Biogeographical analysis of the Central American clade of Sechium (Cucurbitaceae)
DOI:
https://doi.org/10.15517/sy4jvh88Keywords:
domesticated species; machine learning; diversity; endemism; soil typesAbstract
Introduction: The genus Sechium P. Brown (Cucurbitaceae) includes 11 species, of which two are domesticated and nine grow in the wild. The Central American clade of Sechium has six species distributed in Panama and Costa Rica. These species have characteristics that can be transferred from wild to domesticated species. Objective: To use three machine learning stacking algorithms and multivariate tools to describe geographic distribution, diversity degree, and endemism, to identify major conservation areas and to promote research for the improvement of the domesticated species. Methods: Two hundred and nine occurrence records were retrieved from the Global Biodiversity Information Facility. Raster values extracted from 21 bioclimatic variables were analyzed with descriptive and multivariate statistics. The species distribution algorithms were assembled with the SSDM library from R software. Results: Most species are distributed in type A and C climates, mainly in volcanic soils, with abundant organic matter. These species can grow at altitudes exceeding 2 000 m and tolerate low temperatures and high humidity levels. K-medoids established two groups and a 0.39 average silhouette coefficient, which indicates a low clustering trend. The stacked distribution models recorded good performance in areas under the curve (AUC) (> 0.75) and true skill statistic (> 0.75). Conclusions: The main variables that supported the models were elevation, soil types, and precipitation. The main endemism and species diversity areas were in the Cordillera de Talamanca, the Cordillera de Guanacaste, the Cordillera de Tilarán, and the Central Volcanic Range (Costa Rica). These species thrive under similar environmental conditions; however, the diverse areas have significantly different precipitation and soil types.
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