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Reserve Selection in Regions with Poor Biological Data Export

Conservation Biology, Vol. 17, No. 1. (2003), pp. 188-195.

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concepts data sampling site_selection south_africa uncertainty

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New approaches to the identification of priority areas for conservation are gaining popularity for their efficiency in maximizing species representation. However, their dependence on detailed distributional data severely hinders their application to regions where such information is limited, although these are commonly also the regions where conservation planning and action are most urgently required. We used exemplar data on the distribution of southern African birds to assess how sampling effort affects the performance of reserve networks selected by methods based on complementarity. We derived four scenarios of data availability from the initial data, resulting from different levels of sampling effort: abundance data, presence/absence data, low sampling effort, and absence of data. Reserve selection based on data obtained with low sampling effort can be highly effective in the representation of species, with a good relative performance also in terms of representation of species in peaks of abundance. This is because although the data on low sampling effort represent far fewer records than the original data, the records retained are biased toward the selection of peaks of abundance, even for the restricted-range species. Although the best results were naturally obtained from the most effort-intensive data set (with abundance data), these results suggest that methods based on complementarity are potentially valuable tools for reserve selection in regions for which biological data are poor. Seleccion de Reservas en Regiones con Datos Biologicos Pobres Resumen: Nuevas metodologias para identificar areas prioritarias para la conservacion estan ganando popularidad por su eficiencia en la maximizacion de representacion de especies. Sin embargo, su dependencia en datos distribucionales detallados obstaculiza severamente su aplicacion en regiones donde la plan-eacion y accion de la conservacion se requiere de manera urgente. Empleamos datos prototipo de distribucion de aves del sur de Africa para evaluar como los esfuerzos del muestreo afectan la ejecucion de redes de reserva seleccionadas por metodos basados en complementariedad. Derivamos cuatro escenarios de disponibilidad de datos para los datos iniciales, que resultan de diferentes niveles de esfuerzo de muestreo: datos de abundancia, datos de presencia/ausencia bajo esfuerzo de muestreo y ausencia de datos. La seleccion de reservas basada en datos obtenidos con un bajo esfuerzo de muestreo puede ser altamente efectiva en la representacion de especies en picos de abundancia. Esto se debe a que, a pesar de que los datos proven-ientes de bajos esfuerzos de muestreo tienen una severa reduccion en el numero de registros en relacion a los datos originales, los registros guardados estan sesgados hacia la seleccion de picos de abundancia, aun para las especies con rango restringido. A pesar de que los mejores resultados fueron naturalmente obtenidos de los juegos de datos con mayor intensidad de esfuerzo (con abundantes datos), estos resultados sugieren que los metodos basados en la complementariedad son una herramienta potencialmente valiosa para la seleccion de reservas en regiones con pocos datos biologicos.


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