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Updated: Sep 5, 2025

Simulating Impacts of Ice Storms on Forest Ecosystems
Published on: June 30, 2020
Post-disturbance reorganization of forest ecosystems in a changing world
Rupert Seidl1,2, Monica G Turner3
1School of Life Sciences, Technical University of Munich, 85354 Freising, Germany.
Abstract:
Forest ecosystems are strongly impacted by continuing climate change and increasing disturbance activity, but how forest dynamics will respond remains highly uncertain. Here, we argue that a short time window after disturbance (i.e., a discrete event that disrupts prevailing ecosystem structure and composition and releases resources) is pivotal for future forest development. Trees that establish during this reorganization phase can shape forest structure and composition for centuries, providing operational early indications of forest change. While forest change has been fruitfully studied through a lens of resilience, profound ecological changes can be masked by a resilience versus regime shift dichotomy. We present a framework for characterizing the full spectrum of change after disturbance, analyzing forest reorganization along dimensions of forest structure (number, size, and spatial arrangement of trees) and composition (identity and diversity of tree species). We propose four major pathways through which forest cover can persist but reorganize following disturbance: resilience (no change in structure and composition), restructuring (structure changes but composition does not), reassembly (composition changes but structure does not), and replacement (structure and composition both change). Regime shifts occur when vegetation structure and composition are altered so profoundly that the emerging trajectory leads to nonforest. We identify fundamental processes underpinning forest reorganization which, if disrupted, deflect ecosystems away from resilience. To understand and predict forest reorganization, assessing these processes and the traits modulating them is crucial. A new wave of experiments, measurements, and models emphasizing the reorganization phase will further the capacity to anticipate future forest dynamics.
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