Detecting desertification dynamics based on time series analysis and spatio- temporal changes of net primary productivity (NPP) in arid regions

Desertification is a major global environmental threat, impacting ecosystems and human livelihoods. Therefore, a comprehensive assessment of desertification is crucial for selecting mitigation strategies. Actual Net Primary Productivity (ANPP) has emerged as an efficient index for evaluating this phenomenon. This study detected and investigates the spatio-temporal dynamics of desertification hazard in the arid northeastern Iran using the Carnegie-Ames-Stanford Approach (CASA) model to estimate ANPP over a 20-year period (2004–2023). Potential Net Primary Productivity (PNPP) was calculated using the Thornthwaite method and ANPP and PNPP were used to calculate Human Net Primary Productivity (HNPP). HNPP was calculated as the difference between ANPP and PNPP. The modified CASA model demonstrated high accuracy and reliability in estimating ANPP for the arid and semi-arid regions, exhibiting an 86% correlation with MODIS ANPP products. The results revealed a concerning level of desertification in the study area, affecting 81.7% of the region. The analysis attributed 35.8% of desertification to climatic factors, 29.4% to the interaction between climatic factors and human activities, and 16.5% solely to human activities. The primary human-induced drivers of desertification included agricultural practices such as traditional livestock farming and irrigated agriculture, which have severely strained the region’s natural resources by disregarding ecosystem resilience and sustainable development principles. The findings help policymakers and environmental planners to develop and implement sustainable land management practices and effective desertification control measures. These measures are essential for mitigating further environmental degradation and safeguarding the region's long-term ecological and economic stability.