KAUST researchers, in collaboration with Aeon Collective, have issued a call for global leaders to prioritize land restoration and food systems. Their policy paper, launched at COP16 in Riyadh, outlines a framework for halving degraded land by 2050. The initiative aims to reverse the negative impacts of land degradation, including increased food insecurity and exacerbated climate change. Why it matters: The focus on land restoration at a major UN conference hosted in the Middle East highlights the region's growing role in global sustainability efforts and the importance of addressing desertification.
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.