Global crop-specific nitrogen fertilization dataset in 1961-2020.

Nitrogen (N) is an important nutrient for crop growth. However, the overuse of N fertilizers has led to a series of devastating global environmental issues. Recent studies show that multiple datasets have been created for agricultural N fertilizer application with varied temporal or spatial resolutions, nevertheless, how to synchronize and use these datasets becomes problematic due to the inconsistent temporal coverages, spatial resolutions, and crop-specific allocations. Here we reconstructed a comprehensive dataset for crop-specific N fertilization at 5-arc-min resolution (~10 km by 10 km) during 1961-2020, including N application rate, types, and placements. The N fertilization data was segmented by 21 crop groups, 13 fertilizer types, and 2 fertilization placements. Comparison analysis showed that our dataset is aligned with previous estimates. Our spatiotemporal N fertilization dataset could be used for the land surface models to quantify the effects of agricultural N fertilization practices on food security, climate change, and environmental sustainability.

Cropland displacement contributed 60% of the increase in carbon emissions of grain transport in China over 1990-2015.

Rapid urbanization and population growth have increased the need for grain transportation in China, as more grain is being consumed and croplands have been moved away from cities. Increased grain transportation has, in turn, led to higher energy consumption and carbon emissions. Here we undertook a model-based approach to estimate the carbon emissions associated with grain transportation in the country between 1990 and 2015. We found that emissions more than tripled, from 5.68 million tons of CO2 emission equivalent in 1990 to 17.69 million tons in 2015. Grain production displacement contributed more than 60% of the increase in carbon emissions associated with grain transport over the study period, whereas changes in grain consumption and population growth contributed 31.7% and 16.6%, respectively. Infrastructure development, such as newly built highways and railways in western China, helped offset 0.54 million tons of CO2 emission equivalent from grain transport. These findings shed light on the life cycle environmental impact within food supply chains.

Research priorities for global food security under extreme events.

Extreme events, such as those caused by climate change, economic or geopolitical shocks, and pest or disease epidemics, threaten global food security. The complexity of causation, as well as the myriad ways that an event, or a sequence of events, creates cascading and systemic impacts, poses significant challenges to food systems research and policy alike. To identify priority food security risks and research opportunities, we asked experts from a range of fields and geographies to describe key threats to global food security over the next two decades and to suggest key research questions and gaps on this topic. Here, we present a prioritization of threats to global food security from extreme events, as well as emerging research questions that highlight the conceptual and practical challenges that exist in designing, adopting, and governing resilient food systems. We hope that these findings help in directing research funding and resources toward food system transformations needed to help society tackle major food system risks and food insecurity under extreme events.

Comparing rice production systems in China: Economic output and carbon footprint.

In recent years, many rotational and integrated rice production systems coupled with several greenhouse gas (GHG) emissions mitigation practices have been developed and adopted for demand of low carbon production. However, there have been only few studies about comparisons on the balance between high production and mitigation of GHG emissions in different rice production systems. We therefore aimed to evaluate economic output and carbon footprint of different rice production systems, based on several long-term experiments conducted by our lab. CH4 and N2O emission were measured by the same static chamber/gas chromatogram measurement procedure in different rice production systems, including rice-fallow, rice-rapeseed, rice-wheat, double rice, and integrated rice-crayfish production system. Then, we applied the DeNitrification DeComposition model to simulate CH4 and N2O emission over different years under the same condition for comparison. Carbon footprint was calculated following the process-based life cycle assessment (PLCA) methodology. The economic benefit of rice production systems was assessed by cost-benefit analysis. According to the analysis, the double-rice production system exhibited the highest intensity of carbon footprint (ICF = 4.14 kg CO2-eq yuan-1), rain-fed treatment in the rice-rapeseed system had the lowest (ICF = 0.68 kg CO2-eq yuan-1). The intensity of carbon footprint in different treatments in the integrated rice-crayfish production system was around 0.8 kg CO2-eq yuan-1. Overall, the results of this case study suggest: (1) the proposed practices in different rice production systems are no straw returning (rice-fallow), no-tillage without straw returning (rice-wheat), rain-fed farming (rice-rapeseed), no insect and no inoculation (double rice), and feeding with straw returning (rice-crayfish); (2) rotational and integrated systems can achieve high net output with low carbon emission; (3) reducing the amount of nitrogenous fertilizer application is the most important and effective GHG mitigation practice for rotational systems.

Evaluating satellite-based evapotranspiration estimates for hydrological applications in data-scarce regions: A case in Ethiopia.

Water resource development opens up opportunities for improving smallholder farmer livelihoods in sub-Saharan Africa; however, implementation of water resource interventions to ensure sustainability hinges on the availability of sufficient quantity and quality data for monitoring, analysis and planning. Such data is often acquired through instrumentation of water resources (e.g. stream flow monitoring) or the use of hydrological models. In sub-Saharan Africa, data scarcity has limited the ability to monitor and make appropriate decisions for water resource allocation and use. Data derived from remote sensing has been considered a viable option to fill this gap; however, there is limited research in the region that evaluate the quality of the remotely sensed based datasets. This study evaluated actual evapotranspiration (AET) estimates derived from Advanced Very High Resolution Radiometer (AVHRR AET) images and Moderate Resolution Imaging Spectrometer (MOD16 AET) images using estimates from a grid-based Soil and Water Assessment Tool (SWAT). The SWAT model was set up for the entire country of Ethiopia, and calibrated and validated using observed streamflow at several meso-scale watersheds in which satisfactory model performance was obtained. AET estimates from the calibrated and validated SWAT model were then used to evaluate remotely sensed based AET for three landscapes. The AVHRR AET better agreed with the SWAT-simulated AET than the MOD16 AET, although the AVHRR AET overestimated the SWAT-simulated AET in all of the landscapes. Both remotely sensed AET products showed better agreement with the SWAT-simulated AET over agriculture dominated landscapes compared to grassland and forest dominated landscapes. The findings of the study suggest that remotely sensed based AET may help to fine-tune hydrological models in agricultural landscapes in data-scarce regions to improve studies on the impacts of water management interventions aiming to ensure environmental sustainability while enhancing agricultural production, and household income and nutrition.

South-to-North Water Diversion stabilizing Beijing's groundwater levels.

Groundwater (GW) overexploitation is a critical issue in North China with large GW level declines resulting in urban water scarcity, unsustainable agricultural production, and adverse ecological impacts. One approach to addressing GW depletion was to transport water from the humid south. However, impacts of water diversion on GW remained largely unknown. Here, we show impacts of the central South-to-North Water Diversion on GW storage recovery in Beijing within the context of climate variability and other policies. Water diverted to Beijing reduces cumulative GW depletion by ~3.6 km3, accounting for 40% of total GW storage recovery during 2006-2018. Increased precipitation contributes similar volumes to GW storage recovery of ~2.7 km3 (30%) along with policies on reduced irrigation (~2.8 km3, 30%). This recovery is projected to continue in the coming decade. Engineering approaches, such as water diversions, will increasingly be required to move towards sustainable water management.

The role of climate in the trend and variability of Ethiopia's cereal crop yields.

Food security has been and will continue to be a major challenge in Ethiopia. The country's smallholder, rainfed agriculture renders its food production system extremely vulnerable to climate variability and extremes. In this study, we investigate the impact of past climate variability and change on the yields of five major cereal crops in Ethiopia-barley, maize, millet, sorghum, and wheat-during the period 1979-2014 using the Decision Support System for Agrotechnology Transfer (DSSAT) crop model. The model is calibrated at both the site and agroecological-zone scales. At the sites studied, the model results suggest that climate in the past four decades may have contributed to an increasing trend in maize yield, a decreasing trend in wheat yield, and no clear trend in the yields of barley and millet; cereal crop yield is positively correlated with growing season solar radiation and temperature, but negatively correlated with growing season precipitation. For modeled cereal crops across the nation during the study period, yield in western Ethiopia is positively correlated with solar radiation and day time temperature; in the eastern and southeastern Ethiopia where water is a limiting factor for growth, yield is positively correlated with precipitation but negatively correlated with solar radiation and both day time and night time temperature. The national average of simulated yields of most crops (except maize) showed an overall decreasing (although not statistically significant) trend induced by past climate variability and changes. Over a large portion of the highly productive areas where there is a negative correlation between yield and temperature, yield is simulated to have significantly decreased over the past four decades, an indication of adverse climate impact in the past and potential food security concern in the future.

Satellite sun-induced chlorophyll fluorescence detects early response of winter wheat to heat stress in the Indian Indo-Gangetic Plains.

Extremely high temperatures represent one of the most severe abiotic stresses limiting crop productivity. However, understanding crop responses to heat stress is still limited considering the increases in both the frequency and severity of heat wave events under climate change. This limited understanding is partly due to the lack of studies or tools for the timely and accurate monitoring of crop responses to extreme heat over broad spatial scales. In this work, we use novel spaceborne data of sun-induced chlorophyll fluorescence (SIF), which is a new proxy for photosynthetic activity, along with traditional vegetation indices (Normalized Difference Vegetation Index NDVI and Enhanced Vegetation Index EVI) to investigate the impacts of heat stress on winter wheat in northwestern India, one of the world's major wheat production areas. In 2010, an abrupt rise in temperature that began in March adversely affected the productivity of wheat and caused yield losses of 6% compared to previous year. The yield predicted by satellite observations of SIF decreased by approximately 13.9%, compared to the 1.2% and 0.4% changes in NDVI and EVI, respectively. During early stage of this heat wave event in early March 2010, the SIF observations showed a significant reduction and earlier response, while NDVI and EVI showed no changes and could not capture the heat stress until late March. The spatial patterns of SIF anomalies closely tracked the temporal evolution of the heat stress over the study area. Furthermore, our results show that SIF can provide large-scale, physiology-related wheat stress response as indicated by the larger reduction in fluorescence yield (SIFyield ) than fraction of photosynthetically active radiation during the grain-filling phase, which may have eventually led to the reduction in wheat yield in 2010. This study implies that satellite observations of SIF have great potential to detect heat stress conditions in wheat in a timely manner and assess their impacts on wheat yields at large scales.

A Synergy Cropland of China by Fusing Multiple Existing Maps and Statistics.

Accurate information on cropland extent is critical for scientific research and resource management. Several cropland products from remotely sensed datasets are available. Nevertheless, significant inconsistency exists among these products and the cropland areas estimated from these products differ considerably from statistics. In this study, we propose a hierarchical optimization synergy approach (HOSA) to develop a hybrid cropland map of China, circa 2010, by fusing five existing cropland products, i.e., GlobeLand30, Climate Change Initiative Land Cover (CCI-LC), GlobCover 2009, MODIS Collection 5 (MODIS C5), and MODIS Cropland, and sub-national statistics of cropland area. HOSA simplifies the widely used method of score assignment into two steps, including determination of optimal agreement level and identification of the best product combination. The accuracy assessment indicates that the synergy map has higher accuracy of spatial locations and better consistency with statistics than the five existing datasets individually. This suggests that the synergy approach can improve the accuracy of cropland mapping and enhance consistency with statistics.

A global dataset of crowdsourced land cover and land use reference data.

Global land cover is an essential climate variable and a key biophysical driver for earth system models. While remote sensing technology, particularly satellites, have played a key role in providing land cover datasets, large discrepancies have been noted among the available products. Global land use is typically more difficult to map and in many cases cannot be remotely sensed. In-situ or ground-based data and high resolution imagery are thus an important requirement for producing accurate land cover and land use datasets and this is precisely what is lacking. Here we describe the global land cover and land use reference data derived from the Geo-Wiki crowdsourcing platform via four campaigns. These global datasets provide information on human impact, land cover disagreement, wilderness and land cover and land use. Hence, they are relevant for the scientific community that requires reference data for global satellite-derived products, as well as those interested in monitoring global terrestrial ecosystems in general.

CELL5M: A geospatial database of agricultural indicators for Africa South of the Sahara.

Recent progress in large-scale georeferenced data collection is widening opportunities for combining multi-disciplinary datasets from biophysical to socioeconomic domains, advancing our analytical and modeling capacity. Granular spatial datasets provide critical information necessary for decision makers to identify target areas, assess baseline conditions, prioritize investment options, set goals and targets and monitor impacts. However, key challenges in reconciling data across themes, scales and borders restrict our capacity to produce global and regional maps and time series. This paper provides overview, structure and coverage of CELL5M-an open-access database of geospatial indicators at 5 arc-minute grid resolution-and introduces a range of analytical applications and case-uses. CELL5M covers a wide set of agriculture-relevant domains for all countries in Africa South of the Sahara and supports our understanding of multi-dimensional spatial variability inherent in farming landscapes throughout the region.

Patterns of Cereal Yield Growth across China from 1980 to 2010 and Their Implications for Food Production and Food Security.

After a remarkable 86% increase in cereal production from 1980 to 2005, recent crop yield growth in China has been slow. County level crop production data between 1980 and 2010 from eastern and middle China were used to analyze spatial and temporal patterns of rice, wheat and maize yield in five major farming systems that include around 90% of China's cereal production. Site-specific yield trends were assessed in areas where those crops have experienced increasing yield or where yields have stagnated or declined. We find that rice yields have continued to increase on over 12.3 million hectares (m. ha) or 41.8% of the rice area in China between 1980 and 2010. However, yields stagnated on 50% of the rice area (around 14.7 m. ha) over this time period. Wheat yields increased on 13.8 m. ha (58.2% of the total harvest area), but stagnated on around 3.8 m. ha (15.8% of the harvest area). Yields increased on a smaller proportion of the maize area (17.7% of harvest area, 5.3 m. ha), while yields have stagnated on over 54% (16.3 m. ha). Many parts of the lowland rice and upland intensive sub-tropical farming systems were more prone to stagnation with rice, the upland intensive sub-tropical system with wheat, and maize in the temperate mixed system. Large areas where wheat yield continues to rise were found in the lowland rice and temperate mixed systems. Land and water constraints, climate variability, and other environmental limitations undermine increased crop yield and agricultural productivity in these systems and threaten future food security. Technology and policy innovations must be implemented to promote crop yields and the sustainable use of agricultural resources to maintain food security in China. In many production regions it is possible to better match the crop with input resources to raise crop yields and benefits. Investments may be especially useful to intensify production in areas where yields continue to improve. For example, increased support to maize production in southern China, where yields are still rising, seems justified.

Mapping global cropland and field size.

A new 1 km global IIASA-IFPRI cropland percentage map for the baseline year 2005 has been developed which integrates a number of individual cropland maps at global to regional to national scales. The individual map products include existing global land cover maps such as GlobCover 2005 and MODIS v.5, regional maps such as AFRICOVER and national maps from mapping agencies and other organizations. The different products are ranked at the national level using crowdsourced data from Geo-Wiki to create a map that reflects the likelihood of cropland. Calibration with national and subnational crop statistics was then undertaken to distribute the cropland within each country and subnational unit. The new IIASA-IFPRI cropland product has been validated using very high-resolution satellite imagery via Geo-Wiki and has an overall accuracy of 82.4%. It has also been compared with the EarthStat cropland product and shows a lower root mean square error on an independent data set collected from Geo-Wiki. The first ever global field size map was produced at the same resolution as the IIASA-IFPRI cropland map based on interpolation of field size data collected via a Geo-Wiki crowdsourcing campaign. A validation exercise of the global field size map revealed satisfactory agreement with control data, particularly given the relatively modest size of the field size data set used to create the map. Both are critical inputs to global agricultural monitoring in the frame of GEOGLAM and will serve the global land modelling and integrated assessment community, in particular for improving land use models that require baseline cropland information. These products are freely available for downloading from the http://cropland.geo-wiki.org website.

Chinese rice production area adaptations to climate changes, 1949-2010.

Climate change has great impact on cropping system. Understanding how the rice production system has historically responded to external forces, both natural and anthropogenic, will provide critical insights into how the system is likely to respond in the future. The observed historic rice movement provides insights into the capability of the rice production system to adapt to climate changes. Using province-level rice production data and historic climate records, here we show that the centroid of Chinese rice production shifted northeastward over 370 km (2.98°N in latitude and 1.88°E in longitude) from 1949 to 2010. Using a linear regression model, we examined the driving factors, in particular climate, behind such rice production movement. While the major driving forces of the rice relocation are such social economic factors as urbanization, irrigation investment, and agricultural or land use policy changes, climate plays a significant role as well. We found that temperature has been a significant and coherent influence on moving the rice center in China and precipitation has had a significant but less spatially coherent influence.

Affordable nutrient solutions for improved food security as evidenced by crop trials.

The continuing depletion of nutrients from agricultural soils in Sub-Saharan African is accompanied by a lack of substantial progress in crop yield improvement. In this paper we investigate yield gaps for corn under two scenarios: a micro-dosing scenario with marginal increases in nitrogen (N) and phosphorus (P) of 10 kg ha(-1) and a larger yet still conservative scenario with proposed N and P applications of 80 and 20 kg ha(-1) respectively. The yield gaps are calculated from a database of historical FAO crop fertilizer trials at 1358 locations for Sub-Saharan Africa and South America. Our approach allows connecting experimental field scale data with continental policy recommendations. Two critical findings emerged from the analysis. The first is the degree to which P limits increases in corn yields. For example, under a micro-dosing scenario, in Africa, the addition of small amounts of N alone resulted in mean yield increases of 8% while the addition of only P increased mean yields by 26%, with implications for designing better balanced fertilizer distribution schemes. The second finding was the relatively large amount of yield increase possible for a small, yet affordable amount of fertilizer application. Using African and South American fertilizer prices we show that the level of investment needed to achieve these results is considerably less than 1% of Agricultural GDP for both a micro-dosing scenario and for the scenario involving higher yet still conservative fertilizer application rates. In the latter scenario realistic mean yield increases ranged between 28 to 85% in South America and 71 to 190% in Africa (mean plus one standard deviation). External investment in this low technology solution has the potential to kick start development and could complement other interventions such as better crop varieties and improved economic instruments to support farmers.

A hybrid wetland map for China: a synergistic approach using census and spatially explicit datasets.

Wetlands play important ecological, economic, and cultural roles in societies around the world. However, wetland degradation has become a serious ecological issue, raising the global sustainability concern. An accurate wetland map is essential for wetland management. Here we used a fuzzy method to create a hybrid wetland map for China through the combination of five existing wetlands datasets, including four spatially explicit wetland distribution data and one wetland census. Our results show the total wetland area is 384,864 km(2), 4.08% of China's national surface area. The hybrid wetland map also shows spatial distribution of wetlands with a spatial resolution of 1 km. The reliability of the map is demonstrated by comparing it with spatially explicit datasets on lakes and reservoirs. The hybrid wetland map is by far the first wetland mapping that is consistent with the statistical data at the national and provincial levels in China. It provides a benchmark map for research on wetland protection and management. The method presented here is applicable for not only wetland mapping but also for other thematic mapping in China and beyond.

A high-resolution assessment on global nitrogen flows in cropland.

Crop production is the single largest cause of human alteration of the global nitrogen cycle. We present a comprehensive assessment of global nitrogen flows in cropland for the year 2000 with a spatial resolution of 5 arc-minutes. We calculated a total nitrogen input (IN) of 136.60 trillion grams (Tg) of N per year, of which almost half is contributed by mineral nitrogen fertilizers, and a total nitrogen output (OUT) of 148.14 Tg of N per year, of which 55% is uptake by harvested crops and crop residues. We present high-resolution maps quantifying the spatial distribution of nitrogen IN and OUT flows, soil nitrogen balance, and surface nitrogen balance. The high-resolution data are aggregated at the national level on a per capita basis to assess nitrogen stress levels. The results show that almost 80% of African countries are confronted with nitrogen scarcity or nitrogen stress problems, which, along with poverty, cause food insecurity and malnutrition. The assessment also shows a global average nitrogen recovery rate of 59%, indicating that nearly two-fifths of nitrogen inputs are lost in ecosystems. More effective management of nitrogen is essential to reduce the deleterious environmental consequences.