4.6 Article

Efficacy of Land-Cover Models in Predicting Isolation of Marbled Salamander Populations in a Fragmented Landscape

期刊

CONSERVATION BIOLOGY
卷 23, 期 5, 页码 1232-1241

出版社

WILEY
DOI: 10.1111/j.1523-1739.2009.01204.x

关键词

Ambystoma opacum; geographic information systems; genetic isolation; habitat fragmentation; land cover; marbled salamander

资金

  1. Olentangy River Wetland Research Park
  2. Ohio State University (OSU)
  3. Muelbach Memorial Fund
  4. Columbus Zoo/OSU Cooperative Research

向作者/读者索取更多资源

Amphibians worldwide are facing rapid declines due to habitat loss and fragmentation, disease, and other causes. Where habitat alteration is implicated, there is a need for spatially explicit conservation plans. Models built with geographic information systems (GIS) are frequently used to inform such planning. We explored the potential for using GIS models of functional landscape connectivity as a reliable proxy for genetically derived measures of population isolation. We used genetic assignment tests to characterize isolation of marbled salamander populations and evaluated whether the relative amount of modified habitat around breeding ponds was a reliable indicator of population isolation. Using a resampling analysis, we determined whether certain land-cover variables consistently described population isolation. We randomly drew half the data for model building and tested the performance of the best models on the other half 100 times. Deciduous forest was consistently associated with lower levels of population isolation, whereas salamander populations in regions of agriculture and anthropogenic development were more isolated. Models that included these variables and pond size explained 65-70% of variation in genetically inferred isolation across sites. The resampling analysis confirmed that these habitat variables were consistently good predictors of isolation. Used judiciously, simple GIS models with key land-cover variables can be used to estimate population isolation if field sampling and genetic analysis are not possible.

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。

评论

主要评分

4.6
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据