Section for Coastal Ecology Technical University of Denmark National Institute of Aquatic Resources Habitat modeling: linking biology to abiotic predictors.

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Presentation transcript:

Section for Coastal Ecology Technical University of Denmark National Institute of Aquatic Resources Habitat modeling: linking biology to abiotic predictors Claus R. Sparrevohn & Mats Lindegarth

Talk outline First half: Conceptual part Second part: Methodology part Together with Mats

Fisheries science Berverton and Holt Exploitation pattern and level - Recruitment - Top down controlled

Can we map all marine habitats? 1: Large pelagic species California anchovy 2: Spawning volume Baltic Cod 3: Nursery size hypothesis Kattegat plaice

California anchovy Surface front Spatial stable but seasonal unstable

California anchovy Taylor column Spatial stable but temporal unstable

Baltic cod ICES CTD stations 1994 to 2005 From Neuenfeldt and Geitner

Baltic cod? ICES CTD stations Oxygen<2ml/l From Neuenfeldt and Geitner

Baltic cod? ICES CTD stations salinity<11 ppt From Neuenfeldt and Geitner

Baltic cod? ICES CTD stations Oxygen>2 ml/l, salinity>11 ppt From Neuenfeldt and Geitner suitable for cod eggs = reproductive volume

Flatfish nursery grounds 3D time series - Cod spawning habitat volume

Baltic cod? Historical spawning areas for cod in the Baltic Sea. From Bagge, O., Thurow, F., Steffensen, E., Bay, J The Baltic Cod. Dana Vol. 10:1-28, modified by Aro, E 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 , 75 pp.

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

3: Nursery size hypothesis

3: Nursery size hypothesis

Background Involved in the InterReg project BALANCE: Mapping juvenile fish abundance based on predictor/fish count data relationships Predictors: Wave-exposure Dist. Shore to 5 m Dist. Sample to shore Slope No. Sand banks Year Depth Sediment

3: Nursery size hypothesis

Conclusion Are all species limited by availability of suitable habitat Habitat instability in time and place, Year to year variations in population biomass.

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)

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

Methods Zero inflated data: Transform to presence/absence Use other models

Methods Delta and hurdle models Mixture model (ZIP, ZINB)

Thank you