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| DOI | 10.1016/j.foreco.2020.118497 |
| Climate sensitive single tree growth modeling using a hierarchical Bayes approach and integrated nested Laplace approximations (INLA) for a distributed lag model | |
| Nothdurft A. | |
| 发表日期 | 2020 |
| ISSN | 0378-1127 |
| 卷号 | 478 |
| 英文摘要 | A novel methodological framework is presented for climate-sensitive modeling of annual radial stem increments using tree-ring width time series. The approach is based on a hierarchical Bayes model together with a distributed time lag model that take into account the effects of a series of monthly temperature and precipitation values, as well as their interactions. By using a set of random walk priors, the hierarchical Bayes model allows both the detrending of the individual time series and the regression modeling to be performed simultaneously in a single model step. The approach was applied to comprehensive tree-ring width data from Austria collected on sample plots arranged in triplets representing different mixture types. Bayesian predictions revealed that European larch (Larix decidua Mill.), Norway spruce (Picea abies (L.) H. Karst.), and Scots pine (Pinus sylvestris L.) show positive climate-related growth trends throughout higher elevation sites in Tyrol, and these trends remain unchanged under a mixed-stand scenario. At the lower Austrian sites, Norway spruce was found to show a severely negative growth trend under both the pure- and mixed-stand scenario. The increment rates of European beech (Fagus sylvatica L.) were found to have a negative climate-related trend in pure stands, and the trend diminished through an admixture of spruce or larch. The trends of European larch and sessile oak (Quercus petraea (Matt.) Liebl.) showed stationary behavior, irrespective of the mixture scenario. Scots pine data showed a positive trend at the lower elevation sites under both the pure- and mixed-stand scenario. These findings indicate that species mixing does not lower the climate-related increment fluctuations of beech, oak, pine, and spruce at lower elevation sites. © 2020 The Author |
| 英文关键词 | Climate sensitivity; Distributed lag model; Forest growth model; Hierarchical Bayes model; INLA; Species mixing; Tree-ring width analysis |
| 语种 | 英语 |
| scopus关键词 | Bayesian networks; Forestry; Mixtures; Plants (botany); Time series; Trees (mathematics); Bayesian predictions; Distributed lag models; European beech (fagus sylvatica l.); Hierarchical Bayes models; Laplace approximation; Methodological frameworks; Stationary behavior; Tree growth modeling; Climate models; Bayesian analysis; coniferous forest; growth modeling; pine; time series; tree ring; Forestry; Larix Decidua; Mixtures; Picea Abies; Pinus Sylvestris; Sites; Trees; Trends; Fagus; Fagus sylvatica; Larix; Larix decidua; Picea; Picea abies; Pinus sylvestris; Quercus petraea |
| 来源期刊 | Forest Ecology and Management
 |
| 文献类型 | 期刊论文 |
| 条目标识符 | http://gcip.llas.ac.cn/handle/2XKMVOVA/154948 |
| 作者单位 | University of Natural Resources and Life Sciences, Vienna (BOKU), Austria, Department of Forest- and Soil Sciences, Institute of Forest Growth |
| 推荐引用方式 GB/T 7714 | Nothdurft A.. Climate sensitive single tree growth modeling using a hierarchical Bayes approach and integrated nested Laplace approximations (INLA) for a distributed lag model[J],2020,478. |
| APA | Nothdurft A..(2020).Climate sensitive single tree growth modeling using a hierarchical Bayes approach and integrated nested Laplace approximations (INLA) for a distributed lag model.Forest Ecology and Management,478. |
| MLA | Nothdurft A.."Climate sensitive single tree growth modeling using a hierarchical Bayes approach and integrated nested Laplace approximations (INLA) for a distributed lag model".Forest Ecology and Management 478(2020). |
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