Spatiotemporal vegetation trends and climate attribution across Pakistan’s agro-ecological zones

Pakistan encompasses the world’s most climatically and topographically diverse landscapes, spanning hyper-arid deserts, glaciated high-mountain ranges, and irrigated plains. Vegetation dynamics in such heterogeneous regions reflect complex interactions among water availability, thermal conditions, and land management. This study characterized spatiotemporal vegetation dynamics and their lag‑resolved climatic drivers across Pakistan’s Agro‑Ecological Zones (AEZs) during 2001–2024, using the MODIS Enhanced Vegetation Index (EVI) MOD13Q1 product alongside nine ERA5‑Land climate variables. Long‑term vegetation trends were assessed using the Modified Mann–Kendall (MMK) test with autocorrelation correction and False Discovery Rate (FDR) control. Positive vegetation trends (greening) were recorded across all AEZs, with 24% of pixels reaching statistical significance and only 0.8% showing significant browning (declining greenness). Soil moisture was found to be the dominant driver in just over 37% of pixels, confirming that root‑zone water availability governs vegetation variability across most of Pakistan. In the irrigated plains, vegetation trends were strongly correlated with canal irrigation rather than precipitation, consistent with the operation of the Indus irrigation network. The Rainfed Plateau showed the strongest vegetation recovery despite declining rainfall, suggesting improved land management as a contributing factor. In the mountain zones, asymmetric temperature warming was associated with extended growing seasons, while deserts exhibited instantaneous soil‑moisture coupling. Additional drivers included sensible heat flux and dewpoint temperature in the Northern Irrigated Plain, consistent with irrigation‑induced atmospheric humidity feedbacks. The Coastal Zone delta fringe was the only spatially coherent area of browning, associated with freshwater deficits below the Kotri Barrage. These results demonstrate that Pakistan’s vegetation reflects diverse, mechanistically distinct processes across AEZs, and highlight the importance of lag‑resolved, multi‑variable attribution for accurate vegetation–climate diagnosis in climatically heterogeneous irrigated landscapes.