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Results for "Drylands Restoration"

Climate-based Pre-screening of Self-sustaining Regreening Opportunities in Drylands: A Case Study for Saudi Arabia

arXiv ·

Researchers have developed a scalable pre-screening framework that integrates climate and remote sensing data to identify cost-efficient sites for sustainable dryland restoration, using Saudi Arabia as a case study. The framework employs machine learning models to derive a Climate Suitability Score (CSS), which captures climatic dependencies on vegetation persistence. National-scale prediction maps were generated using multi-year ERA5-Land data for Saudi Arabia, leading to the identification of thirteen priority locations with an estimated potential for a 2.5-fold increase in vegetation coverage. Why it matters: This approach significantly reduces the search space and costs associated with restoration efforts, supporting more resilient and sustainable ecosystem recovery planning in water-limited regions of the Middle East.

Plant diversity predicts resistance to grazing pressure on drylands

KAUST ·

A KAUST-led study in *Nature Ecology & Evolution* finds that plant species diversity is the strongest predictor of dryland ecosystem resistance to grazing pressure, outperforming climate and soil factors. Analyzing 73 sites across 25 countries, researchers found that diverse plant communities better maintain vegetation cover under grazing. This is attributed to varied species responses distributing grazing pressure and buffering vegetation loss. Why it matters: The findings highlight the importance of biodiversity in maintaining the productivity and stability of dryland ecosystems, which support half of global livestock production and a billion people's livelihoods.