• Energy Research

Several studies estimate the immediate impact of climate change on agricultural societies in terms of changes in crop yields or farm income, though few studies concentrate on the immediate secondary consequences of climate change. This synthetic analysis uses a set of indicators to assess the repercussions of predicted income reductions resulting from climate change on food consumption, nutrition, health expenditure, education, and recreation in Zimbabwe, Cameroon, South Africa and Ethiopia. We also assess the potential decline in human development potential among smallholder dryland farmers in these sub-Saharan African countries. In contrast to previous efforts, the current study directly integrates the uncertainties in estimations of income changes and secondary consequences through a weighting scheme. The results reveal moderate to high levels of secondary impacts which could lead to increased vulnerability to diseases, susceptibility to nutritional disorders, deprivation of educational opportunities, and ultimately to a reduction in human and societal development potential among the considered nations. The article concludes by proposing a portfolio of policy options for ameliorating the secondary impacts of climate change in these sub-Saharan African countries.

AbstractAppreciating and dealing with the plurality of farmers’ perceptions and their contextual knowledge and perspectives of the functioning and performance of their agroecosystems—in other words, their ‘mental models’—is central for appropriate and sustainable agricultural development. In this respect, the sustainable development goals (SDGs) aim to eradicate poverty and food insecurity by 2030 by envisioning social inclusivity that incorporates the preferences and knowledge of key stakeholders, including farmers. Agricultural development interventions and policies directed at sustainable intensification (SI), however, do not sufficiently account for farmers’ perceptions, beliefs, priorities, or interests. Considering two contrasting agroecological systems in coastal Bangladesh, we used a fuzzy cognitive mapping (FCM)-based simulation and sensitivity analysis of mental models of respondents of different farm types from 240 farm households. The employed FCM mental models were able to (1) capture farmers’ perception of farming system concepts and relationships for each farm type and (2) assess the impact of external interventions (drivers) on cropping intensification and food security. We decomposed the FCM models’ variance into the first-order sensitivity index (SVI) and total sensitivity index (TSI) using a winding stairs algorithm. Both within and outside polder areas, the highest TSIs (35–68%) were observed for effects of agricultural extension on changes in other concepts in the map, particularly food security and income (SI indicators), indicating the importance of extension programs for SI. Outside polders, drainage and micro-credit were also influential; within polders, the availability of micro-credit appears to affect farmer perceptions of SI indicators more than drainage. This study demonstrated the importance of reflection on the differing perspectives of farmers both within and outside polders to identify entry points for development interventions. In addition, the study underscores the need for micro-farming systems-level research to assess the context-based feasibility of introduced interventions as perceived by farmers of different farm types.

Despite the promise of climate-smart agriculture (CSA) to improve food security in South Asia, most CSA practices and technologies have not been widely adopted. We identify the key barriers to CSA adoption in South Asia and suggest strategies to overcome them to increase CSA adoption at scale.

South Asia is the world's most poverty-dense region, where climate change and climate variability are expected to result in increased heat stress and erratic precipitation patterns that affect agricultural productivity. Considerable evidence has been generated on the effects of these stresses on crop yield, though previous research has not yet examined their influence on the economic efficiency of cereal producers. Surveying 240 farmers across eight of Pakistan's twelve agro-ecological zones, we examined the impact of temperature and precipitation anomalies – as indicators of climatic variability – and the number of days when temperature exceeds crop specific heat stress thresholds on the economic efficiency of rice and wheat production. To this end, we employed first-stage stochastic production frontier (SPF) models and second-stage ordinary least square (OLS) and quantile regression models. Both OLS and quantile regressions indicated that terminal heat >34 °C has a significant negative impact on wheat production economic efficiency. Small positive deviation (0.54 °C ± 0.16 SD) of the wheat season's mean temperature from the medium-term historical mean also significantly and negatively affected economic efficiency across all regression models. Heat stress >35.5 °C during rice flowering in the monsoon also had a significant and negative impact. A slight positive deviation in temperature averaging 0.38 °C (±0.11 SD) above the medium-term mean also had significant negative effects across all regressions. Cumulative precipitation conversely had significant yet contrary effects, by offsetting farmers’ investment in supplementary irrigation and increasing economic efficiency. Our results highlight the fact that indicators of climatic variability and heat stress negatively affect the economic efficiency of both rice and wheat producing farmers. Farmers’ education and access to financial and extension services were however both positively associated with economic efficiency. Our findings point to the importance of developing interlinked agronomic, economic and socio-ecological policy strategies to adapt and increase the resilience of Pakistan's cereal systems to climatic variability.

Exploring and quantifying the uncertainties in climate impact assessment with multiple climate-crop models is crucial to reducing the total uncertainty and guiding adaptation strategies for crop production. Here, we carried out a climate-crop ensemble simulation to measure the uncertainty in estimated climate impacts on China's wheat productivity by the 2050s. The ensemble included the simulations conducted with the three-DSSAT wheat model ensemble. As for the future climate, five Global Climate projections (GCMs) under two Representative Concentration Pathways (RCP4.5 and 8.5) and two CO2 concentrations were selected. Our results indicate that the median of simulated yield change was between 4.5% ∼ 5.5%, and -7.7% ∼ -5.6% respectively under elevated and current CO2 concentrations by 2050s compared to 1981–2010. The median of simulated phenology change was nearly -12 ∼ -10 d In percentage terms, higher uncertainty in national yield change was observed compared to phenology change. The total relative contributions of climate projections, crop models, and RCP scenarios have been more than 70% of the total uncertainty of national phenology and yield change. Crop models have accounted for the largest uncertainty of irrigated yield, while crop models and climate projections almost contributed a similar share of the total uncertainty of rainfed yield. These findings highlight the distribution of uncertainty and sources of uncertainty both at the national and grid scales, which would provide a more comprehensive understanding of uncertainties in future yield prediction. Our results also showed that larger uncertainty has been observed in warmer regions (growing season average temperature > 20 °C) than in cooler regions, while the wet regions (growing season rainfall > 400 mm) would suffer smaller uncertainty than dry regions. These findings emphasize the relationships between uncertainty and climate factors, which offers insights for improving crop models and designing adaptation strategies.

AbstractDiversification of smallholder rice-based cropping systems has the potential to increase cropping system intensity and boost food security. However, impacts on resource use efficiencies (e.g., nutrients, energy, and labor) remain poorly understood, highlighting the need to quantify synergies and trade-offs among different sustainability indicators under on-farm conditions. In southern coastal Bangladesh, aman season rice is characterized by low inputs and low productivity. We evaluated the farm-level impacts of cropping system intensification (adding irrigated boro season rice) and diversification (adding chili, groundnut, mungbean, or lathyrus) on seven performance indicators (rice equivalent yield, energy efficiency, partial nitrogen productivity, partial potassium productivity, partial greenhouse gas footprint, benefit-cost ratio, and hired labor energy productivity) based on a comprehensive survey of 501 households. Indicators were combined into a multi-criteria performance index, and their scope for improvement was calculated by comparing an individual farmer’s performance to top-performing farmers (highest 20%). Results indicate that the baseline system (single-crop aman season rice) was the least productive, while double cropped systems increased rice equivalent yield 72–217%. Despite gains in productivity, higher cropping intensity reduced resource use efficiencies due to higher inputs of fertilizer and energy, which also increased production costs, particularly for boro season rice. However, trade-offs were smaller for diversified systems including legumes, largely owing to lower N fertilizer inputs. Aman season rice had the highest multi-criteria performance index, followed by systems with mungbean and lathyrus, indicating the latter are promising options to boost food production and profitability without compromising sustainability. Large gaps between individual and top-performing farmers existed for each indicator, suggesting significant scope for improvement. By targeting indicators contributing most to the multi-criteria performance index (partial nitrogen productivity, energy efficiency, hired labor energy productivity), results suggest further sustainability gains can be achieved through future field research studies focused on optimizing management within diversified systems.

Farmers in low-elevation coastal zones in South Asia face numerous food security and environmental sustainability challenges. This study evaluated the effects of nitrogen (N) rate and source on the agronomic, economic, and environmental performance of transplanted and rainfed 'aman' (monsoon-season) rice in Bangladesh's non-saline coastal areas. Fifty-one farmers participated in trials distributed across two landscape positions described as 'highlands' (on which field water inundation depth typically remains <30 cm) and 'medium-highlands' (inundation depths 30-90 cm) planted singly with varieties appropriate to each position (BRRI dhan 39 for highlands and the traditional variety Bhushiara for medium-highlands). Researcher designed but farmer-managed dispersed plots were located across three district sub-units (Barisal Sadar, Hizla, Mehendigonj) and compared N source (broadcast prilled urea or deep-placed urea super granules (USG)) at four N rates. Rice grown on medium-highlands did not respond to increasing N rates beyond 28 kg N ha-1, indicating that little fertilization is required to maintain yields and profitability while limiting environmental externalities. In highland locations, clear trade-offs between agronomic and environmental goals were observed. To increase yields and profits for BRRI dhan 39, 50 or 75 kg N ha-1 was often needed, although these rates were associated with declining energy and increasing greenhouse gas (GHG) efficiencies. Compared to prilled urea, USG had no impact on yield, economic, energy and GHG efficiencies in medium-highland locations. USG conversely led to 4.2-5.8% yield improvements at higher N rates on highlands, while also increasing energy efficiency. Given the observed yield, agronomic and economic benefit of USG, our preliminary results that farmers can consider use of USG at 50 kg N ha-1 to produce yields equivalent to 75 kg N ha-1 of prilled urea in highland landscapes, while also reducing environmental externalities. These results suggest that when assessing sustainable intensification (SI) strategies for rice in South Asia's coastal zones, N requirements should be evaluated within specific production contexts (e.g. cultivar type within landscape position) to identify options for increasing yields without negatively influencing environmental and economic indicators. Similar studies in other parts of coastal South Asia could help policy-makers prioritize investments in agriculture with the aim of improving rice productivity while also considering income generation and environmental outcomes.