Find research datasets worth reusing

openCC0Feb 2025View details →

Peat depth and occurrence in areas covered by airborne radiometric surveys, southeastern and western Norway, 1983-2023.

This data package contains point measurements of peat depth and occurrence from two study sites in Norway: Skrimfjella, located in eastern Norway, and Ørskogfjellet, located in western Norway. These sites represent contrasting physical geographies, with diverse bedrock and landscape types, including inland hills and mountains, coastal plains, and inland valleys. The data were collected primarily during field campaigns in August 2020 (Skrimfjella) and August 2023 (Ørskogfjellet). The data package also contains peat depth measurements from beyond these primary field campaigns. These ancillary data were provided by the Norwegian Public Roads Administration and the Norwegian Institute of Bioeconomy Research. Peat depths were measured using manual probing, boreholes, and ground-penetrating radar (GPR). The data package is intended for use in digital soil mapping (DSM) applications at the landscape-regional scale, particularly for predicting peat depth and assessing relationships between peat depth and environmental variables. It supports research on peatland carbon stocks, land use planning, and climate change mitigation. The peat depth measurements are intended to be representative of sampled locations within the study areas, with a focus on peatland environments. The data package does not include comprehensive peatland extent mapping but provides insights into the spatial variability of peat depths in Norwegian landscapes.

Nutrient data from the Peat Collapse-Saltwater Intrusion Field Experiment from brackish and freshwater sites within Everglades National Park, Florida (FCE LTER), collected from October 2014 to September 2016

With sea level rise increasing, saltwater intrusion into low-lying coastal wetlands is likely to occur. We simulated saltwater intrusion into an Everglades marsh through monthly additions of elevated salinity water. Monthly porewater nutrients were taken at 15 cm depth from a brackish and a freshwater marsh. Porewater physicochemistry was measured 24 hours after dosing. Collection occurred from Oct 2014 - Sep 2016. The collected water was then analyzed for temperature, conductivity, salinity, pH, alkalinity, chloride, DOC, NH4, SO4, TDN, SRP, TDP, and sulfide. These data are published in Wilson, B.J., Servais, S., Mazzei, V., Davis, S.E., Kelly, S., Gaiser, E., Kominoski, J.S., Richards, J., Rudnick, D., Sklar, F., Stachelek, J., and Troxler, T.G. Salinity pulses interact with seasonal dry-down to increase ecosystem carbon loss in marshes of the Florida Everglades. 2018. Ecological Applications 28:2092-2018.

Leaf nutrient and root biomass data from the Peat Collapse-Saltwater Intrusion Field Experiment within Everglades National Park (FCE), collected from October 2014 to September 2016

With sea level rise increasing, saltwater intrusion into low-lying coastal wetlands is likely to occur. We simulated saltwater intrusion into an Everglades marsh through monthly additions of elevated salinity water. Yearly sawgrass leaf carbon, nitrogen, and phosphorus concentrations and live root biomass measurements were measured from a brackish water and freshwater marsh. All measurements were taken every other month 24 hours after dosing. Measurements occurred from Oct 2014 - Sep 2016. Ecosystem flux measured includes gross ecosystem production, ecosystem respiration of CO2, net ecosystem production, and ecosystem respiration of CH4. These data are published in Wilson, B.J., Servais, S., Mazzei, V., Davis, S.E., Kelly, S., Gaiser, E., Kominoski, J.S., Richards, J., Rudnick, D., Sklar, F., Stachelek, J., and Troxler, T.G. Salinity pulses interact with seasonal dry-down to increase ecosystem carbon loss in marshes of the Florida Everglades. Ecological Applications. Accepted.

Biomass data from the Peat Collapse-Saltwater Intrusion Field Experiment within Everglades National Park (FCE), collected from October 2014 to September 2016

With sea level rise increasing, saltwater intrusion into low-lying coastal wetlands is likely to occur. We simulated saltwater intrusion into an Everglades marsh through monthly additions of elevated salinity water. Monthly biomass, aboveground net primary production, and culm density measurements were measured from a brackish water and freshwater marsh. All measurements were taken every other month 24 hours after dosing. Measurements occurred from Oct 2014 - Sep 2016. Ecosystem flux measured includes gross ecosyetem production, ecosystem respiration of CO2, net ecosystem production, and ecosystem respiration of CH4. These data are published in Wilson, B.J., Servais, S., Mazzei, V., Davis, S.E., Kelly, S., Gaiser, E., Kominoski, J.S., Richards, J., Rudnick, D., Sklar, F., Stachelek, J., and Troxler, T.G. Salinity pulses interact with seasonal dry-down to increase ecosystem carbon loss in marshes of the Florida Everglades. Ecological Applications. Accepted.

Modeled flux data from the Peat Collapse-Saltwater Intrusion Field Experiment within Everglades National Park (FCE), collected from October 2014 to September 2016

With sea level rise increasing, saltwater intrusion into low-lying coastal wetlands is likely to occur. We simulated saltwater intrusion into an Everglades marsh through monthly additions of elevated salinity water. Monthly modeled ecosystem flux measurements were calculated from a brackish water and freshwater marsh. Ecosystem flux was measured 24 hours after dosing. Measurements occurred from Oct 2014 - Sep 2016. Ecosystem flux measured includes gross ecosyetem production, ecosystem respiration of CO2, net ecosystem production, and ecosystem respiration of CH4. These data are published in Wilson, B.J., Servais, S., Mazzei, V., Davis, S.E., Kelly, S., Gaiser, E., Kominoski, J.S., Richards, J., Rudnick, D., Sklar, F., Stachelek, J., and Troxler, T.G. Salinity pulses interact with seasonal dry-down to increase ecosystem carbon loss in marshes of the Florida Everglades. Ecological Applications. Accepted.

Flux data from the Peat Collapse-Saltwater Intrusion Field Experiment within Everglades National Park, collected from October 2014 to September 2016

With sea level rise increasing, saltwater intrusion into low-lying coastal wetlands is likely to occur. We simulated saltwater intrusion into an Everglades marsh through monthly additions of elevated salinity water. Monthly ecosystem flux measurements were taken from a brackish water and freshwater marsh. Ecosystem flux was measured 24 hours after dosing. Measurements occurred from Oct 2014 - Sep 2016. Ecosystem flux measured includes gross ecosyetem production, ecosystem respiration of CO2, net ecosystem production, and ecosystem respiration of CH4. These data are published in Wilson, B.J., Servais, S., Mazzei, V., Davis, S.E., Kelly, S., Gaiser, E., Kominoski, J.S., Richards, J., Rudnick, D., Sklar, F., Stachelek, J., and Troxler, T.G. Salinity pulses interact with seasonal dry-down to increase ecosystem carbon loss in marshes of the Florida Everglades. Ecological Applications. Accepted.

opencc-by-4.0Feb 2024View details →

BSRLC+: An annual land cover dataset for the Baltic Sea Region with crop types and peat bogs at 30 m from 2000 to 2022

(NEW) Baltic Sea Region Land Cover Urban (BSRLC-U) focusing on urban built-up types now available: <a href="https://zenodo.org/records/17347941">https://zenodo.org/records/17347941 </a> Baltic Sea Region Land Cover Plus (BSRLC+) is annual land cover mapping (30 m) dataset in Europe from 2000 to 2022. The maps contain detailed information of 18 land cover (LC) types, including 9 crop types and 2 peat bog types. Input data : Optical multi-temporal remote sensing imageries (Landsat 5 (TM) / 7 (ETM+) / 8 (OLI) / 9 (OLI+) and Sentinel 2 (A / B ) from 2000 to 2022. Data is processed to surface reflectance and tiled into datacube structure using <a href="https://doi.org/10.3390/rs11091124">Framework for Operational Radiometric Correction for Environmental monitoring - FORCE.</a> Mapping method: Maps are produced using data encoding and deep learning classification according to <a href="https://doi.org/10.1016/j.jag.2024.103867">Pham et al. 2024</a> Validation: Maps have been rigorously validated using independent in-situ data <a href="https://doi.org/10.1038/s41597-020-00675-z">The Land Use/Cover Area frame Survey (LUCAS)</a>.  Traing data and validation data are available: <a href="https://zenodo.org/records/11073291">https://zenodo.org/records/11073291</a> This dataset contains: <ul> <li>00_preview.png: Preview map (2022) of the Baltic Sea region</li> <li>BSRLC_{year}.tif: Annual map data (30 m) in GeoTIFF format (projection ETRS89 / EPSG:3035)</li> <li>BSRLC_legend.xlss: Land cover codes and class names</li> <li>BSRLC_qgis_style.qml: Map style to be used in QGIS</li> <li>BSRLC_arcgis_style.lyrx: Map style to be used in ArcGIS</li> </ul> Land cover codes (can also be found in BSRLC_legend.xlss): <ul> <li>1: Built-up</li> <li>2: Bareland</li> <li>3: Water</li> <li>4: Shrubland</li> <li>5: Broadleaf forest</li> <li>6: Coniferous forest</li> <li>7: Wetland marsh</li> <li>8: Exploited peat bog</li> <li>9: Unexploited peat bog</li> <li>10: Wheat</li> <li>11: Barley</li> <li>12: Rye</li> <li>13: Oat</li> <li>14: Maize</li> <li>15: Seed crops</li> <li>16: Root crops</li> <li>17: Pulses, vegetable</li> <li>18: Grassland</li> <li>255: Nodata</li> </ul>   Publication (please cite this publication if you are using the dataset): <ul> <li>Pham, V.-D., de Waard, F., Thiel, F., Bobertz, B., Hellmann, C., Nguyen, D.-V., Beer, F., Arasumani, M., Schwieder, M., Hartleib, J., Frantz, D., & van der Linden, S. (2024). An annual land cover dataset for the Baltic Sea Region with crop types and peat bogs at 30 m from 2000 to 2022. Scientific Data, 11, 1242, <a href="https://doi.org/10.1038/s41597-024-04062-w">https://doi.org/10.1038/s41597-024-04062-w</a></li> </ul>   Other related publications: <ul> <li>Pham, V.-D., Tetteh, G., Thiel, F., Erasmi, S., Schwieder, M., Frantz, D., & van der Linden, S. (2024). Temporally transferable crop mapping with temporal encoding and deep learning augmentations. International Journal of Applied Earth Observation and Geoinformation, 129, 103867, <a href="https://doi.org/10.1016/j.jag.2024.103867">https://doi.org/10.1016/j.jag.2024.103867</a></li> <li>Frantz, D. (2019). FORCE—Landsat + Sentinel-2 Analysis Ready Data and Beyond. Remote Sensing, 11, <a href="https://doi.org/10.3390/rs11091124">https://doi.org/10.3390/rs11091124</a></li> </ul>   Funding This datatset is created in the frame of the Interdisciplinary Research Center for the Baltic Sea Region Research (IFZO) of University of Greifswald, Germany, and the research project Fragmented Transformations, which is funded by the German Federal Ministry of Education and Research (FKZ 01UC2102).

embargoedcc-by-4.0Nov 2024View details →

Modelling CO2 emissions of cultivated and rewetted peat soils with SWAP-ANIMO - Dataset

Three locations in Europe (wet river valley (Denmark), coastal peatland (The Netherlands) and broad river floodplain (Switzerland)) were selected for which two to three years of measurements of hydrological variables and CO2 exchange fluxes were available for some period between 2015 and 2023. The hydrology, grass growth and CO2 fluxes of these sites were modelled with the SWAP-ANIMO model using the available measurement period for model input and calibration. Model simulations were used to improve the understanding of the hydrological drivers of each site and to obtain estimates of the different pools contributing to the measured CO2 fluxes using a period of 10 years (2014-2023). Rewetting was considered either by calibration on direct measurements of an actual rewetting measure (Denmark, The Netherlands) or extrapolation of the reference simulation (Switzerland). Also, the potential impact of climate change on the rate of peat oxidation was modelled for these sites for both the reference and rewetting measure. The dataset contains the relevant detailed, daily model output of the 10 year simulation period and aggregated, yearly model output of the scenario simulations which are detailed in the corresponding report (van de Craats et al., 2024), available at <a href="https://doi.org/10.5281/zenodo.14041243">https://doi.org/10.5281/zenodo.14041243</a>.

opencc-by-4.0Sep 2024View details →

Skogaryd data used for the paper: Evaluation of long-term carbon dynamics in a drained forested peatland using the ForSAFE-Peat Model.

Dataset of abiotic and carbon exchange variables for Skogaryd drained afforested peatland. The dataset include measurements of soil temperature, ground water level, and carbon exhange as well as modelled carbon fluxes performed with the model ForSAFE-Peat

opencc-by-4.0Dec 2021View details →

Fig. 5 in The Diversity And Species Composition Of Water Beetles (Gyrinidae, Dytiscidae, Hydrophilidae) In A Peat Bog In Belarus

Fig. 5. Principal component analysis ordination according of water beetle assemblages in three different water body types: lakes (L), streams (S), and hollows (H). Complete species names are given in table 2.

opencc-by-4.0Dec 2021View details →

Fig. 4 in The Diversity And Species Composition Of Water Beetles (Gyrinidae, Dytiscidae, Hydrophilidae) In A Peat Bog In Belarus

Fig. 4. Non-metric multidimensional scaling ordination according to the characteristic resemblance matrix (Bray-Curtis distance) of water beetle assemblages in three different water body types: lakes (L — samples marked as dots), streams (S — samples marked as pluses), and hollows (H — samples marked as squares).

opencc-by-4.0Apr 2022View details →

Electron Accepting Capacities of a wide variety of peat materials from around the Globe similarly explain CO2 and CH4 production

In peat soils the availability of terminal electron acceptors (TEAs), both inorganic and organic, largely determines the ratio of carbon dioxide to methane formation under waterlogged, anoxic conditions. The redox properties of peat organic matter and their relationship with anoxic carbon mineralization are yet only investigated for a limited amount of peat and reference materials, although electron accepting capacities of organic matter (EACOM) largely predominate over canonical inorganic TEAs in peatlands. To address this knowledge gap, we incubated 60 peat samples from four different depths of 15 sites located in five major peatland regions (including Germany, Sweden, Russia, France and Chile) distributed around the globe covering a variety of both bog and fen type samples and characterized their capacities to serve as electron acceptors for anaerobic carbon dioxide production. The dataset consists of a wide variety of recorded and calculated variables for a 56-day incubation of those samples. These variables include the formation and rates of methane, carbon dioxide, electron acceptor capacities and electron donator capacities at two different times, data on stable isotopes in delta notation (such as nitrogen, carbon and sulfur), molar element ratios for carbon/nitrogen, carbon/sulfur and nitrogen/phosphorus and elemental contents like silicon, phosphorus, sulfur, calcium and iron as well as specific fourier transformed infrared spectroscopy ratios regarding the ratios of polysaccharides and aromatic structures. The dataset was created mostly in 2019, with some additional measurements carried out in 2020 and 2021.

opencc-by-4.0Jul 2024View details →

On the relationship between methane production in anaerobic incubations of peat material and in-situ methane emissions

These files are meant to accompany the publication: On the relationship between methane production in anaerobic incubations of peat material and in-situ methane emissions  Alexandra B. Cory1, Rachel M. Wilson1*, Olivia C. Ogles1, Patrick M. Crill2, Zhen Li3, Kuang-Yu Chang3, Samantha Bosman1, EMERGE Project Coordinators4, Isogenie Field Team5, Virginia I. Rich3, and Jeffrey P. Chanton1 <a name="_Hlk72229759"></a>1Department of Earth, Ocean, and Atmospheric Science, Florida State University, Tallahassee, FL, <a name="_Hlk72229408"></a>USA 2Dept of Geological Sciences and Bolin Centre for Climate Research, Stockholm University; Stockholm, 106 91 Stockholm, Sweden <a name="_Hlk72229459"></a>3Department of Microbiology, The Ohio State University, Columbus, OH, USA 4Lawrence Berkeley National Laboratory; Berkeley, CA, USA. 5EMERGE Project Coordinators list of authors and affiliations appears in Acknowledgements.   Corresponding author: Rachel M. Wilson (rmwilson@fsu.edu) Key Points: ·         Laboratory incubations predict field methane emissions from a peatland ·         Interannual variation is best represented by the modeled results ·         Daily-scale variation is driven by processes other than temperature and water table depth   This paper is being submitted for consideration for publication and includes the following archived files: The file:   (1)    UPLOAD_chamber_CO2_and_CH4_with_T.xlsx contains 3 tabs of data measured from the field: (1) CH4 daily, (2) CO2 daily, (3) temp.   The first tab, CH4 daily contains the measured methane fluxes from the field auto chambers spanning 2012-2018. Column headers are             Date:  date of year measurement taken             DOY:  day of year measurement taken             seqday: sequential day of measurement since 01/01/2002 year: year of measurement site: indicates the autochamber site from which the data are measured cH4_flx (mg CH4/m2/d): measured methane emission in milligrams CH4 per m2 per day gC/m2/d: fluxes in grams of C per m2 per day gC/m2/y: fluxes in grams of C per m2 per year   The second tab, CO2 daily contains the measured CO2 fluxes from the field auto chambers spanning 2012-2018. Column headers are similar to the CH4 daily tab revised for CO2 when appropriate.   The third tab, temp provides the temperature in the peat below the surface at 50cm, 20cm and 10cm for 2012-2018.   (2)    UPLOAD_Incubation_All_Temp_Timesaeries_Data.xlsx contains the CO2 and CH4 production for the incubation vials at the various temperature treatments. The headers are: Habitat: indicates the habitat type from which the incubated peat was taken Depth: indicates shallow (9-19cm) peat vs. deep (25-35cm) peat Temp_C: indicates the temperature at which the incubation was conducted in °C Sample: gives a laboratory unique sample identification code Day: indicates day of incubation CH4_umoles_gDry: is the accumulated CH4 production in micromoles per g dry weight of peat CO2_umoles_gDry: is the accumulated CO2 production in micromoles per g dry weight of peat.   (3)    Fen Python Code and Bog Python Code contain all the files required to recreate the modeling results for the Fen and bog respectively.

opencc-by-sa-4.0Apr 2018View details →

Review of Emissions from Smouldering Peat Fires

The file contains two table compilations of up-to-date inter-study of peat fire gas and particle emission factors (EFs) found in the scientific literature, both from laboratory and field studies. According to the geographical origins of the peat used in fire emission studies, we classified the samples into two categories: boreal and temperate peat (we merge these two climate zones into one category owing to the limited sampling location information reported in the literature), and tropical peat. By doing this,  the best estimate peat fire EFs were calculated and compared between the two peat categories for the first time. It is hoped that the complied peat fire EFs can be used to improve the estimation of the total peat fire emission.  This data was analysed in our journal paper paper: Y. Hu, N. Fernandez-Anez, T. E. L. Smith, G. Rein, Review of Emissions from Smouldering Peat Fires and Their Contribution to Regional Haze Episodes, International Journal of Wildland Fire, 2018 (in press), DOI:10.1071/WF17084.

opencc-by-4.0Aug 2011View details →

Text-fig. 3. Geological map and schematic geological section of the discovery site of the Late Upper Palaeolithic skull from Moča (southern Slovakia). I. – Primary position (?), II. – The discovery site (secondary position), A – B – The schematic geological section of the discovery site 1. H – Fluvial clayey to sandy loams (subordinately humolites) – Holocene; secondary discovery site layer, 2. lm-pH – Loam – peat – Holocene, 3. e Wl – Eolian sands – Late Würm (Late glacial of Würm), 4. lm,sWl – Fluvial clayey (to humic) loams or fine sands – Late Würm (Late glas cial of Würm); original discovery site layer, now eroded, 4a. fe Wl – Fluvial – aeolian silty sands (calcareous) – Late Würm (Late glacial s-lm of Würm), 5. lmW3 – Fluvial loams, sandy loams – final Würm (W3), 5a. W3 – Fluvial sands – final (?) Würm (?W3), 6. gW2+3 – Fluvial gravs els, sandy gravels, sands with gravel – Pleniglacial of Würm (W2+3), 7. lW – Aeolian loess and loess loams – Würm (undivided) in A Late Upper Palaeolithic Skull From Moča (The Slovak Republic) In The Context Of Central Europe

Text-fig. 3. Geological map and schematic geological section of the discovery site of the Late Upper Palaeolithic skull from Moča (southern Slovakia). I. – Primary position (?), II. – The discovery site (secondary position), A – B – The schematic geological section of the discovery site 1. H – Fluvial clayey to sandy loams (subordinately humolites) – Holocene; secondary discovery site layer, 2. lm-pH – Loam – peat – Holocene, 3. e Wl – Eolian sands – Late Würm (Late glacial of Würm), 4. lm,sWl – Fluvial clayey (to humic) loams or fine sands – Late Würm (Late glas cial of Würm); original discovery site layer, now eroded, 4a. fe Wl – Fluvial – aeolian silty sands (calcareous) – Late Würm (Late glacial s-lm of Würm), 5. lmW3 – Fluvial loams, sandy loams – final Würm (W3), 5a. W3 – Fluvial sands – final (?) Würm (?W3), 6. gW2+3 – Fluvial gravs els, sandy gravels, sands with gravel – Pleniglacial of Würm (W2+3), 7. lW – Aeolian loess and loess loams – Würm (undivided)

opencc-by-4.0Dec 2008View details →

Text-fig. 3 Pollen diagram from the locality of Bohutín. 0-0.01 m – sandy soil mixed with humus, slightly clayey, sample B11; 0.05 m – grey-blue strongly sandy clay, sample B10; 0.10-0.25 m – brown-grey sandy clay with plant remains and mixed with a small amount of peat, sample B9, sample B8 (0.15 m), sample B7 (0.20 m), sample B6 (0.25 m); 0.30-0.35 m – dark sandy clay mixed with peat and plant remains, sample B5, sample B4 (0.35 m); 0.40 m – grey strongly sandy clay mixed with peat, sample B3; 0.45-0.50 m – grey-blue strongly sandy clay, sample B2, sample B1 (0.50 m). in Reconstruction Of Vegetation Development On The Floodplain Of The Litavka River In The Holocene (Central Bohemia, Brdy Mts.)

Text-fig. 3 Pollen diagram from the locality of Bohutín. 0-0.01 m – sandy soil mixed with humus, slightly clayey, sample B11; 0.05 m – grey-blue strongly sandy clay, sample B10; 0.10-0.25 m – brown-grey sandy clay with plant remains and mixed with a small amount of peat, sample B9, sample B8 (0.15 m), sample B7 (0.20 m), sample B6 (0.25 m); 0.30-0.35 m – dark sandy clay mixed with peat and plant remains, sample B5, sample B4 (0.35 m); 0.40 m – grey strongly sandy clay mixed with peat, sample B3; 0.45-0.50 m – grey-blue strongly sandy clay, sample B2, sample B1 (0.50 m).

opencc-by-4.0Aug 2020View details →

Fig. 6 in Herpetofauna diversity in Zamrud National Park, Indonesia: baseline checklist for a Sumatra peat swamp forest ecosystem

Fig. 6. Photos of specimen of Lygosoma samajaya Karin, Freitas, Shonleben, Grismer, Bauer, and Das, 2018 encountered in Zamrud National Park, Riau, Indonesia.

opencc-by-4.0Aug 2020View details →

Fig. 4 in Herpetofauna diversity in Zamrud National Park, Indonesia: baseline checklist for a Sumatra peat swamp forest ecosystem

Fig. 4. Species accumulation curve illustrates the accumulation of the encountered species during the 15 days of field sampling.

opencc-by-4.0Aug 2020View details →

Fig. 3 in Herpetofauna diversity in Zamrud National Park, Indonesia: baseline checklist for a Sumatra peat swamp forest ecosystem

Fig. 3. Eight of the 33 species found in this survey. (A) Limnonectes malesianus; (B) Leptobrachium nigrops; (C) Chalcorana parvaccola; (D) Pulchrana rawa; (E) Gonocephalus liogaster; (F) Cyrtodactylus majulah; (G) Cuora amboinensis; (H) Tropidolaemus wagleri.