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EU funding (€2,439,071): Biodiversity change across time and space in the Anthropocene: Leveraging metacommunity modelling, land-use change, and open data to achieve deeper understanding Hor13 Jul 2023 EU Research and Innovation programme "Horizon"
Overview
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Biodiversity change across time and space in the Anthropocene: Leveraging metacommunity modelling, land-use change, and open data to achieve deeper understanding
Despite connections between metacommunity level processes that maintain biodiversity and anthropogenic pressures that erode those processes, these have not been well integrated. I propose a multifaceted approach that (1) builds on metacommunity theory to develop expectations for the influence of anthropogenic drivers on scale-explicit biodiversity change; (2) uses this theory to develop an analytical pipeline to disentangle local and landscape factors driving this change; (3) use the derived results to develop scale-explicit projections of future biodiversity change that can aide biodiversity policy decisions. With theoretical expectations and analytical procedures in hand, we will synthesize biodiversity change across scales, and the relative influence of local versus landscape-level drivers on those changes. We will apply our analytical pipeline to the largest compilation of metacommunity time series to provide a comprehensive analysis of biodiversity change. We will complement this with a data collection campaign to resurvey zooplankton metacommunities from ponds that had been surveyed 10-50 years previously, but which have experienced different levels of background change (e.g., loss of nearby habitat). We will also compile a database to explore the potential influence of habitat restoration via local and landscape processes, and its influence on scale-explicit biodiversity change. We will analyse these synthetic datasets together with geospatial driver data using our novel analytical pipeline. Finally, we will develop a unique pipeline integrating metacomunity theory with our synthetic results and machine learning to develop projections of biodiversity change in the face of scenarios of anthropogenic change. With the information gained, we will contribute not only to a better understanding of the most important feature of life on this planetits biodiversitybut by developing this understanding, we can provide an avenue to mitigate the changes.
Funded Companies:
| Company name | Funding amount |
| MARTIN-LUTHER-UNIVERSITAT HALLE-WITTENBERG | €2,314,071 |
| The University Court of the University of St Andrews | €125,000 |
Source: https://cordis.europa.eu/project/id/101098020
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