19 August 2015 Remote sensing and habitat mapping for bearded capuchin monkeys (Sapajus libidinosus): landscapes for the use of stone tools
Allison M. Howard, Nathan Nibbelink, Sergio Bernardes, Dorothy M. Fragaszy, Marguerite M. Madden
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Abstract
Application of remote sensing and geographic information systems to the characterization of wildlife habitats is an area of growing significance for conservation. We examine the use of space of a group of bearded capuchin monkeys, a species unique in their use of stone tools to extract encapsulated foods. We define important landscape variables associated with the monkeys’ behavior, especially the use of stone tools. Maximum entropy modeling is used to define the landscape characteristics associated with the monkeys’ use of space. The variables evaluated in model building include normalized difference vegetation index, distance to roads, distance to areas of human influence, distance to vertical scarps, elevation, land cover/land use class, and percentages of green vegetation, bare soil, and shadow from spectral mixture analysis. Distance to areas of human influence and distance to vertical scarps were the variables most closely associated with capuchin habitat suitability (permutation importance 31.7% and 21%, respectively). Stone tool use occurred in areas of lower elevation and higher percent green vegetation relative to other behavior. These results may inform efforts for conserving the unique stone tool use of this species, especially relevant due to the recent expansion and intensification of industrial agriculture in the region.
© 2015 Society of Photo-Optical Instrumentation Engineers (SPIE) 1931-3195/2015/$25.00 © 2015 SPIE
Allison M. Howard, Nathan Nibbelink, Sergio Bernardes, Dorothy M. Fragaszy, and Marguerite M. Madden "Remote sensing and habitat mapping for bearded capuchin monkeys (Sapajus libidinosus): landscapes for the use of stone tools," Journal of Applied Remote Sensing 9(1), 096020 (19 August 2015). https://doi.org/10.1117/1.JRS.9.096020
Published: 19 August 2015
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Cited by 7 scholarly publications.
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KEYWORDS
Vegetation

Animal model studies

Remote sensing

Agriculture

Roads

Visualization

Statistical modeling

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