Artículo

Un Análisis Biogeografico de la Composición y Distribución de la Avifauna de Santa Fe, Argentina

Fandiño, Blas Icon; Giraudo, Alejandro Raul Icon

Otros responsables

Fecha

11/2012

Editorial

Neotropical Ornithological Society

Revista

Ornitología Neotropical

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Institución organizadora

ISSN

1075-4377

eISSN

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Idioma

Español

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Resumen

Understanding the biogeographical patterns, in the space and time, is a key issue to identify priority areas in order to develop biodiversity conservation strategies. Distribution data are often used to prioritize areas for conservation (e.g., IBAs, Hotspots) without questioning their quality and representativeness. We studied the composition, completeness of the inventory and distribution of species of birds in Santa Fe using own data (88,192 records) and records from the literature (101,458) and scientific collections (517), analizing the lack of data distribution and taxonomic assignment errors. In order to assess the adequate spatial scale to prioritize conservation areas, we compared the estimated richness (by means of a nonparametric estimators from point counts) with the total richness recorded using own, published and museum records, using celds of 0,25°, 0,5 °, and 1°. We compared current and historical data in order to detect extinguished species at the regional level (EE) according to IUCN criteria. We estimated the completeness of the Santa Fe inventory by species accumulation curves. Of the 448 species listed in Santa Fe, 431 comprising the provincial bird checklist, while 17 were excluded. The estimated richness was higher that detected richness in 0,25° lat?long cells, begin adequated 0,5°?1° lat?long cells to priorities conservation analyses. We detected four EE in Santa Fe, all global or national threatened species. The species accumulation curves estimated between 438?460 (Exponential) and 450?490 (Clench), showing that some new taxa should be recorded. We identified several problems in data distribution and taxonomic errors that can lead to bias in the detection of priority conservation areas, highlighting the need to assess the quality of data and design appropriate programs for monitoring temporal and spatial scales.

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