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Does a Time-Lagged Effect Exist Between Landscape Pattern Changes and Giant Panda Density?

Author

Listed:
  • Qingxia Zhao

    (Shaanxi Key Laboratory of Qinling Ecological Security, Shaanxi Institute of Zoology, Xi’an 710032, China)

  • Qifeng Zhu

    (Shaanxi Key Laboratory of Qinling Ecological Security, Shaanxi Institute of Zoology, Xi’an 710032, China)

  • Jiqin Huang

    (Shaanxi Key Laboratory of Qinling Ecological Security, Shaanxi Institute of Zoology, Xi’an 710032, China)

  • Yueduo Cui

    (Shaanxi Key Laboratory of Qinling Ecological Security, Shaanxi Institute of Zoology, Xi’an 710032, China)

  • Yutai Liu

    (Shaanxi Key Laboratory of Qinling Ecological Security, Shaanxi Institute of Zoology, Xi’an 710032, China)

  • Dong Chen

    (Shaanxi Key Laboratory of Qinling Ecological Security, Shaanxi Institute of Zoology, Xi’an 710032, China)

  • Xuelin Jin

    (Shaanxi Key Laboratory of Qinling Ecological Security, Shaanxi Institute of Zoology, Xi’an 710032, China)

Abstract

Land use and land cover change (LULCC) can influence giant panda distributions by altering landscape structure and configuration. However, the spatial impacts and potential time lag effects of landscape pattern changes on giant pandas remain underexplored. In this study, we applied a random forest classification method to analyze LULCC in 1990, 2000, and 2010, alongside calculating a set of landscape metrics to assess changes in landscape fragmentation, connectivity, and diversity. Random forest regression models were then used to evaluate the spatial relationships between landscape metrics and giant panda density, with the aim of identifying whether a time lag effect exists. The results revealed the following: (1) The random forest classification achieved high land use classification accuracy. Forests remained the dominant land cover, occupying approximately 97% of the study area throughout the period, with only minor fluctuations observed among other land use types. (2) Landscape metrics indicated increasing landscape fragmentation, connectivity, and diversity. While increased landscape fragmentation can negatively impact giant panda habitat, improvements in landscape connectivity and diversity could mitigate these effects by preserving movement corridors and enhancing habitat accessibility. (3) The strongest correlations between giant panda density and landscape metrics were observed when the time points aligned. Landscape metrics from 2010 showed the highest correlation with the 4th NGPS (around 2010), and landscape metrics from 2000 had the highest correlation with the 3rd NGPS (around 2000). The results revealed that giant panda density responded most strongly to contemporary landscape pattern changes, suggesting an immediate response. However, correlations with earlier landscape metrics also suggest that a relatively weak time lag effect may be present. All landscape metrics were derived from remote sensing data, enabling scalable and repeatable GIS-based analysis. These findings highlight the utility of spatial landscape indicators for monitoring species distribution patterns and underscore the importance of maintaining and enhancing habitat connectivity within giant panda conservation efforts.

Suggested Citation

  • Qingxia Zhao & Qifeng Zhu & Jiqin Huang & Yueduo Cui & Yutai Liu & Dong Chen & Xuelin Jin, 2025. "Does a Time-Lagged Effect Exist Between Landscape Pattern Changes and Giant Panda Density?," Land, MDPI, vol. 14(5), pages 1-18, May.
    • Handle: RePEc:gam:jlands:v:14:y:2025:i:5:p:1075-:d:1656676
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    References listed on IDEAS

    as
    1. Tauheed Ullah Khan & Abdul Mannan & Charlotte E. Hacker & Shahid Ahmad & Muhammad Amir Siddique & Barkat Ullah Khan & Emad Ud Din & Minhao Chen & Chao Zhang & Moazzam Nizami & Xiaofeng Luan, 2021. "Use of GIS and Remote Sensing Data to Understand the Impacts of Land Use/Land Cover Changes (LULCC) on Snow Leopard ( Panthera uncia ) Habitat in Pakistan," Sustainability, MDPI, vol. 13(7), pages 1-19, March.
    2. Qing Qin & Yuan Huang & Jingru Liu & Dai Chen & Ling Zhang & Jian Qiu & Hongli Tan & Yali Wen, 2019. "The Landscape Patterns of the Giant Panda Protection Area in Sichuan Province and Their Impact on Giant Pandas," Sustainability, MDPI, vol. 11(21), pages 1-15, October.
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