Stakeholder-driven transformative adaptation is needed for climate-smart nutrition security in sub-Saharan Africa.

Improving nutrition security in sub-Saharan Africa under increasing climate risks and population growth requires a strong and contextualized evidence base. Yet, to date, few studies have assessed climate-smart agriculture and nutrition security simultaneously. Here we use an integrated assessment framework (iFEED) to explore stakeholder-driven scenarios of food system transformation towards climate-smart nutrition security in Malawi, South Africa, Tanzania and Zambia. iFEED translates climate-food-emissions modelling into policy-relevant information using model output implication statements. Results show that diversifying agricultural production towards more micronutrient-rich foods is necessary to achieve an adequate population-level nutrient supply by mid-century. Agricultural areas must expand unless unprecedented rapid yield improvements are achieved. While these transformations are challenging to accomplish and often associated with increased greenhouse gas emissions, the alternative for a nutrition-secure future is to rely increasingly on imports, which would outsource emissions and be economically and politically challenging given the large import increases required.

Perennial biomass cropping and use: Shaping the policy ecosystem in European countries.

Demand for sustainably produced biomass is expected to increase with the need to provide renewable commodities, improve resource security and reduce greenhouse gas emissions in line with COP26 commitments. Studies have demonstrated additional environmental benefits of using perennial biomass crops (PBCs), when produced appropriately, as a feedstock for the growing bioeconomy, including utilisation for bioenergy (with or without carbon capture and storage). PBCs can potentially contribute to Common Agricultural Policy (CAP) (2023-27) objectives provided they are carefully integrated into farming systems and landscapes. Despite significant research and development (R&D) investment over decades in herbaceous and coppiced woody PBCs, deployment has largely stagnated due to social, economic and policy uncertainties. This paper identifies the challenges in creating policies that are acceptable to all actors. Development will need to be informed by measurement, reporting and verification (MRV) of greenhouse gas emissions reductions and other environmental, economic and social metrics. It discusses interlinked issues that must be considered in the expansion of PBC production: (i) available land; (ii) yield potential; (iii) integration into farming systems; (iv) R&D requirements; (v) utilisation options; and (vi) market systems and the socio-economic environment. It makes policy recommendations that would enable greater PBC deployment: (1) incentivise farmers and land managers through specific policy measures, including carbon pricing, to allocate their less productive and less profitable land for uses which deliver demonstrable greenhouse gas reductions; (2) enable greenhouse gas mitigation markets to develop and offer secure contracts for commercial developers of verifiable low-carbon bioenergy and bioproducts; (3) support innovation in biomass utilisation value chains; and (4) continue long-term, strategic R&D and education for positive environmental, economic and social sustainability impacts.

Spatially explicit database on crop-livestock management, soil, climate, greenhouse gas emissions and mitigation potential for all of Bangladesh.

This data article provides spatially explicit data on greenhouse gas (GHG) emissions and mitigation potential at various administrative levels for the whole of Bangladesh. The results arising from analysis of this database are presented in research article "Quantifying opportunities for greenhouse gas emissions mitigation using big data from smallholder crop and livestock farmers across Bangladesh" [1]. We collected crop and livestock management data and associated soil and climatic data from variety of primary and secondary sources outlined below in our methodology. The datafiles on crops and livestock contain model outputs for three greenhouse gases (CO2, CH4 and N2O) and their global warming potential, which are linked, to the information on crop/livestock management, soil and climatic conditions presented in the supplementary data of the associated manuscript. The datafiles on mitigation potential contain district-level annual GHG mitigation potential by 2030 and 2050 segregated by different crops/livestock types and mitigation options. This dataset is useful for Bangladesh's GHG accounting from the agricultural sector, and can be used to update its nationally determined contributions. Administrative level emissions and mitigation potential estimates segregated by crop-livestock types and mitigation options are useful to prioritize agricultural research and development interventions consistent with food security and environmental goals and to organize agricultural extension and support services to better inform farmers on food production and move towards GHG mitigation goals.

Quantifying opportunities for greenhouse gas emissions mitigation using big data from smallholder crop and livestock farmers across Bangladesh.

Climate change is and will continue to have significant implications for agricultural systems. While adaptation to climate change should be the priority for smallholder production systems, adoption of cost-effective mitigation options in agriculture not only contributes to food security but also reduces the extent of climate change and future adaptation needs. Utilizing management data from 16,413 and 12,548 crop and livestock farmers and associated soil and climatic data, we estimated GHG emissions generated from crop and livestock production using crop and livestock models, respectively. Mitigation measures in crop and livestock production, their mitigation potential and cost/benefit of adoption were then obtained from literature review, stakeholder consultations and expert opinion. We applied the identified mitigation measures to a realistic scale of adoption scenario in the short- (2030) and long-term (2050). Our results were then validated through stakeholders consultations. Here, we present identified mitigation options, their mitigation potentials and cost or benefit of adoption in the form of Marginal Abatement Cost Curves (MACC). Based on our analysis, total GHG emissions from agricultural sector in Bangladesh for the year 2014-15 is 76.79 million tonne (Mt) carbon-dioxide equivalent (CO2e). Business-as-usual GHG emissions from the agricultural sector in Bangladesh are approximately 86.87 and 100.44 Mt CO2e year-1 by 2030 and 2050, respectively. Adoption of climate-smart crop and livestock management options to reduce emissions considering a realistic adoption scenario would offer GHG mitigation opportunities of 9.51 and 14.21 Mt CO2e year-1 by 2030 and 2050, respectively. Of this mitigation potential, 70-75% can be achieved through cost-saving options that could benefit smallholder farmers. Realization of this potential mitigation benefit, however, largely depends on the degree to which supportive policies and measures can encourage farmers' adoption of the identified climate smart agricultural techniques. Therefore, government should focus on facilitating uptake of these options through appropriate policy interventions, incentive mechanisms and strengthening agricultural extension programs.

Cost-effective opportunities for climate change mitigation in Indian agriculture.

Long-term changes in average temperatures, precipitation, and climate variability threaten agricultural production, food security, and the livelihoods of farming communities globally. Whilst adaptation to climate change is necessary to ensure food security and protect livelihoods of poor farmers, mitigation of greenhouse gas (GHG) emissions can lessen the extent of climate change and future needs for adaptation. Many agricultural practices can potentially mitigate GHG emissions without compromising food production. India is the third largest GHG emitter in the world where agriculture is responsible for 18% of total national emissions. India has identified agriculture as one of the priority sectors for GHG emission reduction in its Nationally Determined Contributions (NDCs). Identification of emission hotspots and cost-effective mitigation options in agriculture can inform the prioritisation of efforts to reduce emissions without compromising food and nutrition security. We adopted a bottom-up approach to analyse GHG emissions using large datasets of India's 'cost of cultivation survey' and the '19th livestock census' together with soil, climate and management data for each location. Mitigation measures and associated costs and benefits of adoption, derived from a variety of sources including the literature, stakeholder meetings and expert opinion, were presented in the form of Marginal Abatement Cost Curves (MACC). We estimated that by 2030, business-as-usual GHG emissions from the agricultural sector in India would be 515 Megatonne CO2 equivalent (MtCO2e) per year with a technical mitigation potential of 85.5 MtCO2e per year through adoption of various mitigation practices. About 80% of the technical mitigation potential could be achieved by adopting only cost-saving measures. Three mitigation options, i.e. efficient use of fertilizer, zero-tillage and rice-water management, could deliver more than 50% of the total technical abatement potential.

Greenhouse gas emissions and water footprints of typical dietary patterns in India.

Agriculture is a major contributor to India's environmental footprint, particularly through greenhouse gas (GHG) emissions from livestock and fresh water used for irrigation. These impacts are likely to increase in future as agriculture attempts to keep pace with India's growing population and changing dietary preferences. Within India there is considerable dietary variation, and this study therefore aimed to quantify the GHG emissions and water usage associated with distinct dietary patterns. Five distinct diets were identified from the Indian Migration Study - a large adult population sample in India - using finite mixture modelling. These were defined as: Rice & low diversity, Rice & fruit, Wheat & pulses, Wheat, rice & oils, Rice & meat. The GHG emissions of each dietary pattern were quantified based on a Life Cycle Assessment (LCA) approach, and water use was quantified using Water Footprint (WF) data. Mixed-effects regression models quantified differences in the environmental impacts of the dietary patterns. There was substantial variability between diets: the rice-based patterns had higher associated GHG emissions and green WFs, but the wheat-based patterns had higher blue WFs. Regression modelling showed that the Rice & meat pattern had the highest environmental impacts overall, with 0.77 (95% CI 0.64-0.89) kg CO2e/capita/day (31%) higher emissions, 536 (95% CI 449-623) L/capita/day (24%) higher green WF and 109 (95% CI 85.9-133) L/capita/day (19%) higher blue WF than the reference Rice & low diversity pattern. Diets in India are likely to become more diverse with rising incomes, moving away from patterns such as the Rice & low diversity diet. Patterns such as the Rice & meat diet may become more common, and the environmental consequences of such changes could be substantial given the size of India's population. As global environmental stress increases, agricultural and nutrition policies must recognise the environmental impacts of potential future dietary changes.

Greenhouse gas emissions from agricultural food production to supply Indian diets: Implications for climate change mitigation.

Agriculture is a major source of greenhouse gas (GHG) emissions globally. The growing global population is putting pressure on agricultural production systems that aim to secure food production while minimising GHG emissions. In this study, the GHG emissions associated with the production of major food commodities in India are calculated using the Cool Farm Tool. GHG emissions, based on farm management for major crops (including cereals like wheat and rice, pulses, potatoes, fruits and vegetables) and livestock-based products (milk, eggs, chicken and mutton meat), are quantified and compared. Livestock and rice production were found to be the main sources of GHG emissions in Indian agriculture with a country average of 5.65 kg CO2eq kg-1 rice, 45.54 kg CO2eq kg-1 mutton meat and 2.4 kg CO2eq kg-1 milk. Production of cereals (except rice), fruits and vegetables in India emits comparatively less GHGs with <1 kg CO2eq kg-1 product. These findings suggest that a shift towards dietary patterns with greater consumption of animal source foods could greatly increase GHG emissions from Indian agriculture. A range of mitigation options are available that could reduce emissions from current levels and may be compatible with increased future food production and consumption demands in India.

Systems approaches in global change and biogeochemistry research.

Systems approaches have great potential for application in predictive ecology. In this paper, we present a range of examples, where systems approaches are being developed and applied at a range of scales in the field of global change and biogeochemical cycling. Systems approaches range from Bayesian calibration techniques at plot scale, through data assimilation methods at regional to continental scales, to multi-disciplinary numerical model applications at country to global scales. We provide examples from a range of studies and show how these approaches are being used to address current topics in global change and biogeochemical research, such as the interaction between carbon and nitrogen cycles, terrestrial carbon feedbacks to climate change and the attribution of observed global changes to various drivers of change. We examine how transferable the methods and techniques might be to other areas of ecosystem science and ecology.

Clopidogrel plus long-term aspirin after femoro-popliteal stenting. The CLAFS project: 1- and 2-year results.

The aim of this study was to determine the patency rate after femoro-popliteal stenting followed by oral clopidogrel plus long-term aspirin. In a prospective trial, 31 patients with a total of 33 femoro-popliteal artery lesions (21 stenoses, 12 occlusions; 24 femoral, 9 popliteal) were treated with flexible tantalum stents after unsuccessful percutaneous transluminal angioplasty (PTA) preceded by local fibrinolysis in 5 of 12 patients with total occlusion. Post-interventionally, oral aspirin 100 mg was started simultaneously for the long term and was combined with an oral loading dose of 300 mg clopidogrel, followed by 75 mg clopidogrel daily for 28 days. Patients were followed for at least 12 months (maximum 34 months) by clinical examination, Doppler pressure measurement, color and duplex sonography, and angiography in case of suspicion of restenosis. In a retrospective analysis, the results were compared with those of historical groups of patients having received aspirin only (41 patients) or a long-term high-dose low molecular weight heparin (LMWH)+aspirin treatment (42 patients). Three small puncture aneurysms were treated successfully by conservative means and were categorized as minor bleeding complication. Cumulative primary patency rate (PPR) was 76 +/- 7.5% (1 year), and 70 +/- 9.6% (2 years) in the clopidogrel+aspirin group, thus being tendentiously better than in the aspirin-only group showing 75 +/- 4.6% (1 year), and 50 +/- 8.1% (2 years). Long-term high-dose LMWH+aspirin treatment showed 87 +/- 5.8% (1 year), and 72 +/- 9.1% (2 years), thus being superior to the other treatment regimes, with a statistically significant difference (p<0.05) between the LMWH+aspirin and the aspirin group. Clopidogrel plus aspirin is a safe medication regimen and may be effective in the prevention of early stent thrombosis. Mid- and long-term patency rate seems to be intermediate as compared with other therapeutic regimens. The LMWH+aspirin seems to be superior compared with CLAFS; however, randomized studies with larger patient numbers are recommended.