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Potential distribution models from two highly endemic species of subterranean rodents of Argentina: which environmental variables have better performance in highly specialized species?

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Abstract

South American rodents of the genus Ctenomys (tuco-tucos) occupy the underground environment, present high specificity to loose and friable soils and have restricted mobility, with a generally fragmented distribution. We use species distribution models (SDMs) in two Ctenomys species from the Atlantic coast and continental areas of Argentina. We develop SDMs using Maxent software for Ctenomys australis and Ctenomys talarum, which coexist in a narrow coastal landscape with restricted distributions. We model the potential distributions of both species using, first, bioclimatic variables (Group 1), and second, Landsat 8 bands and granulometric layers (Group 2). According to the known distributions of the species, the Group 2 variables showed the greatest accuracy for inferring their potential distributions. The most important variables for predicting habitat suitability were, primarily, the majority of granulometric variables and some Landsat 8 bands such as the bands 4 and 5, related to the vegetation cover. We also analyze the level of overlapping niches between these two species, and we found that there is a certain degree of geographical overlap between them, and also present ecologically similar niches, despite the fact that the characteristics of their habitats differ in certain aspects. We conclude that in tuco-tucos species, their potential distributions are better predicted by variables that consider the particular characteristics of soils and cover vegetation, since they are specialized species of substrates. Also, a higher spatial resolution allows a better performance of the Ctenomys species models, which was expected for species with restricted distributions.

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Acknowledgements

We are grateful to all of our colleagues at the “Grupo Ecología Fisiológica y del Comportamiento” and “Grupo de Ecología y Genética de Poblaciones de Mamíferos” of the Departamento de Biología and IMMyC-CONICET, Universidad Nacional de Mar del Plata for their support at various stages of this research. This study was supported by grants of the Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET, PIP 5844), FONCYT (PICT 201-0427), and from Universidad Nacional de Mar del Plata (Project EXA903/18).

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  1. Departamento de Biología, Facultad de Ciencias Exactas y Naturales, Instituto de Investigaciones Marinas y Costeras, (IIMyC, CONICET), Universidad Nacional de Mar del Plata, Dean Funes 3250, 3rd Floor, 7600, Mar del Plata, Argentina

    Ailin Austrich, Marcelo J. Kittlein & Matías S. Mora

  2. División Mastozoología, Museo Argentino de Ciencias Naturales “Bernardino Rivadavia” CONICET, Angel Gallardo 470, C1405DJR, Buenos Aires, Argentina

    Fernando J. Mapelli

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Fig. S1

Binary maps obtained for C. australis from continuous bioclimatic models, applying the Threshold Criteria 1 (TC1) and the Threshold Criteria 2 (TC2). The dark gray area shows the suitable habitat (PDF 611 KB)

Fig. S2

Binary maps obtained for C. talarum from continuous bioclimatic models, applying the Threshold Criteria 1 (TC1) and the Threshold Criteria 2 (TC2). The dark gray area shows the suitable habitat (PDF 501 KB)

Fig. S3

First output of jackknife test showing the relative importance of different environmental variables (Landsat bands and granulometric layers) in Maxent models of C. talarum. The “With variable” bars indicate the gain of the models if each variable is considered independently; “Without variable” bars indicate the gain of the models as one variable is excluded at a time, creating a model with the remaining variables (PDF 7 KB)

Fig. S4

Potential areas of sympatry for C. australis and C. talarum. The dark gray area shows the potential area of overlap between both species; the records of occurrence of C. australis (white circles) and C. talarum (black circles) are also shown (PDF 143 KB)

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Austrich, A., Kittlein, M.J., Mora, M.S. et al. Potential distribution models from two highly endemic species of subterranean rodents of Argentina: which environmental variables have better performance in highly specialized species?. Mamm Biol 101, 503–519 (2021). https://doi.org/10.1007/s42991-021-00150-1

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