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Modelling species distribution in complex environments: an evaluation of predictive ability and reliability in five shorebird species

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Many wader populations around the world are declining as a consequence of habitat degradation or loss. It is therefore important to identify species-specific habitat demands accurately and to define the important factors explaining species distribution, in order to develop tools that can be used in conservation planning. The aim of this study is to create reliable, functional and ecologically interpretable predictive distribution models for five breeding wader species. Location 

The archipelago of SW Finland in the Baltic Sea. Methods 

We used multivariate adaptive regression splines (MARS) to create single-species and multiresponse distribution models based on 525 study islands and 12 abiotic and biotic environmental variables. Model evaluation was carried out on independent data not used in model building (100 + 116 islands). The models were tested for discrimination with receiver-operating characteristic statistics and for calibration with Millers calibration statistics (MCS). Results 

The single-species models for the turnstone (Arenaria interpres), redshank (Tringa totanus) and oystercatcher (Haematopus ostralegus) showed good predictive abilities, regarding both discrimination and calibration, when evaluated on independent data. The multiresponse models for the less prevalent species, common sandpiper (Actitis hypoleucos) and the common ringed plover (Charadrius hiaticula) had better discriminative abilities than the single-species models. The most influential predictor overall was occurrence of small larids. Exposure, area of forest and low and flat areas were also important, as well as shore habitats. Main conclusions 

We found that the ability of MARS to fit non-linear and multiresponse models makes it a useful method to quantitatively relate species occurrence to environmental characteristics of a complex environment.
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Keywords: Archipelago; MARS; conservation; islands; species distribution modelling; waders

Document Type: Research Article

Publication date: 2009-03-01

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