Share This Article:

Diurnal Methane Fluxes as Affected by Cultivar from Direct-Seeded, Delayed-Flood Rice Production

Abstract Full-Text HTML XML Download Download as PDF (Size:368KB) PP. 957-973
DOI: 10.4236/jep.2017.89060    406 Downloads   641 Views  

ABSTRACT

Methane (CH4) emissions are known to differ between rice (Oryza sativa L.) cultivars, where CH4 emissions from pure-line cultivars are often greater than from hybrids. Numerous field studies have shown that CH4 emissions follow a diurnal pattern, typically reaching their maximum during afternoon hours. However, it is unknown whether cultivar affects CH4 fluxes/emissions at various measurement times of day or how those cultivar effects may differ spatially across soil textures and temporally throughout the rice growing season. The objective of this field study was to evaluate the effects of time of day (300, 800, 1200, 1800, and 2300 hours) and cultivar (one hybrid and one pure-line) on CH4 fluxes before and after heading from a silt-loam and clay soil in a direct-seeded, delayed-flood rice production system. Enclosed headspace chambers, 30 cm in diameter, were used for CH4 gas sampling on 22 July and 19 August at a silt-loam site and on 29 July and 26 August, 2014 at a clay-soil site in the Lower Mississippi River delta region of eastern Arkansas. Methane fluxes measured pre- and post-heading ranged from 0.7 to 2.2 mg CH4-C m-2· hr-1 from the clay soil and from 2 to 7 mg CH4-C m-2·hr-1 from the silt-loam soil. Hourly CH4 fluxes and estimated daily emissions differed among measurement times of day (P < 0.05) for a given cultivar or averaged across cultivars and differed between cultivars (P < 0.05) from the silt-loam soil, but not the clay soil. Results suggested that the optimum measurement time of day to capture either minimum, maximum, or average hourly CH4 flux or daily emissions for a given day differs by soil texture and rice growth stage, but conducting CH4 flux measurements around late morning to mid-day appear to be optimum to best capture the mean CH4 emissions for the day.

1. Introduction

Measurement time of day is important for attaining the most accurate estimations of seasonal and/or annual methane (CH4) emissions [1] . Consequently, temporally scaled CH4 emissions may be under- or over-estimated depending on the time of day in-field CH4 flux measurements are conducted. However, a reasonable balance must also be achieved between accuracy and practicality for conducting in-field CH4 flux measurements for systematic research purposes.

As with many biologically mediated processes, CH4 emissions from flooded soils under rice (Oryza sativa L.) production have been suggested to follow a diel pattern controlled by diurnal soil temperature fluctuations [2] [3] and/or gross ecosystem photosynthesis [4] [5] . However, there is some inconsistency for the time of day when daily peak or average CH4 emissions occur. Most studies have reported peak emissions during the daytime, either in late morning to early afternoon [6] [7] [8] [9] or during mid- to late afternoon [2] [4] [7] [10] [11] [12] [13] . During the night and early morning have generally been reported as the times of day with the lowest CH4 fluxes/emissions [6] [7] [8] [11] [13] . Previous reports indicate diurnal variations (i.e., the amplitude and timing of flux minima and maxima) in CH4 emissions may also differ over time within the growing season [8] [10] [12] . However, numerous studies have also reported no significant difference in CH4 emissions between day and night [6] [14] [15] .

Differences between cultivars have generally been consistent given the multitude of factors that have been shown to affect CH4 fluxes and emissions throughout a growing season, such as soil texture [16] [17] [18] [19] , fertilizer nutrient source [20] , organic soil amendments [8] [12] , residue management/previous crop [21] [22] [23] [24] , water management scheme [8] [25] [26] , and production system [27] . Typically, hybrid rice cultivars have lower season-long CH4 emissions than do pure-line cultivars [23] [24] [28] [29] .

Though cultivar effects on season-long CH4 emissions are generally well- understood, it is unknown how cultivar may affect CH4 fluxes/emissions at different measurement times of day. It is also unknown how potential cultivar effects on diurnal CH4 emissions may interact with soil texture and/or rice growth stage. Furthermore, as many of the previous studies have been conducted decades ago, in-field methodological and analytical laboratory measurement advancements have subsequently been made, which makes revisiting the issue of diel CH4 emissions warranted, particularly in the direct-seeded, delayed-flood rice production system for which no known previous diel emissions studies have been conducted. Therefore, the objective of this field study was to evaluate the effects of time of day and cultivar on CH4 fluxes before and after heading on a silt-loam and clay soil in a direct-seeded, delayed-flood rice production system in Arkansas. It was hypothesized that, similar to other physiological plant- related processes, CH4 fluxes would be greater during the day than during the night. Based on past reports of lower season-long CH4 emissions from hybrid compared to pure-line cultivars, it was also hypothesized that CH4 fluxes from a hybrid would generally be lower than from a pure-line cultivar regardless of measurement time of day over a 24-hr period.

2. Materials & Methods

2.1. Site Description

Research was conducted during the 2014 growing season on a silt-loam soil at the University of Arkansas System Division of Agriculture Rice Research and Extension Center (RREC) near Stuttgart in Arkansas County, Arkansas (34˚27'N, 91˚24'W) and on a clay soil at the Northeast Research and Extension Center (NEREC) at Keiser in Mississippi County, Arkansas (35˚40'N, 90˚05'W). At RREC, study plots were located on a Dewitt silt loam (fine, smectitic, thermic Typic Albaqualfs), while plots were located on a Sharkey clay (very-fine, smectitic, thermic Chromic Epiaquerts) [30] at NEREC. The study site at RREC is located in the northern portion of major land resource area (MLRA) 131D, the Southern Mississippi River Terraces, while the study area at NEREC is located in MLRA 131A, the Southern Mississippi River Alluvium [31] . Mean annual precipitation is 124 and 126 cm and the mean annual air temperature is 16.7 and 15.5˚C at RREC and NEREC, respectively [32] . Both research locations reside in major rice-producing regions in Arkansas and the study areas at both locations have been in an annual soybean [Glycine max L. (Merr.)]-rice rotation for more than 20 years with crop residues incorporated between growing seasons into the top 15 cm of the soil.

2.2. Treatments and Experimental Design

Two common rice cultivars, one hybrid and one pure-line, were selected for field study. The hybrid cultivar CLXL745 (RiceTec, Inc., Houston, TX) is a short- season cultivar that heads at 77 days after emergence [33] and accounted for 22.0% of the total Arkansas rice production in 2014 [34] . The pure-line cultivar Roy J is a mid-season cultivar developed at the University of Arkansas [35] that heads at 85 days after emergence and accounted for 12.6% of the total Arkansas rice production in 2014 [34] . Both cultivars produce long-grain rice and are considered high-yielding cultivars with CLXL745 and Roy J yields averaging 10.0 and 9.9 Mg∙ha−1, respectively, across numerous locations in the 2014 Arkansas Rice Performance Trials [33] .

At both locations, a randomized complete block (RCB) design was established with four replicates of each cultivar. As described in more detail below, the five CH4 flux measurements that were conducted over a 24-hr period on two different dates, representing different rice growth stages, were treated as a repeated measure.

2.3. Plot Management

Field plots, 1.6-m wide by 5-m long that encompassed nine rows of rice, were established in early March 2014 and managed throughout the rice growing season in accordance with University of Arkansas Cooperative Extension Service (UACES) guidelines [36] . On 26 March 2014 at RREC (i.e., the silt-loam-soil location), phosphorus (P) and potassium (K), 100 kg∙ha−1 of each, and 11.2 kg∙ha−1 of zinc (Zn) were manually surface-applied and tilled into the top 10 to 15 cm of soil throughout the study area as per soil-test recommendations. Soil-test results indicated that the study area at NEREC (i.e., the clay-soil location) did not require any P, K, or Zn additions for optimal rice production. On 5 May at RREC and 7 May at NEREC, each plot was independently drill-seeded at an 18-cm row spacing with the pure-line cultivar Roy J at a seeding rate of 82 and 102 kg∙ha−1 at RREC and NEREC, respectively, or the hybrid cultivar CLXL745 at a seeding rate of 34 kg∙ha−1. Clay soils require a greater seeding rate than silt loams and hybrids have lower seeding rates due to an increased capacity to tiller compared to pure-line cultivars [36] . After planting at both locations, levees were constructed around each study area to contain the permanent flood. On 16 June at RREC and on 18 June at NEREC, based on UACES guidelines at the time, N was applied as urea (46% N) in a split application, where Roy J received 100 and 135 kg N ha−1 and CLXL745 received 135 and 168 kg N ha−1 at RREC and NEREC, respectively, as the first application [37] . On 17 June at RREC and on 20 June at NEREC, at the 4- to 5-leaf stage, the permanent flood was established and maintained at an approximate depth of 10 cm throughout the rice growing season until draining. The split application of N occurred at the beginning of internode elongation on 10 and 17 July 2014 at RREC and NEREC, respectively, for Roy J (50 kg N ha−1) and at the booting growth stage on 23 July and 4 August 2014 at RREC and NEREC, respectively, for the hybrid (33 kg N ha−1). According to UACES guidelines [38] [39] , insects and weeds were managed in all field plots throughout the season to remain below yield-affecting threshold levels of pests.

2.4. Soil Sampling

One set of five soil cores was collected prior to N fertilization and flooding from the top 10 cm in each plot using a 2-cm-diameter push probe and combined into one sample per plot. Samples were dried in a forced-draft oven at 70˚C for 48 hr, crushed, and sieved through a 2-mm mesh screen for soil chemical property determinations. Soil electrical conductivity (EC) and pH were determined potentiometrically on a 1:2 (mass:volume) soil-to-solution mixture. Soil organic matter (SOM) concentration was determined by weight-loss-on-ignition at 360˚C for 2 hr. Total C (TC) and N (TN) concentration were determined by high-tem- perature combustion (VarioMax CN analyzer, Elementar Americas Inc., Mt. Laurel, NJ). Total C and TN concentrations were used to calculate the soil C:N ratio. Mehlich-3 extractable nutrient (i.e., P, K, Ca, Mg, Fe, Mn, Na, S, Cu, and Zn) concentrations [40] were measured by inductively coupled plasma atomic emission spectroscopy (Spectro Arcos ICP, Spectro Analytical Instruments, Kleve, Germany).

A second set of samples was collected from the top 10 cm using a slide hammer and 4.7-cm-diameter core chamber with a beveled core tip, dried at 70˚C for 48 hr, weighed for bulk density determinations, and ground to pass through a 2-mm mesh screen for particle-size analysis using a modified 12-hr hydrometer method [41] . Measured soil nutrient concentrations (mg∙kg−1) and measured bulk densities from the top 10 cm were used to calculate and report nutrient contents (kg∙ha−1 or Mg ha−1).

2.5. Methane Gas Sampling

Methane fluxes were measured in all replications of both cultivars at 300, 800, 1200, 1800, and 2300 hours once before heading (i.e., a vegetative growth stage; 22 and 29 July 2014 for RREC and NEREC, respectively) and once after heading (i.e., a reproductive growth stage; 19 and 26 August 2014 for RREC and NEREC, respectively) using 30-cm-diameter enclosed headspace chambers [18] [19] [23] [24] [42] [43] . Elevated boardwalks were erected for minimally disturbing access into each plot prior to flooding. Polyvinyl chloride (PVC) base collars, 20 cm tall with 30-cm inside diameter (ID), were inserted approximately 10 cm deep in each plot immediately after flood establishment. To maintain atmospheric pressure during sampling, chamber caps, constructed from 30-cm-diameter PVC, were outfitted with 15-cm-long section of 4.5-mm ID copper tubing as a vent. Chamber caps were also outfitted with sealed, gray butyl-rubber septa (Voight Global, part number 73828A-RB, Lawrence, KS) for gas sampling and chamber temperature measurement ports. A 2.5-cm-diameter, 9V-battery-operated fan (Sunon Inc., MagLev, Brea, CA), mounted on the underside of each chamber cap, mixed the headspace air within the chamber throughout the duration of chamber closure.

At each diurnal measurement sampling time, chamber headspace gas samples were collected at 0, 20, 40, and 60 minutes after cap closure. Gas samples were extracted using 20-mL B-D syringes (Becton Dickinson and Co., Franklin Lakes, NJ) and injected into pre-evacuated 10-mL, crimp-top glass vials (part number 5182 - 0838, Agilent Technologies, Santa Clara, CA). All gas samples were analyzed within two days using a gas chromatograph (Agilent 6890-N, Agilent Technologies) with a flame ionization detector. As outlined by Parkin and Venterea [43] and used in several recent studies [18] [19] [23] [24] , CH4 fluxes were calculated based on the change in headspace CH4 concentration over time on a chamber-by-chamber basis. Additional details of the gas sampling and analysis procedures have been described in previous studies [18] [19] [23] [24] . Daily CH4 emissions were calculated independently for each of the CH4 fluxes for statistical analyses. In addition, daily CH4 emissions were calculated for statistical analyses from linear interpolation between all five CH4 flux measurements, referred to hereafter on each measurement date as the all-times emissions.

2.6. Statistical Analyses

Based on the RCB design of the cultivar treatments at each location, an analysis of variance (ANOVA) was conducted, separately by location, in SAS (version 9.4, SAS Institute, Inc., Cary, NC) using the PROC Mixed procedure to assess potential cultivar effects on near-surface soil properties prior to beginning gas sampling. Based on visual inspection of normal probability plots of the studentized residuals, CH4 flux data showed no indication of non-normal distribution. Consequently, separate ANOVAs were performed for each location-growth stage combination based on a RCB repeated-measures design, where measurement time of day was treated as the repeated measure, to evaluate the effects of time of day, cultivar, and their interaction on CH4 fluxes and daily CH4 emissions calculated from each different time-of-day flux measurement and for the all-times daily emissions. When appropriate, means were separated by least significant difference (LSD) at the 0.05 level. Due to planting and flooding date differences and differences in the timing of achieving various physiological growth stages between locations, location (i.e., soil texture) was not formally assessed as an experimental variable in this statistical analysis. Similarly, due to differences in the timing of achieving various physiological growth stages between cultivars, growth stage was also not formally assessed as an experimental variable.

3. Results & Discussion

3.1. Initial Soil Properties

Initial, near-surface soil properties varied slightly to not at all between cultivars at each location. At both locations, cultivar did not affect (P > 0.05) soil physical properties, namely sand, silt, and clay concentration and bulk density, in the top 10 cm prior to flood establishment (Table 1). Similarly, at both locations, cultivar did not affect (P > 0.05) near-surface soil chemical properties, namely soil pH, extractable soil Fe, Cu, and Zn and TC and TN contents, or C:N ratio, prior to flood establishment. On the silt-loam soil at RREC, cultivar did not affect (P > 0.05) extractable soil Mg and S and SOM contents, while on the clay soil at NEREC, cultivar did not affect (P > 0.05) extractable soil P content. However, at both locations, extractable soil K, Ca, Mn, and Na contents in the top 10 cm were greater (P < 0.05) for the pure-line than the hybrid cultivar. Soil EC and extractable soil P in the top 10 cm were greater (P < 0.05) for the pure-line than the hybrid cultivar at RREC, but soil EC was greater (P < 0.05) for the hybrid than the pure-line cultivar at NEREC. At NEREC, extractable soil Mg and SOM contents were greater (P < 0.05) for the pure-line than the hybrid cultivar, while extractable soil S content was greater (P < 0.05) for the hybrid than the pure-line cultivar. Though some pre-flood differences in near-surface soil properties existed between cultivars at both locations, the soil property differences were small and not expected to affect rice growth or production at either location [36] .

3.2. Hourly CH4 Fluxes and Estimated Daily Emissions

Hourly CH4 fluxes and estimated daily emissions differed by measurement time of day, rice cultivar, or both among location-growth stage combinations (Table 2). Hourly CH4 fluxes and estimated daily emissions differed between cultivars

Table 1. Summary of the effects of cultivar on mean soil properties (n = 4 per cultivar per location/soil texture) in the top 10 cm prior to flood establishment in a silt-loam soil at the Rice Research and Extension Center (RREC) near Stuttgart, Arkansas and in a clay soil at the Northeast Research and Extension Center (NEREC) in Keiser, Arkansas during the 2014 growing season.

Means within a row and location with different letters are significantly different at the P < 0.05 level.

among the various measurement times of day (P < 0.023) at the pre-heading growth stage from the silt-loam soil at RREC. Hourly CH4 fluxes from the pure- line cultivar were greatest at 2300 hours, smallest at 800 hours, and did not differ among the 300, 1200, and 1800 hours measurement times of day (Figure 1(a)). Similar to the pure-line cultivar, hourly CH4 fluxes from the hybrid were greatest at 2300 hours, but similar among the other four measurement times of day. Hourly CH4 fluxes only differed between cultivars at the 2300 hours measurement time of day, where the hourly flux from the pure-line was 1.6 times greater than that for the hybrid.

Estimated daily CH4 emissions from both cultivars followed similar patterns to hourly fluxes at the pre-heading growth stage from the silt-loam soil at RREC

Table 2. Summary of the effects of measurement time of day (TOD), cultivar, and their interaction on methane (CH4) fluxes and estimated daily emissions from a silt-loam soil at the Rice Research and Extension Center (RREC) near Stuttgart, Arkansas and from a clay soil at the Northeast Research and Extension Center (NEREC) in Keiser, Arkansas for two growth stages (i.e., pre-heading and post-heading) during the 2014 growing season.

(Table 2, Figure 1(b)). Numeric and/or statistically significant daily emissions minima were achieved at 800 hours, while maxima were achieved at 2300 hours for both cultivars (Figure 1(b)). Based on linear interpolation among the hourly CH4 fluxes from five measurement times of day, the all-times estimated daily CH4 emissions was achieved for both cultivars at the 300, 1200, and 1800 hours measurement times of day.

Hourly CH4 fluxes and estimated daily emissions differed between cultivars (P < 0.003) and differed among the various measurement times of day (P < 0.001) at the post-heading growth stage from the silt-loam soil at RREC (Table 2). Similar to that hypothesized and previous Arkansas reports [23] [24] [28] , averaged across measurement times of day, both hourly CH4 fluxes and estimated daily emissions were more than 2.6 times greater from the pure-line (8.16 mg CH4-C m−2∙hr−1 and 195.6 mg CH4-C m−2∙day−1, respectively) compared to the hybrid cultivar (3.11 mg CH4-C m−2∙hr−1 and 74.5 mg CH4-C m−2∙day−1, respectively). Averaged across cultivar, hourly CH4 fluxes were greatest at the 300 and 2300 hours, which did not differ, and lowest at the 800, 1200, and 1800 hours, which did not differ, measurement times of day (Table 3).

Estimated daily CH4 emissions, averaged across cultivar, were greatest at 2300 hours and smallest at 800 and 1800 hours, which did not differ, at the post- heading growth stage from the silt-loam soil at RREC (Table 3). However, in

Figure 1. Hourly CH4 fluxes (a) and estimated daily emissions (b) among measurement times of day at the pre-heading growth stage from the silt-loam soil at the Rice Research and Extension Center near Stuttgart, AR. Different letters above bars within a cultivar indicate a significant difference (P < 0.05) among measurement times of day. The asterisks (*) indicates a significant difference (P < 0.05) between cultivars within a given measurement time of day. The All Times label on panel B represents the estimated daily emissions from the linearly interpolated fluxes across all measurement times of day.

contrast to that at pre-heading, the all-times estimated daily CH4 emissions was only achieved at the 1200 hours measurement time of day. Estimated daily emissions from the 300 and 2300 hours measurement times of day were greater, while that from the 800 and 1800 hours measurement times of day were smaller than the all-times estimated daily CH4 emissions.

In contrast to that at the pre-heading growth stage from the silt-loam soil at RREC, hourly CH4 fluxes and estimated daily emissions only differed among the various measurement times of day (P < 0.001), but were unaffected by cultivar (P > 0.05) at the pre-heading growth stage from the clay soil at NEREC (Table 2). Averaged across cultivar, hourly CH4 fluxes and estimated daily CH4 emissions were greatest at 300 hours and lower, but similar, among the other four measurement times of day (Table 3). The all-times estimated daily CH4 emissions were achieved at the 800, 1800, and 2300 hour measurement times of day. Estimated daily emissions from the 300 hours measurement time of day were greater, while that from the 1200 hours measurement time of day were smaller than the all-times estimated daily CH4 emissions.

Table 3. Summary of the effects of measurement time of day on methane (CH4) fluxes and estimated daily emissions from a silt-loam soil at the Rice Research and Extension Center (RREC) near Stuttgart, Arkansas and from a clay soil at the Northeast Research and Extension Center (NEREC) in Keiser, Arkansas by growth stages (i.e., pre-heading or post-heading) during the 2014 growing season.

Means within a variable and location-growth stage combination with different letters are significantly different at the P < 0.05 level.

Contrary to that hypothesized, the maximum hourly CH4 flux and estimated daily emissions occurred during the night (i.e., at 2300 and/or 300 hours) rather than during the day at both the pre- and post-heading growth stages from the silt-loam soil at RREC and the pre-heading growth stage from the clay soil at NEREC. Though somewhat inconsistent with previous decades-old reports, peak emissions occurring during the night could be explained by a combination of improvements to in-field methodologies and cultivar genetics and differences in rice production systems used presently compared to those present at the time the previous studies were conducted. To our knowledge, no previous studies of diurnal CH4 emissions have been conducted in the direct-seeded, delayed-flood production system in Arkansas, in which this production system differs somewhat from those used in Louisiana, Texas, and California. Enclosed-headspace, chamber-based, in-field measurement procedures have likely advanced to reduce in-field variability and advancements in analytical laboratory techniques (i.e., gas chromatography) likely have enhanced sensitivity and accuracy compared to decades ago. In addition, cultivar breeding efforts, genetics, and trait manipulations have increased in complexity, such that the cultivars, both pure-lines and hybrids, which are being grown presently, are quite different than those that were grown decades ago. Even slight changes in plant physiological and metabolic processes could alter the semi-active, plant-mediated transport of CH4 from the soil through the rice plant’s aerenchyma tissues [4] [44] [45] [46] and potentially shift emissions minima and/or maxima to different times of the day.

Similar to that at the post-heading growth stage from the silt-loam soil at RREC and at the pre-heading growth stage from the clay soil at NEREC, hourly CH4 fluxes and estimated daily emissions differed among the various measurement times of day (P < 0.001), but, similar to that at pre-heading from the clay soil, were also unaffected by cultivar (P > 0.05) at the post-heading growth stage from the clay soil at NEREC (Table 2). Averaged across cultivars, both hourly CH4 fluxes and estimated daily emissions were greatest at 1800 hours and lowest at 800 hours at the post-heading growth stage from the clay soil at NEREC (Table 3). Though hourly CH4 fluxes were greater at 1200 and 2300 hours, which did not differ, than at 300 hours, estimated daily emissions from 300, 1200, and 2300 hours were all similar to the all-times mean estimated daily CH4 emissions.

Methane fluxes measured at the two growth stages in 2014 ranged from 0.7 to 2.2 mg CH4-C m−2∙hr−1 from the clay soil and from 2 to 7 mg CH4-C m−2∙hr−1 from the silt-loam soil (Table 3), which characterized fluxes from relatively low- emissions soils [47] . Though not formally assessed, the numerically lower emissions from the clay compared to the silt-loam soil are consistent with previous reports [16] [18] [19] . It is generally understood that lower gas diffusion rates associated with finer- (i.e., clays) compared to coarser-textured soils (i.e., silt loams) allow for greater CH4 oxidation before being emitted to the atmosphere, thereby reducing CH4 emissions [19] . Furthermore, clay soils tend to require a longer duration than do silt-loam soils to achieve the requisite oxidation-reduction potential for CH4 production [18] [48] , which further reduces CH4 production and emissions from clay compared to silt-loam soils. The soil-texture effect on CH4 emissions may also be responsible for the lack of a cultivar effect on CH4 emissions from the clay (NEREC) compared to the silt-loam soil (RREC) in this study (Table 3).

In contrast to studies that reported no diurnal variation [6] [14] [15] , CH4 fluxes/estimated emissions differed among measurement times of day for each of the four location-growth stage combinations in the direct-seeded, delayed-flood production system measured in this study. These results were similar to the measured diurnal variations reported previously [2] [4] [6] - [13] . Though greater diurnal variations have been reported early compared to late in the growing season [8] [10] , results of this study indicated the proportional range in diurnal CH4 fluxes/estimated emissions was similar before and after heading from both soil textures (Table 3). The numeric peak CH4 flux was 23% to 33% greater than the numeric low among the various measurement times of day across the four location-growth stage combinations, which was similar to the magnitude of variation reported by Yagi and Minami [13] .

Based on results from four location/soil texture-growth stage combinations during the 2014 rice growing season in eastern Arkansas, several commonalities were observed in terms of a potential optimum measurement time of day to result in daily emissions estimates that are similar to the mean daily emissions. Actual CH4 flux measurements made at 1200 hours at both the pre- and post- heading growth stages from the silt-loam soil at RREC, which were neither the daily minima nor maxima fluxes, resulted in daily estimated CH4 emissions that were statistically similar to the all-times mean estimated daily CH4 emissions (Figure 1, Table 3). In contrast, actual CH4 flux measurements made at 2300 hours at both the pre- and post-heading growth stages from the clay soil at NEREC, which were also neither the daily minima nor maxima fluxes, resulted in daily estimated CH4 emissions that were statistically similar to the all-times estimated daily CH4 emissions. However, in three of the four location-growth stage combinations, with the exception of at pre-heading on the clay soil at NEREC, actual CH4 flux measurements conducted at 1200 hours resulted in daily estimated CH4 emissions that were statistically similar to the all-times estimated daily CH4 emissions. Even less consistency occurred among location- growth stage combinations if the maximum daily emissions were to be the emissions target, where the maximum daily emissions occurred for flux measurements conducted at 2300 hours for both growth stages from the silt-loam soil at RREC compared to 300 and 1800 hours for pre- and post-heading, respectively, from the clay soil at NEREC (Figure 1, Table 3). The maximum daily emissions ranged from 14.8% to 26.4% and averaged 22% greater than the all-times daily emissions, whereas daily emissions calculated from measurements at all other times of day ranged from 18.1% lower to 12.8% greater and averaged 5.1% lower than the all-times daily emissions.

It is clear that CH4 flux measurements that are conducted to represent the average daily emissions are likely somewhat conservative estimates of the actual daily emissions because the time of day the average daily emissions occurs differs from the time of day when the daily maximum occurs. However, conducting CH4 flux measurements during the night to capture the maximum hourly flux or daily emissions is impractical; thus, targeting a measurement time of day to result in daily emissions that are similar to the average daily emissions appears to be a more practical goal. The 1200 hours measurement time of day that resulted in similar daily emissions to the all-times daily emissions in three of the four location-growth stage combinations in the direct-seeded, delayed-flood production system is only a few hours or less ahead of the measurement time range used in most recent field studies of 800 to 1000 [18] [19] [23] [24] [28] [49] [50] [51] and is similar to the timing suggested by Minamikawa et al. [1] from measurements in Japan and Weller et al. [52] from measurements in the Philippines.

4. Summary & Conclusions

Based on the results of this field study conducted among four location-growth stage combinations during the 2014 rice growing season from the direct-seeded, delayed-flood production system in eastern Arkansas, hourly CH4 fluxes and estimated daily emissions differed among measurement times of day for a given cultivar or averaged across cultivars. Hourly CH4 fluxes and estimated daily emissions also differed between cultivars from the silt-loam soil (RREC), but did not differ between cultivars from the clay soil (NEREC). In addition, it appears that the optimum measurement time of day to capture either minimum, maximum, or average hourly CH4 flux or daily emissions for a given day differs by soil texture and rice growth stage. However, conducting CH4 flux measurements around late morning to mid-day appears to be optimum to best capture the mean CH4 emissions for the day. Considering measurement time of day when devising a field study will improve the accuracy of seasonal and/or annual estimates of CH4 emissions. Though it is unknown exactly why peak measured CH4 fluxes would occur at night, after photosynthesis for the day has ceased, the combination of recent advances in rice breeding, particularly with hybrid cultivars, and methodological improvements to in-field gas sampling and laboratory analytical techniques warrant revisiting conclusions drawn from studies conducted several decades ago.

Acknowledgements

This research project was supported by a grant from the Arkansas Rice Research and Promotion Board. Planning and field assistance provided by Dr. Jarrod Hardke, Chris Rogers, D. L. Frizzell, M. W. Duren, E. Castaneda-Gonzalez, and W. Smartt were greatly appreciated.

Conflicts of Interest

The authors declare no conflicts of interest.

Cite this paper

Brye, K. , Smartt, A. and Norman, R. (2017) Diurnal Methane Fluxes as Affected by Cultivar from Direct-Seeded, Delayed-Flood Rice Production. Journal of Environmental Protection, 8, 957-973. doi: 10.4236/jep.2017.89060.

References

[1] Minamikawa, K., Yagi, K., Tokida, T., Sander, B.O. and Wassmann, R. (2012) Appropriate Frequency and Time of Day to Measure Methane Emissions from an Irrigated Rice Paddy in Japan Using the Manual Closed Chamber Method. Greenhouse Gas Measurement and Management, 2, 118-128.
https://doi.org/10.1080/20430779.2012.729988
[2] Denier van der Gon, H.A.C. and van Breemen, N. (1993) Diffusion-Controlled Transport of Methane from Soil to Atmosphere as Mediated by Rice Plants. Biogeochemistry, 21, 177-190.
https://doi.org/10.1007/BF00001117
[3] Wang, B., Neue, H.U. and Samonte, H.P. (1997) The Effect of Controlled Soil Temperature on Diel CH4 Emission Variation. Chemosphere, 35, 2083-2092.
[4] Schutz, H., Holzapfel-Pschorn, A., Conrad, R., Rennenberg, H. and Seiler, W. (1989) A 3-Year Continuous Record on the Influence of Daytime, Season and Fertilizer Treatment on Methane Emission Rates from in Italian Rice Paddy. Journal of Geophysical Research, 94, 16405-16416.
https://doi.org/10.1029/JD094iD13p16405
[5] Hatala, J.A., Detto, M. and Baldocchi, D.D. (2012) Gross Ecosystem Photosynthesis Causes a Diurnal Pattern in Methane Emission from Rice. Geophysical Research Letters, 39, L06409.
https://doi.org/10.1029/2012GL051303
[6] Cicerone, R.J., Delwiche, C.C., Tyler, S.C. and Zimmerman, P.R. (1992) Methane Emissions from California Rice Paddies with Varied Treatments. Global Biogeochemical Cycles, 6, 233-248.
https://doi.org/10.1029/92GB01412
[7] Denier van der Gon, H.A.C. and Neue, H. (1995) Influence of Organic Matter Incorporation on the Methane Emission from a Wetland Rice Field. Global Biogeochemical Cycles, 9, 11-22.
https://doi.org/10.1029/94GB03197
[8] Bronson, K.F., Neue, H.U., Singh, U. and Abao Jr., E.B. (1997) Automated Chamber Measurements of Methane and Nitrous Oxide Flux in a Flooded Rice Soil: I. Residue, Nitrogen and Water Management. Soil Science Society of America Journal, 61, 981-987.
https://doi.org/10.2136/sssaj1997.03615995006100030038x
[9] Hou, A.X., Chen, G.X., Wang, A.P., Van Cleemput, O. and Patrick Jr., W.H. (2000) Methane and Nitrous Oxide Emissions from a Rice Field in Relation to Soil Redox and Microbiological Processes. Soil Science Society of America Journal, 64, 2180-2186.
https://doi.org/10.2136/sssaj2000.6462180x
[10] Holzapfel-Pschom, A. and Seiler, W. (1986) Methane Emission during a Cultivation Period from an Italian Rice Paddy. Journal of Geophysical Research, 91, 11803-11814.
https://doi.org/10.1029/JD091iD11p11803
[11] Wassmann, R., Neue, H.U., Lantin, R.S., Aduna, J.B., Alberto, M.C.R., Andales, M.J., Tan, M.J., Denier van der Gon, H.A.C., Hoffmann, H., Papen, H., Rennenberg, H. and Seiler, W. (1994) Temporal Patterns of Methane Emissions from Wetland Rice Fields Treated by Different Modes of N Application. Journal of Geophysical Research, 99, 16457-16462.
https://doi.org/10.1029/94JD00017
[12] Buendia, L.V., Neue, H.U., Wassmann, R., Lantin, R.S., Javellana, A.M., Arah, J., Wang, Z., Wanfang, L., Makarim, A.K., Corton, T.M. and Charoensilp, N. (1998) An Efficient Sampling Strategy for Estimating Methane Emission from Rice Field. Chemosphere, 36, 395-407.
[13] Yagi, K. and Minami, K. (1990) Effect of Organic Matter Application on Methane Emission from Some Japanese Paddy Fields. Soil Science and Plant Nutrition, 36, 599-610.
https://doi.org/10.1080/00380768.1990.10416797
[14] Cicerone, R.J. and Shetter, J.D. (1981) Sources of Atmospheric Methane: Measurements in Rice Paddies and a Discussion. Journal of Geophysical Research, 86, 7203-7209.
https://doi.org/10.1029/JC086iC08p07203
[15] Nouchi, I., Hosono, T., Aoki, K. and Minami, K. (1994) Seasonal Variation in Methane Flux from Rice Paddies Associated with Methane Concentration in Soil Water, Rice Biomass and Temperature and Its Modeling. Plant & Soil, 161, 195-208.
https://doi.org/10.1007/BF00046390
[16] Sass, R.L., Fisher, F.M., Lewis, S.T., Turner, F.T. and Jund, M.F. (1994) Methane Emission from Rice Fields: Effects of Soil Properties. Global Biogeochemical Cycles, 8, 135-140.
https://doi.org/10.1029/94GB00588
[17] Sass, R.L. and Fisher, F.M. (1997) Methane Emissions from Rice Paddies: A Process Study Summary. Nutrient Cycling in Agroecosystem, 49, 119-127.
https://doi.org/10.1023/A:1009702223478
[18] Brye, K.R., Rogers, C.W., Smartt, A.D. and Norman, R.J. (2013) Soil Texture Effects on Methane Emissions from Direct-Seeded, Delayed-Flood Rice Production in Arkansas. Soil Science, 178, 519-529.
https://doi.org/10.1097/SS.0000000000000020
[19] Smartt, A.D., Brye, K.R., Rogers, C.W., Norman, R.J., Gbur, E.E., Hardke, J.T. and Roberts, T.L. (2016a) Characterization of Methane Emissions from Rice Production on a Clay Soil in Arkansas. Soil Science, 181, 57-67.
https://doi.org/10.1097/SS.0000000000000139
[20] Rogers, C.W., Smartt, A.D., Brye, K.R. and Norman, R.J. (2017) Nitrogen Source Effects on Methane Emissions from Drill-Seeded, Delayed-Flood Rice Production. Soil Science, 182, 9-17.
https://doi.org/10.1097/SS.0000000000000188
[21] Bossio, D.A., Horwath, W.R., Mutters, R.G. and van Kessel, C. (1999) Methane Pool and Flux Dynamics in a Rice Field Following Straw Incorporation. Soil Biology & Biochemistry, 31, 1313-1322.
[22] Fitzgerald, G.J., Scow, K.M. and Hill, J.E. (2000) Fallow Season Straw and Water Management Effects on Methane Emissions in California Rice. Global Biogeochemical Cycles, 14, 767-776.
https://doi.org/10.1029/2000GB001259
[23] Rogers, C.W., Brye, K.R., Smartt, A.D., Norman, R.J., Gbur, E.E. and Evans-White, M.A. (2014) Cultivar and Previous Crop Effects on Methane Emissions from Drill-Seeded, Delayed-Flood Rice Production on a Silt-Loam Soil. Soil Science, 179, 28-36.
https://doi.org/10.1097/SS.0000000000000039
[24] Smartt, A.D., Brye, K.R., Rogers, C.W., Norman, R.J., Gbur, E.E., Hardke, J.T. and Roberts, T.L. (2016b) Previous Crop and Cultivar Effects on Methane Emissions from Drill-Seeded, Delayed-Flood Rice Grown on a Clay Soil. Applied and Environmental Soil Science, 2016, Article ID: 9542361.
https://doi.org/10.1155/2016/9542361
[25] Sass, R.L., Fisher, F.M., Wang, Y.B., Turner, F.T. and Jund, M.F. (1992) Methane Emissions from Rice Fields: The Effect of Flood Water Management. Global Biogeochemical Cycles, 6, 249-262.
https://doi.org/10.1029/92GB01674
[26] Cai, Z., Xing, G., Yan, X., Xu, H., Tsuruta, H., Yagi, K. and Minami, K. (1997) Methane and Nitrous Oxide Emissions from Rice Paddy Fields as Affected by Nitrogen Fertilisers and Water Management. Plant & Soil, 196, 7-14.
https://doi.org/10.1023/A:1004263405020
[27] Lindau, C.W. and Bollich, P.K. (1993) Methane Emissions from Louisiana First and Ratoon Crop Rice. Soil Science, 156, 42-48.
https://doi.org/10.1097/00010694-199307000-00006
[28] Simmonds, M.B. anders, M., Adviento-Borbe, M.A., van Kessel, C., McClung, A. and Linquist, B.A. (2015) Seasonal Methane and Nitrous Oxide Emissions of Several Rice Cultivars in Direct Seeded Systems. Journal of Environmental Quality, 44, 103-114.
https://doi.org/10.2134/jeq2014.07.0286
[29] Brye, K.R., Nalley, L.L., Tack, J.B., Dixon, B.L., Barkley, A.P., Rogers, C.W., Smartt, A.D., Norman, R.J. and Jagadish, K. (2016) Factors Affecting Methane Emissions from Rice Production in the Lower Mississippi River Valley, USA. Geoderma Regional, 7, 223-229.
[30] Soil Survey Staff, Natural Resources Conservation Service, United States Department of Agriculture (2016) Web Soil Survey. http://websoilsurvey.sc.egov.usda.gov/App/HomePage.htm
[31] United States Department of Agriculture (USDA) and Natural Resources Conservation Service (NRCS) (2006) Land Resource Regions and Major Land Resource Areas of the United States, the Caribbean and the Pacific Basin.
https://www.nrcs.usda.gov/Internet/FSE_DOCUMENTS/nrcs142p2_050898.pdf
[32] National Oceanic and Atmospheric Administration (NOAA) (2002) Climatography of the United States No. 81: Monthly Station Normals of Temperature, Precipitation and Heating and Cooling Degree Days, 1971-2000, 03, Arkansas.
http://www.ncdc.noaa.gov/climatenormals/clim81/ARnorm.pdf
[33] Hardke, J.T., Frizzell, D.L., Castaneda-Gonzalez, E., Lee, G.J., Moldenhauer, K.A.K., Sha, X., Wamishe, Y.A., Norman, R.J., Blocker, M.M., Bulloch, J.A., Beaty, B.A., Mazzanti, R.S., Baker, R., Kirkpatrick, W., Duren, M. and Liyew, Y. (2016) Arkansas Rice Performance Trials, 2013-2015. In: Norman, R.J. and Moldenhauer, K.A.K., Eds., B.R. Wells Rice Research Studies, 2015, Arkansas Agricultural Experiment Station Research Series 634, Fayetteville, 267-274.
[34] Hardke, J.T. (2016) Reviewing the 2016 Arkansas Rice Season.
https://www.uaex.edu/farm-ranch/crops-commercial-horticulture/rice/Reviewing%20the%202016%20Arkansas%20Rice%20Season.pdf
[35] Moldenhauer, K.A.K., Gibbons, J.W., Lee, F.N., Bernhardt, J.L., Wilson, C.E., Cartwright, R., Norman, R.J., Blocker, M.M., Ahrent, D.K., Boyett, V.A., Stivers, A.M., Bullock, J.M. and Castaneda, E. (2010) “Roy J”, High Yielding, Stiff-Strawed, Long-Grain Rice Variety. In: Norman, R.J. and Moldenhauer, K.A.K., Eds., B.R. Wells Rice Research Studies, 2009, Arkansas Agricultural Experiment Station Research Series 581, Fayetteville, 53-59.
[36] Hardke, J.T. (2013) Arkansas Rice Production Handbook. University of Arkansas Division of Agriculture Cooperative Extension Service MP192, Little Rock.
[37] Norman, R., Slaton, N. and Roberts, T. (2013) Soil Fertility. In: Hardke, J.T., Ed., Arkansas Rice Production Handbook, University of Arkansas Division of Agriculture Cooperative Extension Service MP192, Little Rock, 69-102.
[38] Lorenz, G. and Hardke, J.T. (2013) Insect Management in Rice. In: Hardke, J.T., Ed., Arkansas Rice Production Handbook, University of Arkansas Division of Agriculture Cooperative Extension Service MP192, Little Rock.
[39] Scott, B., Norsworthy, J., Barber, T. and Hardke, J. (2013) Rice Weed Control. In: Hardke, J.T., Ed., Arkansas Rice Production Handbook, University of Arkansas Division of Agriculture Cooperative Extension Service MP192, Little Rock, 53-62.
[40] Tucker, M.R. (1992) Determination of Phosphorus by Mehlich 3 Extraction. In: Donohue, S.J., Ed., Soil and Media Diagnostic Procedures for the Southern Region of the United States, Virginia Agricultural Experiment Station Bulletin 374, Blacksburg, 6-8.
[41] Gee, G.W. and Or, D. (2002) Particle-Size Analysis. In: Dane, J.H. and Topp, G.C., Eds., Methods of Soil Analysis. Part 4: Physical Methods, Soil Science Society of America, Madison, 255-293.
[42] Livingston, G. and Hutchinson, G. (1995) Enclosure-Based Measurement of Trace Gas Exchange: Applications and Sources of Error. In: Matson, P.A. and Harriss, R.C., Eds., Biogenic Trace Gases: Measuring Emissions from Soil and Water, Blackwell Sciences Ltd., Osney Mead, Oxford, 14-51.
[43] Parkin, T. and Venterea, R. (2010) Chamber-Based Trace Gas Flux Measurements.
https://www.ars.usda.gov/ARSUserFiles/np212/Chapter%203.%20GRACEnet%20
Trace%20Gas%20Sampling%20Protocols.pdf
[44] Butterbach-Bahl, K., Papen, H. and Rennenberg, H. (1997) Impact of Gas Transport through Rice Cultivars on Methane Emission from Rice Paddy Fields. Plant, Cell & Environment, 20, 1175-1183.
https://doi.org/10.1046/j.1365-3040.1997.d01-142.x
[45] Holzapfel-Pschorn, A., Conrad, R. and Seiler, W. (1986) Effects of Vegetation on the Emission of Methane from Submerged Paddy Soil. Plant & Soil, 92, 223-233.
https://doi.org/10.1007/BF02372636
[46] Nouchi, I., Mariko, S. and Aoki, K. (1990) Mechanism of Methane Transport from the Rhizosphere to the Atmosphere through Rice Plants. Plant Physiology, 94, 59-66.
https://doi.org/10.1104/pp.94.1.59
[47] Huang, Y., Jiao, Y., Zong, L., Zheng, X., Sass, R.L. and Fisher, F.M. (2002) Quantitative Dependence of Methane Emission on Soil Properties. Nutrient Cycling in Agroecosystems, 64, 157-167.
https://doi.org/10.1023/A:1021132330268
[48] Masscheleyn, P.H., DeLaune, R.D. and Patrick, W.H. (1993) Methane and Nitrous Oxide Emissions from Laboratory Measurements of Rice Soil Suspension: Effect of Soil Oxidation-Reduction Status. Chemosphere, 26, 251-260.
[49] Shang, Q., Yang, X., Gao, C., Wu, P., Liu, J., Xu, Y., Shen, Q., Zou, J. and Guo, S. (2011) Net Annual Global Warming Potential and Greenhouse Gas Intensity in Chinese Double Rice-Cropping Systems: A 3-Year Field Measurement in Long-Term Fertilizer Experiments. Global Change Biology, 17, 2196-2210.
https://doi.org/10.1111/j.1365-2486.2010.02374.x
[50] Adviento-Borbe, M.A., Pittelkow, C.M. anders, M., van Kessel, C., Hill, J.E., McClung, A.M., Six, J. and Linquist, B.A. (2013) Optimal Fertilizer N Rates and Yield-Scaled Global Warming Potential in Drill Seeded Rice. Journal of Environmental Quality, 42, 1623-1634.
https://doi.org/10.2134/jeq2013.05.0167
[51] Rogers, C.W., Brye, K.R., Norman, R.J., Gbur, E.E., Mattice, J.D., Parkin, T.B. and Roberts, T.L. (2013) Methane Emissions from Drill-Seeded, Delayed-Flood Rice Production on a Silt-Loam Soil in Arkansas. Journal of Environmental Quality, 42, 1059-1069.
https://doi.org/10.2134/jeq2012.0502
[52] Weller, S., Kraus, D., Butterbach-Bahl, K., Wassmann, R., Tirol-Padre, A. and Kiese, R. (2015) Diurnal Patterns of Methane Emissions from Paddy Rice Fields in the Philippines. Journal of Plant Nutrition and Soil Science, 178, 755-767.
https://doi.org/10.1002/jpln.201500092

  
comments powered by Disqus

Copyright © 2018 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.