Section for Coastal Ecology Technical University of Denmark
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Section for Coastal Ecology Technical University of DenmarkNational Institute of Aquatic Resources
Habitat modeling: linking biology to abiotic predictors
Claus R. Sparrevohn&
Mats Lindegarth
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Talk outline
First half: Conceptual part Second part: Methodology part Together with Mats
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Fisheries science
Berverton and Holt 1957
-Exploitation pattern and level- Recruitment- Top down controlled
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Can we map all marine habitats?
1: Large pelagic speciesCalifornia anchovy
2: Spawning volumeBaltic Cod
3: Nursery size hypothesisKattegat plaice
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California anchovy
•Surface frontSpatial stable but seasonal unstable
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California anchovy
•Taylor columnSpatial stable but temporal unstable
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Baltic cod
ICES CTD stations 1994 to 2005
From Neuenfeldt and Geitner
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Baltic cod?
ICES CTD stations Oxygen<2ml/l
From Neuenfeldt and Geitner
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Baltic cod?
ICES CTD stations salinity<11 ppt
From Neuenfeldt and Geitner
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Baltic cod?
ICES CTD stations Oxygen>2 ml/l, salinity>11 ppt
From Neuenfeldt and Geitner
suitable for cod eggs=reproductive volume
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Flatfish nursery grounds
3D time series - Cod spawning habitat volume
Year1960 1965 1970 1975 1980 1985 1990 1995
Hab
itat v
olum
e [k
m3 ]
0
100
200
300
400
500
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Baltic cod?
Historical spawning areas for cod in the Baltic Sea. From Bagge, O., Thurow, F., Steffensen, E., Bay, J. 1994. The Baltic Cod. Dana Vol. 10:1-28, modified by Aro, E. 2000. The spatial and temporal distribution patterns of cod (Gadus morhua callarias) in the Baltic Sea and their dependence on environmental variability – implications for fishery management. Academic dissertation. University of Helsinki and Finnish Game and Fisheries Research Institute, Helsinki 2000, ISBN-951-776-271-2, 75 pp.
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3: Nursery size hypothesis
Nursery size hypothesis-Argues that there is a relationship between the size of the nursery and the stock
1) Sufficient supply of offshore spawned larvae
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3: Nursery size hypothesis
1995 1997
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3: Nursery size hypothesis
Year
Pla
ice
per 1
0 m
in
1910 1930 1950 1970 1990 2010
050
100
150
200
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Background
•Involved in the InterReg project BALANCE: Mapping juvenile fish abundance based on predictor/fish count data relationships
Predictors:Wave-exposureDist. Shore to 5 mDist. Sample to shoreSlopeNo. Sand banksYearDepthSediment
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3: Nursery size hypothesis
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Conclusion
• Are all species limited by availability of suitable habitat•Habitat instability in time and place,• Year to year variations in population biomass.
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Methods
Do we have the right statistical models and are we using them the right way?:• Different models: Linear vs. non linear models (GLM, GAM), Zero inflated and overdispersed data, use of hurdle models
• Regression threes (Mats)
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Methods
Start with a simple GLM• Correlation between predictors• Trends in the residuals
What to do when we have trend in the residuals:• Extend the model with an interaction term• Extend the model with a non-linear predictor (e.g. predictort+predictor^2)• Transform your predictor• Use a GAM model
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Methods
Zero inflated data:• Transform to presence/absence•Use other models
050
010
0015
00
Counts of plaice
Freq
0 6 13 21 29 37 45 53 61 69 77 85 93 102
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Methods
Delta and hurdle models
Mixture model (ZIP, ZINB)
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Thank you