Conducting animal censuses amongst abrupt topography; aGIS‐based alternative toDistance

Abstract

AbstractManagement often bases decisions on estimates of animal density and population size. Aerial sampling is expensive whilst current ground methods, noticeablyDistancesampling, assume a single detection function for each habitat and that visibility in a given habitat type declines in a smooth, increasing manner with distance from the observer. If the visibility within a habitat varies widely or is suddenly cut off, as amongst abrupt topography, these assumptions are invalidated. We present an affordable, accessible and accurate method for conducting repeated annual censuses on large herbivores in such terrain. We used aGIShabitat‐based approach. Monthly, over a two year period, we conducted repeated road transects inIthalaGameReserve,SouthAfrica, usingGPSto record the geographic position of each sighting. These records (n = 8742) were then imported into aGISand overlaid onto an existing habitat‐typeGISlayer. With the sampled area thus defined as an irregular polygon in theGISencompassing all records, we calculated densities of each herbivore species by habitat type and extrapolated total population size estimates. Estimates of maximum population size for wildebeest and zebra correlated (±15%) with management's estimates based on aerial surveys, walked transects and experience. White rhino are individually counted in the reserve and our estimates (year 1: 52; year 2: 57) matched these known numbers (year 1: 50; year 2: 53). Our method also yielded realistic numbers for impala, but unrealistic numbers for kudu and warthog. OurGIS‐based census technique produced realistic maximum population estimates for abundant grazing and mixed‐feeder mesoherbivores and for scarce, but highly visible, megaherbivores, but not for cryptic species. With the increasing availability ofGISdata, the technique is recommended to those working in abrupt terrain frustrated by the inability of current ground census techniques, principallyDistancesampling, to produce realistic population estimates.