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60 results for “gas flux”
Dataset from: Automatic high-frequency measurements of full soil greenhouse gas fluxes in a tropical forest Biogeosciences 2019
<p>Dataset used for the manuscript <strong>Automatic high-frequency measurements of full soil greenhouse gas fluxes in a tropical forest</strong> in Biogesciences, 2019</p>
Soil greenhouse gas fluxes and associated parameters from forest and oil palm in the SAFE landscape
<b>Description: </b><p>Greenhouse gas fluxes measured by the static chamber method including associated environmental parameters</p><p><b>Project: </b>This dataset was collected as part of the following SAFE research project: <a href="https://www.safeproject.net/projects/project_view/126"><b>Characterising soil microbial communities and measuring associated biogeochemical fluxes</b></a></p><p><b>Funding: </b>These data were collected as part of research funded by: </p><ul><li>NERC HMTF (Research Programme, (NE/K016091/1), <a href=" http://lombok.nerc-hmtf.info/"> http://lombok.nerc-hmtf.info/</a>)</li></ul><p>This dataset is released under the CC-BY 4.0 licence, requiring that you cite the dataset in any outputs, but has the additional condition that you acknowledge the contribution of these funders in any outputs.</p><p></p><p><b>Permits: </b>These data were collected under permit from the following authorities:</p><ul><li>Sabah Biodiversity Centre (Research licence JKM/MBS.1000-2/2 JLD.5 (79))</li></ul><p></p><p><b>XML metadata: </b>GEMINI compliant metadata for this dataset is available <a href="https://www.safeproject.net/datasets/xml_metadata?id=3258117">here</a></p><p><b>Files: </b>This consists of 1 file: 3_GHG_jdrewer.xlsx</p><p><b>3_GHG_jdrewer.xlsx</b></p><p>This file contains dataset metadata and 2 data tables:</p><ol><li><p><b>data one off field</b> (described in worksheet Data_one_off)</p><p>Description: Soil and litter parameters</p><p>Number of fields: 14</p><p>Number of data rows: 56</p><p>Fields: </p><ul><li><b>Location</b>: Location measurement was taken (Field type: Location)</li><li><b>site</b>: Location measurement was taken (Field type: ID)</li><li><b>chamber_id</b>: Chamber ID (Field type: ID)</li><li><b>landuse</b>: Land use of location (Field type: Categorical)</li><li><b>pH</b>: Soil pH (Field type: Numeric)</li><li><b>bulk_density</b>: dry weight of soil (Field type: Numeric)</li><li><b>soil_N%</b>: Percentage of soil N (Field type: Numeric)</li><li><b>soil_C%</b>: Percentage of soil C (Field type: Numeric)</li><li><b>litter_N%</b>: Percentage of leaf Nitrogen (Field type: Numeric)</li><li><b>litter_C%</b>: Percentage of leaf Carbon (Field type: Numeric)</li><li><b>C/N_soil</b>: Ratio of soil Carbon: Nitrogen (Field type: Numeric)</li><li><b>Latitude</b>: Latitude of sampling point (Field type: Latitude)</li><li><b>Longitude</b>: Longitude of sampling point (Field type: Longitude)</li><li><b>Elevation</b>: Elevation of sampling point (Field type: Numeric)</li></ul></li><li><p><b>data of repeated measures</b> (described in worksheet Data_repeated_measures)</p><p>Description: Soil greenhouse gas flux data and associated variables</p><p>Number of fields: 14</p><p>Number of data rows: 672</p><p>Fields: </p><ul><li><b>Location</b>: Location measurement was taken (Field type: Location)</li><li><b>site</b>: Location measurement was taken (Field type: ID)</li><li><b>chamber_id</b>: Chamber ID (Field type: ID)</li><li><b>landuse</b>: Land use of location (Field type: Categorical)</li><li><b>date</b>: Date the measurement was taken (Field type: Date)</li><li><b>time</b>: Time the measurement was taken (Field type: Time)</li><li><b>flux_CH4</b>: Soil CH4 flux (Field type: Numeric)</li><li><b>flux_CO2-C</b>: Soil CO2 flux (Field type: Numeric)</li><li><b>flux_N2O-N</b>: Soil N2O flux (Field type: Numeric)</li><li><b>NH4-N</b>: Soil NH4 concentration (Field type: Numeric)</li><li><b>NO3-N</b>: Soil NO3 concentration (Field type: Numeric)</li><li><b>air_temp</b>: Air temperature around the flux chamber (Field type: Numeric)</li><li><b>soil_temp</b>: Soil temperature around the flux chamber (Field type: Numeric)</li><li><b>soil_moisture</b>: Soil moisture around the flux chamber (Field type: Numeric)</li></ul></li></ol><p><b>Date range: </b>2015-01-01 to 2016-12-31</p><p><b>Latitudinal extent: </b>4.5000 to 5.0700</p><p><b>Longitudinal extent: </b>116.7500 to 117.8200</p>
Soil greenhouse gas fluxes along transects from oil palm to riparian forests in the SAFE landscape
<b>Description: </b><p>Riparian greenhouse gas fluxes measured by the static chamber method including associated environmental parameters and river water </p><p><b>Project: </b>This dataset was collected as part of the following SAFE research project: <a href="https://www.safeproject.net/projects/project_view/126"><b>Characterising soil microbial communities and measuring associated biogeochemical fluxes</b></a></p><p><b>Funding: </b>These data were collected as part of research funded by: </p><ul><li>NERC HMTF (Research Programme, (NE/K016091/1), <a href=" http://lombok.nerc-hmtf.info/"> http://lombok.nerc-hmtf.info/</a>)</li></ul><p>This dataset is released under the CC-BY 4.0 licence, requiring that you cite the dataset in any outputs, but has the additional condition that you acknowledge the contribution of these funders in any outputs.</p><p></p><p><b>Permits: </b>These data were collected under permit from the following authorities:</p><ul><li>Sabah Biodiversity Centre (Research licence JKM/MBS.1000-2/2 JLD.5 (79))</li></ul><p></p><p><b>XML metadata: </b>GEMINI compliant metadata for this dataset is available <a href="https://www.safeproject.net/datasets/xml_metadata?id=3258079">here</a></p><p><b>Files: </b>This consists of 1 file: 1_HJ_river_water_riparian.xlsx</p><p><b>1_HJ_river_water_riparian.xlsx</b></p><p>This file contains dataset metadata and 3 data tables:</p><ol><li><p><b>river_water</b> (described in worksheet river_water)</p><p>Description: river water measurments</p><p>Number of fields: 17</p><p>Number of data rows: 63</p><p>Fields: </p><ul><li><b>site</b>: location sample was taken (Field type: Location)</li><li><b>location</b>: habitat (Field type: Categorical)</li><li><b>replicate</b>: water sample replicate number (Field type: Replicate)</li><li><b>sampling_occasion</b>: date of sample collection (Field type: Date)</li><li><b>date</b>: date of sample analysis (Field type: Date)</li><li><b>TDS</b>: Total Desolved Solids (Field type: Numeric)</li><li><b>pH</b>: water pH (Field type: Numeric)</li><li><b>conductivity</b>: water conductivity (Field type: Numeric)</li><li><b>Temp</b>: tempreture of river water (Field type: Numeric)</li><li><b>air_CH4</b>: air concentration of CH4 (Field type: Numeric)</li><li><b>water_CH4</b>: water concentration of CH4 (Field type: Numeric)</li><li><b>air_N2O</b>: air concentration of N2O (Field type: Numeric)</li><li><b>water_N2O</b>: water concentration of N2O (Field type: Numeric)</li><li><b>air_CO2</b>: air concentration of CO2 (Field type: Numeric)</li><li><b>water_CO2</b>: water concentration of CO2 (Field type: Numeric)</li><li><b>NH4-N</b>: concentration of NH4-N in water (Field type: Numeric)</li><li><b>NO3-N</b>: concentration of NO3-N in water (Field type: Numeric)</li></ul></li><li><p><b>data_one_off_field</b> (described in worksheet data_one_off_field)</p><p>Description: soil and littter property measurements</p><p>Number of fields: 12</p><p>Number of data rows: 48</p><p>Fields: </p><ul><li><b>Location</b>: location of chamber (Field type: Location)</li><li><b>chamber_id</b>: chamber ID (Field type: ID)</li><li><b>site</b>: Site ID (Field type: ID)</li><li><b>landuse</b>: land use type (Field type: Categorical)</li><li><b>pH</b>: soil pH (Field type: Numeric)</li><li><b>soil_N</b>: soil nitrogen content (Field type: Numeric)</li><li><b>soil_C</b>: soil carbon content (Field type: Numeric)</li><li><b>litter_N</b>: litter nitrogen content (Field type: Numeric)</li><li><b>litter_C</b>: litter carbon content (Field type: Numeric)</li><li><b>C_N</b>: soil C:N ratio (Field type: Numeric)</li><li><b>Latitude</b>: GPS co-ordinate that the sample was taken (Field type: Latitude)</li><li><b>Longitude</b>: GPS co-ordinate that the sample was taken (Field type: Longitude)</li></ul></li><li><p><b>data_repeated_measures</b> (described in worksheet data_repeated_measures)</p><p>Description: repeated soil measures</p><p>Number of fields: 16</p><p>Number of data rows: 336</p><p>Fields: </p><ul><li><b>chamber_id</b>: Chamber ID (Field type: ID)</li><li><b>site</b>: Site ID (Field type: ID)</li><li><b>landuse</b>: land use type (Field type: Categorical)</li><li><b>sampling_occasion</b>: date of sample collection (Field type: Date)</li><li><b>date</b>: date of sample analysis (Field type: Date)</li><li><b>time</b>: Time the measurement was taken (Field type: Time)</li><li><b>flux_CH4-C</b>: Soil CH4 flux (Field type: Numeric)</li><li><b>flux_CO2-C</b>: Soil CO2 flux (Field type: Numeric)</li><li><b>flux_N2O-N</b>: Soil N2O flux (Field type: Numeric)</li><li><b>NH4-N_H2O</b>: Soil NH4 concentration (Field type: Numeric)</li><li><b>NO3-N_H2O</b>: Soil NO3 concentration (Field type: Numeric)</li><li><b>NH4-N_KCl</b>: Soil NH4 concentration (Field type: Numeric)</li><li><b>NO3-N_KCl</b>: Soil NO3 concentration (Field type: Numeric)</li><li><b>air_temp</b>: Air temperature around the flux chamber (Field type: Numeric)</li><li><b>soil_temp</b>: Soil temperature around the flux chamber (Field type: Numeric)</li><li><b>soil_moisture</b>: Soil moisture around the flux chamber (Field type: Numeric)</li></ul></li></ol><p><b>Date range: </b>2016-11-01 to 2017-11-30</p><p><b>Latitudinal extent: </b>4.3960 to 5.0700</p><p><b>Longitudinal extent: </b>116.7500 to 117.8200</p>
Data set supporting Journal article: Siebicke, L., and Emad, A., "True eddy accumulation trace gas flux measurements: proof of concept", Atmos. Meas. Tech., 12, 1–28, 2019.
<p>This data set contains carbon dioxide trace gas flux measurements obtained by the true eddy accumulation technique as described in the research article:</p> <p>Siebicke, L., and Emad, A., "True eddy accumulation trace gas flux measurements: proof of concept", Atmos. Meas. Tech., 12, 1–28, 2019.</p> <p>It contains meteorological measurements (file "meteo.csv"), turbulent energy fluxes (file "energy_fluxes.csv"), three-diomensional wind vector measurements ("file wind.csv"), and carbon dioxide trace gas fluxes obtained by true eddy accumulation (file "co2_flux_TEA.csv") and eddy covariance using data from two separate anomemoters (files "co2_flux_EC_TEA_sonic.csv" and "co2_flux_EC_EC_sonic.csv").</p>
Greenhouse gas and energy fluxes in a boreal peatland forest after clearcutting
<p>This package contains the data used in the research article: "Greenhouse gas and energy fluxes in a boreal peatland forest after clearcutting" published in Biogeosciences journal.</p> <p>Changes in this version:</p> <p>Chamber_data.xlsx is now named Chamber_data_clearcut.xlsx. CO2 fluxes were also corrected.</p> <p>Added daily mean CO2, CH4 and N2O fluxes measured at the control site.</p> <p> </p> <p>Chamber_data_clearcut.xlsx contains the daily mean fluxes of CO2, CH4 and N2O measured with soil chambers at the clearcut site.</p> <p>Chamber_data_control.xlsx contains the daily mean fluxes of CO2, CH4 and N2O measured with soil chambers at the control site.</p> <p>EC_CO2_fluxes.xlsx contains the gapfilled 30-min mean CO2 fluxes (NEE) and its components (GPP and respiration).</p> <p>Energy_fluxes.xlsx contains the gapfilled hourly mean energy fluxes.</p> <p>Meteo_data.xlsx contains the daily means of the meteorological variables used in the study.</p>
Datasets: RECCAP2 A Synthesis of Global Coastal Ocean Greenhouse Gas Fluxes
<p>Processed data and scripts to produce figures for the contribution to RECCAP2: "A Synthesis of Global Coastal Ocean Greenhouse Gas Fluxes", published 2023.</p>
Data from: Pollution-tolerant invertebrates enhance greenhouse gas flux in urban wetlands
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Data from: Technical note: rapid image-based field methods improve the quantification of termite mound structures and greenhouse-gas fluxes
Termite mounds (TMs) mediate biogeochemical processes with global relevance, such as turnover of the important greenhouse gas methane (CH4). However, the complex internal and external morphology of TMs impede an accurate quantitative description. Here we present two novel field methods, photogrammetry (PG) and cross-section image analysis, to quantify TM external and internal mound structure of 29 TMs of three termite species. Photogrammetry was used to measure epigeal volume (VE), surface area (AE) and mound basal area (AB) by reconstructing 3D models from digital photographs, and compared against a water-displacement method and the conventional approach of approximating TMs by simple geometric shapes. To describe TM internal structure, we introduce TM macro- and micro-porosity (θM and θµ), the volume fractions of macroscopic chambers, and microscopic pores in the wall material, respectively. Macro-porosity was estimated using image analysis of single TM cross-sections, and compared against full x-ray tomography (CT) scans of 17 TMs. For these TMs we present complete pore fractions to assess species-specific differences in internal structure. The PG method yielded VE nearly identical to a water-displacement method, while approximation of TMs by simple geometric shapes led to errors of 4–200 %. Likewise, using PG substantially improved the accuracy of CH4 emission estimates by 10–50 %. Comprehensive CT scanning revealed that investigated TMs have species-specific ranges of θM and θµ, but similar total porosity. Image analysis of single TM cross-sections produced good estimates of θM for species with thick walls and evenly distributed chambers. The new image-based methods allow rapid and accurate quantitative characterisation of TMs to answer ecological, physiological and biogeochemical questions. The PG method should be applied when measuring greenhouse-gas emissions from TMs to avoid large errors from inadequate shape approximations.
Data from: Using greenhouse gas fluxes to define soil functional types
Aim: Soils provide key ecosystem services and directly control ecosystem functions; thus, there is a need to define the reference state of soil functionality. Most common functional classifications are vegetation-centered, such as plant functional types (PFTs), and neglect soil characteristics and processes. We propose Soil Functional Types (SFTs) as a conceptual approach to represent and describe the functionality of soils based on characteristics of their greenhouse gas (GHG) flux dynamics. Methods: We used automated measurements of CO2, CH4 and N2O soil fluxes in a forested area to define SFTs as surface areas with similar GHG dynamics. We performed mixed effects models, and independent cluster analyses of our environmental variables and SFT classifications. Results Unique groupings based on SFTs, but not environmental variables, supported the hypothesis that SFTs provide additional insights on the spatial variability of soil functionality beyond information represented by commonly measured soil parameters (e.g., soil moisture, soil temperature, litter biomass). Conclusions: This approach could complement vegetation-based functional classifications to better represent the broad range of ecosystem functions. A global application of the proposed SFT framework will only be possible if there is a community-wide effort to share data and create a global database of GHG emissions from soils.
Dataset on laboratory soil greenhouse gas fluxes and soil microbial parameters as affected by soil management strategies in SOMMIT long term experiments
<p>We present a database containing over 50 soil-microbial parameters from eight long-term European experiments where specific soil management strategies are compared. Intact topsoil cores (7 cm diameter, 7 cm height) were collected from LTE participating in the tasks WP3.2 and WP3.3. from the SOMMIT experiment, and incubated under standard conditions in the laboratory. The soil management strategies considered at the eight LTEs ("ACBB Estrées-Mons, France", "Rutzendorf_17, Austria", , "Foggia, Italy", "ULBF-Ljubljana, Slovenia", "Toholampi, Finland", "Senés, Spain", "La Poveda, Spain" and "Grabow 1, Poland") included crop residue management, addition of different types of compost and sludge and biochar addition. All LTEs are referenced according to the LTE Index from https://doi.org/10.5281/zenodo.7598122 . The soil cores were subjected to i) a pre-equilibration phase of five days ("pre.inc"), followed by ii) a drying phase ("DR") of ten days and finally a iii) rewetting (five days, "RW"). A subset of the cores were kept under iv) constantly moist conditions for comparison purposes ("moist"). By the end of the "pre.inc" phase, soil microbial biomass, soil microbial community (phospholipidic fatty acids), enzymatic activities and soil nutrient data were collected. After the "pre.inc" phase, soil fluxes of N2O and CO2 were monitored with an automated system at subdaily temporal resolution. In addition, soil nutrients and microbial biomass data were estimated during at the end of the "DR", "RW" and "moist" phases. This dataset contributes to a better understanding of the linkages between soil conditions, soil microbes and soil greenhouse gas fluxes as affected by different soil management strategies across European agro-ecosystems. This product is part of the EJP SOIL internal project SOMMIT, and serves as deliverable WP3.4</p>
Field data of soil greenhouse gas fluxes from SOMMIT long-term experiments
<p>This is a database of field data of soil greenhouse gas fluxes and ancillary data from long-term experiments (LTEs) that participated in the task 1 of the work package 3 from SOMMIT. As of November 2024 (V 1.0) six LTEs have contributed with data: "ACBB Estrées-Mons, France", "Rutzendorf_17, Austria", "Maintainance of organic orchards, Italy", "Fagna, Italy", "ULBF-Ljubljana, Slovenia" and "Grabow 2, Poland". All LTEs are referenced according to the LTE Index from <a href="https://doi.org/10.5281/zenodo.7598122" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.7598122</a>. The data includes soil greenhouse gas fluxes (N2O, CO2 and CH4) under different management practices, as well as ancillary data that might be useful to explain the observed fluxes. The database includes metadata on how soil greenhouse flux data and ancillary data were collected. Individual soil gas flux estimates are also expressed in CO2 equivalents [mg CO2-eq m-2 h-1], thereby providing a dataset on the contribution of soil CO2, N2O and CH4 fluxes to the soil global warming potential. This product is part of the EJP SOIL internal project SOMMIT, and serves as deliverables WP3.2 and WP3.3.</p>
Dataset for Measuring turbulent CO2 fluxes with a closed-path gas analyzer in a marine environment (2018)
<p>Dataset for Honkanen et al. (2018). The package contains .csv datafile and .pdf readme file.</p> <p>Included .csv file consists of CO2 flux and additional data measured at the Utö Atmospheric and Marine Research Station (59°46’55” N, 21°21’27” E) during July-October 2017. The file is comma-separated and its headers describe the variable name and the units: see readme file for more information about the columns. Missing values are indicated with -999. For more information, the reader is referred to Honkanen et al. (2018).</p> <p>Honkanen, M., Tuovinen, J.-P., Laurila, T., Mäkelä, T., Hatakka, J., Kielosto, S., and Laakso, L.: Measuring turbulent CO<sub>2</sub> fluxes with a closed-path gas analyzer in marine environment, Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2018-61, in review, 2018.</p>
Dataset for "Responses of Soil Greenhouse Gas Fluxes to Land Management in Forests and Grasslands : A Global Meta-analysis"
<p>This dataset archives the original data for the study "Responses of Soil Greenhouse Gases Fluxes to Land Management in Forests and Grasslands: A Global Meta-analysis".</p>
Data from: Technical note: rapid image-based field methods improve the quantification of termite mound structures and greenhouse-gas fluxes
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Data from: Soil trace gas fluxes along orthogonal precipitation and soil fertility gradients in tropical lowland forests of Panama
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Data from: Using greenhouse gas fluxes to define soil functional types
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Linking potential greenhouse gas and nitric oxide fluxes to soil microbial communities in incubation experiments with soil from the SAFE landscape
<b>Description: </b><p>Controlled lab experiment to measure potential GHG emissions and associated parameters from SAFE soil. Soil taken Nov 2016, lab experiment carried out Apr-May 2017. Day 0 is before fertilisation, day 1 application of NH4NO3 solution to simulate N deposition of approx. 5 kg N ha-1 y-1 . Day 15 for (OP2,OP7 and RR) application of NH4NO3 solution to simulate N deposition of approx 50 kg N ha-1 y-1.</p><p><b>Project: </b>This dataset was collected as part of the following SAFE research project: <a href="https://www.safeproject.net/projects/project_view/126"><b>Characterising soil microbial communities and measuring associated biogeochemical fluxes</b></a></p><p><b>Funding: </b>These data were collected as part of research funded by: </p><ul><li>NERC HMTF (Research Programme, (NE/K016091/1), <a href=" http://lombok.nerc-hmtf.info/"> http://lombok.nerc-hmtf.info/</a>)</li></ul><p>This dataset is released under the CC-BY 4.0 licence, requiring that you cite the dataset in any outputs, but has the additional condition that you acknowledge the contribution of these funders in any outputs.</p><p></p><p><b>Permits: </b>These data were collected under permit from the following authorities:</p><ul><li>Sabah Biodiversity Centre (Research licence JKM/MBS.1000-2/3 JLD.2 (115))</li></ul><p></p><p><b>XML metadata: </b>GEMINI compliant metadata for this dataset is available <a href="https://www.safeproject.net/datasets/xml_metadata?id=3897394">here</a></p><p><b>Files: </b>This consists of 1 file: Lab_experiment_Melissa_corrected.xlsx</p><p><b>Lab_experiment_Melissa_corrected.xlsx</b></p><p>This file contains dataset metadata and 2 data tables:</p><ol><li><p><b>parameters_repeated_measures</b> (described in worksheet parameters_repeated_measures)</p><p>Description: soil characteristics</p><p>Number of fields: 16</p><p>Number of data rows: 207</p><p>Fields: </p><ul><li><b>core_id</b>: Location measurement was taken (Field type: id)</li><li><b>site</b>: Location measurement was taken (Field type: location)</li><li><b>landuse</b>: Land use of location (Field type: categorical)</li><li><b>day_of_exp</b>: day number (Field type: numeric)</li><li><b>flux_CH4</b>: Soil CH4 flux (Field type: numeric)</li><li><b>flux_CO2</b>: Soil CO2 flux (Field type: numeric)</li><li><b>flux_N2O-N</b>: Soil N2O flux (Field type: numeric)</li><li><b>flux_NO</b>: Soil NO flux (Field type: numeric)</li><li><b>NH4-N</b>: Soil NH4 concentration (Field type: numeric)</li><li><b>NO3-N</b>: Soil NO3 concentration (Field type: numeric)</li><li><b>soil_moisture</b>: Soil moisture around the flux chamber (Field type: numeric)</li><li><b>archaeal amoA</b>: Gene transcript abundance (Field type: numeric)</li><li><b>Proteobacteria_nirS</b>: Gene transcript abundance (Field type: numeric)</li><li><b>AniA_nirK</b>: Gene transcript abundance (Field type: numeric)</li><li><b>nosZ-I</b>: Gene transcript abundance (Field type: numeric)</li><li><b>nosZ-II</b>: Gene transcript abundance (Field type: numeric)</li></ul></li><li><p><b>parameters_one_off</b> (described in worksheet parameters_one_off)</p><p>Description: soil pH and density</p><p>Number of fields: 5</p><p>Number of data rows: 18</p><p>Fields: </p><ul><li><b>core id</b>: Location measurement was taken (Field type: id)</li><li><b>site</b>: Location measurement was taken (Field type: location)</li><li><b>landuse</b>: Land use of location (Field type: categorical)</li><li><b>pH</b>: Soil pH (Field type: numeric)</li><li><b>bulk_density</b>: dry weight of soil (Field type: numeric)</li></ul></li></ol><p><b>Date range: </b>2016-11-01 to 2017-05-30</p><p><b>Latitudinal extent: </b>4.5000 to 5.0700</p><p><b>Longitudinal extent: </b>116.7500 to 117.8200</p>
Data from: Proximate controls on semiarid soil greenhouse gas fluxes across 3 million years of soil development
Soils are important sources and sinks of three greenhouse gases (GHGs): carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O). However, it is unknown whether semiarid landscapes are important contributors to global fluxes of these gases, partly because our mechanistic understanding of soil GHG fluxes is largely derived from more humid ecosystems. We designed this study with the objective of identifying the important soil physical and biogeochemical controls on soil GHG fluxes in semiarid soils by observing seasonal changes in soil GHG fluxes across a three million year substrate age gradient in northern Arizona. We also manipulated soil nitrogen (N) and phosphorus availability with 7 years of fertilization and used regression tree analysis to identify drivers of unfertilized and fertilized soil GHG fluxes. Similar to humid ecosystems, soil N2O flux was correlated with changes in N and water availability and soil CO2 efflux was correlated with changes in water availability and temperature. Soil CH4 uptake was greatest in relatively colder and wetter soils. While fertilization had few direct effects on soil CH4 flux, soil nitrate was an important predictor of soil CH4 uptake in unfertilized soils and soil ammonium was an important predictor of soil CH4 uptake in fertilized soil. Like in humid ecosystems, N gas loss via nitrification or denitrification appears to increase with increases in N and water availability during ecosystem development. Our results suggest that, with some exceptions, the drivers of soil GHG fluxes in semiarid ecosystems are often similar to those observed in more humid ecosystems.
Experimental study of the effect of molecular collision frequency and adsorption capacity on gas seepage flux in coal
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Tracing low-CO2 fluxes in soil incubation and 13C labeling experiments: a simplified gas sampling system for respiration and photosynthesis measurements
<p>Data set containing data from feature tests (1-3) as well as photosynthesis and respiration measurements.</p>
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OpenNeuro
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