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Moving forward: insights and applications of moving‐habitat models for climate change ecology

Harsch, Melanie A., Phillips, Austin, Zhou, Ying, Leung, Margaret‐Rose, Rinnan, D. Scott, Kot, Mark
The journal of ecology 2017 v.105 no.5 pp. 1169-1181
best management practices, biocenosis, biologists, climate change, climatic factors, demography, equations, habitats, infectious diseases, models, population density, prediction
Predicting and managing species’ responses to climate change is one of the most significant challenges of our time. Tools are needed to address problems associated with novel climatic conditions, biotic interactions and greater climate velocities. We present a spatially explicit moving‐habitat model (MHM) and demonstrate its versatility in tackling critical questions in climate change research, including dispersal in multiple spatial dimensions, population stage structure, interspecific interactions, asymmetric range shifts, Allee effects and the presence of infectious diseases. The model utilizes integrodifference equations to track changes in population density over time in a habitat that is moving. The model is quite flexible and can accommodate variation in demography, dispersal patterns, biotic interaction and stochasticity in the velocity of climate change. The methods provide a general mechanistic understanding of the underlying ecological processes that drive a system. Field data can be readily incorporated into the model to give insight into specific populations of interest and inform management decisions. Synthesis. Moving‐habitat models unite ecological theory, data‐centred modelling and conservation decision support under a single framework. Their ability to generate testable hypotheses, incorporate data and inform best management practices proves that these models provide a valuable framework for climate change biologists.