Increased Yield Variability Research Articles

Biochar effects on crop yield variability

Context or ProblemNumerous studies have demonstrated that biochar application can increase crop yield by improving soil properties and health. Yet, these studies, however, neglected how biochar alters yield variability across years – reflecting the yield stability. Objective or Research questionThis study aimed to investigate the effects of biochar application on crop yield variability. MethodsPublished data from 38 experimental sites were collected from the Web-of-Science. Two-thirds of the data were originated from three main staple crops: maize, wheat, and rice. The remaining were from rapeseed, soybean, sweet potato, and peppermint. Biochar effects on crop yield and its variability as well as their driving factors were analyzed by linear mixed models depending on soil conditions, field management practices, and climate types. ResultsBiochar increased the crop yield globally by 14 %, especially in soils with low pH (< 5.5), low nitrogen (N) and phosphorus (P) inputs (≤ 120 kg N ha−1, < 35 kg P ha−1), with high biochar inputs (≥ 20 Mg ha−1), and under crop rotation. Biochar increased crop yields by 12 % in short-term (≤ 5 years) and 21 % in long-term (> 5 years) experiments. Biochar increased yield variability by 42 % in acidic soils (pH < 5.5) and by 24 % with low N inputs (≤ 120 kg N ha−1), mainly because its liming and fertilization effects were short-lasting within the first few years. The yield variability after biochar application decreased with the increase in mean annual temperature, inter-annual variabilities of temperature and precipitation, but with the decrease in mean annual precipitation in the growing season. Yield variability under biochar increased in short-term experiments by 27 %, but there was no change (0 %) in long-term experiments because of the higher yield gains and resistance to fluctuating weather conditions. Therefore, crop yield variability decreased with increasing yield in long-term experiments. ConclusionsBiochar application increased short-term variability of crop yields, but its long-term variability remained unaffected. Implications or SignificanceThis study highlights that biochar can support steadily future crop production in the long run.

Wheat crop traits conferring high yield potential may also improve yield stability under climate change

Abstract Increasing genetic wheat yield potential is considered by many as critical to increasing global wheat yields and production, baring major changes in consumption patterns. Climate change challenges breeding by making target environments less predictable, altering regional productivity and potentially increasing yield variability. Here we used a crop simulation model solution in the SIMPLACE framework to explore yield sensitivity to select trait characteristics (radiation use efficiency [RUE], fruiting efficiency and light extinction coefficient) across 34 locations representing the world’s wheat-producing environments, determining their relationship to increasing yields, yield variability and cultivar performance. The magnitude of the yield increase was trait-dependent and differed between irrigated and rainfed environments. RUE had the most prominent marginal effect on yield, which increased by about 45 % and 33 % in irrigated and rainfed sites, respectively, between the minimum and maximum value of the trait. Altered values of light extinction coefficient had the least effect on yield levels. Higher yields from improved traits were generally associated with increased inter-annual yield variability (measured by standard deviation), but the relative yield variability (as coefficient of variation) remained largely unchanged between base and improved genotypes. This was true under both current and future climate scenarios. In this context, our study suggests higher wheat yields from these traits would not increase climate risk for farmers and the adoption of cultivars with these traits would not be associated with increased yield variability.

Future climate change significantly alters interannual wheat yield variability over half of harvested areas

Climate change affects the spatial and temporal distribution of crop yields, which can critically impair food security across scales. A number of previous studies have assessed the impact of climate change on mean crop yield and future food availability, but much less is known about potential future changes in interannual yield variability. Here, we evaluate future changes in relative interannual global wheat yield variability (the coefficient of variation (CV)) at 0.25° spatial resolution for two representative concentration pathways (RCP4.5 and RCP8.5). A multi-model ensemble of crop model emulators based on global process-based models is used to evaluate responses to changes in temperature, precipitation, and CO2. The results indicate that over 60% of harvested areas could experience significant changes in interannual yield variability under a high-emission scenario by the end of the 21st century (2066–2095). About 31% and 44% of harvested areas are projected to undergo significant reductions of relative yield variability under RCP4.5 and RCP8.5, respectively. In turn, wheat yield is projected to become more unstable across 23% (RCP4.5) and 18% (RCP8.5) of global harvested areas—mostly in hot or low fertilizer input regions, including some of the major breadbasket countries. The major driver of increasing yield CV change is the increase in yield standard deviation, whereas declining yield CV is mostly caused by stronger increases in mean yield than in the standard deviation. Changes in temperature are the dominant cause of change in wheat yield CVs, having a greater influence than changes in precipitation in 53% and 72% of global harvested areas by the end of the century under RCP4.5 and RCP8.5, respectively. This research highlights the potential challenges posed by increased yield variability and the need for tailored regional adaptation strategies.

Environmental and socio-economic performance of different tillage systems in maize grain production: Application of Life Cycle Assessment and Multi-Criteria Decision Making

The growing need for additional production due to high global food demand should be supplied through sustainable intensification of agriculture. In Poland, conventional tillage with deep full ploughing is still the most common practice, however, it may harm the environment and natural resources. Therefore, this study aimed to evaluate the sustainability of no tillage (NT), reduced tillage (RT) and conventional tillage (CT) in grain maize monoculture based on economic, environmental, and social aspects. Based on the outcomes of long-term field experiments conducted at the Agricultural Experimental Station in Grabów (Mazowieckie Voivodship), life cycle assessment (LCA) and fuzzy analytic hierarchy process (FAHP) were applied to evaluate tillage systems and calculate the criteria weights. Results showed better performance for CT on economic and social criteria while NT and RT had better performances on environmental criteria. The final evaluation illustrated the greatest overall performance for CT followed by RT and NT. Findings emphasized that, in order to achieve a comprehensive view, it is necessary to study the impact of main criteria weights and annual yield variation conditions on the overall performance of alternatives. Sensitivity analysis was conducted combining five weights sets and two production scenarios conditions. The results showed that, except for the environmental criteria, in all other cases CT had the best performance. Moreover, it was illustrated that yield had a significant impact on the overall performance of the tillage systems. The results of final ranking introduced NT with the best performance in a year with the lowest level of grain yield, while on the contrary, under favorable conditions for maximum grain yield, CT was ranked first. According to the obtained results, it is concluded that expectations of climate change leading to increased yield variability may play an important role in the development of conservation tillage systems (RT and NT) in the studied area in Poland.

Economics of Wheat Breeding Strategies: Focusing on Oklahoma Hard Red Winter Wheat

Wheat breeding continues to be an important component of agricultural innovations in the Great Plains region of the US. This paper reviews Oklahoma’s wheat breeding program over the past several decades with an emphasis on the economic aspects and planning of future breeding strategies. Over the past century, Oklahoma’s wheat yields have increased but the productivity gains have been offset in part due to increased yield variability. The shift to improved wheat varieties has resulted in increased susceptibility to plant disease and pest pressure. While a few varieties introduced over the past few decades have dominated the wheat seed market, recent trends indicate producers are adopting a more diverse range of wheat varieties. Producers’ concerns have expanded beyond demands for high yielding varieties to include more market oriented needs to increase protein content and test weight. This paper identifies several key policy instruments that Oklahoma stakeholders and policy makers should consider when planning future breeding strategies. A critical need is to assist Oklahoma producers in adapting to climate change by developing drought and heat resistant wheat varieties. Marketing new varieties would be improved and revenue increased if more innovative pricing structures were adopted to better align producers’ willingness to pay with seed development costs, which could then be re-invested in breeding. Research budgets, which have remained stagnant in real terms, will need to be increased to adequately address producers’ needs into the 21st century.

Modelling crop diversification and association effects in agricultural systems

The need to redesign more sustainable agricultural systems able of producing more, especially through intercropping or agroforestry, cannot be achieved without taking into account the essential aspect of production variability. Yet, although many studies have focused on the effect of intercropping on overall production, the particular issue of production variability in such systems remains relatively unstudied. The approach we propose, for a shift towards sustainable intensification of agricultural systems, considers the dual dimensions of yield and risk in a combined framework for the assessment and the comparison of two diversification strategies: (i) a simple diversification strategy (SDS) considered as an increasing number of crops grown on separate plots within a farm and (ii) an intercropping strategy (IC) considered as a within-plot increased diversity, where more than one species is grown at the same time and place. The two perspectives examined here were Modern Portfolio Theory and Land Equivalent Ratio. The former quantifies the effect of diversification on risk, the latter measures the effect of association on production. This research merges both approaches in a combined framework in order to assess intercropping system performances. By applying our framework to cases selected from the literature, we explored and compared the potential benefits of these two strategies in terms of yield and risk. Results showed that intercropping, in addition to being interesting with regard to yield, can have an additional risk reduction effect compared to a simple diversification strategy. Conversely, some crop mixtures maintained or even increased yield variability. Our work contributes to a better understanding of the possible impacts of diversification strategies on trade-offs between yield and risk, but also underlines the importance of taking yield variability into account in further studies.

Cell Density Effects in Different Cell Culture Media and Their Impact on the Propagation of Foot-And-Mouth Disease Virus.

Foot-and-mouth disease virus (FMDV) is endemic in many parts of the world. Vaccination is an important control measure, limits viral spread, and can help to eradicate the disease. However, vaccination programs are cost-intensive because of the short shelf life of vaccines and the need for frequent re-vaccination. Animal-component-free (ACF) or chemically defined media (CDM) at high cell densities are a promising approach for the production of inexpensive high-quality vaccines, but the occurrence of cell density effects has been reported for various virus-cell systems in vaccine production. For FMDV, the use of CDM or ACF media for vaccine production has not been studied and no information about cell density effects is available. This work describes the propagation of FMDV in ACF or in CDM. Cells were grown at increasing cell densities and either 100% media exchange or addition of 30% fresh media was performed before infection with FMDV. Increasing cell densities reduced the viral titer and increased yield variability in all media except BHK300G. This effect can be mitigated by performing a 100% media exchange before infection or when using the controlled environment of a bioreactor. The media composition and also a fragile relationship between virus and cell metabolism seem to be causal for that phenomenon.

Climate change impacts on hard red spring wheat yield and production risk: evidence from Manitoba, Canada

A Just–Pope production function is employed to investigate the effects of historic weather changes on hard red spring wheat yield variability in Manitoba. Field-level data on wheat yield, proportion of wheat seeded area, and fertilizer inputs from the Manitoba Agricultural Services Corporation were employed to determine how temperature and precipitation affect mean wheat yield and production risk, and how projected climate scenarios impact yield variability in heterogeneous risk areas of Manitoba. Variety richness increases average yield and reduces yield variance while varieties protected by plant breeders’ rights increase yield variance. Phosphorus fertilizer is positively associated with average wheat yield while total precipitation is shown to negatively affect mean yield and positively impact yield variability. June precipitation matters while June and July temperatures negatively affect yield. Projected climate change is expected to increase yield variability in both the medium (2034–2050) and long term (2079–2095), both under low- and high-carbon scenarios with production variance effects differing across crop districts. Adaptation strategies may be required to mitigate yield risk effects of climate change resulting in late seeding decisions from increased spring precipitation.

Sensitivity and requirement of improvements of four soybean crop simulation models for climate change studies in Southern Brazil.

Crop growth models have many uncertainties that affect the yield response to climate change. Based on that, the aim of this study was to evaluate the sensitivity of crop models to systematic changes in climate for simulating soybean attainable yield in Southern Brazil. Four crop models were used to simulate yields: AQUACROP, MONICA, DSSAT, and APSIM, as well as their ensemble. The simulations were performed considering changes of air temperature (0, + 1.5, + 3.0, + 4.5, and + 6.0°C), [CO2] (380, 480, 580, 680, and 780ppm), rainfall (- 30, - 15, 0, + 15, and + 30%), and solar radiation (- 15, 0, + 15), applied to daily values. The baseline climate was from 1961 to 2014, totalizing 53 crop seasons. The crop models simulated a reduction of attainable yield with temperature increase, reaching 2000kgha-1 for the ensemble at + 6°C, mainly due to shorter crop cycle. For rainfall, the yield had a higher rate of reduction when it was diminished than when rainfall was increased. The crop models increased yield variability when solar radiation was changed from - 15 to + 15%, whereas [CO2] rise resulted in yield gains, following an asymptotic response, with a mean increase of 31% from 380 to 680ppm. The models used require further attention to improvements in optimal and maximum cardinal temperature for development rate; runoff, water infiltration, deep drainage, and dynamic of root growth; photosynthesis parameters related to soil water availability; and energy balance of soil-plant system to define leaf temperature under elevated CO2.

Changes in yield variability of major crops for 1981–2010 explained by climate change

While changes in temperature and precipitation extremes are evident, their influence on crop yield variability remains unclear. Here we present a global analysis detecting yield variability change and attributing it to recent climate change using spatially-explicit global data sets of historical yields and an agro-climatic index based on daily weather data. The agro-climatic index used here is the sum of effective global radiation intercepted by the crop canopy during the yield formation stage that includes thresholds for extreme temperatures and extreme soil moisture deficit. Results show that year-to-year variations in yields of maize, soybean, rice and wheat in 1981–2010 significantly decreased in 19%–33% of the global harvested area with varying extent of area by crop. However, in 9%–22% of harvested area, significant increase in yield variability was detected. Major crop-producing regions with increased yield variability include maize and soybean in Argentina and Northeast China, rice in Indonesia and Southern China, and wheat in Australia, France and Ukraine. Examples of relatively food-insecure regions with increased yield variability are maize in Kenya and Tanzania and rice in Bangladesh and Myanmar. On a global scale, over 21% of the yield variability change could be explained by the change in variability of the agro-climatic index. More specifically, the change in variability of temperatures exceeding the optimal range for yield formation was more important in explaining the yield variability change than other abiotic stresses, such as temperature below the optimal range for yield formation and soil water deficit. Our findings show that while a decrease in yield variability is the main trend worldwide across crops, yields in some regions of the world have become more unstable, suggesting the need for long-term global yield monitoring and a better understanding of the contributions of technology, management, policy and climate to ongoing yield variability change.

The role of risk aversion and labor constraints in the adoption of low input practices supported by the CAP green payments in cash crop farms

Since the late 1980s, many alternative practices have been proposed to European farmers to reduce pesticide and input use in general. These practices have been promoted by agro-environmental contracts signed between individual farmers and the European Union and by which farmers engage themselves in changing their practices. The adoption rate of these measures has remained very low in many European regions particularly in Southwestern France. This article aims at stressing the role played by risk attitude and labor constraint in farmers’ adoption decision. After presenting a static theoretical model which assesses the impact of labor constraints and risk attitude on the level of adoption of low input practices supported by agro-environmental contracts, the article proposes a numerical application based on a mathematical programming risk-model implemented on two typical crop farms in South-western France. Three kinds of contracts (no tillage, long rotation, lower pest treatments) are tested, two of them (long rotation and lower pest treatments) aiming at directly reducing input use. The results show that, despite the overall positive impact of alternative practices under contract on environment and farmers’ income, increased yield variability under positive risk aversion and larger labor requirements are actual barriers to adoption.

What would happen to barley production in Finland if global warming exceeded 4 °C? A model-based assessment

In research to date, projected climate change has been considered to be beneficial for agriculture under Nordic conditions, where crop production is mainly limited by low temperatures resulting in short growing seasons. However, with the rapid increases in global mean temperature implied at the high end of the uncertainty range of current projections, which are typically amplified at high latitudes, conditions for crop production could change so dramatically that yields would be reduced, even accounting for the positive effects of CO 2 fertilization. In this study, we used the WOFOST crop growth simulation model to examine crop yield responses to a set of plausible scenarios of climate change for Finland up to 2100, including some that exceed 4 °C global mean temperature increase relative to pre-industrial. We selected spring barley ( Hordeum vulgare L.) as an indicator crop and calculated water-limited yields for two Finnish locations, Jokioinen and Jyväskylä and for a clay and a sandy soil. Scenarios included systematic increases in temperatures, changes in precipitation distribution and altered daily climatic variability using the M&Rfi weather generator. We also examined the effectiveness of a few adaptation options, such as shifts in sowing dates and hypothetical new crop cultivars. Increasing temperature reduced total growth duration and yield considerably, even with adjusted earlier sowing. A reduced number of rainy days had marked negative effects only in combination with increases in temperature of 4 °C or greater, leading to distinctly higher yield losses on the sandy soil than on the clay. Prolonged dry spells clearly increased yield variability. For scenarios with temperature increases of +6 °C and + 7°C, yield losses at Jokioinen were highest; losses at Jyväskylä were generally less pronounced. Neither CO 2 fertilization nor adjusted sowing could compensate the yield losses from temperature changes exceeding +4 °C. On clay soils, yield loss could be compensated by new cultivars. For sandy soils even with new cultivars, there would be yield loss at temperature increases exceeding +3 °C. It can be concluded that the positive effects of climate warming and elevated CO 2 concentrations on cereal production at high latitudes are likely to be reversed at temperature increases exceeding 4 °C, with a high risk of marked yield loss. Only plant breeding efforts aimed at increasing yield potential jointly with drought resistance and adjusted agronomic practices, such as sowing, and adequate nitrogen fertilizer management and plant protection, holds a prospect of partly restoring yield levels and reducing the risks of yield shortfall.

Farm-Level Impacts of Revenue Assurance

With the onset of the 1995 Farm Bill debate, the issue of government intervention and its appropriate levels will most assuredly be debated. Due to the government's historically strong presence in agriculture, it is probable that the government will stay involved. The debate will, therefore, focus on how government policy can most efficiently assist the agricultural sector. While several problems can be identified within the agricultural policy arena, the inherent instability of farm prices and income have been key in justifying government involvement. Stability is significant in reducing economic stress on farm families and minimizing faulty production and investment decisions. Instability in agriculture is caused by a variety of factors. Weather as well as the existence of disease, insects, and other pests increase yield variability and risk to producers. These factors not only lead to variations in individual producer yields, but also affect national crop production and prices. Producer price risk is further increased by the inelastic demand for agricultural products. The combination of yield and price variability results in a high degree of income risk for farmers. The United States has a 60-year tradition of government intervention in stabilizing farm prices and incomes. Supporting farm prices and income became a farm policy goal during the depression conditions of the 1930's and continues to be a priority. The role of government policy in reducing instability is a significant issue for discussion. Government programs that both limit price and income variability and still allow the market to function by sending economic signals to both producers and consumers are difficult to design (Tweeten; Knutson, Penn, and Boehm). The problem of unstable farm prices, yields, and income and the corresponding optimal level of policy intervention are further complicated by government costs. While the relative cost of agricultural outlays as a percentage of the total federal budget was lower in 1993 at 1.5 percent ($20.4 billion) than its former high of 3.7 percent in 1963 and 1964 ($4 billion), agriculture is being forced to succumb o budgetary pressures. Therefore, the problem becomes one of trying to stabilize and support producer incomes and prices at lower government costs. Tweeten contended that uncertainty and instability constitute a potentially large social cost to society. The payoff is great from carefully formulated public policy that reduces instability and provides benefits to producers and consumers in excess of costs. The difficulty lies in determining the appropriate policies and economic levels to provide such results. Therefore, it is necessary to study the policy alternatives and evaluate their stabilizing ability and associated level of government costs. The purpose of this research is to compare the current program to two alternative revenue assurance programs. A simulation model is developed to generate probability distributions of representative farms' gross receipts and government costs. The level of revenue support and the stability of producer revenues and government outlays to individual producers will be compared for the three alternative policies. This comparison shows alternative consequences that legislators must weigh in determining the best policy option for agricultural producers.

The Use of Field Days in Economic Models of Crop Farms

The time available for the completion of field operations, commonly referred to as field days, is important to the economic efficiency of crop farms. The effects of field days on economical cropping decisions is complicated by the significant variation which occurs in field days from season to season and year to year. This paper discusses the use of field days data in economic models of crop farms. It presents two linear programming models of a midwestern U.S. corn (Zea mays L.) and soybean [Glycine max (L.) Merr.] farm. The first model treats field days deterministically, with known values in each production period. The second model treats field days as random variables, using the technique of discrete stochastic programming. Optimal solutions from the two models are compared to demonstrate the economic impacts of field days variability [...]

Effect of changes in interannual climatic variability on CERES-wheat yields: sensitivity and [formula omitted] general circulation model studies

This study concerns the investigation of how changes in climate variability could affect agricultural production. To date very few studies of this effect have been made, whereas changes in climate variability, in addition to changes in mean conditions could have serious effects on crops. Currently there is very little certainty regarding how climate variability will change in a greenhouse-gas-warmed world. In view of this uncertainty, it is desirable to perform sensitivity analyses of how crop-climate models (e.g. the CERES-Wheat model) respond to changes in climate variability. We apply the winter wheat model to two climate stations in the wheat growing region of Kansas. Goodland in the western region, and Topeka in the moister eastern region. Time series of temperature and precipitation, are simulated, systematically changing the interannual variance of the series (from one quarter to four times the actual variance), and determining how the crop climate model responds to these changes. In addition, these variability changes are combined with mean changes of both temperature and precipitation. We then also apply a GCM-derived climate change scenario. Results indicate that it is the relative magnitude of change of the mean and variance of the climate that determines their relative importance to changes in wheat yields. In general increases in variability of temperature and precipitation resulted in significant increases in yield variability and crop failures in the sensitivity experiments, but precipitation changes had a more pronounced effect. In the GCM-derived scenario, mean temperature effects dominate, resulting in increased yield variability and crop failures, because the magnitude of mean change is much greater than the magnitude of variance change. Over all experiments, the importance of considering not only mean but also variance changes of climate variables, when investigating the effect of climate change on wheat yields, is confirmed.

WEATHER SENSITIVITY OF WESTERN CANADA WHEAT YIELD, 1900–1988

Recent work suggests that climate change will impact negatively on Canadian prairie wheat through more severe and frequent droughts and increased yield variability, and adaptive strategies have been called for to meet the coming change. However, previous studies have not determined if climate change has already affected wheat yields, nor has the entire prairie region been examined. Using a prairie wheat yield simulation model (PWYSM) at current (constant) technology, it is shown that the weather as it affects wheat, has had a zero trend over the 1900–1988 period. Also, there is no evidence that yield variability has recently increased. Prairie wheat yields therefore appear so far unconnected to the global warming trend this century, suggesting no current need to adapt to a changing climatic regime. Results also show that, at current technology, departures from mean weather may cause decade-long average yield fluctuations as large as ± 10% from the long-term mean, and climate change effects must be detected against this background fluctuation. Also, a 35% decline in actual wheat yields from the first to fourth decades of this century was not matched by deteriorating weather although weather contributed to the decline, and improved yields since 1940 are not explained by better weather. The study of Williams et al. (1988) concluded that a 1930s type dry spell would reduce Saskatchewan wheat yield by 20%, compared to the 1961–1979 mean That applied only to stubble-sown wheat. When adjusted here for the contribution of fallow-sown wheat, the reduction became 16.7%. With Alberta and Manitoba included, the yield reduction for the whole prairie became 13.8% — in good agreement with a 14.0% reduction obtained with the PWYSM. Yield reductions for Saskatchewan are larger than for the prairie as a whole. The reference period chosen also significantly affects findings, and, because the last decade has been relatively unfavourable, PWYSM results show that 1930s type weather would lower mean prairie wheat yield by only 11.0% relative to the 1979–1988 mean. Grain industry decision makers would more likely refer to the last decade than to a more distant period such as 1961–1979, and applying relative yield reductions to the 1979–1988 mean would result in substantial yield underestimates for drought scenarios. Reference periods must be carefully selected for consistent results. Key words: Climate change, wheat yield

SOURCES OF INCREASED VARIABILITY IN WORLD CEREAL PRODUCTION SINCE THE 1960s

Recent growth in world cereal production has been accompanied by a more than proportional increase in the standard deviation of production. This study applies variance decomposition procedures to data on crop production by major geographical regions of the world to analyse the sources of this increased instability. It is found that the increase in aggregate production variability is predominantly due to increased yield variability and to a simultaneous loss in offsetting patterns of variation in yields between crops and regions. These changes are probably associated with the sharp increase in the variability of world cereal and oil prices since the early 1970s and with the more widespread adoption of improved seed/fertiliser intensive technologies.

Sources of Increased Instability in Indian and U.S. Cereal Production

AbstractRecent growth in Indian and U.S. cereal production has been accompanied by a more than proportional increase in the standard deviation of production. This study applies variance decomposition procedures to state data on crop production to analyze the sources of this increased instability. It is found that production has become significantly more covariate between states and crops, largely because of increased yield variability and a loss in offsetting patterns of variation between crop yields in different states. These changes may be associated with more variable prices, with higher‐yielding technologies, and with a narrowing of the genetic base.