Estimating optimal complexity for ecological niche models: A jackknife approach for species with small sample sizes
Estimating optimal complexity for ecological niche models: A jackknife approach for species with small sample sizes
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DOI：
10.1016/j.ecolmodel.2013.08.011
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发表时间：
2013-11-10
影响因子：
3.1
通讯作者：
Anderson, Robert P.
中科院分区：
文献类型：
--
作者：
Shcheglovitova, Mariya;Anderson, Robert P.
生态位模型和物种分布模型的生成算法在植物地理学和保护生物学中有着广泛的应用。然而，在某些情况下，这些算法产生的模型可能并不代表最佳的复杂性水平，因此，可能高估或低估了物种的生态容忍度。在这里，我们评估了一种删除一个折刀方法，用于调整模型设置以接近最佳模型复杂度，并增强对数据集的预测，其中数据集很少（在这里，
Algorithms for producing ecological niche models and species distribution models are widely applied in biogeography and conservation biology. However, in some cases models produced by these algorithms may not represent optimal levels of complexity and, hence, likely either overestimate or underestimate the species' ecological tolerances. Here, we evaluate a delete-one jackknife approach for tuning model settings to approximate optimal model complexity and enhance predictions for datasets with few (here,