The study of species' environmental niches underpins numerous questions in ecology and evolution and has increasing relevance in a rapidly changing world. Environmental niches, characterized by observations of organisms, inform about a species' specialization in multivariate environment space and help assess their exposure and sensitivity to changing conditions. Environmental niches are also the central concept behind species distribution models (SDMs), which quantify and predict the geographic variation in environmental suitability. Despite the clear role of past evolutionary processes in shaping contemporary biodiversity distribution, the assessment of multivariate or n‐dimensional (where n is the number of environmental axes) niches in a phylogenetic framework has remained limited and constrained by restrictive assumptions. This hampers important existing and emerging applications, such as assessments of niche conservatism, estimates of species' adaptive potential under changing climates, and prediction of niches in less‐studied parts of the tree of life. Here, we introduce a framework that extends SDMs to estimate n‐dimensional environmental niches jointly with underlying evolutionary processes. Specifically, we fit the relationship between niche similarity and phylogenetic distance as a latent Gaussian process across all species in a clade. We demonstrate mathematically how the parameters of the Gaussian process can be linked to existing traditional evolutionary models. Simulations indicate that the approach successfully recovers niche and evolutionary parameters. Applied to two clades of hummingbirds, the presented joint framework uncovers the relationships among species' niches in phylogenetic space and supports the quantification and hypothesis testing of niche evolution. A key advantage of the presented framework is its joint estimation of the evolutionary process alongside niches directly from species observations with uncertainty propagated to evolutionary model parameters. The proposed approach has the potential to increase the robustness of inference about niche evolution and improve understanding of how the processes of niche formation and evolution interact.

中文翻译：

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测量 n 维环境生态位的演变


对物种环境生态位的研究支撑着生态学和进化论中的许多问题，并且在快速变化的世界中具有越来越大的相关性。以观察生物体为特征的环境生态位告知物种在多元环境空间中的特化，并有助于评估它们对变化条件的暴露和敏感性。环境生态位也是物种分布模型 （SDM） 背后的中心概念，该模型量化和预测环境适宜性的地理变化。尽管过去的进化过程在塑造当代生物多样性分布方面发挥着明确的作用，但在系统发育框架中对多变量或 n 维（其中 n 是环境轴的数量）生态位的评估仍然受到限制并受到限制性假设的约束。这阻碍了重要的现有和新兴应用，例如生态位保守性的评估、物种在气候变化下的适应潜力的估计，以及生命之树中研究较少的部分的生态位预测。在这里，我们介绍了一个框架，该框架扩展了 SDM 以与潜在的进化过程一起估计 n 维环境生态位。具体来说，我们将生态位相似性和系统发育距离之间的关系拟合为一个分支中所有物种的潜在高斯过程。我们用数学方法演示了高斯过程的参数如何与现有的传统进化模型联系起来。模拟表明，该方法成功地恢复了生态位和进化参数。 应用于蜂鸟的两个分支，所提出的联合框架揭示了物种在系统发育空间中生态位之间的关系，并支持生态位进化的量化和假设检验。所提出的框架的一个关键优势是它直接从物种观察中对进化过程和生态位的联合估计，不确定性传播到进化模型参数。所提出的方法有可能提高关于生态位进化的推理的稳健性，并提高对生态位形成和进化过程如何相互作用的理解。