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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Global Change Biolog...arrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Global Change Biology
Article . 2014 . Peer-reviewed
License: Wiley Online Library User Agreement
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Optimizing rice yields while minimizing yield‐scaled global warming potential

Authors: Cameron M, Pittelkow; Maria A, Adviento-Borbe; Chris, van Kessel; James E, Hill; Bruce A, Linquist;

Optimizing rice yields while minimizing yield‐scaled global warming potential

Abstract

AbstractTo meet growing global food demand with limited land and reduced environmental impact, agricultural greenhouse gas (GHG) emissions are increasingly evaluated with respect to crop productivity, i.e., on a yield‐scaled as opposed to area basis. Here, we compiled available field data on CH4 and N2O emissions from rice production systems to test the hypothesis that in response to fertilizer nitrogen (N) addition, yield‐scaled global warming potential (GWP) will be minimized at N rates that maximize yields. Within each study, yield N surplus was calculated to estimate deficit or excess N application rates with respect to the optimal N rate (defined as the N rate at which maximum yield was achieved). Relationships between yield N surplus and GHG emissions were assessed using linear and nonlinear mixed‐effects models. Results indicate that yields increased in response to increasing N surplus when moving from deficit to optimal N rates. At N rates contributing to a yield N surplus, N2O and yield‐scaled N2O emissions increased exponentially. In contrast, CH4 emissions were not impacted by N inputs. Accordingly, yield‐scaled CH4 emissions decreased with N addition. Overall, yield‐scaled GWP was minimized at optimal N rates, decreasing by 21% compared to treatments without N addition. These results are unique compared to aerobic cropping systems in which N2O emissions are the primary contributor to GWP, meaning yield‐scaled GWP may not necessarily decrease for aerobic crops when yields are optimized by N fertilizer addition. Balancing gains in agricultural productivity with climate change concerns, this work supports the concept that high rice yields can be achieved with minimal yield‐scaled GWP through optimal N application rates. Moreover, additional improvements in N use efficiency may further reduce yield‐scaled GWP, thereby strengthening the economic and environmental sustainability of rice systems.

Related Organizations
Keywords

Greenhouse Effect, Air Pollutants, Nitrogen, Nitrous Oxide, Agriculture, Oryza, Global Warming, Gases, Fertilizers, Methane

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
126
Top 1%
Top 10%
Top 10%
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