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.

中文翻译：

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在一个等级框架中调查稀有物种的生态位和分布：弗吉尼亚的鸣鸟（Leiothlypis virginiae）在其东北范围极限

语境

小模型集合（ESM）是一种克服出现点少的问题的技术。通过在顺序更精细的空间尺度上限制可利用的栖息地，在空间分层框架中应用ESM可以提高预测和结论的准确性。

目标

我们的目标是展示在分级生境选择框架中应用ESM可以如何帮助理解不同规模的稀有物种的生态位。我们比较了委员会平均法和加权平均法得出的ESM的准确性。我们还比较的ESM的预测能力由弗吉尼亚州的莺各种建模技术（由Leiothlypis virginiae）在其东北区间的上限。

方法

我们为美国黑山的弗吉尼亚莺定义了生物相关的栖息地选择等级顺序。我们在最大范围内模拟了生境适应性，将其作为生物气候协变量的函数，在更小尺度上则对土地覆盖率，土壤群和景观协变量的函数进行了建模。

结果

建模技术的性能因规模而异。与加权平均相比，使用委员会平均法得出的结果更准确。从最广泛的角度来看，弗吉尼亚的鸣鸟有狭窄的气候生态位。协变量的重要性随着更精细的顺序而变化，因此在更广泛的顺序中，许多协变量很重要，而在更精细的顺序中，某些协变量变得比其他更重要。

结论

我们得出结论，在分级框架内应用ESM可以得出有关稀有物种的生态位，每个生境选择顺序的限制因素以及潜在分布的详细信息，这可以帮助进行多尺度管理。