Evaluating the value of agricultural climate services using hindcast experiments Methods development in India and Bangladesh

This research note offers insights to a new method for understanding the economic benefits of utilizing climate services for decision making in agriculture, which can provide justification for the public and private investment in provision of climate services to farmers. In order to understand the potential benefits of weather information for improved farm decision making, case studies from wheat farming in India and Bangladesh are presented

Agriculture, Food and Nutrition Security: Concept, Datasets and Opportunities for Computational Social Science Applications

Ensuring food and nutritional security requires effective policy actions that consider the multitude of direct and indirect drivers. The limitations of data and tools to unravel complex impact pathways to nutritional outcomes have constrained efficient policy actions in both developed and developing countries. Novel digital data sources and innovations in computational social science have resulted in new opportunities for understanding complex challenges and deriving policy outcomes. The current chapter discusses the major issues in the agriculture and nutrition data interface and provides a conceptual overview of analytical possibilities for deriving policy insights. The chapter also discusses emerging digital data sources, modelling approaches, machine learning and deep learning techniques that can potentially revolutionize the analysis and interpretation of nutritional outcomes in relation to food production, supply chains, food environment, individual behaviour and external drivers. An integrated data platform for digital diet data and nutritional information is required for realizing the presented possibilities

How to build a pandemic resilient agrifood system? A review of policy lessons from COVID-19 in Bangladesh

The COVID-19 pandemic impacted most of the Bangladesh population and almost all sectors of its economy, including the agriculture and food systems. The Government of Bangladesh (GoB) and development partners took measures to prevent the spread of the virus and keep the agriculture and food systems running, and farmers and communities adopted local techniques as resilience measures to adapt to and lessen the effect of the virus. This review attempts to synthesize the knowledge on impacts of COVID-19 on Bangladesh agriculture and food systems, and document government's and development partners' policy responses and measures to COVID-19 to mitigate the impacts and farmers' coping strategies as effective resilience measures. The aim here is to provide a comprehensive picture of impacts and policy lessons to the Bangladesh government and development partners to effectively manage any future pandemics such as COVID-19 in the country and in developing countries of Asia. The core lesson is that agriculture needs a transformation to technology intensive (both digital and non-digital), efficient supply chains (i.e., shorter value chains), mechanization, farmer organizations led, and consumer connected (e.g., online platforms and direct marketing channels) with various kinds of resilience measures, including information sharing systems, financial mechanisms and social safety nets. A diversified approach is required for perishable and non-perishable commodities. There is also need of international effort to minimize trade and supply disruption and prevention of export ban and similar policies to reduce the impact on food system and associated livelihoods

Multi-level socioecological drivers of agrarian change:Longitudinal evidence from mixed rice-livestock-aquaculture farming systems of Bangladesh

Coastal systems are facing natural and human-driven change coupled with a rising population. With increasing shifts in socioecological conditions during the past several decades, it is important to understand how socioecological drivers at different hierarchical levels: -micro, -meso, and -macro affect coastal farming systems, which play a crucial role in the livelihoods of coastal dwellers. Mixed rice-livestock-aquaculture farming in Southern Bangladesh exemplifies the rapid change occurring in many of the world's coastal farming systems in response to these drivers. We used panel data observations from the above study area and modeled trajectories of farm typologies, and the impact of multi-level socioecological drivers by a novel approach. Our approach integrates: (1) a well-articulated conceptual frame of change observed using (2) a temporal view of the potential drivers, change process and farm type outcomes, with the twenty years panel data of 502 households that is analyzed by means of (3) multivariate statistics in conjunction with panel data models that operationalize the conceptual frame. Our approach allows (a) estimating dynamic effects over time that typically cannot be estimated in a cross-sectional data set, (b) distinguishing between time-invariant fixed and time dependent random effects of multi-level socioecological drivers, and (c) controlling for omitted variables to a certain extent. Considering farming systems both within and outside of polder embankment systems intended to protect against oceanic water intrusion, we found a gradual shift from heterogeneous, rice-livestock farm types to more homogenous farms with less livestock and more off-farm activities. Micro-level factors including farm plot fragmentation, farmers' experience in cropping, machinery, salinity and soil fertility were influencing changes in farming systems. Meso-level factors including markets, road infrastructure, labor availability, access to extension and land tenure also affect the trajectory of farming systems change. Among macro-level drivers, increasing population density positively and significantly influenced cropping intensity among farms outside polder systems. Within polders, a positive but non-significant trend was observed for the influence of population density on cropping intensity. Our data also indicate negative and significant influence of cyclonic storms on cropping intensity over time in both areas. Our results underscore the importance of accounting for multiple levels of socioecological drivers of change when developing appropriate policy options for sustainable development in South Asia's coastal farming systems

Quantifying farmers’ preferences for cropping systems intensification: A choice experiment approach applied in coastal Bangladesh’s risk prone farming systems

Sustainable intensification (SI) is envisioned as an effective strategy for developing countries to increase farm productivity while reducing negative environmental and social externalities. The development of regionally appropriate SI options however requires accounting for the knowledge and preferences of key stakeholders. In Bangladesh, the Government has requested international donors to support the development of dry season rice expansion in the coastal region. Policies however tend to be made without adequate study of farmers’ preferences and ambitions; this can render crop intensification efforts ineffective. Understanding farmers’ preferences for alternative crops and crop management practices are therefore crucial for success where agricultural development investments aim at incorporating the principles of SI. OBJECTIVE(S): Using coastal Bangladesh as a case study– we aim to (1) quantify farmers’ preferences for alternative irrigated crop and crop management options in comparison to the status quo (land fallowing), (2) analyze whether farmers’ preferences are conditioned by concerns regarding the cost and availability of irrigation and fertilizer inputs in comparison to expected net revenues, (3) understand how the heterogeneity in preferences can be attributed to farmer and/or farm characteristics, institutional, and biophysical factors, (4) determine how much farmers’ are willing to invest in different crops and crop management options – including those reliant and not reliant on irrigation. METHODS: Taking 300 farmers in two diverse coastal environments, a choice experiment (CE) was employed to explore the heterogeneity in farmers’ preferences for different dry “rabi” season intensification options (‘boro’ rice, maize, wheat and mungbean) against the status quo (dry season land fallowing after harvest of the monsoon season rice crop). Analyses included random parameter logit modeling followed by willingness-to-invest and profit simulations. RESULTS AND CONCLUSIONS: Analyses revealed strong farmer preferences against rice and in favor of irrigated maize, and also in favor of rainfed or partially irrigated mungbean as an alternative to land fallowing. Irrespective of their location and environmental conditions, respondents had largely a negative preference for irrigation and fertilizer use due to high investment costs and associated production risks in the dry season. Nonetheless, a significant positive effect on their willingness-to-intensify cropping was observed where farmers felt it feasible to provide in-field drainage to limit waterlogging risks.Estación Experimental Agropecuaria BarilocheFil: Aravindakshan, Sreejith. Wageningen University and Research. Farming Systems Ecology, ; HolandaFil: Aravindakshan, Sreejith. International Maize and Wheat Improvement Center (CIMMYT); BangladeshFil: Krupnik, Timothy J. International Maize and Wheat Improvement Center (CIMMYT); BangladeshFil: Amjath-Babu, T.S. International Maize and Wheat Improvement Center (CIMMYT); BangladeshFil: Speelman, Stijn. Ghent University. Department of Agricultural Economics; BélgicaFil: Tur-Cardona, Juan. Ghent University. Department of Agricultural Economics; BélgicaFil: Tittonell, Pablo Adrian. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Bariloche; ArgentinaFil: Tittonell, Pablo Adrian. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Instituto de Investigaciones Forestales y Agropecuarias Bariloche; ArgentinaFil: Tittonell, Pablo Adrian. Groningen University. Groningen Institute of Evolutionary Life Sciences; HolandaFil: Groot, Jeroen C.J. Wageningen University and Research. Farming Systems Ecology; HolandaFil: Groot, Jeroen C.J. Bioversity International; ItaliaFil: Groot, Jeroen C.J. International Maize and Wheat Improvement Center (CIMMYT); Mexic

Developing a framework for an early warning system of seasonal temperature and rainfall tailored to aquaculture in Bangladesh

The occurrence of high temperature and heavy rain events during the monsoon season are a major climate risk affecting aquaculture production in Bangladesh. Despite the advances in the seasonal forecasting, the development of operational tools remains a challenge. This work presents the development of a seasonal forecasting approach to predict the number of warm days (NWD) and number of heavy rain days (NHRD) tailored to aquaculture in two locations of Bangladesh (Sylhet and Khulna). The approach is based on the use of meteorological and pond temperature data to generate linear models of the relationship between three-monthly temperature and rainfall statistics and NWD and NHRD, and on the evaluation of the skill of three operational dynamical models from the North American Multi-Model Ensemble (NMME) project. The linear models were used to evaluate the forecasts for two seasons and 1-month lead time: May to July (MJJ), forecast generated in April, and August to October (ASO), forecast generated in July. Differences were observed in the skill of the models predicting maximum temperature and rainfall (Spearman correlation, Root Mean Square Error, Bias statistics, and Willmott’s Index of Agreement,), in addition to NWD and NHRD from linear models, which also vary for the target seasons and location. In general, the models show higher predictive skill for NWD than NHRD, and for Sylhet than in Khulna. Among the three evaluated NMME models, CanSIPSv2 and GFDL-SPEAR exhibit the best performance, they show similar features in terms of error metrics, but CanSIPSv2 presents a lower interannual standard deviation

Bridging the climate information gap for adaptation: Mainstreaming climate services into higher education in Bangladesh

Bangladesh has proactively integrated climate change into national policies, and is renowned for constantly improving adaptation capacity. Yet, much of the focus has concentrated on long-term climate change scenarios and short-term weather forecasts. Additionally, most decision-makers (both policymakers and practitioners) lack the knowledge and skills to understand and use available climate information (past, present, short-, medium- and long-term future) that can support locally-led adaptation and reduce loss and damage. Bangladesh Meteorological Department (BMD) has been working with IRI and others to improve not only the range and quality of information products but also its communication modalities. International Centre for Climate Change and Development (ICCCAD), International Research Institute for Climate and Society (IRI), Bangladesh Meteorological Department (BMD), and International Maize and Wheat Improvement Center (CIMMYT) jointly created the Bangladesh Academy for Climate Services (BACS) to strengthen national climate services through training, academic engagement and stakeholder convening. This report describes the outcomes of an Adaptation Research Alliance (ARA) funded microgrant project aligned with the BACS goals of co-producing climate services content that can help bridge the climate services knowledge gap in Bangladesh through transdisciplinary collaboration. The project was a collaboration between several universities across the country to support a long-term vision where young people are trained in every climate-sensitive sector to make use of all information available to improve their resilience

Analyzing farm household strategies for food security and climate resilience: The case of Climate-Smart Villages of Southeast Asia

This paper develops a conceptual framework with an indicator-based approach to assess Climate-Smart Villages (CSVs) and applies it to case study sites in Lao PDR (Ekxang CSV), Cambodia (Rohal Suong CSV), and Vietnam (Tra Hat CSV) in Southeast Asia. The intensification, extensification, diversification, commercialization, alteration of practices, use of common lands, migration strategies that can augment climate resilience, farm income, assets, and food security are assessed based on a composite index of the strategies and key outcome variables. The study demonstrates a method that can be applied widely for assessing climate-smart agriculture strategies and finding possible entry points for climate-smart interventions. The influence of gender in resource control and livelihood strategies is also discussed. It is also evident that the climate-smart interventions can augment different livelihood strategies of farmers and enhance the developmental and climate resilience outcomes. There is a need to prioritize the possible interventions in each case and implement them with the help of donor agencies, local institutions, and government offices

Comparing smallholder farmers' perception of climate change with meteorological data: A case study from southwestern Nigeria

This paper examines smallholder farmers’ perceptions of climate change, climate variability and their impacts, and adaptation strategies adopted over the past three decades. We use ethnographic analysis, combined with Cumulative Departure Index (CDI), Rainfall Anomaly Index (RAI) analysis, and correlation analysis to compare farmers’ perceptions in Southwestern Nigeria with historical meteorological data, in order to assess the way farmers’ observations mirror the climatic trends. The results show that about 67% of farmers who participated had observed recent changes in climate. Perceptions of rural farmers on climate change and variability are consistent with the climatic trend analysis. RAI and CDI results illustrate that not less than 11 out of 30 years in each study site experienced lower-than-normal rainfall. Climatic trends show fluctuations in both early growing season (EGS) and late growing season (LGS) rainfall and the 5-year moving average suggests a reduction in rainfall over the 30 years. Climatic trends confirmed farmers’ perceptions that EGS and LGS precipitations are oscillating, that rainfall onset is becoming later, and EGS rainfall is reducing. Overall impacts of climate change on both crops and livestock appear to be highly negative, much more on maize (62.8%), yam (52.2%), poultry (67%) and cattle (63.2%). Years of farming experiences and level of income of farmers appear to have a significant relationship with farmers’ choice of adaptation strategies, with r≥0.60@ p < 0.05 and r≥0.520@ p <0.05 respectively. The study concluded that farmers’ perceptions of climate change mirror meteorological analysis, though their perceptions were based on local climate parameters. Smallholder farmers are particularly vulnerable to climate change since the majority of them do not have enough resources to cope

Transitioning to groundwater irrigated intensified agriculture in Sub-Saharan Africa: An indicator based assessment

Growing populations, changing market conditions, and the food security risks posed by rainfed cropping and climate change collectively indicate that Sub-Saharan African nations could benefit from transforming agricultural production to more intensive yet resilient and sustainable systems. Although highly underutilized, emerging evidence indicates that groundwater may be more widely available than previously thought, highlighting its potential role in facilitating such a transformation. Nevertheless, the possibility for such a transition is conditioned by number of complex factors. We therefore construct a transition index that integrates data considering groundwater and energy availability and cost, market access, infrastructural needs, farm conditions and natural resource stocks, labor availability, climate, population density, as well as economic and political framework variables, using a principal component analysis based methodology. Using the consequent multi-dimensional transition index and constituent intermediate indices, we provide an assessment of groundwater irrigation potential discussed in consideration of Burkina Faso, Ghana, Malawi, Ethiopia, Nigeria, Zambia, Namibia, Cameroon, and Zimbabwe. Our results, though preliminary, provide a methodology for conducting such an integrated assessment, while deriving a holistic set of policy options considering the transition towards appropriate use of groundwater for agricultural development