High nitrous oxide fluxes from rice indicate the need to manage water for both long- and short-term climate impacts

Kritee, K.; Nair, Drishya; Zavala-Araiza, Daniel; Proville, Jeremy; Rudek, J.; Adhya, T. K.; Loecke, Terrance D.; Esteves, Tashina; Balireddygari, Shalini; Dava, Obulapathi; Ram, Karthik; Abhilash, S. R.; Madasamy, Murugan; Dokka, Ramakrishna V.; Anandaraj, Daniel; Athiyaman, D.; Reddy, M. M.; Ahuja, Richie; Hamburg, Steven P.

doi:10.1073/pnas.1809276115

Cited by 146 publications

(81 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In recent decades increasing emphasis has been put on reducing water-use in paddy cultivation and encouraging intermittent irrigation. However, it has been claimed in a recent report [25], that even as intermittent irrigation helps in water saving and a reduction in CH 4 emissions in comparison to the classical way of continuous flooding based paddy cultivation, the advantages are offset to a great extent by an increase in the N 2 O emissions. The more recent findings of these authors [7,19] do not support the claims of Kritee et al [25].…”

Section: Resultsmentioning

confidence: 99%

“…However, it has been claimed in a recent report [25], that even as intermittent irrigation helps in water saving and a reduction in CH 4 emissions in comparison to the classical way of continuous flooding based paddy cultivation, the advantages are offset to a great extent by an increase in the N 2 O emissions. The more recent findings of these authors [7,19] do not support the claims of Kritee et al [25]. Evidently a lot more research is required before a broad consensus emerges on the role of water use in driving the net GHG emissions from paddy wetlands.…”

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

Modelling Methane and Nitrous Oxide Emissions from Rice Paddy Wetlands in India Using Artificial Neural Networks (ANNs)

Abbasi

Luithui

et al. 2019

Water

View full text Add to dashboard Cite

Paddy fields, which are shallow man-made wetlands, are estimated to be responsible for ~11% of the total methane emissions attributed to anthropogenic sources. The role of water use in driving these emissions, and the apportioning of the emissions to individual countries engaged in paddy cultivation, are aspects that have been mired in controversy and disagreement. This is largely due to the fact that methane (CH4) emissions not only change with the cultivar type but also regions, climate, soil type, soil conditions, manner of irrigation, type and quantity of fertilizer added—to name a few. The factors which can influence these aspects also encompass a wide range, and have origins in causes which can be physical, chemical, biological, and combinations of these. Exceedingly complex feedback mechanisms, exerting different magnitudes and types of influences on CH4 emissions under different conditions, are operative. Similar is the case of nitrous oxide (N2O); indeed, the present level of understanding of the factors which influence the quantum of its emission is still more patchy. This makes it difficult to even understand precisely the role of the myriad factors, less so model them. The challenge is made even more daunting by the fact that accurate and precise data on most of these aspects is lacking. This makes it nearly impossible to develop analytical models linking causes with effects vis a vis CH4 and N2O emissions from paddy fields. For situations like this the bioinspired artificial intelligence technique of artificial neural network (ANN), which can model a phenomenon on the basis of past data and without the explicit understanding of the mechanism phenomena, may prove useful. However, no such model for CH4 or N2O has been developed so far. Hence the present work was undertaken. It describes ANN-based models developed by us to predict CH4 and N2O emissions using soil characteristics, fertilizer inputs, and rice cultivar yield as inputs. Upon testing the predictive ability of the models with sets of data not used in model development, it was seen that there was excellent agreement between model forecasts and experimental findings, leading to correlations coefficients of 0.991 and 0.96, and root mean square error (RMSE) of 11.17 and 261.3, respectively, for CH4 and N2O emissions. Thus, the models can be used to estimate CH4 and N2O emissions from all those continuously flooded paddy wetlands for which data on total organic carbon, soil electrical conductivity, applied nitrogen, phosphorous and potassium, NPK, and grain yield is available.

show abstract

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Modelling Methane and Nitrous Oxide Emissions from Rice Paddy Wetlands in India Using Artificial Neural Networks (ANNs)

Abbasi

Luithui

et al. 2019

Water

View full text Add to dashboard Cite

show abstract

“…. General understanding of climate impacts of rice farms under continuous flooding or alternate wetting and drying (AWD) (10) compared with highest rice-N 2 O from two studies (1,7) to highlight that N 2 O, not methane, is the dominant greenhouse gas emitted under intense forms of intermittent flooding.…”

mentioning

confidence: 99%

Reply to Yan and Akiyama: Nitrous oxide emissions from rice and their mitigation potential depend on the nature of intermittent flooding

Kritee

Rudek

Hamburg

et al. 2018

Proc. Natl. Acad. Sci. U.S.A.

Self Cite

View full text Add to dashboard Cite

“…Although DSR, nutrient management, and AWD provide many benefits in terms of climate change adaptation and mitigation, they also have many potential trade-offs. Balancing methane versus nitrous oxide emission is one example of these trade-offs [55,57].…”

Section: Understanding Synergies and Trade-off Of Solutions To Climatmentioning

confidence: 99%

Trans-Disciplinary Responses to Climate Change: Lessons from Rice-Based Systems in Asia

Hellin

Balié

Fisher

et al. 2020

Climate

View full text Add to dashboard Cite

Climate change will continue to have a largely detrimental impact on the agricultural sector worldwide because of predicted rising temperatures, variable rainfall, and an increase in extreme weather events. Reduced crop yields will lead to higher food prices and increased hardship for low income populations, especially in urban areas. Action on climate change is one of the Sustainable Development Goals (SDG 13) and is linked to the Paris Climate Agreement. The research challenge posed by climate change is so complex that a trans-disciplinary response is required, one that brings together researchers, practitioners, and policy-makers in networks where the lines between “research” and “development” become deliberately blurred. Fostering such networks will require researchers, throughout the world, not only to work across disciplines but also to pursue new South–North and South–South partnerships incorporating policy-makers and practitioners. We use our diverse research experiences to describe the emergence of such networks, such as the Direct Seeded Rice Consortium (DSRC) in South and Southeast Asia, and to identify lessons on how to facilitate and strengthen the development of trans-disciplinary responses to climate change.

show abstract

High nitrous oxide fluxes from rice indicate the need to manage water for both long- and short-term climate impacts

Cited by 146 publications

References 28 publications

Modelling Methane and Nitrous Oxide Emissions from Rice Paddy Wetlands in India Using Artificial Neural Networks (ANNs)

Modelling Methane and Nitrous Oxide Emissions from Rice Paddy Wetlands in India Using Artificial Neural Networks (ANNs)

Reply to Yan and Akiyama: Nitrous oxide emissions from rice and their mitigation potential depend on the nature of intermittent flooding

Trans-Disciplinary Responses to Climate Change: Lessons from Rice-Based Systems in Asia

Contact Info

Product

Resources

About