About the project
The demand for forecasting the effects of global warming on biodiversity and ecosystem functioning is growing. However, present models have severe limitations. Uncertainties in ecological scenarios stem from unrealistic model assumptions and intrinsic stochasticity of natural processes. The proposed project will answer these challenges by merging hypothesis testing of ecological mechanisms with applied climate scenario forecasting. Expected output is i) improved methods for forecasting ecological effects of climate change, ii) climate change scenarios for case study systems and iii) quantification and identification of main sources of uncertainties. We will build single-, two- and multi-species models forecasting impact of different climate scenarios. Northern freshwater with their salmonid fishes and zooplankton prey will be used as case studies. These systems are ideal due to their relative simplicity, and extensive knowledge on physiological performance and the ecological functioning of main organism groups. The first part of the project will fill gaps in empirical knowledge. In addition, several large affiliated projects will generate sub-models. Thereafter, derived and existing knowledge of physiological performance, adpative variation and ecological mechanisms will be integrated with correlative models. The approaches will be both within the Bayesian framework, and with models blending functional and correlative derived knowledge. Finally, we will compare the different sources of uncertainty, ranging from measurement error to process stochasticity and expert opinions on model performance. The project will promote recruitment to ecological climate change forecasting by including a PhD position in biostatistics and ecological modeling.
Financing
This project funded by the Norwegian Research Council and the Norwegian Institute for Nature Research.
Period
Start: 1.1.2010. End: 31.03.2012.