International Center for Tropical Agriculture

We developed interpolated climate surfaces for global land areas (excluding Antarctica) at a spatial resolution of 30 arc s (often referred to as 1-km spatial resolution). The climate elements considered were monthly precipitation and mean, minimum, and maximum temperature. Input data were gathered from a variety of sources and, where possible, were restricted to records from the 1950–2000 period. We used the thin-plate smoothing spline algorithm implemented in the ANUSPLIN package for interpolation, using latitude, longitude, and elevation as independent variables. We quantified uncertainty arising from the input data and the interpolation by mapping weather station density, elevation bias in the weather stations, and elevation variation within grid cells and through data partitioning and cross validation. Elevation bias tended to be negative (stations lower than expected) at high latitudes but positive in the tropics. Uncertainty is highest in mountainous and in poorly sampled areas. Data partitioning showed high uncertainty of the surfaces on isolated islands, e.g. in the Pacific. Aggregating the elevation and climate data to 10 arc min resolution showed an enormous variation within grid cells, illustrating the value of high-resolution surfaces. A comparison with an existing data set at 10 arc min resolution showed overall agreement, but with significant variation in some regions. A comparison with two high-resolution data sets for the United States also identified areas with large local differences, particularly in mountainous areas. Compared to previous global climatologies, ours has the following advantages: the data are at a higher spatial resolution (400 times greater or more); more weather station records were used; improved elevation data were used; and more information about spatial patterns of uncertainty in the data is available. Owing to the overall low density of available climate stations, our surfaces do not capture of all variation that may occur at a resolution of 1 km, particularly of precipitation in mountainous areas. In future work, such variation might be captured through knowledge-based methods and inclusion of additional co-variates, particularly layers obtained through remote sensing. Copyright © 2005 Royal Meteorological Society.

Sampling and analysis or visual examination of soil to assess its status and use potential is widely practiced from plot to national scales. However, the choice of relevant soil attributes and interpretation of measurements are not straightforward, because of the complexity and site-specificity of soils, legacy effects of previous land use, and trade-offs between ecosystem services. Here we review soil quality and related concepts, in terms of definition, assessment approaches, and indicator selection and interpretation. We identify the most frequently used soil quality indicators under agricultural land use. We find that explicit evaluation of soil quality with respect to specific soil threats, soil functions and ecosystem services has rarely been implemented, and few approaches provide clear interpretation schemes of measured indicator values. This limits their adoption by land managers as well as policy. We also consider novel indicators that address currently neglected though important soil properties and processes, and we list the crucial steps in the development of a soil quality assessment procedure that is scientifically sound and supports management and policy decisions that account for the multi-functionality of soil. This requires the involvement of the pertinent actors, stakeholders and end-users to a much larger degree than practiced to date.

Food systems contribute 19%–29% of global anthropogenic greenhouse gas (GHG) emissions, releasing 9,800–16,900 megatonnes of carbon dioxide equivalent (MtCO 2 e) in 2008. Agricultural production, including indirect emissions associated with land-cover change, contributes 80%–86% of total food system emissions, with significant regional variation. The impacts of global climate change on food systems are expected to be widespread, complex, geographically and temporally variable, and profoundly influenced by socioeconomic conditions. Historical statistical studies and integrated assessment models provide evidence that climate change will affect agricultural yields and earnings, food prices, reliability of delivery, food quality, and, notably, food safety. Low-income producers and consumers of food will be more vulnerable to climate change owing to their comparatively limited ability to invest in adaptive institutions and technologies under increasing climatic risks. Some synergies among food security, adaptation, and mitigation are feasible. But promising interventions, such as agricultural intensification or reductions in waste, will require careful management to distribute costs and benefits effectively.

Summary Biodiversity is responsible for the provision of many ecosystem services; human well‐being is based on these services, and consequently on biodiversity. In soil, earthworms represent the largest component of the animal biomass and are commonly termed ‘ecosystem engineers’. This review considers the contribution of earthworms to ecosystem services through pedogenesis, development of soil structure, water regulation, nutrient cycling, primary production, climate regulation, pollution remediation and cultural services. Although there has been much research into the role of earthworms in soil ecology, this review demonstrates substantial gaps in our knowledge related in particular to difficulties in identifying the effects of species, land use and climate. The review aims to assist people involved in all aspects of land management, including conservation, agriculture, mining or other industries, to obtain a broad knowledge of earthworms and ecosystem services.

The narrowing of diversity in crop species contributing to the world's food supplies has been considered a potential threat to food security. However, changes in this diversity have not been quantified globally. We assess trends over the past 50 y in the richness, abundance, and composition of crop species in national food supplies worldwide. Over this period, national per capita food supplies expanded in total quantities of food calories, protein, fat, and weight, with increased proportions of those quantities sourcing from energy-dense foods. At the same time the number of measured crop commodities contributing to national food supplies increased, the relative contribution of these commodities within these supplies became more even, and the dominance of the most significant commodities decreased. As a consequence, national food supplies worldwide became more similar in composition, correlated particularly with an increased supply of a number of globally important cereal and oil crops, and a decline of other cereal, oil, and starchy root species. The increase in homogeneity worldwide portends the establishment of a global standard food supply, which is relatively species-rich in regard to measured crops at the national level, but species-poor globally. These changes in food supplies heighten interdependence among countries in regard to availability and access to these food sources and the genetic resources supporting their production, and give further urgency to nutrition development priorities aimed at bolstering food security.

The objective of this review is to explore and discuss the concept of local food system resilience in light of the disruptions brought to those systems by the 2020 COVID-19 pandemic. The discussion, which focuses on low and middle income countries, considers also the other shocks and stressors that generally affect local food systems and their actors in those countries (weather-related, economic, political or social disturbances). The review of existing (mainly grey or media-based) accounts on COVID-19 suggests that, with the exception of those who lost members of their family to the virus, as per June 2020 the main impact of the pandemic derives mainly from the lockdown and mobility restrictions imposed by national/local governments, and the consequence that the subsequent loss of income and purchasing power has on people's food security, in particular the poor. The paper then uses the most prominent advances made recently in the literature on household resilience in the context of food security and humanitarian crises to identify a series of lessons that can be used to improve our understanding of food system resilience and its link to food security in the context of the COVID-19 crisis and other shocks. Those lessons include principles about the measurement of food system resilience and suggestions about the types of interventions that could potentially strengthen the abilities of actors (including policy makers) to respond more appropriately to adverse events affecting food systems in the future.

The Digital Surface Model that has been derived from the February 2000 Shuttle Radar Topography Mission (SRTM) has been one of the most important publicly available new spatial datasets in recent years. However, the ‘finished’ version of the data still contains data voids (some 836,000 km2) – and other anomalies - that prevents immediate use for a wide range of applications. These voids can be filled using a range of interpolation algorithms in conjunction with other sources of elevation data, but there is little guidance on the most appropriate void filling method. This paper describes; (i) a methodology to fill voids using a variety of methods, (ii) a methodology to determine the most appropriate void filling algorithms using a classification of the voids based on their size and a typology of their surrounding terrain; and (iii) the classification of the most appropriate algorithm to each of the 3,339,913 voids in the SRTM data. Based on a sample of 1,304 artificial but realistic voids across six terrain types and eight void size classes, we found that the choice of void filling algorithm is dependent on both the size and terrain type of the void. Contrary to some previous findings, the best methods can be generalised as: Kriging or Inverse Distance Weighting interpolation for small and medium size voids in relatively flat low-lying areas; Spline interpolation for small and medium sized voids in high altitude and dissected terrain; Triangular Irregular Network or Inverse Distance Weighting interpolation for large voids in very flat areas, and an advanced Spline Method (ANUDEM) for large voids in other terrains.

Farmers in mixed crop-livestock systems produce about half of the world's food. In small holdings around the world, livestock are reared mostly on grass, browse, and nonfood biomass from maize, millet, rice, and sorghum crops and in their turn supply manure and traction for future crops. Animals act as insurance against hard times and supply farmers with a source of regular income from sales of milk, eggs, and other products. Thus, faced with population growth and climate change, small-holder farmers should be the first target for policies to intensify production by carefully managed inputs of fertilizer, water, and feed to minimize waste and environmental impact, supported by improved access to markets, new varieties, and technologies.

Abstract Black carbon (BC) is an important pool of the global C cycle, because it cycles much more slowly than others and may even be managed for C sequestration. Using stable isotope techniques, we investigated the fate of BC applied to a savanna Oxisol in Colombia at rates of 0, 11.6, 23.2 and 116.1 t BC ha −1 , as well as its effect on non‐BC soil organic C. During the rainy seasons of 2005 and 2006, soil respiration was measured using soda lime traps, particulate and dissolved organic C (POC and DOC) moving by saturated flow was sampled continuously at 0.15 and 0.3 m, and soil was sampled to 2.0 m. Black C was found below the application depth of 0–0.1 m in the 0.15–0.3 m depth interval, with migration rates of 52.4±14.5, 51.8±18.5 and 378.7±196.9 kg C ha −1 yr −1 (±SE) where 11.6, 23.2 and 116.1 t BC ha −1 , respectively, had been applied. Over 2 years after application, 2.2% of BC applied at 23.2 t BC ha −1 was lost by respiration, and an even smaller fraction of 1% was mobilized by percolating water. Carbon from BC moved to a greater extent as DOC than POC. The largest flux of BC from the field (20–53% of applied BC) was not accounted for by our measurements and is assumed to have occurred by surface runoff during intense rain events. Black C caused a 189% increase in aboveground biomass production measured 5 months after application (2.4–4.5 t additional dry biomass ha −1 where BC was applied), and this resulted in greater amounts of non‐BC being respired, leached and found in soil for the duration of the experiment. These increases can be quantitatively explained by estimates of greater belowground net primary productivity with BC addition.

ABSTRACT Micronutrient malnutrition affects over 2 billion people in the developing world. Iron (Fe) deficiency alone affects >47% of all preschool aged children globally, often leading to impaired physical growth, mental development, and learning capacity. Zinc (Zn) deficiency, like iron, is thought to affect billions of people, hampering growth and development, and destroying immune systems. In many micronutrient‐deficient regions, wheat is the dominant staple food making up >50% of the diet. Biofortification, or harnessing the powers of plant breeding to improve the nutritional quality of foods, is a new approach being used to improve the nutrient content of a variety of staple crops. Durum wheat in particular has been quite responsive to breeding for nutritional quality by making full use of the genetic diversity of Fe and Zn concentrations in wild and synthetic parents. Micronutrient concentration and genetic diversity has been well explored under the HarvestPlus biofortification research program, and very positive associations have been confirmed between grain concentrations of protein, Zn, and Fe. Yet some work remains to adequately explain genetic control and molecular mechanisms affecting the accumulation of Zn and Fe in grain. Further, evidence suggests that nitrogen (N) nutritional status of plants can have a positive impact on root uptake and the deposition of micronutrients in seed. Extensive research has been completed on the role of Zn fertilizers in increasing the Zn density of grain, suggesting that where fertilizers are available, making full use of Zn fertilizers can provide an immediate and effective option to increase grain Zn concentration, and productivity in particular, under soil conditions with severe Zn deficiency.

There is growing international interest in better managing soils to increase soil organic carbon (SOC) content to contribute to climate change mitigation, to enhance resilience to climate change and to underpin food security, through initiatives such as international '4p1000' initiative and the FAO's Global assessment of SOC sequestration potential (GSOCseq) programme. Since SOC content of soils cannot be easily measured, a key barrier to implementing programmes to increase SOC at large scale, is the need for credible and reliable measurement/monitoring, reporting and verification (MRV) platforms, both for national reporting and for emissions trading. Without such platforms, investments could be considered risky. In this paper, we review methods and challenges of measuring SOC change directly in soils, before examining some recent novel developments that show promise for quantifying SOC. We describe how repeat soil surveys are used to estimate changes in SOC over time, and how long-term experiments and space-for-time substitution sites can serve as sources of knowledge and can be used to test models, and as potential benchmark sites in global frameworks to estimate SOC change. We briefly consider models that can be used to simulate and project change in SOC and examine the MRV platforms for SOC change already in use in various countries/regions. In the final section, we bring together the various components described in this review, to describe a new vision for a global framework for MRV of SOC change, to support national and international initiatives seeking to effect change in the way we manage our soils.

The concept of food system has gained prominence in recent years amongst both scholars and policy-makers. Experts from diverse disciplines and backgrounds have in particular discussed the nature and origin of the “unsustainability” of our modern food systems. These efforts tend, however, to be framed within distinctive disciplinary narratives. In this paper we propose to explore these narratives and to shed light on the explicit -or implicit- epistemological assumptions, mental models, and disciplinary paradigms that underpin those. The analysis indicates that different views and interpretations prevail amongst experts about the nature of the “crisis”, and consequently about the research and priorities needed to “fix” the problem. We then explore how sustainability is included in these different narratives and the link to the question of healthy diets. The analysis reveals that the concept of sustainability, although widely used by all the different communities of practice, remains poorly defined, and applied in different ways and usually based on a relatively narrow interpretation. In so doing we argue that current attempts to equate or subsume healthy diets within sustainability in the context of food system may be misleading and need to be challenged. We stress that trade-offs between different dimensions of food system sustainability are unavoidable and need to be navigated in an explicit manner when developing or implementing sustainable food system initiatives. Building on this overall analysis, a framework structured around several entry points including outcomes, core activities, trade-offs and feedbacks is then proposed, which allows to identify key elements necessary to support the transition toward sustainable food systems.

Abstract The increasing pressure on agricultural production systems to achieve global food security and prevent environmental degradation necessitates a transition towards more sustainable practices. The purpose of this scoping review is to understand how the incentives offered to farmers motivate the adoption of sustainable agricultural practices and, ultimately, how and whether they result in measurable outcomes. To this end, this scoping review examines the evidence of nearly 18,000 papers on whether incentive-based programmes lead to the adoption of sustainable practices and their effect on environmental, economic and productivity outcomes. We find that independent of the incentive type, programmes linked to short-term economic benefit have a higher adoption rate than those aimed solely at providing an ecological service. In the long run, one of the strongest motivations for farmers to adopt sustainable practices is perceived benefits for either their farms, the environment or both. Beyond this, the importance of technical assistance and extension services in promoting sustainable practices emerges strongly from this scoping review. Finally, we find that policy instruments are more effective if their design considers the characteristics of the target population, and the associated trade-offs between economic, environmental and social outcomes.

Climate change will have far-reaching impacts on crop, livestock and fisheries production, and will change the prevalence of crop pests. Many of these impacts are already measurable. Climate impact studies are dominated by those on crop yields despite the limitations of climate-crop modelling, with very little attention paid to more systems components of cropping, let alone other dimensions of food security. Given the serious threats to food security, attention should shift to an action-oriented research agenda, where we see four key challenges: (a) changing the culture of research; (b) deriving stakeholder-driven portfolios of options for farmers, communities and countries; (c) ensuring that adaptation actions are relevant to those most vulnerable to climate change; (d) combining adaptation and mitigation.

The dynamics of deforestation in the Brazilian Amazon are complex. A growing debate considers the extent to which deforestation is a result of the expansion of the Brazilian soy industry. Most recent analyses suggest that deforestation is driven by the expansion of cattle ranching, rather than soy. Soy seems to be replacing previously deforested land and/or land previously under pasture. In this study, we use municipality-level statistics on agricultural and deforested areas across the Legal Amazon from 2000 to 2006 to examine the spatial patterns and statistical relationships between deforestation and changes in pasture and soybean areas. Our results support previous studies that showed that deforestation is predominantly a result of pasture expansion. However, we also find support for the hypothesis that an increase of soy in Mato Grosso has displaced pasture further north, leading to deforestation elsewhere. Although not conclusive, our findings suggest that the debate surrounding the drivers of Amazon deforestation is not over, and that indirect causal links between soy and deforestation may exist that need further exploration. Future research should examine more closely how interlinkages between land area, prices, and policies influence the relationship between soy and deforestation, in order to make a conclusive case for 'displacement deforestation'.

ABSTRACT Micronutrient malnutrition, the so‐called hidden hunger, affects more than one‐half of the world's population, especially women and preschool children in developing countries. Despite past progress in controlling micronutrient decencies through supplementation and food fortification, new approaches are needed to expand the reach of food‐based interventions. Biofortification, a new approach that relies on conventional plant breeding and modern biotechnology to increase the micronutrient density of staple crops, holds great promise for improving the nutritional status and health of poor populations in both rural and urban areas of the developing world. HarvestPlus, a research program implemented with the international research institutes of the CGIAR, targets a multitude of crops that are a regular part of the staple‐based diets of the poor and breeds them to be rich in iron, zinc, and provitamin A. This paper emphasizes the need for interdisciplinary research and addresses the key research issues and methodological considerations for success. The major activities to be undertaken are broadly grouped into research related to nutrition research and impact analysis, and research considerations for delivering biofortified crops to end‐users effectively. The paper places particular emphasis on the activities of the plant breeding and genetics component of this multidisciplinary program. The authors argue that for biofortification to succeed, product profiles developed by plant breeders must be driven by nutrition research and impact objectives and that nutrition research must understand that the probability of success for biofortified crops increases substantially when product concepts consider farmer adoption and, hence, agronomic superiority.

Genomic Selection (GS) is a new breeding method in which genome-wide markers are used to predict the breeding value of individuals in a breeding population. GS has been shown to improve breeding efficiency in dairy cattle and several crop plant species, and here we evaluate for the first time its efficacy for breeding inbred lines of rice. We performed a genome-wide association study (GWAS) in conjunction with five-fold GS cross-validation on a population of 363 elite breeding lines from the International Rice Research Institute's (IRRI) irrigated rice breeding program and herein report the GS results. The population was genotyped with 73,147 markers using genotyping-by-sequencing. The training population, statistical method used to build the GS model, number of markers, and trait were varied to determine their effect on prediction accuracy. For all three traits, genomic prediction models outperformed prediction based on pedigree records alone. Prediction accuracies ranged from 0.31 and 0.34 for grain yield and plant height to 0.63 for flowering time. Analyses using subsets of the full marker set suggest that using one marker every 0.2 cM is sufficient for genomic selection in this collection of rice breeding materials. RR-BLUP was the best performing statistical method for grain yield where no large effect QTL were detected by GWAS, while for flowering time, where a single very large effect QTL was detected, the non-GS multiple linear regression method outperformed GS models. For plant height, in which four mid-sized QTL were identified by GWAS, random forest produced the most consistently accurate GS models. Our results suggest that GS, informed by GWAS interpretations of genetic architecture and population structure, could become an effective tool for increasing the efficiency of rice breeding as the costs of genotyping continue to decline.

Abstract Increased atmospheric nitrogen (N) deposition is known to reduce plant diversity in natural and semi‐natural ecosystems, yet our understanding of these impacts comes almost entirely from studies in northern Europe and North America. Currently, we lack an understanding of the threat of N deposition to biodiversity at the global scale. In particular, rates of N deposition within the newly defined 34 world biodiversity hotspots, to which 50% of the world's floristic diversity is restricted, has not been quantified previously. Using output from global chemistry transport models, here we provide the first estimates of recent (mid‐1990s) and future (2050) rates and distributions of N deposition within biodiversity hotspots. Our analysis shows that the average deposition rate across these areas was 50% greater than the global terrestrial average in the mid‐1990s and could more than double by 2050, with 33 of 34 hotspots receiving greater N deposition in 2050 compared with 1990. By this time, 17 hotspots could have between 10% and 100% of their area receiving greater than 15 kg N ha −1 yr −1 , a rate exceeding critical loads set for many sensitive European ecosystems. Average deposition in four hotspots is predicted to be greater than 20 kg N ha −1 yr −1 . This elevated N deposition within areas of high plant diversity and endemism may exacerbate significantly the global threat of N deposition to world floristic diversity. Overall, we highlight the need for a greater global approach to assessing the impacts of N deposition.

Coffee has proven to be highly sensitive to climate change. Because coffee plantations have a lifespan of about thirty years, the likely effects of future climates are already a concern. Forward-looking research on adaptation is therefore in high demand across the entire supply chain. In this paper we seek to project current and future climate suitability for coffee production (Coffea arabica and Coffea canephora) on a global scale. We used machine learning algorithms to derive functions of climatic suitability from a database of geo-referenced production locations. Use of several parameter combinations enhances the robustness of our analysis. The resulting multi-model ensemble suggests that higher temperatures may reduce yields of C. arabica, while C. canephora could suffer from increasing variability of intra-seasonal temperatures. Climate change will reduce the global area suitable for coffee by about 50 % across emission scenarios. Impacts are highest at low latitudes and low altitudes. Impacts at higher altitudes and higher latitudes are still negative but less pronounced. The world’s dominant production regions in Brazil and Vietnam may experience substantial reductions in area available for coffee. Some regions in East Africa and Asia may become more suitable, but these are partially in forested areas, which could pose a challenge to mitigation efforts.

The ‘sustainable intensification’ (SI) approach and ‘climate-smart agriculture’ (CSA) are highly complementary. SI is an essential means of adapting to climate change, also resulting in lower emissions per unit of output. With its emphasis on improving risk management, information flows and local institutions to support adaptive capacity, CSA provides the foundations for incentivizing and enabling intensification. But adaptation requires going beyond a narrow intensification lens to include diversified farming systems, local adaptation planning, building responsive governance systems, enhancing leadership skills, and building asset diversity. While SI and CSA are crucial for global food and nutritional security, they are only part of a multi-pronged approach, that includes reducing consumption and waste, building social safety nets, facilitating trade, and enhancing diets.