How many are there? Multiple-covariate distance sampling for monitoring pampas deer in Corrientes, Argentina
Talía Zamboni A D , Alicia Delgado B , Ignacio Jiménez-Pérez B and Carlos De Angelo C
+ Author Affiliations
- Author Affiliations
A Facultad de Ciencias Exactas, Físicas y Naturales, Universidad Nacional de Córdoba, Avenue. Haya de la Torre s/n, CP 5000, Córdoba, Argentina.
B The Conservation Land Trust Argentina, Scalabrini Ortiz 3355, 4° J, CP 1425, Buenos Aires, Argentina.
C National Scientific and Technical Research Council (CONICET); Instituto de Biología Subtropical, Facultad de Ciencias Forestales, Universidad Nacional de Misiones; Asociación Civil Centro de Investigaciones del Bosque Atlántico; Bertoni 85, N3370BFA, Puerto Iguazú, Misiones, Argentina.
D Corresponding author. Present address: Alejandro Korn 3189, CP 5016, Córdoba, Argentina. Email: taliazamboni@gmail.com
Wildlife Research 42(4) 291-301 https://doi.org/10.1071/WR14222
Submitted: 26 February 2014 Accepted: 28 May 2015 Published: 3 August 2015
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 1200 km2 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.
Additional keywords: habitat type, line transects, Ozotoceros bezoarticus, roads, survey effort.
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