Studies that question important conceptual and methodological aspects of the field of ecological niche modeling (and species distribution modeling) have cast doubts on whether it is possible to estimate the fundamental niche of a species using presence-only data. The main limitation in niche estimation is that presence data come from the realized niche, which is only a subset of the fundamental niche. Most of the existing methods lack the ability to overcome this limitation and therefore fit niches that resemble the realized niche. To obtain a more accurate estimate of the fundamental niche, we propose using the geographic region that is accessible to a species (based on its dispersal ability) to determine a sampling distribution, in environmental space, from which we can quantify the likelihood of observing a particular environmental combination in a sample of presence points. We incorporate this sampling distribution into a multivariate normal model (i.e., a Mahalanobis distance model) by creating a weight function that modifies the probabilities of observing different environmental combinations in a sample of presences. This modification accounts for the uneven availability of environmental conditions. We show that the parameters of this weighted-normal model can be approximated with a maximum likelihood estimation approach; and then used to draw ellipsoids (confidence regions) that represent the fundamental niche of the species. We illustrate the application of our model with two worked examples. First, we use presence data for an invasive species and an accessible area that includes only its native range to evaluate whether the fitted model predicts confirmed establishments of the species outside its native range. Second, we use presence data for closely related species with known accessible areas to demonstrate how the different dispersal abilities of the species constrain a classic Mahalanobis distance model. Overall, we show that accounting for the distribution of environmental conditions that are accessible to a species indeed affects the estimation of the ellipsoids used to model its fundamental niche.

中文翻译：

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估计基本生态位：考虑校准区域现有气候的不均衡可用性

质疑生态位建模（和物种分布建模）领域的重要概念和方法学方面的研究对是否有可能使用仅存在数据估计物种的基本生态位产生了怀疑。利基估计的主要限制是存在数据来自已实现的利基，它只是基本利基的一个子集。大多数现有方法缺乏克服这种限制的能力，因此适合类似于已实现的壁龛的壁龛。为了获得对基本生态位的更准确估计，我们建议使用物种可进入的地理区域（基于其传播能力）来确定环境空间中的采样分布，我们可以从中量化在存在点样本中观察特定环境组合的可能性。我们通过创建一个权重函数将这种抽样分布合并到一个多元正态模型（即马哈拉诺比斯距离模型）中，该权重函数修改了在存在样本中观察不同环境组合的概率。这种修改解释了环境条件的不均衡可用性。我们表明，这个加权正态模型的参数可以用最大似然估计方法来近似；然后用于绘制代表物种基本生态位的椭球（置信区域）。我们用两个工作示例说明了我们模型的应用。第一的，我们使用入侵物种的存在数据和仅包括其原生范围的可访问区域来评估拟合模型是否预测了该物种在其原生范围之外的确认场所。其次，我们使用具有已知可到达区域的密切相关物种的存在数据来证明物种的不同传播能力如何限制经典的马氏距离模型。总体而言，我们表明，考虑到物种可接近的环境条件的分布确实会影响用于对其基本生态位进行建模的椭球体的估计。我们使用具有已知可到达区域的密切相关物种的存在数据来证明物种的不同传播能力如何限制经典的马氏距离模型。总体而言，我们表明，考虑到物种可接近的环境条件的分布确实会影响用于对其基本生态位进行建模的椭球体的估计。我们使用具有已知可到达区域的密切相关物种的存在数据来证明物种的不同传播能力如何限制经典的马氏距离模型。总体而言，我们表明，考虑到物种可接近的环境条件的分布确实会影响用于对其基本生态位进行建模的椭球体的估计。