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Partitioning variations into ”natural” and anthropogenic variations?. Jacob Carstensen Dept. of Marine Ecology National Environmental Research Institute Aarhus University. Disentangling different sources of variation. Error. Natural perturbations. Error. Ecosystem indicators. ECOSYSTEM.
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Partitioning variations into ”natural” and anthropogenic variations? Jacob Carstensen Dept. of Marine Ecology National Environmental Research Institute Aarhus University
Disentangling different sources of variation Error Natural perturbations Error Ecosystem indicators ECOSYSTEM Error Anthropogenic perturbations
Factors operate at different time scales • Meteorological conditions affect samples on the short time-scale (rain event, storms, calm periods, etc.) • Human accidental episodes (oil spills, leaks from industrial plants, etc.) • Seasonal variations give rise to cyclic patterns (light, temperature, and many other components associated with these) • Anthropogenic processes are often linked to the seasonal variation (nutrient inputs, atmospheric emissions, etc.) • Climate trends affect ecosystems (NAO, global warming, wind patterns, etc.) • Long-term effects of anthropogenic activities (eutrophication, acidification, etc.)
The BACI approach Control Impact Before BACI = (IA - IB) – (CA - CB) After Relative differences will filter out the natural perturbations Natural and anthopogenic perturbations Natural perturbations only
BACI approach to time series Impact Control
A bit more sophisticated example: Macroalgae cover at stone reefs Estimated cover at a standard depth of 15 m
A bit more sophisticated example: Macroalgae cover at stone reefs Estimated cover at a standard depth of 15 m
Conclusions • Natural and anthropogenic perturbations act on the ecosystem at different time scales (and spatial scales as well) • Natural variations can be ”filtered out”, provided that there is a reference site unaffected by humans but similarly affected by natural variations • If reference sites are not available, modelling is the only resort, e.g. by multiple regression analyses using natural and anthropogenic disturbances as input variables