Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1016/j.foreco.2017.06.061 |
Productivity of Fagus sylvatica under climate change - A Bayesian analysis of risk and uncertainty using the model 3-PG | |
Augustynczik, Andrey L. D.1; Hartig, Florian2,3; Minunno, Francesco4; Kahle, Hans-Peter5; Diaconu, Daniela5; Hanewinkel, Marc1; Yousefpour, Rasoul1 | |
2017-10-01 | |
发表期刊 | FOREST ECOLOGY AND MANAGEMENT |
ISSN | 0378-1127 |
EISSN | 1872-7042 |
出版年 | 2017 |
卷号 | 401 |
文章类型 | Article |
语种 | 英语 |
国家 | Germany; Finland |
英文摘要 | 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. |
英文关键词 | Uncertainty Risk Forest management Bayesian calibration European beech |
领域 | 气候变化 |
收录类别 | SCI-E |
WOS记录号 | WOS:000408073300020 |
WOS关键词 | TREE SPECIES COMPOSITION ; FOREST GROWTH-MODEL ; DECISION-MAKING ; CARBON STORAGE ; CALIBRATION ; DYNAMICS ; MANAGEMENT ; BIOMASS ; PLANTATION ; ROBUST |
WOS类目 | Forestry |
WOS研究方向 | Forestry |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/22502 |
专题 | 气候变化 |
作者单位 | 1.Univ Freiburg, Chair Forestry Econ & Forest Planning, Tennenbacherstr 4, D-79106 Freiburg, Germany; 2.Univ Freiburg, Biometry & Environm Syst Anal, Tennenbacherstr 4, D-79106 Freiburg, Germany; 3.Univ Regensburg, Theoret Ecol, Fac Biol & Preclin Med, Univ Str 31, D-93053 Regensburg, Germany; 4.Univ Helsinki, Dept Forest Sci, Latokartanonkaari 7, FIN-00014 Helsinki, Finland; 5.Univ Freiburg, Chair Forest Growth & Dendroecol, Tennenbacherstr 4, D-79106 Freiburg, Germany |
推荐引用方式 GB/T 7714 | Augustynczik, Andrey L. D.,Hartig, Florian,Minunno, Francesco,et al. Productivity of Fagus sylvatica under climate change - A Bayesian analysis of risk and uncertainty using the model 3-PG[J]. FOREST ECOLOGY AND MANAGEMENT,2017,401. |
APA | Augustynczik, Andrey L. D..,Hartig, Florian.,Minunno, Francesco.,Kahle, Hans-Peter.,Diaconu, Daniela.,...&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. |
MLA | Augustynczik, Andrey L. D.,et al."Productivity of Fagus sylvatica under climate change - A Bayesian analysis of risk and uncertainty using the model 3-PG".FOREST ECOLOGY AND MANAGEMENT 401(2017). |
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