Global spatially explicit yield gap time trends reveal regions at risk of future crop yield stagnation.

Yield gaps, here defined as the difference between actual and attainable yields, provide a framework for assessing opportunities to increase agricultural productivity. Previous global assessments, centred on a single year, were unable to identify temporal variation. Here we provide a spatially and temporally comprehensive analysis of yield gaps for ten major crops from 1975 to 2010. Yield gaps have widened steadily over most areas for the eight annual crops and remained static for sugar cane and oil palm. We developed a three-category typology to differentiate regions of 'steady growth' in actual and attainable yields, 'stalled floor' where yield is stagnated and 'ceiling pressure' where yield gaps are closing. Over 60% of maize area is experiencing 'steady growth', in contrast to ∼12% for rice. Rice and wheat have 84% and 56% of area, respectively, experiencing 'ceiling pressure'. We show that 'ceiling pressure' correlates with subsequent yield stagnation, signalling risks for multiple countries currently realizing gains from yield growth.

Increased probability of hot and dry weather extremes during the growing season threatens global crop yields.

Although extreme weather events recur periodically everywhere, the impacts of their simultaneous occurrence on crop yields are globally unknown. In this study, we estimate the impacts of combined hot and dry extremes as well as cold and wet extremes on maize, rice, soybean, and wheat yields using gridded weather data and reported crop yield data at the global scale for 1980-2009. Our results show that co-occurring extremely hot and dry events have globally consistent negative effects on the yields of all inspected crop types. Extremely cold and wet conditions were observed to reduce crop yields globally too, although to a lesser extent and the impacts being more uncertain and inconsistent. Critically, we found that over the study period, the probability of co-occurring extreme hot and dry events during the growing season increased across all inspected crop types; wheat showing the largest, up to a six-fold, increase. Hence, our study highlights the potentially detrimental impacts that increasing climate variability can have on global food production.

Crop Yield Loss Risk Is Modulated by Anthropogenic Factors.

High crop yield variation between years-caused by extreme shocks on the food production system such as extreme weather-can have substantial effects on food production. This in turn introduces vulnerabilities into the global food system. To mitigate the effects of these shocks, there is a clear need to understand how different adaptive capacity measures link to crop yield variability. While existing literature provides many local-scale studies on this linkage, no comprehensive global assessment yet exists. We assessed reported crop yield variation for wheat, maize, soybean, and rice for the time period 1981-2009 by measuring both yield loss risk (variation in negative yield anomalies considering all years) and changes in yields during "dry" shock and "hot" shock years. We used the machine learning algorithm XGBoost to assess the explanatory power of selected gridded indicators of anthropogenic factors globally (i.e., adaptive capacity measures such as the human development index, irrigation infrastructure, and fertilizer use) on yield variation at a 0.5° resolution within climatically similar regions (to rule out the role of average climate conditions). We found that the anthropogenic factors explained 40%-60% of yield loss risk variation across the whole time period, whereas the factors provided noticeably lower (5%-20%) explanatory power during shock years. On a continental scale, especially in Europe and Africa, the factors explained a high proportion of the yield loss risk variation (up to around 80%). Assessing crop production vulnerabilities on global scale provides supporting knowledge to target specific adaptation measures, thus contributing to global food security.

Should Gene Editing Be Used to Develop Crops for Continuous-Living-Cover Agriculture? A Multi-Sector Stakeholder Assessment Using a Cooperative Governance Approach.

Continuous-living-cover (CLC) agriculture integrates multiple crops to create diversified agroecosystems in which soils are covered by living plants across time and space continuously. CLC agriculture can greatly improve production of many different ecosystem services from agroecosystems, including climate adaptation and mitigation. To go to scale, CLC agriculture requires crops that not only provide continuous living cover but are viable in economic and social terms. At present, lack of such viable crops is strongly limiting the scaling of CLC agriculture. Gene editing (GE) might provide a powerful tool for developing the crops needed to expand CLC agriculture to scale. To assess this possibility, a broad multi-sector deliberative group considered the merits of GE-relative to alternative plant-breeding methods-as means for improving crops for CLC agriculture. The group included many of the sectors whose support is necessary to scaling agricultural innovations, including actors involved in markets, finance, policy, and R&D. In this article, we report findings from interviews and deliberative workshops. Many in the group were enthusiastic about prospects for applications of GE to develop crops for CLC agriculture, relative to alternative plant-breeding options. However, the group noted many issues, risks, and contingencies, all of which are likely to require responsive and adaptive management. Conversely, if these issues, risks, and contingencies cannot be managed, it appears unlikely that a strong multi-sector base of support can be sustained for such applications, limiting their scaling. Emerging methods for responsible innovation and scaling have potential to manage these issues, risks, and contingencies; we propose that outcomes from GE crops for CLC agriculture are likely to be much improved if these emerging methods are used to govern such projects. However, both GE of CLC crops and responsible innovation and scaling are unrefined innovations. Therefore, we suggest that the best pathway for exploring GE of CLC crops is to intentionally couple implementation and refinement of both kinds of innovations. More broadly, we argue that such pilot projects are urgently needed to navigate intensifying grand challenges around food and agriculture, which are likely to create intense pressures to develop genetically-engineered agricultural products and equally intense social conflict.

Crop harvests for direct food use insufficient to meet the UN's food security goal.

Rising competition for crop usage presents policy challenges exacerbated by poor understanding of where crops are harvested for various uses. Here we create high-resolution global maps showing where crops are harvested for seven broad use categories-food, feed, processing, export, industrial, seed and losses. Yields for food crops are low relative to other crop-use categories. It is unlikely, given current trends, that the minimum calorie requirement to eliminate projected food undernourishment by 2030 will be met through crops harvested for direct food consumption, although enough calories will be harvested across all usages. Sub-Saharan African nations will probably fall short of feeding their increased population and eliminating undernourishment in 2030, even if all harvested calories are used directly as food.

Sensitivity of global major crop yields to climate variables: A non-parametric elasticity analysis.

Climate variability controls crop yield variability with impacts on food security at the local, regional and global levels. This study uses non-parametric elasticity to investigate the sensitivity of crop yields of the top four global crops (wheat, rice, maize, and soybean) to three climate variables (precipitation (PRE), potential evapotranspiration (PET), and mean air temperature (TMP)). Trends and serial correlations exist in both climate variables and crop yields over the study period (1961 to 2014). To overcome this limitation, the Trend Free Pre-Whitening (TFPW) method was applied. Crop yields are most sensitive to TMP globally. But the exact sensitivity varies across continents. The highest sensitivity regions are located in parts of the Southeast Asia. Wheat yields are more sensitive to TMP in Western Europe and Northern America, whereas maize has higher sensitivity to TMP for regions located in South America and parts of Eastern and Western Africa. Soybean is more sensitive in North and South America. The elasticities of wheat and rice yields to TMP are negative in most of the regions (i.e. increased TMP decreases yield), whereas maize witnessed positive and soybean witnessed mixed positive and negative signals depending on the region. PRE has lower influence on crop yields. The non-parametric elasticity concept is a simple and an efficient approach that complements the existing linear models methods used to detect climate change impacts on crop yields and can be used to investigate the future consequences of climate change on local to global scale agricultural production.

Climate adaptation by crop migration.

Many studies have estimated the adverse effects of climate change on crop yields, however, this literature almost universally assumes a constant geographic distribution of crops in the future. Movement of growing areas to limit exposure to adverse climate conditions has been discussed as a theoretical adaptive response but has not previously been quantified or demonstrated at a global scale. Here, we assess how changes in rainfed crop area have already mediated growing season temperature trends for rainfed maize, wheat, rice, and soybean using spatially-explicit climate and crop area data from 1973 to 2012. Our results suggest that the most damaging impacts of warming on rainfed maize, wheat, and rice have been substantially moderated by the migration of these crops over time and the expansion of irrigation. However, continued migration may incur substantial environmental costs and will depend on socio-economic and political factors in addition to land suitability and climate.

Climate change has likely already affected global food production.

Crop yields are projected to decrease under future climate conditions, and recent research suggests that yields have already been impacted. However, current impacts on a diversity of crops subnationally and implications for food security remains unclear. Here, we constructed linear regression relationships using weather and reported crop data to assess the potential impact of observed climate change on the yields of the top ten global crops-barley, cassava, maize, oil palm, rapeseed, rice, sorghum, soybean, sugarcane and wheat at ~20,000 political units. We find that the impact of global climate change on yields of different crops from climate trends ranged from -13.4% (oil palm) to 3.5% (soybean). Our results show that impacts are mostly negative in Europe, Southern Africa and Australia but generally positive in Latin America. Impacts in Asia and Northern and Central America are mixed. This has likely led to ~1% average reduction (-3.5 X 1013 kcal/year) in consumable food calories in these ten crops. In nearly half of food insecure countries, estimated caloric availability decreased. Our results suggest that climate change has already affected global food production.

Future warming increases probability of globally synchronized maize production shocks.

Meeting the global food demand of roughly 10 billion people by the middle of the 21st century will become increasingly challenging as the Earth's climate continues to warm. Earlier studies suggest that once the optimum growing temperature is exceeded, mean crop yields decline and the variability of yield increases even if interannual climate variability remains unchanged. Here, we use global datasets of maize production and climate variability combined with future temperature projections to quantify how yield variability will change in the world's major maize-producing and -exporting countries under 2 °C and 4 °C of global warming. We find that as the global mean temperature increases, absent changes in temperature variability or breeding gains in heat tolerance, the coefficient of variation (CV) of maize yields increases almost everywhere to values much larger than present-day values. This higher CV is due both to an increase in the SD of yields and a decrease in mean yields. For the top four maize-exporting countries, which account for 87% of global maize exports, the probability that they have simultaneous production losses greater than 10% in any given year is presently virtually zero, but it increases to 7% under 2 °C warming and 86% under 4 °C warming. Our results portend rising instability in global grain trade and international grain prices, affecting especially the ∼800 million people living in extreme poverty who are most vulnerable to food price spikes. They also underscore the urgency of investments in breeding for heat tolerance.

Climate variation explains a third of global crop yield variability.

Many studies have examined the role of mean climate change in agriculture, but an understanding of the influence of inter-annual climate variations on crop yields in different regions remains elusive. We use detailed crop statistics time series for ~13,500 political units to examine how recent climate variability led to variations in maize, rice, wheat and soybean crop yields worldwide. While some areas show no significant influence of climate variability, in substantial areas of the global breadbaskets, >60% of the yield variability can be explained by climate variability. Globally, climate variability accounts for roughly a third (~32-39%) of the observed yield variability. Our study uniquely illustrates spatial patterns in the relationship between climate variability and crop yield variability, highlighting where variations in temperature, precipitation or their interaction explain yield variability. We discuss key drivers for the observed variations to target further research and policy interventions geared towards buffering future crop production from climate variability.

Direct human influence on atmospheric CO2 seasonality from increased cropland productivity.

Ground- and aircraft-based measurements show that the seasonal amplitude of Northern Hemisphere atmospheric carbon dioxide (CO2) concentrations has increased by as much as 50 per cent over the past 50 years. This increase has been linked to changes in temperate, boreal and arctic ecosystem properties and processes such as enhanced photosynthesis, increased heterotrophic respiration, and expansion of woody vegetation. However, the precise causal mechanisms behind the observed changes in atmospheric CO2 seasonality remain unclear. Here we use production statistics and a carbon accounting model to show that increases in agricultural productivity, which have been largely overlooked in previous investigations, explain as much as a quarter of the observed changes in atmospheric CO2 seasonality. Specifically, Northern Hemisphere extratropical maize, wheat, rice, and soybean production grew by 240 per cent between 1961 and 2008, thereby increasing the amount of net carbon uptake by croplands during the Northern Hemisphere growing season by 0.33 petagrams. Maize alone accounts for two-thirds of this change, owing mostly to agricultural intensification within concentrated production zones in the midwestern United States and northern China. Maize, wheat, rice, and soybeans account for about 68 per cent of extratropical dry biomass production, so it is likely that the total impact of increased agricultural production exceeds the amount quantified here.

Leverage points for improving global food security and the environment.

Achieving sustainable global food security is one of humanity's contemporary challenges. Here we present an analysis identifying key "global leverage points" that offer the best opportunities to improve both global food security and environmental sustainability. We find that a relatively small set of places and actions could provide enough new calories to meet the basic needs for more than 3 billion people, address many environmental impacts with global consequences, and focus food waste reduction on the commodities with the greatest impact on food security. These leverage points in the global food system can help guide how nongovernmental organizations, foundations, governments, citizens' groups, and businesses prioritize actions.

Yield Trends Are Insufficient to Double Global Crop Production by 2050.

Several studies have shown that global crop production needs to double by 2050 to meet the projected demands from rising population, diet shifts, and increasing biofuels consumption. Boosting crop yields to meet these rising demands, rather than clearing more land for agriculture has been highlighted as a preferred solution to meet this goal. However, we first need to understand how crop yields are changing globally, and whether we are on track to double production by 2050. Using ∼2.5 million agricultural statistics, collected for ∼13,500 political units across the world, we track four key global crops-maize, rice, wheat, and soybean-that currently produce nearly two-thirds of global agricultural calories. We find that yields in these top four crops are increasing at 1.6%, 1.0%, 0.9%, and 1.3% per year, non-compounding rates, respectively, which is less than the 2.4% per year rate required to double global production by 2050. At these rates global production in these crops would increase by ∼67%, ∼42%, ∼38%, and ∼55%, respectively, which is far below what is needed to meet projected demands in 2050. We present detailed maps to identify where rates must be increased to boost crop production and meet rising demands.

Recent patterns of crop yield growth and stagnation.

In the coming decades, continued population growth, rising meat and dairy consumption and expanding biofuel use will dramatically increase the pressure on global agriculture. Even as we face these future burdens, there have been scattered reports of yield stagnation in the world's major cereal crops, including maize, rice and wheat. Here we study data from ∼2.5 million census observations across the globe extending over the period 1961-2008. We examined the trends in crop yields for four key global crops: maize, rice, wheat and soybeans. Although yields continue to increase in many areas, we find that across 24-39% of maize-, rice-, wheat- and soybean-growing areas, yields either never improve, stagnate or collapse. This result underscores the challenge of meeting increasing global agricultural demands. New investments in underperforming regions, as well as strategies to continue increasing yields in the high-performing areas, are required.

Closing yield gaps through nutrient and water management.

In the coming decades, a crucial challenge for humanity will be meeting future food demands without undermining further the integrity of the Earth's environmental systems. Agricultural systems are already major forces of global environmental degradation, but population growth and increasing consumption of calorie- and meat-intensive diets are expected to roughly double human food demand by 2050 (ref. 3). Responding to these pressures, there is increasing focus on 'sustainable intensification' as a means to increase yields on underperforming landscapes while simultaneously decreasing the environmental impacts of agricultural systems. However, it is unclear what such efforts might entail for the future of global agricultural landscapes. Here we present a global-scale assessment of intensification prospects from closing 'yield gaps' (differences between observed yields and those attainable in a given region), the spatial patterns of agricultural management practices and yield limitation, and the management changes that may be necessary to achieve increased yields. We find that global yield variability is heavily controlled by fertilizer use, irrigation and climate. Large production increases (45% to 70% for most crops) are possible from closing yield gaps to 100% of attainable yields, and the changes to management practices that are needed to close yield gaps vary considerably by region and current intensity. Furthermore, we find that there are large opportunities to reduce the environmental impact of agriculture by eliminating nutrient overuse, while still allowing an approximately 30% increase in production of major cereals (maize, wheat and rice). Meeting the food security and sustainability challenges of the coming decades is possible, but will require considerable changes in nutrient and water management.

Solutions for a cultivated planet.

Increasing population and consumption are placing unprecedented demands on agriculture and natural resources. Today, approximately a billion people are chronically malnourished while our agricultural systems are concurrently degrading land, water, biodiversity and climate on a global scale. To meet the world's future food security and sustainability needs, food production must grow substantially while, at the same time, agriculture's environmental footprint must shrink dramatically. Here we analyse solutions to this dilemma, showing that tremendous progress could be made by halting agricultural expansion, closing 'yield gaps' on underperforming lands, increasing cropping efficiency, shifting diets and reducing waste. Together, these strategies could double food production while greatly reducing the environmental impacts of agriculture.

The impact of future land use scenarios on runoff volumes in the Muskegon River Watershed.

In this article we compared the response of surface water runoff to a storm event for different rates of urbanization, reforestation and riparian buffer setbacks across forty subwatersheds of the Muskegon River Watershed located in Michigan, USA. We also made these comparisons for several forecasted and one historical land use scenarios (over 140 years). Future land use scenarios to 2040 for forest regrowth, urbanization rates and stream setbacks were developed using the Land Transformation Model (LTM). Historical land use information, from 1900 at 5-year time step intervals, was created using a Backcast land use change model configured using artificial neural network and driven by agriculture and housing census information. We show that (1) controlling the rate of development is the most effective policy option to reduce runoff; (2) establishing setbacks along the mainstem are not as effective as controlling urban growth; (3) reforestation can abate some of the runoff effects from urban growth but not all; (4) land use patterns of the 1970s produced the least amount of runoff in most cases in the Muskegon River Watershed when compared to land use maps from 1900 to 2040; and, (5) future land use patterns here not always lead to increased (worse) runoff than the past. We found that while ten of the subwatersheds contained futures that were worse than any past land use configuration, twenty-five (62.5%) of the subwatersheds produced the greatest amount of runoff in 1900, shortly after the entire watershed was clear-cut. One third (14/40) of the subwatersheds contained the minimum amount of runoff in the 1960s and 1970s, a period when forest amounts were greatest and urban amounts relatively small.