Climate change, pollution, and habitat loss are hitting marine, freshwater, and land ecosystems all at once, but ecologists lack reliable ways to predict which systems will collapse and which will hold steady. The problem is that current measures of ecological stability are fragmented and flawed. Some track individual species, others track diversity or ecosystem function, but they rarely account for basic statistical realities—that numbers today are linked to numbers yesterday, that nearby populations behave alike, and that related species respond similarly. These ignored correlations make existing stability indicators unreliable. On top of that, multiple stressors interact in unpredictable ways: the effect of rising temperature depends on whether pollution is also present. This project aims to fix those gaps. The researchers will develop new stability indicators that formally account for temporal, spatial, and evolutionary correlations. They will then build simulation models to predict how different ecosystems respond to multiple simultaneous stressors, and test those predictions against real data from terrestrial, marine, and freshwater environments. The work is fundamental science—it will not directly change a policy or a water treatment plant tomorrow. But without better stability indicators, efforts to protect drinking water, fisheries, and forests are essentially guessing. A clearer understanding of when and why ecosystems break down could eventually underpin more targeted conservation and resource management.
View original technical description
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; and 3. Test model predictions and the efficacy of improved indicators of stability using experimental and field collected data from terrestrial, marine and freshwater ecosystems.
Plain English summaries and category classifications on this site are generated by AI and may not perfectly reflect the original research.
Is something wrong? Let us know