Environmental factors influencing guanaco distribution and abundance in central Patagonia, Argentina
Julieta Pedrana A B F , Alejandro Travaini A , Juan Ignacio Zanón C , Sonia Cristina Zapata A , Alejandro Rodríguez D and Javier Bustamante E
+ Author Affiliations
- Author Affiliations
A Centro de Investigación Puerto Deseado, Universidad Nacional de la Patagonia Austral, CONICET, Avenida Prefectura Naval S/N, 9050 Puerto Deseado, Santa Cruz, Argentina.
B Present address: Recursos Naturales y Gestión Ambiental. Instituto Nacional de Tecnología Agropecuaria, EEA Balcarce, CC 276, 7620 Balcarce, Argentina.
C Instituto de Ciencias de la Tierra y Ambientales de La Pampa (INCITAP-CONICET), Universidad Nacional de La Pampa, Avenida Uruguay 151, 6300 Santa Rosa, Argentina.
D Department of Conservation Biology. Estación Biológica de Doñana, CSIC, C/Américo Vespucio 26, 41092 Sevilla, España.
E Department of Wetland Ecology & Remote Sensing and GIS lab (LAST-EBD), Estación Biológica de Doñana, CSIC, C/Américo Vespucio 26, 41092 Sevilla, España.
F Corresponding author. Email: pedrana.julieta@inta.gob.ar
Wildlife Research 46(1) 1-11 https://doi.org/10.1071/WR18085
Submitted: 7 May 2018 Accepted: 5 October 2018 Published: 16 January 2019
Abstract
Context: The guanaco is the largest wild herbivore inhabiting the Patagonian steppes. Since the end of the 19th Century, it has suffered a progressive decline in numbers owing to poaching and unregulated hunting because of on an assumed competition with sheep. Unfortunately, there has never been a management program for guanaco populations in Argentine Patagonia. Consequently, the guanaco is still considered a pest species by ranchers and has never been considered profitable in the range management model implemented in Patagonia.
Aims: The present article updates the distribution limits of guanaco and estimate its abundance across Chubut, a large province of Patagonia, Argentina. The relative effects of several environmental and anthropogenic factors on guanaco distribution are also assessed.
Methods: Road surveys (7010 km) and species distribution modelling were used to build a habitat suitability model and a distribution map. A distance sampling method was used to estimate guanaco population densities and size. The survey effort required to monitor population trends in this region was also calculated.
Key results: According to the best habitat suitability model, guanaco distribution decreased with altitude and primary productivity, as measured by Normalised Difference Vegetation Index (NDVI), and increased with the distance to the nearest urban centre and oil field. Guanaco distribution showed a clear geographical pattern in Chubut, with low to medium occurrence probability towards the west and higher values towards the east. Guanaco population size was estimated as 657 304 individuals (95% CI 457 437 to 944 059), with a mean density of 2.97 guanacos km–2. Finally, through simulations of guanaco monitoring, it was estimated that an annual survey effort of 10 to thirty 30-km road transects is needed to detect with confidence a significant population decrease or increase over the next 6 or 10 years.
Conclusions: The habitat suitability map presented herein highlights areas with high guanaco densities in Chubut, where it would be possible to identify ranches suitable for performing profitable herding and shearing experiences.
Implications: The maps of guanaco distribution and density, as well as the survey effort required to monitor population trends, may be used to inform decisions concerning the sustainable use of this species.
Additional keywords: habitat models, Lama guanicoe, monitoring, predictive cartography, population density.
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