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Contributed Talk

Session: : Communities: Spatial Patterns And Environmental Gradients 6

COS 124-1 - Mortality agents driving forest turnover in eastern US forests

Tuesday, August 8, 2023
3:30 PM – 3:45 PM PDT
Location: B119
Abstract: Forest mortality rates are reportedly increasing globally. Tree mortality is the fastest way to lose carbon and biodiversity from intact forests. Increasing our capacity to detect forest health issues when they are limited in spatial extent, while there may still be time to mitigate them, remains one or our best hopes for limiting tree mortality. Early detection of tree mortality events and tree decline through remotely sensed products provides an avenue for biodiversity conservation. Mortality events most often occur at the scale of the individual or a small group of trees in a forest. Our ability to detect shifts in tree mortality and determine the causal factors responsible is defined by the intensity, scale, and frequency of our observations. Currently, most observations are too coarse in spatial scale and too infrequent in time to determine causal factors of mortality or how they vary across space and time and lack detail of why a tree died. We aim to fill this knowledge gap. Our objective is to address this challenge and build scalable models of tree mortality with underlying factors associated with tree death.



To evaluate causal factors and detectability of mortality from remote sensing, we collected annual tree health data across five ForestGEO plots on over 60,000 trees. We also accessed repeated airborne remote sensing data (lidar, RGB, and hyperspectral) collected by the National Ecological Observatory Network (NEON) at all of these plots and their surrounding landscape. We also acquired very high resolution data from UAV collections to leverage both spectral and spatial information about different tree health status conditions. Our field surveys have found a wide range of species specific mortality rates and an even wider assortment of factors associated with tree death (i.e., damages and diseases) often with species-specific syndromes. We have found that the species that are experiencing the highest mortality have compound causal agents corresponding to an accumulation of problems that ultimately kill the tree. We will present our preliminary results on connecting remote sensing to tree health censuses to provide insights into which factors associated with tree death are well resolved in the remote sensing products. Our results could help drive early detection systems to limit forest health issues.