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Xin-lei Guo, Shu-hua Yi, Yu Qin, Jian-jun Chen. Habitat environment affects the distribution of plateau pikas: A study based on an unmanned aerial vehicle[J]. Pratacultural Science, 2017, 11(6): 1306-1313. DOI: 10.11829/j.issn.1001-0629.2017-0090
Citation: Xin-lei Guo, Shu-hua Yi, Yu Qin, Jian-jun Chen. Habitat environment affects the distribution of plateau pikas: A study based on an unmanned aerial vehicle[J]. Pratacultural Science, 2017, 11(6): 1306-1313. DOI: 10.11829/j.issn.1001-0629.2017-0090

Habitat environment affects the distribution of plateau pikas: A study based on an unmanned aerial vehicle

  • Plateau pikas (Ochotona curzoniae) were considered a keystone species on the Qinghai-Tibetan plateau (QTP). Much attention has been paid to the effect of habitat environment on their spatial distribution. However, most of the previous studies mainly focused on qualitative description, because pikas’ holes were difficult to identify by satellite-based remote sensing and traditional field observation was time-consuming. High-precision photography and low costs make the use of unmanned aerial vehicles (UAVs) a feasible option for investigating the spatial distribution of pikas at the plot or even the regional scale. In the present study, we investigated pikas’ burrow density by using aerial photography with light UAVs from July to August 2015. Altogether, approximately 300 work points were set and 1800 aerial photos were obtained. Each photograph covered 26 m×35 m on the ground and each pixel covered approximately 1 cm2. Coupled with normalized difference vegetation index (NDVI), soil water content (SWC) and land surface temperature (LST) data derived from satellite——based remote sensing, we analysed the effect of habitat environment on plateau pikas’ spatial distribution. The results showed that 1) the burrow density of pikas significantly varied with grassland types (P<0.05); alpine meadows had the maximum burrow density, whereas deserts had the lowest; 2) the most suitable habitat for pikas was 0.5~0.6 for NDVI, 20%~25% for SWC, and 28.5~29 ℃ for LST, respectively; and 3) burrow density was positively correlated with NDVI and SWC (P<0.05), but significantly negatively correlated with LST (P<0.05). Our results suggested that NDVI, SWC, and LST were the dominant factors affecting the distribution of pikas. Owing to the high resolution of the aerial photographs, UAVs provided a novel and efficient method of improving our understanding of the role of pikas over large regions on the QTP.
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