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Assessment of richness estimation methods on macroinvertebrate communities of mountain ponds in Castilla y León (Spain)

Published online by Cambridge University Press:  17 May 2010

Carlos Martínez-Sanz*
Affiliation:
Area of Ecology, Faculty of Biology and Environmental Science, University of León, Campus de Vegazana, s/n. C.P. 24071, León, Spain
Francisco García-Criado
Affiliation:
Area of Ecology, Faculty of Biology and Environmental Science, University of León, Campus de Vegazana, s/n. C.P. 24071, León, Spain
Camino Fernández Aláez
Affiliation:
Area of Ecology, Faculty of Biology and Environmental Science, University of León, Campus de Vegazana, s/n. C.P. 24071, León, Spain
Margarita Fernández Aláez
Affiliation:
Area of Ecology, Faculty of Biology and Environmental Science, University of León, Campus de Vegazana, s/n. C.P. 24071, León, Spain
*
*Corresponding author: cmars@unileon.es
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Abstract

Complete inventories of the fauna at a given place, for a specific community or geographical area are often exceedingly hard to get. In recent years a number of estimation techniques have emerged that can be used to extrapolate from these samples to the true number of species in an area. These estimation models are based on different mathematical approaches and can be classified as either species accumulation curves or nonparametric estimators (Brose et al., 2003, Ecology, 84, 2364–2377). In this paper, we have tested the performance of some of the richness estimators on nineteen mountain ponds in Castilla y León (Spain) in order to provide guidance on their potential use in future researches. We collected benthic macroinvertebrate of these ponds from the littoral zone with a pond net by kicking and sweeping. Ten-second samples were collected in each pond up to a total time of 3 to 5 minutes per pond, depending on the pond size. In addition, two of the ponds, were sampled in 2004, 2006 and 2007 providing a three-year time series. The results of this study showed that Jackknife 2 was the best of the evaluated methods based on all chosen criteria and also performed well across all studied ponds. Jackknife 1, Chao 1 and Chao 2 also presented good results and they were inferior to Jackknife 2 mainly because of the requirement for larger sub-sample sizes.

Type
Research Article
Copyright
© EDP Sciences, 2010

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