Soil Organic Carbon and Nitrogen Feedbacks on Crop Yields under Climate Change

Basso, Bruno; Dumont, Benjamin; Maestrini, Bernardo; Shcherbak, Iurii; Robertson, G. Philip; Porter, John R.; Smith, Pete; Paustian, Keith; Grace, Peter R.; Asseng, Senthold; Bassu, Simona; Biernath, Christian; Boote, Kenneth J.; Cammarano, Davide; Sanctis, Giacomo De; Durand, J. L.; Ewert, F.; Gayler, Sebastian; Hyndman, D. W.; Kent, J.; Martre, Pierre; Nendel, Claas; Priesack, Eckart; Ripoche, Dominique; Ruane, Alexander C.; Sharp, Joanna; Thorburn, Peter J.; Hatfield, Jerry L.; Jones, James W.; Rosenzweig, Cynthia

doi:10.2134/ael2018.05.0026

Cited by 46 publications

(31 citation statements)

References 29 publications

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“…Such a platform would support and facilitate the use of ensemble modeling approaches. Advantages of an ensemble approach are to provide 'central tendency' estimates from a group of models [98] and to better Figure 6. Overview of the components and information flow for an approach to quantify soil carbon stock changes (and net GHG emissions) from field to national scales, purposed to support different implementation policies to remove atmospheric CO 2 and sequester soil carbon.…”

Section: Toward a New Global Soil Information Systemmentioning

confidence: 99%

Quantifying carbon for agricultural soil management: from the current status toward a global soil information system

et al. 2019

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The importance of building/maintaining soil carbon, for soil health and CO 2 mitigation, is of increasing interest to a wide audience, including policymakers, NGOs and land managers. Integral to any approaches to promote carbon sequestering practices in managed soils are reliable, accurate and cost-effective means to quantify soil C stock changes and forecast soil C responses to different management, climate and edaphic conditions. While technology to accurately measure soil C concentrations and stocks has been in use for decades, many challenges to routine, cost-effective soil C quantification remain, including large spatial variability, low signal-to-noise and often high cost and standardization issues for direct measurement with destructive sampling. Models, empirical and process-based, may provide a cost-effective and practical means for soil C quantification to support C sequestration policies. Examples are described of how soil science and soil C quantification methods are being used to support domestic climate change policies to promote soil C sequestration on agricultural lands (cropland and grazing land) at national and provincial levels in Australia and Canada. Finally, a quantification system is outlinedconsisting of well-integrated datamodel frameworks, supported by expanded measurement and monitoring networks, remote sensing and crowd-sourcing of management activity datathat could comprise the core of a new global soil information system. Take Home messages:Increasing soil organic carbon (SOC) stocks would improve the performance of working (managed) soils especially under drought or other stressors, increase agricultural resilience and fertility, and reduce net GHG emissions from soils.There are many improved management practices that can be and are currently being applied to cropland and grazing lands to increase SOC.Land managers are decision makers who operate in larger contexts that bound their agricultural and financial decisions (e.g. market forces, crop insurance, input subsidies, conservation mandates, etc.).Any effort to value improvements in the performance of agricultural soils through enhanced levels of SOC will require feasible, credible and creditable assessment of SOC stocks, which are governed by dynamic and complex soil processes and properties. This paper evaluates currently accepted methods of quantifying and forecasting SOC that, when augmented and pulled together, could provide the basis for a new global soil information system.

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Section: Toward a New Global Soil Information Systemmentioning

confidence: 99%

Quantifying carbon for agricultural soil management: from the current status toward a global soil information system

et al. 2019

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“…Climate change, particularly the warming temperature and varying precipitation, has a negative effect on grain yield and soil organic carbon (SOC). The increased temperature under climate change leads to faster crop development which reflects in yield declines and quicker soil carbon mineralization [8,9]. The unpredictable precipitation frequency imposes water deficiency stress on crop growth, which in turn reduces biomass accumulation and residue return to soils [9].…”

Section: Introductionmentioning

confidence: 99%

“…The increased temperature under climate change leads to faster crop development which reflects in yield declines and quicker soil carbon mineralization [8,9]. The unpredictable precipitation frequency imposes water deficiency stress on crop growth, which in turn reduces biomass accumulation and residue return to soils [9]. No-till practice may reduce such adverse climate impact on yield and SOC by conserving soil structure, storing carbon and nutrient and enhancing water retention [10,11,12].…”

Section: Introductionmentioning

confidence: 99%

“…The interconnections among grain yield, SOC, tillage management and climate change, however, have been overlooked. SOC dynamics is determined by mineralization rates, which is affected by temperature, soil moisture, and return of residue, which is affected by climate and tillage management [9,16,17]. A few studies have focused on the feedback between climate and SOC [18,19,9] provided the first study in the literature where the concomitant effects of yield decline and SOC losses under climate change were addressed in a systems feedback loop.…”

Section: Introductionmentioning

confidence: 99%

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Impacts of climate variability and adaptation strategies on crop yields and soil organic carbon in the US Midwest

Liu

Basso

2020

PLoS ONE

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Climate change is likely to increase the frequency of drought and more extreme precipitation events. The objectives of this study were i) to assess the impact of extended drought followed by heavy precipitation events on yield and soil organic carbon (SOC) under historical and future climate, and ii) to evaluate the effectiveness of climate adaptation strategies (notillage and new cultivars) in mitigating impacts of increased frequencies of extreme events and warming. We used the validated SALUS crop model to simulate long-term maize and wheat yield and SOC changes of maize-soybean-wheat rotation cropping systems in the northern Midwest USA under conventional tillage and no-till for three climate change scenarios (one historical and two projected climates under the Representative Concentration Path (RCP) 4.5 and RCP6) and two precipitation changes (extreme precipitation occurring early or late season). Extended drought events caused additional yield reduction when they occurred later in the season (10-22% for maize and 5-13% for wheat) rather than in early season (5-17% for maize and 2-18% for wheat). We found maize grain yield declined under the projected climates, whereas wheat grain yield increased. No-tillage is able to reduce yield loss compared to conventional tillage and increased SOC levels (1.4-2.0 t/ha under the three climates), but could not reverse the adverse impact of climate change, unless early and new improved maize cultivars are introduced to increase yield and SOC under climate change. This study demonstrated the need to consider extreme weather events, particularly drought and extreme precipitation events, in climate impact assessment on crop yield and adaptation through no-tillage and new genetics reduces yield losses.

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“…The SALUS model does not have an explicit module to account for pest, weeds and diseases. The detailed descriptions of the model and key algorithms have been presented in Basso et al (2006), Dzotsi et al (2013) and Ritchie and Basso (2008) and Basso et al (2018).…”

Section: Description Of the Salus Crop Modelmentioning

confidence: 99%

Linking field survey with crop modeling to forecast maize yield in smallholder farmers’ fields in Tanzania

Liu

Basso

2020

Food Sec.

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Short term food security issues require reliable crop forecasting data to identify the population at risk of food insecurity and quantify the anticipated food deficit. The assessment of the current early warning and crop forecasting system which was designed in mid 80's identified a number of deficiencies that have serious impact on the timeliness and reliability of the data. We developed a new method to forecast maize yield across smallholder farmers' fields in Tanzania (Morogoro, Kagera and Tanga districts) by integrating field-based survey with a process-based mechanistic crop simulation model. The method has shown to provide acceptable forecasts (r 2 values of 0.94, 0.88 and 0.5 in Tanga, Morogoro and Kagera districts, respectively) 14-77 days prior to crop harvest across the three districts, in spite of wide range of maize growing conditions (final yields ranged from 0.2-5.9 t/ha). This study highlights the possibility of achieving accurate yield forecasts, and scaling up to regional levels for smallholder farming systems, where uncertainties in management conditions and field size are large.

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Soil Organic Carbon and Nitrogen Feedbacks on Crop Yields under Climate Change

Cited by 46 publications

References 29 publications

Quantifying carbon for agricultural soil management: from the current status toward a global soil information system

Quantifying carbon for agricultural soil management: from the current status toward a global soil information system

Impacts of climate variability and adaptation strategies on crop yields and soil organic carbon in the US Midwest

Linking field survey with crop modeling to forecast maize yield in smallholder farmers’ fields in Tanzania

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