Publications

Detsch, F; Otte, I; Appelhans, T; Hemp, A; Nauss, T (2016). Seasonal and long-term vegetation dynamics from 1-km GIMMS-based NDVI time series at Mt. Kilimanjaro, Tanzania. REMOTE SENSING OF ENVIRONMENT, 178, 70-83.

Abstract
Vegetation dynamics in the Kilimanjaro region, Tanzania, are subject to (i) global climate change and (ii) local land-cover change resulting from natural or anthropogenic disturbance. While recent climate models predict rising temperatures over East Africa throughout the 21st century, effects of land-use change on the local-scale water budget and, related therewith, on vegetation response are much more diverse. In addition, sea surface temperature anomalies in the Pacific (El Nino Southern Oscillation, ENSO) and Indian Ocean (Indian Ocean Dipole, IOD) are known to severely impact rainfall patterns and vegetation activity in the study area and possibly reinforce each other. Here we present long-term and seasonal vegetation dynamics derived from a GIMMS-based NDVI record resampled to 1 km spatial resolution and covering a 30-year period (1982-2011). In the long term, most of the upper mountain regions showed positive trends which was mainly attributed to vegetation recovery after disastrous fires during the outgoing 20th century. Along the western mountainside, by contrast, strong negative trends emerged as a consequence of fire-driven downward migration of Erica bush along the upper slopes and massive land conversion processes affecting the lower slopes. On the seasonal scale, a strong dependence of the regional vegetation on the effects of ENSO/IOD teleconnections became evident. Similar to previous findings on rainfall, the most beneficial effects occurred during concurrent El Nino/IOD events, while the impacts of La Nina were far less pronounced. To sum up, the newly created 1-km NDVI record proved capable of capturing long-term and seasonal vegetation patterns, which particularly applies for large-scale teleconnections, and thus provides an invaluable archive of decadal-scale vegetation dynamics in the study area. (C) 2016 Elsevier Inc. All rights reserved.

DOI:
10.1016/j.rse.2016.03.007

ISSN:
0034-4257