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Mapping Russian Wetlands and Estimating Methane Fluxes

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NIAID Data Ecosystem2026-05-02 收录
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https://zenodo.org/record/13997235
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Mapping Russian Wetlands and Estimating Methane Fluxes 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. Data Overview 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: Total Wetland Area: 173.96 million hectares of mapped wetlands, capturing diverse ecosystems, including bogs, fens, and swampy areas. Open Water Area: Lakes, rivers, and smaller water bodies within wetland zones were separately mapped, totaling 42.6 million hectares. Emission Modeling and Ecosite Analysis 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. Methane Emission Estimates 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: Ecosystem Area Calculation: Area estimates for each ecosite type were derived from field-based proportions applied to the classified wetland map. Emission Period: Calculated for each grid cell based on Bio10 data, varying continuously across climatic zones. 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. 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 Total Annual Methane Emissions: 11.39 MtCH₄ per year from all mapped wetland areas. Open Water Contributions: 2.54 MtCH₄ per year from open water bodies, including intra-wetland lakes and rivers. Data Highlights High-resolution wetland classification covering 173.96 million hectares across diverse wetland ecosystems. Detailed methane emission data derived from multi-year field measurements and validated against climatic data, providing spatially continuous methane flux estimates across Russia. 50x50 km² grid cell calculations, accounting for methane emission rates, emission periods, and ecosystem proportions for each cell. 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
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2024-10-28
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