4.3 Article

Geoadditive regression modeling of stream biological condition

期刊

ENVIRONMENTAL AND ECOLOGICAL STATISTICS
卷 18, 期 4, 页码 709-733

出版社

SPRINGER
DOI: 10.1007/s10651-010-0158-4

关键词

Proportional odds model; Gradient boosting; Geoadditive regression; Stream biological condition; Maryland Biological Streams Survey

资金

  1. Deutsche Forschungsgemeinschaft (DFG) [HO 3242/1-3]
  2. Interdisciplinary Center for Clinical Research (IZKF) at the University Hospital of the University of Erlangen-Nuremberg [J11]
  3. Smithsonian Institution
  4. US Environmental Protection Agency National Center for Environmental Research (NCER) Science [R831369]
  5. EPA [908959, R831369] Funding Source: Federal RePORTER

向作者/读者索取更多资源

Indices of biotic integrity have become an established tool to quantify the condition of small non-tidal streams and their watersheds. To investigate the effects of watershed characteristics on stream biological condition, we present a new technique for regressing IBIs on watershed-specific explanatory variables. Since IBIs are typically evaluated on an ordinal scale, our method is based on the proportional odds model for ordinal outcomes. To avoid overfitting, we do not use classical maximum likelihood estimation but a component-wise functional gradient boosting approach. Because component-wise gradient boosting has an intrinsic mechanism for variable selection and model choice, determinants of biotic integrity can be identified. In addition, the method offers a relatively simple way to account for spatial correlation in ecological data. An analysis of the Maryland Biological Streams Survey shows that nonlinear effects of predictor variables on stream condition can be quantified while, in addition, accurate predictions of biological condition at unsurveyed locations are obtained.

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

4.3
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