A standardized conceptual and practical approach to automatically model ecosystem CO2 fluxes based on periodic closed chamber measurements

Open Research Data Portal
DOI for Scientific and Technical Data
10.4228/ZALF.2011.339
Title
A standardized conceptual and practical approach to automatically model ecosystem CO2 fluxes based on periodic closed chamber measurements
Citation
Hoffmann, Mathias; Jurisch, Nicole; Albiac Borraz, Elisa; Augustin, Jürgen (2017): A standardized conceptual and practical approach to automatically model ecosystem CO2 fluxes based on periodic closed chamber measurements, Leibniz Centre for Agricultural Landscape Research (ZALF) e.V.[doi: 10.4228/ZALF.2011.339]
Publisher
Leibniz Centre for Agricultural Landscape Research (ZALF), Müncheberg (Germany)
Dates

Collected: 2010/2012
Available: 2017
Accepted: 2017
Contributor(s)
DataCollector: Institute of Landscape Biogeochemistry, Leibniz Centre for Agricultural Landscape Research (ZALF)
ContactPerson: Hoffmann, Mathias
HostingInstitution: Leibniz Centre for Agricultural Landscape Research (ZALF), Müncheberg (Germany)
Creator(s)
Hoffmann, Mathias
Jurisch, Nicole
Albiac Borraz, Elisa
Augustin, Jürgen
Subject(s)
Chamber measurement
Carbon dioxide
Flux calculation
empirically modelling
R-script

AGROVOC:
peat soil

GEMET:
fen
Description
Closed chamber measurements are widely used for determining the CO2 exchange of different ecosystems. Among the chamber design and operational handling, the data processing procedure is a considerable source of uncertainty of obtained results. We developed a standardized automatic dataprocessing algorithm, based on the statistical computing environment R, which (i) calculates CO2 fluxes measured by closed chmabers, (ii) parameterizes temperature (Reco) and PAR (GPP) dependency models, (iii) optionally computes an adaptive temperature model, (iv) models Reco, GPP and NEE, and (v) evaluates model uncertainty. The dataset contains the developed R-script and the used test data, originating from measurments (2010-2012) at a cultivated fen situated in the northeast of Germany.
Language
English
Related Datasets
IsSupplementTo: http://dx.doi.org/10.1016/j.agrformet.2014.09.005
Location
Paulinenaue
Data Format
csv, pdf
Type of Resource
Dataset: Tables, Script
Rights
Creative Commons BY 4.0
Parameters
(parameter; compartment; instrument; method)
soil temperature(°C); -2cm; T-107 Temperature Probe; half hourly mean
soil temperature(°C); -2cm; thermometer, VOLTCRAFT DET1R; instantaneous value
soil temperature(°C); -5cm; T-107 Temperature Probe; half hourly mean
soil temperature(°C); -10cm; T-107 Temperature Probe; half hourly mean
PAR radiation(µmol/m² s); 200cm; Skye quantumsensor (SKP 215); half hourly mean
Air temperature(°C); Chamber headspace; T-107 Temperature Probe; instantaneous value
Air temperature(°C); outside the hood (200cm height) ; T-107 Temperature Probe; instantaneous value
PAR radiation(µmol/m² s); 20cm; Skye quantumsensor (SKP 215); instantaneous value
soil temperature(°C); -5cm; thermometer, VOLTCRAFT DET1R; instantaneous value
soil temperature(°C); -10cm; thermometer, VOLTCRAFT DET1R; instantaneous value
air pressure(Pa); Air; Weather Transmitter; default
Air temperature(°C); outside the hood (200cm height) ; T-107 Temperature Probe; half hourly mean
CO2_concentration(ppm); Chamber headspace; LI-820 and LI-840, LI-COR; instantaneous value
Structure of Data Table(s)

Table: Weather_station_data

Column name Measurement aim Measurement unit Description
DATE_TIME   Date and time, format: "DD.MM.YYYY HH:MM"
PAR_AVG Photosynthetic active radiation (PAR)  µmol/m² s   Half-hourly PAR in µmol/m² s , measured by the nearbye weather station
AIR_TEMP_200CM_AVGAir temperature in 200 cm height°CHalf-hourly air temperature in °C in 200 cm height, measured by the nearbye weather station
SOIL_TEMP_2CM_AVG Soil temperature in 2 cm soil depth°CHalf-hourly soil temperature in °C in 2 cm soil depth, measured by the nearbye weather station
SOIL_TEMP_5CM_AVG Soil temperature in 5 cm soil depth°CHalf-hourly soil temperature in °C in 5 cm soil depth, measured by the nearbye weather station
SOIL_TEMP_10CM_AVGSoil temperature in 10 cm soil depth°CHalf-hourly soil temperature in °C in 10 cm soil depth, measured by the nearbye weather station

 

Table: CO2_FLUX_data

Column name Measurement aim Measurement unit Description
DATE_TIME   Date and time, format: "DD.MM.YYYY HH:MM"
RECORD_ID   Recordnumber (rownumber)
MEASUREMENT_ID  Identification number of the measurement
AIR_TEMP_IN Air temperature inside chamber°CAir temperature inside the chamber in °C
AIR_TEMP_OUT Air temperature outside chamber°CAir temperature outside the chamber in °C
CO2_CONCENTRATIONCO2-concentrationppm Measured CO2-concentration, using a infrared gas analyzer (IRGA; LI-820/LI-840, LI-COR Biosciences, Nebraska USA)
PAR Photosynthetic active radiation (PAR)µmol/m² s Instantaneous PAR in µmol/m² s , measured by the nearbye weather station
STATUS   System status
SITE_PLOT_NAME  Site and Plot name
CHAMBER_TYPE   Chamber type (D=opaque; T=transparent)
SOIL_TEMP_2CMSoil temperature in 2 cm soil depth°CInstantaneous soil temperature in °C in 2 cm soil depth, measured by the nearbye weather station
SOIL_TEMP_5CM Soil temperature in 5 cm soil depth°CInstantaneous soil temperature in °C in 5 cm soil depth, measured by the nearbye weather station
SOIL_TEMP_10CMSoil temperature in 10 cm soil depth°CInstantaneous soil temperature in °C in 10 cm soil depth, measured by the nearbye weather station
DUMMY_I   
DUMMY_II   
DUMMY_III   
CHAMBER_VOLUME Chamber volumeChamber volume in m³
AIR_PRESSUREAir pressurePaStandardized air pressure (101300 Pa)
CAMPAIGN  Identification number of the measurement campaign
Tool for calculation

R Documentation

Automated and standardized modelling of ecosystem CO2 fluxes

Usage

### SETTING
Measurement<-c("place from ... to ...")
folder_name<-"C:/test/"
Site_Plot_name<-c("site_plot I","site_plot II","site_plot III")
Exclude_Plot<-c("NO")
Modelling_Source<-c("Site")
Name_climate_data<-c("climate_station.csv")
Window_Size<-c(7)
FOG_Treatment<-c(500)
Preference_Window<-c(0.25)
basal_area<-c(0.5625)
Edge_cutter<-c(0.1)
PAR_correcting<-c(0.86)
Water_steam_correction<-c("NO")
significance_level<-c(0.1)
significance_level_linear<-c(0.1)
Temp_model<-c("YES",5)
Jumper<-c(3)
Range<-c(90)
PAR_Vorgabe<-c("WATT")
Time_step<-c(30)
Flux_calculation_approach<-c("LINEAR")

### Artificial campaign data
Artificial_date_1<-c("NO","AVG","05.10.2009 12:00",1,50,0,-0.01)

### Artificial harvest data
Harvest_date_1<-c("YES","08.09.2010 12:00",1,50,0,-0.01)

Arguments

MeasurementA character string giving the measurement place and periode.
folder_name A character string giving path to the working directory including the folder: ‘source’ (with all measured source data) & ‘climate_station’ (with one file of climate data).
Site_Plot_name Character strings giving the measurement site and plot.
Exclude_Plot A character string of a certain Site_plot_name or NO defining whether or not excluding the named plot.
Modelling_Source A character string of the certain Site_plot_name or site defining wether or not exclusively modelling the named plot.
Name_climate_data A character string giving the file name for the climate data.
Window_Size Numeric value >3. Accepted minimum number of data points to be kept for single CO2 fluxes.
FOG_Treatment Numeric value. Higher CO2 fluxes caused by stable stratification of the air will be proportional reduced. Threshold value of the Initial CO2 concentration (ppm) that is characteristic for stable layering.
Preference_Window Numeric value. percentage of data points that will be removed at the beginning (non-transparent chamber) and the end (transparent chamber) of single CO2 fluxes to avoid saturation effect.
basal_area Numeric value. Area of measured frames.
Edge_cutter Numeric value from 0 to 100. Percentage of data points that will be removed at the beginning and the end of each single CO2 flux to exclude "noise" in the data before moving window calculation.
PAR_correcting Numeric value. PAR values detected outside the chamber during CO2 measurement will be reduced by the percentage by which the chamber is shielding the radiation.
Water_steam_correction A character string YES or NO, whether a correction depending on the water steam is required.
significance_level Numeric value. Significance level for regression parameters.
significance_level_linear Numeric value. Significance level for linear regression parameters.
Temp_model A character string YES or NO, if temperature modell is required or not. Additional a numeric giving the minimum acceptable temperature range for regression.
Jumper Numeric value. A factor, multiplied with IQR. Outliner test for rapid changes in measured CO2 concentration to avoid unrealistic flux rates caused by measurement errors.
Range Numeric value. Percentage of the daily temperature range which should be covered by the measured temperature during the Reco measurements.
PAR_Vorgabe A character string WATT or MMOL giving the unit of measured PAR.
Time_step A Numeric value. Required Intervall in minutes for the resulting CO2 modell.
Flux_calculation_approach Choosing the required calculation approach for CO2 fluxes: LINEAR, EXPONENTIAL or QUADRATIC.
Artificial_date_1 ... 40 To use the option of setting artificial campaign dates choose YES instead of NO, give the control temperature for Reco (IN, OUT, -2, -5), date and time 01.01.2011 12:00 as well as the parameters for Rref, E0, alpha and Gpmax.
Harvest_date_1 ... 20 To use the option of setting artificial campaigns for harvest events choose YES instead of NO, give date and time 01.01.2011 12:00 as well as the parameters for Rref, E0, alpha and Gpmax.

Details

A modular R script was developed for stepwise dataprocessing and final visualization. Based on raw data of CO2 concentration change within-chamber and environmental parameters, the program

1. calculates measured CO2 fluxes and parameterizes Reco and GPP models within a integrative step,

2. optionally computes an adaptive temperature model, and

3. models Reco, GPP, and NEE for the entire measurement period.

4. Finally, the model performance is evaluated. Depending on availability and quality of the raw data, a range of user defined parameters can be used, to adjust the script to different measurement and ecosystems.

Statistical analysis, model calibration and comprehensive error prediction are provided for all steps of the modeling process.

Note

The editors/authors excludes all liability for the topicality, correctness, completeness or quality of the provided calculation tool and its results!

Author(s)

Mathias Hoffmann Mathias.Hoffmann@zalf.de, Nicole Jurisch, Elisa Albiac Borraz

References

M. Hoffmann, N. Jurisch, E. Albiac Borraz, U. Hagemann, M. Droesler, M. Sommer, J. Augustin (2015), Automated modeling of ecosystem CO2 fluxes based on periodic closed chamber measurements: A standardized conceptual and practical approach, Agricultural and Forest Meteorology, DOI: 10.1016/j.agrformet.2014.09.005

YSee Also

zoo, plyr, base, boot, andrews, akima, lattice, plotrix, shape, lmtest, nortest, hydroGOF, ggplot2, reshape, gridExtra

Examples

## See usage
View Sample Data
WEATHER_STATION_DATA and CO2_FLUX_DATA
Download Link
Download Complete Dataset
Metadata on DataCite
go to DataCite
This data by ZALF is licensed under the Creative Commons BY 4.0Creative Commons License