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Abstract BackgroundTrypanosomaare protozoa parasites that infect animals and can cause economic losses in cattle production.Trypanosomalive in the blood and are transmitted by hematophagous insects, such as flies in the genusTabanus.Using ecological niche models, we explored the current geography of six commonTabanusspecies in Brazil, which are considered vectors ofTrypanosoma vivaxandTr. evansiin the Neotropics. MethodsWe used georeferenced data and biotic and abiotic variables integrated using a fundamental ecological niche modeling approach. Modeling results from sixTabanusspecies were used to identify risk areas ofTrypanosomatransmission in Latin America accounting for area predicted, landscape conditions, and density of livestock. We performed Jaccard, Schoener, and Hellinger metrics to indicate the ecological niche similarities of pairs ofTabanusspecies to identify known and likely vectors overlapping in distribution across geographies. ResultsOur results revealed significant ecological niche similarities for twoTabanusspecies (T. pungensandT. sorbillans), whereasT. triangulumandT. importunushave low ecological similarity. Ecological niche models predicted risk ofTrypanosomatransmission across Neotropical countries, with the highest risk in southern South America, Venezuela, and central Mexico. ConclusionsMore than 1.6 billion cattle and 38 million horses are under a threat category for infection risk. Furthermore, we identified specific areas and livestock populations at high risk of trypanosomiasis in Latin America. This study reveals the areas, landscapes, and populations at risk ofTrypanosomainfections in livestock in the Americas. Graphical Abstract 

El conjunto de ideas, métodos y programas informáticos que se conoce como “Modelado de Nicho Ecológico” (MNE)—y el relacionado “Modelado de Distribución de Especies” (MDS)—han sido objeto de intensa exploración e investigación en las últimas décadas. A pesar de existir al menos cuatro síntesis publicadas, este campo ha crecido tanto en complejidad, que la formación de nuevos investigadores es difícil. Hasta ahora, dicha formación se ha hecho de manera presencial en cursos organizados por universidades o centros de investigación, de los que hemos formado parte como instructores. Sin embargo, el acceso a este tipo de cursos especializados es restringido, por un lado, porque los cursos no se ofrecen en todas las universidades, y por otro, porque normalmente se imparten en inglés. Para facilitar el acceso a una mayor comunidad de científicos de habla hispana, presentamos un curso en español, completamente digital y de acceso gratuito, que se realizó vía Internet durante 23 semanas consecutivas en 2018. Aunque las barreras intrínsecas al uso de Internet pueden dificultar la accesibilidad a los materiales del curso, hemos usado diversos formatos para la divulgación de los contenidos académicos (video, audio, pdf) con el objetivo de eliminar la mayor parte de estos problemas. 

The stability of ecological communities is critical for the stable provisioning of ecosystem services, such as food and forage production, carbon sequestration, and soil fertility. Greater biodiversity is expected to enhance stability across years by decreasing synchrony among species, but the drivers of stability in nature remain poorly resolved. Our analysis of time series from 79 datasets across the world showed that stability was associated more strongly with the degree of synchrony among dominant species than with species richness. The relatively weak influence of species richness is consistent with theory predicting that the effect of richness on stability weakens when synchrony is higher than expected under random fluctuations, which was the case in most communities. Land management, nutrient addition, and climate change treatments had relatively weak and varying effects on stability, modifying how species richness, synchrony, and stability interact. Our results demonstrate the prevalence of biotic drivers on ecosystem stability, with the potential for environmental drivers to alter the intricate relationship among richness, synchrony, and stability.