RESEARCH PAPER
Counting giraffes: A comparison of abundance estimators on the Ongava Game Reserve, Namibia
 
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1
Université de Lyon; CNRS, UMR 5558, Laboratoire de Biométrie et Biologie Évolutive
 
2
Ongava Research Center
 
 
Online publication date: 2023-03-06
 
 
Publication date: 2023-03-06
 
 
Corresponding author
Christophe Bonenfant   

Centre National de la Recherche Scientifique
 
 
Hystrix It. J. Mamm. 2023;34(1):1-7
 
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ABSTRACT
Camera-traps are a versatile and widely adopted tool for collecting biological data for wildlife conservation and management. While estimating population abundance from camera-trap data is the primarily goal of many projects, the question of which population estimator is suitable for analysing these data needs to be investigated. We took advantage of a 21 day camera-trap monitoring period of giraffes (Giraffa camelopardalis angolensis) on the Ongava Game Reserve (Namibia) to compare capture-recapture (CR), rarefaction curves and N-mixture estimators of population abundance. A marked variation in detection probability of giraffes was observed both in time and between individuals, with a skewed occurrence of animals at some waterholes. The mean daily visit frequency of waterholes by giraffes was f= 0.25 although they were less likely to be detected after they were seen at a waterhole. We estimated the population size to be 104 giraffes (Cv= 0.02) using the most robust reference estimator (CR). All other estimators deviated from the CR population size by ca. -16 to > +106\%. This was due the fact that these models did not account for the temporal and individual variations in detection probability. We found that modelling choice was much less forgiving for N-mixture models than CR estimators because the former leads to very variable and inconsistent estimations of abundance. Double counts were problematic for N-mixture models, challenging the use of raw counts (i.e. when individuals are not identified), to monitor the abundance of giraffes or of other species without idiosyncratic coat patterns.
ACKNOWLEDGEMENTS
We are grateful to Jean-Michel Gaillard and Agathe Chassagneux for commenting on a previous draft of the ms and improving Fig. 1. We acknowledge the help and constructive comments by Stefano Focardi and an anonymous reviewer that contributed to improve our manuscript.
eISSN:1825-5272
ISSN:0394-1914
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