Modeling the Effects of Gap Cuts on Stand-Level Resilience in Financial and Carbon Sequestration Contexts

Research output: Contribution to journal › Research article › Contributed › peer-review

Contributors

  • Jonathan Fibich - , Technical University of Munich (Author)
  • Alexander Lange - , Technical University of Munich (Author)
  • Thomas Clemen - , Hamburg University of Applied Sciences (Author)
  • Dominik Thom - , Chair of Silviculture (Author)
  • Thomas Knoke - , Technical University of Munich (Author)

Abstract

Climate change is amplifying disturbances in Central European forests, making resilience a key concept in forest management planning. Yet, the impacts and trade-offs of practices regarded as resilience-enhancing, such as pre-rotation age establishment of young trees in canopy gaps remain insufficiently quantified. Here, we adapt a recent quantification framework, using the post-disturbance recovery time of the present value of a given ecosystem service (ES) as stand-level resilience metric. Our novel, Monte-Carlo Simulation-based (MCS) approach models time series for two ES (net revenues and aboveground carbon sequestration) to quantify the impacts of disturbances under different gap-cut regimes, which we compare against a clear-cut baseline. Gap-cuts can notably enhance resilience, reducing average recovery times by up to 6.6 years (-15.7%) in the financial and 3.3 years (-21.3%) in the carbon sequestration context. Concerning the financial aspects, some gap-cut regimes small in gap size and late in timing could enhance resilience without associated losses in soil expectation value. However, most regimes, although dominating in the resilience metric, were associated with opportunity costs. These costs were less pronounced for carbon sequestration. We conclude that gap-cut induced regeneration can enhance resilience in both financial and carbon contexts, but their optimal timing and size depends on the prioritized ecosystem service. As the complexity of forest stand representations is inherently limited by our MCS-approach, further research should refine forest-value estimation through neural networks and mechanistic models, enabling richer representations of growth and disturbance dynamics and more detailed management regimes.

Details

Original languageEnglish
Article number122
JournalEnvironmental Management
Volume76
Issue number4
Publication statusPublished - 18 Mar 2026
Peer-reviewedYes

External IDs

PubMed 41845106
ORCID /0000-0001-8091-6075/work/225495780

Keywords

Sustainable Development Goals

Keywords

  • Carbon sequestration, Forest economics, Gap-cuts, Quantification, Resilience