Greenhouse Gas Emissions and Management Practices that Affect Emissions in US Rice Systems

Abstract

Previous reviews have quantified factors affecting greenhouse gas (GHG) emissions from Asian rice ( L.) systems, but not from rice systems typical for the United States, which often vary considerably particularly in practices (i.e., water and carbon management) that affect emissions. Using meta-analytic and regression approaches, existing data from the United States were examined to quantify GHG emissions and major practices affecting emissions. Due to different production practices, major rice production regions were defined as the mid-South (Arkansas, Texas, Louisiana, Mississippi, and Missouri) and California, with emissions being evaluated separately. Average growing season CH emissions for the mid-South and California were 194 (95% confidence interval [CI] = 129-260) and 218 kg CH ha season (95% CI = 153-284), respectively. Growing season NO emissions were similar between regions (0.14 kg NO ha season). Ratoon cropping (allowing an additional harvestable crop to grow from stubble after the initial harvest), common along the Gulf Coast of the mid-South, had average CH emissions of 540 kg CH ha season (95% CI = 465-614). Water and residue management practices such as alternate wetting and drying, and stand establishment method (water vs. dry seeding), and the amount of residue from the previous crop had the largest effect on growing season CH emissions. However, soil texture, sulfate additions, and cultivar selection also affected growing season CH emissions. This analysis can be used for the development of tools to estimate and mitigate GHG emissions from US rice systems and other similarly mechanized systems in temperate regions.

Can ratoon cropping improve resource use efficiencies and profitability of rice in central China?

“…Annual CH 4 emission from rice cultivation was calculated using a daily emission factor of 1.3 kg CH 4 ha −1 day −1 and the approximate duration of the rice crop cycle, and some specific scaling factors associated with water regime and organic amendment (Intergovernmental Panel on Climate Change (IPCC, 2006; Supplementary Table S5). We were aware of recent advances in estimating field-level CH 4 emissions (Linquist et al, 2018); however, we did not use this approach in our study because (i) not all required data inputs were available ( e.g. , soil texture and chemical properties) and (ii) this approach has only been validated for temperate regions.…”

Effects of water management and cultivar on carbon dynamics, plant productivity and biomass allocation in European rice systems

“…However, while research on the effects of water management (including AWD) on yield, grain quality and CH 4 flux in rice is relatively well-developed, much less is known about the effects of different water management practices on ecosystem C dynamics, including processes such as net primary production (NPP), ecosystem respiration (ER), soil organic matter (SOM) decomposition, and biomass allocation (Linquist et al, 2018; Sass and Fisher, 1997; Wassmann et al, 2009). Given that AWD represents a shift to more oxidizing soil conditions, one potential impact of AWD is it may accelerate the decay of plant residues and SOM, particularly during the vegetative growth phase of rice.…”

Methane flux measurements in rice by static flux chamber and eddy covariance

“…Emissions measured by SFC were greater than EC due to greater mid‐season measured fluxes. The total season emissions were smaller than average emissions in the U.S. Midsouth (146 kg CH 4 –C ha −1 season −1 , reported as 194 kg CH 4 ha −1 season −1 ) , but were within 97–195 kg CH 4 –C ha −1 season −1 (reported as 129–260 kg CH 4 ha −1 season −1 ) as the 95% confidence range (Linquist et al., 2018). In 2016, the total emissions from both methods and both fields were within the 95% confidence range, whereas the 2015 total emission was below the 95% confidence range.…”

“…The majority of CH 4 flux measurements in rice have come from SFC‐measured studies at the small plot‐scale (Linquist et al., 2018). The basis of models and global estimates of greenhouse gas (GHG) fluxes have largely been SFC.…”