PARENT SESSION
Poster Session # 2: Statistical Ecology and Ecological Modeling.
Monday, August 4 Presentation from 5:00 PM to 6:30 PM. SITCC Exhibit Hall B.
Predicting population response to climate change: A non-linear modeling approach.
Ellis, Alicia1, 2, Post, Eric1, 1 Penn State University, University Park, PA2 Dartmouth College, Hanover, NH
ABSTRACT- The rapidly growing body of research on the ecological consequences of global climate change has elicited a growing interest in the use of time series analysis of long-term datasets to investigate population dynamics and stability in a changing climate. Here, we use non-linear self-excitatory threshold autoregressive (SETAR) models to investigate the potential influence of climate change on the stability and persistence of an isolated, undisturbed wolf population on Isle Royale, Michigan, USA. The SETAR model revealed that the population was influenced by climate only at low densities, possibly reflecting the overriding influence of density dependence on dynamics at high densities. Stability analysis suggests that if the population remains above a certain threshold density, it may maintain equilibrium densities despite climatic change. Conversely, if the population decreases below this threshold, climate change is likely to lead to population decline, possibly to extinction, in the next 100 years. In the absence of climate change, the population may exhibit multiple stable states, switching between them when environmental perturbations are strong. Our results indicate that non-linearity in the strength of density dependence can have substantial implications for the stability and persistence of populations in a changing climate. Further investigations into the implications of climate change for population stability and changes in mean density may facilitate the formation of appropriate conservation and management policies.
Key words: Isle Royale (USA), stability, climate change, non-linear modeling