Augustynczik, Andrey L. D. and Hartig, Florian and Minunno, Francesco and Kahle, Hans-Peter and Diaconu, Daniela and Hanewinkel, Marc and Yousefpour, Rasoul (2017) Productivity of Fagus sylvatica under climate change - A Bayesian analysis of risk and uncertainty using the model 3-PG. FOREST ECOLOGY AND MANAGEMENT, 401. pp. 192-206. ISSN 0378-1127, 1872-7042
Full text not available from this repository. (Request a copy)Abstract
To assess the long-term impacts of forest management interventions under climate change, process based models, which allow to predict transient dynamics under environmental change, are arguably the most suitable tools available. A challenge for using these models for management decisions, however, is their higher parametric uncertainty, which propagates to predictions and thus into the decision making process. Here, we demonstrate how this problem can be addressed through Bayesian inference. We first conduct a Bayesian calibration to generate an estimate of posterior parametric uncertainty for the process-based forest growth model 3-PG for Fagus sylvatica. The calibration uses data from twelve sites in Germany, together with a robust (Student's t) error model. We then propagate the estimated uncertainty together with economic uncertainty to forest productivity and Land Expectation Value (LEV), allowing us to evaluate alternative management regimes under climate change. Our results demonstrate that parametric and economic uncertainty have strong impacts on the variation of predicted forest productivity and profitability. Management regimes with increased thinning intensity were overall most robust to economic, climate change and parametric model uncertainty. We conclude that estimating and propagating economic and model uncertainty is crucial for developing robust adaptive management strategies for forests under climate change. (C) 2017 Elsevier B.V. All rights reserved.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | TREE SPECIES COMPOSITION; ROBUST DECISION-MAKING; FOREST GROWTH-MODEL; CARBON STORAGE; EUCALYPTUS PLANTATIONS; MANAGEMENT; EUROPE; CALIBRATION; DYNAMICS; BIOMASS; Uncertainty; Risk; Forest management; Bayesian calibration; European beech |
| Subjects: | 500 Science > 580 Botanical sciences |
| Divisions: | Biology, Preclinical Medicine > Institut für Pflanzenwissenschaften |
| Depositing User: | Dr. Gernot Deinzer |
| Date Deposited: | 14 Dec 2018 13:19 |
| Last Modified: | 18 Feb 2019 14:17 |
| URI: | https://pred.uni-regensburg.de/id/eprint/2149 |
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