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NSF
Forests provide substantial economic and ecological benefits to human society, including timber resources, wildlife habitat, and water quality regulation. However, an increasing frequency and severity of disturbances that kill trees (such as storms, pests, wildfires, and droughts) threatens the sustainability of these resources and services. This project combines existing field experiments and a recent ice storm in the forests of northern Michigan to evaluate how forest structure and productivity are affected by interacting disturbances. The project is focused specifically on how aspects of prior disturbances, such as timing and severity, might affect the response of the forest to subsequent disturbance. An improved understanding of the effect of interacting disturbances on forest structure and productivity will be highly beneficial to forest scientists and managers in predicting and managing for the effects of changing disturbance regimes. Openly available technical resources are being produced that focus on helping land managers and commercial foresters predict the outcomes of disturbances, such as ice storms, on the sustainability of our forest resources and develop management strategies to promote future forest resilience. Training is being provided to graduate and undergraduate students and a post-doctoral researcher with applicability to future careers in sustainable forest resource and land management, geospatial analytics, and data science. In addition, the data produced in the project and the field experiments at the University of Michigan Biological Station are an open training resource available to a large number of students, researchers, and educators. This project leverages a significant ice storm disturbance and multiple existing long-term ecosystem-scale disturbance experiments at the University of Michigan Biological Station to better understand the effect of prior disturbance severity, pattern, and timing on forest ecosystem structural and functional response to compounding disturbance. Mounting evidence indicates that changing frequency and scale of disturbances is producing more common and extensive instances of compounding disturbance, with uncertain consequences for core ecosystem functions. Based on prior work and preliminary data, forest ecosystem productivity is hypothesized to be more resistant to ice storm disturbance where prior experimental disturbance was: 1) less severe, 2) more focused on the lower canopy stratum, and 3) less recent. Study plots in the three existing disturbance experiments span gradients in prior disturbance timing (6-116 years prior), severity (0-85% basal area loss), and directionality (top-down vs. bottom-up) providing a novel template and extensive existing data resources on which to build an analysis of subsequent disturbance outcomes. In each experiment, the project is tracking change in forest NPP (relative to controls and pre-ice storm baselines) and shifts in structural and functional characteristics that are hypothesized to underlie variable resistance. To address these questions the project is utilizing existing long-term data resources, remote sensing-based analysis of forest canopy structural and functional change using terrestrial lidar and the National Ecological Observatory Network Aerial Observation Platform, and field plot-based assessments of tree damage, vegetation response, and wood production. The data and outcomes of the project are being used, in collaboration with regional and national forestry practitioner communities, to develop and deliver science-based management strategies focused on forest resilience to emerging and compounding disturbance regimes. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Up to $38K
2026-07-31
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