Review of Nationally Determined Contributions (NCD) of China from the perspective of food systems

Tek Sapkota (2023, [Documento de trabajo])

China is the largest emitter of greenhouse gases (GHG) and one of the countries most affected by climate change. China's food systems are a major contributor to climate change: in 2018, China's food systems emitted 1.09 billion tons of carbondioxide equivalent (CO2eq) GHGs, accounting for 8.2% of total national GHG emissions and 2% of global emissions. According to the Third National Communication (TNC) Report, in 2010, GHG emissions from energy, industrial processes, agriculture, and waste accounted for 78.6%, 12.3%, 7.9%, and 1.2% of total emissions, respectively, (excluding emissions from land use, land-use change and forestry (LULUCF). Total GHG emissions from the waste sector in 2010 were 132 Mt CO2 eq, with municipal solid waste landfills accounting for 56 Mt. The average temperature in China has risen by 1.1°C over the last century (1908–2007), while nationally averaged precipitation amounts have increased significantly over the last 50 years. The sea level and sea surface temperature have risen by 90 mm and 0.9°C respectively in the last 30 years. A regional climate model predicted an annual mean temperature increase of 1.3–2.1°C by 2020 (2.3–3.3°C by 2050), while another model predicted a 1–1.6°C temperature increase and a 3.3–3.7 percent increase in precipitation between 2011 and 2020, depending on the emissions scenario. By 2030, sea level rise along coastal areas could be 0.01–0.16 meters, increasing the likelihood of flooding and intensified storm surges and causing the degradation of wetlands, mangroves, and coral reefs. Addressing climate change is a common human cause, and China places a high value on combating climate change. Climate change has been incorporated into national economic and social development plans, with equal emphasis on mitigation and adaptation to climate change, including an updated Nationally Determined Contribution (NDC) in 2021. The following overarching targets are included in China's updated NDC: • Peaking carbon dioxide emissions “before 2030” and achieving carbon neutrality before 2060. • Lowering carbon intensity by “over 65%” by 2030 from the 2005 level. • Increasing forest stock volume by around 6 billion cubic meters in 2030 from the 2005 level. The targets have come from several commitments made at various events, while China has explained very well the process adopted to produce its third national communication report. An examination of China's NDC reveals that it has failed to establish quantifiable and measurable targets in the agricultural sectors. According to the analysis of the breakdown of food systems and their inclusion in the NDC, the majority of food system activities are poorly mentioned. China's interventions or ambitions in this sector have received very little attention. The adaptation component is mentioned in the NDC, but is not found to be sector-specific or comprehensive. A few studies have rated the Chinese NDC as insufficient, one of the reasons being its failure to list the breakdown of each sector's clear pathway to achieving its goals. China's NDC lacks quantified data on food system sub-sectors. Climate Action Trackers' "Insufficient" rating indicates that China's domestic target for 2030 requires significant improvements to be consistent with the Paris Agreement's target of 1.5°C temperature limit. Some efforts are being made: for example, scientists from the Institute of Environment and Sustainable Development in Agriculture, Chinese Academy of Agricultural Sciences (IEDA-CAAS) have developed methods for calculating GHG emissions from livestock and poultry farmers that have been published as an industrial standard by the Ministry of Agriculture and Rural Affairs, PRC (Prof Hongmin Dong, personal communication) but this still needs to be consolidated and linked to China’s NDC. The updated Nationally Determined Contributions fall short of quantifiable targets in agriculture and food systems as a whole, necessitating clear pathways. China's NDC is found to be heavily focused on a few sectors, including energy, transportation, and urban-rural development. The agricultural sectors' and food systems' targets are vague, and China's agrifood system has a large carbon footprint. As a result, China should focus on managing the food system (production, processing, transportation, and food waste management) to reduce carbon emissions. Furthermore, China should take additional measures to make its climate actions more comprehensive, quantifiable, and measurable, such as setting ambitious and clear targets for the agriculture sector, including activity-specific GHG-reduction pathways; prioritizing food waste and loss reduction and management; promoting sustainable livestock production and low carbon diets; reducing chemical pollution; minimizing the use of fossil fuel in the agri-system and focusing on developing green jobs, technological advancement and promoting climate-smart agriculture; promoting indigenous practices and locally led adaptation; restoring degraded agricultural soils and enhancing cooperation and private partnership. China should also prepare detailed NDC implementation plans including actions and the GHG reduction from conditional targets.

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA GREENHOUSE GAS EMISSIONS CLIMATE CHANGE FOOD SYSTEMS LAND USE CHANGE AGRICULTURE POLICIES DATA ANALYSIS FOOD WASTES

The input reduction principle of agroecology is wrong when it comes to mineral fertilizer use in sub-Saharan Africa

Gatien Falconnier Marc Corbeels Frédéric Baudron Antoine Couëdel leonard rusinamhodzi bernard vanlauwe Ken Giller (2023, [Artículo])

Can farmers in sub-Saharan Africa (SSA) boost crop yields and improve food availability without using more mineral fertilizer? This question has been at the center of lively debates among the civil society, policy-makers, and in academic editorials. Proponents of the “yes” answer have put forward the “input reduction” principle of agroecology, i.e. by relying on agrobiodiversity, recycling and better efficiency, agroecological practices such as the use of legumes and manure can increase crop productivity without the need for more mineral fertilizer. We reviewed decades of scientific literature on nutrient balances in SSA, biological nitrogen fixation of tropical legumes, manure production and use in smallholder farming systems, and the environmental impact of mineral fertilizer. Our analyses show that more mineral fertilizer is needed in SSA for five reasons: (i) the starting point in SSA is that agricultural production is “agroecological” by default, that is, very low mineral fertilizer use, widespread mixed crop-livestock systems and large crop diversity including legumes, but leading to poor soil fertility as a result of widespread soil nutrient mining, (ii) the nitrogen needs of crops cannot be adequately met solely through biological nitrogen fixation by legumes and recycling of animal manure, (iii) other nutrients like phosphorus and potassium need to be replaced continuously, (iv) mineral fertilizers, if used appropriately, cause little harm to the environment, and (v) reducing the use of mineral fertilizers would hamper productivity gains and contribute indirectly to agricultural expansion and to deforestation. Yet, the agroecological principles directly related to soil fertility—recycling, efficiency, diversity—remain key in improving soil health and nutrient-use efficiency, and are critical to sustaining crop productivity in the long run. We argue for a nuanced position that acknowledges the critical need for more mineral fertilizers in SSA, in combination with the use of agroecological practices and adequate policy support.

Manure Crop Yields Smallholder Farming Systems Environmental Hazards CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA BIOLOGICAL NITROGEN FIXATION LEGUMES NUTRIENT BALANCE SOIL FERTILITY AGROECOLOGY YIELD INCREASES LITERATURE REVIEWS

Agroecology can promote climate change adaptation outcomes without compromising yield in smallholder systems

Sieglinde Snapp Yodit Kebede Eva Wollenberg (2023, [Artículo])

A critical question is whether agroecology can promote climate change mitigation and adaptation outcomes without compromising food security. We assessed the outcomes of smallholder agricultural systems and practices in low- and middle-income countries (LMICs) against 35 mitigation, adaptation, and yield indicators by reviewing 50 articles with 77 cases of agroecological treatments relative to a baseline of conventional practices. Crop yields were higher for 63% of cases reporting yields. Crop diversity, income diversity, net income, reduced income variability, nutrient regulation, and reduced pest infestation, indicators of adaptative capacity, were associated with 70% or more of cases. Limited information on climate change mitigation, such as greenhouse gas emissions and carbon sequestration impacts, was available. Overall, the evidence indicates that use of organic nutrient sources, diversifying systems with legumes and integrated pest management lead to climate change adaptation in multiple contexts. Landscape mosaics, biological control (e.g., enhancement of beneficial organisms) and field sanitation measures do not yet have sufficient evidence based on this review. Widespread adoption of agroecological practices and system transformations shows promise to contribute to climate change services and food security in LMICs. Gaps in adaptation and mitigation strategies and areas for policy and research interventions are finally discussed.

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CLIMATE CHANGE CROPS FOOD SUPPLY GAS EMISSIONS GREENHOUSE GASES FARMING SYSTEMS AGROECOLOGY FOOD SECURITY LESS FAVOURED AREAS SMALLHOLDERS YIELDS NUTRIENTS BIOLOGICAL PEST CONTROL CARBON SEQUESTRATION LEGUMES

Satellite Earth Observation (EO) for agriculture

Gerald Blasch (2023, [Objeto de congreso])

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA MONITORING AGRICULTURE SATELLITE OBSERVATION EARTH OBSERVATION SATELLITES

High-throughput plot-level quantitative phenotyping using convolutional neural networks on very high-resolution satellite images

Francisco Pinto Matthew Paul Reynolds Robert Furbank (2024, [Artículo])

Deep Learning Object-Based Image Analysis Optical Imagery CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA AGRICULTURE IMAGE ANALYSIS PLANT BREEDING REMOTE SENSING MACHINE LEARNING

Big data, small explanatory and predictive power: Lessons from random forest modeling of on-farm yield variability and implications for data-driven agronomy

Martin van Ittersum (2023, [Artículo])

Context: Collection and analysis of large volumes of on-farm production data are widely seen as key to understanding yield variability among farmers and improving resource-use efficiency. Objective: The aim of this study was to assess the performance of statistical and machine learning methods to explain and predict crop yield across thousands of farmers’ fields in contrasting farming systems worldwide. Methods: A large database of 10,940 field-year combinations from three countries in different stages of agricultural intensification was analyzed. Random effects models were used to partition crop yield variability and random forest models were used to explain and predict crop yield within a cross-validation scheme with data re-sampling over space and time. Results: Yield variability in relative terms was smallest for wheat and barley in the Netherlands and for wheat in Ethiopia, intermediate for rice in the Philippines, and greatest for maize in Ethiopia. Random forest models comprising a total of 87 variables explained a maximum of 65 % of cereal yield variability in the Netherlands and less than 45 % of cereal yield variability in Ethiopia and in the Philippines. Crop management related variables were important to explain and predict cereal yields in Ethiopia, while predictive (i.e., known before the growing season) climatic variables and explanatory (i.e., known during or after the growing season) climatic variables were most important to explain and predict cereal yield variability in the Philippines and in the Netherlands, respectively. Finally, model cross-validation for regions or years not seen during model training reduced the R2 considerably for most crop x country combinations, while for wheat in the Netherlands this was model dependent. Conclusion: Big data from farmers’ fields is useful to explain on-farm yield variability to some extent, but not to predict it across time and space. Significance: The results call for moderate expectations towards big data and machine learning in agronomic studies, particularly for smallholder farms in the tropics where model performance was poorest independently of the variables considered and the cross-validation scheme used.

Model Accuracy Model Precision Linear Mixed Models CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA MACHINE LEARNING SUSTAINABLE INTENSIFICATION BIG DATA YIELDS MODELS AGRONOMY

Towards gender-inclusive innovation: Assessing local conditions for agricultural targeting

Diana E. Lopez Romain Frelat Lone Badstue (2022, [Artículo])

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA AGRICULTURE CLIMATE FEMALES GENDER HUMANS GENDER EQUALITY

Sustainability evaluation of contrasting milpa systems in the Yucatán Peninsula, Mexico

Santiago Lopez-Ridaura Tania Carolina Camacho Villa (2023, [Artículo])

The milpa agroecosystem is an intercropping of maize, beans, squash and other crops, developed in Mesoamerica, and its adoption is widely variable across climates and regions. An example of particular interest is the Yucatan Peninsula in Mexico, which holds highly diverse milpas, drawing on ancestral Mayan knowledge. Traditional milpas have been described as sustainable resource management models, based on long rotations within a slash-and-burn cycle in forest areas. Nevertheless, due to modernization and intensification processes, new variants of the approach have appeared. The objective of this study was to evaluate the sustainability of three milpa systems (traditional, continuous, and mechanized) in four case studies across the Peninsula, with emphasis on food self-sufficiency, social inclusion and adoption of innovations promoted by a development project. The Framework for the Evaluation of Agroecosystems using Indicators (MESMIS, for its Spanish acronym) was used for its flexible, participatory approach. A common group of indicators was developed despite regional differences between study cases, with a high level of farmer participation throughout the iterative process. The results show lower crop yields in traditional systems, but with lower inputs costs and pesticide use. In contrast, continuous milpas had higher value in terms of crop diversity, food security, social inclusion, and innovation adoption. Mechanized milpas had lower weed control costs. Profitability of cash crops and the proportion of forest were high in all systems. Highly adopted innovations across milpa types and study cases included spatial crop arrangement and the use of residues as mulches. However, most innovations are not adapted to local conditions, and do not address climate change. Further, women and youth participation is low, especially in traditional systems.

Milpa Intensification Processes Women and Youth Participation CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA SUSTAINABILITY INTERCROPPING FOOD SECURITY INNOVATION SOCIAL INCLUSION AGROECOSYSTEMS CASE STUDIES

Review of Nationally Determined Contributions (NCD) of Vietnam from the perspective of food systems

Tek Sapkota (2023, [Documento de trabajo])

Over the past decades, Vietnam has significantly progressed and has transformed from being a food-insecure nation to one of the world’s leading exporters in food commodities, and from one of the world’s poorest countries to a low-middle-income country. The agriculture sector is dominated by rice and plays a vital role in food security, employment, and foreign exchange. Vietnam submitted its updated Nationally Determined Contributions (NDC) in 2022 based on the NDC 2020. There is a significant increase in greenhouse gas (GHG) emission reduction, towards the long-term goals identified in Vietnam’s National Climate Change Strategy to 2025, and efforts are being made to fulfil the commitments made at COP26. The Agriculture Sector is the second-largest contributor of GHG emissions in Vietnam, accounting for 89.75 MtCO2eq, which was about 31.6 percent of total emissions in 2014. Rice cultivation is the biggest source of emissions in the agriculture sector, accounting for 49.35% of emissions from agriculture. The total GHG removal from Land Use, Land Use Change and Forestry (LULUCF) in 2014 was -37.54 MtCO2eq, of which the largest part was from the forest land sub-sector (35.61 MtCO2eq), followed by removal from croplands (7.31 MtCO2eq) (MONRE 2019).

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CLIMATE CHANGE GREENHOUSE GAS EMISSIONS FOOD SYSTEMS LAND USE CHANGE AGRICULTURE POLICIES DATA ANALYSIS

Review of Nationally Determined Contributions (NCD) of Colombia from the perspective of food systems

Tek Sapkota (2023, [Documento de trabajo])

Food is a vital component of Colombia's economy. The impact of climate change on agriculture and food security in the country is severe. The effects have resulted in decreased production and in the productivity of agricultural soil. Desertification processes are accelerating and intensifying. Colombia's government formally submitted its Nationally Determined Contribution (NDC) on December 29, 2020. This paper examines Colombia's NDC from the standpoint of the food system.

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CLIMATE CHANGE GREENHOUSE GAS EMISSIONS FOOD SYSTEMS LAND USE CHANGE AGRICULTURE POLICIES DATA ANALYSIS FOOD WASTES