The role of spatial complexity in population dynamics under climate change

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Peter Chesson and Yi Jie Wu, Life Sciences, National Chung Hsing University, Taichung, Taiwan, Peter Chesson, Ecology and Evolutionary Biology, University of Arizona, Tucson, AZ

Background/Question/Methods
Standard ecological models and theory have generally assumed no long-term trends in the environment, limiting the ability to conceptualize a natural world inescapably influenced by long-term change. Recent theory of asymptotic environmentally determined trajectories (aedts) defines preferred paths that an ecosystem should follow in a changing environment whether change is stationary or nonstationary, i.e. accounts for long-term climate change. The recent extension of aedt theory to populations moving across landscapes emphasizes that spatial complexity is key to understanding the maintenance of population integrity under climate change. A spatial equilibrium is one indication that a changed environment may continue to support a population under changed conditions, but because conditions continually change, and a population cannot instantly adjust, a complex of factors contribute to long-term population persistence. These factors include the degree of landscape complexity, connectivity, the speed of population dynamics and the strength of density-dependent processes. Spatial aedt theory shows how the preferred path of population dynamics can be represented as a generalized geometric series moving average of past environmentally-determined equilibria, and provides the means for investigating these questions through the coefficients of the series. We applied this approach to a Beverton-Holt (discrete-time logistic) spatial population model.
Results/Conclusions
The generalized geometric series representation in effect defines a memory for a spatial ecological process from which a mean and other characteristic moments define the responsiveness of the spatially distributed population to changing conditions. Memory, along with two other interacting factors are of major importance for maintenance of the integrity of the spatially-distributed population: spatial complexity and landscape connectivity. Memory is shown to decrease with the strength of density-dependence, spatial complexity and spatial connectivity. However, results so far show that population persistence is strongest under long memories for generally deteriorating or periodically deteriorating environments, but short memories may be better for population persistence with high spatial complexity and intermediate or high landscape connectivity. The generalized geometric series approach in aedt theory is shown to be a powerful method for navigating the complexities of fluctuating trending climates on realistically complex landscapes.