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广泛的因素塑造了穗花狐尾藻的生态位和地理分布。

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

机构信息

Department of Ecology and Evolutionary Biology & Biodiversity Institute, University of Kansas, Lawrence, Kansas, United States of America.

出版信息

PLoS One. 2023 May 4;18(5):e0276951. doi: 10.1371/journal.pone.0276951. eCollection 2023.

Abstract

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.

摘要

选择合适的独立变量来创建描述物种生态位的模型,在分布生态学中至关重要。这个定义生态位的维度集可以说明哪些因素限制了物种的分布潜力。我们使用多步骤方法来选择与水生浮萍(Spirodela polyrhiza)生态位建模相关的变量,考虑到使用不同算法、校准区域和变量空间分辨率所产生的变异性。我们发现,即使在初始选择有意义的变量之后,根据统计推断选择的最终变量集也会根据使用的算法、校准区域和空间分辨率的组合而有很大差异。然而,代表极端温度和干旱期的变量比其他变量更经常被选择,尽管处理方式不同,这突出了它们在塑造该物种分布方面的重要性。其他与太阳辐射季节性、夏季太阳辐射和水中一些营养物质的土壤代用指标相关的变量也经常被选择,但不如上述变量频繁。我们认为,这些后期变量对于理解物种的分布潜力也很重要,但在代表此类建模需求的尺度上,它们的影响可能不那么明显。我们的结果表明,尽管与数据或建模算法相关的因素会导致差异,但通过明智地定义初始变量集、对这些预测因子进行过滤和探索的一系列统计步骤,以及考虑多组预测因子的模型选择练习,可以提高确定塑造物种生态位和分布的变量的能力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8fcd/10159170/66c82c83994d/pone.0276951.g001.jpg

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