Investigating niches and distribution of a rare species in a hierarchical framework: Virginia's Warbler (Leiothlypis virginiae) at its northeastern range limit
Investigating niches and distribution of a rare species in a hierarchical framework: Virginia's Warbler (Leiothlypis virginiae) at its northeastern range limit
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DOI：
10.1007/s10980-021-01217-7
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发表时间：
2021-02-23
影响因子：
5.2
通讯作者：
Swanson, David L.
中科院分区：
文献类型：
--
作者：
Amirkhiz, Reza Goljani;Dixon, Mark D.;Swanson, David L.
上下文小模型集成（ESMs）是一种克服发生点少问题的技术。在空间层次框架中应用esm可以通过在更细的空间尺度上限制可用栖息地来提高预测和结论的准确性。我们的目的是展示在分层生境选择框架中应用esm如何有助于了解不同尺度上稀有物种的生态位。我们比较了委员会平均法和加权平均法的esm的准确性。我们还比较了各种建模技术对弗吉尼亚林莺（leiothlyypis virginiae）在其东北范围内的预测能力。方法定义了美国布莱克山维吉尼亚莺栖息地选择的生物学相关等级顺序，并在最广泛的尺度上模拟了生物气候协变量的栖息地适宜性，在更小的尺度上模拟了土地覆盖、土壤类群和景观协变量的栖息地适宜性。结果不同尺度的建模技术的性能存在差异。采用委员会平均法得到的结果比加权平均法更准确。从最广泛的角度来看，弗吉尼亚莺的气候生态位很窄。协变量的重要性在更精细的顺序中发生了变化，例如在更广泛的顺序中，许多协变量是重要的，而在更精细的顺序中，某些协变量变得比其他协变量更重要。结论在层次结构框架下应用esm可以获得珍稀物种生态位、各生境选择顺序的限制因素和潜在分布的详细信息，为多尺度管理提供依据。
Context Ensemble of small models (ESMs) is a technique to overcome the problem of few occurrence points. Applying the ESMs in a spatially hierarchical framework could increase the accuracy of predictions and conclusions by restricting available habitat at sequentially finer spatial scales. Objectives Our objective was to show how applying ESMs in a hierarchical habitat selection framework could help to understand rare species' niches at various scales. We compared the accuracy of ESMs made by committee averaging and weighted averaging methods. We also compared the predictive power of ESMs made by various modeling techniques for Virginia's warbler (Leiothlypis virginiae) at its northeastern range limit. Methods We defined biologically relevant hierarchical orders of habitat selection for Virginia's warbler in the Black Hills, U.S.A. We modeled habitat suitabity at the broadest scale as a function of bioclimatic covariates and at finer scales as functions of landcover, soil group and landscape covariates. Results The performance of modeling techniques varied among scales. Using the committee averaging method led to more accurate results than weighted averaging. At the broadest order, Virginia's warbler had a narrow climatic niche. The importance of covariates changed across finer orders, such that at broader orders many covariates were important whereas at finer orders certain covariates became more important than others. Conclusion We conclude that applying ESMs within a hierarchical framework can lead to detailed information about rare species' niches, limiting factors at each habitat selection order, and potential distribution, which could help inform multiscale management.