Limnological layers improve species distribution modeling of aquatic macrophytes at fine-spatial resolution

Abstract

Species distribution modeling (SDM) studies of aquatic macrophytes are still attached to methodological paradigms focused on terrestrial plants, such as the use of bioclimatic layers. Our goal was to evaluate the applicability of this paradigm based on a SDM study of Egeria densa, Pontederia crassipes, and Salvinia auriculata in the São Francisco river, Brazil. We compared performances of optimizations of computed models using AUC and TSS with distribution records of these species and bioclimatic layers, or limnological layers generated from the interpolation of data obtained in the field. We calculated models using six algorithms. The models calculated using layers of limnological variables had higher performances than did those calculated using layers of bioclimatic variables, except when the Maximum Entropy Default algorithm was used. We attribute these results to the specificities of the data obtained to develop the limnological layers, such as observations obtained in different habitats of the river and during different hydrologic periods. We conclude that the use of bioclimatic layers, a methodological paradigm traditionally used for SDM of aquatic macrophytes, can be questionable for some situations, such as in investigations at local and regional scales.