Periodic Reporting for period 1 - NIPMAP (Non-Invasive Predictive Modelling of Amphibian and Pathogen Diversity)
Periodo di rendicontazione: 2023-03-01 al 2025-04-30
The NIPMAP project (Non-Invasive Predictive Modelling of Amphibian and Pathogen Diversity) aimed to develop these tools by integrating molecular methods using DNA collected from amphibian habitats (e.g. pond water), generating maps, and creating open access data repositories. The goal was to create a field-to-conservation-practices ready system to detect, monitor and predict amphibians and pathogens in the environment without direct animal handling.
Focussing on amphibian communities in Alpine habitats, the project combined field sampling with genetic analyses and predictive mapping. DNA from swabs collected from the skin of amphibians and filtered water samples was used to detect species and pathogens and subsequently to build models predicting their presence across diverse environments. These models inform conservation planning, even in areas with limited field access.
To ensure transparency and reusability, data and analytical code are archived on open access platforms such as OpenBioMaps and GitHub, in formats that help stakeholders visualise and interpret results.
NIPMAP worked closely with researchers, park managers, and citizen scientists, building bridges between science and society. Outreach efforts included public seminars and teaching activities to raise awareness on amphibian health and biodiversity. The project delivered a replicable, open framework for long-term monitoring of amphibian populations and emerging pathogens across Europe.
Thanks to the creation of a collaborative network, approximately 40 sites from 11 countries across Europe were surveyed for pathogens and amphibians, leading to a biobank of more than 500 swabs and 80 water filters.
Samples were analysed using mitochondrial and nuclear markers to confirm species presence and genetic structure, and were tested for the three most devastating amphibian pathogens: Batrachochytrium dendrobatidis, B. salamandrivorans (two chytrid fungi), and Ranaviruses.
Spatial models to predict pathogen presence throughout Europe were created using publicly available data, and combined with data on environmental variables like climate. All analytical scripts were developed in R and are available at GitHub. The models can be updated as more data on pathogen presence in Europe is generated.
Skin microbiota data were analysed to compare inter- and intraspecific differences, and to test for variation between pathogen-positive and -negative sites. These results help identify microbial factors potentially linked to pathogen resistance.
The project concluded with the development of a web tool to enable stakeholders to interactively explore and visualise (e.g. in map format) NIPMAP data. This prototype is being tested with interested stakeholders, and could be extended to museums and parks across Europe and beyond to improve access to and re-use of amphibian and pathogen information.
Further uptake will require investment in molecular infrastructure, harmonisation of cross-border data standards (including adoption of FAIR data principles), and the development of protocols for using eDNA in conservation reporting. Continued collaboration with protected areas and NGOs will support long-term implementation at broader scales.