4.7 Article

LiDAR measurements of canopy structure predict spatial distribution of a tropical mature forest primate

Journal

REMOTE SENSING OF ENVIRONMENT
Volume 127, Issue -, Pages 98-105

Publisher

ELSEVIER SCIENCE INC
DOI: 10.1016/j.rse.2012.08.014

Keywords

Amazon; Carnegie Airborne Observatory; Forest structure; Home range; LiDAR; Pithecia irrorata; Primate; Remote sensing; Saki monkey

Funding

  1. Gordon and Betty Moore Foundation

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The three-dimensional spatial configuration of forest habitats affects the capacity of arboreal vertebrates to move, access food, and avoid predation. However, vegetation sampling over large areas from a sufficient density of field plots to quantify fine-grained heterogeneity in canopy structure is logistically difficult, labor-intensive, time-consuming and costly, particularly in remote areas of tropical forests. We used airborne waveform light detection and ranging (LiDAR) data acquired over the southeastern Peruvian Amazon in combination with detailed field data on a population of bald-faced saki monkeys (Pithecia irrorata) to assess the utility of LiDAR-derived indices of canopy structure in describing parameters of preferred forest types for this arboreal primate. Forest structure parameters represented by LiDAR measurements were significantly different between home range areas used by sakis and those that were not used. Home range areas used by sakis represented a predictable subset of available forest areas, generally those containing the tallest and most uniform canopies. Differences observed within a 335-ha focal area occupied by five previously habituated and systematically followed study groups were consistent across the wider study landscape (6,400 ha): sakis were missing from areas of low-statured, heterogeneous canopies, but they occupied adjacent areas dominated by taller and less variable canopies. These findings provide novel insights into the relationship between vegetation structure and habitat use by a tropical arboreal vertebrate and demonstrate that high-resolution, three-dimensional remote sensing measurements can be useful in predicting habitat occupancy and selection by forest canopy species. (c) 2012 Elsevier Inc. All rights reserved.

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