生物多样性 ›› 2022, Vol. 30 ›› Issue (6): 21310.  DOI: 10.17520/biods.2021310

• 研究报告: 生态系统多样性 •    下一篇

青海湖自然保护区人类数字足迹及草地生物量的人类活动暴露度的时空模式分析

涂文娜1,2, 易嘉伟1,2, 杜云艳1,2,*(), 王楠1,2, 千家乐1,2, 黄胜1,2, 王晓悦1,2   

  1. 1.中国科学院地理科学与资源研究所资源与环境信息系统国家重点实验室, 北京 100101
    2.中国科学院大学, 北京 100049
  • 收稿日期:2021-08-11 接受日期:2022-04-19 出版日期:2022-06-20 发布日期:2022-06-19
  • 通讯作者: 杜云艳
  • 作者简介:* E-mail: duyy@lreis.ac.cn
  • 基金资助:
    中国科学院战略性先导科技专项(XDA20040401);中国科学院战略性先导科技专项(XDA19040501)

A spatiotemporal analysis of human digital footprint and the human activities exposure of grassland biomass in Qinghai Lake National Nature Reserve

Wenna Tu1,2, Jiawei Yi1,2, Yunyan Du1,2,*(), Nan Wang1,2, Jiale Qian1,2, Sheng Huang1,2, Xiaoyue Wang1,2   

  1. 1. State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101
    2. University of Chinese Academy of Sciences, Beijing 100049
  • Received:2021-08-11 Accepted:2022-04-19 Online:2022-06-20 Published:2022-06-19
  • Contact: Yunyan Du

摘要:

开展保护区人类活动压力定量评估对保护区内生态系统安全、降低人类活动影响具有重要意义。许多学者从人类活动对生物多样性、生物的生境或生态系统服务及其价值的影响等角度已开展了大量研究, 但由于反映人类活动的统计数据在时空尺度上较粗, 难以精细刻画保护区内短期动态的人类活动干扰。本研究尝试通过记录人的位置到访信息的高时空分辨率数字足迹数据, 以青海湖国家级自然保护区为研究区域, 利用0.01°逐日的定位请求数据和草地生物量数据, 从人类数字足迹覆盖率、数字足迹强度和草地生物量的人类活动暴露度3个指标上对青海湖自然保护区内人类数字足迹入侵强度及其对生态环境的影响开展了研究。研究结果显示, 青海湖保护区人类数字足迹具有“多尖峰、南高北低、景区节律”的时空模式; 每日人类数字足迹覆盖率和足迹强度呈现按月聚集模式, 最大值分别为7.42%和5.24; 草地生物量的人类活动暴露度显示人类数字足迹对青海湖二郎剑-黑马河沿线的草地生物量影响最大, 此时草地生物量的人类活动暴露度水平在热门旅游景点较高, 最高达到2.24。通过位置大数据挖掘青海湖保护区内人类数字足迹的时空变化及其对于生态环境的影响, 不仅证明了数字足迹用于人类活动对于生态环境影响研究的有效性, 也为保护区生态环境精细化的管理提供支撑。

关键词: 数字足迹, 大数据, 暴露度, 青海湖, 保护区

Abstract

Aims: Quantifying the pressure of human activities in protected areas is important for protecting ecological systems and reducing the impact of human activities. While many researchers have evaluated the impacts of human activities on species diversity, biological habitats or ecosystem services, it remains challenging to quantify the short-term dynamics of human disturbance in protected areas due to the coarse spatial and temporal resolutions of data reflecting human activity. This research attempts to study the dynamics of the scope and intensity of human activities through high- resolution digital footprint data, providing a new pathway for human activity monitoring and management refinement in protected areas.
Methods: Qinghai Lake Nature Reserve was selected as the research area in this study. We used 0.01° daily Tencent location request data and grassland biomass to derive three indicators for exploring the intensity of human digital footprint invasion and its impact on the ecological environment in Qinghai Lake Nature Reserve. These indicators included the human digital footprint coverage (α), the human digital footprint intensity (β), and the human activities exposure of grassland biomass (ε).
Results: (1) The human digital footprint in Qinghai Lake Nature Reserve had a spatiotemporal pattern of “multiple peaks, high in the southern and low in the northern zones, and rhythm of attractions”. After the Qinghai Lake was opened to the public in April, the β increased and then decreased, with the highest in August and the lowest in February. Human digital footprints mainly distributed in the popular scenic spots in the south and along the highway around Qinghai Lake. (2) The α and β showed a pattern of aggregation by month, with the largest values observed in August. The maximum daily α and β were 7.42% and 5.24, respectively. The closure of the Bird Island Scenic Area and Sand Island Scenic Area played an important role in reducing human invasion. (3) During the peak travel period in July and August, the human digital footprints invaded more seriously into the buffer zone and Experimental zone of Qinghai Lake Nature Reserve. Analysis on the human activities exposure of grassland biomass showed that human digital footprints had the greatest impact on grassland biomass along the Erlangjian-Heimahe route in the Qinghai Lake Nature Reserve, with a highest impact of 2.24 at key tourist sites.
Conclusion: Our research demonstrated the potential effectiveness of digital human footprint data to study the impact of human activities on the ecological environment of the Qinghai Lake Nature Reserve, which could support the refined ecological management in the reserve.

Key words: digital footprint, big data, exposure, Qinghai Lake, nature reserve