9c36be45-cc4b-4df3-a611-599aa7e60d29 Miguel Cabrera Brufau Departament de Biologia Evolutiva, Ecologia i Ciències Ambientals, Universitat de Barcelona (UB) PostDoc miguelcabrera@ub.edu 0000-0002-0740-9306 Camille Minaudo Departament de Biologia Evolutiva, Ecologia i Ciències Ambientals, Universitat de Barcelona (UB) PostDoc camille.minaudo@ub.edu 0000-0003-0979-9595 Daniel von Schiller Departament de Biologia Evolutiva, Ecologia i Ciències Ambientals, Universitat de Barcelona (UB) Associate professor d.vonschiller@ub.edu 0000-0002-9493-3244 Biel Obrador Departament de Biologia Evolutiva, Ecologia i Ciències Ambientals, Universitat de Barcelona (UB) Associate professor obrador@ub.edu 0000-0003-4050-0491 Katrin Attermeyer WasserCluster Lunz - Biologische Station Group Leader katrin.attermeyer@wcl.ac.at 0000-0002-6503-9497 Antonio Camacho University of Valencia Full professor antonio.camacho@uv.es 0000-0003-0841-2010 Martina Pulieri University of Salento Research assistant martina.pulieri@unisalento.it 0009-0001-9691-1989 Miguel Cabrera Brufau Departament de Biologia Evolutiva, Ecologia i Ciències Ambientals, Universitat de Barcelona (UB) PostDoc miguelcabrera@ub.edu 0000-0002-0740-9306 Raquel Ambrosio Tour du Valat Research technician ambrosio.raquel3esob@gmail.com Content Provider Katrin Attermeyer WasserCluster Lunz - Biologische Station Group Leader katrin.attermeyer@wcl.ac.at 0000-0002-6503-9497 Content Provider Giancarlo Bachi National Research Council (CNR), Institute of Biophysics (IBF) PostDoc giancarlo.bachi@cnr.it 0000-0002-8077-1512 Content Provider Nina Bègue Tour du Valat Engineer begue@tourduvalat.org Content Provider Martynas Bučas Marine Research Institute, Klaipeda University Researcher martynas.Bucas@ku.lt 0000-0003-4668-5669 Content Provider Alba Camacho-Santamans Departament de Biologia Evolutiva, Ecologia i Ciències Ambientals, Universitat de Barcelona (UB) PhD student a.camacho-santamans@ub.edu 0000-0001-8639-2364 Content Provider Lídia Cañas Departament de Biologia Evolutiva, Ecologia i Ciències Ambientals, Universitat de Barcelona (UB) Research technician lcanas@ub.edu 0000-0002-1101-2694 Content Provider Rafael Carballeira University of Valencia Temporary Professor rafael.carballeira@gmail.com 0000-0002-2807-6942 Content Provider Marco Carloni National Research Council (CNR), Institute of Biophysics (IBF) Technician marco.carloni@ibf.cnr.it Content Provider Lamara Cavalcante Universidade de Aveiro PhD Student lamaracavalcante@live.ua.pt 0000-0003-2293-2602 Content Provider Constantin Cazacu University of Bucharest Assistant professor constantin.cazacu@g.unibuc.ro 0000-0003-4521-7185 Content Provider Giovanni Checcucci National Research Council (CNR), Institute of Biophysics (IBF) Researcher giovanni.checcucci@ibf.cnr.it 0000-0002-7960-7168 Content Provider João Pedro Coelho Universidade de Aveiro Researcher jpcoelho@ua.pt 0000-0003-1975-8308 Content Provider Valentin Dinu University of Bucharest Researcher valentin.dinu@bio.unibuc.ro 0000-0001-5084-8630 Content Provider Valtere Evangelista National Research Council (CNR), Institute of Biophysics (IBF) Technician valtere.evangelista@ibf.cnr.it Content Provider Ilenia Férez Martín University of Barcelona Graduate student iferezma60@alumnes.ub.edu Content Provider Jonas Gintauskas Marine Research Institute, Klaipėda University Specialist jonas.gintauskas@ku.lt 0000-0001-6110-8638 Content Provider Relu Constantin Giuca University of Bucharest Researcher relu_constantin.giuca@g.unibuc.ro 0000-0002-3199-9852 Content Provider Anis Guelmami Tour du Valat Engineer guelmami@tourduvalat.org 0000-0002-3906-6424 Content Provider Mirco Guerrazzi National Research Council (CNR), Institute of Biophysics (IBF) Technician mirco.guerrazzi@cnr.it Content Provider Samuel Hilaire Tour du Valat Research technician hilaire@tourduvalat.org 0000-0002-7286-9819 Content Provider Marija Katarzyte Marine Research Institute, Klaipeda University Researcher marija.Katarzyte@ku.lt 0000-0001-7751-3187 Content Provider Ana Lillebø Universidade de Aveiro Principal researcher lillebo@ua.pt 0000-0002-5228-0329 Content Provider Raquel Lizán University of Valencia Technician raquel.lizan@uv.es Content Provider Benjamin Misteli WasserCluster Lunz - Biologische Station PostDoc benjamin.misteli@wcl.ac.at 0000-0002-7733-4354 Content Provider Jorge Juan Montes-Pérez Departament de Biologia Evolutiva, Ecologia i Ciències Ambientals, Universitat de Barcelona (UB) PostDoc jmontesp@ub.edu 0000-0002-0257-4062 Content Provider Daniel Morant University of Valencia Researcher daniel.morant@uv.es 0000-0001-8267-5340 Content Provider Bruna R. F. Oliveira Universidade de Aveiro Researcher bruna.oliveira@ua.pt 0000-0001-5877-8614 Content Provider Vitor Hugo Pessoa Oliveira University of Aveiro Junior Researcher vitor.hugo.oliveira@ua.pt 0000-0002-5119-1295 Content Provider Marta Pedrón University of Valencia PhD student marta.pedron@uv.es 0009-0002-9715-0680 Content Provider Jolita Petkuviene Marine Research Institute, Klaipėda University Senior researcher jolita.petkuviene@ku.lt 0000-0001-9015-9899 Content Provider Antonio Picazo Mozo University of Valencia Senior Researcher antonio.picazo-mozo@uv.es 0000-0002-7572-9686 Content Provider Tudor Racoviceanu University of Bucharest Researcher tudor.racoviceanu@drd.unibuc.ro 0000-0003-1560-1696 Content Provider Sara Ribeiro University of Aveiro Graduate technician sararibeiro@ua.pt 0000-0002-5074-5452 Content Provider Carlos Rochera University of Valencia Researcher carlos.rochera@uv.es 0000-0002-8294-4755 Content Provider Michael Ronse Tour du Valat Engineer ronse@tourduvalat.org Content Provider Chiara Santinelli National Research Council (CNR), Institute of Biophysics (IBF) Researcher chiara.santinelli@ibf.cnr.it 0000-0002-8921-275X Content Provider Ana I. Sousa Universidade de Aveiro Researcher anaisousa@ua.pt 0000-0003-0783-5177 Content Provider Gertraud Steniczka WasserCluster Lunz - Biologische Station Technician gertraud.steniczka@wcl.ac.at Content Provider Wouter Suykerbuyk Wageningen Marine Research Researcher wouter.suykerbuyk@wur.nl 0009-0002-2461-7964 Content Provider Edvinas Tiskus Marine Research Institute, Klaipėda University Research assistant edvinas.tiskus@ku.lt 0000-0002-6293-2140 Content Provider Claudia Tropea National Research Council (CNR), Institute of Biophysics (IBF) PhD student claudia.tropea@ibf.cnr.it 0009-0005-4100-3309 Content Provider Diana Vaičiūtė Marine Research Institute, Klaipeda University Researcher diana.Vaiciute@ku.lt 0000-0003-4479-5688 Content Provider silvia valsecchi National Research Council (CNR), Institute of Biophysics (IBF) PhD student silvia.valsecchi@mare.arditi.pt 0000-0002-9169-8947 Content Provider Marinka van Puijenbroek Wageningen University and Research Researcher marinka.vanpuijenbroek@wur.nl 0000-0003-1237-6403 Content Provider Mourine Jesire Yegon WasserCluster Lunz - Biologische Station PhD student mourine.yegon@wcl.ac.at 0000-0001-5379-325X Content Provider Martina Pulieri University of Salento Research assistant martina.pulieri@unisalento.it 0009-0001-9691-1989 Information Manager Ilaria Rosati National Research Council (CNR), Institute of Research on Terrestrial Ecosystems (IRET) Technologist ilaria.rosati@cnr.it 0000-0003-3422-7230 Custodian Steward 2028-01-01 English This dataset includes instantaneous fluxes of CO2 and CH4 for 3043 individual incubations, performed under transparent and dark light-conditions in 2123 distinct deployments of static greenhouse gas chambers. Three different flux estimates (linear, non-linear and 2-point) are provided for each incubation and gas, accompanied by a selection of best-flux estimate based on systematic criteria of estimate-quality metrics (also included). Fluxes were measured in-situ, using static chambers coupled with portable greenhouse gas analyzers. Spatially, the dataset contains fluxes of 36 different sites, corresponding to 6 different casepilot wetlands and 3 conservation status (altered, preserved, restored), that is two sites per wetland-conservation status combination. In each site, measurements were performed during four seasonal samplings covering Autum 2023 through Summer 2024. Within each site, static chamber measurements were taken proportionally to the areal cover of three strata categories: vegetated, open water and bare sediment/soil. Sampling contextual information (light-condition of chamber, geographical coordinates, time of measurement, water depth, vegetation description and aboveground vegetation biomass) is also included for every incubation. <span data-teams="true">This dataset is currently under embargo period and it will be available after the 31/12/2027.</span> ecological restoration Biodiversity Thesaurus greenhouse gas fluxes carbon dioxide methane wetland Environmental Thesaurus cc-by-nc-sa https://creativecommons.org/licenses/by-nc-sa/4.0/ DOI https://doi.org/10.48372/c29b-qw38 Danube Delta 28.2843 29.7459 45.4723 44.8032 Ria de Aveiro -8.72507 -8.59663 40.74963 40.63271 Marjal dels moros -0.27997 -0.240362 39.64107 39.61579 Curonian lagoon 20.5142 21.2653 55.7186 54.8743 Camargue 4.4382 4.9275 43.674 43.3229 Dutch wetlands 3.9907 4.4087 51.6811 51.2754 2023-10-03 2024-08-01 http://www.w3.org/ns/dcat#keyword http://vocabs.lter-europe.net/EnvThes/21162 http://www.w3.org/ns/dcat#keyword http://vocabs.lter-europe.net/EnvThes/20808 http://www.w3.org/ns/dcat#keyword http://vocabs.lter-europe.net/EnvThes/20812 http://www.w3.org/ns/dcat#keyword http://vocabs.lter-europe.net/EnvThes/21797 http://www.w3.org/ns/dcat#keyword http://data.loterre.fr/ark:/67375/BLH-F8D2QQL7-K Miguel Cabrera Brufau Departament de Biologia Evolutiva, Ecologia i Ciències Ambientals, Universitat de Barcelona (UB) PostDoc miguelcabrera@ub.edu 0000-0002-0740-9306 Daniel von Schiller Departament de Biologia Evolutiva, Ecologia i Ciències Ambientals, Universitat de Barcelona (UB) Associate professor d.vonschiller@ub.edu 0000-0002-9493-3244 Antonio Camacho University of Valencia Full professor antonio.camacho@uv.es 0000-0003-0841-2010 Static chamber measurements: In each designated spot a static chamber was placed (cylindrical or semi-spherical, transparent or opaque, depending on the spot presence of vegetation and water) and immediately after placement, CO2 and CH4 gas concentration timeseries were synchronously recorded for a duration of 5 to 12 minutes using a portable gas analyzer. Incubation-related information was recorded in a field-sheet and later digitalized (Incubation ID, date, season, casepilot, site, GPS coordinates, start time, end time, vegetation presence, vegetation type, water depth, chamber type and dimensions, light conditions, instrument used, personnel performing the incubation, general observations and incidences during incubation). Import of raw data and mapping of incubations: Raw GHG concentration timeseries data was downloaded from the portable gas analyzers alongside (if available) the instrument-recorded start-end time of each incubation. For each incubation, manually annotated incubation start-end times were combined with those recorded by instrument (if any). Each individual incubation was visually inspected, and the start-end times were adjusted appropriately in cases where this inspection revealed mismatches between recorded start-end times and GHG concentration patterns consistent with closing and opening of the chamber. Additionally, the presence of patterns of ebullitive behavior for methane concentration timeseries were recorded for each incubation for later use. Meteorological information needed for the flux estimates calculation was collected from nearby meteorological stations. Flux estimates calculations: Briefly, for each CO2 and CH4 gas concentration time series, three different flux estimates of were calculated (total.flux, LM, HM). Total.flux estimate was calculated as the net concentration change throughout the incubation using the average (10 s) initial and final concentrations. Linear (LM) and non-linear (HM) (Hutchinson and Mosier, 1981) regression models were used to obtain a linear and a nonlinear flux estimate using the goFlux R package v2.0.0 (Rheault et al., 2024). Areal molar fluxes were calculated for each of the three approaches via the ideal gas equation using the chamber footprint area and effective volume recorded in the field, and initial temperature and atmospheric pressure recorded by the nearest meteorological station. Selection of best flux estimate: Selection of best flux estimate followed objective sequential criteria based on model performance statistics (inspired by goFlux R package best.flux function) and, for methane flux estimates, the presence of ebullitive patterns recorded during visual inspection. Selection procedure: First, all methane timeseries with visual evidence of ebullition (recorded during previous inspection) were assigned to the total.flux estimate unless the linear model presented and R2 above 0.99 (LM.r2 higher than 0.99). For the rest of the timeseries, absent of ebullitive patterns, the HM model was chosen only when all the following criteria were met (defaulting to the LM estimate when one or more were violated): HM model produces a valid flux estimate (HM.flux ≠ NA). LM flux estimate is above the minimal detectable flux (Christiansen et al., 2015). HM curvature parameter Kappa is below the theoretical maximum (Hüppi et al., 2018). The ratio between the non-linear (HM) flux estimate and the linear (LM) estimate, the g-fact (Hüppi et al., 2018) is below the gas species-specific custom threshold (CO2 g-fact less than 4; CH4 g-fact less than 3). Akaike Information Criterion corrected for small sample size (AICc) of HM model is lower than that of the LM model. Mean absolute error (MAE) of HM model is at least 5% lower than that of LM model. The raw GHG concentration timeseries and accessory data required for flux calculation can be found in https://doi.org/10.5281/zenodo.18803756. The code used for flux calculation and estimate selection is deposited at https://doi.org/10.5281/zenodo.19184152. Miguel Cabrera Brufau Departament de Biologia Evolutiva, Ecologia i Ciències Ambientals, Universitat de Barcelona (UB) PostDoc miguelcabrera@ub.edu 0000-0002-0740-9306 Point Of Contact Benjamin Misteli WasserCluster Lunz - Biologische Station PostDoc benjamin.misteli@wcl.ac.at 0000-0002-7733-4354 Point Of Contact Antonio Camacho University of Valencia Full professor antonio.camacho@uv.es 0000-0003-0841-2010 Point Of Contact Deployments_contextual_field_Information.csv Dataset of static chamber deployments. Contains contextual sampling information associated with each deployment of a static chamber. Each deployment corresponds to either one or two incubations identified by a dark or transparent UniqueID code and for which instantaneous GHG fluxes are provided in the other data tables. Deployments_contextual_field_Information.csv 342778 MD5:71b99a23144103875bb4a61afa601f11 UTF-8 1 column , parentEventID Parent Event ID Code that identifies the deployment of a static chamber. A single parentEventID chamber deployment code can correspond to up to two chamber incubations (darkUniqueID and transparentUniqueID) performed under dark or transparent light-conditions, while sharing the exact same position and other contextual information. Any Text http://ecoinformatics.org/oboe/oboe.1.2/oboe-core.owl#hasCode http://rs.tdwg.org/dwc/terms/parentEventID season Season Code that identifies the season (S1: Autumn, S2: Winter, S3: Spring, S4: Summer). S1 Autumn - S2 Winter - S3 Spring - S4 Summer - http://ecoinformatics.org/oboe/oboe.1.2/oboe-core.owl#hasContext http://www.eionet.europa.eu/gemet/concept/7529 higherGeography Higher Geography Full name of wetland casepilot where measurement was taken. Any Text http://ecoinformatics.org/oboe/oboe.1.2/oboe-core.owl#hasContext http://rs.tdwg.org/dwc/terms/higherGeography locationID Location ID Code that identifies the location (the wetland "unit") where the measurement was taken. Coded as a combination of the casepilot (higherGeography) abreviation and one of "A1", "A2", "P1", "P2", "R1" or "R2". Letters A, P, R followed by number correspond to the ecological status classification of the locations (A=Altered, P=Preserved, R= Restored). Any Text http://ecoinformatics.org/oboe/oboe.1.2/oboe-core.owl#hasCode http://rs.tdwg.org/dwc/terms/locationID eventDate Event Date The date-time or interval during which a dwc:Event occurred. YYYY-MM-DD http://ecoinformatics.org/oboe/oboe.1.2/oboe-core.owl#hasContext http://rs.tdwg.org/dwc/terms/eventDate eventTime Event Time Time (hh:mm:ss, UTC) at which the first incubation started (regardless of subsequent incubations for the same chamber deployment). hh:mm:ss http://ecoinformatics.org/oboe/oboe.1.2/oboe-core.owl#hasContext http://rs.tdwg.org/dwc/terms/eventTime decimalLatitude Decimal Latitude The geographic latitude (in decimal degrees, using the spatial reference system given in dwc:geodeticDatum) of the geographic center of a dcterms:Location. Positive values are north of the Equator, negative values are south of it. Legal values lie between -90 and 90, inclusive. degree real http://ecoinformatics.org/oboe/oboe.1.2/oboe-core.owl#hasContext http://rs.tdwg.org/dwc/terms/decimalLatitude decimalLongitude Decimal Longitude The geographic longitude (in decimal degrees, using the spatial reference system given in dwc:geodeticDatum) of the geographic center of a dcterms:Location. Positive values are east of the Greenwich Meridian, negative values are west of it. Legal values lie between -180 and 180, inclusive. degree real http://ecoinformatics.org/oboe/oboe.1.2/oboe-core.owl#hasContext http://rs.tdwg.org/dwc/terms/decimalLongitude gasAnalyzer Gas Analyser Code of the gas analyzer model used to record greenhouse gas concentration during the incubation. LI-COR Li-COR 7810 - Picarro Picarro G4301 - Los Gatos GLA132-GGA - http://ecoinformatics.org/oboe/oboe.1.2/oboe-core.owl#hasContext http://opendata.inrae.fr/thesaurusINRAE/c_16853 strata Strata Classification of the type of surface cover where the chamber was deployed (vegetated, open water or bare). vegetated Area covered by vegetation regardless of water presence - open water Areas without emergent vegetation and with water of more than 10 cm depth - bare Areas where sediment/soil is exposed to the atmoshpere without water or vegetation - http://ecoinformatics.org/oboe/oboe.1.2/oboe-core.owl#hasContext https://www.eionet.europa.eu/gemet/en/concept/4612 waterDepth Water Depth Water depth where the chamber was deployed. centimeter real http://ecoinformatics.org/oboe/oboe.1.2/oboe-core.owl#containsMeasurementsOfType http://vocabs.lter-europe.net/EnvThes/22310 fieldNotes Field Notes Harmonised observations made in the field, contextual for the deployment (humidity of sediment, presence of submerged vegetation, tide behaviour,…) Any Text http://ecoinformatics.org/oboe/oboe.1.2/oboe-core.owl#hasContext http://rs.tdwg.org/dwc/terms/fieldNotes ABGVegDescription Aboveground Vegetation Description Description of aboveground vegetation inside the chamber. Contains identification at different taxonomic levels (species, genus, non-systematic names, separated by semi-colons ";") and (when available) visual assessment of plant state within parenthesis. Absence of vegetation is denoted with "no aboveground vegetation". Any Text http://ecoinformatics.org/oboe/oboe.1.2/oboe-core.owl#hasContext http://vocabs.lter-europe.net/EnvThes/20535 ABGVegBiomass Aboveground Biomass Aboveground vegetation dry biomass. Calculated from the dry weight of vegetation inside the chamber and the area covered by the chamber. gramPerMeterSquared real http://ecoinformatics.org/oboe/oboe.1.2/oboe-core.owl#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00001135 darkUniqueID Dark Unique ID UniqueID code identifying the incubation performed under dark (opaque) light-conditions during the chamber deployment identified by parentEventID. Used as key for identification of CO2 and CH4 flux estimates. Any Text http://ecoinformatics.org/oboe/oboe.1.2/oboe-core.owl#hasCode http://rs.tdwg.org/dwc/terms/eventID transparentUniqueID Transparent Unique ID UniqueID identifying the incubation performed under transparent light-conditions during the chamber deployment identified by parentEventID. Used as key for identification of CO2 and CH4 flux estimates. Any Text http://ecoinformatics.org/oboe/oboe.1.2/oboe-core.owl#hasCode http://rs.tdwg.org/dwc/terms/eventID 2123 Instantaneous_CO2_flux.csv Dataset of instantaneous carbon dioxide (CO2) flux estimates. Contains three flux estimates (and associated quality parameters) for each static chamber incubation identified with a uniqueID code. Instantaneous_CO2_flux.csv 1038864 MD5:fe46a20f730f8732e8d448c74cf47f4e UTF-8 1 column , uniqueID Unique ID Code that uniquely identifies a chamber incubation, performed under dark or transparent light conditions. Matches with darkUniqueID or transparentUniqueID columns in Deployments_contextual_field_Information data table. Any Text duration Duration Duration (in seconds) of GHG concentration timeseries used to obtain flux estimates. second real flux.term Flux term Term used to convert flux untis from change in ppm per second to µmol per square meter per second. It takes into account the chamber geometry (base area and volume) as well as temperature, atmospheric pressure and water vapor concetration inside the chamber at the beginning of the incubation. See: https://qepanna.quarto.pub/goflux/goFlux.html moles per meter squared real MDF.lim Minimal Detectable Flux Limit under which a flux estimate is considered below the detection limit (depends on instrument accuracy and duration of incubation and chamber geometry). micromolePerMeterSquaredPerSecond real C0.10s CO2 average concentration Average concentration of CO2 gas during the first 10 seconds of the incubation. parts per million real C0.10s.sd Standard deviation of CO2 average concentration Standard deviation of the average concentration of CO2 gas during the first 10 seconds of the incubation. parts per million real Cf.10s CO2 average concentration Average concentration of CO2 gas during the last 10 seconds of the incubation. parts per million real Cf.10s.sd Standard deviation of CO2 average concentration Standard deviation of the average concentration of CO2 gas during the last 10 seconds of the incubation. parts per million real total.flux Total flux Two-point CO2 flux estimate, calculated via the difference between C0.10s and Cf.10s through the duration of the incubation and multiplied by the flux.term value. micromolePerMeterSquaredPerSecond real total.flux.se Total flux standard error Standard error of total.flux. micromolePerMeterSquaredPerSecond real LM.flux Linear Model flux Linear CO2 flux estimate. Obtained via Linear regression of CO2 concentration (ppm) through time (duration, s) and multiplied by flux.term value. micromolePerMeterSquaredPerSecond real LM.flux.se Linear Model flux standard error Standard error of LM.flux. micromolePerMeterSquaredPerSecond real LM.MAE Linear Model Mean Absolute Error Mean Absolute Error of LM model. parts per million real LM.RMSE Linear Model Root Mean Square Error Root Mean Square Error of LM model. parts per million real LM.AICc Linear Model Akaike Information Criterion Akaike Information Criterion corrected for small sample size of LM model. dimensionless real LM.r2 Linear Model R2 Coefficient of determination (R-squared) of LM model. dimensionless real LM.p.val Linear Model p-value P-value of LM model, test if the slope if statistically different from cero. dimensionless real HM.flux Hutchinson and Mosier model flux Non-linear (HM) CO2 flux estimate. Obtained via the application of the Hutchinson and Mosier 1981 flux model, multiplied by flux.term value. micromolePerMeterSquaredPerSecond real HM.flux.se Hutchinson and Mosier model flux standard error Standard error of HM.flux. micromolePerMeterSquaredPerSecond real HM.MAE Hutchinson and Mosier model Mean Absolute Error Mean Absolute Error of HM model. parts per million real HM.RMSE Hutchinson and Mosier model Root Mean Square Error Root Mean Square Error of HM model. parts per million real HM.AICc Hutchinson and Mosier model Akaike Information Criterion Akaike Information Criterion corrected for small sample size of HM model. dimensionless real HM.r2 Hutchinson and Mosier model R2 Coefficient of determination (R-squared) of HM model. dimensionless real HM.k Hutchinson and Mosier model K Kappa of HM model. Determines the curvature of the model. A large kappa returns a strong curvature. inverse second real k.max K max Maximum limit for the kappa (HM.K) curvature parameter. Estimated from the LM.flux, the MDF.lim and the duration of the incubation. Inverse second real g.fact g factor Ratio between a the non-linear flux estimate (HM.flux) and the linear flux estimate (LM.flux). dimensionless real best.model Best Model Name of the flux estimate (LM, HM, total.flux, None appropriate) that is considered to be best (based on objective criteria of model performance). “None appropriate” code indicates incubations with severe artefacts, precluding the selection of any flux estimate for them. LM Linear Model - HM Hutchinson and Mosier model - total.flux Two point estimate - None appropriate Artefacts preclude reliable flux estimation - best.model.flags Best Model Flags Main reason or reasons for the selection of best.model. Includes flags for the failure of various objective conditions that determine which model estimate (LM, HM total.flux) is considered to be the most appropriate. Any Text 3042 Instantaneous_CH4_flux.csv Dataset of instantaneous methane (CH4) flux estimates. Contains three flux estimates (and associated quality parameters) for each static chamber incubation identified with a uniqueID code. Instantaneous_CH4_flux.csv 1036925 MD5:5e3caeab87f182e44589e51c4c002abc UTF-8 1 column , UniqueID Unique ID Code that uniquely identifies a chamber incubation, performed under dark or transparent light conditions. Matches with darkUniqueID or transparentUniqueID columns in Deployments_contextual_field_Information data table. Any Text duration Duration Duration (in seconds) of GHG concentration timeseries used to obtain flux estimates. second real flux.term Flux term Term used to convert flux untis from change in ppb per second to nmol per square meter per second. It takes into account the chamber geometry (base area and volume) as well as temperature, atmospheric pressure and water vapor concetration inside the chamber at the beginning of the incubation. See: https://qepanna.quarto.pub/goflux/goFlux.html. moles per meter squared real MDF.lim Minimal Detectable Flux Limit under which a flux estimate is considered below the detection limit (depends on instrument accuracy and duration of incubation and chamber geometry) nanomole per square meter per second real C0.10s CH4 average concentration Average concentration of CH4 gas during the first 10 seconds of the incubation. parts per billion real C0.10s.sd CH4 average concentration standard deviation Standard deviation of the average concentration of CH4 gas (ppb) during the first 10 seconds of the incubation. parts per billion real Cf.10s CH4 average concentration Average concentration of CH4 gas during the last 10 seconds of the incubation. parts per billion real Cf.10s.sd CH4 average concentration standard deviation Standard deviation of the average concentration of CH4 gas during the last 10 seconds of the incubation parts per billion real total.flux Total flux Two-point CH4 flux estimate, calculated via the difference between C0.10s and Cf.10s through the duration of the incubation and multiplied by the flux.term value. nanomole per square meter per second real total.flux.se Total flux standard error Standard error of total.flux. nanomole per square meter per second real LM.flux Linear Model flux Linear CH4 flux estimate. Obtained via Linear regression of CH4 concentration (ppb) through time (duration, s) and multiplied by flux.term value. nanomole per square meter per second real LM.flux.se Linear Model flux standard error Standard error of LM.flux. nanomole per square meter per second real LM.MAE Linear Model Mean Absolute Error Mean Absolute Error of LM model. parts per billion real LM.RMSE Linear Model Root Mean Square Error Root Mean Square Error of LM model. parts per billion real LM.AICc Linear Model Akaike Information Criterion Akaike Information Criterion corrected for small sample size of LM model. dimensionless real LM.r2 Linear Model R2 Coefficient of determination (R-squared) of LM model. dimensionless real LM.p.val Linear Model p-value P-value of LM model, test if the slope if statistically different from cero. dimensionless real HM.flux Hutchinson and Mosier model flux Non-linear (HM) CH4 flux estimate. Obtained via the application of the Hutchinson and Mosier 1981 flux model, multiplied by flux.term value. nanomole per square meter per second real HM.flux.se Hutchinson and Mosier model flux stardard error Standard error of HM.flux. nanomole per square meter per second real HM.MAE Hutchinson and Mosier model Mean Absolute Error Mean Absolute Error of HM model. parts per billion real HM.RMSE Hutchinson and Mosier model Root Mean Square Error Root Mean Square Error of HM model. parts per billion real HM.AICc Hutchinson and Mosier model Akaike Information Criterion Akaike Information Criterion corrected for small sample size of HM model. dimensionless real HM.r2 Hutchinson and Mosier model R2 Coefficient of determination (R-squared) of HM model. dimensionless real HM.k Hutchinson and Mosier model K Kappa of HM model. Determines the curvature of the model. A large kappa returns a strong curvature. inverse second real k.max K maximum Maximum limit for the kappa (HM.K) curvature parameter. Estimated from the LM.flux, the MDF.lim and the duration of the incubation. Inverse second real g.fact g factor Ratio between a the non-linear flux estimate (HM.flux) and the linear flux estimate (LM.flux). dimensionless real best.model Best Model Name of the flux estimate (LM, HM, total.flux, None appropriate) that is considered to be best (based on objective criteria of model performance). “None appropriate” code indicates incubations with severe artefacts, precluding the selection of any flux estimate for them. LM Linear Model - HM Hutchinson and Mosier model - total.flux Two-point estimate - None appropriate Artefacts preclude reliable flux estimation - best.model.flags Best Model Flags Main reason or reasons for the selection of best.model. Includes flags for the failure of various objective conditions that determine which model estimate (LM, HM total.flux) is considered to be the most appropriate. Any Text 3042