State Key Laboratory of Protein and Plant Gene Research, School of Life Sciences, Peking University, Beijing, China.
State Key Laboratory of Protein and Plant Gene Research, School of Life Sciences, Peking University, Beijing, China.
Sci Total Environ. 2024 Feb 20;912:169501. doi: 10.1016/j.scitotenv.2023.169501. Epub 2023 Dec 23.
As climate changes increasingly influence species distributions, ecosystem functions, and biodiversity, the urgency to understand how species' ranges shift under those changes is great. Species distribution models (SDMs) are vital approaches that can predict species distributions under changing climates. However, SDMs based on the species' current occurrences may underestimate the species' climatic tolerances. Integrating species' realized niches at different periods, also known as multi-temporal calibration, can provide an estimation closer to its fundamental niche. Based on this, we further proposed an integrated framework that combines eco-evolutionary data and SDMs (phylogenetically-informed SDMs) to provide comprehensive predictions of species range shifts under climate change. To evaluate our approach's performance, we applied it to a group of related species, the Chrysanthemum zawadskii species complex (Anthemidae, Asteracee). First, we investigated the niche differentiation between species and intraspecific lineages of the complex and estimated their rates of niche evolution. Next, using both standard SDMs and our phylogenetically-informed SDMs, we generated predictions of suitability areas for all species and lineages and compared the results. Finally, we reconstructed the historical range dynamics for the species of this complex. Our results showed that the species and intraspecific lineages of the complex had varying degrees of niche differentiation and different rates of niche evolution. Lineage-level SDMs can provide more realistic predictions for species with intraspecific differentiation than species-level models can. The phylogenetically-informed SDMs provided more complete environmental envelopes and predicted broader potential distributions for all species than the standard SDMs did. Range dynamics varied among the species that have different rates of niche evolution. Our framework integrating eco-evolutionary data and SDMs contributes to a better understanding of the species' responses to climate change and can help to make more targeted conservation efforts for the target species under climate change, particularly for rare species.
随着气候变化越来越多地影响物种分布、生态系统功能和生物多样性，了解物种在这些变化下的分布范围如何变化的紧迫性变得越来越大。物种分布模型（SDM）是预测气候变化下物种分布的重要方法。然而，基于物种当前出现的 SDM 可能低估了物种的气候容忍度。整合物种在不同时期的实现生态位，也称为多时间校准，可以提供更接近其基础生态位的估计。基于此，我们进一步提出了一个集成框架，该框架结合了生态进化数据和 SDM（基于系统发育的 SDM），以提供气候变化下物种分布范围变化的综合预测。为了评估我们方法的性能，我们将其应用于一组相关物种，即 Chrysanthemum zawadskii 物种复合体（菊科，菊科）。首先，我们研究了复合体中物种和种内谱系之间的生态位分化，并估计了它们的生态位进化速率。接下来，我们使用标准 SDM 和我们基于系统发育的 SDM 为所有物种和谱系生成了适宜区域的预测，并比较了结果。最后，我们重建了该复合体中物种的历史分布动态。我们的结果表明，复合体中的物种和种内谱系具有不同程度的生态位分化和不同的生态位进化速率。谱系水平的 SDM 可以为具有种内分化的物种提供比物种水平模型更现实的预测。基于系统发育的 SDM 为所有物种提供了更完整的环境包络，并预测了比标准 SDM 更广泛的潜在分布。具有不同生态位进化速率的物种的分布动态有所不同。我们的框架将生态进化数据和 SDM 集成在一起，有助于更好地了解物种对气候变化的反应，并可以帮助针对气候变化下的目标物种进行更有针对性的保护工作，特别是针对稀有物种。
