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Robust management strategies promoting ecological resilience and economic efficiency of a mixed conifer-broadleaf forest in Southwest Germany under the risk of severe drought

Juan Carlos Zamora-Pereira, Marc Hanewinkel and Rasoul Yousefpour

Ecological Economics, 2023, vol. 209, issue C

Abstract: Robust decision-making in forestry seeks solutions that reduce the risk of environmental damage and economic losses, which matters for designing forest adaptation measures. We propose a state-of-the-art methodology to identify robust drought adaptive strategies. First, we used a process-based model with an ensemble of climate change scenarios to simulate managed forest dynamics. Second, we quantified the ecological resilience and financial return as net present value (NPV), applying business-as-usual (BAU) and alternative adaptation strategies to regenerate the overstorey layer (trees ≥ 30 cm dbh) of the forest (e.g., “active”, “reactive”, and “do-nothing”). Afterward, we analyzed robustness by searching for the strategy with minimum worst-case losses of ecological and economic signposts. Our analysis found a reduced forest drought resilience under BAU and “do-nothing” strategies, determining a high probability of economic failure (∼ −49% and ∼ −67% loss in NPV respectively). While, an early “active” strategy would increase the NPV (∼ +10%), and a highly-intense “reactive” strategy would have minimal losses (∼ −2%). Finally, we found that local conditions influence the signpost performance magnitude but do not vary the robust solution. We conclude that our methodology facilitates applying a robustness analysis in forestry, and drought adaptation should occur rather sooner than later, considering constant revision.

Keywords: Robustness analysis; Risk management; Ecological resilience; Economic efficiency; Adaptive management; Severe drought (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecolec:v:209:y:2023:i:c:s0921800923000885

DOI: 10.1016/j.ecolecon.2023.107825

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