生物多样性 ›› 2020, Vol. 28 ›› Issue (9): 1075-1080.DOI: 10.17520/biods.2020094

• 中国野生动物红外相机监测网络专题 • 上一篇    下一篇

秦岭中段野生动物多样性的红外相机监测数据库平台介绍

刘雪华1,*(), 张语克1, 赵翔宇1, 何祥博2, 蔡琼3, 朱云3, 何百锁4, 酒强5   

  1. 1 清华大学环境学院, 北京 100084
    2 佛坪国家级自然保护区, 陕西佛坪 723400
    3 观音山国家级自然保护区, 陕西佛坪 723400
    4 长青国家级自然保护区, 陕西汉中 723000
    5 黄柏塬国家级自然保护区, 陕西太白 721600
  • 收稿日期:2020-04-19 接受日期:2020-06-24 出版日期:2020-09-20 发布日期:2020-11-06
  • 通讯作者: 刘雪华
  • 作者简介:*E-mail: xuehua-hjx@tsinghua.edu.cn
  • 基金资助:
    国家自然科学基金(41271194);国家自然科学基金(41671183);原国家林业局大熊猫国际合作专项资金(CM1424, 2017年项目)

Introduction to the wildlife camera-trapping database of the middle Qinling Mountains

Xuehua Liu1,*(), Yuke Zhang1, Xiangyu Zhao1, Xiangbo He2, Qiong Cai3, Yun Zhu3, Baisuo He4, Qiang Jiu5   

  1. 1 School of Environment, Tsinghua University, Beijing 100084
    2 Foping National Nature Reserve, Foping, Shaanxi 723400
    3 Guanyinshan National Nature Reserve, Foping, Shaanxi 723400
    4 Changqing National Nature Reserve, Hanzhong, Shaanxi 723000
    5 Hangbaiyuan National Nature Reserve, Taibai, Shaanxi 721600
  • Received:2020-04-19 Accepted:2020-06-24 Online:2020-09-20 Published:2020-11-06
  • Contact: Xuehua Liu

摘要:

秦岭地处我国中西部, 生物地理位置重要, 拥有丰富的生物多样性, 有大熊猫(Ailuropoda melanoleuca)、秦岭羚牛(Budorcas bedfordi)、金丝猴(Rhinopithecus roxellana)和朱鹮(Nipponia nippon)等4个秦岭森林旗舰物种, 被称为“秦岭四宝”。利用红外相机技术开展秦岭野生动物的非损伤性监测不仅可以为秦岭山系提供物种名录信息, 还可以为了解秦岭野生动物的行为和活动格局提供科学数据。清华大学环境学院生态团队自2009-2020年在秦岭中段南坡先后实施了7个项目, 对秦岭南坡的4个保护区进行了野生动物监测, 面积达1,113 km 2(26.5 km × 42 km), 红外相机位点数267个, 相机日数152,160天, 共获取红外相机照片855,260张。共鉴定出27种野生兽类和63种野生鸟类, 并应用这些照片数据开展了信息挖掘工作, 对野生动物行为、稀有物种、与生境的关系, 以及人为活动对野生动物的影响等领域进行了研究, 已取得部分成果。在此基础上建立了“秦岭中段野生动物多样性的红外相机监测数据库平台”, 供团队内部及合作者使用。通过10年的监测, 我们提出未来研究建议: (1)对于非常偶见的物种, 还需要更长的时间并在更多样化的生境布设相机, 以获取更多影像数据评估其现状; (2)数据库需要在更大程度和深度上进行信息挖掘, 尤其在种间关系、物种-生境关系、种群动态等方面; (3)对典型大种群数量的物种(如秦岭羚牛和野猪Sus scrofa)及食物链顶端大型捕食动物(如金钱豹Panthera pardus)进行种群动态研究, 为整个秦岭生态系统的健康持续提供科学支撑; (4)利用数据库的数据及今后红外相机监测数据进行野生动物疾病的发生发展监测研究。

关键词: 红外相机技术, 野生动物监测, 物种名录, 秦岭中段, 数据库平台

Abstract

The Qinling Mountains, which are located in the midwestern part of China, are biogeographically important because they are home to China’s four national wildlife treasures, i.e., giant panda (Ailuropoda melanoleuca), golden takin (Budorcas bedfordi), golden monkey (Rhinopithecus roxellana) and crested ibis (Nipponia nippon). These species are also called the four flagship species in the Qinling forest ecosystem. Therefore, using infrared camera trapping to monitor the wildlife in the Qinling Mountains is very important since it can provide information of species and also scientific data on wildlife behaviour and activity pattern. The ecological research team from Tsinghua University conducted camera trappings between 2009 and 2020 in the Qinling Mountains for seven projects. These projects monitored wildlife diversity, primarily in four nature reserves, covering an area of 1,113 km 2 (26.5 km × 42 km). There were a total of 267 camera-trapping sites. For the 152,160 camera working days, we were able to obtain totally 855,260 photos. From these photos we identified 27 mammal species and 63 bird species, and were able to address several research aspects including: wildlife behavior, identifying rare species, understanding habitat use and adaption, and understanding the human impacts on wildlife. Based on the gathered photos, we established the wildlife camera-trapping database of the middle Qinling Mountains, which has only been shared within the research group and collaborators. Based on our results from 10 years of monitoring, we propose the following suggestions for future research: (1) We need much longer time and we need to implement camera trapping in more habitat types to collect more digital images to be able to monitor the status of animal species rarely seen in front of cameras. For example, Mustela kathiah, Lutra lutra, and Catopuma temminckii were each captured only once in 10-year monitoring. (2) More deep data mining work is necessary in using this database to understand species-species relationships, species-habitat relationships, and population dynamics. (3) Continual research on the population dynamics of species with large populations (like Budorcas bedfordi and Sus scrofa) and carnivores species at the top of food chain (like Panthera pardus) is able to provide scientific support to the whole Qinling ecosystem. (4) Mining this photo database to monitor and research wildlife disease’s occurring as well as developing.

Key words: camera trapping, wildlife monitoring, species list, Qinling, database platform