Impacts of cropping practices on yield-scaled greenhouse gas emissions from rice fields in China: A meta-analysis

Feng, Jing; Chen, Chang; Zhang, Yi; Song, Zhenwei; Deng, Aixing; Zheng, Chengyan; Zhang, Weijian

doi:10.1016/j.agee.2012.10.009

Cited by 191 publications

(121 citation statements)

References 47 publications

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“…Additionally, while fertilization could increase emissions of GHG such as NO2 or CH4, those emissions could potentially be offset by the carbon sink created by faster growing sisal plants. In this case study, the usage of the biogas production residual as fertilizer would minimize additional GHG emissions, in accordance with (Feng, et al, 2013), which found that biogas residues have low GHG emissions compared to other fertilizers. It is difficult however to estimate the impacts of irrigation and fertilization without additional experimental data.…”

Section: Productive Uses Scenariosupporting

confidence: 78%

Powering production. The case of the sisal fibre production in the Tanga region, Tanzania

Nerini

Andreoni

Bauner³

et al. 2016

Energy Policy

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Section: Productive Uses Scenariosupporting

confidence: 78%

Powering production. The case of the sisal fibre production in the Tanga region, Tanzania

Nerini

Andreoni

Bauner³

et al. 2016

Energy Policy

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“…Only a 2 % mitigation of CH 4 emissions from no-tillage in this 5-year period was simulated. In a meta-analysis of CH 4 emissions in Chinese rice fields, Feng et al (2013) also reported that no-tillage could reduce CH 4 emissions by 26 % in comparison to conventional tillage. Li et al (2011) attributed the lower CH 4 emissions in no-tillage system to higher soil bulk density and lower dissolved organic carbon content, which could restrict substrate availability for methanogenesis.…”

Section: Methane Fluxesmentioning

confidence: 99%

Daycent Simulation of Methane Emissions, Grain Yield, and Soil Organic Carbon in a Subtropical Paddy Rice System

Weiler

Tornquist

Zschornack

et al. 2018

Rev. Bras. Ciênc. Solo

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ABSTRACT:The DayCent ecosystem model, widely tested in upland agroecosystems, was recently updated to simulate waterlogged soils. We evaluated the new version in a paddy rice experiment in Southern Brazil. DayCent was used to simulate rice yield, soil organic carbon (SOC), and soil CH 4 fluxes. Model calibration was conducted with a multiple-year dataset from the conventional tillage treatment, followed by a validation phase with data from the no-tillage treatment. Model performance was assessed with statistics commonly used in modeling studies: root mean square error (RMSE), model efficiency (EF), and mean difference (M). In general, DayCent slightly underestimated rice yields under no-tillage (by 0.07 Mg ha -1 , or 9.2 %) and slightly overestimated soil C stocks, especially in the first years of the experiment. A comparison of observed and simulated CH 4 daily fluxes showed that DayCent could simulate the general patterns of soil CH 4 fluxes with slight discrepancies. Daily soil CH 4 fluxes were overestimated by 0.43 kg ha -1 day -1 (12 %). Growth-season CH 4 emissions under no-tillage were also somewhat overestimated (11 % or 45.29 kg ha -1). We conclude that DayCent simulated SOC, rice yield, and CH 4 with some inaccuracies, but the overall performance was considered adequate. However, the model failed to represent the observed potential of no-tillage to mitigate CH 4 emissions, possibly because model algorithms could not capture the actual field conditions derived from no-tillage management, such as soil redox potential, plant senescence, and surface placement of plant residue.

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“…Thus, a moderate increase in planting density with less basal N application could make a trade-off between CH4 production and oxidation, resulting in the lowest CH4 emissions level among the treatments at the three tested sites. Recent findings from literature exhibits that N rates with optimal grain yield have no net effect on CH4 emission due to the counter-balanced by the positive effect of N addition on CH4 production and oxidation (Banger et al, 2012;Linquist et al, 2012;Feng et al, 2013;Pittelkow et al, 2014). That may be true in farmer's fields, but specifically as in present study for CK and DR1 with optimal yield, only basal and tillering N was decreased and the panicle N application was the same for both CK and DR1, which may results in inhibitory effect of reduced N application on CH4 oxidation only occurred at tillering stage; in addition, the negative effect of reduced N application on CH4 oxidation may be modified by deficiency of oxygen for Methanotrophs due to continuous flooding at tillering stage (Banger et al, 2012).…”

Section: Discussionmentioning

confidence: 99%

“…For rice, yield-scaled GWP is mainly decided by CH4 emission and rice yield, since CH4 emission is the major contributor to GWP (Linquist et al, 2012;Feng et al, 2013;Pittelkow et al, 2013). It was reported that yield-scaled GWP was minimized at optimal N rates with maximum yield (Pittelkow et al, 2014).…”

Section: Discussionmentioning

confidence: 99%

Effects of Dense Planting with Less Basal N Fertilization on Rice Yield, N Use Efficiency and Greenhouse Gas Emissions

Zhu¹,

Wang²,

Li³

et al. 2015

IJAB

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Rice cropping innovations for high yield with high N use efficiency (NUE) and low greenhouse gas (GHG) emissions are significant in ensuring food security and coping with climate change. The objective of this study was to investigate the comprehensive effects of dense planting with less basal N application (DR) on rice yield, NUE and GHG emissions. Field experiments were conducted at three sites in China: Shenyang, Danyang and Jinxian representing annual single rice cropping system, wheat-rice cropping system and double rice cropping system, respectively. Four planting densities with 25, 50, 75 and 100% higher each time correspondingly with about 25, 50, 75 and 100% less in basal N rate (i.e., DR1, DR2, DR3 and DR4 correspondingly) relative to traditional cropping for high yield (CK). Across three tested sites, the DR1 mode showed a large potential of NUE enhancement by 19.6% and GHG emissions mitigation by 12.2% at area-and yield-scaled with similar rice yield compared to the CK. However, further increase in planting density and decrease in basal N application caused a significant reduction in rice yield with a large increase in GHG emissions. Our results will provide important reference to rice cropping innovations for the integrated goals of food security, environmental health and climate change mitigation in China.

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Impacts of cropping practices on yield-scaled greenhouse gas emissions from rice fields in China: A meta-analysis

Cited by 191 publications

References 47 publications

Powering production. The case of the sisal fibre production in the Tanga region, Tanzania

Powering production. The case of the sisal fibre production in the Tanga region, Tanzania

Daycent Simulation of Methane Emissions, Grain Yield, and Soil Organic Carbon in a Subtropical Paddy Rice System

Effects of Dense Planting with Less Basal N Fertilization on Rice Yield, N Use Efficiency and Greenhouse Gas Emissions

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