2016
DOI: 10.1111/gcbb.12343
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Comparative assessment of ecosystem C exchange in Miscanthusand reed canary grass during early establishment

Abstract: Land-use change to bioenergy crop production can contribute towards addressing the dual challenges of greenhouse gas mitigation and energy security. Realisation of the mitigation potential of bioenergy crops is, however, dependent on suitable crop selection and full assessment of the carbon (C) emissions associated with land conversion. Using eddy covariance-based estimates, ecosystem C exchange was studied during the early-establishment phase of two perennial crops, C 3 reed canary grass (RCG) and C 4 Miscant… Show more

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Cited by 9 publications
(3 citation statements)
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References 100 publications
(114 reference statements)
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“…Data outside a ± 3.5 standard deviation range (consecutive six values) from a 14-day running mean window were identified as outliers and were removed (Wagle et al, 2015a). This allowed us to filter out the data outside of the accepted range of -50 < CO2 flux < 60 μmol m -2 s -1 , -20 < LE < 600 W m -2 , and -100 < H < 400W m -2 (Joo et al, 2016;Ní Choncubhair et al, 2016;Zeri et al, 2011). We used the online R package "REddyProc" tool developed at the Max Planck Institute for Biogeochemistry, Jena, Germany (Moffat et al, 2007;Reichstein et al, 2005) for gap filling of flux data and partitioning of NEE into ecosystem respiration (ER) and gross primary production (GPP).…”
Section: Data Screening and Gap Filling For Eddy Flux Tower Datamentioning
confidence: 99%
“…Data outside a ± 3.5 standard deviation range (consecutive six values) from a 14-day running mean window were identified as outliers and were removed (Wagle et al, 2015a). This allowed us to filter out the data outside of the accepted range of -50 < CO2 flux < 60 μmol m -2 s -1 , -20 < LE < 600 W m -2 , and -100 < H < 400W m -2 (Joo et al, 2016;Ní Choncubhair et al, 2016;Zeri et al, 2011). We used the online R package "REddyProc" tool developed at the Max Planck Institute for Biogeochemistry, Jena, Germany (Moffat et al, 2007;Reichstein et al, 2005) for gap filling of flux data and partitioning of NEE into ecosystem respiration (ER) and gross primary production (GPP).…”
Section: Data Screening and Gap Filling For Eddy Flux Tower Datamentioning
confidence: 99%
“…It is also not possible to rule out temporary losses of soil C following the tillage contributing to the higher respiration, with these losses compensated with later gains resulting in the absence of any observable impacts within the soil samples. Such direct loses of soil C have been proposed as a contributing factor to analogous patterns of changes in GPP:TER ratios observed in the early stages of land use change to bioenergy Ní Choncubhair et al, 2017;Zenone et al, 2013). Future quantification of the relative contribution of these different potential drivers may open pathways to reduced unwanted respiration and the associated climate forcing.…”
Section: F I G U R Ementioning
confidence: 96%
“…During the quality check, we also excluded data outside a ±3.5 standard deviation range from a 14-day running mean window [29]. This allowed us to filter out the data outside of the accepted range [30][31][32]. The gaps in the dataset created due to filtering of bad quality and unreliable values and malfunctioning of the sensors were gap filled using REddyProc package, developed at the Max Planck Institute for Biogeochemistry, Jena, Germany [33,34].…”
Section: Introductionmentioning
confidence: 99%