Climate Change Data Portal
DOI | 10.1016/j.foreco.2020.118432 |
Habitat and stand factors related to spatial dynamics of Norway spruce dieback driven by Ips typographus (L.) in the Białowieża Forest District | |
Kamińska A.; Lisiewicz M.; Kraszewski B.; Stereńczak K. | |
发表日期 | 2020 |
ISSN | 0378-1127 |
卷号 | 476 |
英文摘要 | Among the complex tasks involved in forest protection, one of the most laborious is dealing with tree mortality caused by forest pests. The European spruce bark beetle, which settles primarily on spruces, causes major damages in temperate and boreal forests. To manage forest activities more accurately during outbreaks, robust models are needed to understand how a given phenomenon expands. Our study examines spruce dieback dynamics in a 13,000-ha area of the Białowieża Forest in Białowieża Forest District in Poland, using individual trees assigned to a 100 × 100 m resolution grid based on data from 2015 and 2017. To find the most important factors affecting bark beetle outbreaks, two different approaches were applied. In the first approach, we conducted spatial hot-spot analyses by means of global and local Moran's coefficients. In the second one, we used a machine learning technique, i.e. boosted regression trees (BRTs). Both approaches allowed us to identify the share of area covered by tree crowns excluding spruce, stand height, and share of spruce as the key factors for bark beetle infestation. It means, that the most intensive outbreak progressed in old stands dominated by spruces. Proposed methodology of spatial analysis allowed to discover potential initiation points of beetle-caused tree mortality, localized in more opened old stands and indicate the most outbreak-resistant areas with young trees less than 90 years old. Methods and results presented in this study serve as baseline information, supporting the efforts to model the spread of bark beetle dynamics and future decision-making. © 2020 Elsevier B.V. |
英文关键词 | Boosted Regression Trees; Disturbance; Hot-Spot analysis; Ips typographus; Outbreak; Picea abies; Tree mortality |
语种 | 英语 |
scopus关键词 | Decision making; Dynamics; Learning systems; Spatial variables measurement; Boosted regression trees; Forest activities; Forest protection; Individual tree; Machine learning techniques; Spatial analysis; Spatial dynamics; Spruce bark beetles; Forestry; beetle; coniferous forest; dieback; disease resistance; machine learning; mortality; pest outbreak; spatial analysis; stand structure; Area; Bark; Decision Making; Dynamics; Forestry; Mortality; Picea Abies; Trees; Bialowieza Forest; Poland [Central Europe]; Coleoptera; Ips typographus; Picea; Picea abies; Scolytinae |
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/155004 |
作者单位 | Department of Geomatics, Forest Research Institute, Sękocin Stary, Braci Leśnej 3 Street, Raszyn, 05-090, Poland |
推荐引用方式 GB/T 7714 | Kamińska A.,Lisiewicz M.,Kraszewski B.,et al. Habitat and stand factors related to spatial dynamics of Norway spruce dieback driven by Ips typographus (L.) in the Białowieża Forest District[J],2020,476. |
APA | Kamińska A.,Lisiewicz M.,Kraszewski B.,&Stereńczak K..(2020).Habitat and stand factors related to spatial dynamics of Norway spruce dieback driven by Ips typographus (L.) in the Białowieża Forest District.Forest Ecology and Management,476. |
MLA | Kamińska A.,et al."Habitat and stand factors related to spatial dynamics of Norway spruce dieback driven by Ips typographus (L.) in the Białowieża Forest District".Forest Ecology and Management 476(2020). |
条目包含的文件 | 条目无相关文件。 |
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。