Mechanisms and prediction of large-scale ecological responses to environmental change

地球上的每一个自然生态系统和景观都是独一无二的。然而，一系列的一般生物多样性模式被一致地观察到：共存物种的数量、丰度和空间分布的规律性。生态系统如何应对气候变暖、栖息地退化和破碎化、生物量收获和环境污染物积累等广泛的压力源？我们所说的生态环境中的稳定性是什么意思？它是如何与这些压力源相互作用的？为了解决这些紧迫的问题，并能够预测生物多样性对气候变化和其他压力源的反应，有必要了解大空间尺度上构建生态系统的基本过程。我们对空间生物多样性格局的理解最近取得了突破，这是由于重现大规模生态现象的模型的发展。Lotka Volterra元群落模型（LVMCM）结合了元群落理论的物种分选、质量效应和斑块动力学范式，揭示了在现实生态系统中所观察到的主要自然生物多样性模式。在这个项目中，我们以这个原型为基础，用它来探索宏观生态学中的关键基础和应用问题。LVMCM代表了抽象层面的现实，政策制定者制定环境目标，决策者思考环境影响，生态学家提出基本问题。通过进一步探索这种建模方法，我们将解决NERC在这项资助的呼吁文本中提出的所有五个大问题，这些问题包括生态系统如何、为什么和在哪里对大规模压力源做出反应，以及生态稳定性在这些反应中扮演什么角色。该模型的简单性将使我们能够为控制空间生物多样性模式和生态系统对大尺度压力源的反应的过程开发新的分析理论，从而揭示可以直观理解工作机制的原理，更重要的是，揭示这些机制所依赖的条件。将实地数据与基于过程的模型（如LVMCM）的输出进行比较，我们还将开发新的生态指标和基于经验数据集的计算方案，以及数据要求和可重复性的指导方针，供保护生态学家和政策制定者使用。

Each natural ecosystem and each landscape on earth is unique. Yet, a range of generic biodiversity patterns is consistently observed: regularities in the numbers of co-existing species, their abundances, and their spatial distributions. How do ecosystems respond to wide-ranging stressors such as climate warming, habitat degradation and fragmentation, harvesting of biomass, and the accumulation of environmental pollutants? What do we mean by stability in an ecological context and how does it interact with these stressors? In order to address these pressing questions and be able to predict the responses of biodiversity to climate change and other stressors, it is essential to understand the fundamental processes that structure ecological systems over large spatial scales. Recent breakthroughs in our understanding of spatial biodiversity patterns have been made possible by the development of models that reproduce large-scale ecological phenomena. The major known natural biodiversity patterns consistently observed in real ecological systems have recently been shown to emerge naturally in one such spatial model, the Lotka Volterra Metacommunity Model (LVMCM), which unifies the species-sorting, mass-effect, and patch-dynamics paradigms of metacommunity theory. In this project we build upon this prototype and use it to explore key fundamental and applied questions in macrecology. The LVMCM represents reality at the level of abstraction at which policy formulates environmental targets, decision makers think about environmental impacts, and ecologists ask fundamental questions. By further exploring this modelling approach, we will address all five grand questions raised by NERC in the call text for this grant, which ask how, why and where ecosystems respond to large-scale stressors, and what role ecological (in)stability plays for these responses. The model's simplicity will permit us to develop novel analytic theory for the processes controlling spatial biodiversity patterns and ecosystem responses to stressors on large scales, thus exposing principles that can inform an intuitive understanding of the mechanisms at work and--importantly--the conditions on which these mechanisms depend. Comparing field data with outputs from a process-based model like the LVMCM we will also develop novel ecological indicators and protocols for their computation from empirical datasets, together with guidelines on data requirements and reproducibility, for use by conservation ecologists and policy makers.