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气候变化影响不确定性评估及利用多作物和气候模型实现可持续玉米生产的适应措施。

Climate change impact uncertainty assessment and adaptations for sustainable maize production using multi-crop and climate models.

机构信息

Sugarcane Research Institute, Ayub Agricultural Research Institute, Faisalabad, Pakistan.

Asian Disaster Preparedness Centre (ADPC), Islamabad, Pakistan.

出版信息

Environ Sci Pollut Res Int. 2022 Mar;29(13):18967-18988. doi: 10.1007/s11356-021-17050-z. Epub 2021 Oct 27.

Abstract

Future climate scenarios are predicting considerable threats to sustainable maize production in arid and semi-arid regions. These adverse impacts can be minimized by adopting modern agricultural tools to assess and develop successful adaptation practices. A multi-model approach (climate and crop) was used to assess the impacts and uncertainties of climate change on maize crop. An extensive field study was conducted to explore the temporal thermal variations on maize hybrids grown at farmer's fields for ten sowing dates during two consecutive growing years. Data about phenology, morphology, biomass development, and yield were recorded by adopting standard procedures and protocols. The CSM-CERES, APSIM, and CSM-IXIM-Maize models were calibrated and evaluated. Five GCMs among 29 were selected based on classification into different groups and uncertainty to predict climatic changes in the future. The results predicted that there would be a rise in temperature (1.57-3.29 °C) during the maize growing season in five General Circulation Models (GCMs) by using RCP 8.5 scenarios for the mid-century (2040-2069) as compared with the baseline (1980-2015). The CERES-Maize and APSIM-Maize model showed lower root mean square error values (2.78 and 5.41), higher d-index (0.85 and 0.87) along reliable R (0.89 and 0.89), respectively for days to anthesis and maturity, while the CSM-IXIM-Maize model performed well for growth parameters (leaf area index, total dry matter) and yield with reasonably good statistical indices. The CSM-IXIM-Maize model performed well for all hybrids during both years whereas climate models, NorESM1-M and IPSL-CM5A-MR, showed less uncertain results for climate change impacts. Maize models along GCMs predicted a reduction in yield (8-55%) than baseline. Maize crop may face a high yield decline that could be overcome by modifying the sowing dates and fertilizer (fertigation) and heat and drought-tolerant hybrids.

摘要

未来的气候情景预测,干旱和半干旱地区的可持续玉米生产将面临相当大的威胁。通过采用现代农业工具来评估和制定成功的适应实践,可以最大程度地减少这些不利影响。采用多模式方法(气候和作物)来评估气候变化对玉米作物的影响和不确定性。进行了广泛的田间研究,以探索在连续两年的 10 个播种日期中,在农民田间种植的玉米杂种的时间热变化。采用标准程序和协议记录有关物候学、形态学、生物量发育和产量的数据。校准和评估了 CSM-CERES、APSIM 和 CSM-IXIM-Maize 模型。根据分类到不同组和对未来气候变化预测的不确定性,在 29 个 GCM 中选择了 5 个 GCM。结果预测,在使用 RCP 8.5 情景对本世纪中叶(2040-2069 年)进行预测时,与基线(1980-2015 年)相比,五个 GCM 中玉米生长季节的温度将升高(1.57-3.29°C)。CERES-Maize 和 APSIM-Maize 模型在抽穗期和成熟期的根均方误差值(2.78 和 5.41)较低,d 指数(0.85 和 0.87)较高,可靠 R(0.89 和 0.89)分别较高,而 CSM-IXIM-Maize 模型在生长参数(叶面积指数、总干物质)和产量方面表现良好,具有相当好的统计指标。CSM-IXIM-Maize 模型在两年中都表现良好,而气候模型 NorESM1-M 和 IPSL-CM5A-MR 对气候变化影响的结果则不太不确定。玉米模型与 GCM 一起预测产量(8-55%)低于基线。玉米作物可能面临高减产的风险,可以通过改变播种日期和肥料(施肥)以及耐热耐旱杂种来克服。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1578/8882089/05ad30e7ae91/11356_2021_17050_Fig1_HTML.jpg

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