section for coastal ecology technical university of denmark
DESCRIPTION
Habitat modeling: linking biology to abiotic predictors. Claus R. Sparrevohn & Mats Lindegarth. Section for Coastal Ecology Technical University of Denmark National Institute of Aquatic Resources. Talk outline. Second part: Methodology part Together with Mats. - PowerPoint PPT PresentationTRANSCRIPT
Section for Coastal Ecology Technical University of DenmarkNational 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 1957
-Exploitation pattern and level- Recruitment- Top down controlled
Can we map all marine habitats?
1: Large pelagic speciesCalifornia anchovy
2: Spawning volumeBaltic Cod
3: Nursery size hypothesisKattegat plaice
California anchovy
•Surface frontSpatial stable but seasonal unstable
California anchovy
•Taylor columnSpatial 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
Year1960 1965 1970 1975 1980 1985 1990 1995
Hab
itat v
olum
e [k
m3 ]
0
100
200
300
400
500
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.
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
1995 1997
3: Nursery size hypothesis
Year
Pla
ice
per 1
0 m
in
1910 1930 1950 1970 1990 2010
050
100
150
200
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
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
050
010
0015
00
Counts of plaice
Freq
0 6 13 21 29 37 45 53 61 69 77 85 93 102
Methods
Delta and hurdle models
Mixture model (ZIP, ZINB)
Thank you