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Nutrient budgets help to identify the excess or insufficient use of fertilizers and other nutrient sources in agriculture. They allow for the calculation of indicators, such as the nutrient balance (surplus if positive or deficit if negative) and nutrient use efficiency, that help to monitor agricultural productivity and sustainability across the world. We present a global database of country-level budget estimates for nitrogen (N), phosphorus (P) and potassium (K) on cropland. The database, disseminated in FAOSTAT, is meant to provide a global reference, synthesizing and continuously updating the state of the art on this topic. The database covers 205 countries and territories, as well as regional and global aggregates, for the period from 1961 to 2020. Results highlight the wide range in nutrient use and nutrient use efficiencies across geographic regions, nutrients, and time. The average N balance on global cropland has remained fairly steady at about 50-55kgha-1yr-1 during the past 15 years, despite increasing N inputs. Regional trends, however, show recent average N surpluses that range from a low of about 10kgNha-1yr-1 in Africa to more than 90kgNha-1yr-1 in Asia. Encouragingly, average global cropland N use efficiency decreased from about 59% in 1961 to a low of 43% in 1988, but it has risen since then to a level of 55%. Phosphorus deficits are mainly found in Africa, whereas potassium deficits occur in Africa and the Americas. This study introduces improvements over previous work in relation to the key nutrient coefficients affecting nutrient budgets and nutrient use efficiency estimates, especially with respect to nutrient removal in crop products, manure nutrient content, atmospheric deposition and crop biological N fixation rates. We conclude by discussing future research directions and highlighting the need to align statistical definitions across research groups as well as to further refine plant and livestock coefficients and expand estimates to all agr

Agricultural nutrient budgets help to identify an excess or an insufficiency in use of fertilizers and other nutrient sources. Nutrient budgets allow for indicators such as the nutrient balance (surplus or deficit) and nutrient use efficiency to be estimated. This can help in the monitoring of agricultural productivity and sustainability globally. The present dataset is a global database of country-level budget estimates for nitrogen (N), phosphorus (P) and potassium (K) in cropland. The database is disseminated in FAOSTAT and provides a global reference, synthesizing and continuously updating the state-of-the-art on this topic. The database covers the period 961 to 2020 for 205 countries and territories, as well as regional and global aggregates. Results indicate the wide range in nutrient use and use efficiencies across regions, nutrients, and time. This dataset introduces improvements over previous work in relation to key nutrient coefficients affecting nutrient budgets and use efficiency estimates. This is especially for nutrient removal in crop products, manure nutrient content, atmospheric deposition and crop biological N fixation rates.

Estimates of crop nutrient removal (as crop products and crop residues) are an important component of crop nutrient balances. Crop nutrient removal can be estimated through multiplication of the quantity of crop products or crop residues (removed) by the nutrient concentration of those crop products and crop residue components respectively. Data for quantities of crop products removed at a country level are available through FAOSTAT (https://www.fao.org/faostat/en/), but equivalent data for quantities of crop residues are not available at a global level. However, quantities of crop residues can be estimated if the relationship between quantity of crop residues and crop products is known. Harvest index (HI) provides one such indication of the relationship between quantity of crop products and crop residues. HI is the proportion of above-ground biomass as crop products and can be used to estimate quantity of crop residues based on quantity of crop products. Previously, meta-analyses or surveys have been performed to estimate nutrient concentrations of crop products and crop residues and harvest indices (collectively known as crop coefficients). The challenges for using these coefficients in global nutrient balances include the representativeness of world regions or countries. Moreover, it may be unclear which countries or crop types are actually represented in the analyses of data. In addition, units used among studies differ which makes comparisons challenging. To overcome these challenges, data from meta-analyses and surveys were collated in one dataset with standardised units and referrals to the original region and crop names used by the sources of data. Original region and crop names were converted into internationally recognised names, and crop coefficients were summarised into two Tiers of data, representing the world (Tier 1, with single coefficient values for the world) and specific regions or countries of the world (Tier 2, with single coefficient values for

Nutrient inputs play a critical role in raising crops and livestock for food security, human nutrition and other uses in the bioeconomy. Their production and management must change so as to nourish crops, reduce harmful environmental impacts caused by nutrient losses and contribute to the restoration of soil health more effectively. A new paradigm for plant nutrition follows a food system approach in which multiple socioeconomic, environmental and health objectives must be achieved. The coming 10-20 years will be most critical for making the transition to a global food system in which all stakeholders look at food and nutrients in a holistic manner, including in regard to their hidden environmental, health and socioeconomic costs. Consumers, as well as governments and other stakeholders, need to support such a transformation, because farmers and the industry supporting them will not be able to implement all of the required actions alone. The outcome of this transformation will be a new societal plant nutrition optimum, rather than a purely economic optimum. The new nutrient economy will become an integral component of a low-carbon emission, environment-friendly and circular economy, supporting the food and nutrition requirements of a rising global population and improving the income and livelihood of farmers worldwide.

Grasslands cover around 25% of the global ice-free land surface, they are used predominantly for forage and livestock production and are considered to contribute significantly to soil carbon (C) sequestration. Recent investigations into using ‘nature-based solutions’ to limit warming to <2 °C suggest up to 25% of GHG mitigation might be achieved through changes to grassland management. In this study we evaluate pasture management interventions at the Rothamsted Research North Wyke Farm Platform, under commercial farming conditions, over two years and consider their impacts on net CO2 exchange. We investigate if our permanent pasture system (PP) is, in the short-term, a net sink for CO2 and whether reseeding this with deep-rooting, high-sugar grass (HS) or a mix of high-sugar grass and clover (HSC) might increase the net removal of atmospheric CO2. In general CO2 fluxes were less variable in 2018 than in 2017 while overall we found that net CO2 fluxes for the PP treatment changed from a sink in 2017 (−5.40 t CO2 ha−1 y−1) to a source in 2018 (6.17 t CO2 ha−1 y−1), resulting in an overall small source of 0.76 t CO2 ha−1 over the two years for this treatment. HS showed a similar trend, changing from a net sink in 2017 (−4.82 t CO2 ha−1 y−1) to a net source in 2018 (3.91 t CO2 ha−1 y−1) whilst the HSC field was a net source in both years (3.92 and 4.10 t CO2 ha−1 y−1, respectively). These results suggested that pasture type has an influence in the atmospheric CO2 balance and our regression modelling supported this conclusion, with pasture type and time of the year (and their interaction) being significant factors in predicting fluxes.

Understanding how much inorganic fertilizer (referred to as fertilizer) is applied to different crops at national, regional and global levels is an essential component of fertilizer consumption analysis and demand projection. Good information on fertilizer use by crop (FUBC) is rarely available because it is difficult to collect and time-consuming to process and validate. To fill this gap, a first global FUBC report was published in 1992 for the 1990/1991 period, based on an expert survey conducted jointly by the Food and Agriculture Organization (FAO) of the UN, the International Fertilizer Development Center (IFDC) and the International Fertilizer Association (IFA). Since then, similar expert surveys have been carried out and published every two to four years in the main fertilizer-consuming countries. Since 2008 IFA has led these efforts and, to our knowledge, remains the only globally available data set on FUBC. This dataset includes data (in CSV format) from a survey carried out by IFA to represent the 2017–18 period as well as a collation of all historic FUBC data.

Reliable estimates of crop nitrogen (N) uptake and offtake are critical in estimating N balances, N use efficiencies and potential losses to the environment. Calculation of crop N uptake and offtake requires estimates of yield of crop product (e.g. grain or beans) and crop residues (e.g. straw or stover) and the N concentration of both components. Yields of crop products are often reasonably well known, but those of crop residues are not. While the harvest index (HI) can be used to interpolate the quantity of crop residue from available data on crop product yields, harvest indices are known to vary across locations, as do N concentrations of residues and crop products. The increasing availability of crop data and advanced statistical and machine learning methods present us with an opportunity to move towards more locally relevant estimates of crop harvest index and N concentrations using more readily available data. The aim of this study was to investigate whether improved estimates of maize crop HI and N concentrations of crop products and crop residues can be based on crop data available at the global scale, such as crop yield, fertilizer application rates and estimates of yield potential. Experiments from 1487 different locations conducted across 31 countries were used to test various prediction models. Predictions from mixed-effects models and random forest machine learning models provided reasonable levels of prediction accuracy (R2 of between 0.33 and 0.68), with the random forest method having greater accuracy. Although the mixed-effects prediction models had lower prediction accuracy than random forest, they did provide better interpretability. Selection of which method to use will depend on the objective of the user. Here, the random forest and mixed-effects methods were applied to N in maize, but could equally be applied to other crops and other nutrients, if data becomes available. This will enable obtaining more locally relevant estimates of crop nutrien

Grasslands cover around 25% of the global ice-free land surface, they are used predominantly for forage and livestock production and are considered to contribute significantly to soil carbon (C) sequestration. Recent investigations into using ‘nature-based solutions’ to limit warming to <2 °C suggest up to 25% of GHG mitigation might be achieved through changes to grassland management. In this study we evaluate pasture management interventions at the Rothamsted Research North Wyke Farm Platform, under commercial farming conditions, over two years and consider their impacts on net CO2 exchange. We investigate if our permanent pasture system (PP) is, in the short-term, a net sink for CO2 and whether reseeding this with deep-rooting, high-sugar grass (HS) or a mix of high-sugar grass and clover (HSC) might increase the net removal of atmospheric CO2. In general CO2 fluxes were less variable in 2018 than in 2017 while overall we found that net CO2 fluxes for the PP treatment changed from a sink in 2017 (−5.40 t CO2 ha−1 y−1) to a source in 2018 (6.17 t CO2 ha−1 y−1), resulting in an overall small source of 0.76 t CO2 ha−1 over the two years for this treatment. HS showed a similar trend, changing from a net sink in 2017 (−4.82 t CO2 ha−1 y−1) to a net source in 2018 (3.91 t CO2 ha−1 y−1) whilst the HSC field was a net source in both years (3.92 and 4.10 t CO2 ha−1 y−1, respectively). These results suggested that pasture type has an influence in the atmospheric CO2 balance and our regression modelling supported this conclusion, with pasture type and time of the year (and their interaction) being significant factors in predicting fluxes.

Understanding how much inorganic fertilizer (referred to as fertilizer) is applied to different crops at national, regional and global levels is an essential component of fertilizer consumption analysis and demand projection. Good information on fertilizer use by crop (FUBC) is rarely available because it is difficult to collect and time-consuming to process and validate. To fill this gap, a first global FUBC report was published in 1992 for the 1990/1991 period, based on an expert survey conducted jointly by the Food and Agriculture Organization (FAO) of the UN, the International Fertilizer Development Center (IFDC) and the International Fertilizer Association (IFA). Since then, similar expert surveys have been carried out and published every two to four years in the main fertilizer-consuming countries. Since 2008 IFA has led these efforts and, to our knowledge, remains the only globally available data set on FUBC. This dataset includes data (in CSV format) from a survey carried out by IFA to represent the 2017–18 period as well as a collation of all historic FUBC data., Understanding how much inorganic fertilizer (referred to as fertilizer) is applied to different crops at national, regional and global levels is an essential component of fertilizer consumption analysis and demand projection. Good information on fertilizer use by crop (FUBC) is rarely available because it is difficult to collect and time-consuming to process and validate. To fill this gap, a first global FUBC report was published in 1992 for the 1990/1991 period, based on an expert survey conducted jointly by the Food and Agriculture Organization (FAO) of the UN, the International Fertilizer Development Center (IFDC) and the International Fertilizer Association (IFA). Since then, similar expert surveys have been carried out and published every two to four years in the main fertilizer-consuming countries. Since 2008 IFA has led these efforts and, to our knowledge, remains the only globally available data set on FUBC. This dataset includes data (in CSV format) from a survey carried out by IFA to represent the 2017–18 period as well as a collation of all historic FUBC data.

Estimates of crop nitrogen (N) uptake and offtake are critical in estimating N balances, N use efficiencies and potential losses to the environment. Calculation of crop N uptake and offtake requires estimates of crop product yield (e.g. grain or beans) and crop residue yield (e.g. straw or stover) and the N concentration of both components. Yields of crop products are often reasonably well known, but those of crop residues are not. While the harvest index (HI) can be used to interpolate the quantity of crop residue from available data on crop product yields, harvest indices are known to vary across locations, as do N concentrations of residues and crop products. The increasing availability of crop data and advanced statistical and machine learning methods present us with an opportunity to move towards more locally relevant estimates of crop harvest index and N concentrations using more readily available data. This dataset includes maize field experiment data. It is a culmination of summary statistic data collected from the literature as well as raw data requested from various researchers and organisations from around the world. These data will enable more locally relevant estimates of crop nutrient offtake, nutrient balances and nutrient use efficiency at national, regional or global levels, as part of strategies towards more sustainable nutrient management., Estimates of crop nitrogen (N) uptake and offtake are critical in estimating N balances, N use efficiencies and potential losses to the environment. Calculation of crop N uptake and offtake requires estimates of crop product yield (e.g. grain or beans) and crop residue yield (e.g. straw or stover) and the N concentration of both components. Yields of crop products are often reasonably well known, but those of crop residues are not. While the harvest index (HI) can be used to interpolate the quantity of crop residue from available data on crop product yields, harvest indices are known to vary across locations, as do N concentrations of residues and crop products. The increasing availability of crop data and advanced statistical and machine learning methods present us with an opportunity to move towards more locally relevant estimates of crop harvest index and N concentrations using more readily available data. This dataset includes maize field experiment data. It is a culmination of summary statistic data collected from the literature as well as raw data requested from various researchers and organisations from around the world. These data will enable more locally relevant estimates of crop nutrient offtake, nutrient balances and nutrient use efficiency at national, regional or global levels, as part of strategies towards more sustainable nutrient management.

The coming 10–20 years will be most critical for making the transition to a global food system in which mineral nutrients in agriculture must be managed in a more holistic manner. Fertilizers play a particular role in that because they are among the key drivers for securing global food security and improving human nutrition through increased crop yields and nutritional quality. A new paradigm for responsible plant nutrition follows a food systems and circular economy approach to achieve multiple socioeconomic, environmental and health objectives. Achieving that requires utilizing all available organic and inorganic nutrient sources with high efficiency, tailored to the specific features of food systems and agroecosystems in different world regions. Critical actions include: (i) sustainability-driven nutrient roadmaps, (ii) digital crop nutrition solutions, (iii) nutritious crops, (iv) nutrient recovery and recycling, (v) climate-smart fertilizers, and (vi) accelerated innovation. The outcome of this transformation will be a new societal plant nutrition optimum rather than a purely economic optimum. New partnerships and sustainability-focused business models will create added value for all actors in the nutrient chain and benefit farmers as well as consumers. Research needs to become more problem-driven and merge excellent science with entrepreneurial innovation approaches in order to develop robust solutions faster and at larger scale. Evidence-based policies should focus on creating and supporting the necessary nutrient stewardship roadmaps, including realistic national targets, progressive regulation and incentives that support technology and business innovation.

Soil property and class maps for the continent of Africa were so far only available at very generalised scales, with many countries not mapped at all. Thanks to an increasing quantity and availability of soil samples collected at field point locations by various government and/or NGO funded projects, it is now possible to produce detailed pan-African maps of soil nutrients, including micro-nutrients at fine spatial resolutions. In this paper we describe production of a 30 m resolution Soil Information System of the African continent using, to date, the most comprehensive compilation of soil samples (N≈150,000) and Earth Observation data. We produced predictions for soil pH, organic carbon (C) and total nitrogen (N), total carbon, effective Cation Exchange Capacity (eCEC), extractable—phosphorus (P), potassium (K), calcium (Ca), magnesium (Mg), sulfur (S), sodium (Na), iron (Fe), zinc (Zn)—silt, clay and sand, stone content, bulk density and depth to bedrock, at three depths (0, 20 and 50 cm) and using 2-scale 3D Ensemble Machine Learning framework implemented in the mlr (Machine Learning in R) package. As covariate layers we used 250 m resolution (MODIS, PROBA-V and SM2RAIN products), and 30 m resolution (Sentinel-2, Landsat and DTM derivatives) images. Our fivefold spatial Cross-Validation results showed varying accuracy levels ranging from the best performing soil pH (CCC = 0.900) to more poorly predictable extractable phosphorus (CCC = 0.654) and sulphur (CCC = 0.708) and depth to bedrock. Sentinel-2 bands SWIR (B11, B12), NIR (B09, B8A), Landsat SWIR bands, and vertical depth derived from 30 m resolution DTM, were the overall most important 30 m resolution covariates. Climatic data images—SM2RAIN, bioclimatic variables and MODIS Land Surface Temperature—however, remained as the overall most important variables for predicting soil chemical variables at continental scale. This publicly available 30-m Soil Information System of Africa aims at supporting numerous ap

Intensive systems with two or three rice (Oryza sativa L.) crops per year account for about 50% of the harvested area for irrigated rice in Asia. Any reduction in productivity or sustainability of these systems has serious implications for global food security. Rice yield trends in the world's longest-running long-term continuous cropping experiment (LTCCE) were evaluated to investigate consequences of intensive cropping and to draw lessons for sustaining production in Asia. Annual production was sustained at a steady level over the 50-y period in the LTCCE through continuous adjustment of management practices and regular cultivar replacement. Within each of the three annual cropping seasons (dry, early wet, and late wet), yield decline was observed during the first phase, from 1968 to 1990. Agronomic improvements in 1991 to 1995 helped to reverse this yield decline, but yield increases did not continue thereafter from 1996 to 2017. Regular genetic and agronomic improvements were sufficient to maintain yields at steady levels in dry and early wet seasons despite a reduction in the yield potential due to changing climate. Yield declines resumed in the late wet season. Slower growth in genetic gain after the first 20 y was associated with slower breeding cycle advancement as indicated by pedigree depth. Our findings demonstrate that through adjustment of management practices and regular cultivar replacement, it is possible to sustain a high level of annual production in irrigated systems under a changing climate. However, the system was unable to achieve further increases in yield required to keep pace with the growing global rice demand.

Soil property and class maps for the continent of Africa were so far only available at very generalised scales, with many countries not mapped at all. Thanks to an increasing quantity and availability of soil samples collected at field point locations by various government and/or NGO funded projects, it is now possible to produce detailed pan-African maps of soil nutrients, including micro-nutrients at fine spatial resolutions. In this paper we describe production of a 30 m resolution Soil Information System of the African continent using, to date, the most comprehensive compilation of soil samples (N≈150,000) and Earth Observation data. We produced predictions for soil pH, organic carbon (C) and total nitrogen (N), total carbon, effective Cation Exchange Capacity (eCEC), extractable—phosphorus (P), potassium (K), calcium (Ca), magnesium (Mg), sulfur (S), sodium (Na), iron (Fe), zinc (Zn)—silt, clay and sand, stone content, bulk density and depth to bedrock, at three depths (0, 20 and 50 cm) and using 2-scale 3D Ensemble Machine Learning framework implemented in the mlr (Machine Learning in R) package. As covariate layers we used 250 m resolution (MODIS, PROBA-V and SM2RAIN products), and 30 m resolution (Sentinel-2, Landsat and DTM derivatives) images. Our fivefold spatial Cross-Validation results showed varying accuracy levels ranging from the best performing soil pH (CCC = 0.900) to more poorly predictable extractable phosphorus (CCC = 0.654) and sulphur (CCC = 0.708) and depth to bedrock. Sentinel-2 bands SWIR (B11, B12), NIR (B09, B8A), Landsat SWIR bands, and vertical depth derived from 30 m resolution DTM, were the overall most important 30 m resolution covariates. Climatic data images—SM2RAIN, bioclimatic variables and MODIS Land Surface Temperature—however, remained as the overall most important variables for predicting soil chemical variables at continental scale. This publicly available 30-m Soil Information System of Africa aims at supporting numerous ap

PR, IFPRI3; ISI; UNFSS; CRP4; 1 Fostering Climate-Resilient and Sustainable Food Supply; 2 Promoting Healthy Diets and Nutrition for all; 5 Strengthening Institutions and Governance, A4NH, CGIAR Research Program on Agriculture for Nutrition and Health (A4NH)

Vous avez un chien se présente sous la forme d’une bande dessinée qui met en scène un/e chien/ne et son/sa maître/sse. C’est un manuel d’éducation pour tous ceux qui vivent avec des animaux domestiques ou d’autres êtres vivants. Ecrit par Balkis Berger-Dobermann, qui partageait la vie des Friedman, Vous avez un chien aurait pu s’intituler « Comment dresser ses maîtres», mais l’auteur a préféré s’en tenir à un titre plus « général » et moins « anthropomorphe ». Vous avez un chien est aussi un livre pour ceux qui ont des chats, des canaris, des poissons rouges. Il énonce selon des principes simples «comment vivre avec les autres, sans être maître, ni esclave» pour reprendre le titre d’un autre ouvrage de Friedman. Yona Friedman est né à Budapest le 5 juin 1923. Il commence des études d’architecture à Budapest en 1943 qu’il achèvera au Technion de Haïfa en Israël en 1948. C’est là qu’il fait l’expérience d’une architecture nouvelle, pensée avec les habitants eux-mêmes. Il vit et travaille à Paris depuis 1957. Aux éditions de l’éclat ont paru (ou reparu) la plupart de ses livres (anciens et plus récents). Sa disparition a été annoncée le 21 février 2020 sur son compte Instagram.

Vous avez un chien se présente sous la forme d’une bande dessinée qui met en scène un/e chien/ne et son/sa maître/sse. C’est un manuel d’éducation pour tous ceux qui vivent avec des animaux domestiques ou d’autres êtres vivants. Ecrit par Balkis Berger-Dobermann, qui partageait la vie des Friedman, Vous avez un chien aurait pu s’intituler « Comment dresser ses maîtres», mais l’auteur a préféré s’en tenir à un titre plus « général » et moins « anthropomorphe ». Vous avez un chien est aussi un livre pour ceux qui ont des chats, des canaris, des poissons rouges. Il énonce selon des principes simples «comment vivre avec les autres, sans être maître, ni esclave» pour reprendre le titre d’un autre ouvrage de Friedman. Yona Friedman est né à Budapest le 5 juin 1923. Il commence des études d’architecture à Budapest en 1943 qu’il achèvera au Technion de Haïfa en Israël en 1948. C’est là qu’il fait l’expérience d’une architecture nouvelle, pensée avec les habitants eux-mêmes. Il vit et travaille à Paris depuis 1957. Aux éditions de l’éclat ont paru (ou reparu) la plupart de ses livres (anciens et plus récents). Sa disparition a été annoncée le 21 février 2020 sur son compte Instagram.

PR, IFPRI3; ISI; CRP4; DCA; 1 Fostering Climate-Resilient and Sustainable Food Supply; 2 Promoting Healthy Diets and Nutrition for all; 4 Transforming Agricultural and Rural Economies; 5 Strengthening Institutions and Governance; Capacity Strengthening, A4NH, CGIAR Research Program on Agriculture for Nutrition and Health (A4NH), Research and science should not only inform food and environmental policy but should be adopted and mainstreamed into actions at all levels. Food systems are faced with grander and interconnected challenges and constraints that bring about new research questions. Research has a vital role in charting a positive and sustainable direction for global food security, nutrition, and health. The status quo must be challenged to shape food systems transformation to deliver sustainable, healthier diets. Global Food Security provides a platform where evidence is shared in an accessible manner for those who need to act on it.

Scalable theory have led to many advances. Data flow is constantly growing and systems are expanding. Theoretical principles of red-black trees can help to build a scalable system, where data easily can expand and in the end energy is saved. We propose a novel solution, an organizational platform, an algorithm for the analysis of agents, which we call Mop. With experimental results we show, that Mop is faster than the Apriori or any other algorithm concerning scalable theory. Mop is even faster than the ADFD-growth algorithm, especially when tested in a very low key RAM environment.

To assess the scope of infection control measures for multidrug-resistant bacteria in high-risk settings, a survey among university hospitals was conducted. Fourteen professionals from 8 sites participated. Reported policies varied largely with respect to the types of wards conducting screening, sample types used for screening and implementation of contact precautions. This variability among sites highlights the need for an evidence-based consensus of current infection control policies.

To assess the scope of infection control measures for multidrug-resistant bacteria in high-risk settings, a survey among university hospitals was conducted. Fourteen professionals from 8 sites participated. Reported policies varied largely with respect to the types of wards conducting screening, sample types used for screening and implementation of contact precautions. This variability among sites highlights the need for an evidence-based consensus of current infection control policies.

To assess the scope of infection control measures for multidrug-resistant bacteria in high-risk settings, a survey among university hospitals was conducted. Fourteen professionals from 8 sites participated. Reported policies varied largely with respect to the types of wards conducting screening, sample types used for screening and implementation of contact precautions. This variability among sites highlights the need for an evidence-based consensus of current infection control policies.

Nearly all countries in the world today are burdened with malnutrition, manifesting as undernutrition, micronutrient deficiencies, and/or overweight and obesity. Despite some progress, efforts to alleviate malnutrition are hampered by a shortage in number, skills, and geographic coverage, of a workforce for nutrition. Here, we report the findings of the Castel Gandolfo workshop, a convening of experts from diverse fields in March 2014 to consider how to develop the capacity of a global cadre of nutrition professionals for the post-2015 development era. Workshop participants identified several requirements for developing a workforce for nutrition, including an ability to work as part of a multisectoral team; communication, advocacy, and leadership skills to engage decision makers; and a set of technical skills to address future challenges for nutrition. Other opportunities were highlighted that could immediately contribute to capacity development, including the creation of a consortium to link global North and South universities, online training modules for middle managers, and practical, hands-on experiences for frontline nutrition workers. Institutional and organizational support is needed to enable workshop recommendations on education and training to be effectively implemented and sustained. The findings from the Castel Gandolfo workshop can contribute to the delivery of successful nutrition-relevant actions in the face of mounting external pressures and informing and attaining the forthcoming Sustainable Development Goals.

PR, IFPRI3; ISI; CRP4; Capacity Strengthening, PHND; A4NH, CGIAR Research Program on Agriculture for Nutrition and Health (A4NH)

PR, IFPRI3; ISI; B Promoting healthy food systems; F Strengthening institutions and governance; G Cross-cutting gender theme; CRP2, DSGD; PIM, CGIAR Research Program on Policies, Institutions, and Markets (PIM)

PR, IFPRI4

PR, IFPRI4, DSGD; EPTD, vii, 477 p. : ill. (some col.), col. maps ; 23 cm.

PR, IFPRI4; ASTI, EPTD

In the present paper, we review 4 topics that were identified through extensive consultation with stakeholders as issues of high impact and influence for the grains industry: improving soil testing and interpretation; role of fluid fertilisers in the Western Australian (WA) grains industry; using spatial and temporal information to improve crop nutrient management, particularly for nitrogen; and developing recommendations for managing emerging nutrient deficiencies. The key findings are summarised below. To further improve soil testing and interpretation, the review suggests that future research should focus on addressing soil sampling and interpretation questions, as they are important factors affecting the accuracy of fertiliser recommendations with changing cropping practices. There have been several studies to compare fluid with granular forms of P in WA, but the responses have not, so far, been consistent. More work may be needed to understand different crop response to fluid P fertiliser additions, particularly on low pH soils in WA. An understanding of the long-term performance of fluid P will also require an assessment of the residual value of fluid P compared with granular P under field conditions. Precision agriculture (PA) technology has potential to improve crop nutrient management and farm profitability in WA. The review indicates that understanding both spatial and temporal yield variation is critical for the successful adoption of PA technology by growers. The review also suggests that in WA, there is a need to explore the use of different layers of spatial information for determining management zones. In response to wide adoption of no-till and stubble retention cropping systems, increased use of fluid fertilisers together with advanced application technologies, and increased interest in cropping in the high rainfall zone, there is need to better understand growers' practices and attitudes to crop nitrogen (N) management, and thus to better position

In the present paper, we review 4 topics that were identified through extensive consultation with stakeholders as issues of high impact and influence for the grains industry: improving soil testing and interpretation; role of fluid fertilisers in the Western Australian (WA) grains industry; using spatial and temporal information to improve crop nutrient management, particularly for nitrogen; and developing recommendations for managing emerging nutrient deficiencies. The key findings are summarised below. To further improve soil testing and interpretation, the review suggests that future research should focus on addressing soil sampling and interpretation questions, as they are important factors affecting the accuracy of fertiliser recommendations with changing cropping practices. There have been several studies to compare fluid with granular forms of P in WA, but the responses have not, so far, been consistent. More work may be needed to understand different crop response to fluid P fertiliser additions, particularly on low pH soils in WA. An understanding of the long-term performance of fluid P will also require an assessment of the residual value of fluid P compared with granular P under field conditions. Precision agriculture (PA) technology has potential to improve crop nutrient management and farm profitability in WA. The review indicates that understanding both spatial and temporal yield variation is critical for the successful adoption of PA technology by growers. The review also suggests that in WA, there is a need to explore the use of different layers of spatial information for determining management zones. In response to wide adoption of no-till and stubble retention cropping systems, increased use of fluid fertilisers together with advanced application technologies, and increased interest in cropping in the high rainfall zone, there is need to better understand growers' practices and attitudes to crop nitrogen (N) management, and thus to better position

This paper provides an overview of what the Millennium Ecosystem Assessment (MA) call "indirect and direct drivers" of change in ecosystem services at a global level. The MA definition of a driver is any natural or human-induced factor that directly or indirectly causes a change in an ecosystem. A direct driver unequivocally influences ecosystem processes. An indirect driver operates more diffusely by altering one or more direct drivers. Global driving forces are categorized as demographic, economic, sociopolitical, cultural and religious, scientific and technological, and physical and biological. Drivers in all categories other than physical and biological are considered indirect. Important direct drivers include changes in climate, plant nutrient use, land conversion, and diseases and invasive species. This paper does not discuss natural drivers such as climate variability, extreme weather events, or volcanic eruptions.

This paper provides an overview of what the Millennium Ecosystem Assessment (MA) call "indirect and direct drivers" of change in ecosystem services at a global level. The MA definition of a driver is any natural or human-induced factor that directly or indirectly causes a change in an ecosystem. A direct driver unequivocally influences ecosystem processes. An indirect driver operates more diffusely by altering one or more direct drivers. Global driving forces are categorized as demographic, economic, sociopolitical, cultural and religious, scientific and technological, and physical and biological. Drivers in all categories other than physical and biological are considered indirect. Important direct drivers include changes in climate, plant nutrient use, land conversion, and diseases and invasive species. This paper does not discuss natural drivers such as climate variability, extreme weather events, or volcanic eruptions.

This paper provides an overview of what the Millennium Ecosystem Assessment (MA) call "indirect and direct drivers" of change in ecosystem services at a global level. The MA definition of a driver is any natural or human-induced factor that directly or indirectly causes a change in an ecosystem. A direct driver unequivocally influences ecosystem processes. An indirect driver operates more diffusely by altering one or more direct drivers. Global driving forces are categorized as demographic, economic, sociopolitical, cultural and religious, scientific and technological, and physical and biological. Drivers in all categories other than physical and biological are considered indirect. Important direct drivers include changes in climate, plant nutrient use, land conversion, and diseases and invasive species. This paper does not discuss natural drivers such as climate variability, extreme weather events, or volcanic eruptions.

Long-term irrigated rice (Oryza sativa L.) cultivation is an important yet unstudied source of soil variation in tropical lowland rice fields, A field study was conducted to quantify spatial soil variability and to analyze correlations among soil properties at different spatial scales, Soil samples from the 0- to 20-cm depth were collected from adjacent rice fields consisting of Typic Tropaquepts and Typic Tropaqualfs, Structural variogram analysis and factorial kriging (FKA) were used to describe the coregionalization of 14 soil properties, Coregionalization was described by a model comprising (i) a nugget effect, (ii) a spherical model with a range of 12 m, and (iii) a Gaussian model with a range of 36 m, Correlations among soil properties varied depending on spatial scale. Short-range soil variation was caused by irrigation and land leveling, but results were not consistent for both fields, Similar autovariograms and high correlations between depth to the Cg horizon and extractable K in the Gaussian structure (rho(u nu)(2)=-0.95 to -0.99) revealed a strong influence of weathering of volcanic tuff on long-range trends in K, Electrical conductivity (EC), Na, and B were spatially trended and correlated with depth to the Cg horizon (rho(u nu)(2)=0.59-0.97) in the Gaussian structure, Subsurface water flow through cracks above an impermeable layer and surface water dow along the gentle field slope were sources of long-range variation in EC, Na, and B caused by irrigation, The FKA provides quantitative measures of complex spatial process results and offers new ways for generating hypotheses about the phenomenon itself.

Long-term irrigated rice (Oryza sativa L.) cultivation is an important yet unstudied source of soil variation in tropical lowland rice fields, A field study was conducted to quantify spatial soil variability and to analyze correlations among soil properties at different spatial scales, Soil samples from the 0- to 20-cm depth were collected from adjacent rice fields consisting of Typic Tropaquepts and Typic Tropaqualfs, Structural variogram analysis and factorial kriging (FKA) were used to describe the coregionalization of 14 soil properties, Coregionalization was described by a model comprising (i) a nugget effect, (ii) a spherical model with a range of 12 m, and (iii) a Gaussian model with a range of 36 m, Correlations among soil properties varied depending on spatial scale. Short-range soil variation was caused by irrigation and land leveling, but results were not consistent for both fields, Similar autovariograms and high correlations between depth to the Cg horizon and extractable K in the Gaussian structure (rho(u nu)(2)=-0.95 to -0.99) revealed a strong influence of weathering of volcanic tuff on long-range trends in K, Electrical conductivity (EC), Na, and B were spatially trended and correlated with depth to the Cg horizon (rho(u nu)(2)=0.59-0.97) in the Gaussian structure, Subsurface water flow through cracks above an impermeable layer and surface water dow along the gentle field slope were sources of long-range variation in EC, Na, and B caused by irrigation, The FKA provides quantitative measures of complex spatial process results and offers new ways for generating hypotheses about the phenomenon itself.

Field-scale variation in soil fertility can be a major source of uneven crop growth on acid soils of the humid tropics, but this has not received much research attention. We used factorial kriging (FKA) to analyze processes causing spatial variation in soil chemical properties (pH, P, K, Na, Ca, Mg, Al) measured at two depths within a single field on an acid Ultisol in the Philippines. A linear model of coregionalization comprising (i) a nugget effect, (ii) a spherical structure with a range of 20 m, and (iii) a linear structure was fitted to the experimental auto- and cross-variograms of the topsoiI properties. Variograms for subsoil variables were modeled using a nugget effect plus a linear structure. Regionalized factors associated with short- and long-range variation were then mapped and formed the basis for a conceptual model of soil formation and soil variation at the study site. Patchy inputs of nutrients from buffalo excrement have led to pronounced short-range variation in P, Ca, Mg, and K concentrations in the topsoil. The effects of these are superimposed on long-range processes operating along the topographic slope. The latter include vertical and lateral water how causing translocation of basic and acidic cations. Leaching of acidity along the major directions of the field slope seems to be a process of general importance in sloping lands of the humid tropics. Amelioration of soil acidity as well as design of field experiments have to account for this kind of slope-dependent systematic soil variation. Combining pedological expert knowledge with techniques such as FKA helps to explore complex processes in a quantitative way.

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