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Updated: Jan 13, 2026

Measuring the Structure, Composition, and Change of Underwater Environments with Large-area Imaging
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Ecosystem quality dynamics and attribution in protected areas: An integrated analysis framework based on the

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  • 1College of Land Management, Nanjing Agricultural University, Nanjing, 210095, China.

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Summary

Global biodiversity loss is a major challenge. This study evaluated ecosystem quality (EQ) in China

Keywords:
Driving factorsEcosystem qualityEcosystem servicesOptimal parameter geographic detectorProtected areas

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Area of Science:

  • Ecology
  • Conservation Biology
  • Environmental Science

Background:

  • Global biodiversity loss and ecosystem degradation necessitate urgent conservation strategies.
  • Ecosystem quality (EQ) within protected areas (PAs) is crucial for ecological functions but current assessments lack socio-ecological integration.
  • Evaluating EQ in China's national PAs is vital for effective conservation planning.

Purpose of the Study:

  • To develop and apply a comprehensive framework (structure-function-resilience-pressure) for evaluating EQ in China's national PAs.
  • To analyze the drivers and interactions influencing EQ across different PA types.
  • To identify optimal spatial scales for EQ assessment and inform adaptive PA governance.

Main Methods:

  • Developed a structure-function-resilience-pressure framework for EQ assessment.
  • Utilized the optimal parameter geographic detector (OPGD) model to analyze EQ drivers and interactions.
  • Conducted multiscale analysis to determine the optimal spatial scale for EQ evaluation.

Main Results:

  • EQ shows a declining trend with significant spatial heterogeneity across China's PAs.
  • Forest and grassland PAs exhibit higher EQ stability compared to animal and paleontological PAs.
  • Natural factors (precipitation, NDVI) are primary drivers at the optimal 2 km scale, with human disturbances having lesser impact; interactions between natural and anthropogenic factors significantly increase explanatory power.

Conclusions:

  • EQ in China's PAs is declining and spatially heterogeneous, with varying stability across PA types.
  • Natural factors are dominant drivers of EQ, but socio-ecological interactions are critical for a comprehensive understanding.
  • Findings support adaptive classification and governance of PAs for enhanced conservation effectiveness and long-term sustainability.