How many are there? Multiple-covariate distance sampling for monitoring pampas deer in Corrientes, Argentina

Abstract

Context The pampas deer (Ozotoceros bezoarticus) is an endangered species in Argentina. Scarce information exists about one of the four last populations that survive in Corrientes province, where direct counts estimated a population of <500 individuals. Aims To evaluate the status of the pampas deer population in Corrientes by applying a standardised methodology and to develop methodological recommendations for future deer monitoring. Methods We conducted six population censuses between 2007 and 2010, using line transects placed on roads throughout 1200km2 of grasslands in the Aguapey region, Corrientes, Argentina. From a moving vehicle, we counted every pampas deer group observed along transects. We used Distance 6.0 and its multiple-covariate distance sampling engine to estimate deer density, while exploring the potential effect of roads, habitat type, hour, season, observer experience and survey effort on deer occurrence and density estimation. Key results The occurrence of pampas deer was irrespective of transect location (minor or major road) but a greater number of animals was detected over transects in minor roads and in areas covered by grasslands with young pine plantations. We estimated a density of 1.17 individuals km-2 (s.e.≤0.52), and habitat type was the most important covariate for density estimation. We estimated a total population of 1495 deer (95% CI≤951-2351, CV≤23.27%) for the Aguapey region in Argentina. Conclusions Corrientes hosts one of the largest populations of pampas deer in Argentina, with ∼1000 individuals. The fact that we estimated a larger population than did previous studies could be explained either by actual population growth during the past 10 years, or by the use of more exhaustive and sophisticated sampling design and data analysis. Implications Population surveys using covariate distance sampling on ground line transects can provide more realistic population estimates than do other simpler methods. Our population estimates and methods can be used as a baseline for future monitoring of this population, as long as factors such as sampling effort, type of roads for locating transects, and habitat type are considered in future analysis.