"Spatial population processes, global drivers, and positive interactions: critical lacunae in ecological forecasting"

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Ecosystems and landscapes are being affected by anthropogenic changes to habitats, climate, and species composition. Some species will be resilient to these changes, and others will change or disappear. The task of applied ecology has been to predict these changes by integrating knowledge and theory across disciplines to answer society's needs. Along the way, new quantitative approaches have been required that correctly account for the spatio-temporal nature of the empirical data available to support decisions and to quantify prediction uncertainty. In this research, I propose to forecast populations in four dynamic ecological systems: woodland caribou and mountain pine beetle (MPB) in the boreal forest of Canada, wolves in the Western US, and alpine treelines in 3 continental mountain ranges. These systems are experiencing dramatic range and population changes through expansions (MPB, wolves, treeline) or contractions (caribou). These changes are driven by a complex of factors in flux that include climate (e.g., MPB and treeline), habitat degradation and increased predation (caribou), and severe hunting restrictions during reintroduction that have now been removed (wolves). Accurate forecasts of the evolution of these systems will have potentially large direct economic impacts (e.g. on the pine forestry resource in boreal Canada and woodland caribou recovery plans) and will contribute to the conservation of endangered species (caribou, wolves and others). I will use an Occam's Razor inspired approach to integrating diverse ecological and applied fields in a spatially explicit, individual-based modeling framework. To be able to develop credible spatially dynamic models, I have identified three critical areas of uncertainty that require more detailed empirical analyses: dispersal through complex landscapes, distinguishing global from the local drivers that may allow management actions, and the potential for positive interactions among individuals within the same trophic level that can markedly alter system dynamics. The combination of advances in understanding of these detailed ecological phenomena and the integration of these with prior studies will allow me to best forecast species within the intact, but changing systems.