Predicting Polylepis distribution: vulnerable and increasingly important Andean woodlands

Authors

  • Brian R. Zutta 1 Center for Embedded Networked Sensing, University of California Los Angeles, 3563 Boelter Hall, Los Angeles, CA 90095-1596, EEUU. 2 Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Drive, Pasadena, CA 91109, EEUU.
  • Phillip W. Rundel 1 Center for Embedded Networked Sensing, University of California Los Angeles, 3563 Boelter Hall, Los Angeles, CA 90095-1596, EEUU.
  • Sassan Saatchi 2 Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Drive, Pasadena, CA 91109, EEUU.
  • Jorge D. Casana Parque Nacional Huascarán, Instituto Nacional de Recursos Naturales, Federico Salyrosas N° 555, Huaraz, Perú.
  • Paul Gauthier Gauthier Research School of Biology. The Australian National University, Canberra, ACT 0200. Australia
  • Aldo Soto Centro de Datos para la Conservación, Universidad Nacional Agraria La Molina, Av. La Molina S/N, Apartado 12-056, Perú.
  • Yessenia Velazco Department of Biological Sciences, California State University Los Angeles, 5151 State University Drive, Los Angeles, CA 90032, EEUU.
  • Wolfgang Buermann Center for Tropical Research, Institute of the Environment, University of California Los Angeles, La Kretz Hall, Suite 300, Box 951496, Los Angeles, CA 90095- 1496, EEUU.

DOI:

https://doi.org/10.15381/rpb.v19i2.849

Keywords:

Maxent, MODIS, Polylepis, QSCAT, remote sensing, species distribution modeling, WorldClim.

Abstract

Polylepis woodlands are a vital resource for preserving biodiversity and hydrological functions, which will be altered by climate change and challenge the sustainability of local human communities. However, these highaltitude Andean ecosystems are becoming increasingly vulnerable due to anthropogenic pressure including fragmentation, deforestation and the increase in livestock. Predicting the distribution of native woodlands has become increasingly important to counteract the negative effects of climate change through reforestation and conservation. The objective of this study was to develop and analyze the distribution models of two species that form extensive woodlands along the Andes, namely Polylepis sericea and P. weberbaueri. This study utilized the program Maxent, climate and remotely sensed environmental layers at 1 km resolution. The predicted distribution model for P. sericea indicated that the species could be located in a variety of habitats along the Andean Cordillera, while P. weberbaueri was restricted to the high elevations of southern Peru and Bolivia. For both species, elevation and temperature metrics were the most significant factors for predicted distribution. Further model refinement of Polylepis and other Andean species using increasingly available satellite data demonstrate the potential to help define areas of diversity and improve conservation strategies for the Andes.

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Revista Peruana de Biologia 19(2)

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Published

08/13/2012

Issue

Vol. 19 No. 2 (2012)

Section

Articles

License

Copyright (c) 2012 Brian R. Zutta, Phillip W. Rundel, Sassan Saatchi, Jorge D. Casana, Paul Gauthier Gauthier, Aldo Soto, Yessenia Velazco, Wolfgang Buermann

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How to Cite

Zutta, Brian R., Phillip W. Rundel, Sassan Saatchi, Jorge D. Casana, Paul Gauthier Gauthier, Aldo Soto, Yessenia Velazco, and Wolfgang Buermann. 2012. “Predicting Polylepis Distribution: Vulnerable and Increasingly Important Andean Woodlands”. Revista Peruana De Biología 19 (2): 205-12. https://doi.org/10.15381/rpb.v19i2.849.