Modeling ecological responses to climate change

Background/Question/Methods Projecting the effects of global climate change on ecological communities is an emerging challenge for ecologists. Forecasts of future ecological states must incorporate uncertainty both in predicted climatic conditions and in ecological responses. We investigate and apply methods for projecting range and compositional shifts of plant communities in response to forecast climate change. We utilize four approaches that differ substantially in both their methodology and the spatial scale of their resultant projections: (1) Simple process models of community response to changing environmental conditions, (2) Stand models that incorporate detailed, species-specific demographic responses to environmental change, (3) Landscape models that dynamically update local environmental conditions in response to regional climate and subsequently project ecological responses, and finally (4) Bioclimatic (or niche) models that project future regional distributions of species based on statistical relationships between current species presence and climatic conditions.

Results/Conclusions We illustrate the challenges and potential of these four approaches for projecting the responses of ecological communities to anticipated regional climate change both within the Florida Everglades and across the southeastern United States. We show that simple process models can be useful for delineating the range of potential ecological responses to climate change, including nonlinear or threshold responses to climate forcing. The elucidation of possible ecological trajectories serves a critical function, but lacks the certainty that would characterize this approach as a method of forecasting. Stand models, in contrast, produce detailed projections of future ecological states in response to climatic change. The quantity of demographic information required to parameterize species responses to climatic change is daunting. Large uncertainty in model parameters, nonlinearities, and possible feedbacks within systems can limit the capacity of these methods for forecasting. Bioclimatic models provide a means for projecting future species distributions at regional scales through a low dimensional mapping of current species-climate relationships. The implicit assumptions in using niche models to project future species distributions are that this mapping will remain constant and that species associations assort independently. Landscape models provide flexibility in that they can incorporate components of the three other approaches, while providing capacity for feedbacks between community components. We illustrate the utility of incorporating multiple approaches as a means of assessing uncertainty in model predictions and appropriateness of underlying assumptions inherent in each approach. The interaction between climate uncertainty and uncertainty in species interactions and adaptation challenges the potential for any of these models to produce accurate forecasts of community change.