气候变化领域集成服务门户(CCPortal): Predicting abundance and diversity of tree-related microhabitats in Central European montane forests from common forest attributes

CCPortal

DOI	10.1016/j.foreco.2018.09.043
	Predicting abundance and diversity of tree-related microhabitats in Central European montane forests from common forest attributes
	Asbeck T.; Pyttel P.; Frey J.; Bauhus J.
发表日期	2019
ISSN	0378-1127
起始页码	400
结束页码	408
卷号	432
英文摘要	The continued provision of old-growth elements in forest landscapes is a critical factor for biodiversity conservation in Central Europe. A well-established method for predicting the potential of forests to maintain biodiversity is to quantify tree-related microhabitat structures (TreMs). Our aim was to predict the TreM abundance and diversity for collectives of TreM-bearing trees; here 15 large trees per plot that were preselected by the largest crown sizes using remote sensing information. TreMs were inventoried on 2085 living trees across 139 plots (each 1 ha) in montane forests of the Black Forest, southwest Germany according to a detailed catalogue comprising 64 different TreM structures. We tested the influence of forest management, forest cover in the surrounding landscape (25 km radius), forest type, the number of standing dead trees, altitude and mean diameter at breast height (DBH) on the abundance and diversity of TreMs on living trees. All plots are managed or have been recently (20–40 yrs) abandoned from management. Generalized linear models (GLM) were used to identify the drivers of abundance and diversity of TreMs. The abundance of TreMs borne by the 15 large trees per plot is greater on plots located at higher altitudes. Increasing mean DBH leads to significantly higher abundance and diversity of TreMs. Groups of TreM-bearing trees in monospecific coniferous forests have the highest abundance but those in mixed-coniferous-broadleaved forests have the greatest diversity of TreMs. The occurrences of 11 out of 64 specific TreM structures were related to forest management, forest type, altitude or mean DBH. Large branch holes and buttress cavities increased with mean DBH and were found more frequently in mixed-coniferous-broadleaved forests than in the other forest types. The abundance of epiphytes on TreM bearing trees increased with altitude. This study demonstrates that the average abundance and diversity of TreMs can be predicted with readily available forest attributes. Additionally, the occurrence of specific TreMs could be described with the variation in these selected forest attributes. © 2018
语种	英语
scopus关键词	Biodiversity; Conservation; Ecosystems; Forecasting; Remote sensing; Biodiversity conservation; Broad-leaved forests; Coniferous forests; Critical factors; Forest landscape; Generalized linear model; Remote sensing information; Standing dead trees; Forestry; abundance; altitude; biodiversity; broad-leaved forest; coniferous forest; conservation status; forest cover; forest ecosystem; forest management; landscape; microhabitat; montane forest; old-growth forest; prediction; remote sensing; species diversity; tree; Biodiversity; Conservation; Ecosystems; Forecasts; Forestry; Remote Sensing; Baden-Wurttemberg; Black Forest; Germany; Germany
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/156376
作者单位	Chair of Silviculture, University of Freiburg, Tennenbacherstr. 4, Freiburg, 79085, Germany; Chair of Remote Sensing and Landscape Information Systems, University of Freiburg, Tennenbacherstr. 4, Freiburg, 79085, Germany
推荐引用方式 GB/T 7714	Asbeck T.,Pyttel P.,Frey J.,et al. Predicting abundance and diversity of tree-related microhabitats in Central European montane forests from common forest attributes[J],2019,432.
APA	Asbeck T.,Pyttel P.,Frey J.,&Bauhus J..(2019).Predicting abundance and diversity of tree-related microhabitats in Central European montane forests from common forest attributes.Forest Ecology and Management,432.
MLA	Asbeck T.,et al."Predicting abundance and diversity of tree-related microhabitats in Central European montane forests from common forest attributes".Forest Ecology and Management 432(2019).