Global patterns of forest greening and browning: the imprint of land-use change, management, and fire

Forests are under increasing pressure from climate change, land-use transformation, and human activities, threatening their capacity to regulate climate, store carbon, and sustain biodiversity. Detecting long-term changes in forest canopy structure and productivity is therefore essential. Leaf Area Index (LAI) is a widely used proxy of vegetation structure and function and serves as a key indicator of forest productivity. It captures greening associated with canopy densification and potential carbon uptake, and browning linked to forest degradation, disturbance, or loss. However, global assessments of forest greening and browning and their spatial determinants remain limited.

Here, we present a global analysis of forest LAI trends over the last ~25 years using the High-Quality Reprocessed MODIS LAI dataset (HiQ-LAI; 8-day, 500 m; 2000–2024). The analysis is restricted to pure forest pixels derived from Hansen’s 30 m global forest cover map. Trends were quantified using Sen’s slope estimator and their significance assessed with the Mann–Kendall test. Globally, 21 % of forest areas exhibited significant greening, while 8 % showed browning, revealing strong regional contrasts. Browning patterns in tropical and subtropical forests are predominantly associated with land-use change, whereas in boreal regions they are largely driven by fire disturbances. In contrast, greening hotspots extend beyond climatic and CO₂ fertilization effects and strongly overlap with intensively managed forests, including plantation-dominated regions in China and Europe.

Our findings demonstrate that land-use change, forest management, and disturbance regimes are key spatial determinants of observed forest greening and browning patterns. However, these processes remain underrepresented in many Earth system models. By providing a spatially explicit global baseline, this study supports improved representation of human and disturbance processes in climate–vegetation modelling and informs conservation, climate mitigation, and sustainable forest management strategies under accelerating global change.