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40 results for “peat bogs”
Indicative distribution map for Ecosystem Functional Group TF1.6 Boreal, temperate and montane peat bogs
<p>This archive contains indicative distribution maps and profiles for <strong>TF1.6 Boreal, temperate and montane peat bogs</strong>, a ecosystem functional group (EFG, level 3) of the <a href="https://global-ecosystems.org/">IUCN Global Ecosystem Typology</a> (v2.0). Please refer to Keith <em>et al.</em> (2020) for details.</p> <p>The descriptive profiles provide brief summaries of key ecological traits and processes, maps are indicative of global distribution patterns, and are not intended to represent fine-scale patterns. The maps show areas of the world containing major (value of 1, coloured red) or minor occurrences (value of 2, coloured yellow) of each ecosystem functional group. Minor occurrences are areas where an ecosystem functional group is scattered in patches within matrices of other ecosystem functional groups or where they occur in substantial areas, but only within a segment of a larger region. Given bounds of resolution and accuracy of source data, the maps should be used to query which EFG are likely to occur within areas, rather than which occur at particular point locations. Detailed methods and references for the maps are included in the profile (xml format).</p>
BSRLC+: An annual land cover dataset for the Baltic Sea Region with crop types and peat bogs at 30 m from 2000 to 2022
<p><strong>(NEW) </strong>Baltic Sea Region Land Cover <em>Urban</em> (BSRLC-U) focusing on urban built-up types now available: <a href="https://zenodo.org/records/17347941">https://zenodo.org/records/17347941 </a></p> <p><strong>Baltic Sea Region Land Cover <em>Plus </em>(BSRLC+) </strong>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.</p> <p>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></p> <p>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></p> <p>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>. </p> <p>Traing data and validation data are available: <a href="https://zenodo.org/records/11073291">https://zenodo.org/records/11073291</a></p> <p>This dataset contains:</p> <ul> <li><strong>00_preview.png</strong>: Preview map (2022) of the Baltic Sea region</li> <li><strong>BSRLC_{year}.tif</strong>: Annual map data (30 m) in GeoTIFF format (projection ETRS89 / EPSG:3035)</li> <li><strong>BSRLC_legend.xlss</strong>: Land cover codes and class names</li> <li><strong>BSRLC_qgis_style.qml</strong>: Map style to be used in QGIS</li> <li><strong>BSRLC_arcgis_style.lyrx</strong>: Map style to be used in ArcGIS</li> </ul> <p>Land cover codes (can also be found in <strong>BSRLC_legend.xlss</strong>):</p> <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> <p> </p> <p><strong>Publication (please cite this publication if you are using the dataset):</strong></p> <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. <em>Scientific Data, 11</em>, 1242, <a href="https://doi.org/10.1038/s41597-024-04062-w">https://doi.org/10.1038/s41597-024-04062-w</a></li> </ul> <p> </p> <p><strong>Other related publications:</strong></p> <ul> <li><em>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></em></li> <li><em>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></em></li> </ul> <p> </p> <p><strong>Funding</strong></p> <p>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). </p>
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.
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).
FIG. 1 in Mallomonas teres, sp. nov. (Chrysophyceae), simultaneously revealed in two distant European peat-bog regions
FIG. 1. — Body scales of Mallomonas teres, sp. nov.: A, B, scales observed in a transmission electron microscope; C, a scale observed in a scanning electron microscope. Scale bars: 1 µm.
Data from: Taxonomic and functional turnover are decoupled in European peat bogs
In peatland ecosystems, plant communities mediate a globally significant carbon store. The effects of global environmental change on plant assemblages are expected to be a factor in determining how ecosystem functions such as carbon uptake will respond. Using vegetation data from 56 Sphagnum-dominated peat bogs across Europe, we show that in these ecosystems plant species aggregate into two major clusters that are each defined by shared response to environmental conditions. Across environmental gradients, we find significant taxonomic turnover in both clusters. However, functional identity and functional redundancy of the community as a whole remain unchanged. This strongly suggests that in peat bogs, species turnover across environmental gradients is restricted to functionally similar species. Our results demonstrate that plant taxonomic and functional turnover are decoupled, which may allow these peat bogs to maintain ecosystem functioning when subject to future environmental change.
Vertical Stratification of Peat Pore Water Dissolved Organic Matter composition in a peat bog in Northern Minnesota
<p>Currently peatlands represent a sink for carbon dioxide and source of atmospheric methane. It is unclear the impact that climate change will have on these systems. As such, a large-scale ecosystem manipulation (Spruce and Peatland Responses under Climatic and Environmental Change, SPRUCE) has been implemented at a peat bog (S1 bog) at the Marcel Experimental Forest (MEF), Minnesota, USA, to determine the effects of climatic forcing on ecosystem processes in northern peatlands. In this study, we aimed to: (i) identify peat pore water dissolved organic matter (DOM) composition as a function of depth before the initiation of the manipulation experiment and (ii) contribute to the knowledge of DOM chemistry and decomposition processes at the S1 bog. We found strong vertical resolution in DOM molecular composition and optical properties within the peat column at the S1 bog. Surface samples were dominated by inputs from surface vegetation. The mid-depth, 30-75cm was an area of high reactivity and increased microbial activity with diagenetic formation of many unique compounds such as polycyclic aromatic compounds (PAC) that contain both nitrogen and sulfur heteroatoms. These compounds were previously observed in coal-derived products and were assumed to be responsible for coal’s biological activity. Biological processes taking place at the intermediate depth zone of the peat profile at the S1 bog are assumed to be responsible for the formation of these heteroatomic PAC in our system. Conversely, these compounds might stem from black carbon and nitrogen from potential fires that occurred at the site in the past. Surface and deep DOM exhibited more similar characteristics suggesting the possibility of lateral and vertical advection of pore water from the surface to the deeper horizons. Our results highlight the importance of understanding processes that control DOM production and transformation with depth.</p> <p>Included: FTICR MS data and optical properties data</p>
Fig. 1 in The Diversity And Species Composition Of Water Beetles (Gyrinidae, Dytiscidae, Hydrophilidae) In A Peat Bog In Belarus
Fig. 1. Study area and the sampling places: L — Lakes, H — Hollows, S — Streams.
Data from: Plant–moth community relationships at the degraded urban peat-bog in Central Europe
<p>Peatlands have their own, specific insect fauna. They are a habitat not only for ubiquistic but also stenotopic moths that feed on plants limited to wet, acid and oligotrophic habitats. In the past, raised bogs and fens were widely distributed in Europe. This has changed since 20th c. Due to irrigation, modern forestry and increasing human settlement, peatlands have become isolated islands in agricultural and urban landscape. Here we analyse the flora in a degraded bog situated in a large Lodz city agglomeration in Poland in relation to the diversity and composition of moth fauna. Over the last 40 years since the bog has been protected as a nature reserve, birch, willow and alder shrubs replaced the typical raised bog plant communities due to the decreased water level. The analysis of moth communities sampled in 2012 and 2013 indicates dominance of ubiquistic taxa associated with deciduous wetland forests and rushes. Tyrphobiotic and tyrphophile moth taxa were not recorded. We conclude that the absence of moths typical of bog habitats and the dominance of common, woodland species are associated with hydrological changes, the expansion of trees and brushes over typical bog plant communities and light pollution.</p>
Quantifying the effects sizes of common controls on methane emissions from an ombrotrophic peat bog
<p>Northern wetlands and bogs are a large source of biogenic methane (CH<sub>4</sub>) to the atmosphere and shape climate. There is then substantial interest in quantifying the effect sizes of controls on bog CH<sub>4</sub> emissions. Yet quantification is complicated because wetland emissions are, like the controls that regulate them, spatially and temporarily heterogeneous within individual wetland systems. To account for this heterogeneity, we established 55 measurement plots in a sampling design that had extensive spatial, and repeated temporal, coverage over one ombrotrophic bog. This coverage allowed us to robustly estimate the effect sizes of known environmental controls on CH<sub>4</sub> emissions such as temperature, water table depth (WTD), and plant functional composition. As expected, 89% of the cumulative measured flux came from 16% of the plots, with consistently high CH<sub>4</sub> emissions over two consecutive growing seasons. Soil temperature exhibited the strongest control on emissions, while WTD and vegetation composition had much smaller relative effects compared to temperature. Interestingly, at high temperatures, WTD was a strong determinant of whether a plot had high vs. lower emissions. Despite temperature's large effect size, the controls we measured only explained ~29% of the variance in CH<sub>4</sub> fluxes. Overall, our data confirm observations from other wetlands that CH<sub>4</sub> emissions are highly variable at local scales, and yet our data also reveal that effect sizes can be quantified robustly within this heterogeneity. Highly-replicated, local designs may therefore be useful for generating data that can serve to help refine wetland CH<sub>4</sub> emissions uncertainties.</p>
Data from: Taxonomic and functional turnover are decoupled in European peat bogs
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Quantifying the effects sizes of common controls on methane emissions from an ombrotrophic peat bog
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Data from: Plant–moth community relationships at the degraded urban peat-bog in Central Europe
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FIGURE 6 in A new Paraleptamphopidae (Crustacea Amphipoda) in the burrow of Virilastacus rucapihuelensis (Parastacidae) and surrounding peat bogs. Rudolphia macrodactylus n. gen., n. sp. from southern South America
FIGURE 6. Most parsimonious cladogram from analysis of 36 morphological characters of 8 taxa: Rudolphia macrodactylus, Falklandella obtusa, Praefalklandella cuspidata, Paraleptamphopus subterraneus, Ringanui koonuiroa, Austrogammarus telsosetosus, Pilbarus millsi, and Sternophysinx calceola., with synapomorphies.
FIGURE 3. Rudolphia macrodactylus n in A new Paraleptamphopidae (Crustacea Amphipoda) in the burrow of Virilastacus rucapihuelensis (Parastacidae) and surrounding peat bogs. Rudolphia macrodactylus n. gen., n. sp. from southern South America
FIGURE 3. Rudolphia macrodactylus n. sp., a–e: Holotype male, peraeopods. a: P3; b: P4; c: P5; d: P6; e: P7. f: Paratype female, P4 with coxal gill and oostegite. Scale= 0.2 mm.
FIGURE 5. Rudolphia macrodactylus n in A new Paraleptamphopidae (Crustacea Amphipoda) in the burrow of Virilastacus rucapihuelensis (Parastacidae) and surrounding peat bogs. Rudolphia macrodactylus n. gen., n. sp. from southern South America
FIGURE 5. Rudolphia macrodactylus n. sp. male 5.2 mm. Scanning electron micrographs of calceoli on A1. a: concave surface; b: convex surface. Scale= 10 Μm.
FIGURE 2. Rudolphia macrodactylus n in A new Paraleptamphopidae (Crustacea Amphipoda) in the burrow of Virilastacus rucapihuelensis (Parastacidae) and surrounding peat bogs. Rudolphia macrodactylus n. gen., n. sp. from southern South America
FIGURE 2. Rudolphia macrodactylus n. sp. Holotype male. a: right Mx1; b: left Mx1; c: Mx2; d: distal margin of inner lobe Mx2; e: Mxp; f: Gn1; g: Gn2. Scale= 0.1 mm.
FIGURE 4. Rudolphia macrodactylus n in A new Paraleptamphopidae (Crustacea Amphipoda) in the burrow of Virilastacus rucapihuelensis (Parastacidae) and surrounding peat bogs. Rudolphia macrodactylus n. gen., n. sp. from southern South America
FIGURE 4. Rudolphia macrodactylus n. sp. Holotype male. a: Pl 1; b: Pl 2; c: Pl 2 last setae of exopodite; d: Pl 3; e: Ur1; f: Ur2; g: Ur3; h; Telson.
FIGURE 1. Rudolphia macrodactylus n in A new Paraleptamphopidae (Crustacea Amphipoda) in the burrow of Virilastacus rucapihuelensis (Parastacidae) and surrounding peat bogs. Rudolphia macrodactylus n. gen., n. sp. from southern South America
FIGURE 1. Rudolphia macrodactylus n. sp. a: Allotype female 5.8 mm, habitus. b–h: Holotype male. b: A1; c: A1 inner flagellum; d: A2; e: labrum; f: right Md; g: left Md; h: labium.
Water level near peat extraction site Nida bog, Latvia
<p>Data set for the water level monitoring near peat exgtraction site at Nida bog, Latvia</p>
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