Biodiversity Data Science
We are a team of young researchers using data science to aid biodiversity conservation and management, in line with the UN 2030 Agenda for Sustainable Development. Our research employs cutting-edge technologies, such as machine learning, artificial intelligence, and big-data computational frameworks, to unravel the underlying mechanisms driving biodiversity and to forecast global distribution patterns, ranging from genes to entire ecosystems, and from past climate fluctuations to future climate change scenarios. Our analyses consider anthropogenic impacts, such as climate change, habitat degradation, overexploitation and the introduction of invasive species. We share our data under the FAIR principle (easy to find, access and reuse) to citizens, managers, and policymakers so that they can make informed decisions on the best strategies for protecting, conserving, and managing biodiversity. We believe our work is crucial for ensuring a sustainable future for both human society and the natural world.