Novel multimodel ensemble approach to evaluate the sole effect of elevated CO2 on winter wheat productivity

Ahmed, Mukhtar; Stöckle, Claudio O.; Nelson, Roger; Higgins, Stewart S.; Ahmad, Shakeel; Raza, Muhammad Ali

doi:10.1038/s41598-019-44251-x

Cited by 52 publications

(10 citation statements)

References 98 publications

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“…Grain formation of wheat occurs during March at both study regions, under either semi-arid or arid climatic conditions. Usually, mid-March high temperature currently has a negative impact on grain size and ultimately on grain yield, as it has also been depicted in previous studies under rainfed climatic conditions [38][39][40][41][42]. In the future, March could have worse effects than the current conditions on the final grain yield of wheat.…”

Section: Future Climate and Wheat Grain Yieldmentioning

confidence: 66%

Effect of Temperature on Sowing Dates of Wheat under Arid and Semi-Arid Climatic Regions and Impact Quantification of Climate Change through Mechanistic Modeling with Evidence from Field

et al. 2021

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Rising temperature from climate change is the most threatening factor worldwide for crop production. Sustainable wheat production is a challenge due to climate change and variability, which is ultimately a serious threat to food security in Pakistan. A series of field experiments were conducted during seasons 2013–2014 and 2014–2015 in the semi-arid (Faisalabad) and arid (Layyah) regions of Punjab-Pakistan. Three spring wheat genotypes were evaluated under eleven sowing dates from 16 October to 16 March, with an interval of 14–16 days in the two regions. Data for the model calibration and evaluation were collected from field experiments following the standard procedures and protocols. The grain yield under future climate scenarios was simulated by using a well-calibrated CERES-wheat model included in DSSAT v4.7. Future (2051–2100) and baseline (1980–2015) climatic data were simulated using 29 global circulation models (GCMs) under representative concentration pathway (RCP) 8.5. These GCMs were distributed among five quadrants of climatic conditions (Hot/Wet, Hot/Dry, Cool/Dry, Cool/Wet, and Middle) by a stretched distribution approach based on temperature and rainfall change. A maximum of ten GCMs predicted the chances of Middle climatic conditions during the second half of the century (2051–2100). The average temperature during the wheat season in a semi-arid region and arid region would increase by 3.52 °C and 3.84 °C, respectively, under Middle climatic conditions using the RCP 8.5 scenario during the second half-century. The simulated grain yield was reduced by 23.5% in the semi-arid region and 35.45% in the arid region under Middle climatic conditions (scenario). Mean seasonal temperature (MST) of sowing dates ranged from 16 to 27.3 °C, while the mean temperature from the heading to maturity (MTHM) stage was varying between 12.9 to 30.4 °C. Coefficients of determination (R2) between wheat morphology parameters and temperature were highly significant, with a range of 0.84–0.96. Impacts of temperature on wheat sown on 15 March were found to be as severe as to exterminate the crop before heading. The spikes and spikelets were not formed under a mean seasonal temperature higher than 25.5 °C. In a nutshell, elevated temperature (3–4 °C) till the end-century can reduce grain yield by about 30% in semi-arid and arid regions of Pakistan. These findings are crucial for growers and especially for policymakers to decide on sustainable wheat production for food security in the region.

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Section: Future Climate and Wheat Grain Yieldmentioning

confidence: 66%

Effect of Temperature on Sowing Dates of Wheat under Arid and Semi-Arid Climatic Regions and Impact Quantification of Climate Change through Mechanistic Modeling with Evidence from Field

et al. 2021

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“…These models also consider different socio-economic projections, including income and population growth, energy use, and industrial growth to predict earth's future climate. These global climate projections are then used by bio-physical scientists in different crop models to simulate biological processes of crop growth and productivity [3][4][5][6][7][8][9][10][11][12][13]. They provide the estimated impact of climate change on crop yield and human health.…”

Section: Introductionmentioning

confidence: 99%

Economic Effects of Climate Change-Induced Loss of Agricultural Production by 2050: A Case Study of Pakistan

et al. 2020

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This research combined global climate, crop and economic models to examine the economic impact of climate change-induced loss of agricultural productivity in Pakistan. Previous studies conducted systematic model inter-comparisons, but results varied widely due to differences in model approaches, research scenarios and input data. This paper extends that analysis in the case of Pakistan by taking yield decline output of the Decision Support System for Agrotechnology Transfer (DSSAT) for CERES-Wheat, CERES-Rice and Agricultural Production Systems Simulator (APSIM) crop models as an input in the global economic model to evaluate the economic effects of climate change-induced loss of crop production by 2050. Results showed that climate change-induced loss of wheat and rice crop production by 2050 is 19.5 billion dollars on Pakistan’s Real Gross Domestic Product coupled with an increase in commodity prices followed by a notable decrease in domestic private consumption. However, the decline in the crops’ production not only affects the economic agents involved in the agriculture sector of the country, but it also has a multiplier effect on industrial and business sectors. A huge rise in commodity prices will create a great challenge for the livelihood of the whole country, especially for urban households. It is recommended that the government should have a sound agricultural policy that can play a role in influencing its ability to adapt successfully to climate change as adaption is necessary for high production and net returns of the farm output.

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“…The ability of APSIM-Wheat model to predict yield in the semi-arid environment was confirmed by previous studies 91 – 95 . Application of APSIM-Wheat for grain yield simulation showed reasonable predictive results not only in semi-arid climate 43 , 46 , 96 – 99 , but also in arid 44 , 45 , 100 and Mediterranean 41 , 42 , 101 – 103 environments.…”

Section: Discussionmentioning

confidence: 89%

“…In addition, the results of predictions of the effect of sowing date on wheat yield using APSIM model were also consistent with many of the findings of simulations using other crop models in the semi-arid environment 34 , 115 – 118 . Therefore, extended life duration and favorable temperature especially at the grain filling stage, might be the main reason for the higher grain yield in early sowing dates 43 , 119 , 120 . While, delaying the sowing date beyond the optimum sowing date led to reduced grain yield, due to a shorter vegetative growth period of wheat 115 , 121 .…”

Section: Discussionmentioning

confidence: 99%

Wheat (Triticum aestivum) adaptability evaluation in a semi-arid region of Central Morocco using APSIM model

Briak

Kebede

2021

Sci Rep

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In this study, we evaluated the suitability of semi-arid region of Central Morocco for wheat production using Agricultural Production Systems sIMulator (APSIM) considering weather, soil properties and crop management production factors. Model calibration was carried out using data collected from field trials. A quantitative statistics, i.e., root mean square error (RMSE), Nash–Sutcliffe efficiency (NSE), and index of agreement (d) were used in model performance evaluation. Furthermore, series of simulations were performed to simulate the future scenarios of wheat productivity based on climate projection; the optimum sowing date under water deficit condition and selection of appropriate wheat varieties. The study showed that the performance of the model was fairly accurate as judged by having RMSE = 0.13, NSE = 0.95, and d = 0.98. The realization of future climate data projection and their integration into the APSIM model allowed us to obtain future scenarios of wheat yield that vary between 0 and 2.33 t/ha throughout the study period. The simulated result confirmed that the yield obtained from plots seeded between 25 October and 25 November was higher than that of sown until 05 January. From the several varieties tested, Hartog, Sunstate, Wollaroi, Batten and Sapphire were yielded comparatively higher than the locale variety Marzak. In conclusion, APSIM-Wheat model could be used as a promising tool to identify the best management practices such as determining the sowing date and selection of crop variety based on the length of the crop cycle for adapting and mitigating climate change.

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Novel multimodel ensemble approach to evaluate the sole effect of elevated CO2 on winter wheat productivity

Cited by 52 publications

References 98 publications

Effect of Temperature on Sowing Dates of Wheat under Arid and Semi-Arid Climatic Regions and Impact Quantification of Climate Change through Mechanistic Modeling with Evidence from Field

Effect of Temperature on Sowing Dates of Wheat under Arid and Semi-Arid Climatic Regions and Impact Quantification of Climate Change through Mechanistic Modeling with Evidence from Field

Economic Effects of Climate Change-Induced Loss of Agricultural Production by 2050: A Case Study of Pakistan

Wheat (Triticum aestivum) adaptability evaluation in a semi-arid region of Central Morocco using APSIM model

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