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Robust abundance estimates of wild animal populations are needed to inform management policies and are often obtained through mark–recapture (MR) studies. Visual methods are commonly used, which limits data collection to daylight hours and good weather conditions. Passive acoustic monitoring offers an alternative, particularly if acoustic cues are naturally produced and individually distinctive. Here we investigate the potential of using individually distinctive signature whistles in a MR framework and evaluate different components of study design.

Recently introduced unmarked spatial capture–recapture (SCR), spatial mark–resight (SMR), and 2-flank spatial partial identity models (SPIMs) extend the domain of SCR to populations or observation systems that do not always allow for individual identity to be determined with certainty. For example, some species do not have natural marks that can reliably produce individual identities from photographs, and some methods of observation produce partial identity samples as is the case with remote cameras that sometimes produce single-flank photographs.

Accurately estimating hippopotamus (Hippopotamus amphibius) numbers is difficult due to their aggressive nature, amphibious lifestyle, and habit of diving and surfacing. Traditionally, hippos are counted using aerial surveys and land/boat surveys. We compared estimates of numbers of hippos in a lagoon in the Okavango Delta, counted from land to counts from video taken from a DJI Phantom 4TM drone, testing for effectiveness at three heights (40 m, 80 m, and 120 m) and four times of day (early morning, late morning, early afternoon, and late afternoon).

African elephants (Loxodonta africana) are imperiled by poaching and habitat loss. Despite global attention to the plight of elephants, their population sizes and trends are uncertain or unknown over much of Africa. To conserve this iconic species, conservationists need timely, accurate data on elephant populations. Here, we report the results of the Great Elephant Census (GEC), the first continent-wide, standardized survey of African savannah elephants. We also provide the first quantitative model of elephant population trends across Africa.