Author Correction: The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data

The following authors were omitted from the original version of this Data Descriptor: Markus Reichstein and Nicolas Vuichard. Both contributed to the code development and N. Vuichard contributed to the processing of the ERA-Interim data downscaling. Furthermore, the contribution of the co-author Frank Tiedemann was re-evaluated relative to the colleague Corinna Rebmann, both working at the same sites, and based on this re-evaluation a substitution in the co-author list is implemented (with Rebmann replacing Tiedemann). Finally, two affiliations were listed incorrectly and are corrected here (entries 190 and 193). The author list and affiliations have been amended to address these omissions in both the HTML and PDF versions

The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data.

The FLUXNET2015 dataset provides ecosystem-scale data on CO2, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible

The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data

The FLUXNET2015 dataset provides ecosystem-scale data on CO2, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible.Peer reviewe

Dynamics of temperature normalized stem CO2 efflux in Norway spruce stand

Respiration of stems contributes approximately 8 to 13 % to the total respiration of forest ecosystem, which is not negligible, and it has to be included in carbon flux estimates. The aim of this study was to determine dynamics of stem CO2 efflux during the growing season in Norway spruce stand and factors affecting this efflux. Continuous measurements of stem CO2 efflux were carried out by an automated system during the growing season in 2006–2009. Further measured characteristics were stem temperature, stem increment and precipitations. Stem CO2 efflux was in tight relationship with changes in temperature with the mean coefficient of determination of 0.76. This infers that temperature was the main factor driving changes in CO2 efflux during the season. To eliminate effect of temperature and determine other factors influencing stem CO2 efflux, CO2 efflux was normalized for temperature of 10 °C (R10). Basic seasonal course of R10 followed the pattern of stem growth rate with its maxima in June and July. The other factor effect, which was possible to determine, was presence of rainfall. Rainfall strong enough caused mostly increase in R10. This effect was the most significant when the R10 course had a decreasing trend in the second part of the growing season

Effect of measurement time of the day on the relationship between temperature and soil CO2 efflux

In this study we investigated effect of the time of the day when manual measurements of soil CO2 efflux are performed on estimates of seasonal sums of released carbon from the soil. We subsampled continuous measurement of soil CO2 efflux into six sets of data in accordance to the time of the day when the measurements were taken – 0 h, 4 h, 8 h, 12 h, 16 h and 20 h. To estimate seasonal carbon flux from the soil we used continuously measured soil temperature and parameters R10 (soil CO2 efflux normalized for temperature of 10 °C) and Q10 (the proportional change in CO2 efflux caused by 10 °C increase in temperature) calculated from continuous measurements and from measurements taken at individual hours. Values of Q10 calculated from 12 h and 16 h data were lower than Q10 calculated from continuous measurements. On the contrary, Q10 at 0 h, 4 h, 8 h and 20 h were higher. Seasonal carbon flux from the soil based on 0 h, 4 h and 8 h measurements was overestimated compare to the flux calculated from continuous measurements. On the contrary, measurements at 12 h, 16 h and 20 h measurements underestimated the carbon flux. The under- or overestimation was significant for 0 h, 4 h, 8 h and 20 h data sub-sets

EXTRACTION OF ACID PHOSPHOMONOESTERASE FROM SOIL: TESTING OF VARIOUS EXTRACTANS

Abstract HOLÍK, L., DUNDEK, P., VRANOVÁ, V., REJŠEK, K., JANOUŠ, D., FORMÁNEK, P.: Extraction of acid phosphomonoesterase from soil: testing of various extractants. Acta univ. agric. et silvic. Mendel. Brun., 2011, LIX, No. 3, pp. 51-5

The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data

The FLUXNET2015 dataset provides ecosystem-scale data on CO2, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible

Author Correction: The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data (Scientific Data, (2020), 7, 1, (225), 10.1038/s41597-020-0534-3)

The following authors were omitted from the original version of this Data Descriptor: Markus Reichstein and Nicolas Vuichard. Both contributed to the code development and N. Vuichard contributed to the processing of the ERA-Interim data downscaling. Furthermore, the contribution of the co-author Frank Tiedemann was re-evaluated relative to the colleague Corinna Rebmann, both working at the same sites, and based on this re-evaluation a substitution in the co-author list is implemented (with Rebmann replacing Tiedemann). Finally, two affiliations were listed incorrectly and are corrected here (entries 190 and 193). The author list and affiliations have been amended to address these omissions in both the HTML and PDF versions. © 2021, This is a U.S. government work and not under copyright protection in the U.S.; foreign copyright protection may apply