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

环境变化大规模生态响应机制及预测

基本信息

批准号：
NE/T003510/1
负责人：
Axel Rossberg
金额：
$ 154.57万
依托单位：
Queen Mary University of London
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2020
资助国家：
英国
起止时间：
2020 至无数据
项目状态：
未结题

来源：
https://gtr.ukri.org/projects?ref=NE%2FT003510%2F1
关键词：
Mechanisms prediction large scale ecological

项目摘要

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.

地球上的每一个自然生态系统和每一个景观都是独一无二的。然而，一系列的通用生物多样性模式是一致的观察：共存物种的数量，它们的丰度，和它们的空间分布。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因素？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的反应，必须了解在大空间尺度上构建生态系统的基本过程。最近的突破，我们的空间生物多样性格局的理解已经成为可能的模型，重现大规模的生态现象的发展。在真实的生态系统中一直观察到的主要已知的自然生物多样性模式最近被证明是在这样一个空间模型中自然出现的，即Lotka沃尔泰拉准共生模型（LVMCM），它统一了准共生理论的物种分类、质量效应和斑块动力学范式。在这个项目中，我们建立在这个原型，并使用它来探索macrecology的关键基础和应用问题。LVMCM代表了抽象层面的现实，在这个层面上，政策制定环境目标，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在该拨款的呼吁文本中提出的所有五大问题，即生态系统如何，为什么以及在哪里对大规模压力源做出反应，以及生态（不）稳定性对这些反应起着什么作用。该模型的简单性将使我们能够开发新的分析理论的过程控制空间生物多样性模式和生态系统对压力的反应在大尺度上，从而暴露的原则，可以告知一个直观的理解的机制在工作中，重要的是，这些机制所依赖的条件。将现场数据与LVMCM等基于过程的模型的输出进行比较，我们还将开发新的生态指标和协议，用于从经验数据集进行计算，以及数据要求和再现性指南，供保护生态学家和政策制定者使用。