MOVING SPECIES: MODELLING SPATIAL AND TEMPORAL RESPONSES TO ENVIRONMENTAL CHANGE

我们周围的世界正在迅速变化。自然栖息地的面积正在缩小，孤立的面积正在增加，气候正在变暖，极端天气事件越来越频繁。这些变化中有许多对生物多样性有负面影响--与我们共享这个星球的动植物。最近的研究记录了物种如何应对最近的气候变化。例如，物种正在将其分布转移到温度较低的高海拔和高纬度地区，随着生长季节的延长和春季的提前，植物在一年中开花时间提前。然而，我们仍然缺乏可靠的模型来预测物种未来的反应，以及生物多样性变化对维持地球生命至关重要的生态系统进程的影响，如养分循环、水净化以及更大空间尺度上的气候调节。本提案试图应对这一挑战。首先，我将综合全球数据库的植物分布和物候（周期性的生活史事件的时间），以检查物种的变化对最近的人为气候变暖的反应。然后，我将尝试模拟这种变化，考虑到物种之间的差异以及物种之间的相互作用，以生成一个统一的框架，将空间和时间的反应结合在一起。其次，我将探讨群落结构与其生态功能之间的联系。越来越多的证据表明，随着时间的推移，更多样化的社区往往更有生产力，更稳定。然而，重要的不仅仅是物种的总数，还有它们之间的互补性。系统发育-进化的生命树-提供了一个物种相似性的测量，因为理论预测，更密切相关的物种将在生态上更相似，因此可以提供一个更好的物种互补性指数。在这里，我将使用植物生命树的信息来解释生产力和北美森林树木群落的系统发育结构之间的关系。然后，我将使用从气候数据中重建物种分布的算法，利用气候预测来预测未来森林群落的可能组成。通过描述未来群落的可能结构，这项工作使我们能够推测气候变化下生态系统功能的可能变化。我的目标是提高我们的能力，不仅预测物种的未来，而且预测未来生态系统的功能特性。

The world around us is changing rapidly. Natural habitats are shrinking in size and increasing in isolation, the climate is warming, and extreme weather events are becoming more frequent. Many of these changes have negative impacts on biodiversity—the plants and animals with which we share the planet. Recent research has documented how species have responded to recent changes in climate. For example, species are shifting their distributions to higher elevations and latitudes where temperatures are cooler, and plants are flowering earlier in the year as the growing season lengthens and spring moves forward. However, we still lack robust models for predicting species’ future responses and the impacts of biodiversity change on the ecosystem processes critical for sustaining life on Earth, such as nutrient cycling, water purification and, at larger spatial scales, climate regulation. This proposal attempts to address this challenge. First, I will synthesise global databases on plant distributions and phenology (the timing of periodic life history events) to examine the variation in species’ response to recent anthropogenic climate warming. I will then attempt to model this variation taking into account species differences as well as the interactions between species to generate a unified framework that brings together both responses in space and time. Second, I will explore the links between the structure of communities and their ecological function. There is growing evidence that more diverse communities tend to be more productive and more stable through time. However, it is not just the total number of species that is important, but also their complementarity to one another. Phylogeny—the evolutionary tree-of-life—provides one measure of species similarity as theory predicts that more closely related species will be more ecologically similar, and thus may provide a better index of species complementarity. Here, I will use information on the plant tree-of-life to characterise the relationship between productivity and the phylogenetic structure of forest tree communities across North America. I will then use algorithms that reconstruct species distributions from climate data to predict the likely composition of future forest communities using climate projections. By describing the likely structure of future communities, this work allows us to speculate on possible changes in ecosystem functioning under climate change. My aim is to improve our ability to predict not only species’ futures, but also the functional properties of future ecosystems.