Sub‐Saharan Africa (SSA) could face food shortages in the future because of its growing population. Agricultural expansion causes forest degradation in SSA through livestock grazing, reducing forest carbon (C) sinks and increasing greenhouse gas (GHG) emissions. Therefore, intensification should produce more food while reducing pressure on forests. This study assessed the potential for the dairy sector in Kenya to contribute to low‐emissions development by exploring three feeding scenarios. The analyses used empirical spatially explicit data, and a simulation model to quantify milk production, agricultural emissions and forest C loss due to grazing. The scenarios explored improvements in forage quality (Fo), feed conservation (Fe) and concentrate supplementation (Co): FoCo fed high‐quality Napier grass (Pennisetum purpureum), FeCo supplemented maize silage and FoFeCo a combination of Napier, silage and concentrates. Land shortages and forest C loss due to grazing were quantified with land requirements and feed availability around forests. All scenarios increased milk yields by 44%–51%, FoCo reduced GHG emission intensity from 2.4 ± 0.1 to 1.6 ± 0.1 kg CO2eq per kg milk, FeCo reduced it to 2.2 ± 0.1, whereas FoFeCo increased it to 2.7 ± 0.2 kg CO2eq per kg milk because of land use change emissions. Closing the yield gap of maize by increasing N fertilizer use reduced emission intensities by 17% due to reduced emissions from conversion of grazing land. FoCo was the only scenario that mitigated agricultural and forest emissions by reducing emission intensity by 33% and overall emissions by 2.5% showing that intensification of dairy in a low‐income country can increase milk yields without increasing emissions. There are, however, risks of C leakage if agricultural and forest policies are not aligned leading to loss of forest to produce concentrates. This approach will aid the assessment of the climate‐smartness of livestock production practices at the national level in East Africa.

We use an attributional life cycle assessment (LCA) and simulation modelling to assess the effect of improved feeding practices and increased yields of feed crops on milk productivity and GHG emissions from the dairy sector of Tanzania’s southern highlands region. We calculated direct non-CO2 emissions from dairy production and the CO2 emissions resulting from the demand for croplands and grasslands using a land footprint indicator. Baseline GHG emissions intensities ranged between 19.8 and 27.8 and 5.8–5.9 kg CO2eq kg−1 fat and protein corrected milk for the Traditional (local cattle) and Modern (improved cattle) sectors. Land use change contributed 45.8–65.8% of the total carbon footprint of dairy. Better feeding increased milk yields by up to 60.1% and reduced emissions intensities by up to 52.4 and 38.0% for the Traditional and Modern sectors, respectively. Avoided land use change was the predominant cause of reductions in GHG emissions under all the scenarios. Reducing yield gaps of concentrate feed crops lowered emissions further by 11.4–34.9% despite increasing N2O and CO2 emissions from soils management and input use. This study demonstrates that feed intensification has potential to increase LUC emissions from dairy production, but that fertilizer-dependent yield gains can offset this increase in emissions through avoided emissions from land use change.

Deforestation and forest degradation are major drivers of global environmental change and tropical forests are subjected to unprecedented pressures from both. For most tropical zones, deforestation rates are averaged across entire countries, often without highlighting regional differentiation. There are also very few estimates of forest degradation, either averaged or localized for the tropics. We quantified regional and country‐wide changes in deforestation and forest degradation rates for Madagascar from Landsat temporal data (in two intervals, 1994–2002 and 2002–2014). To our knowledge, this is the first country‐wide estimate of forest degradation for Madagascar. We also performed an intensity analysis to categorize the magnitude and speed of transitions between forest, vegetation matrix, cultivated land and exposed surface. We found significant regional heterogeneity in deforestation and forest degradation. Deforestation rates decreased annually in lowland evergreen moist forest by −0.24% and in all other vegetation zones. Forest degradation rates had annual increases in the same period in lowland evergreen moist forest (0.09%), littoral forest (0.06%) but decreased in medium altitude moist evergreen forest (−0.25%), dry deciduous forest (−0.23%) and scelrophyllous woodland (−0.61%) in the same period. Despite these regional differences, higher rates of deforestation and forest degradation were consistently driven by rapid and large‐sized conversions of largely intact forest to cultivated lands and exposed surfaces, most of which occurred between 1994 and 2002. These results suggest that while targeted conservation projects may have reduced forest degradation rates in some areas (e.g. medium altitude moist evergreen forest), the drivers of land cover change remain intense in relatively neglected regions. We advocate a more balanced approach to future conservation initiatives, one recognizing that deforestation and forest degradation, particularly in tropical Africa, are often driven by region‐specific conditions and therefore require conservation policies tailored for local conditions.

A growing body of evidence shows that more intensive dairy systems can be good for both nature and people. Little research considers whether such systems correspond with local priorities and preferences. Using a mixed methods approach, this study examined the effects of three intensification scenarios on milk yield and emission intensities in Kenya and Tanzania. Scenarios included (a) an incremental change to feed management; (b) adaptive change by replacing poor quality grass with nutrient-rich fodder crops; and (c) multiple change involving concurrent improvements to breeds, feeds and concentrate supplementation. These scenarios were co-constructed with diverse stakeholder groups to ensure these resonate with local preferences and priorities. Modelling these scenarios showed that milk yield could increase by 2%–15% with incremental changes to over 200% with multiple changes. Greenhouse gas emission intensities are lowest under the multiple change scenario, reducing by an estimated 44%. While raising yields, incremental change conversely raises emission intensities by 9%. Our results suggest that while future interventions that account for local priorities and preferences can enhance productivity and increase the uptake of practices, far-reaching shifts in practices are needed to reduce the climatic footprint of the dairy sector. Since top-down interventions does not align with local priorities and preferences in many situations, future low-emission development initiatives should place more emphasis on geographic and stakeholder heterogeneity when designing targeting and implementation strategies. This suggests that in low-income countries, bottom-up approaches may be more likely to improve dairy productivity and align with mitigation targets than one-size-fits-all approaches.