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Geoadditive regression modeling of stream biological condition
Authors:Matthias Schmid  Torsten Hothorn  Kelly O. Maloney  Donald E. Weller  Sergej Potapov
Affiliation:1.Institut für Medizininformatik, Biometrie und Epidemiologie,Friedrich-Alexander-Universit?t Erlangen-Nürnberg,Erlangen,Germany;2.Institut für Statistik,Ludwig-Maximilians-Universit?t München,Munich,Germany;3.Smithsonian Environmental Research Center,Edgewater,USA
Abstract: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.
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