ecologically analogous species Ecologically different species
12-02-2015 [email protected]
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What about the biomass distribution in the communities?
Mean Functional dissimilarity per hauls of the pairwise functional dissimilarities of the two species with the highest abundance in each haul.
12-02-2015 [email protected]
Conclusion
• Strong environmental control : Salinity high explanatory power of species and functional richness in the Baltic.
• In general, Environmental filtering appears to drive the Baltic fish assemblages composition and is especially strong in the Western Baltic, which corresponds to the salinity transition zone.
• The fish communities in the Baltic have a lower functional richness than expected by random. The communities are composed of functionally similar species.
1212-02-2015 [email protected]
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2nd study:Functional diversity of coastal fish
assemblages along a salinity gradient
Laurène Pécuchet, Martin Lindegren, Jens Olsson, Anna Gårdmark and friends
12-02-2015 [email protected]
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Why a new study on Baltic fish assemblages?
• Studying a longer salinity gradient• Permits to include the freshwater species – absent from BITS
survey• Sensitive to other environmental pressures, e.g. eutrophication• Datasets available
Wetzel, 200112-02-2015 [email protected]
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What type of data?Example. Gillnet survey from Sweden
If possible environmental information:• Salinity• Oxygen• Temperature• Depth• Sediment type/habitat
& Gear type, mesh size
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Which hypothesis and analysis?
• Would be depending of the datasets available• Spatial analyses and not temporal – no need of long time-series• Due to different surveys catchability, CPUE is risky. Use of
presence/absence only?• Functional diversity patterns – other traits could describe better
ecological niche of the coastal fish?
12-02-2015 [email protected]
