Modelación del nicho ecológico del Roble Negro (Colombobalanus excelsa) y educación ambiental ante cambio climático Ecological Niche Modeling of Black Oak (Colombobalanus excelsa) and Environmental Education in the Face of Climate Change
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El roble negro colombiano (Colombobalanus excelsa) es una especie endémica amenazada que habita cuatro áreas aisladas en Colombia. Este estudio evalúa el efecto del cambio climático sobre su distribución geográfica en el corregimiento La Buitrera, Valle del Cauca, mediante modelación de nicho ecológico con MaxEnt. Se georreferenciaron 53 individuos y se utilizaron 19 variables bioclimáticas para generar modelos de distribución actual y proyecciones para 2030 y 2050 bajo escenarios de cambio climático (SSP2-4.5 y SSP5-8.5). Los resultados muestran que las condiciones climáticas óptimas para la especie se concentran en áreas específicas con temperaturas entre 16-25°C y precipitaciones de 1.841-3.000 mm anuales. El modelo predice cambios significativos en la distribución potencial, con reducciones de hasta 68.4% en áreas óptimas hacia 2050. Esta información es crucial para desarrollar estrategias de conservación de esta especie vulnerable y su hábitat fragmentado, así como para fortalecer la educación ambiental en contextos locales.
The Colombian black oak (Colombobalanus excelsa) is an endangered endemic species inhabiting four isolated areas in Colombia. This study evaluates the effect of climate change on its geographical distribution in La Buitrera district, Valle del Cauca, through ecological niche modeling with MaxEnt. Fifty-three individuals were georeferenced and 19 bioclimatic variables were used to generate current distribution models and projections for 2030 and 2050 under climate change scenarios (SSP2-4.5 and SSP5-8.5). Results show that optimal climatic conditions for the species are concentrated in specific areas with temperatures between 16-25°C and annual precipitation of 1,841-3,000 mm. The model predicts significant changes in potential distribution, with reductions of up to 68.4% in optimal areas by 2050. This information is crucial for developing conservation strategies for this vulnerable species and its fragmented habitat, as well as for strengthening environmental education in local contexts.
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