作物模型在对比施肥和残留物管理下预测玉米种植系统土壤有机碳变化的能力:来自长期实验的证据

IF 2.6 3区 农林科学 Q1 AGRONOMY Italian Journal of Agronomy Pub Date : 2022-12-30 DOI:10.4081/ija.2022.2179
A. Pulina, R. Ferrise, Laura Mula, L. Brilli, L. Giglio, I. Iocola, D. Ventrella, L. Zavattaro, C. Grignani, P. Roggero
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引用次数: 2

摘要

本研究评估了一组作物模型(MME)在基于玉米连作系统的长期实验(LTE)中预测施肥和作物残留物管理对土壤有机碳(SOC)和地上生物量(AGB)影响的能力。使用了来自意大利北部LTE的数据。处理包括连续谷物(MG)或青贮玉米(MS),用矿物、牛浆和农家肥施肥。MME中位数是观测值的最佳预测值。模拟MG时,模型的性能比模拟MS更好,并且与有机肥料相比,矿物处理的作物的模型性能更好。预测SOC动态的能力受到所使用的模型以及年×残留物管理和年×肥料相互作用的影响。该模型和残留物×肥料的相互作用影响了模拟AGB动力学的能力。结果表明,MME可以有效预测对比施肥和作物残留管理下SOC和玉米作物产量的长期动态,从而预测其缓解气候变化的潜力。SOC模拟中的不确定性与模拟SOC划分的模型例程以及管理因素之间随着时间的推移相互作用的复杂性有关。亮点-在一项长期实验中,编制了一个作物模型集合,以模拟土壤有机碳和玉米地上生物量的动态在对比施肥和作物残留管理的情况下,对独立模型及其组合的性能进行了评估使用模拟中值的多模型集合是长期实验中观察到的变量的最佳预测因子当作物残留物被掺入土壤时,无论施肥管理如何,模拟中的表现都有所改善青贮玉米和有机施肥种植系统SOC模拟的不确定性随着时间的推移而增加。
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The ability of crop models to predict soil organic carbon changes in a maize cropping system under contrasting fertilization and residues management: Evidence from a long-term experiment
This study assesses the ability of an ensemble of crop models (MME) to predict the impacts of fertilization and crop residue management on soil organic carbon (SOC) and aboveground biomass (AGB) in a long-term experiment (LTE) based on continuous maize cropping systems. Data from a LTE in Northern Italy were used. Treatments included continuous grain (MG) or silage (MS) maize, fertilized with mineral, cattle slurry, and farmyard manure. The MME median resulted the best predictor of the observed values. Models performance was better when simulating MG than MS, and for crops treated with mineral compared to organic fertilizers. The ability to predict the dynamics of SOC was affected by the model used and by the year × residues management and year × fertilizer interactions. The model and the residue × fertilizer interaction affected the ability to simulate AGB dynamics. Results showed that a MME can effectively predict the long-term dynamics of SOC and maize crop production under contrasting fertilization and crop residue management, and thus their potential for climate change mitigation. The uncertainty in the simulation of SOC is related to the model routines simulating SOC partitioning and to the complexity of the interactions between management factors over time. Highlights - A crop model ensemble was compiled to simulate soil organic carbon and maize aboveground biomass dynamics in a long-term experiment. - The performances of stand-alone models and their ensemble were assessed under contrasting fertilization and crop residue management. - The multi-model ensemble using the median value of simulation was the best predictor of the variables observed in the long-term experiment. - Improved performances in simulations were observed when crop residues were incorporated into the soil, regardless of the fertilization management. - The uncertainty in SOC simulation increased over time for cropping systems with silage maize and organic fertilization.
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来源期刊
CiteScore
4.20
自引率
4.50%
发文量
25
审稿时长
10 weeks
期刊介绍: The Italian Journal of Agronomy (IJA) is the official journal of the Italian Society for Agronomy. It publishes quarterly original articles and reviews reporting experimental and theoretical contributions to agronomy and crop science, with main emphasis on original articles from Italy and countries having similar agricultural conditions. The journal deals with all aspects of Agricultural and Environmental Sciences, the interactions between cropping systems and sustainable development. Multidisciplinary articles that bridge agronomy with ecology, environmental and social sciences are also welcome.
期刊最新文献
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