Quantification of fire effects and post-fire dynamics

点击翻译按钮获取中文摘要

Natural disturbances in Canadian forests are expected to increase in frequency, severity, and extent due to global climate change. It is critical to fully understand the impact of these disturbances on forest carbon pools as well as post-disturbance dynamics (e.g., dead wood dynamics, regeneration). As a result, disturbance effects and recovery dynamics need to be quantified by type and severity across a range of ecoregions. The immediate and long-term disturbance impacts need to be incorporated into carbon budget models which are increasingly being used to develop adaptation strategies to climate change and to ensure sustainable forest management practices.***The long-term goals of my research are threefold: (1) enhance our ability to explain and model spatial variability in disturbance severity and its impact on carbon pools; (2) advance our knowledge of natural disturbance impacts on forest resources by quantifying disturbance effects with methods that allow making causal inferences from forest inventory data in combination with remote sensing data; and (3) improve our understanding of post-disturbance dynamics in forest ecosystems by implementing and analyzing long-term monitoring plots. The proposed work focuses on achieving the long-term research goals by analyzing forest wildfires in British Columbia (BC) interior and coastal forests that cause pressing environmental and social problems in BC. The proposed work will focus on three inter-related research projects: (1) Spatial variability of fire severity and impacts on carbon pools; (2) regional fire effects estimates, and (3) post-fire monitoring in BC coastal forests.***The results of the proposed research program will improve our ability to assess, model, and simulate immediate and long-term fire effects. Increased understanding of natural disturbance dynamics is needed to support forest management decisions that lead to sustainable forest management and will also provide parameters to improve the calibration of existing carbon budget models.***