TY - JOUR
T1 - Undertaking wildlife surveys with unmanned aerial vehicles in rugged mountains with dense vegetation
T2 - A tentative model using Sichuan Snub-nosed monkeys in China
AU - He, Gang
AU - Yan, Xiaodong
AU - Zhang, Xiao
AU - Guo, Ming
AU - Wang, Jie
AU - Wei, Qiangxin
AU - Shen, Yibo
AU - Wang, Chengliang
AU - Lei, Yinghu
AU - Jin, Xuelin
AU - Hou, Xiduo
AU - Guo, Gaigai
AU - Lu, Yu
AU - Zhao, Wenya
AU - Feng, Yimin
AU - Pan, Hao
AU - Zhang, Hexian
AU - Zou, Huan
AU - Wang, Weifeng
AU - Pan, Ruliang
AU - Guo, Songtao
AU - Li, Baoguo
N1 - Funding Information:
We sincerely thank the other team members at the Management Bureau of Shaanxi Changqing National Nature Reserve for their hard work and remarkable contributions. This project was supported by: the National Nature Science Foundation of China ( 32070450 – Gang He, 32371563 – Baoguo Li, 32220103002 – Songtao Guo); the National Giant Panda Park Species and Plant resources protection project (2021 – Gang He); the Key Research and Development Program of Shaanxi ( 2022ZDLSF06-02 – Gang He); the Strategic Priority Research Program of the Chinese Academy of Sciences (XDB 31020302 – Baoguo Li). We also thank Professor Dereck Dunn for his kind help editing this manuscript.
Publisher Copyright:
© 2023 The Authors
PY - 2023/12
Y1 - 2023/12
N2 - Unmanned aerial vehicles (UAVs) have broad applications. However, their use for wildlife surveys in rugged mountains with dense vegetation is uncommon. Therefore, developing appropriately designed methods, selecting suitable facilities, establishing effective monitoring processes, and managing databases that align with a region's distinctive geographic landscapes, environments, ecology, and habitats are essential. This study focuses on the Giant Panda National Park in China's densely vegetated Qinling Mountains to carry out surveys using UAVs to assess the Sichuan snub-nosed monkey population size (Rhinopithecus roxellana) over an area of 30,000 ha. The results indicate that eight distinct groups were identified, totaling 648–755 individuals. Thus, this study offers proof-of-principle for using UAVs for surveying wildlife in remote mountainous regions with complex landscapes and dense vegetation and demonstrates how UAVs can be used in animal monitoring and conservation. Furthermore, the study highlights the broader potential application of UAVs in other remote mountainous regions, where animal demographic information is urgently needed to establish database-driven conservation strategies.
AB - Unmanned aerial vehicles (UAVs) have broad applications. However, their use for wildlife surveys in rugged mountains with dense vegetation is uncommon. Therefore, developing appropriately designed methods, selecting suitable facilities, establishing effective monitoring processes, and managing databases that align with a region's distinctive geographic landscapes, environments, ecology, and habitats are essential. This study focuses on the Giant Panda National Park in China's densely vegetated Qinling Mountains to carry out surveys using UAVs to assess the Sichuan snub-nosed monkey population size (Rhinopithecus roxellana) over an area of 30,000 ha. The results indicate that eight distinct groups were identified, totaling 648–755 individuals. Thus, this study offers proof-of-principle for using UAVs for surveying wildlife in remote mountainous regions with complex landscapes and dense vegetation and demonstrates how UAVs can be used in animal monitoring and conservation. Furthermore, the study highlights the broader potential application of UAVs in other remote mountainous regions, where animal demographic information is urgently needed to establish database-driven conservation strategies.
KW - Design flight routes
KW - Population size and distribution
KW - Primates
KW - The Qinling Mountains
KW - UAV survey
KW - Wildlife dynamic monitoring
UR - http://www.scopus.com/inward/record.url?scp=85174693366&partnerID=8YFLogxK
U2 - 10.1016/j.gecco.2023.e02685
DO - 10.1016/j.gecco.2023.e02685
M3 - Article
AN - SCOPUS:85174693366
SN - 2351-9894
VL - 48
JO - Global Ecology and Conservation
JF - Global Ecology and Conservation
M1 - e02685
ER -