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Estimating abundance and population trends when detection is low and highly variable: A comparison of three methods for the Hermann's tortoise

Authors

  • Thibaut Couturier,

    Corresponding author
    1. Laboratoire de Biogéographie et Ecologie des Vertébrés, Ecole Pratique des Hautes Etudes, Centre d'Ecologie Fonctionnelle et Evolutive, UMR 5175, 1919 Route de Mende, F34293 Montpellier Cedex 5, France
    • Laboratoire de Biogéographie et Ecologie des Vertébrés, Ecole Pratique des Hautes Etudes, Centre d'Ecologie Fonctionnelle et Evolutive, UMR 5175, 1919 Route de Mende, F34293 Montpellier Cedex 5, France===

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  • Marc Cheylan,

    1. Laboratoire de Biogéographie et Ecologie des Vertébrés, Ecole Pratique des Hautes Etudes, Centre d'Ecologie Fonctionnelle et Evolutive, UMR 5175, 1919 Route de Mende, F34293 Montpellier Cedex 5, France
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  • Albert Bertolero,

    1. IRTA Aquatic Ecosystems, Ctra. Poble Nou km 5.5, 43540 Sant Carles de la Ràpita, Catalonia, Spain
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  • Guillelme Astruc,

    1. Laboratoire de Biogéographie et Ecologie des Vertébrés, Ecole Pratique des Hautes Etudes, Centre d'Ecologie Fonctionnelle et Evolutive, UMR 5175, 1919 Route de Mende, F34293 Montpellier Cedex 5, France
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  • Aurelien Besnard

    1. Laboratoire de Biogéographie et Ecologie des Vertébrés, Ecole Pratique des Hautes Etudes, Centre d'Ecologie Fonctionnelle et Evolutive, UMR 5175, 1919 Route de Mende, F34293 Montpellier Cedex 5, France
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  • Associate Editor: John Maerz

Abstract

Assessing population trends is a basic prerequisite to carrying out adequate conservation strategies. Selecting an appropriate method to monitor animal populations can be challenging, particularly for low-detection species such as reptiles. This study compares 3 detection-corrected abundance methods (capture–recapture, distance sampling, and N-mixture) used to assess population size of the threatened Hermann's tortoise. We used a single dataset of 432 adult tortoise observations collected at 118 sampling sites in the Plaine des Maures, southeastern France. We also used a dataset of 520 tortoise observations based on radiotelemetry data collected from 10 adult females to estimate and model the availability (g0) needed for distance sampling. We evaluated bias for N-mixture and capture–recapture, by using simulations based on different values of detection probabilities. Finally, we conducted a power analysis to estimate the ability of the 3 methods to detect changes in Hermann's tortoise abundances. The abundance estimations we obtained using distance sampling and N-mixture models were respectively 1.75 and 2.19 times less than those obtained using the capture–recapture method. Our results indicated that g0 was influenced by temperature variations and can differ for the same temperature on different days. Simulations showed that the N-mixture models provide unstable estimations for species with detection probabilities <0.5, whereas capture–recapture estimations were unbiased. Power analysis showed that none of the 3 methods were precise enough to detect slow population changes. We recommend that great care should be taken when implementing monitoring designs for species with large variation in activity rates and low detection probabilities. Although N-mixture models are easy to implement, we would not recommend using them in situations where the detection probability is very low at the risk of providing biased estimates. Among the 3 methods allowing estimation of tortoise abundances, capture–recapture should be preferred to assess population trends. © 2013 The Wildlife Society.

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