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Sampling bias inverts ecogeographical relationships in island reptiles

Authors

  • Gentile Francesco Ficetola,

    Corresponding author
    1. Dipartimento di Scienze dell'Ambiente e del Territorio, e di Scienze della Terra, Università degli Studi di Milano-Bicocca, Milano, Italy
    2. Laboratoire d'Ecologie Alpine (LECA), CNRS UMR 5553, Université Grenoble Alpes, Grenoble Cedex 9, France
    • Correspondence: Gentile Francesco Ficetola, Laboratoire d'Ecologie Alpine (LECA), CNRS UMR 5553, Université Grenoble Alpes, BP 53, 38041 Grenoble Cedex 9, France.

      E-mail: francesco.ficetola@gmail.com

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  • Massimo Cagnetta,

    1. Dipartimento di Scienze dell'Ambiente e del Territorio, e di Scienze della Terra, Università degli Studi di Milano-Bicocca, Milano, Italy
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  • Emilio Padoa-Schioppa,

    1. Dipartimento di Scienze dell'Ambiente e del Territorio, e di Scienze della Terra, Università degli Studi di Milano-Bicocca, Milano, Italy
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  • Anita Quas,

    1. Department of Economics, Finance and Control, EMLYON Business School, ECULLY Cedex, France
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  • Edoardo Razzetti,

    1. Museo di Storia Naturale, Università degli Studi di Pavia, Pavia, Italy
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  • Roberto Sindaco,

    1. Museo Civico di Storia Naturale, Carmagnola, Italy
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  • Anna Bonardi

    1. Dipartimento di Scienze dell'Ambiente e del Territorio, e di Scienze della Terra, Università degli Studi di Milano-Bicocca, Milano, Italy
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  • Editor: José A. F. Diniz-Filho

Abstract

Aim

Species richness is one of the commonest measures of biodiversity, and is a basis for analyses at multiple scales. Data quality may affect estimations of species richness, but most broad-scale studies do not take sampling biases into account. We analysed reptile richness on islands that have received different sampling efforts, and assessed how inventory completeness affects the results of ecogeographical analyses. We also used simulations to evaluate under what circumstances insufficient sampling can bias the outcome of biodiversity analyses.

Location

 Mediterranean islands.

Methods

We gathered data on reptile richness from 974 islands, assuming better sampling in islands with specific inventories. We used Moran's eigenvector mapping to analyse the factors that determine whether an island has been surveyed, and to identify the relationships between reptile richness, geographical parameters and anthropic parameters. We simulated islands, mimicking patterns of true data, and sampled them with varying effort. Simulated richness was analysed using the same approach used for real-world data.

Results

The probability that islands were sampled for reptiles was higher in large, human-populated islands. The relationship between human impact and reptile richness was negative in well-surveyed islands, but positive in islands that had not been systematically surveyed, because densely populated and accessible islands receive better sampling. In simulations, analyses successfully retrieved the relationships between species richness and human presence only if the average species detection probability was ≥75%. Poorer sampling resulted in biased regression results.

Main conclusions

 Human activities may strongly affect biodiversity, but human presence and accessibility improve sampling effort and thus the quality of biodiversity information. Therefore, regressing known species richness on parameters representing human presence may result in apparent positive relationships. These two facets of human presence (positive on biodiversity knowledge, negative on actual biodiversity) represent a major challenge for ecogeographical studies, as not taking them into account would bias analyses and underestimate human impact.

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