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82 results for “methane flux”

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dryad36/100

Graminoids vary in functional traits, carbon dioxide and methane fluxes in a restored peatland: implications for modeling carbon storage

1. One metric of peatland restoration success is the re-establishment of a carbon sink, yet considerable uncertainty remains around the timescale of carbon sink trajectories. Conditions post-restoration may promote the establishment of vascular plants such as graminoids, often at greater density than would be found in undisturbed peatlands, with consequences for carbon storage. Although graminoid species are often considered as a single plant functional type (PFT) in land-atmosphere models, our understanding of functional variation among graminoid species is limited, particularly in a restoration context. 2. We used a traits-based approach to evaluate graminoid functional variation and to assess whether different graminoid species should be considered a single PFT or multiple types. We tested hypotheses that greenhouse gas fluxes (CO2, CH4) would vary due to differences in plant traits among five graminoid species in a restored peatland in central Alberta, Canada. We further hypothesized that species would form two functionally distinct groupings based on taxonomy (grass, sedge). 3. Differences in gas fluxes among species were primarily driven by variation in leaf physiology related to photosynthetic efficiency and resource-use, and secondarily by plant size. Multivariate analyses did not reveal distinct functional groupings based on taxonomy or environmental preferences. Rather, we identified functional groups defined by plant traits and carbon fluxes that are consistent with ecological strategies related to differences in growth rate, resource-acquisition, and leaf economics, representing plants with either a strategy to grow quickly and invest in resource capture or to prioritize structural investment and resource conservation. These functional groups displayed larger average carbon fluxes compared to graminoid PFTs currently used in modeling. 4. Existing PFT designations in peatland models may be more appropriate for pristine or high-latitude systems than those under restoration. Although replacing PFTs with plant traits remains a challenge in peatlands, traits related to leaf physiology and growth rate strategies offer a promising avenue for future applications.

opencc-zeroMay 2022View details →

zenodo36/100

Carbon Dioxide and Methane Flux Meta Analysis, Schaerer et al: Permafrost microbes unleashed: thaw reactors provide timely insights into greenhouse gas feedbacks for climate stewardship

Meta-analysis results and workflow: Meta-Analysis-Report-V1.pdf  raw data tables for input into meta-analysis: co2_flux_by_layer_temp.csv co2_flux_by_layer_time.csv ch4_flux_by_layer_temp.csv ch4_flux_by_layer_time.csv co2_flux_by_headspace_temp.csv (Data included in these tables was digitized using the R package metaDigitize) **** We also attempted to summarize the raw data from 12 studies which is summarized in the Flux_Summary_Report document. we converted all units into mg C / g Soil * d (calculations are included in the co2_meta_analysis spreadsheet). For studies not reporting raw data or data tables (7/12 studies), we estimated the values from the figures manually. This typically resulted in an estimate of the mean flux of several replicates (all studies had 3-10 replicates). We filled in metadata as well as we could based on the information available in the papers, although there were many gaps. This information is summarized in the flux_data_compilation spreadsheet. Studies in the raw data comparison include: Mackelprang 2011, Waldrop 2010 & 2021, Barbato 2022, Dang 2022, Muller 2018, Monteaux 2020, Dutta 2006, Lee 2012, O'Donnell 2009, Roy Chowdhury 2014, Trubl 2021.

opencc-by-4.0Apr 2024View details →

zenodo36/100

Mapping Russian Wetlands and Estimating Methane Fluxes

<h3>Mapping Russian Wetlands and Estimating Methane Fluxes</h3> Introduction Wetlands are crucial in regulating the Earth’s climate, acting as both carbon sinks and significant methane sources. Russian wetlands represent one of the largest and most diverse wetland complexes globally, extending across biomes from Arctic tundra to boreal forests. Despite their importance, these wetlands remain underexplored, particularly in terms of their spatial distribution and greenhouse gas contributions. This dataset provides a detailed typological map of Russian wetlands and accompanying methane flux estimates, representing the most comprehensive methane emissions dataset for Russian wetlands to date. The maps and calculations were developed in Google Earth Engine (GEE) through a combination of multi-seasonal Landsat composites, PALSAR radar imagery, and extensive field-based validation data from peatland sites across Western Siberia. <h3>Data Overview</h3> Input Layers The wetland mapping relied on seasonal Landsat composites (spring, summer, fall) and PALSAR radar data to capture the distinct structural and hydrological characteristics of each wetland type. Additional layers, such as GMTED topographic slope and Hansen’s TreeCover, were included to exclude non-wetland areas and to enhance the classification by distinguishing forested from non-forested wetlands. Training Points A comprehensive training site database was created, integrating field knowledge, high-resolution imagery, and georeferenced photos. Approximately 2,450 representative points were selected to capture 12 primary wetland types across Russia, with each point validated against high-resolution imagery to ensure accuracy. Points were collected to represent the wide-ranging wetland ecosystems in Russia, from open water and patterned bogs to swampy and forested fens, providing robust ground-truth data for training the classification model. Random Forest Classifier The random forest classifier was chosen for its capacity to handle large datasets and complex relationships among input layers. Optimized for Landsat and PALSAR inputs, the classifier used over 100 trees, each making independent predictions based on subsets of data, which were averaged to produce the final classification. This ensemble approach minimized overfitting, a crucial factor for the varied ecological regions across Russia. Russian Wetlands Map The final Russian Wetlands Map encompasses 12 wetland types, detailing their distribution and extent across the country: <ul> <li> Total Wetland Area: 173.96 million hectares of mapped wetlands, capturing diverse ecosystems, including bogs, fens, and swampy areas. </li> <li> Open Water Area: Lakes, rivers, and smaller water bodies within wetland zones were separately mapped, totaling 42.6 million hectares. </li> </ul> <h3>Emission Modeling and Ecosite Analysis</h3> Ecosite Proportions for Methane Emission Modeling Each wetland type was further divided into ecosite units representing distinct, smaller areas with uniform hydrological and geochemical properties. This level of detail enabled precise methane emission estimates by capturing the variability within complex wetland ecosystems. For instance, ridges and hollows within patterned bogs exhibit unique methane emission dynamics due to differences in vegetation and water levels. Ecosite proportions for methane emission were calculated from 20-30 representative field sites per wetland type, capturing the typical area breakdown of each wetland type across Russia. Methane Emission Period Calculation To estimate seasonal methane emission periods across Russia’s climatic zones, the average summer temperature (Bio10) parameter from WorldClim data was used. Bio10 values reflect seasonal variation in emission potential, correlating with longer and warmer summers in southern regions versus shorter, cooler summers in the north. Using these data, an emission period was calculated for each 50 km x 50 km grid cell based on a regression model derived from Western Siberia data: Emission Period (hours) = 303 * Bio10 – 675 This equation, which explained 98% of the variation in emission duration, provided a dynamic method for estimating emission periods across Russia’s diverse landscape. <h3>Methane Emission Estimates</h3> Calculation Approach Methane emission estimates were derived from a multi-step approach that incorporated ecosystem-specific emission factors, ecosystem area, and the estimated emission period: <ol> <li> Ecosystem Area Calculation: Area estimates for each ecosite type were derived from field-based proportions applied to the classified wetland map. </li> <li> Emission Period: Calculated for each grid cell based on Bio10 data, varying continuously across climatic zones. </li> <li> Methane Flux Values: Based on quantiles from field measurements within three main zones (Tundra, Northern Taiga, and Southern Taiga) to account for natural variability in methane emissions. </li> </ol> Using this approach, methane emissions were calculated for each 50 km per 50 km grid cell, factoring in the unique emission characteristics of each wetland type and zone. This produced a spatially detailed estimate of methane fluxes, reflective of the temperature and vegetation gradients across Russia.   Resulting National Estimate <ul> <li> Total Annual Methane Emissions: 11.39 MtCH₄ per year from all mapped wetland areas. </li> <li> Open Water Contributions: 2.54 MtCH₄ per year from open water bodies, including intra-wetland lakes and rivers. </li> </ul> <h3>Data Highlights</h3> <ul> <li> High-resolution wetland classification covering 173.96 million hectares across diverse wetland ecosystems. </li> <li> Detailed methane emission data derived from multi-year field measurements and validated against climatic data, providing spatially continuous methane flux estimates across Russia. </li> <li> 50x50 km² grid cell calculations, accounting for methane emission rates, emission periods, and ecosystem proportions for each cell. </li> </ul> This dataset serves as an essential tool for environmental scientists, climate modelers, and conservationists, supporting further research into wetland carbon dynamics, climate mitigation strategies, and regional land-use planning. The high resolution data availbale at url: https://code.earthengine.google.com/d6a9d4045255fd84298777e56a38ae03

opencc-by-4.0Oct 2024View details →

zenodo36/100

Dataset for "Interpreting eddy covariance data from heterogeneous Siberian tundra: land cover-specific methane fluxes and spatial representativeness"

The micrometeorological dataset used in Tuovinen, J.-P., Aurela, M., Hatakka, J., Räsänen, A., Virtanen, T., Mikola, J., Ivakhov, V., Kondratyev, V. and Laurila, T.: Interpreting eddy covariance data from heterogeneous Siberian tundra: land cover-specific methane fluxes and spatial representativeness. Biogeosciences Discussions, https://doi.org/10.5194/bg-2018-155, 2018 (accepted for publication in Biogeosciences).

opencc-by-4.0Dec 2018View details →

dryad36/100

Maps of predicted carbon dioxide and methane fluxes from waterbodies in the Yukon-Kuskokwim Delta, Alaska

In the Arctic, waterbodies are abundant, and rapid thaw of permafrost is destabilizing the carbon cycle and changing hydrology. It is particularly important to quantify and accurately scale aquatic carbon emissions in arctic ecosystems. Recently available high-resolution remote sensing datasets capture the physical characteristics of arctic landscapes at unprecedented spatial resolution. We demonstrate how machine learning models can capitalize on these spatial datasets to greatly improve accuracy when scaling waterbody CO2 and CH4 fluxes across the Yukon-Kuskokwim (YK) Delta of south-west AK. These datasets include carbon dioxide and methane dissolved concentrations and diffusive fluxes from a research watershed in the central YK Delta.

opencc-zeroDec 2022View details →

zenodo36/100

Methane Fluxes and 13C-CH4 from a Northern Temperate Peatland

This dataset contains methane (CH4) emissions and their 13C isotope composition (δ13C-CH4) measured using the static flux chamber method in a poor fen in New Hampshire, USA. Measurements were collected weekly (CH4 emissions) to bi-weekly (δ13C-CH4) from flux collars with varying microtopgraphy (hummock, lawn, and wet) from May to August 2020 and 2021. Datasets includes metadata of water table depth, peat and air temperature, and precipitation collected alongside flux meausurements. Each data file contains a "README" tab with a guide for variable units and descriptions.

opencc-by-4.0Jan 2023View details →

zenodo36/100

Subsurface redox interactions regulate ebullitive methane flux in heterogeneous Mississippi River deltaic wetland

This dataset is model outputs archive from a model study about  'Subsurface redox interactions regulate ebullitive methane flux in heterogeneous Mississippi River deltaic wetland' (manuscript is Under Review). Plotting scripts are also included in this data file. There are four model results. 'Ebull' model output are ebullition flux, 'Jswi' model output are diffusion flux across soil-water interface, and 'Methane' files are porewater concentration results in each soil layers, and 'LtranR' model outputs for redox species exchange rates across different soil layers. The model source codes can be found at <a href="https://zenodo.org/record/8084441">https://zenodo.org/record/8084441</a> and <a href="https://zenodo.org/record/8087566">https://zenodo.org/record/8087566</a>.

opencc-by-4.0Jun 2023View details →

dryad36/100

Data from: Microbial activity contributes to spatial heterogeneity of wetland methane fluxes

The emission of methane from wetlands is spatially heterogeneous, as concurrently measured surface fluxes can vary by orders of magnitude within the span of a few meters. Despite extensive study and the climatic significance of these greenhouse gas emissions, it remains unclear what drives these large within-site variations, creating a knowledge-gap that impedes a mechanistic understanding of wetland fluxes. While geophysical variables including water table depth (WTD) and soil temperature are known to correlate with CH4 flux, measurable variance in these parameters declines as spatial and temporal scales become finer. Here, we leveraged depth-stratified gene abundance and gene expression measurements of methanogenesis and methanotrophy to investigate CH4 flux variance at an ombrotrophic peat bog. Our results show that the flux variance was strongly correlated to methanogen abundance and that peat depth also exerted significant control over CH4 flux, methanogen abundance, and the relationship between the two. Correlations between CH4 flux and either WTD or soil temperature were absent or minimal. These findings suggest that microbial factors likely underlie localized variance in wetland CH4 flux, and that a greater reliance on biological predictors could improve our ability to understand wetland methane fluxes at finer scales than is currently possible.

opencc-zeroSep 2023View details →

zenodo36/100

Hourly methane and carbon dioxide fluxes from temperate ponds

This dataset consists of methane and carbon dioxide flux measurements from three forest and three open-land ponds in Denmark. Furthermore, oxygen, water temperature and weather data are also available. The data is part of the scientifical paper published in Springer Biogeochemistry  Hourly methane and carbon dioxide fluxes from temperate ponds

openother-openJun 2023View details →

zenodo36/100

Evolution of sediment temperature, pressure, phases distribution, carbon pools and seabed methane flux at the Arctic continental Shelves since the Last Glacial Maximum

This dataset are produced by a manuscript (Biodegradation of Ancient Organic Carbon Fuels Seabed Methane Emission at the Arctic Continental Shelves)  to be submitted to the Journal of Geophysical Research - Global Biogeochemical Cycles.  I The file "MethaneEmission_Permafrost" contains the predicted  temperature, pressure, pore water salinity, ice stable zone, methane hydrate stable zone, ice saturation, methane hydrate saturation, free methane gas saturation, labile organic carbon content, stable organic carbon content, and methanogenesis rate from seafloor to 1200 m depth from 18,000 years before present to 2,000 years after present for 8 different simulation scenarios.  The file "Seabed_Methane_Flux" contains the predicted seabed methane emission rate from 18,000 years before present to 2,000 years after present for 8 different simulation scenarios.  Detailed information about the model could be found in the paper Biodegradation of Ancient Organic Carbon Fuels Seabed Methane Emission at the Arctic Continental Shelves.

opencc-by-4.0Oct 2023View details →

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