Valeria is a 2022 World Wildlife Fund Russell E. Train Fellow
Congratulations to Valeria! The WWF EFN program will support her during her final years of the doctorate program at UC Berkeley.
Valeria Ramírez Castañeda in Leticia, Amazonas, Colombia. Photo by Darío Alarcón
An excerpt from Valeria’s application:
Research and conservation of neotropical snakes is not only relevant but also urgent and timely in the face of the rapid deforestation rate of the Amazon rainforest in the last decade. The city of Leticia, located in the center of the Amazon rainforest, has 50,000 inhabitants of diverse origins who interact in different ways with nature, yet all of them encounter snakes in their daily lives. More than 30 species of snakes are commonly found in this city but at least a hundred live in the Central Amazon basin region, including at least three endemic species. However, it is estimated that millions of snakes are killed daily in Colombia, the main reasons being deforestation and intentional mortality by humans. Therefore, the urbanization processes in the Amazon and the city’s inhabitants are key players in the future of the rainforest.
Snakes are secondary predators and accomplish a key role in the ecosystem as frog, lizard, and small mammal consumers. Thus, studying snake interactions is fundamental to determining trophic networks in the rainforest. My main interest is to understand how reciprocal interaction between species can maintain and produce biodiversity in the tropics. Coevolution has traditionally been based on non-tropical models. For example, in my research topic, one of the best-known predator-prey models is the interaction between Californian garter snakes and their toxic newt prey. Although this model has revealed how resistance against a single toxin in a one-to-one species interaction arises, diversity in the tropics imposes new challenges. In the Colombian Amazon, more than 50 species of snakes species are feeding on frogs that secrete toxin cocktails. Thus, it is necessary to investigate tropical systems to understand coevolution in complex scenarios.