Abstract
European bat species are strictly protected by law, and the Member States of the European Union are obliged to record species condition and to contribute to their conservation. Habitat-suitability models are an essential aid in assessing the conservation status and distribution of a species. However, model performance depends on the data quality. This study compares habitat-suitability models that were generated from two data sets that differ in the degree of details included. The first model used data that were low in detail but freely available and the second used data that were very detailed but costly. Three hypotheses were addressed: (1) that the model using low-detailed data is sufficient in its performance to aid the assessment of species distribution and infrastructural planning; (2) the visualisation of actual species distribution is more accurate in the high-detailed model; and (3) habitat-suitability maps can depict species distribution better than species occurrence data alone. To develop models, climate, geographic and roosting data of Myotis bechsteinii were used. Models allowed very good spatial predictions of suitable habitats. However, the model using low-detailed data overestimated suitable habitat. The high-detailed model was more able to predict actual species distribution. These findings were supported by field evaluation where M. bechsteinii could only be detected in areas where both models predicted high habitat suitability. This framework is promising as it resulted in spatially explicit habitat-suitability maps and suggests that similar models may be used to improve the understanding of bat distribution and factors endangering other species of bats.
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Special thanks go to the Hessen-Forst FENA, who provided relevant data for analysis. This study was only possible with the provision of data from the State Offices for the Environment and Geology (HLUG) and Land Management and Geological Information (HVBG).
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Becker, N.I., Encarnação, J.A. Cost-effectiveness of habitat-suitability maps using low-detailed data for elusive bat species. Eur J Wildl Res 58, 945–953 (2012). https://doi.org/10.1007/s10344-012-0637-z
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DOI: https://doi.org/10.1007/s10344-012-0637-z