Data associated with: Climate change will likely threaten areas of suitable habitats for the most relevant medicinal plants native to the Caatinga dry forest

Medicinal plants play an important role in providing ecosystem services, such as local cultural and economic value, and human well-being, especially in poor regions. The use of plants to improve living conditions and increase the chances of survival comes from the beginning of human life. Climate change has the potential to contract areas of suitable habitat for medicinal plant species across different regions. As a consequence of climate change, the possibility of treating diseases can be compromised, and even interrupted. We collected data from the medicinal applications and the parts that are used of 10 species of medicinal plants native to the Caatinga dry forest [i.e., Myracrodruon urundeuva Allemão (Anacardiaceae), Cereus jamacaru DC (Cactaceae), Neocalyptrocalyx longifolium (Mart) Cornejo & Iltis (Caparaceae), Maytenus rigida Mart (Celastraceae), Operculina hamiltonii (G Don) DF Austin Staples, Operculina macrocarpa (L) Urb (Convolvulaceae), Amburana cearensis (Allemao) AC Sm, Anadenantehra colubrina (Vell) Brenan, Bauhinia cheilantha (Bong) Steud and Erythrina velutina Willd (Legimonosae). In addition, we also collected precise georeferenced data (native occurrence) of these medicinal plant species, that was accessed in 1) The Global Biodiversity Information Facility platform (GBIF) is an international data network funded by governments around the world, providing open access to data on all life on Earth (https:// www.gbif.org, accessed May 2022); 2) REFLORA - Herbário Virtual, virtual herbarium network that contains information on Brazilian plants that are deposited in 63 herbaria in Brazil and 10 international herbaria (http://reflora.jbrj.gov.br/reflora/herbarioVirtual, accessed May 2022); 3) Botanical Information and Ecology Network Platform (BIEN), a global information network that helps to document patterns of plant diversity, trait records and distribution, which includes georeferenced plant observation data from herbarium records, plots, survey inventories (https://bien .nceas.ucsb.edu/bien/biendata, accessed May 2022) and 4) 95 botanical monographs and floras. We excluded all repeated and mismatch occurrence data for each species. We collected all the available points for the studied species.