The potential global distribution and dynamics of wheat under multiple climate change scenarios.

Accurately predicting changes in the potential distribution of crops resulting from climate change has great significance for adapting to and mitigating the impacts of climate change and ensuring food security. Based on very large datasets of wheat (Triticum aestivum L.) occurrence points and the main environmental factors that affect wheat growth, we used the Maxent model to predict the future global potential distribution and land suitability for wheat cultivation under multiple global climate change scenarios.

Spatial-Temporal Pattern of Human-Induced Land Degradation in Northern China in the Past 3 Decades-RESTREND Approach.

Land degradation is one of the world's most serious environmental issues. Human activities play an important role in it. Therefore, human-induced land degradation monitoring is of crucial scientific significance in revealing the evolution of land degradation and guiding its governance.