Impacts of mean climate and extreme climate indices on soybean yield and yield components in Northeast China

Guo, Shibo; Guo, Erjing; Zhang, Zhentao; Dong, Meiqi; Wang, Xi; Fu, Zhenzhen; Guan, Kaixin; Zhang, Wenmeng; Zhang, Wenjing; Zhao, Jin; Liu, Zhijuan; Zhao, Chuang; Yang, Xiaoguang

doi:10.1016/j.scitotenv.2022.156284

Cited by 31 publications

(10 citation statements)

References 38 publications

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“…The negative effects of temperature and water s in many areas will, however, exceed the positive effects of CO 2 fertilization, resulting in a negative net change [ 11 , 46 , 47 ]. Similar trends have been reported elsewhere; for example, Guo et al [ 48 ] projected a 49% decrease in soybean yields by 2050 under climate change. There is a need for further studies to evaluate the crossover point where the positive impacts of increased CO 2 are canceled by increased temperatures.…”

Section: Discussionsupporting

confidence: 88%

Use of modelling tools to assess climate change impacts on smallholder oil seed yields in South Africa

Kephe,

Mkuhlani,

Rusere

et al. 2024

PLoS ONE

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Oil seed crops are the second most important field crops after cereals in the agricultural economy globally. The use and demand for oilseed crops such as groundnut, soybean and sunflower have grown significantly, but climate change is expected to alter the agroecological conditions required for oilseed crop production. This study aims to present an approach that utilizes decision-making tools to assess the potential climate change impacts on groundnut, soybean and sunflower yields and the greenhouse gas emissions from the management of the crops. The Decision Support Tool for Agrotechnology Transfer (DSSAT v4.7), a dynamic crop model and the Cool Farm Tool, a GHG calculator, was used to simulate yields and estimate GHG emissions from these crops, respectively. Four representative concentration pathways (RCPs 2.6, 4.5, 6.0, and 8.5), three nitrogen (0, 75, and 150 kg/ha) and phosphorous (0, 30 and 60 P kg/ha) fertilizer rates at three sites in Limpopo, South Africa (Ofcolaco, Syferkuil and Punda Maria) were used in field trials for calibrating the models. The highest yield was achieved by sunflower across all crops, years and sites. Soybean yield is projected to decrease across all sites and scenarios by 2030 and 2050, except at Ofcolaco, where yield increases of at least 15.6% is projected under the RCP 4.5 scenario. Positive climate change impacts are predicted for groundnut at Ofcolaco and Syferkuil by 2030 and 2050, while negative impacts with losses of up to 50% are projected under RCP8.5 by 2050 at Punda Maria. Sunflower yield is projected to decrease across all sites and scenarios by 2030 and 2050. A comparison of the climate change impacts across sites shows that groundnut yield is projected to increase under climate change while notable yield losses are projected for sunflower and soybean. GHG emissions from the management of each crop showed that sunflower and groundnut production had the highest and lowest emissions across all sites respectively. With positive climate change impacts, a reduction of GHG emissions per ton per hectare was projected for groundnuts at Ofcolaco and Syferkuil and for sunflower in Ofcolaco in the future. However, the carbon footprint from groundnut is expected to increase by 40 to 107% in Punda Maria for the period up to 2030 and between 70–250% for 2050, with sunflower following a similar trend. We conclude that climate change will potentially reduce yield for oilseed crops while management will increase emissions. Therefore, in designing adaptation measures, there is a need to consider emission effects to gain a holistic understanding of how both climate change impacts on crops and mitigation efforts could be targeted.

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Section: Discussionsupporting

confidence: 88%

Use of modelling tools to assess climate change impacts on smallholder oil seed yields in South Africa

Kephe,

Mkuhlani,

Rusere

et al. 2024

PLoS ONE

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“…Only when extreme climate occurs during soybean growing season does it affect soybean yield. In this study, we intended to assess the impacts of five types of extreme climate disasters, cold, heat, drought, waterlogging and compound heat-drought, during soybean main growing season (between planting and harvest days) that are relevant to soybean yield [14,24,37]. The soybean growing seasons were from the GEPIC model and were based on the SAGE [38] and the MIRCA2000 [39] crop calendars.…”

Section: Extreme Climate Indicatorsmentioning

confidence: 99%

Coupling Process-Based Crop Model and Extreme Climate Indicators with Machine Learning Can Improve the Predictions and Reduce Uncertainties of Global Soybean Yields

et al. 2022

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Soybean is one of the most important agricultural commodities in the world, thus making it important for global food security. However, widely used process-based crop models, such as the GIS-based Environmental Policy Integrated Climate (GEPIC) model, tend to underestimate the impacts of extreme climate events on soybean, which brings large uncertainties. This study proposed an approach of hybrid models to constrain such uncertainties by coupling the GEPIC model and extreme climate indicators using machine learning. Subsequently, the key extreme climate indicators for the globe and main soybean producing countries are explored, and future soybean yield changes and variability are analyzed using the proposed hybrid model. The results show the coupled GEPIC and Random Forest (GEPIC+RF) model (R: 0.812, RMSD: 0.716 t/ha and rRMSD: 36.62%) significantly eliminated uncertainties and underestimation of climate extremes from the GEPIC model (R: 0.138, RMSD: 1.401 t/ha and rRMSD: 71.57%) compared to the other five hybrid models (R: 0.365–0.612, RMSD: 0.928–1.021 and rRMSD: 47.48–52.24%) during the historical period. For global soybean yield and those in Brazil and Argentina, low-temperature-related indices are the main restriction factors, whereas drought is the constraining factor in the USA and China, and combined drought–heat disaster in India. The GEPIC model would overestimate soybean yields by 13.40–27.23%. The GEPIC+RF model reduced uncertainty by 28.45–41.83% for the period of 2040–2099. Our results imply that extreme climate events will possibly cause more losses in soybean in the future than we have expected, which would help policymakers prepare for future agriculture risk and food security under climate change.

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“…Climate change scenarios project high probabilities of decreases in rainfall in arid and semiarid lands around the world, with potential increase in the frequency and intensity of extreme climatic events such as prolonged droughts, floods, and heat waves (Wang et al., 2018; Zhang et al., 2019). The occurrence of combined extreme climatic events will result in a pronounced negative effect on crops yield and land productivity (Guo et al., 2022; Ortiz‐Bobea et al., 2021).…”

Section: Introductionmentioning

confidence: 99%

“…To date, increases in crop yields have been driven by Green Revolution cultivars that lent themselves to more intensive irrigation, fertilization, and mechanization (Garcia et al., 2023). However, in recent years, yield per hectare has plateaued while human population growth and food demand are increasing (Beltran‐Peña et al., 2020; Guo et al., 2022). Further investment in the current strategies may not suffice to further boost yield to meet future food demand due to their high energy consumption, and great economic and harmful environmental costs (Beltran‐Peña & D'Odorico, 2022; Mahankale, 2023).…”

Section: Introductionmentioning

confidence: 99%

Potential use of wild Onobrychis species for climate change mitigation and adaptation

Sakhraoui,

Ltaeif,

Sakhraoui

et al. 2023

Crop Science

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Climate change is threatening environmental and nutritional security. In this scenario, forage crops and their wild relatives may contribute to maintain ecosystem services and minimize the effects of global warming. We reviewed the literature regarding the ecological, agronomic and nutraceutical values of wild Onobrychis Miller species (sainfoins, Family Fabaceae). We also discuss their application prospect and existing problems hampering their widespread domestication. Wild species of the genus Onobrychis have certain interesting agronomic and ecological features such as perenniality, deep root system and high stress tolerance, which make them suitable for future cultivation under climate change. Wild Onobrychis species are multipurpose species which can be utilized for fodder and honey production under harsh environmental conditions. In addition, wild Onobrychis species exhibit anti‐oxidant, anti‐diabetic, anti‐inflammatory, anti‐tumor, anti‐microbial, anti‐stressor and many other pharmacological effects. Wild Onobrychis species have not been the subject of detailed studies. Compared with the cultivated forage legumes, wild Onobrychis species are still under‐exploited despite their potential to alleviate forage and food insecurity, either by domestication or by providing novel alleles for breeding purposes of the cultivated species Onobrychis viciifolia. Our review aims to increase scientific awareness towards exploring the potential uses of wild Onobrychis species to tackle current climate change.This article is protected by copyright. All rights reserved

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Impacts of mean climate and extreme climate indices on soybean yield and yield components in Northeast China

Cited by 31 publications

References 38 publications

Use of modelling tools to assess climate change impacts on smallholder oil seed yields in South Africa

Use of modelling tools to assess climate change impacts on smallholder oil seed yields in South Africa

Coupling Process-Based Crop Model and Extreme Climate Indicators with Machine Learning Can Improve the Predictions and Reduce Uncertainties of Global Soybean Yields

Potential use of wild Onobrychis species for climate change mitigation and adaptation

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