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SUMMARY: Smallholder livestock systems in Central America are typically based on pastures with traditional grasses and associated management practices, such as pasture burning and extensive grazing. With the rise of the global population and a corresponding increase in demand for meat and milk production, research efforts have focused on the development of improved grasses and the incorporation of legume species that can increase productivity and sustainability of Central American livestock systems. However, farmer adoption remains very limited, in part due to the lack of site-specific evaluation and recommendations by local institutions. Using a multi-site participatory approach, this study examined the potential of five improved grasses and five species of forage legumes as alternatives to the broadly disseminated grass Hyparrhenia rufa (cv. Jaragua) in pasture-based cattle systems in western Honduras and northern El Salvador. Improved grasses (four Brachiaria sp. and Megathyrsus maximus) produced significantly more biomass than H. rufa ; also four of the five legume varieties evaluated (Canavalia ensiformis , Canavalia brasiliensis , Vigna unguiculata , and Vigna radiata) demonstrated high adaptability to diverse environmental conditions across sites. Farmer participatory evaluation offers a valuable means to assess performance of forages and will likely contribute to their improved utilization. Future research is needed on more refined management recommendations, pasture system design, costs and environmental benefits associated with the adoption of these forages in local livestock production systems. [ABSTRACT FROM AUTHOR]

Livestock systems in the tropics can contribute to mitigate climate change by reducing greenhouse gas (GHG) emissions and increasing carbon accumulation. We quantified C stocks and GHG emissions of 30 dual-purpose cattle farms in Nicaragua using farm inventories and lifecycle analysis. Trees in silvo-pastoral systems were the main C stock above-ground (16–24 Mg ha-1), compared with adjacent secondary forests (43 Mg C ha-1). We estimated that methane from enteric fermentation contributed 1.6 kg CO2-eq., and nitrous oxide from excreta 0.4 kg CO2-eq. per kg of milk produced. Seven farms that we classified as climate-smart agriculture (CSA) out of 16 farms had highest milk yields (6.2 kg cow-1day-1) and lowest emissions (1.7 kg CO2-eq. per kg milk produced). Livestock on these farms had higher-quality diets, especially during the dry season, and manure was managed better. Increasing the numbers of CSA farms and improving CSA technology will require better enabling policy and incentives such as payments for ecosystem services. [ABSTRACT FROM AUTHOR]

Achieving inclusive value chain development is a challenging task due to the complex and dynamic nature of interconnected value chains and their social, economic, and ecological dimensions. While many policies and intervention options exist to upgrade value chains, there are fewer methods that can be used to understand and quantify the multidimensional impacts that value chain policies and interventions may have throughout the value chain. This paper addresses this methodological gap by employing a system dynamics (SD) modeling approach. SD models allow us to model and quantify the processes and relationships inherent in the value chain through simulations, serving as a policy laboratory for the empirical assessment of intervention options. An SD model of the Matiguás dairy value chain in Nicaragua was developed and tested through a participatory modeling process. Our research tested and evaluated the short-, medium-, and long-term impacts of specific interventions and policies in the Matiguás dairy value chain with the goal of strengthening the competitiveness and inclusion of small- and medium-scale producers. These interventions centered on improving the feeding system, which was identified by stakeholders as the critical constraint to competitiveness. The policy analysis reveals that both improved pastures and increased use of concentrates raise producer milk productivity by 5% and 11%, respectively in the long run, but are also expensive strategies for smallholder producers, leading to a reduction in profits relative to the baseline by 1% and 3%, respectively. Consequently, policymakers should identify strategies that help to reduce concentrate costs and support producers with investments in improved pasture, while also promoting training in pasture management skills. Indeed, in the long-run, model results reveal that investment and training in pasture management results in a 30% and 35% increase in milk production during the wet and dry season, respectively. Simulation results further highlighted that intensifying the feeding system to improve cow milk yields is mainly profitable in the long term, and thus requires a longer-term perspective by policymakers. The model provides a deeper understanding of the complex and dynamic nature of the Matiguás dairy value chain and the interactions between markets, coordination aspects, biophysical phenomena, and income. The system dynamics approach to value chain analysis further addresses a major analytical shortcoming in value chain analysis and provides decision makers with an improved platform for planning and policy formulation. [ABSTRACT FROM AUTHOR]

Abstract: The tropical dry forest region along the western slope of Central America represents a biodiverse and fragile area that is under increasing pressure from agricultural production, thus threatening the provision of ecosystem services, the integrity of these landscapes, and the rural communities who depend on them. To address this issue, we evaluated the influence of common agricultural management practices (cropping and livestock systems) vs. the Quesungual slash-and-mulch agroforestry system (QSMAS) on diverse parameters of soil quality and function. We then used this information to identify soil invertebrate bioindicators that represent key aspects of soil quality (chemical fertility, physical properties, aggregate morphology, and biological functioning). In February of 2011 soil sampling was conducted on six hillside farms near the town of Somotillo in western Nicaragua to assess soil properties and the abundance and diversity of soil macrofauna within four management systems: (1) QSMAS, based on maize production, (2) traditional maize cropping system with few trees (TC), (3) silvopastoral system with low tree density (SP), and (4) secondary forest (SF), used as a reference. The conversion of forest to agriculture demonstrated the greatest impact of management in this study. For example, SF presented significantly higher diversity of soil invertebrate taxonomic groups than either TC or SP (P <0.03), and demonstrated the lowest level of soil compaction, significantly less than SP (P <0.05). Additionally, SF demonstrated the highest value of soil quality according to a synthetic indicator that integrates chemical, physical and biological aspects of soil quality. Although overall soil quality under QSMAS was lower than SF, this system demonstrated the highest abundance (number of individuals) of soil macrofauna, and appeared to at least partially mitigate the negative consequences of forest conversion on soil functioning. Using the Indicator Value Index, which ranks species according to their specificity and fidelity across sites, along with farmer consultation we found seven indicator taxa of soil quality that could greatly facilitate future evaluation of land management impacts by farmers and technicians in the region. We suggest that the methodology applied is robust and adaptable to diverse agroecological contexts and would allow for more rapid responses to evolving land use issues as they arise. [Copyright &y& Elsevier]