Spatial patterns of long‐term vegetation greening and browning are consistent across multiple scales: Implications for monitoring land degradation

Abstract

Abstract Understanding spatial–temporal patterns of terrestrial vegetation response to climate change (long‐term greening/browning) is important for developing strategies to mitigate degradation. Semiarid rangelands are especially susceptible to degradation, which challenges wildlife conservation and human livelihoods that depend on livestock production. In the cold‐arid Trans‐Himalayan ecosystem (northern India), temperature is increasing, and it is also becoming progressively wetter. Yet, counter‐intuitively, there are widespread concerns over degradation. We evaluated whether greening/browning patterns in long‐term satellite‐derived vegetation indices (normalized difference vegetation index [NDVI]) are consistent across different spatial and temporal scales using 6 datasets: MODIS (250 m, 500 m, 1 km, and 5.5 km), SPOT 1 km, and GIMMS 8 km. Results indicate browning in the spring and greening in late summer. Location of hotspots of degradation (browning) was broadly consistent across spatial scales (10 −2 –10 2 km 2 ) and were found in regions with warmer temperature and at higher elevations. Broadly, the spatial/temporal pattern of browning does not coincide strongly with location and timing of human land use via livestock grazing. This geographical and seasonal context indicates that vegetation response may be more strongly related to climate than to human land use (overgrazing). Importantly, the dynamic nature of greening/browning, across space and time, is not captured by composite annual metrics (sum‐NDVI, max‐NDVI, and mean‐NDVI). This reiterates the importance of both intraannual and interannual assessments. Location of hotspots indicates that degradation occurs in a spatially contiguous manner, but these are not stationary and instead shift with seasons. Overall, the results show that evaluating the consistency of greening/browning trends across different spatial/temporal scales is critical for understanding and managing vegetation degradation.