An Maria Omer Notenbaert

Smart Investments in Sustainable Food Production: Revisiting Mixed Crop-Livestock Systems

Farmers in mixed crop-livestock systems produce about half of the world’s food. In small holdings around the world, livestock are reared mostly on grass, browse, and nonfood biomass from maize, millet, rice, and sorghum crops and in their turn supply manure and traction for future crops. Animals act as insurance against hard times and supply farmers with a source of regular income from sales of milk, eggs, and other products. Thus, faced with population growth and climate change, small-holder farmers should be the first target for policies to intensify production by carefully managed inputs of fertilizer, water, and feed to minimize waste and environmental impact, supported by improved access to markets, new varieties, and technologies.

Biomass use, production, feed efficiencies, and greenhouse gas emissions from global livestock systems

Significance This report is unique in presenting a high-resolution dataset of biomass use, production, feed efficiencies, and greenhouse gas emissions by global livestock. This information will allow the global-change research community in enhancing our understanding of the sustainability of livestock systems and their role in food security, livelihoods and environmental sustainability. We present a unique, biologically consistent, spatially disaggregated global livestock dataset containing information on biomass use, production, feed efficiency, excretion, and greenhouse gas emissions for 28 regions, 8 livestock production systems, 4 animal species (cattle, small ruminants, pigs, and poultry), and 3 livestock products (milk, meat, and eggs). The dataset contains over 50 new global maps containing high-resolution information for understanding the multiple roles (biophysical, economic, social) that livestock can play in different parts of the world. The dataset highlights: (i) feed efficiency as a key driver of productivity, resource use, and greenhouse gas emission intensities, with vast differences between production systems and animal products; (ii) the importance of grasslands as a global resource, supplying almost 50% of biomass for animals while continuing to be at the epicentre of land conversion processes; and (iii) the importance of mixed crop–livestock systems, producing the greater part of animal production (over 60%) in both the developed and the developing world. These data provide critical information for developing targeted, sustainable solutions for the livestock sector and its widely ranging contribution to the global food system.

Climate change mitigation through livestock system transitions.

Significance The livestock sector contributes significantly to global warming through greenhouse gas (GHG) emissions. At the same time, livestock is an invaluable source of nutrition and livelihood for millions of poor people. Therefore, climate mitigation policies involving livestock must be designed with extreme care. Here we demonstrate the large mitigation potential inherent in the heterogeneity of livestock production systems. We find that even within existing systems, autonomous transitions from extensive to more productive systems would decrease GHG emissions and improve food availability. Most effective climate policies involving livestock would be those targeting emissions from land-use change. To minimize the economic and social cost, policies should target emissions at their source—on the supply side—rather than on the demand side. Livestock are responsible for 12% of anthropogenic greenhouse gas emissions. Sustainable intensification of livestock production systems might become a key climate mitigation technology. However, livestock production systems vary substantially, making the implementation of climate mitigation policies a formidable challenge. Here, we provide results from an economic model using a detailed and high-resolution representation of livestock production systems. We project that by 2030 autonomous transitions toward more efficient systems would decrease emissions by 736 million metric tons of carbon dioxide equivalent per year (MtCO2e⋅y−1), mainly through avoided emissions from the conversion of 162 Mha of natural land. A moderate mitigation policy targeting emissions from both the agricultural and land-use change sectors with a carbon price of US

Spatial determinants of poverty in rural Kenya

10 per tCO2e could lead to an abatement of 3,223 MtCO2e⋅y−1. Livestock system transitions would contribute 21% of the total abatement, intra- and interregional relocation of livestock production another 40%, and all other mechanisms would add 39%. A comparable abatement of 3,068 MtCO2e⋅y−1 could be achieved also with a policy targeting only emissions from land-use change. Stringent climate policies might lead to reductions in food availability of up to 200 kcal per capita per day globally. We find that mitigation policies targeting emissions from land-use change are 5 to 10 times more efficient—measured in “total abatement calorie cost”—than policies targeting emissions from livestock only. Thus, fostering transitions toward more productive livestock production systems in combination with climate policies targeting the land-use change appears to be the most efficient lever to deliver desirable climate and food availability outcomes.

Spatial determinants of poverty in rural Kenya: A national and provincial analysis

This article investigates the link between poverty incidence and geographical conditions within rural locations in Kenya. Evidence from poverty maps for Kenya and other developing countries suggests that poverty and income distribution are not homogenous. We use spatial regression techniques to explore the effects of geographic factors on poverty. Slope, soil type, distance/travel time to public resources, elevation, type of land use, and demographic variables prove to be significant in explaining spatial patterns of poverty. However, differential influence of these and other factors at the location level shows that provinces in Kenya are highly heterogeneous; hence different spatial factors are important in explaining welfare levels in different areas within provinces, suggesting that targeted propoor policies are needed. Policy simulations are conducted to explore the impact of various interventions on location-level poverty levels. Investments in roads and improvements in soil fertility are shown to potentially reduce poverty rates, with differential impacts in different regions.

Derivation of a household-level vulnerability index for empirically testing measures of adaptive capacity and vulnerability

This article investigates the link between poverty incidence and geographical conditions within rural locations in Kenya. Evidence from poverty maps for Kenya and other developing countries suggests that poverty and income distribution are not homogenous. We use spatial regression techniques to explore the effects of geographic factors on poverty. Slope, soil type, distance/travel time to public resources, elevation, type of land use, and demographic variables prove to be significant in explaining spatial patterns of poverty. However, differential influence of these and other factors at the location level shows that provinces in Kenya are highly heterogeneous; hence different spatial factors are important in explaining welfare levels in different areas within provinces, suggesting that targeted propoor policies are needed. Policy simulations are conducted to explore the impact of various interventions on location-level poverty levels. Investments in roads and improvements in soil fertility are shown to potentially reduce poverty rates, with differential impacts in different regions.

Livestock water productivity: feed resourcing, feeding and coupled feed-water resource data bases

Recent studies have projected significant climate change impacts in Africa. In order to understand what this means in terms of human well-being at local level, we need to understand how households can cope and adapt. This need has led many authors to argue for approaches to adaptation that are based on vulnerability analysis. Vulnerability is one of the key terms in the climate change literature, but little progress has been made in the field of its quantification. Typically, indicators are combined according to a weighing scheme, with the identification of indicators and the weighing schemes based on expert judgment rather than empirical evidence. In addition, most quantitative assessments are applied to countries or other administrative units, whereas managing climate risk has traditionally been the responsibility of households. We therefore focus on the adaptive capacity of households. We analyze the coping strategies and vulnerability to climatic stresses of agro-pastoralists in Mozambique and test the validity of a number of commonly used vulnerability indicators. We derive a household-level vulnerability index based on survey data. We find that only 9 out of 26 indicators tested exhibit a statistically significant relationship with households’ vulnerability. In total, they explain about one-third of the variation in vulnerability between households, confirming the need for more research on underlying determinants and processes of vulnerability. With inclusion of local knowledge, our study findings can be used for local targeting, priority setting and resource allocation. Complemented with studies analyzing climate change impacts and findings from country-level adaptive capacity studies, governmental policy can be informed.

Evaluating oat cultivars for dairy forage production in the central Kenyan highlands

While water requirement for livestock is widely perceived as daily drinking water consumption, ~100 times more water is required for daily feed production than for drinking water. Increasing livestock water productivity can be achieved through increasing the water-use efficiency (WUE) of feed production and utilisation. The current paper briefly reviews water requirements for meat and milk production and the extent of, and reason for, variations therein. Life-cycle analysis (LCA) can reveal these variations in WUE but LCA are not tools that can be employed routinely in designing and implementing water-use-efficient feed resourcing and feeding strategies. This can be achieved by (1) choosing agricultural by-products and crop residues where water applications are partitioned over several products for example grain and straw (or food and fodder) contrary to planted forage production where water and land have to be exclusively allocated to fodder production, (2) select and breed WUE crops and forages and exploit cultivar variations, (3) increase crop productivity by closing yield gaps; and (4) increase per animal productivity to reduce the proportion of feed (and therefore water) allocated for maintenance requirement rather than productive purposes. Feed-mediated WUE of dairy buffalo production on almost completely (94%) by-product-based feeding systems could be reduced from 2350 to 548 L of water per kg of milk by the combined effect of increasing basal ration quality in a total mixed ration, which resulted in increased milk yield of ~30%, and by increasing crop productivity from 1 t (actual crop yield) to 3 t (potential crop yield). Exemplary, multi-dimensional sorghum improvement using staygreen quantitative trait loci (QTL) introgression for concomitant improvement of WUE of grain and stover production and stover fodder quality showed opportunities for further linked improvement in WUE of crop and livestock production. Metabolisable energy (ME) yield under water stress conditions measured in lysimeters, (which measure crop water transpired) ranged QTL dependent from 16.47 to 23.93 MJ ME per m3 H2O. This can be extrapolated to 8.23–11.97 MJ ME per m3 H2O evapotranspired under field conditions. To mainstream improvement in WUE of feed resourcing and feeding, the paper suggests the combination of feed resource databases with crop–soil–meteorological data to calculate how much water is required to produce the feed at the available smallest spatial scale of crop–soil–meteorological data available. A framework is presented of how such a tool can be constructed from secondary datasets on land use, cropping patterns and spatially explicit crop–soil–meteorological datasets.

Environmental Security and Pastoralism

With the projected increase in future demand for animal products, efforts to raise animal productivity are necessary to match the rise. Already, the estimated per-capita milk consumption in Kenya has increased to 150 L from 100 L estimated in 1998 while the population is growing at 2.65% annually. Improving milk production is largely constrained by inadequate feeding, particularly from basal roughages. To contribute towards addressing this concern, five oat cultivars (Conway, Glamis, Balado, Mascani and Rhapsody) new to eastern Africa were evaluated versus a ‘Local’ check. Agronomic attributes, forage quality and farmers’ preferences were assessed in the 2015/16 growing season. Dry matter (DM) yields ranged from 5 to 22 t DM ha−1 with Conway accumulating most DM, whereas the relative feed value was in the order Balado > Mascani > Rhapsody > Conway > Glamis > Local. However, crude protein (CP) yield (kg CP ha−1) was highest in Conway and lowest in Mascani. The two most preferred cultivars by the farmers were Conway and Glamis. Based on DM and CP production, and farmers’ choice, we conclude that Conway and Glamis stand a high chance of improving forage production in the area and other similar systems.

The role of spatial analysis in livestock research for sustainable development

Pastoral areas are home for more than 200 million people and provide essential environmental, economic and social services at global level. Despite the key role of grasslands for many emerging economies, these areas are historically affected by intensifying challenges, like droughts, desertification, burgeoning populations and extreme poverty. As a result of these conditions many countries in Africa, Middle East and Asia are host to a disproportionate number of the worlds violent conflicts, where vulnerable pastoralist communities play a key role. The main aim of this paper is to provide an overview of the importance of pastoral areas for the security and an analysis of the role of Geomatic tools to support environmental security analysis in pastoral areas, with special consideration for the activities carried out by ILRI as part of its global mandate to eradicate poverty and insecurity through sustainable livestock production.