Disentangling climate and human drivers of land degradation in East and Southern Africa

Loading...
Thumbnail Image

Date Issued

Date Online

2025-04

Language

en

Review Status

Peer Review

Access Rights

Limited Access Limited Access

Share

Citation

Muthoni, F. K., Manda, J. & Dubovky, O. (2025). Disentangling climate and human drivers of land degradation in East and Southern Africa. Land Degradation & Development, 1— 16.

Permanent link to cite or share this item

External link to download this item

Abstract/Description

Timely monitoring of land degradation (LD) is essential to guide targeting the sustainable land management (SLM) practices to the suitable context that assists in achieving an LD neutral world. This study applied a 40-year time series of remote sensing data representing vegetation indices and rainfall to identify the hotspots for the climatic and human-induced LD or improvements in the East and Southern Africa (ESA) region. This was complemented by a field assessment of LD and SLM practices applied by farmers in Tanzania. Remote sensing analysis at the regional scale identified hotspots in the ESA region that experienced statistically significant LD and improvement trends primarily driven by human and climatic factors during two temporal segments from 1983 to 2005 (T1) and 2006–2022 (T2). The Normalized Difference Vegetation Index (NDVI) trends exhibited a browning-to-greening trend reversal between T1 and T2 in northern Zambia and Tanzania, contrasting with persistent browning in Central Malawi and southern Zambia. At the local scale, severe LD in Kongwa district of Tanzania was primarily caused by erosion by water, wind, and unsustainable exploitation of natural vegetation, although their magnitude varied over different landscape gradients. These collaborated with the remotely sensed browning trend observed in the Kongwa district, but the greening plots were largely smoothened out by coarse-resolution NDVI data. The regional scale identification of factors driving the greening or browning trends provides a first-instance evidence-based sampling frame for future studies to identify the actual practices applied in the greening zone that can be used to rehabilitate the degraded land.

Author ORCID identifiers

CGIAR Action Areas
CGIAR Programs and Accelerators
CGIAR Initiatives