Forest disturbance trajectories enable better understanding and prediction of carbon uptake
A. USCANGA, K.M. DAHLIN
Department of Geography, Environment, and Spatial Sciences, Michigan State University, 673 Auditorium Rd, East Lansing, MI 48824, USA

Land-use and forest disturbance deeply influence the ability of forests to uptake and store carbon. Given landscapes are rapidly changing due to human activities, keeping track of the amount of carbon that forests store is difficult, especially in understudied landscapes. With the objective of better understanding the role of forest disturbance in shaping carbon accumulation, in this project we use satellite imagery time series to characterize forest disturbance trajectories and group them into disturbance syndromes. We hypothesize that disturbance syndromes can help explain current forest structure and function, reducing uncertainty in carbon estimates. Using Landsat record of images (1985-2022) and the algorithm landtrendr , we characterize the disturbance trajectories of four temperate forests that are part of NEON, and that have experienced different types of disturbance in recent decades. With a non-hierarchical cluster analysis, we group such trajectories into general patterns of disturbance (or syndromes) and test their explanatory power by comparing the well-known structure and composition of these forests derived from airborne observations with the obtained syndromes. Explicitly incorporating the effect of disturbance and land-use on forest structure through disturbance syndromes can greatly improve regional and global estimates of carbon storage and inform efforts to transition to a net-zero society.