Intersection between environmental data science and the R community in Latin America

Environmental data science is used to solve environmental problems, and to help answer complex questions about biodiversity loss, climate change, and water scarcity, among others thereby allowing sustainable decision-making using data-driven approaches. In this opinion piece, I describe some recent Latin American experiences in the data science community, and what is needed for environmental data scientists to take advantage of those experiences. Specifically, I show the importance of being part of a diverse and local data science community.