Forests in flux: reconstructing ecotone shifts to improve understanding of climate--vegetation feedbacks

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Climate change is predicted to impact all sectors of the Canadian economy. The ability of society to mitigate and adapt in response to these impacts relies in part on understanding how how climate-vegetation feedbacks (CVFs) amplify or mediate climatic changes; this is a central question in global change ecology. CVFs operate at multiple timescales. Fast processes (e.g., leaf-scale carbon fluxes) operate at sub-annual timescales, while slow processes (e.g., driven by changes in forest composition and structure) occur over decadal and longer timescales. Slow processes are rarely directly observed from instrumental data. However, predictions of the future terrestrial biosphere, CVFs, and the carbon cycle depend on current understanding of these slow processes. Networks of paleoecological data, particularly sediment pollen and dendroecological data, offer the strongest observational constraints on long-term vegetation dynamics; they allow for inference about ecological processes and feedbacks. Improved understanding of slow processes that influence CVFs requires the development of new approaches that leverage paleoecological data and understanding of biosphere-atmosphere interactions. The long-term objective of this research program is to improve understanding of feedbacks between the terrestrial biosphere and the atmosphere. This proposal describes a path towards this objective via a series of scaffolded projects that increase in complexity. More specifically, my intermediary objectives in order of increasing complexity are to: (1) develop new methods to reconstruct biophysical land cover attributes from paleoecological proxy data, (2) leverage and integrate information from these biophysical reconstructions and existing methods to test hypotheses about the impacts of vegetation on climate and vice versa, (3) develop new methods to formally assimilate biophysical reconstructions into Earth System Models, and (4) develop and implement data optimization strategies to fill in paleoecological data gaps. Canada is predicted to experience some of the largest climate changes this century; Boreal forests are thought to be highly sensitive to climate disruptions. These predicted changes are forcing land managers to develop new management strategies. However, understanding of CVFs remains a critical area of uncertainty. This research program addresses the lack of understanding of the fundamental processes that govern CVFs using a modern approach to data-model integration by combining advanced quantitative methods with existing evidence and understanding. These advances will inform climate adaptation planning by providing both managers and policymakers with transformative knowledge about slow processes and their impacts on CVFs.