The FAOSTAT database of greenhouse gas emissions from agriculture

Peer reviewedPublisher PD

A multi-approach software library for estimating crop suitability to environment

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Adapting agriculture to climate change

The strong trends in climate change already evident, the likelihood of further changes occurring, and the increasing scale of potential climate impacts give urgency to addressing agricultural adaptation more coherently. There are many potential adaptation options available for marginal change of existing agricultural systems, often variations of existing climate risk management. We show that implementation of these options is likely to have substantial benefits under moderate climate change for some cropping systems. However, there are limits to their effectiveness under more severe climate changes. Hence, more systemic changes in resource allocation need to be considered, such as targeted diversification of production systems and livelihoods. We argue that achieving increased adaptation action will necessitate integration of climate change-related issues with other risk factors, such as climate variability and market risk, and with other policy domains, such as sustainable development. Dealing with the many barriers to effective adaptation will require a comprehensive and dynamic policy approach covering a range of scales and issues, for example, from the understanding by farmers of change in risk profiles to the establishment of efficient markets that facilitate response strategies. Science, too, has to adapt. Multidisciplinary problems require multidisciplinary solutions, i.e., a focus on integrated rather than disciplinary science and a strengthening of the interface with decision makers. A crucial component of this approach is the implementation of adaptation assessment frameworks that are relevant, robust, and easily operated by all stakeholders, practitioners, policymakers, and scientists

A new cropland area database by country circa 2020

We describe a new dataset of cropland area circa the year 2020, with global coverage and with data for 221 countries and territories and 34 regional aggregates. Data are generated from geospatial information on the agreement–disagreement characteristics of six open-access high-resolution cropland maps derived from remote sensing. The cropland area mapping (CAM) aggregation dataset provides information on (i) mean cropland area and its uncertainty, (ii) cropland area by six distinct cropland agreement classes, and (iii) cropland area by specific combinations of underlying land cover product. The results indicated that world cropland area is 1500 ± 400 Mha (mean and 95 % confidence interval), with a relative uncertainty of 25 % that increased across regions. It was 50 % in Central Asia (40 ± 20 Mha), South America (180 ± 80 Mha), and Southern Europe (40 ± 20 Mha) and up to 40 % in Australia and New Zealand (50 ± 20 Mha), Southeastern Asia (80 ± 30 Mha), and Southern Africa (16 ± 6 Mha). Conversely, cropland area was estimated with better precision, i.e., smaller uncertainties in the range 10 %–25 % in Southern Asia (230 ± 30 Mha), Northern America (200 ± 40 Mha), Northern Africa (40 ± 10 Mha), and Eastern Europe and Western Europe (40 ± 10 Mha). The new data can be used to investigate the coherence of information across the six underlying products, as well as to explore important disagreement features. Overall, 70 % or more of the estimated mean cropland area globally and by region corresponded to good agreement of underlying land cover maps – four or more. Conversely, in Africa cropland area estimates found significant disagreement, highlighting mapping difficulties in complex landscapes. Finally, the new cropland area data were consistent with FAOSTAT (FAO, 2023) in 15 out of 18 world regions, as well as for 114 out of 182 countries with a cropland area above 10 kha. By helping to highlight features of cropland characteristics and underlying causes for agreement–disagreement across land cover products, the CAM aggregation dataset may be used as a reference for the quality of country statistics and may help guide future mapping efforts towards improved agricultural monitoring. Data are publicly available at https://doi.org/10.5281/zenodo.7987515 (Tubiello et al., 2023a).</p

Data-driven estimates of global nitrous oxide emissions from croplands

Croplands are the single largest anthropogenic source of nitrous oxide (N2O) globally, yet their estimates remain difficult to verify when using Tier 1 and 3 methods of the Intergovernmental Panel on Climate Change (IPCC). Here, we re-evaluate global cropland-N2O emissions in 1961–2014, using N-rate-dependent emission factors (EFs) upscaled from 1206 field observations in 180 global distributed sites and high-resolution N inputs disaggregated from sub-national surveys covering 15593 administrative units. Our results confirm IPCC Tier 1 default EFs for upland crops in 1990–2014, but give a ∼15% lower EF in 1961–1989 and a ∼67% larger EF for paddy rice over the full period. Associated emissions (0.82 ± 0.34 Tg N yr–1) are probably one-quarter lower than IPCC Tier 1 global inventories but close to Tier 3 estimates. The use of survey-based gridded N-input data contributes 58% of this emission reduction, the rest being explained by the use of observation-based non-linear EFs. We conclude that upscaling N2O emissions from site-level observations to global croplands provides a new benchmark for constraining IPCC Tier 1 and 3 methods. The detailed spatial distribution of emission data is expected to inform advancement towards more realistic and effective mitigation pathways

Chapter 11 - Agriculture, forestry and other land use (AFOLU)

Agriculture, Forestry, and Other Land Use (AFOLU) plays a central role for food security and sustainable development. Plants take up carbon dioxide (CO2) from the atmosphere and nitrogen (N) from the soil when they grow, re-distributing it among different pools, including above and below-ground living biomass, dead residues, and soil organic matter. The CO2 and other non-CO2 greenhouse gases (GHG), largely methane (CH4) and nitrous oxide (N2O), are in turn released to the atmosphere by plant respiration, by decomposition of dead plant biomass and soil organic matter, and by combustion. Anthropogenic land-use activities (e.g., management of croplands, forests, grasslands, wetlands), and changes in land use / cover (e.g., conversion of forest lands and grasslands to cropland and pasture, afforestation) cause changes superimposed on these natural fluxes. AFOLU activities lead to both sources of CO2 (e.g., deforestation, peatland drainage) and sinks of CO2 (e.g., afforestation, management for soil carbon sequestration), and to non-CO2 emissions primarily from agriculture (e.g., CH4 from livestock and rice cultivation, N2O from manure storage and agricultural soils and biomass burning. The main mitigation options within AFOLU involve one or more of three strategies: reduction / prevention of emissions to the atmosphere by conserving existing carbon pools in soils or vegetation that would otherwise be lost or by reducing emissions of CH4 and N2O; sequestration - enhancing the uptake of carbon in terrestrial reservoirs, and thereby removing CO2 from the atmosphere; and reducing CO2 emissions by substitution of biological products for fossil fuels or energy-intensive products. Demand-side options (e.g., by lifestyle changes, reducing losses and wastes of food, changes in human diet, changes in wood consumption), though known to be difficult to implement, may also play a role. Land is the critical resource for the AFOLU sector and it provides food and fodder to feed the Earth's population of ~7 billion, and fibre and fuel for a variety of purposes. It provides livelihoods for billions of people worldwide. It is finite and provides a multitude of goods and ecosystem services that are fundamental to human well-being. Human economies and quality of life are directly dependent on the services and the resources provided by land. Figure 11.1 shows the many provisioning, regulating, cultural and supporting services provided by land, of which climate regulation is just one. Implementing mitigation options in the AFOLU sector may potentially affect other services provided by land in positive or negative ways. In the Intergovernmental Panel on Climate Change (IPCC) Second Assessment Report (SAR) and in the IPCC Fourth Assessment Report (AR4), agricultural and forestry mitigation were dealt with in separate chapters. In the IPCC Third Assessment Report (TAR), there were no separate sectoral chapters on either agriculture or forestry. In the IPCC Fifth Assessment Report (AR5), for the first time, the vast majority of the terrestrial land surface, comprising agriculture, forestry and other land use (AFOLU), is considered together in a single chapter, though settlements (which are important, with urban areas forecasted to triple in size from 2000 global extent by 2030), are dealt with in Chapter 12. This approach ensures that all land-based mitigation options can be considered together; it minimizes the risk of double counting or inconsistent treatment (e.g., different assumptions about available land) between different land categories, and allows the consideration of systemic feedbacks between mitigation options related to the land surface. Considering AFOLU in a single chapter allows phenomena common across land-use types, such as competition for land and water, co-benefits, adverse side-effects and interactions between mitigation and adaptation to be considered consistently. The complex nature of land presents a unique range of barriers and opportunities, and policies to promote mitigation in the AFOLU sector need to take account of this complexity. In this chapter, we consider the competing uses of land for mitigation and for providing other services. Unlike the chapters on agriculture and forestry in AR4, impacts of sourcing bioenergy from the AFOLU sector are considered explicitly in a dedicated appendix. Also new to this assessment is the explicit consideration of food / dietary demand-side options for GHG mitigation in the AFOLU sector, and some consideration of freshwater fisheries and aquaculture, which may compete with the agriculture and forestry sectors, mainly through their requirements for land and / or water, and indirectly, by providing fish and other products to the same markets as animal husbandry. This chapter deals with AFOLU in an integrated way with respect to the underlying scenario projections of population growth, economic growth, dietary change, land-use change (LUC), and cost of mitigation. We draw evidence from both "bottom-up" studies that estimate mitigation potentials at small scales or for individual options or technologies and then scale up, and multi-sectoral "top-down" studies that consider AFOLU as just one component of a total multi-sector system response. In this chapter, we provide updates on emissions trends and changes in drivers and pressures in the AFOLU sector, describe the practices available in the AFOLU sector, and provide refined estimates of mitigation costs and potentials for the AFOLU sector, by synthesising studies that have become available since AR4. We conclude the chapter by identifying gaps in knowledge and data, providing a selection of Frequently Asked Questions, and presenting an Appendix on bioenergy to update the IPCC Special Report on Renewable Energy Sources and Climate Change Mitigation (SRREN)

Brazil's agricultural land, cropping frequency and second crop area: FAOSTAT statistics and new estimates.

Resumo: Uma representação acurada do território é crucial para uma avaliação adequada da sustentabilidade da produção de alimentos e bioenergia. No Brasil, três culturas com ambos os usos (soja, milho e cana) ocupam 3/4 da área agrícola do país. A área de uso agropecuário da terra, a frequência de cultivo e a área de cultivo na segunda safra são parâmetros essenciais para um grande número de modelos de uso da terra. Entretanto, os autores detectaram inconsistências nas estimativas da FAOSTAT e da literatura quanto a esses parâmetros. O objetivo deste trabalho é apresentar os resultados de uma iniciativa conjunta entre a Embrapa e a FAO para atualizar esses parâmetros com base em estatísticas oficiais. A atualização dos dados da FAOSTAT levou a uma mudança na área de agricultura e pastagem do Brasil para 63 e 172 Mha em 2016, respectivamente, 28% e 12% menores do que os valores anteriores. Considerando isso, a frequência de cultivo (área colhida sobre área de uso da terra) no Brasil é maior que 1.2, que resulta 30% superior às estimativas atualmente presentes na literatura e à média global. A área de segunda safra em 2017 pode ter alcançado 16 Mha, um aumento de 92% desde 2006. Em 2017, isso representava 21% da área total colhida no país, sendo composta principalmente de milho (68%), trigo (13%) e feijão (6%). Os novos dados têm importantes repercussões para modelos de uso da terra e políticas públicas para a promoção de uma agricultura e bioenergia sustentáveis. -- Abstract: Accurate territory representation plays crucial role in proper food and crop-based bioenergy sustainability evaluation processes. Three crops used for both purposes (soybean, corn and sugarcane) account for 3/4 of croplands in Brazil. Agricultural land, cropping frequency and second crop area are essential parameters for a variety of land-use models. However, the authors of the current study have identified inconsistencies in FAOSTAT and in literature estimates on them. The aim of the current study is to present the results of a joint effort carried out by Embrapa and FAO in order to update those parameters with verified official records. FAOSTAT's updated estimates show that cropland and pasture areas in Brazil back in 2016 covered 63 Mha and 172 Mha, respectively, and these numbers were 28% and 12% lower than previous figures for the same year. Accordingly, cropping frequency (i.e., ratio of harvested area / cropland) in Brazil is higher than 1.2, which is 30% higher than both the currently available estimates and the global average. Second crop area in 2017 may have reached 16 Mha, a 92% increase since 2006. In 2017, it accounted for 21% of total harvested area in the country, which mostly comprised corn (68%), wheat (13%) and bean (6%). The new data presented herein have important repercussions on land-use models and policy design to promote sustainable agriculture and bioenergy production

The impacts of increased heat stress events on wheat yield under climate change in China

China is the largest wheat producing country in the world. Wheat is one of the two major staple cereals consumed in the country and about 60% of Chinese population eats the grain daily. To safeguard the production of this important crop, about 85% of wheat areas in the country are under irrigation or high rainfall conditions. However, wheat production in the future will be challenged by the increasing occurrence and magnitude of adverse and extreme weather events. In this paper, we present an analysis that combines outputs from a wide range of General Circulation Models (GCMs) with observational data to produce more detailed projections of local climate suitable for assessing the impact of increasing heat stress events on wheat yield. We run the assessment at 36 representative sites in China using the crop growth model CSM-CropSim Wheat of DSSAT 4.5. The simulations based on historical data show that this model is suitable for quantifying yield damages caused by heat stress. In comparison with the observations of baseline 1996-2005, our simulations for the future indicate that by 2100, the projected increases in heat stress would lead to an ensemble-mean yield reduction of –7.1% (with a probability of 80%) and –17.5% (with a probability of 96%) for winter wheat and spring wheat, respectively, under the irrigated condition. Although such losses can be fully compensated by CO2 fertilization effect as parameterized in DSSAT 4.5, a great caution is needed in interpreting this fertilization effect because existing crop dynamic models are unable to incorporate the effect of CO2 acclimation (the growth enhancing effect decreases over time) and other offsetting forces