Spatial abundance models and seasonal distribution for guanaco (Lama guanicoe) in central Tierra del Fuego, Argentina

PLoS One. 2018 May 21;13(5):e0197814. doi: 10.1371/journal.pone.0197814. eCollection 2018.

Abstract

Spatially explicit modelling allows to estimate population abundance and predict species' distribution in relation to environmental factors. Abiotic factors are the main determinants of a herbivore´s response to environmental heterogeneity on large spatiotemporal scales. We assessed the influence of elevation, geographic location and distance to the coast on the seasonal abundance and distribution of guanaco (Lama guanicoe) in central Tierra del Fuego, by means of spatially explicit modelling. The estimated abundance was 23,690 individuals for the non-breeding season and 33,928 individuals for the breeding season. The factors influencing distribution and abundance revealed to be the elevation for the non-breeding season, and the distance to the coast and geographic location for the breeding season. The southwest of the study area presented seasonal abundance variation and the southeast and northeast presented high abundance during both seasons. The elevation would be the driving factor of guanaco distribution, as individuals move to lower areas during the non-breeding season and ascend to high areas during the breeding season. Our results confirm that part of the guanaco population performs seasonal migratory movements and that the main valleys present important wintering habitats for guanacos as well as up-hill zones during summer. This type of study would help to avoid problems of scale mismatch and achieve better results in management actions and is an example of how to assess important seasonal habitats from evaluations of abundance and distribution patterns.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Argentina
  • Biodiversity
  • Camelids, New World / physiology*
  • Herbivory / physiology*
  • Models, Theoretical
  • Population Dynamics
  • Seasons
  • Spatio-Temporal Analysis

Grants and funding

This work received support from Fondo para la Investigación Científica y Tecnológica (FONCYT- ANPCYT, PICT-2011-1329), www.agencia.mincyt.gob.ar/, Proyectos Federales de Innovación Productiva (SCTIP 1198/06), www.cofecyt.mincyt.gob.ar/, and Consejo Nacional de Investigaciones Científicas y Técnicas, www.conicet.gov.ar. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.