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Forecasting Global Change Impacts On Ecosystems Using a Unified Plant Functional Spectrum

Project description

Characterising a unified plant functional space and its relationship to ecosystem functioning

Trait-based ecology focuses on how organisms’ functional traits affect their responses to the environment, their interactions and their effects on ecosystem processes. An important goal, particularly in the context of global climate change and biodiversity decline, is the ability to predict community composition and ecosystem functioning from traits. The ERC-funded PLECTRUM project aims to make this possible. Using unprecedented data of aboveground and belowground traits, the team will quantify functional dimensionality and estimate the position of thousands of species in the unified plant functional space. Researchers will then use deep learning to link the functional structure of communities to ecosystem functioning and environmental change.

Objective

Functional traits of organisms determine their responses to the environment, disturbances, biotic interactions, but also their effects on ecosystem processes. Therefore trait-based approaches can potentially advance our understanding of complex ecological questions. However, straightforward approaches for accurate predictions of community composition and ecosystem functioning from traits are not yet available. Studies have considered different traits, which hampers synthesis, and analytical tools have been limited. Trait-based predictions need a holistic approach incorporating all aspects of the functional structure of plant communities within a unified plant functional space (UPFS) that considers the independent information provided by above- and belowground traits. PLECTRUM takes advantage of the UPFS and provides solutions for three of the most intractable problems for trait-based ecology: (i) the dimensionality of functional variation across ecosystems, (ii) predicting functional structure from environmental variables, and (iii) using this knowledge to forecast the effects of global change on functional structure, ecosystem functioning, and species’ extinction risk. I will combine the information from massive datasets of vegetation plots and plant traits with the first global standardized sampling of key above- and belowground traits. I will use this data to quantify functional dimensionality across ecosystems, and estimate the position of thousands of species in the UPFS. Then, I will use species distributions in the UPFS analogous to images and apply deep learning methods to link the functional structure of communities to ecosystem functioning and environmental change. The methodological toolbox developed in the project, combined with the synergy of aboveground and root traits, will allow us to forecast the effects of different global change scenarios on plant communities and their functioning across scales.

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Programme(s)

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Topic(s)

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Funding Scheme

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HORIZON-ERC - HORIZON ERC Grants

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Call for proposal

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(opens in new window) ERC-2023-COG

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Host institution

AGENCIA ESTATAL CONSEJO SUPERIOR DE INVESTIGACIONES CIENTIFICAS
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.

€ 1 210 810,89
Address
CALLE SERRANO 117
28006 MADRID
Spain

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Region
Comunidad de Madrid Comunidad de Madrid Madrid
Activity type
Research Organisations
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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.

€ 1 210 810,89

Beneficiaries (2)

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