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Assessing the performance of nonparametric estimators of species richness in meadows

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Abstract

To accurately measure the number of species in a biological community, a complete inventory should be performed, which is generally unfeasible; hopefully, estimators of species richness can help. Our main objectives were (i) to assess the performance of nonparametric estimators of plant species richness with real data from a small set of meadows located in the Basque campiña (northern Spain), and (ii) to apply the best estimator to a larger dataset to test the effects on plant species richness caused by environmental conditions and human practices. Two non-asymptotic and seven asymptotic accumulation functions were fitted to a randomized sample-based rarefaction curve computed with data from three well sampled meadows, and information theoretic methods were used to select the best fitting model; this was the Morgan-Mercer-Flodin, and its asymptote was taken as our best guess of true richness. Then, five nonparametric estimators were computed: ICE, Chao 2, Jackknife 1 and 2, and Bootstrap; MMRuns and MMMeans were also assessed. According to the criteria set for our performance assessment (i.e., bias, precision, and accuracy), the best estimator was Jackknife 1. Finally, Jackknife 1 was applied to assess the effects of terrain slope and soil parent material, and also fertilization, grazing, and mowing, on plant species richness from a larger dataset (20 meadows). Results suggested that grass cutting was causing a loss of richness close to 30%, as compared to unmowed meadows. It is concluded that the use of nonparametric estimators of species richness can improve the evaluation of biodiversity responses to human management practices.

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Acknowledgements

This work has been financially supported by the ‘Plan Nacional de I+D+i 2004–2007’, through the CGL2005-08046-C03-02/BOS Project. We sincerely thank José Antonio Elorrieta for his company and technical assistance during field work in Urdaibai and Robert K. Colwell for his help with the EstimateS software. Constructive comments and suggestions by two anonymous referees greatly improved a previous version of the manuscript.

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Authors and Affiliations

  1. Department of Ecosystems, NEIKER – Tecnalia, Basque Institute of Agricultural Research and Development, C/Berreaga 1, 48160, Derio, Spain

    José Antonio González-Oreja, Carlos Garbisu, Sorkunde Mendarte, Ainhoa Ibarra & Isabel Albizu

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  1. José Antonio González-Oreja
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  2. Carlos Garbisu
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  3. Sorkunde Mendarte
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  4. Ainhoa Ibarra
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  5. Isabel Albizu
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Correspondence to José Antonio González-Oreja.

Appendix

Appendix

See Table 4.

Table 4 List of the 65 plant species found in the whole data set (200 quadrats), ordered by decreasing Importance Value (IV): IV = M × Q × MC (%). M is the relative frequency of the meadows where a species was present; Q is relative frequency of the quadrats in those meadows where a species was present, and MC (%) is the mean percent cover of every species in those quadrats where it was present
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González-Oreja, J.A., Garbisu, C., Mendarte, S. et al. Assessing the performance of nonparametric estimators of species richness in meadows. Biodivers Conserv 19, 1417–1436 (2010). https://doi.org/10.1007/s10531-009-9770-8

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