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Pathways of resilience and evasion of tipping in ecosystems

Project description

Shaping of tipping-prone ecosystems

Tipping points represent a crucial concern in the battle against climate change. These points emerge when damage to ecosystems surpasses a critical threshold, leading to profound and irreversible alterations. Human activities are often responsible for such damage, resulting in various impacts on the planet, including climate change. However, recent research has validated that stressed ecosystems tend to develop spatial patterns, such as vegetation, which significantly bolster their capacity to withstand tipping points and recover from damage. The ERC-funded Resilience project investigates how ecosystems’ tipping points can be prevented through structural processes and spatial patterns. The project will integrate fields like ecology, mathematics and data science to foster a dynamic response to the threats posed by climate change.

Objective

There is an urgent need to understand the catastrophic effects that global environmental and climate change can have on the Earth, its system components and ecosystems. One area of critical concern is the imminent high-impact, abrupt and irreversible tipping of ecosystems. Recent discoveries indicate that tipping could be evaded and even reversed in ecosystems through spatial pattern formation of vegetation, thereby creating pathways of resilience. Many undiscovered pathways of resilience through spatial pattern formation could exist for tipping-prone ecosystems. This resilience could be even enhanced by the unexplored connection between spatial pattern formation and community assembly. The aim of RESILIENCE is to fundamentally advance our understanding and predictions of tipping and critical transitions in ecosystems and reveal how these can be evaded and even reversed through spatial pattern formation.

The RESILIENCE team consists of field-leading and complementary PI’s and is capable of addressing all aspects of this overarching project, linking theory and observation, spanning the fields of ecology, physics and mathematics. RESILIENCE will develop a new theory for emerging resilience through spatial pattern formation and link this with real tipping-prone biomes undergoing accelerating global change: savanna and tundra. Central to our theoretical approach is the novel mathematical connection between the origin of the formation of patterns and their resilience once they emerged. Our empirical approach will include the analysis of existing and new data from in situ observations and drone and satellite-based remote sensing. Our research will reveal which conditions and spatial patterns lead to the evasion and even reversal of tipping. Identifying these conditions and patterns will also expose how human interventions can prevent or reverse tipping and uncover that tipping-prone ecosystems could be much more resilient than currently thought.

Fields of science (EuroSciVoc)

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Keywords

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Programme(s)

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Topic(s)

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Funding Scheme

Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.

HORIZON-ERC-SYG - HORIZON ERC Synergy Grants

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Call for proposal

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(opens in new window) ERC-2022-SYG

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Host institution

UNIVERSITEIT UTRECHT
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 3 279 125,00
Address
HEIDELBERGLAAN 8
3584 CS Utrecht
Netherlands

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Activity type
Higher or Secondary Education Establishments
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Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

€ 3 279 125,00

Beneficiaries (4)

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