A case study of climate-smart management in foxtail millet (Setaria italica) production under future climate change in Lishu county of Jilin, China

Liu, Tao; Yang, Xiaoguang; Batchelor, William D.; Liu, Zhijuan; Wan, Nenghan; Sun, Shuang; He, Bin; Gao, Jiqing; Bai, Fan; Zhang, Fangliang; Zhao, Jin

doi:10.1016/j.agrformet.2020.108131

Cited by 12 publications

(7 citation statements)

References 43 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This good climate and the excellent soil quality make NEC become an important crop production area in the country (Zhao et al, 2015;Liu et al, 2018). However, during the period of 1961-2007, annual average temperature in NEC has increased by 0.38 °C per decade, but annual precipitation and sunshine duration have decreased by 9 mm per decade and 42 h per decade, respectively (Liu et al, 2020). In NEC, maize, rice and soybean were the three most important crops, and the planting areas of maize, rice and soybean in 2015 were 1.42 × 10 7 (51.1%), 5.82 × 10 6 (20.9%) and 3.75 × 10 6 ha (13.5%), respectively (Yan et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Trends and Climate Response in the Phenology of Crops in Northeast China

et al. 2021

View full text Add to dashboard Cite

Crop phenology is the process of crop growth and yield formation, which is largely driven by climatic conditions. It is vital to investigate the shifts in crop phenological processes in response to climate variability. Previous studies often only explored the response of a single crop phenology to climate change, and lacked comparative studies on the climate response in different crop phenology. We intend to investigate the trends in phenological change of three typical crops (i.e., maize, rice and soybean) in Northeast China (NEC) and their response to climate change during 1981–2010. Its main purpose is to reveal the differences in the sensitivity of different crop phenology to key climate factors [e.g., mean temperature (T), accumulated precipitation (AP) and accumulated sunshine hours (AS) during the crop growth period]. We found that the three crops have different phenological changes and varying ranges, and significant spatial heterogeneity in phenological changes. The results indicated that the lengths of different crop growth stages [e.g., the vegetative growth period (VGP), the reproductive growth period (RGP) and the whole growth period (WGP)] were negatively correlated with T, especially in VGP and WGP. However, the lengths of growth period of the three crops were positively correlated with AP and AS. For each 1°C increase in T, the number of days shortened in WGP (about 5 days) was the largest, and that in RGP (less than 2 days) was the smallest. Therefore, the increases in T during past 3 decades have significantly shortened VGP and WGP of three crops, but had slight and inconsistent effects on RGP. Moreover, changes in AP has slight impact on the growth periods of maize and rice, and significantly shortened RGP and WGP of soybean. Changes in AS exerted important and inconsistent effects on the phenology of three crops. This study indicated that there are significant differences in the sensitivity and response of different crop phenology to climate factors. Therefore, in evaluating the response and adaptation of crops to climate change, comparison and comprehensive analysis of multiple crops are helpful to deeply understand the impact of climate change on crop production.

show abstract

Section: Introductionmentioning

confidence: 99%

Trends and Climate Response in the Phenology of Crops in Northeast China

et al. 2021

View full text Add to dashboard Cite

show abstract

“…The future climate scenario data were generated with higher horizontal resolution of 25 km×25 km dynamic downscaling based on the results of PRECIS (Providing REgional Climates for Impacts Studies) nested global model HadGEM2-ES simulation. This set of data has been widely used in studying the impacts of climate change, and its validity has also been verified in previous studies (Xu et al, 2006;Khiem et al, 2014;Massey et al, 2015;Liu et al, 2020;Meng et al, 2020). We further took the average of the gridded data within the region of Fujin city to represent the future climate scenario data at this research site.…”

Section: Historical and Future Climate Datamentioning

confidence: 87%

A case study on the impacts of future climate change on soybean yield and countermeasures in Fujin city of Heilongjiang province, China

Li,

Chang,

Gao

et al. 2024

Front. Agron.

View full text Add to dashboard Cite

Global climate change poses a great impact on crop growth, development and yield. Soybean production in Northeast China, which is one of the traditional dominant soybean production areas in China, is of great significance for developing the domestic soybean industry and reducing dependence on imported soybeans. Therefore, it is crucial to evaluate the impacts of future climate change on soybean yield in Northeast China, and to propose reasonable adaptation measures. In this study, we took Fujin city of Heilongjiang province in Northeast China as an example, and used the CROPGRO-soybean model in DSSAT (Decision Support System for Agrotechnology Transfer) to simulate the impacts of future climate change on soybean yield in the four periods of the 2020s (2021-2030), 2030s (2031-2040), 2040s (2041-2050) and 2050s (2051-2060) under two representative concentration pathway (RCP) scenarios (RCP4.5 and RCP8.5), and further determine the best agronomic management practices. The results showed that the calibrated and validated model is suitable for simulating soybean in the study area. By analyzing the meteorological data under future climate scenarios RCP4.5 and RCP8.5 from the PRECIS regional climate model, we found that the average temperature, cumulative precipitation and cumulative solar radiation would mostly increase during the growing season in Fujin city of Heilongjiang province. Combined with the model simulation results, it is shown that under the effect of CO2 fertilization, future climate change will have a positive impact on soybean yield. Compared to the baseline (1986-2005), the soybean yield would increase by 0.6% (7.4%), 3.3% (5.1%), 6.0% (16.8%) and 12.3% (20.6%) in the 2020s, 2030s, 2040s and 2050s under RCP4.5 (RCP8.5).Moreover, the optimal sowing dates and the optimal supplemental irrigation amount under RCP4.5 (RCP8.5) are May 10 (May 5) and 50 mm (40mm), respectively. Under future climate conditions, the agronomic management practices, such as advancing the sowing date and supplementary irrigation in the key stage of soybean growth would increase soybean yield and make soybean growth more adaptable to future climate change.

show abstract

“…Additionally, irrational human activities, such as urban construction, hydroelectric development, and other industrial practices, could further contribute to a dramatic decline in potential distribution areas of S . italica [ 37 ]. This study focused on environmental factor variables for two periods (2050 and 2070).…”

Section: Discussionmentioning

confidence: 99%

Potential global distribution of Setaria italica, an important species for dryland agriculture in the context of climate change

Yang,

Jiang,

et al. 2024

PLoS ONE

View full text Add to dashboard Cite

Setaria italica (S. italica, Linnaeus, 1753) is a drought-resistant, barren-tolerant, and widely adapted C-4 crop that plays a vital role in maintaining agricultural and economic stability in arid and barren regions of the world. However, the potential habitat of S. italica under current and future climate scenarios remains to be explored. Predicting the potential global geographic distribution of S. italica and clarifying its ecological requirements can help promote sustainable agriculture, which is crucial for addressing the global food crisis. In this study, we predicted the potential global geographic distribution of S. italica based on 3,154 global distribution records using the Maxent model and ArcGIS software. We assessed the constraints on its potential distribution based on the contribution of environmental factors variables. The predictive accuracy of the Maxent model was evaluated using AUC values, TSS values, and Kappa statistics, respectively. The results showed that the Maxent model had a high prediction accuracy, and the simulation results were also reliable; the total suitable habitats of S. italica is 5.54×107 km2, which mainly included the United States (North America), Brazil (South America), Australia (Oceania), China, India (Asia), and the Russian Federation (Europe). The most suitable habitat of S. italica was 0.52×107 km2, accounting for 9.44% of the total areas, mainly in the United States, India, the Russian Federation, and China. Soil and precipitation (driest monthly precipitation, hottest seasonal precipitation) are the most critical factors limiting the potential distribution of S. italica. Compared with the modern potential distribution, we predict that the four future climate change scenarios will result in varying reductions in the possible geographic ranges of S. italica. Overall, climate change may significantly affect the global distribution of S. italica, altering its worldwide production and trade patterns.

show abstract

A case study of climate-smart management in foxtail millet (Setaria italica) production under future climate change in Lishu county of Jilin, China

Cited by 12 publications

References 43 publications

Trends and Climate Response in the Phenology of Crops in Northeast China

Trends and Climate Response in the Phenology of Crops in Northeast China

A case study on the impacts of future climate change on soybean yield and countermeasures in Fujin city of Heilongjiang province, China

Potential global distribution of Setaria italica, an important species for dryland agriculture in the context of climate change

Contact Info

Product

Resources

About