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Related Experiment Video

Updated: Nov 23, 2025

Simulating Impacts of Ice Storms on Forest Ecosystems

Simulating Impacts of Ice Storms on Forest Ecosystems

Published on: June 30, 2020

Simulating forest resilience: A review.

Katharina Albrich^1,2, Werner Rammer^1,2, Monica G Turner³

¹Institute of Silviculture University of Natural Resources and Life Sciences (BOKU) Vienna Wien Austria.

Global Ecology and Biogeography : a Journal of Macroecology

|December 31, 2020

Summary

This summary is machine-generated.

Forest simulation models often fail to capture key resilience mechanisms. This gap hinders accurate assessment of forest persistence under global change, necessitating new model development for effective forest management.

Keywords:

ecosystem modelling literature review model development process‐based modelling resilience processes simulation model

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Area of Science:

Ecology
Forestry
Computational modeling

Background:

Forest ecosystems face unprecedented global change pressures.
Quantifying forest resilience is crucial for predicting ecosystem persistence.
Simulation models are primary tools for assessing forest resilience.

Purpose of the Study:

To synthesize the literature on forest resilience simulation models.
To evaluate the implementation of key resilience mechanisms in these models.
To identify gaps between theoretical/empirical findings and model representations.

Main Methods:

Systematic literature review of 119 forest resilience simulation studies (1994-2019).
Identification of critical resilience mechanisms from general ecological literature.
Analysis of model representation of these mechanisms, categorized by drivers and responses.

Main Results:

Wide diversity in simulation models, from analytical to landscape-scale.
Most studies focused on forest cover resilience to fire.
Crucial mechanisms (regeneration, soil processes, legacies) were poorly represented (34-46% of models).

Conclusions:

Significant discrepancy exists between known resilience processes and their simulation.
Existing models, often developed for other purposes, are inadequate for resilience assessment.
Development of novel models is essential for understanding and managing resilient forests.