Decoding the drivers of global desertification sensitivity from 2005 to 2020

Area of Science:

• Environmental Science
• Remote Sensing
• Geospatial Analysis

Background:

• Land desertification poses a significant global threat to ecosystems and socioeconomic stability.
• Understanding desertification sensitivity is crucial for effective land management and sustainable development.

Purpose of the Study:

• To assess global desertification sensitivity from 2005 to 2020.
• To identify and quantify the primary drivers of desertification.
• To evaluate the causal relationships between environmental factors and desertification.

Main Methods:

• Utilized the Google Earth Engine-Mediterranean Desertification and Land Use (GEE-MEDALUS) model.
• Integrated Climate (CQI), Soil (SQI), Vegetation (VQI), and Management (MQI) Quality Indices.
• Employed Optimal Parameters-based Geographical Detector (OPGD) for global driver analysis and Geographical Convergent Cross Mapping (GCCM) for causality in China.

Main Results:

• High to extreme desertification sensitivity is concentrated in arid, semi-arid, and sub-humid regions, notably North Africa, the Middle East, and Central Asia.
• Climate Quality Index (CQI) and Soil Quality Index (SQI) emerged as dominant drivers, with the Aridity Index and Soil Organic Matter being most influential.
• Extreme sensitivity areas remained stable, while high sensitivity areas slightly expanded; causal linkages were confirmed for most indicators.

Conclusions:

• Desertification is primarily driven by a co-limitation of climate and soil factors.
• Findings underscore the need for targeted interventions focusing on climate and soil management to enhance land resilience.
• The study provides a robust framework for global desertification monitoring and risk assessment.