Section 38
Chapter 37,709

A simple method for sampling protocols with the object of inventorization of hyper diverse taxa the practical case of the families Araneidae and Thomisidae Araneae in Comunidad de Madrid, Spain Un metodo sencillo para seleccionar puntos de muestreo con el objeto de inventariar taxones hiperdiversos el caso practico de las familias Araneidae y Thomisidae Araneae en la comunidad de Madrid, Espana

Jimenez-Valverde, A.; Lobo, J.M.

Ecologia (Madrid) 18: 297-308


Accession: 037708083

Elaborating effective conservation strategies requires having faunistic information homogenously distributed across the environmental spectrum of conditions of a region. This is possible if data collection has been carried out by well designed, efficient and specific sampling protocols for each biological group. In this paper, an easy methodology is presented for the selection of sampling points, specially useful in the case of hiperdiverse groups, in those the gathering of faunistic information requires a remarkable effort and the taxonomic determination of the collected material is not possible during the field work. The method is based in the classification of the territorial units of a region according to the values of some environmental and spatial variables, previously selected by its recognized influence on the distribution of the considered taxonomical group and compiled in a Geographic Information System. After defining the area and the number of territorial units in which is possible to obtain reliable inventories, the k-means cluster strategy is used to obtain a regional classification in a number of subregions equal to the sampled territorial units. The territorial unit within each subregion can be selected taking into account several criteria as the spatio-environmental distance to the subregional centroid, its accessibility or the amount of previously available information. A practical example of this methodology is provided using the Araneidae and Thomisidae spider families in the Community of Madrid.

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