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Engaging European local communities in biodiversity genomics research : a five-step framework for scientists
Christian de Guttry, Chiara Bortoluzzi, Luísa S. Marins, Tinatin Chkhartishvili, Camilla R. De Pierri, Stefaniya Kamenova, Jennifer A. Leonard, Kay Lucek, Lada Lukić-Bilela, Camila J. Mazzoni, Elena Bužan, 2026, original scientific article

Abstract: Biodiversity genomics research can inform conservation, management, and policy, including implementation and monitoring linked to the Kunming–Montreal Global Biodiversity Framework (KMGBF). Still, its societal relevance depends on how research is designed and interpreted with the people who live in, work with, and care for the species and places being studied. Local Communities often hold Local Ecological Knowledge that can improve sampling design, contextualise genomic patterns, and support the translation of findings into practice. Yet, community participation in biodiversity genomics remains limited, partly because researchers may lack practical guidance, training, incentives, or time for engagement. Here, we propose a five-step framework for engaging European Local Communities in biodiversity genomics projects. The framework covers early relationship building, respect for local context and knowledge, co-creation of research roles, transparent benefit sharing, and long-term knowledge transfer. We also outline biodiversity genomics-specific points that require early discussion, including biological sampling, genomic sequence data, genetic variant data, analytical outputs, associated ecological and locality information, Digital Sequence Information, repository deposition, interpretation, and reuse. The framework is intended as a practical starting point for research teams, funders, and community collaborators seeking to make biodiversity genomics research more transparent, locally informed, and useful for conservation decision-making.
Keywords: biodiversity conservation, community engagement, equitable research, knowledge co-creation, local ecological knowledge, participatory genomics
Published in RUP: 14.07.2026; Views: 306; Downloads: 13
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