Interspecific Interactions as a Factor of Limitation of Geographical Distribution: Evidence Obtained by Modeling Home Ranges of Vole Twin Species Microtus Arvalis – M. Levis (Rodentia, Microtidae)

Abstract Based on the maximum entropy modeling algorithm and using 12 environmental variables, we modeled the distribution of the vole twin species Microtus arvalis and M. levis, with particular attention to regions where the species overlap. For both species models performances were considered “exc...

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Bibliographic Details
Published in:Vestnik Zoologii
Main Authors: Mezhzherin, S. V., Lashkova, E. I., Kozinenko, I. I., Rashevskaya, A. V., Tytar, V. M.
Format: Article in Journal/Newspaper
Language:unknown
Published: Walter de Gruyter GmbH 2017
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Online Access:http://dx.doi.org/10.1515/vzoo-2017-0051
http://content.sciendo.com/view/journals/vzoo/51/5/article-p429.xml
http://www.degruyter.com/view/j/vzoo.2017.51.issue-5/vzoo-2017-0051/vzoo-2017-0051.pdf
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Summary:Abstract Based on the maximum entropy modeling algorithm and using 12 environmental variables, we modeled the distribution of the vole twin species Microtus arvalis and M. levis, with particular attention to regions where the species overlap. For both species models performances were considered “excellent” (AUC > 0.9), although some occurrences appeared in areas of low habitat suitability, whereas in some areas of predicted high habitat suitability there were no occurrences. Apparently, both species do not fully occupy areas predicted to be favorable in terms of habitat suitability and persistence. Th e cause for such restriction are not the considered factors (including bioclimatic), but competitive interactions that prevent individuals of one species from expanding within the home range of the other. Contributions of the considered environmental variables for generating the potential distribution prediction were distinguished: for M. arvalis net primary production alone made the largest contribution (42 %), whereas for M. levis there was a cumulative effect of a number of factors.