Research project NG| GINAMO: genetic indicators for nature monitoring
The ongoing biodiversity crisis risks nature’s contributions to people and is being intensified by climate change. Genetic diversity within species is key to maintaining adaptive potential and ecosystem resilience. It is one of the three pillars of biodiversity, but is widely ignored in both policy and management, due to knowledge and implementation gaps.
Project description
In GINAMO, we follow a co-creation process to provide clear scientific guidelines and ready-to-use workflows to estimate genetic indicators that are understood and embraced by end users. Two indicators in the Kunming-Montreal Global Biodiversity Framework are appropriate for monitoring and reporting on genetic diversity.
These indicators relate
a) to a minimum effective population size, Ne, of 500, with Ne being an essential biodiversity variable enabling the quantification of genetic diversity loss and
b) to maintain genetically distinct populations within species.
In GINAMO we first will determine best practices to obtain accurate and robust Ne estimates for species with reference DNA-based data. Genetic data will help designing realistic evolutionary scenarios for simulations, to understand how spatial distributions, life history traits, data quantity and types, sampling strategies and statistical methods affect Ne estimates.
For species without DNA-based data available, we will develop best practices to estimate Ne from proxies with publicly available data sources (e.g population size counts, occurrence data in observation portals, and relevant terrestrial habitat properties generated by satellite and drone data).
A key component in GINAMO is to partner and co-decide from the outset with the stakeholder community for an optimal integration of all resources produced from our activities (i.e. databases, scripts, and guidelines) to meet their concerns, reporting duties and monitoring needs.
Standardised and automated workflows will be co-created for assessing genetic indicators on various transboundary geographical scales, following FAIR (findable, accessible, interoperable and reusable) principles. The impact of the co-creation processes on participants’ knowledge, perceived usefulness of genetic indicators and willingness to implement, will be evaluated through interviews, focus groups and surveys. This co-creation process will strongly benefit from the multidisciplinary research team, including both natural and social scientists with expertise in policy and implementation.
GINAMO effectively fits all three themes as it will integrate various sources of available data in existing biodiversity databases to address knowledge gaps and provide outreach materials and Open Science tools for genetic indicators applicable in international (e.g. EU Biodiversity Strategy for 2030) and national policies, to improve new biodiversity data collection and inform specific conservation management actions. GINAMO is an EU Biodiversa+ project.
Project members
Project managers
Ian Brown
Associate professor, Docent
