Forecasting species distributions: coping with uncertainties in processes
In order to achieve more
robust projections of future species ranges, process-based species
distribution models were developed. These models are based on the
responses of biological processes important to the species life cycle
(e.g. growth, respiration, offspring production). These models require
a good knowledge of the species, and thus cannot be readily applied to
numerous species.
Because they rely on causal relationships between traits and environmental variables, they can be more confidently extrapolated to future conditions than correlative models. However, all models neglect some processes, and not all processes are as important in each location. We thus proposed a method to generate informed consensus among existing process-based or hybrid distribution models, to provide more robust estimates of future distributions.
Because they rely on causal relationships between traits and environmental variables, they can be more confidently extrapolated to future conditions than correlative models. However, all models neglect some processes, and not all processes are as important in each location. We thus proposed a method to generate informed consensus among existing process-based or hybrid distribution models, to provide more robust estimates of future distributions.
