Transitions and thresholds in global ecological changes of forest ecosystems

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Global ecological changes are having unexpected effects on forest ecosystems and understanding of how various human-induced stressors (e.g., climate change) interact with natural disturbance regimes is largely unknown. This is partly due to insufficient empirical analysis and partly due to insufficient modeling of threshold behavior. We examine a variety of effects -- at scales from individuals to populations to landscapes -- from both empirical and modeling perspectives. The main objective is to improve our understanding of spatial and temporal dynamics, including predicting “critical” transitions in tree, tree population and forest dynamics in the face of stress and disturbances. One objective of our research program is to examine tree (largely dendrochronological) and forest (through paleopollen) data and explore ‘early-warning systems’ using both established and new analytical (statistical) tools to help detect transitions, both critical and non-critical. On the other hand we will build process-based models at the population and ecosystem level to help better understand these transitions under a number of new scenarios, paying close attention to recently discovered threshold behaviour of trees. Little work has been done to link statistical tools available to detect critical transitions with process-based models which highlights the novelty of our work. A closer integration of empirical and theoretical approaches to understanding stress and disturbance effects on forest dynamics will advance the field of ecology, improve our fundamental understanding of forest ecosystems and inform management decisions. Our studies, which will help to determine under which conditions abrupt changes occur, and whether or not they are ‘critical’, could help to prepare for or avert future surprises in ecosystem response. Though the new field studies will focus on Canada and Brazil, discoveries will be applicable worldwide because the theoretical, statistical and modelling approaches are more general and can be easily adapted to local studies/species.