Long-term spatiotemporal dynamics of forest disturbances in Wuyishan National Park: Patterns, drivers, and conservation insights
• Landsat time series reveal 33-year forest dynamics in Wuyishan National Park. • Recovery dominated post-disturbance; tea expansion drove anthropogenic pressure. • Time-series analysis confirms the 2015 National Park Pilot curbed forest loss. • Disturbance trajectories aligned with policy, economics, and climate extremes. Navigating complex human-nature interactions remains a critical challenge for protected areas globally. China’s establishment of the National Park System represents a fundamental governance shift toward ecological integrity, yet its long-term efficacy in economically vibrant regions remains underexplored. Focusing on Wuyishan National Park, we reconstructed forest disturbance dynamics from 1991 to 2023 using Landsat time series and the LandTrendr algorithm. Over this period, an estimated 6.0% of the park area (approximately 7,739.4 ha) experienced disturbances. Quantitative analysis revealed that the majority (58.8%) of disturbed forests eventually recovered, whereas tea plantation expansion (23.0%) exerted the primary permanent anthropogenic pressure, clustering selectively in non-protected Gaps and along administrative boundaries, while the Core Protected Area remained safeguarded. Disturbance trajectories aligned with policy evolution, economic incentives, and climatic extremes. Following the 2015 National Park Pilot, disturbances stabilized at minimal levels, coinciding with the effective containment of historical tea expansion. This study establishes a transferable remote sensing framework for evaluating conservation outcomes, highlighting the utility of continuous spatial monitoring in assessing protected areas confronting complex socio-economic and climatic pressures.
Authors
- Yefeng Xie (ORCID: https://orcid.org/0000-0001-8378-8347)
- Haowei Mu (ORCID: https://orcid.org/0000-0002-9465-822X)
- Lifu Zhang (ORCID: https://orcid.org/0000-0002-3533-9966)
- Hualiang Liu
- Feizhou Zhang
- Tiebiao Liu
- Shilin Luo
Institutions
- Central South University of Forestry and Technology (CN)
- Central South University (CN)
- Chinese Academy of Sciences (CN)
- Changsha University (CN)
- Peking University (CN)
- Aerospace Information Research Institute (CN)
- University of Chinese Academy of Sciences (CN)
- State Key Laboratory of Remote Sensing Science (CN)
- Nanjing University (CN)
Publication Details
- Journal
- International Journal of Applied Earth Observation and Geoinformation
- Published
- 2026-05-17
- DOI
- https://doi.org/10.1016/j.jag.2026.105343
- Primary Topic
- Ecology and Vegetation Dynamics Studies
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Hunan Province