Inclusive and adaptive business models for climate-smart value creation

Climate-smart business models target multiple Sustainable Development Goals by fostering agricultural productivity, supporting farm and farmer livelihood resilience, and encouraging climate mitigation. While many business models (cl)aiming to create climate-smart value already exist both in agricultural development and business practice, little scholarly attention has so far been directed toward their functioning. In this paper, we argue that business models need to be inclusive and adaptive to generate climate-smart value equitably for all stakeholders involved and sustainably over time. Inclusivity involves not only providing the poor at the Bottom-of-the-Pyramid (BoP) with access to resources (e.g. finance, technology, access to markets) in business models but also, according to some scholars, with guaranteeing their representation in decision-making over the use of these resources. Adaptability entails the capacity to smoohtly adjust structures and processes of enterprise-BoP partnerships that underlie business models. We suggest that building inclusive and adaptive climate-smart business models is non-trivial work which, in the future, will require rapid cycles of collective experimentation and reflection between decision-makers in climate-smart business models and researchers studying them.</p

Strengthening research skills and creativity among PhD students in RUFORUM regional PhD programmes : report

Meeting: Regional Scientific Data Management and Learning Workshop for PhD Students and Staff, Bunda College of Agriculture, 14-18 November 2011, Lilongwe, MalawiThe training course (2011) was supported by Regional Universities Forum for Capacity Building in Agriculture (RUFORUM). The course aimed to provide PhD students in Malawi who are involved in agricultural research systems, with additional skills to design, collect, manage, analyse and present results from their data and to improve the efficiency of agricultural information and research. The report documents activities, outputs and outcomes of the training

The private sector is already creating climate-smart value

However, the prevailing narrative suggests an endless search for inclusive business models that support a transition towards climate-smart agriculture (CSA). Our approach is a literature review of business models and CSA and qualitative fieldwork with four business models in Southern Africa to investigate the extent and way business models work to support CSA

Evaluation framework of community-based livestock breeding programs

The objective of this paper is to present an evaluation framework to provide guidance for an assessment of the performance, outputs and associated impacts of community-based livestock breeding programs (CBBPs), responding to the need of formalizing the evaluation procedures as it was stressed by FAO. The purpose of such evaluation is to monitor and evaluate on-going activities in CBBPs, to identify challenges and mistakes in the execution of the program, so that appropriate actions can be taken. This evaluation also serves as a guide for funding bodies to measure socio-economic impact on the livelihoods of livestock farmers in order to decide if the program’s goals have been met. The evaluation framework is divided into three domains: evaluation of CBBP implementation based on organizational and technical criteria; monitoring of implementation outputs to evaluate genetic improvement at herd/flock level and the consequential changes at the household level and the community at large; and evaluation of impacts to assess improvement in livelihoods of livestock farmers and eventual effects on the environment. For each evaluation criteria, several indicators are provided.EEA BarilocheFil: Lamuno, Doreen. National Animal Genetic Resources Centre and Databank; UgandaFil: Sölkner, Johann. National Animal Genetic Resources Centre and Databank; UgandaFil: Mészáros, Gabor. National Animal Genetic Resources Centre and Databank; UgandaFil: Nakimbugwe, Helen. National Animal Genetic Resources Centre and Databank; UgandaFil: Mulindwa, Henry. National Agricultural Research Organization, UgandaFil: Nandolo, Wilson. Lilongwe University of Agriculture and Natural Resources, MalawiFil: Gondwe, Timothy. United States Department of Agriculture; Estados UnidosFil: van Tassel, Curt. United States Department of Agriculture; Estados UnidosFil: Mueller, Joaquín Pablo. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Bariloche; ArgentinaFil: Wursinger, Maria. University of Natural Resources and Life Sciences; AustriaFil: Gutierrez, Gustavo. Universidad Nacional Agraria La Molina; Per

Scaling up community-based goat breeding programmes via multi-stakeholder collaboration

Community-based livestock breeding programmes (CBBPs) have emerged as a potential approach to implement sustainable livestock breeding in smallholder systems. In Malawi and Uganda, goat CBBPs were introduced to improve production and productivity of indigenous goats through selective breeding. Scaling up CBBPs have recently received support due to evidence-based results from current implementation and results of CBBPs implemented in other regions of the world. This paper explores strategies for scaling up goat CBBPs in Malawi and Uganda, and documents experiences and lessons learned during implementation of the programme. A number of stakeholders supporting goat-based interventions for improving smallholders’ livelihoods exists. This offers an opportunity for different actors to work together by pooling financial resources and technical expertise for establishment and sustainability of goat CBBPs. Scaling up strategies should be an integral part of the pilot design hence dissemination partners need to be engaged during the design and inception stages of the pilot CBBPs. Creation of self-sustaining CBBPs requires early collaborative programme planning, meaningful investment and long-term concerted and coordinated efforts by collaborating partners. Permanently established actors, like government agencies and research and training institutions, are better placed to coordinate such efforts. The overall goal of the scaling up programme should be creation of a financially sustainable system, in which smallholders are able, on their own, to transact and sustain operations of their local breeding institutions using locally generated revenue/ resources. Since CBBP scaling up is a ‘learning by doing process’, an effective monitoring and evaluation system should be an integral part of the process

How to succeed in implementing community-based breeding programs: Lessons from the field in Eastern and Southern Africa

Breeding programs involving either centralized nucleus schemes and/or importation of exotic germplasm for crossbreeding were not successful and sustainable in most Africa countries. Community-based breeding programs (CBBPs) are now suggested as alternatives that aim to improve local breeds and concurrently conserve them. Community-based breeding program is unique in that it involves the different actors from the initial phase of design up until implementation of the programs, gives farmers the knowledge, skills and support they need to continue making improvements long into the future and is suitable for low input systems. In Ethiopia, we piloted CBBPs in sheep and goats, and the results show that they are technically feasible to implement, generate genetic gains in breeding goal traits and result in socio-economic impact. In Malawi, CBBPs were piloted in local goats, and results showed substantial gain in production traits of growth and carcass yields. CBBPs are currently being integrated into goat pass-on programs in few NGOs and is out-scaled to local pig production. Impressive results have also been generated from pilot CBBPs in Tanzania. From experiential monitoring and learning, their success depends on the following: 1) identification of the right beneficiaries; 2) clear framework for dissemination of improved genetics and an up/out scaling strategy; 3) institutional arrangements including establishment of breeders’ cooperatives to support functionality and sustainability; 4) capacity development of the different actors on animal husbandry, breeding practices, breeding value estimation and sound financial management; 5) easy to use mobile applications for data collection and management; 6) long-term technical support mainly in data management, analysis and feedback of estimated breeding values from committed and accessible technical staff; 7) complementary services including disease prevention and control, proper feeding, and market linkages for improved genotypes and non-selected counterparts; 8) a system for certification of breeding rams/bucks to ensure quality control; 9) periodic program evaluation and impact assessment; and 10) flexibility in the implementation of the programs. Lessons relating to technical, institutional, community dynamics and the innovative approaches followed are discussed

δ13C methane source signatures from tropical wetland and rice field emissions

The atmospheric methane (CH4) burden is rising sharply, but the causes are still not well understood. One factor of uncertainty is the importance of tropical CH4 emissions into the global mix. Isotopic signatures of major sources remain poorly constrained, despite their usefulness in constraining the global methane budget. Here, a collection of new δ13CCH4 signatures is presented for a range of tropical wetlands and rice fields determined from air samples collected during campaigns from 2016 to 2020. Long-term monitoring of δ13CCH4 in ambient air has been conducted at the Chacaltaya observatory, Bolivia and Southern Botswana. Both long-term records are dominated by biogenic CH4 sources, with isotopic signatures expected from wetland sources. From the longer-term Bolivian record, a seasonal isotopic shift is observed corresponding to wetland extent suggesting that there is input of relatively isotopically light CH4 to the atmosphere during periods of reduced wetland extent. This new data expands the geographical extent and range of measurements of tropical wetland and rice δ13CCH4 sources and hints at significant seasonal variation in tropical wetland δ13CCH4 signatures which may be important to capture in future global and regional models. This article is part of a discussion meeting issue ‘Rising methane: is warming feeding warming? (part 2)’

Gap-filling eddy covariance methane fluxes : Comparison of machine learning model predictions and uncertainties at FLUXNET-CH4 wetlands

Time series of wetland methane fluxes measured by eddy covariance require gap-filling to estimate daily, seasonal, and annual emissions. Gap-filling methane fluxes is challenging because of high variability and complex responses to multiple drivers. To date, there is no widely established gap-filling standard for wetland methane fluxes, with regards both to the best model algorithms and predictors. This study synthesizes results of different gap-filling methods systematically applied at 17 wetland sites spanning boreal to tropical regions and including all major wetland classes and two rice paddies. Procedures are proposed for: 1) creating realistic artificial gap scenarios, 2) training and evaluating gap-filling models without overstating performance, and 3) predicting halfhourly methane fluxes and annual emissions with realistic uncertainty estimates. Performance is compared between a conventional method (marginal distribution sampling) and four machine learning algorithms. The conventional method achieved similar median performance as the machine learning models but was worse than the best machine learning models and relatively insensitive to predictor choices. Of the machine learning models, decision tree algorithms performed the best in cross-validation experiments, even with a baseline predictor set, and artificial neural networks showed comparable performance when using all predictors. Soil temperature was frequently the most important predictor whilst water table depth was important at sites with substantial water table fluctuations, highlighting the value of data on wetland soil conditions. Raw gap-filling uncertainties from the machine learning models were underestimated and we propose a method to calibrate uncertainties to observations. The python code for model development, evaluation, and uncertainty estimation is publicly available. This study outlines a modular and robust machine learning workflow and makes recommendations for, and evaluates an improved baseline of, methane gap-filling models that can be implemented in multi-site syntheses or standardized products from regional and global flux networks (e.g., FLUXNET).Peer reviewe

Using the community-based breeding program (CBBP) model as a collaborative platform to develop the African Goat Improvement Network—Image collection protocol (AGIN-ICP) with mobile technology for data collection and management of livestock phenotypes

Introduction: The African Goat Improvement Network Image Collection Protocol (AGIN-ICP) is an accessible, easy to use, low-cost procedure to collect phenotypic data via digital images. The AGIN-ICP collects images to extract several phenotype measures including health status indicators (anemia status, age, and weight), body measurements, shapes, and coat color and pattern, from digital images taken with standard digital cameras or mobile devices. This strategy is to quickly survey, record, assess, analyze, and store these data for use in a wide variety of production and sampling conditions.Methods: The work was accomplished as part of the multinational African Goat Improvement Network (AGIN) collaborative and is presented here as a case study in the AGIN collaboration model and working directly with community-based breeding programs (CBBP). It was iteratively developed and tested over 3 years, in 12 countries with over 12,000 images taken.Results and discussion: The AGIN-ICP development is described, and field implementation and the quality of the resulting images for use in image analysis and phenotypic data extraction are iteratively assessed. Digital body measures were validated using the PreciseEdge Image Segmentation Algorithm (PE-ISA) and software showing strong manual to digital body measure Pearson correlation coefficients of height, length, and girth measures (0.931, 0.943, 0.893) respectively. It is critical to note that while none of the very detailed tasks in the AGIN-ICP described here is difficult, every single one of them is even easier to accidentally omit, and the impact of such a mistake could render a sample image, a sampling day’s images, or even an entire sampling trip’s images difficult or unusable for extracting digital phenotypes. Coupled with tissue sampling and genomic testing, it may be useful in the effort to identify and conserve important animal genetic resources and in CBBP genetic improvement programs by providing reliably measured phenotypes with modest cost. Potential users include farmers, animal husbandry officials, veterinarians, regional government or other public health officials, researchers, and others. Based on these results, a final AGIN-ICP is presented, optimizing the costs, ease, and speed of field implementation of the collection method without compromising the quality of the image data collection

Sustainable Utilization of Indigenous Goats in Southern Africa

Goats have a key role in ensuring food security and economic livelihood to smallholder farmers in rural areas. Women play a vital role in goat rearing, promoting economic autonomy within households. Indigenous goats dominate and are of high significance due to their adaptive traits that are relevant for climate change and low maintenance. However, lack of emphasis on farmer-centered technology development and proper breed characterization remains a hitch to sustainable utilization and breed development of indigenous goats. This can be over come through proper linkage between market and production, workable regional and national agricultural policies, community breeding programs, collaborative research work within the region, and consistent government support