Throughout the project, the researcher carried out a comprehensive programme combining training, data collection, modelling and dissemination activities. The work was organised in several research modules, each addressing different aspects of extinction risk prediction in freshwater gastropods.
The project compiled an extensive dataset for over 800 hydrobiid species, including geographical, ecological and evolutionary information, which served to train and validate automated extinction risk assessments using the IUCNN machine learning framework. Fieldwork conducted in central and eastern Spain provided fresh specimens for genomic analyses and new occurrence data for range-size reconstruction. This led to the sequencing and assembly of a high-quality reference genome, while 22 lower-coverage genomes from seven species were successfully obtained from museum-preserved material, demonstrating the feasibility of using historical collections as valuable sources of genetic material for conservation studies.
Training activities strengthened the researcher’s expertise in neural network modelling, bioinformatics, and IUCN Red List assessment protocols, as well as in fieldwork safety and conservation management. The project also contributed to national conservation efforts by updating the Libro Rojo de los Invertebrados Amenazados de España for 11 hydrobiid species and by participating in collaborative reports and publications with the IUCN Specialist Groups.
Dissemination and outreach activities increased the project’s visibility among both scientific and general audiences. The problem, methodology and results were presented at international and national conferences, published through institutional channels, and used to educate student teachers and the public.
Although the project concluded earlier than initially planned, all major scientific and training objectives were achieved, laying a strong foundation for future research on freshwater biodiversity conservation in Spain and beyond.
