期刊
LANDSCAPE ECOLOGY
卷 28, 期 3, 页码 401-413出版社
SPRINGER
DOI: 10.1007/s10980-013-9847-3
关键词
Apollo butterfly; Conservation planning; Distribution; GLM; Iberian Peninsula; Information-theoretic approach; Lepidoptera; Mountains
资金
- Universidad Rey Juan Carlos/Comunidad de Madrid [URJC-CM-2006-CET-0592]
- Spanish Ministry of Education and Science [REN2002-12853-E/GLO, CGL2005-06820/BOS, CGL2008-04950/BOS]
- British Ecological Society
- Royal Society
Models relating species distribution records to environmental variables are increasingly applied to biodiversity conservation. Such techniques could be valuable to predict the distribution, abundance or habitat requirements of species that are rare or otherwise difficult to survey. However, despite widely-documented positive intraspecific relationships between occupancy and abundance, few studies have demonstrated convincing associations between models of habitat suitability based on species occurrence, and observed measures of habitat quality such as abundance. Here we compared models based on field-derived abundance and distribution (presence-absence) data for a rare mountain butterfly in 2006-2008. Both model types selected consistent effects of environmental variables, which corresponded to known ecological associations of the species, suggesting that abundance and distribution may be a function of similar factors. However, the models based on occurrence data identified stronger effects of a smaller number of environmental variables, indicating less uncertainty in the factors controlling distribution. Furthermore, cross-validation of the models using observed abundance data from different years, or averaged across years, suggested a marginally stronger ability of models based on occurrence data to predict observed abundance. The results suggest that, for some species, distribution models could be efficient tools for estimating habitat quality in conservation planning or management, when information on abundance or habitat requirements is costly or impractical to obtain.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据