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A method for evaluating ecological quality levels and trends using natural evolution time series.

Qiulin Li1, Caiyong Wei1,2, Xiaojing Xue1

  • 1School of Information Engineering, China University of Geosciences, Beijing, 100083, China.

Environmental Science and Pollution Research International
|November 13, 2024
PubMed
Summary

This study developed a remote sensing model to assess grassland ecological quality in arid regions, finding it relatively stable and superior. The method offers a flexible framework for ecological restoration and management in diverse areas.

Keywords:
Ecological quality evaluationEvolutionary characteristics of natural ecosystemsGrassland ecosystemImproved derivative dynamic time warping (DDTW) algorithmRemote-sensing time seriesThe Mann–Kendall trend test and the Sen’s slopeThe arid area

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Area of Science:

  • Environmental Science
  • Remote Sensing
  • Ecology

Background:

  • Ecological quality assessment is crucial for understanding development impacts and guiding ecological governance.
  • Existing research often overlooks regional variations, focusing on large-scale assessments.
  • There is a need for comprehensive, objective, and accurate ecological quality evaluation methods.

Purpose of the Study:

  • To establish a remote sensing-based model for regional ecological quality assessment.
  • To evaluate the ecological quality of grassland ecosystems in the arid areas of the Ningxia Hui Autonomous Region (NHAR).
  • To analyze the spatial and temporal characteristics of soil and water conservation, water source conservation, and carbon sequestration capacities.

Main Methods:

  • Utilized Modified soil-adjusted vegetation index (MSAVI), wetness components (WET), and net primary productivity (NPP) as indicators.
  • Employed the improved derivative dynamic time warping (DDTW) algorithm for time-series comparison against natural evolution.
  • Classified ecological quality using natural breaks (Jenks) and analyzed trends with the Mann-Kendall test and Sen's slope.

Main Results:

  • Selected indicators (MSAVI, WET, NPP) showed minimal correlation within evaluation units, except for MSAVI and WET in plains.
  • Significant spatial heterogeneity in natural evolution characteristics and reference frame similarity was observed.
  • Soil and water conservation, water source conservation, and carbon sequestration capacities were predominantly at Level 2, indicating stable and superior quality.

Conclusions:

  • The grassland ecosystems in the arid NHAR exhibit relatively stable and superior ecological quality.
  • The developed remote sensing model is broadly applicable and adaptable for regional ecological quality and restoration assessments.
  • The study provides valuable insights for regional ecological management and governance.