4.6 Article

Broad-scale factors shaping the ecological niche and geographic distribution of Spirodela polyrhiza

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PLOS ONE
卷 18, 期 5, 页码 -

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PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pone.0276951

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The selection of appropriate independent variables to create models characterizing ecological niches of species is crucial in distributional ecology. The set of dimensions in which a niche is defined can provide insights into the factors that limit a species' distributional potential. Using a multistep approach, we found that the final selection of variables for modeling the ecological niche of Spirodela polyrhiza varied considerably depending on the algorithms, calibration areas, and spatial resolutions used. However, variables representing extreme temperatures and dry periods were consistently selected, highlighting their importance in shaping the distribution of this species. Our results suggest that an informed selection of variables, statistical filtering, and model selection exercises can improve the determination of variables that shape the niche and distribution of a species, despite differences in data and modeling algorithms.
The choice of appropriate independent variables to create models characterizing ecological niches of species is of critical importance in distributional ecology. This set of dimensions in which a niche is defined can inform about what factors limit the distributional potential of a species. We used a multistep approach to select relevant variables for modeling the ecological niche of the aquatic Spirodela polyrhiza, taking into account variability arising from using distinct algorithms, calibration areas, and spatial resolutions of variables. We found that, even after an initial selection of meaningful variables, the final set of variables selected based on statistical inference varied considerably depending on the combination of algorithm, calibration area, and spatial resolution used. However, variables representing extreme temperatures and dry periods were more consistently selected than others, despite the treatment used, highlighting their importance in shaping the distribution of this species. Other variables related to seasonality of solar radiation, summer solar radiation, and some soil proxies of nutrients in water, were selected commonly but not as frequently as the ones mentioned above. We suggest that these later variables are also important to understanding the distributional potential of the species, but that their effects may be less pronounced at the scale at which they are represented for the needs of this type of modeling. Our results suggest that an informed definition of an initial set of variables, a series of statistical steps for filtering and exploring these predictors, and model selection exercises that consider multiple sets of predictors, can improve determination of variables that shape the niche and distribution of the species, despite differences derived from factors related to data or modeling algorithms.

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