Objective
Resilience is an essential attribute inherent to natural ecosystems that maintains the health and proper functioning of biological communities. However, major pressures including fishing and climate change are eroding ecosystem resilience, and many biological communities are approaching dangerous tipping points. Crossing such tipping points causes sudden and catastrophic functional phase shifts, in which productive and healthy communities become unhealthy and degraded. The occurrence of these functional phase shifts are especially problematic in marine fish communities, as the associated biodiversity loss generate immeasurable costs for ~500 million people worldwide in terms of food, economics, spirituality, and culture. Due to its importance, international agencies such as the Kunming-Montreal (GBF) and the Sustainable Development Goals (SDGs) have incorporated the priority to avoid the occurrence of phase shifts keeping the resilience of the marine communities into their agendas. However, to date we lack methods to predict where and when these sudden functional changes may occur in an ecosystem. Such predictive tools are, however, crucial if ecosystems are to be prevented from crossing tipping points and, consequently, for maintaining the resilience and proper functioning of natural ecosystems. To overcome this conservation challenge, the aim of RESEALIENT is to investigate and forecast the occurrence of sudden and catastrophic functional phase shifts in marine fish communities. The novelty of our proposal lies in understanding the resilience of marine fish communities through the lens of functional redundancy. For that, we will employ a multidisciplinary approach that integrates theoretical resilience knowledge, empirical functional fish traits, current and future scenarios of fishing and climate change, and cutting-edge machine learning tools with open-source databases and software.
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: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
- agricultural sciencesagriculture, forestry, and fisheriesfisheries
- natural sciencescomputer and information sciencessoftware
- natural sciencescomputer and information sciencesdatabases
- natural sciencesbiological sciencesecologyecosystems
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Keywords
Programme(s)
- HORIZON.1.2 - Marie Skłodowska-Curie Actions (MSCA) Main Programme
Funding Scheme
HORIZON-TMA-MSCA-PF-GF - HORIZON TMA MSCA Postdoctoral Fellowships - Global FellowshipsCoordinator
75794 Paris
France