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September 2018 Joining the incompatible: Exploiting purposive lists for the sample-based estimation of species richness
Alessandro Chiarucci, Rosa Maria Di Biase, Lorenzo Fattorini, Marzia Marcheselli, Caterina Pisani
Ann. Appl. Stat. 12(3): 1679-1699 (September 2018). DOI: 10.1214/17-AOAS1126

Abstract

The lists of species obtained by purposive sampling by field ecologists can be used to improve the sample-based estimation of species richness. A new estimator is here proposed as a modification of the difference estimator in which the species inclusion probabilities are estimated by means of the species frequencies from incidence data. If the species list used to support the estimation is complete the estimator guesses the true richness without error. In the case of incomplete lists, the estimator provides values invariably greater than the number of species detected by the combination of sample-based and purposive surveys. An asymptotically conservative estimator of the mean squared error is also provided. A simulation study based on two artificial communities is carried out in order to check the obvious increase in accuracy and precision with respect to the widely applied estimators based on the sole sample information. Finally, the proposed estimator is adopted to estimate species richness in the Maremma Regional Park, Italy.

Citation

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Alessandro Chiarucci. Rosa Maria Di Biase. Lorenzo Fattorini. Marzia Marcheselli. Caterina Pisani. "Joining the incompatible: Exploiting purposive lists for the sample-based estimation of species richness." Ann. Appl. Stat. 12 (3) 1679 - 1699, September 2018. https://doi.org/10.1214/17-AOAS1126

Information

Received: 1 May 2017; Revised: 1 November 2017; Published: September 2018
First available in Project Euclid: 11 September 2018

zbMATH: 06979647
MathSciNet: MR3852693
Digital Object Identifier: 10.1214/17-AOAS1126

Rights: Copyright © 2018 Institute of Mathematical Statistics

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Vol.12 • No. 3 • September 2018
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