Title:

Counting giraffes: A comparison of abundance estimators on the Ongava Game Reserve, Namibia

Publication Year:
2022
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 Nmixture 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 giraffe or of other species without idiosyncratic coat patterns. Keywords: camera trap, Giraffa camelopardalis, large mammal, multiple counts, population size, savannah.

Publication Title:

Hystrix, the Italian Journal of Mammalogy

Volume:
2022
Item Type:
Journal Article
Language:
en