Project description
Novel machine learning solution for extinction risk evaluation
The rapidly increasing threat to global biodiversity caused by human-induced climate change has prompted urgent calls for the implementation of new policies and actions to enhance and broaden conservation efforts. Assessing the contemporaneous extinction risk (CER) of species is crucial for quantifying the biodiversity crisis and guiding conservation measures. However, due to taxonomic bias, many understudied taxa, particularly those inhabiting freshwater environments, remain poorly assessed and receive minimal protection. The MSCA-funded PROTECT project will use innovative technologies such as machine learning to identify predictors of CER in freshwater habitats, with a specific focus on hydrobiidae species. The resulting efforts will enhance the understanding of CER predictors, improve the integration of frameworks for conservation, and enhance categorisation methods.
Objective
"Accurate assessments of species’ contemporaneous extinction risk (CER) are vital to quantifying the current biodiversity crisis and prioritising conservation efforts. However, the most comprehensive global dataset of CER - the IUCN Red List of Threatened Species - is taxonomically biased due to the lengthy assessment process, leaving understudied taxa, such as those in freshwaters, under no formal PROTECTion. Prediction-based models based on novel machine learning methods enable large-scale automated assessments of CER, reducing data deficits rapidly. The main goal of this project is to identify predictors of CER in freshwater habitats, focusing on the largest family of freshwater gastropods, the Hydrobiidae. First, we will use a deep-learning approach to automatically predict the Red List status of hundreds of hydrobiid species from multiple regions and ecosystems that have not been evaluated yet, basing the predictions on ecological and macroevolutionary data. Second, high-throughput sequencing methods will be conducted for the first time in this taxon to compare microevolutionary diversity with population trends derived from long-term field surveys. Last, by establishing a multifactorial prediction-based method, the project will identify which features (ecological, macro-, microevolutionary or all) are meaningful to inferring CER in freshwater organisms. The implications of this proposal are threefold and relevant to scientific, technological and societal concerns. Our findings may provide a basis for comparing predictors of CER across taxa. They will also open up a more integrative framework for conservation actions, moving beyond species-by-species categorisation. Focussing on the ""Natural Resources, Agriculture & Environment"" area from HORIZON 2021-2027, this project addresses knowledge gaps in species threats and safeguards freshwater resources, illustrating this with understudied taxa."
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- natural sciences biological sciences ecology ecosystems
- agricultural sciences agriculture, forestry, and fisheries agriculture
You need to log in or register to use this function
Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
-
HORIZON.1.2 - Marie Skłodowska-Curie Actions (MSCA)
MAIN PROGRAMME
See all projects funded under this programme
Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
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.
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-TMA-MSCA-PF-EF - HORIZON TMA MSCA Postdoctoral Fellowships - European Fellowships
See all projects funded under this funding scheme
Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) HORIZON-MSCA-2023-PF-01
See all projects funded under this callCoordinator
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.
28006 MADRID
Spain
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.