Abstract
Inaccurate estimates of animal populations may lead to flawed management interventions, therefore, it is essential to understand the status and population trend of a species in order to plan its management efficiently. Aerial surveys are considered a useful method for estimating the population size of large conspicuous animals inhabiting large areas, but raw count data from aerial surveys usually underestimate population sizes due to imperfect detection. The use of N-mixture models with aerial count data provides a useful tool to estimate the population sizes while taking detection probability into account. As a study case we used aerial surveys conducted for monitoring black rhinoceros (Diceros bicornis) in Madikwe Game Reserve and Pilanesberg Nature Reserve (South Africa) during 1999–2015, and we analysed data with a dynamic extension of the N-mixture model. We estimated 0.078–0.098 and 0.139–0.142 individuals/km2, respectively, and we found evidence for density dependence in both reserves with a carrying capacity of 0.122 (0.102–0.142) individuals/100 km2. Based on simulations used to assess precision of the estimates, root-mean-square error model (RMSE) estimates was significantly smaller than those for the raw maximum counts.The N-mixture models provide a promising approach to estimate population size, trends and demographic characteristics of large conspicuous mammals such as black rhinoceroses. Such analysis can provide estimates that are more accurate than raw counts. In addition, use of model covariates that affect a species' population parameters can provide useful information for their conservation and management.
Highlights
Reliable information on the status of animal populations is essential to inform decision-making processes, assess the degree of compliance with planned conservation and management goals, or avoid undesirable outcomes from interventionsZ
The density estimates we obtained from this study were between 0.078 and 0.154 rhinos/km2 which were similar to the density estimates reported in Pilanesberg (0.076 individuals/km2) by Adcock et al (1998), who pointed out that this population was still below its ecological carrying capacity
Model selection for the N-mixture model allowed us to confirm that density-dependent processes were evident for these populations of black rhino
Summary
Reliable information on the status of animal populations is essential to inform decision-making processes, assess the degree of compliance with planned conservation and management goals, or avoid undesirable outcomes from interventionsZ. Knowledge of population sizes, especially for those animals that are elusive or distributed over large areas at low density, can be technically difficult or costly to obtain (Skalski, 1994). In such cases, given that there are limited resources for monitoring wildlife populations, there is a need for effective and cost-efficient survey methods (Parker et al, 2011). Species of African rhinoceroses, the white rhino (Ceratotherium simum) and the black rhino (Diceros bicornis), are prime examples of this challenge They typically occur at low density in protected areas administered by government and private owners (Walpole et al, 2001). Over the last two decades, the remaining subspecies have been declining throughout the continent (Amin et al, 2006) despite anti-poaching efforts (Cromsigt et al, 2002; Gakahu, 1993; Hrabar and du Toit, 2005)
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