Improved feeding and forages at a crossroads: Farming systems approaches for sustainable livestock development in East Africa

Dairy development provides substantial potential economic opportunities for smallholder farmers in East Africa, but productivity is constrained by the scarcity of quantity and quality feed. Ruminant livestock production is also associated with negative environmental impacts, including greenhouse gas (GHG) emissions, air pollution, high water consumption, land-use change, and loss of biodiversity. Improved livestock feeding and forages have been highlighted as key entry point to sustainable intensification, increasing food security, and decreasing environmental trade-offs including GHG emission intensities. In this perspective article, we argue that farming systems approaches are essential to understand the multiple roles and impacts of forages in smallholder livelihoods. First, we outline the unique position of forages in crop-livestock systems and systemic obstacles to adoption that call for multidisciplinary thinking. Second, we discuss the importance of matching forage technologies with agroecological and socioeconomic contexts and niches, and systems agronomy that is required. Third, we demonstrate the usefulness of farming systems modeling to estimate multidimensional impacts of forages and for reducing agro-environmental trade-offs. We conclude that improved forages in East Africa are at a crossroads: if adopted by farmers at scale, they can be a cornerstone of pathways toward sustainable livestock systems in East Africa.</p

Agroecology in large scale farming:A research agenda

Agroecology promises a third way between common global agriculture tradeoffs such as food production and nature conservation, environmental sustainability and ecosystem services. However, most successful examples of mainstreaming agroecology come from smallholder, family agriculture, that represents only about 30% of the world agricultural area. Mainstreaming agroecology among large scale farmers is urgently needed, but it requires addressing specific questions in research, technology and policy development to support sustainable transitions. Here we take stock of the existing knowledge on some key aspects necessary to support agroecological transitions in large scale farming, considering two contrasting starting points: highly subsidized and heavily taxed agricultural contexts, represented here by the examples of Western Europe and temperate South America. We summarize existing knowledge and gaps around service crops, arthropod-mediated functions, landscape and watershed regulation, graze-based livestock, nature-inclusive landscapes, and policy mechanisms to support transitions. We propose a research agenda for agroecology in large scale farming organized in five domains: (i) Breeding for diversity, (ii) Scalable complexity, (iii) Managing cycles beyond fields and farms, (iv) Sharing the cultivated landscape, and (v) Co-innovation with farmers, value chains and policy makers. Agroecology may result in a renewed impetus in large scale farming, to attract the youth, foster clean technological innovation, and to promote a new generation of large-scale farmers that take pride in contributing to feeding the world while serving the planet and its people

Implications of landscape configuration on understory forage productivity: a remote sensing assessment of native forests openings

Sound management of native forests used for cattle grazing requires understanding the dynamics of forage productivity in the openings. Despite their importance, forage productivity drivers in highly heterogeneous forested landscapes, or their variability over the year, are still unclear. The aim of this work is to find predictors of Normalized Difference Vegetation Index (NDVI) variation in the openings of native temperate forests and to evaluate how these predictors change within the growing season. We used high spatial resolution remote sensing imagery from NW Patagonia to separate forest openings from tree dense canopy. We obtained data of each opening related with herbaceous and shrub forage productivity and calculated landscape metrics. We estimated a multiple linear regression model for predicting NDVI in each season. Beyond known variables related with forage productivity (altitude, precipitation, etc.), the shape of forest’ openings appeared as relevant in predicting NDVI. Higher values of forest opening perimeters were related with a decrease in NDVI in spring when soil water content is not limiting and conversely with an increase in NDVI in summer when water is limiting growth. These results suggest that environmental drivers such as temperature and soil moisture inside the opening, and competition or facilitation process between trees and grasses are mediated by the shape of the opening. Management of heterogeneous native forests for cattle raising requires considering the shape of the openings to maximize forage productivity.Fil: Trinco, Fabio Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigaciones en Recursos Naturales, Agroecología y Desarrollo Rural. - Universidad Nacional de Rio Negro. Instituto de Investigaciones en Recursos Naturales, Agroecología y Desarrollo Rural; ArgentinaFil: Rusch, Verónica E.. Instituto Nacional de Tecnología Agropecuaria; ArgentinaFil: Howison, Ruth A.. University of Groningen; Países BajosFil: Garibaldi, Lucas Alejandro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigaciones en Recursos Naturales, Agroecología y Desarrollo Rural. - Universidad Nacional de Rio Negro. Instituto de Investigaciones en Recursos Naturales, Agroecología y Desarrollo Rural; ArgentinaFil: Tittonell, Pablo. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Patagonia Norte. Estación Experimental Agropecuaria San Carlos de Bariloche. Instituto de Investigaciones Forestales y Agropecuarias Bariloche. - Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigaciones Forestales y Agropecuarias Bariloche; Argentin

Xanthomonas Wilt of banana drives changes in land-use and ecosystem services across Infected landscapes

Changes in land-use have been observed in banana-based systems in the African Great Lakes region affected by Xanthomonas wilt disease (XW) of banana. Through focus group discussions (FGDs) and the 4-cell method (to map the area under production and the number of households involved), changes in land-use were assessed in 13 XW-affected landscapes/villages along a 230 km transect from Masisi (where XW arrived in 2001) to Bukavu (XW arrived around 2014) in the Eastern Democratic Republic of Congo. Farmers’ perceptions on the sustainability of new land uses were also documented. Soil nutrient content and erosion levels were measured for five major land-use options/trajectories on 147 fields across 55 farms in three landscapes along the transect. From banana being ranked the most important crop (92% of landscapes) before XW outbreaks, its importance had declined, with it grown on smaller farms by most households in 36% of the landscapes, while in 64% of cases by few households on smaller plots. Farmers uprooted entire banana mats or fields, expanding land under other crops. Species richness did not change at landscape level, although 21 crops were introduced at farm level. Banana is, however, still perceived as more sustainable due to its multi-functional roles. Soils under banana had better chemical attributes, while high erosion levels (Mg ha−1 year−1) occurred under cassava (1.7–148.9) compared with banana (0.3–10.7) and trees (0.3–5.9). The shifts from banana could thus affect supply of key services and sustainability of the farming systems. This study offers a good basis for interventions in XW-affected landscapes

Capturing farm diversity with hypothesisbased typologies: An innovative methodological framework for farming system typology development

Creating typologies is a way to summarize the large heterogeneity of smallholder farming systems into a few farm types. Various methods exist, commonly using statistical analysis, to create these typologies. We demonstrate that the methodological decisions on data collection, variable selection, data-reduction and clustering techniques can bear a large impact on the typology results. We illustrate the effects of analysing the diversity from different angles, using different typology objectives and different hypotheses, on typology creation by using an example from Zambia's Eastern Province. Five separate typologies were created with principal component analysis (PCA) and hierarchical clustering analysis (HCA), based on three different expert-informed hypotheses. The greatest overlap between typologies was observed for the larger, wealthier farm types but for the remainder of the farms there were no clear overlaps between typologies. Based on these results, we argue that the typology development should be guided by a hypothesis on the local agriculture features and the drivers and mechanisms of differentiation among farming systems, such as biophysical and socio-economic conditions. That hypothesis is based both on the typology objective and on prior expert knowledge and theories of the farm diversity in the study area. We present a methodological framework that aims to integrate participatory and statistical methods for hypothesis-based typology construction. This is an iterative process whereby the results of the statistical analysis are compared with the reality of the target population as hypothesized by the local experts. Using a well-defined hypothesis and the presented methodological framework, which consolidates the hypothesis through local expert knowledge for the creation of typologies, warrants development of less subjective and more contextualized quantitative farm typologies.Estación Experimental Agropecuaria BarilocheFil: Alvarez, Stephanie. Wageningen University & Research. Farming Systems Ecology; HolandaFil: Timler, Carl J. Wageningen University & Research. Farming Systems Ecology; HolandaFil: Michalscheck, Mirja. Wageningen University & Research. Farming Systems Ecology; HolandaFil: Paas, Wim. Wageningen University & Research. Farming Systems Ecology; HolandaFil: Descheemaeker, Katrien. Wageningen University & Research. Plant Production Systems; HolandaFil: Tittonell, Pablo Adrian. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Bariloche. Área de Recursos Naturales; ArgentinaFil: Andersson, Jens A. International Maize and Wheat Improvement Center (CIMMYT); ZimbaweFil: Groot, Jeroen C. J. Wageningen University & Research. Farming Systems Ecology Group, Plant Sciences; Holand