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Sister species that diverged in allopatry in similar environments are expected to exhibit niche conservatism. Using ecological niche modeling and a multivariate analysis of climate and habitat data, I test the hypothesis that the Bicknell's Thrush (Catharus bicknelli) and Gray-cheeked Thrush (C. mimimus), sister species that breed in the North American boreal forest, show niche conservatism. Three tree species that are important components of breeding territories of both thrush species were combined with climatic variables to create niche models consisting of abiotic and biotic components. Abiotic-only, abiotic+biotic, and biotic-only models were evaluated using the area under the curve (AUC) criterion. Abiotic+biotic models had higher AUC scores and did not over-project thrush distributions compared to abiotic-only or biotic-only models. From the abiotic+biotic models, I tested for niche conservatism or divergence by accounting for the differences in the availability of niche components by calculating (1) niche overlap from ecological niche models and (2) mean niche differences of environmental values at occurrence points. Niche background similarity tests revealed significant niche divergence in 10 of 12 comparisons, and multivariate tests revealed niche divergence along 2 of 3 niche axes. The Bicknell's Thrush breeds in warmer and wetter regions with a high abundance of balsam fir (Abies balsamea), whereas Gray-cheeked Thrush often co-occurs with black spruce (Picea mariana). Niche divergence, rather than conservatism, was the predominant pattern for these species, suggesting that ecological divergence has played a role in the speciation of the Bicknell's Thrush and Gray-cheeked Thrush. Furthermore, because niche models were improved by the incorporation of biotic variables, this study validates the inclusion of relevant biotic factors in ecological niche modeling to increase model accuracy.
Pubmed ID: 28770067
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View all literature mentionsA set of global climate layers (climate grids) with a spatial resolution of about 1 square kilometer. The data can be used for mapping and spatial modeling in a GIS or with other computer programs. If you are not familiar with such programs, you can try DIVA-GIS or the R raster package.
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