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This paper presents estimates of the effects of changing climate on crop yields for grain corn and soybeans in Ontario, Canada, for 1959–2013. We were able to use a database that is more comprehensive with respect to explanatory variables than some previous efforts had available. Our model includes climate variables, prices, land quality, groundwater level, CO2 concentration, and a time trend. Our results indicate that trends in temperature and precipitation during our study period have not yet resulted in appreciable threats to crop yields in the region. [ABSTRACT FROM AUTHOR]

This paper projects the race between technologically driven increases in crop yields and changing climatic conditions in the central USA, one of the world's most productive agricultural regions. Using the highest, average, and lowest decadal rates of technologically driven increases in crop yields over the 1980 to 2017 period, we develop spatially explicit yield scenarios to the end of the twenty-first century under RCP4.5 and RCP8.5. We find that with static technological innovation, severe climate change will decrease yields by an average of 22.4% (26.1 bu. ac−1) for maize, 27.9% (8.83 bu. ac−1) for soybeans, and 20% (7.14 bu. ac−1) for winter wheat in the central USA; however, with even the lowest rates of technological yield growth, yields increase by an average of 25.0% (40.5 bu. ac−1) for maize and 30.2% (14.2 bu. ac−1) for soybeans. We conclude that technology has the potential to overcome the negative impacts of climate change on the yields of maize, soybeans, and winter wheat in the central USA, but if these increases are to be environmentally sustainable, technological developments must be information-intensive rather than input-intensive. [ABSTRACT FROM AUTHOR]

A long time series in crop yield is usually expressed as a long-term trend and a short-term fluctuation due to agricultural technological advance and climatic anomaly. The real climate risk is related to the short-term fluctuation in crop yield. In the paper, the climate risk of maize yield response to long-term climate variables is tested with the long time series (1961–2015) by a trend base line method. The long time series of maize yield is divided into short-term fluctuating meteorological yield and long-term trend yield. The long time series of climate variables are also divided into fluctuating variables and trend variables. After that, Pearson correlation analysis between fluctuating maize yield and fluctuating climate variables is used to identify risk factor causing maize yield fluctuation. Our results reveal that the main risk factors are night-time precipitation and extreme high temperature in growing season. Comparing climate risks in maize-producing provinces, much more climate risks are identified in some regions such as Liaoning province. The results provide useful information for reducing maize yield loss under climatic change. [ABSTRACT FROM AUTHOR]

Global surface temperature is projected to warm over the coming decades, with regional differences expected in temperature change, rainfall and the frequency of extreme events. Temperature is a major determinant of crop growth and development, affecting planting date, growing season length and yield. We investigated the effects of increments of mean global temperature warming from 0.5 °C to 4 °C on soybean and maize development and yield, both globally and for the main producing countries, and simulated adaptation through changing planting date and variety. Increasing temperature resulted in reduced growing season lengths and ultimately reduced yields for both crops. The global yield for maize decreased as temperature increased, although the severity of the decrease was dependent on geographic region. Small temperature increases of 0.5 °C had no effect on soybean yield, although yield decreased as temperature increased. These negative effects, however, were partly compensated for by the implementation of adaptation strategies including planting earlier in the season and changing variety. The degree of compensation was dependent on geographical area and crop, with maize adaptation delaying the negative effects of temperature on yield, compared to soybean adaptation which increased yield in China, India and Korea DPR as well as delaying the effects in the remaining countries. The results of this paper indicate the degree to which farmer-controlled adaptation strategies can alleviate the negative impacts of increasing temperature on two major crop species. [ABSTRACT FROM AUTHOR]

In the North China Plain, the grain yield of irrigated wheat-maize cropping system has been steadily increasing in the past decades under a significant warming climate. This paper combined regional and field data with modeling to analyze the changes in the climate in the last 40 years, and to investigate the influence of changes in crop varieties and management options to crop yield. In particular, we examined the impact of a planned adaptation strategy to climate change -'Double-Delay' technology, i.e., delay both the sowing time of wheat and the harvesting time of maize, on both wheat and maize yield. The results show that improved crop varieties and management options not only compensated some negative impact of reduced crop growth period on crop yield due to the increase in temperature, they have contributed significantly to crop yield increase. The increase in temperature before over-wintering stage enabled late sowing of winter wheat and late harvesting of maize, leading to overall 4-6% increase in total grain yield of the wheat-maize system. Increased use of farming machines and minimum tillage technology also shortened the time for field preparation from harvest time of summer maize to sowing time of winter wheat, which facilitated the later harvest of summer maize. [ABSTRACT FROM AUTHOR]

Rising temperatures and more frequent droughts caused by global climate change reduce yields and increase climate risk, especially in rain-fed agriculture. Together with scarce land and water resources, this poses a serious threat to food security. Field experiments have shown that relay intercropping systems under irrigated conditions can improve productivity. However, little is known whether these improvements could also be obtained with simultaneous intercropping in rain-fed agriculture under water-limited conditions. To investigate this question, we analyzed a maize/soybean simultaneous intercropping system, using a modeling approach. A light interception model for strip intercrops was implemented into the APSIM classic model for simulating crop growth and yield in strip-intercropped maize and soybean and then calibrated and validated using field experiments conducted from 2017 to 2019 at 4 sites in Northeast China. We then ran a simulation using climatic data (1961–2020) from these sites. Model validation showed good agreements between observations and simulations. The results obtained from our simulation over the period from 1961 to 2020 showed that intercropping was predicted to increase total yields by 41.3% and subsequently enhanced total economic revenue by 23.8% compared to sole systems. It also reduced yield gap of maize by 33%, soybean by 56%, and the system by 45%. Attainable land equivalent ratio (LER) under rain-fed conditions was 1.27 over 60 years across the 4 sites, with a relative yield gain of maize of 0.35 and a relative yield loss of soybean of 0.08. Attainable LER was higher than potential LER. Yields and LER were significantly higher between 1991 and 2020, indicating a potential increase in land productivity with intercropping under a warming climate. Our results thus suggest that simultaneous intercropping offers great opportunities for yield enhancement in rain-fed agriculture under global climate change. [ABSTRACT FROM AUTHOR]

Plants are constantly threatened by adverse environments including heat stress which can significantly decrease crop yield. Trehalose involvement in plant resistance to heat stress has been reported, but the mechanisms of trehalose-induced plant resistance are unclear. In this study, the role of trehalose in enhancing heat—stressed maize (Zea mays L.) light reaction of photosynthesis was investigated. We observed that exogenously supplied trehalose accelerated photosynthetic electron transport in heat-stressed leaves. We further found that exogenously supplied trehalose under heat stress conditions greatly improved the values of actual photosystem II (PSII) efficiency [Y(II)] and the photochemical quenching coefficient (qP) and accelerated the rate of photosynthetic electron transport from pheophytin (Pheo) to QA to QB in PSII. In addition, exogenously supplied trehalose elevated the rate of cyclic electron flow (CEF), the xanthophyll cycle, ATPase activities, the osmotic component of the trans-thylakoid proton motive force and size of the plastoquinone (PQ) pool and reduced photosystem I (PSI)donor-side limitation. We conclude that exogenously supplied trehalose improves electron transport from Pheo to QA and QA to QB by protecting the oxygen-evolving complex and the PSII reaction center, thereby improving the values of Y(II) and qP during heat stress. Our study reveals a good technological method to improve photosynthetic electron transport in maize under changing climatic conditions like heat. [ABSTRACT FROM AUTHOR]

The fifth assessment report (AR5) predicted that land temperatures would rise faster over Africa than other global averages while changes in rainfall are uncertain across Sub-Saharan Africa. These portend water availability challenges with direct impacts on agricultural production. Existing studies on yield vulnerability in Nigeria are mostly at a national scale, which is not adequate for local decision making. This study provides a spatially explicit model of Maize yield vulnerabilities across the growing areas (GA). Thereby, turning available data into actionable information to support development actions. Yield vulnerability index was constructed as a relationship among exposure, yield sensitivity and adaptive capacity. Exposure was computed as the ratio between long and short-term climatic factors. Yield sensitivities were expressed as the ratio between expected and actual yield. Adaptive capacity was captured using a combination of socio-economic proxies. The result shows that Maize yields were vulnerable to climate variability across most of the GAs. Exposure values indicate a very high level of climate variability with the northern region more exposed. Yield sensitivity ranges between ranges 0.47 and 0.95, and highest along the northern extremes, moderate sensitivities were observed across large tracts of the north-west, northeast, south-east and south–south geopolitical regions. Adaptive capacity is highly variable ranging between 0.27 and 1. Yield vulnerability ranges between 0.46 and 1.51. The general assumption of a north–south divide for yield vulnerability was invalidated. Vulnerability is more disparate beyond latitudinal differences. The model presented, creates a framework to support targeted response, and opportunity for building resilience to climate change impact for crop yield. [ABSTRACT FROM AUTHOR]

Drought, which negatively affects crop yields, is expected to intensify in the future and will continue to threaten food security. Understanding crop yield responses to drought is essential for seeking more effective strategic adaptations and for reducing the risk of yield failure. However, how to regionally quantify drought-induced yield loss rates remains unclear. We addressed this gap through studying summer maize cultivated in the Huang-Huai-Hai farming region of China during 1981–2010. By incorporating yearly phenological data and dividing the growing season into the vegetative stage and reproductive stage, we used the standardized precipitation evapotranspiration index (SPEI) that is specific to different growth stages to reflect drought conditions. The spatial-temporal characteristics of drought conditions were further depicted, and the drought-induced yield loss rate was analyzed. The results showed that drought was unevenly and spatially distributed throughout the whole region, and extreme drought mostly occurred in the northern and northwestern regions even though they have a lower drought frequency. However, the drought tendency was alleviated across the maize growing season since the accumulated precipitation and average daily maximum temperature together determined the direction of drought severity. The drought-induced yield loss rate is related to both the intensification of extreme drought and the local precipitation conditions. These findings highlight the potential incentive of the drought-induced yield loss rate, and emphasize that innovation on farming activity is urgently needed to enhance maize productivity in regions with overexploited groundwater. [ABSTRACT FROM AUTHOR]

Climate change and variability are major threats to crop productivity. Crop models are being used worldwide for decision support system for crop management under changing climatic scenarios. Two-year field experiments were conducted at the Water Management Research Center (WMRC), University of Agriculture Faisalabad, Pakistan, to evaluate the application of CERES-Maize model for climate variability assessment under semi-arid environment. Experimental treatments included four sowing dates (27 January, 16 February, 8 March, and 28 March) with three maize hybrids (Pioneer-1543, Mosanto-DK6103, Syngenta-NK8711), adopted at farmer fields in the region. Model was calibrated with each hybrid independently using data of best sowing date (27 January) during the year 2015 and then evaluated with the data of 2016 and remaining sowing dates. Performance of model was evaluated by statistical indices. Model showed reliable information with phenological stages. Model predicted days to anthesis and maturity with lower RMSE (< 2 days) during both years. Model prediction for biological yield and grain yield were reasonably good with RMSE values of 963 and 451 kg ha−1, respectively. Model was further used to assess climate variability. Historical climate data (1980-2016) were used as input to simulate the yield for each year. Results showed that days to anthesis and maturity were negatively correlated with increase in temperature and coefficient of regression ranged from 0.63 to 0.85, while its values were 0.76 to 0.89 kg ha−1 for grain yield and biological yield, respectively. Sowing of maize hybrids (Pioneer-1543 and Mosanto-DK6103) can be recommended for the sowing on 17 January to 6 February at the farmer field for general cultivation in the region. Early sowing before 17 January should be avoided due to severe reduction in grain yield of all hybrids. A good calibrated CERES-Maize model can be used in decision-making for different management practices and assessment of climate variability in the region. [ABSTRACT FROM AUTHOR]

Global weather changes compel agriculture to be adequately productive under diverse and marginal conditions. In maize, modern hybrids fail to meet this requirement. Although breeding has achieved spectacular progress in grain yield per area through improved tolerance to stresses, including intense crowding, yields at low plant population densities remain almost unchanged. Stagnated plant yield potential renders hybrids unable to take advantage of resource abundance at lower populations, designating them population dependent. Consequently, the optimum population varies greatly across environments. Generally, the due population increases as the environmental yield potential gets higher. As a remedy, relatively low populations are recommended for low-input conditions leading to inappropriate population in occasional adequacy of resources and considerable yield loss. For example, for a rain-fed hybrid tested at one location across 11 seasons, crop yield potential and optimum population on the basis of the quadratic yield-plateau model varied from 1,890 to 8,980 kg/ha and 4.56 to 10.2 plants/m, respectively, while 100 % yield loss is computed in the driest season if the optimum population for the most favorable season is used. The article reviews the consequences in terms of crop sustainability under widely diverse environments imposed by climatic changes and proposes crop management strategies to address the situation. The major points are: (1) variable-yielding environments require variable optimum populations, (2) population dependence is an insurmountable barrier in making a decision on plant population, (3) farmers suffer from considerable yield and income loss, (4) estimating the less population-dependent hybrids among the currently cultivated ones is a major challenge for agronomists, and (5) the development of population-neutral hybrids is a fundamental challenge for maize breeding. Honeycomb breeding is a valuable tool to pursue this goal since it places particular emphasis on the so-far stagnated plant yield potential that is essential for population-neutral hybrid development. [ABSTRACT FROM AUTHOR]

Extreme weather conditions can strongly affect agricultural production, with negative impacts that can at times be detected at regional scales. In France, crop yields were greatly influenced by drought and heat stress in 2003 and by extremely wet conditions in 2007. Reported regional maize and wheat yields where historically low in 2003; in 2007 wheat yields were lower and maize yields higher than long-term averages. An analysis with a spatial version (10 × 10 km) of the EPIC crop model was tested with regards to regional crop yield anomalies of wheat and maize resulting from extreme weather events in France in 2003 and 2007, by comparing simulated results against reported regional crops statistics, as well as using remotely sensed soil moisture data. Causal relations between soil moisture and crop yields were specifically analyzed. Remotely sensed (AMSR-E) JJA soil moisture correlated significantly with reported regional crop yield for 2002-2007. The spatial correlation between JJA soil moisture and wheat yield anomalies was positive in dry 2003 and negative in wet 2007. Biweekly soil moisture data correlated positively with wheat yield anomalies from the first half of June until the second half of July in 2003. In 2007, the relation was negative the first half of June until the second half of August. EPIC reproduced observed soil dynamics well, and it reproduced the negative wheat and maize yield anomalies of the 2003 heat wave and drought, as well as the positive maize yield anomalies in wet 2007. However, it did not reproduce the negative wheat yield anomalies due to excessive rains and wetness in 2007. Results indicated that EPIC, in line with other crop models widely used at regional level in climate change studies, is capable of capturing the negative impacts of droughts on crop yields, while it fails to reproduce negative impacts of heavy rain and excessively wet conditions on wheat yield, due to poor representations of critical factors affecting plant growth and management. Given that extreme weather events are expected to increase in frequency and perhaps severity in coming decades, improved model representation of crop damage due to extreme events is warranted in order to better quantify future climate change impacts and inform appropriate adaptation responses. [ABSTRACT FROM AUTHOR]

Summary The crop growth model CERES-Maize is used to estimate the direct (through enhanced fertilisation effect of ambient CO 2) and indirect (through changed climate conditions) effects of increased concentration of atmospheric CO 2 on maize yields. The analysis is based on multi-year crop model simulations run with daily weather series obtained alternatively by a direct modification of observed weather series and by a stochastic weather generator. The crop model is run in two settings: stressed yields are simulated in water and nutrient limited conditions, potential yields in water and nutrient unlimited conditions. The climate change scenario was constructed using the output from the ECHAM3/T42 model (temperature), regression relationships between temperature and solar radiation, and an expert judgement (precipitation). Results: (i) After omitting the two most extreme misfits, the standard error between the observed and modelled yields is 11%. (ii) The direct effect of doubled CO 2: The stressed yields would increase by 36?41% in the present climate and by 61?66% in the 2???CO 2 climate. The potential yields would increase only by 9?10% as the improved water use efficiency does not apply. (iii) The indirect effect of doubled CO 2: The stressed yields would decrease by 27?29% (14?16%) at present (doubled) ambient CO 2 concentration. The increased temperature shortens the phenological phases and does not allow for the optimal development of the crop. The simultaneous decrease of precipitation and increase of temperature and solar radiation deepen the water stress, thereby reducing the yields. The reduction of the potential yields is significantly smaller as the effect of the increased water stress does not apply. (iv) If both direct and indirect effects of doubled CO 2 are considered, the stressed yields should increase by 17?18%, and the potential yields by 5?14%. (v) The decrease of the stressed yields due to the indirect effect may be reduced by applying earlier planting dates. [ABSTRACT FROM AUTHOR]