权益分类	功能权益	普通用户	{{item.name}}会员
{{category.name}}	{{benefitItem.name}}

The coherence of ecological stability among ecosystems and across ecological scales

生态系统之间和跨生态尺度的生态稳定性的一致性

基本信息

批准号：
NE/T003502/1
负责人：
Andrew Beckerman
金额：
$ 177.82万
依托单位：
University of Sheffield
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%2FT003502%2F1
关键词：
coherence ecological stability among ecosystems

项目摘要

Climate and environmental change is impacting on all ecosystems - marine, freshwater and terrestrial - in the world. The changes are associated with a wide range of 'stress' like rising temperature, drought, nutrient run-off, pesticides, over-harvesting and habitat loss. For example, more than 50% of freshwater aquatic communities that provide drinking water, recreation and food are threatened by detrimental anthropogenic stress in the last century, including rising temperature, pollution and N/P run-off. In marine communities, climate change, acidification, overfishing and pollution threaten food resources, coastal communities and carbon storage capacity. In terrestrial communities, rising temperatures, agricultural run-off, habitat fragmentation, pollution and more frequent extreme events threaten to forest, grassland and agricultural communities and the services they provide. This detail suggests that the stability of populations, communities and ecosystem function is threatened by multiple, simultaneous stressors. Making predictions about these effects is hard. We highlight three substantial challenges to advancing the understanding of stability within and among ecosystems. First, there are lots of ways to measure stability and dynamics and they work at different ecological scales - some are about individual species and others are about diversity of many species.. We must demonstrate the value of using simultaneously multiple measures and the appropriateness of them at different ecological scales. Second, the kind of data we use to assess the stability and dynamics of organisms - numbers in time and space and among species - have properties that must be accounted for, but rarely are. We know that the numbers of a species today and yesterday are more related than numbers today and 5 years ago. This is temporal correlation. We know that populations that live close to each other will be more alike than those far apart. This is spatial correlation. And we know that species that are closely related will be more similar than distantly related ones. This is evolutionary correlation. The majority of stability indicators have failed to accommodate these disruptive and well know features of real data. Third, there might be interactions among stressors. This means that the effect of one stressor depends on what the presence, absence or magnitude of another. This make prediction challenging, especially if we don't know about the dependencies. We need theory and data to understand how, and at what scales, multiple stressors impact stability. Our project aims to deal with all of these using three research objectives. 1. Develop improved indicators of stability, at multiple ecological scales (e.g. biomass/abundance, community structure/diversity, function), that formally rectify long recognised but rarely addressed issues arising from spatial, temporal and phylogenetic covariation;2. Make predictions about stability among ecosystems (coherence) facing multiple, simultaneous stressors produced by advanced simulation models that allow insight into the intrinsic processes and feedback mechanisms driving stability; and3. Test model predictions and the efficacy of improved indicators of stability using experimental and field collected data from terrestrial, marine and freshwater ecosystems.

气候和环境变化正在影响世界上所有的生态系统-海洋、淡水和陆地生态系统。这些变化与一系列广泛的“压力”有关，如气温上升、干旱、养分流失、杀虫剂、过度捕捞和栖息地丧失。例如，在上个世纪，超过50%的提供饮用水、娱乐和食物的淡水水生群落受到有害的人为压力的威胁，包括温度上升、污染和N/P径流。在海洋社区，气候变化、酸化、过度捕捞和污染威胁着食物资源、沿海社区和碳储存能力。在陆地社区，气温上升、农业径流、生境破碎化、污染和更频繁的极端事件威胁着森林、草原和农业社区及其提供的服务。这一细节表明，人口，社区和生态系统功能的稳定性受到多重，同时压力。对这些影响做出预测是很困难的。我们强调了三个重大挑战，以促进对生态系统内部和之间的稳定性的理解。首先，有很多方法来衡量稳定性和动态性，它们在不同的生态尺度上起作用-有些是关于单个物种的，有些是关于许多物种的多样性。我们必须证明同时使用多种措施的价值及其在不同生态尺度上的适当性。第二，我们用来评估生物体稳定性和动态的数据--时间和空间上的数量以及物种之间的数量--具有必须被解释的特性，但很少被解释。我们知道，一个物种的今天和昨天的数量比今天和5年前的数量更相关。这就是时间相关性。我们知道，生活在一起的人比生活在一起的人更相似。这就是空间相关性。我们知道，亲缘关系近的物种比亲缘关系远的物种更相似。这就是进化相关性。大多数稳定性指标都未能适应真实的数据的这些破坏性且众所周知的特征。第三，压力源之间可能存在相互作用。这意味着一个压力源的影响取决于另一个压力源的存在、不存在或大小。这使得预测具有挑战性，特别是如果我们不知道依赖关系。我们需要理论和数据来了解多种压力源如何以及在何种程度上影响稳定性。我们的项目旨在使用三个研究目标来处理所有这些问题。1.在多个生态尺度（例如生物量/丰度、群落结构/多样性、功能）上制定更好的稳定性指标，正式纠正长期公认但很少解决的空间、时间和系统发育协变问题;2.预测生态系统的稳定性（一致性），这些生态系统面临着由先进的模拟模型产生的多个同时的压力源，这些模型可以洞察驱动稳定性的内在过程和反馈机制;利用从陆地、海洋和淡水生态系统收集的实验和实地数据，测试模型预测和改进的稳定性指标的效力。