Human land-use practices have been highly variable over the course of the Holocene, a diversity evident in the differentiated effects of human activity on land cover. Historically, agriculture was one of the most significant forms of land use, but even mobile hunter-gatherers transformed land cover through landscape-scale burning (Bliege Bird 2008). Livestock-keeping, plowing, irrigation, and the production of metal, ceramics, and bricks, have also been drivers of historical change.

The climate-smart agriculture (CSA) concept reflects an ambition
to improve the integration of agriculture development and climate
responsiveness. It aims to achieve food security and broader
development goals under a changing climate and increasing food
demand. CSA initiatives sustainably increase productivity, enhance
resilience, and reduce/remove greenhouse gases (GHGs), and
require planning to address trade-offs and synergies between
these three pillars: productivity, adaptation, and mitigation [1].

Environment and Production Technology Division, International Food Policy Research Institute, Washington, DC 20005; bState Key Laboratory for Biology
of Plant Diseases and Insect Pests, Institute of Plant Protection, Chinese Academy of Agricultural Sciences, Beijing 100193, China; cCentre for Crop Systems
Analysis, Wageningen University, 6700 AK Wageningen, The Netherlands; dChina Center for Agricultural Policy, School of Advanced Agricultural Sciences,

This study aims to explain effects of soil textural class, topography, land use, and land use history on soil greenhouse gas (GHG) fluxes in the Lake Victoria region. We measured GHG fluxes from intact soil cores collected in Rakai, Uganda, an area characterized by low‐input smallholder (<2 ha) farming systems, typical for the East African highlands. The soil cores were air dried and rewetted to water holding capacities (WHCs) of 30, 55, and 80%. Soil CO2, CH4, and N2O fluxes were measured for 48 h following rewetting.

In the Tana River Basin in Kenya, six Regional Circulation Models (RCMs) simulating two Representative Concentration Pathways (RCPs) (i.e., 4.5 and 8.5) were used as input to the Soil and Water Assessment Tool (SWAT) model to determine the possible implications for the hydrology and water resources of the basin. Four hydrological characteristics – water yield, groundwater recharge, base flow and flow regulation – were determined and mapped throughout the basin for three 30-year time periods: 2020–2049, 2040–2069 and 2070–2099. Results were compared with a baseline period, 1983–2011.