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Revista chilena de historia natural

versión impresa ISSN 0716-078X


NAVARRO, FERNANDO R et al. Can insect data be used to infer areas of endemism?: An example from the Yungas of Argentina. Rev. chil. hist. nat. [online]. 2009, vol.82, n.4, pp.507-522. ISSN 0716-078X.

The main purpose of this study is to analyze whether areas of endemism can be characterized quantitatively by using insects, which are typically much more poorly sampled than vertebrates or plants. For this, an optimality criterion in the search for endemic areas was used to analyze approximately 1,100 georeferences from 288 species of holometabolous insects found in the study region, the Yungas (a very moist, montane rainforest), located in north-western Argentina. The optimality criterion is implemented with the programs NDM/VNDM, used to evaluate areas of endemism (i.e. a set of cells defined by two or more endemic species). Five grid sizes were used, three square (Io, 0.5°, and 0.25°) and two rectangular (0.25° x 0.5° and 0.5° x 0.25°). In agreement with the traditional biogeographic proposal, the results of the present study indicate that the Yungas can be characterized as a biogeographic unit with its own identity. Twenty six areas related to Yungas have shown 23 species of insects (in 14 families) as endemic, restricted to Yungas environment, and 46 species (in 10 families) as endemic, present in Yungas and surrounding habitats. Our analysis suggests that the use of insects to identify areas of endemism is a powerful tool, even considering the current fragmentary knowledge of these groups in South América. Given that there is no criterion to choose an optimal grid size, the use of different grid sizes is crucial; medium and small sizes are highly recommended because both identify seemingly different patterns. The quantitative method used here is useful to identify areas of endemism, such as disjoint areas or partially overlapping areas, which are difficult to see with other traditional biogeographic methods.

Palabras clave : biogeography; distribution patterns; Montane forests; NDM/VNDM.

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