This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.Here, we briefly respond to critique of our study (1) by Wassmann et al. (2). A detailed response to their letter is available online (edf.org/riceN2O)

Adhya, Tapan K.

Ahuja, Richie

Hamburg, Steven P.

Kritee, Kritee

Loecke, Terrance D.

Nair, Drishya

Proville, Jeremy

Rudek, Joseph

English

KU ScholarWorks

LETTERREPLY TO WASSMANN ET AL.:Moredataathighsampling intensity frommedium-and intense-intermittently flooded rice farmsis crucialKritee Kriteea,1, Joseph Rudeka, Jeremy Provillea, Tapan K. Adhyab, Terrance Loeckec, Drishya Naird,e,Richie Ahujaa, and Steven P. HamburgaHere, we briefly respond to critique of our study (1) byWassmann et al. (2). A detailed response to their letteris available online (edf.org/riceN2O).Field DesignIt is not necessary to compare intermittently floodedfarms with continuously flooded farms serving ascontrols to understand the impacts of multiple aera-tion events on soil redox conditions and resulting rice-N2O. Wassmann et al. (2) define alternate wetting anddrying (AWD) as a mitigation strategy, whereas weconsider AWD as intermittent flooding that includesalternating dry and wet periods regardless of thecause (active drainage and/or percolation). Our studywas conducted in farmers’ fields which, as stated pre-viously (1, 3), oftenmeans that watermanagement doesnot align precisely with recommendations. The farmersin our study considered the “baseline” condition as con-tinuous flooding. However, daily water-level measure-ments highlighted that frequent irrigation does notactually mean continuous flooding. Low clay content ofsoils cannot be the sole reason of our high rice-N2Oresults: A previous study has shown high rice-N2O un-der deliberate AWD in clay-rich soils (4).Sampling FrequencyWassmann et al. (2) cite studies with high-frequencysampling that are not relevant because they wereperformed under conditions that should not triggerhigh rice-N2O—that is, continuous (5, 6) or lowlandflooding (7), no waterlogging (post–rice-harvest dryperiod) (8), or midseason drainage (a form of mild in-termittent flooding) (9). We call for high-frequencysampling measurements from medium- or intense-intermittent flooding regimes.Interpolation ErrorsWe did not use broad peaks but instead used an ex-ponential curve interpolation method described ear-lier (10), because we recognized errors introducedusing other interpolation methods. Our supportingfigures show broad peaks because they present linearinterpolation of raw data, not plots based on expo-nential decay of the peaks that were used to estimateseasonal N2O emissions.Model DevelopmentOur model is constrained to linear functions charac-terizing known mechanistic drivers of fluxes, and theresult is an excellent fit. We are not advocating forour model relative to others. Other models [includingdenitrification–decomposition (DNDC)] might haverice-N2O risks similar to ours if they incorporate upda-ted fertilizer use, empirically determined high rice-N2O,and intense-intermittent flooding regimes (1).Interpretation of RisksWe do not claim that all practices result in high rice-N2O: Our extrapolation under the continuous-floodingscenario suggests negligible rice-N2O. We do assertthat precise management/flooding condition mapsat farmer-managed farms and high-frequency sam-pling measurements at intense-intermittent floodingregimes are required to fully understand N2O trade-offsof recommendations designed for reducing methaneemissions.We posit that many farmers practicing AWD mightbe deploying mild-intermittent flooding regimes thatwill minimize both methane and rice-N2O emissions.We agree that more data are necessary to better as-sess both the conditions that trigger high rice-N2OaEnvironmental Defense Fund, New York, NY 10010; bSchool of Biotechnology, Kalinga Institute of Industrial Technology, Bhubaneswar 751 024,Odisha, India; cEnvironmental Studies Program, University of Kansas, Lawrence, KS 66045; dDepartment of Agroecology, Aarhus University, Viborg8000, Denmark; and eFair Climate Network, Bagepalli 561 207, Karnataka, IndiaAuthor contributions: K.K. and D.N. analyzed data; and K.K., J.R., J.P., T.K.A., T.L., R.A., and S.P.H. wrote the paper.The authors declare no conflict of interest.Published under the PNAS license.1To whom correspondence should be addressed. Email: kritee@edf.org.Published online January 22, 2019.1466–1467 | PNAS | January 29, 2019 | vol. 116 | no. 5 www.pnas.org/cgi/doi/10.1073/pnas.1819676116LETTERDownloaded by guest on February 8, 2021 emissions and the spatiotemporal variability of those conditionsglobally. We hope that the global community will collect additionaldata that can be used to validate and improve our model and othersthat predict emissions (e.g., DNDC and Daycent). Weekly measure-ments are clearly insufficient to capture rice-N2O emission dynamics,and we encourage future collections to be at least once every 2 d.1 Kritee K, et al. (2018) High nitrous oxide fluxes from rice indicate the need to manage water for both long- and short-term climate impacts. Proc Natl Acad Sci USA115:9720–9725.2 Wassmann R, et al. (2019) New records of very high nitrous oxide fluxes from rice cannot be generalized for water management and climate impacts. Proc NatlAcad Sci USA 116:1464–1465.3 Kritee K, et al. (2018) Reply to Yan and Akiyama: Nitrous oxide emissions from rice and their mitigation potential depend on the nature of intermittent flooding.Proc Natl Acad Sci USA 115:E11206–E11207.4 Lagomarsino A, et al. (2016) Alternate wetting and drying of rice reduced CH4 but triggered N2O peaks in a clayey soil of central Italy. Pedosphere 26:533–548.5 Gaihre YK, et al. (2018) Nitrous oxide and nitric oxide emissions and nitrogen use efficiency as affected by nitrogen placement in lowland rice fields. Nutr CyclAgroecosyst 110:277–291.6 Gaihre YK, et al. (2015) Impacts of urea deep placement on nitrous oxide and nitric oxide emissions from rice fields in Bangladesh. Geoderma 259-260:370–379.7 Abao EB, Bronson KF, Wassmann R, Singh U (2000) Simultaneous records of methane and nitrous oxide emissions in rice-based cropping systems under rainfedconditions. Nutr Cycl Agroecosyst 58:131–139.8 Yao Z, et al. (2009) Comparison of manual and automated chambers for field measurements of N2O, CH4, CO2 fluxes from cultivated land. Atmos Environ43:1888–1896.9 Bronson KF, Neue H-U, Abao EB, Singh U (1997) Automated chamber measurements of methane and nitrous oxide flux in a flooded rice soil: I. Residue, nitrogen,and water management. Soil Sci Soc Am J 61:981–987.10 Tiwari R, et al. (2015) Sampling guidelines and analytical optimization for direct greenhouse gas emissions from tropical rice and upland cropping systems.Carbon Manag 6:169–184.Kritee et al. PNAS | January 29, 2019 | vol. 116 | no. 5 | 1467Downloaded by guest on February 8, 2021 

Reply to Wassmann et al.: More data at high sampling intensity from medium- and intense-intermittently flooded rice farms is crucial

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Reply to Wassmann et al.: More data at high sampling intensity from medium- and intense-intermittently flooded rice farms is crucial

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