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785 results for “Boreal”
Perry et al. (2025) Data Package: Effects of diluted bitumen and remediation methods on lower trophic levels within boreal lake enclosures. Data were collected during 2019 at the IISD Experimental Lakes Area in Northwestern Ontario.
This data package corresponds to a research study by Perry et al. (2025) titled "The effects of diluted bitumen, the shoreline cleaner Corexit EC9580A, and bio-stimulation on the lower food web of a boreal lake, with a focus on natural phytoplankton communities." The study examines the effect of controlled spills of diluted bitumen and two remediation methods on lower trophic levels (phytoplankton, periphyton, zooplankton). The study was undertaken within shoreline enclosures within Lake 260 at the IISD Experimental Lakes Area during 2019. In addition to primary oil recovery using sorbent pads, the two secondary remediation methods: 1) enhanced monitoring natural recovery (eMNR) that included the biostimulation of microbial communities via a slow release nutrient fertilizer, and 2) a shoreline washing agent (SWA or SCA; Corexit 9580) used to increase oil removal from affected shorelines. This data package includes the response of perphyton and zooplankton.
Particle concentration data from: Long-term measurement of sub-3nm particles and their precursor gases in the boreal forest
<p>The knowledge of the dynamics of sub-3nm particles in the atmosphere is crucial for our understanding of first steps of atmospheric new particle formation. Therefore, accurate and stable long-term measurements of the smallest atmospheric particles are needed. In this study, we analyzed over five years of particle concentrations in size classes 1.1–1.7 nm and 1.7–2.5 nm obtained with the Particle Size Magnifier (PSM) and three years of precursor vapor concentrations measured with the Chemical Ionization Atmospheric Pressure Interface Time-of-Flight mass spectrometer (CI-APi-ToF) at the SMEAR II station in Hyytiälä, Finland. The results show that the 1.1–1.7 nm particle concentrations have a daytime maximum during all seasons, which is due to increased photochemical activity. There are significant seasonal differences in median concentrations of 1.7–2.5 nm particles, underlining the different frequency of new particle formation between seasons. Aerosol precursor vapors have notable diurnal and seasonal differences as well. Sulfuric acid and highly oxygenated organic molecule (HOM) monomer concentrations have clear daytime maxima, while HOM dimers have their maxima during the night. HOM concentrations for both monomers and dimers are the highest during summer and the lowest during winter. Higher median concentrations during summer result from increased biogenic activity in the surrounding forest. Sulfuric acid concentrations are the highest during spring and summer, with autumn and winter concentrations being two to three times lower. A correlation analysis between the sub-3nm concentrations and aerosol precursor vapor concentrations indicates that HOMs, particularly their dimers, and sulfuric acid play a significant role in new particle formation in the boreal forest. Our analysis also suggests that there might be seasonal differences in new particle formation pathways that need to be investigated further. </p> <p> </p>
Dataset on surface peat stoichiometry and physical properties in boreal undrained peatlands in Finland, Natural Resources Institute Finland (Luke) and Geological Survey of Finland (GTK)
<p><strong>Dataset on surface peat stoichiometry and physical properties in boreal undrained peatlands in Finland </strong></p><p><strong>Creators: </strong>Larmola T, Anttila J, Turunen J, Laine-Petäjäkangas A, Ovaskainen J, Laatikainen M </p><p>The dataset consists of peat properties in a subset of 16 undrained peatland sites (32 peat samples) in Geological Survey of Finland (GTK) national peatland inventory. These sites were sampled between 2002 and 2017 and the subset selected from GTK peat sample archives. These 16 sites represented two pine-<i>Sphagnum-</i> dominated site types (IR, KR) and two treeless sedge fen types (VSN, RhSN) all in 4 replicates and sampled in 2 depths 20-40, 40-60cm). </p><p><strong>Peat analyses</strong> The peat samples were analyzed for C:H:N:S and ash concentration with Leco 628 CHNS analyzer following standard SFS EN13039 with FINAS accredited adjustments JOK3023. The dry matter content was analyzed after drying the sample at 105 ℃ and ash content based on loss on ignition at 550 ℃. The O concentration was determined by difference: %O = 100 - % (ash + total C + N + H + S).</p><p><strong>Stoichiometric calculations</strong>The O concentration was determined by difference: %O = 100 - % (ash + total C + N + H + S). Atomic ratios of C:N, H:C and O:C were calculated based on the individual sample mass values. The C oxidation state (Cox), the oxidative ratio (OR), and the degree of unsaturation (DU) were calculated following equations in the study by Masiello et al. (2008). The analyses are described in more detail in Turunen et al. (manuscript). </p><p>Related datasets used in the same publication are:</p><p>Larmola T, Anttila J, Alm J Dataset on surface peat stoichiometry and physical properties in boreal forestry-drained peatlands in Finland</p><p>Turunen J. (2023). Surface peat data, Geological Survey of Finland (Version 1) [Data set]. Zenodo. <a href="https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fdoi.org%2F10.5281%2Fzenodo.8434148&data=05%7C01%7Cluke.tuula.larmola%40valtion.mail.onmicrosoft.com%7Cc48ffad4c0e341d0fa5808dbcaff0289%7C7c14dfa4c0fc47259f0476a443deb095%7C0%7C0%7C638326968887189768%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=AyYOxR7Mas2ef8y3wI7oCrzHWSyqBzt%2FJB0CMN%2BJUiU%3D&reserved=0">https://doi.org/10.5281/zenodo.8434148</a></p><p> </p><p><strong>Data column description </strong></p><p>ID - Site identifier</p><p>site - undrained peatland (UDP) for all rows</p><p>ncoord - North coordinate (latitude), degrees.</p><p>depth - Sampling depth. 20: 0-20 cm, 40: 20-40cm, 60: 40-60cm.</p><p>type - Site type classification according to the Finnish peatland site type system.</p><p>origin - UDP site type. I: treed peatland (peat typically Sphagnum-wood), II: treeless peatland (or sparsely treed, peat typically Sphagnum-sedge)</p><p>type_num - Nutrient level according to site type. 1 is the most nutrient rich and 4 is the least.</p><p>Cmol - Molar carbon concentration in the sample</p><p>Hmol - Molar hydrogen concentration in the sample</p><p>Nmol - Molar nitrogen concentration in the sample</p><p>Omol - Molar oxygen concentration in the sample</p><p>Smol - Molar sulphur concentration in the sample</p><p>bd - Bulk density, kg/m3</p><p>cox - C oxidation state</p><p>or - Oxidative ratio</p><p>du - Degree of unsaturation</p><p>hc - H:C ratio</p><p>cn - C:N ratio</p><p>oc - O:C ratio</p><p><strong>References</strong></p><p>Masiello CA, Gallagher ME, Randerson JT, Deco RM, Chadwick OA (2008) Evaluating two experimental approaches for measuring ecosystem carbon oxidation state and oxidative ratio, Journal of Geophysical Research 113, G03010, <a href="https://doi.org/10.1029/2007JG000534">https://doi.org/10.1029/2007JG000534</a></p><p>Turunen J, Anttila J, Laine-Petäjäkangas A, Ovaskainen J, Laatikainen M, Alm J, Larmola T 2023. Impacts of forestry drainage on surface peat stoichiometry and physical properties in boreal peatlands in Finland. <i>manuscript.</i></p>
Dataset on surface peat stoichiometry and physical properties in boreal forestry-drained peatlands in Finland, Natural Resources Institute Finland
<p><strong>Dataset on surface peat stoichiometry and physical properties in boreal forestry-drained peatlands in Finland</strong></p><p><strong>Creators: Larmola T, Anttila J, Alm J </strong></p><p>The dataset consists of peat properties in a subsample of 30 drained peatland forests in Finland selected from the permanent sample plots of the 8th National Forest Inventory (systematic sample of plots on drained peatland forests, e.g., Hotanen et al. 2006). The subsample included equally different site types of forestry-drained peatlands of those parts of Finland where drainage for forestry is economically viable (Latitude 60-66 ºN, annual temperature sum > 750 dd). </p><p><strong>The site selection criteria</strong> were average peat layer thickness of over 20 cm, no clear-cut areas, site drained before 1995 and ditching had detectably altered hydrology or vegetation. <strong>Peat analyses</strong> Finnish Forest Research Institute (now Natural Resources Institute Finland) sampled peat cores with a box corer in 2002, samples were analysed for bulk density, archived and remaining samples at depths 20-30, 30-40 cm (total of 58) were analysed in 2021. The peat samples were analyzed for C:H:N:S and ash concentration with Leco 628 CHNS analyzer following standard SFS EN13039 with FINAS accredited adjustments JOK3023. The dry matter content was analyzed after drying the sample at 105 ℃ and ash content based on loss on ignition at 550 ℃. </p><p><strong>Stoichiometric calculations</strong>The O concentration was determined by difference: %O = 100 - % (ash + total C + N + H + S). Atomic ratios of C:N, H:C and O:C were calculated based on the individual sample mass values. The C oxidation state (Cox), the oxidative ratio (OR), and the degree of unsaturation (DU) were calculated following equations in the study by Masiello et al. (2008). The analyses are described in more detail in Turunen et al. (manuscript). </p><p>Related datasets used in the same publication are:</p><p>Larmola, T. Anttila J, Turunen J, Laine-Petäjäkangas A, Ovaskainen J, Laatikainen M Dataset on surface peat stoichiometry and physical properties in boreal undrained peatlands in Finland, Natural Resources Institute Finland (Version 1) [Dataset]. Zenodo. doi.org/<strong>10.5281/zenodo.10068486</strong></p><p>Turunen J. (2023). Surface peat data, Geological Survey of Finland (Version 1) [Data set]. Zenodo. <a href="https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fdoi.org%2F10.5281%2Fzenodo.8434148&data=05%7C01%7Cluke.tuula.larmola%40valtion.mail.onmicrosoft.com%7Cc48ffad4c0e341d0fa5808dbcaff0289%7C7c14dfa4c0fc47259f0476a443deb095%7C0%7C0%7C638326968887189768%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=AyYOxR7Mas2ef8y3wI7oCrzHWSyqBzt%2FJB0CMN%2BJUiU%3D&reserved=0">https://doi.org/10.5281/zenodo.8434148</a></p><p> </p><p><strong>Data column description</strong></p><p>ID - Site identifier</p><p>site - Forestry-drained peatland (FDP) for all rows</p><p>ncoord - North coordinate (latitude), degrees.</p><p>depth - Sampling depth. 30: 20-30 cm, 40: 30-40cm, avg: average of both depths.</p><p>type - Site type classification according to the Finnish peatland site type system.</p><p>origin – Origin of the FDP site type at undrained state. I: treed peatland (peat typically Sphagnum-wood), II: treeless peatland (or sparsely treed, peat typically Sphagnum-sedge)</p><p>type_num - Nutrient level according to site type. 1 is the most nutrient rich and 4 is the least.</p><p>Cmol - Molar carbon concentration in the sample</p><p>Hmol - Molar hydrogen concentration in the sample</p><p>Nmol - Molar nitrogen concentration in the sample</p><p>Omol - Molar oxygen concentration in the sample</p><p>Smol - Molar sulphur concentration in the sample</p><p>bd - Bulk density, kg/m3</p><p>cox - C oxidation state</p><p>or - Oxidative ratio</p><p>du - Degree of unsaturation</p><p>hc - H:C ratio</p><p>cn - C:N ratio</p><p>oc - O:C ratio</p><p>n - Number of samples. 2 for averages from both depths, 1 for all other rows.</p><p> </p><p><strong>References</strong></p><p>Hotanen JP, Maltamo M, Reinikainen A (2006) Canopy stratification in peatland forests in Finland. Silva Fennica 40:53–82.</p><p>Masiello CA, Gallagher ME, Randerson JT, Deco RM, Chadwick OA (2008) Evaluating two experimental approaches for measuring ecosystem carbon oxidation state and oxidative ratio, Journal of Geophysical Research 113, G03010, <a href="https://doi.org/10.1029/2007JG000534">https://doi.org/10.1029/2007JG000534</a></p><p>Turunen J, Anttila J, Laine-Petäjäkangas A, Ovaskainen J, Laatikainen M, Alm J, Larmola T 2023. Impacts of forestry drainage on surface peat stoichiometry and physical properties in boreal peatlands in Finland. <i>manuscript.</i></p><p> </p>
Arctic-boreal bryophyte dynamics since the last glacial from ancient DNA metabarcoding
<p>A total of 26 lake-sediment cores collected from 26 study sites spanning the glacial and interglacial transition are used in this study. These sites are distributed across Siberia, Beringia, and Alaska regions, with a gradient of vegetation types dominated by tundra in the northern region and transitioning to boreal forest in the southern extents. DNA samples from the sediment core were analysed with a standard sedimentary ancient DNA metabarcoding pipeline (see additional description), which resulted in a raw dataset of all DNA plant sequences, which were then filtered for Bryophytes (Bryophyte DNA dataset). The Bryophyte DNA dataset contains 120 unique ASV. Samples in the Bryophyte DNA dataset are then grouped into 1000-year time slices and are subsequently resampled to a base count of 500 read counts for each time slice. After that, a Bryophyte trait datastet is assigned to the Bryophyte DNA dataset. </p> <p> </p> <h3>Input files</h3> <ul> <li><strong>Excel file with all data used in the R-Script:</strong> "Bryophytes_data.xlsx"</li> <li><strong>WorldClim 2.0 dataset with mean temperatures of Warmest Quarter</strong> (https://www.worldclim.org/; Fick, S.E. and R.J. Hijmans, 2017. WorldClim 2: new 1km spatial resolution climate surfaces for global land areas. <a href="https://rmets.onlinelibrary.wiley.com/doi/abs/10.1002/joc.5086">International Journal of Climatology 37 (12): 4302-4315</a>): "wc2.1_30s_bio_10.tif"</li> </ul> <h3>R script</h3> <ul> <li><strong>R-Script:</strong> "2025-01-14_R-Script_ arctic_boreal_bryophyte_dynamics_DNA_metabarcoding.R"</li> </ul> <h3>R outputs</h3> <ul> <li><strong>resampled Bryophyte metabarcoding percentage dataset with ASV:</strong> "2025-01-14_bryophyta_resampled_percentages_mean_100runs_sequences.csv"</li> <li><strong>resampled Bryophyte metabarcoding percentage dataset with unique scientific names: </strong>"2025-01-14_bryophyta_resampled_percentages_mean_100runs_scientific_names.csv"</li> <li><strong>GBIF taxa occurrences with WorldClim temperature data: </strong>"2025-01-14_gbif_taxa_occurrences_seqtypes_climate.csv"</li> </ul> <p> </p>
Phenology of flowers and leaves following experimental warming in the initiation and maturation years for 7 understory boreal plants at the Bonanza Creek Long Term Ecological Research (BNZ LTER) site in Interior Alaska: 2017-2019
This dataset contains the results of experimental warming of flower and leaf buds for 7 understory boreal plants: Rhododendron groenlandicum, Rosa acicularis, Rubus chamaemorus, Shepherdia canadensis, Viburnum edule, Vaccinium uliginosum, and Vaccinium vitis-idaea. Plants in two cohorts were subjected to one of four treatments: warming in the initiation year (the year prior to flowering or leaf-out) only, warming in the maturation year (the year of flowering or leaf-out) only, warming in both years, or no warming (controls). The timing of flowering (both cohorts) and leaf-out (usually one cohort) was monitored. We also tracked developmental stages of the flower bud primordia using repeated desctructive sampling followed scanning electron microscopy throughout the initiation years. Environmental data associated with the plots, including air temperature throughout the summer, soil temperature and depth of ground thaw in late May, and canopy cover, are also reported.
Nutrient Limitation of Algal Biomass in Boreal Streams located near the Bonanza Creek LTER in Fairbanks, Alaska - Summer 2022
This dataset contains estimates of chlorophyll-a accumulated on nutrient-diffusing substrata during ~21 d incubation in each of nine streams located in the interior of Alaska near Fairbanks.
AIRBORNE SPECTROMETER MEASUREMENTS FMOM BOREAL SNOW-COVERED LANDSCAPE
<p>The dataset contains 10 meter resolution reflectance data from boreal snow-covered landscape. The purpose of the airborne measurements was to investigate the effect of forest canopy on optical remote sensing signals for snow-covered surfaces. The hyperspectral airborne data was acquired with an AisaDUAL imaging spectrometer on March 18 and on March 21, 2010 in Sodankylä, Finland. The image swath was 240 meters and flight lines were several kilometers long. The original spatial resolution of the data is 80 cm x 80 cm, but it was resampled to pixel size of 10 m x 10 m. All measurements were carried out in non-cloudy conditions (0/8 to 2/8 cloud cover). On 18 March, the tree canopy was snow-free and snow on the ground was several days old, while on 21 March, the tree canopy was snow-covered and snow on ground was fresh. The data contains mosaics of the flight lines for the bands 555 nm, 645 nm, 858.5 nm and 1640 nm for both days 18 March 2010 and 21 March 2010.</p>
AIRBORNE SPECTROMETER MEASUREMENTS FROM BOREAL AND TUNDRA SITE DURING SPRING SNOW MELT
<p>The dataset contains 10 meter resolution reflectance data from boreal and tundra sites during spring snow melt. The purpose of the airborne measurements was to investigate the effect of forest canopy and snow melting on optical remote sensing signals at the very end of melting period. The hyperspectral airborne data was acquired with an AisaDUAL imaging spectrometer on 5 May 2011 in Sodankylä and in Saariselkä, Finland. Saariselkä is a fell region and partly represents open tundra. The image swath was 240 meters and flight lines were several kilometers long. The original spatial resolution of the data is 80 cm x 80 cm, but it was resampled to pixel size of 10 m x 10 m. Snow depth was between 0 cm and 30 cm at the Sodankylä site and between 0 cm and 60 cm at the Saariselkä site implying that the spring melt was clearly more advanced in Sodankylä. Additionally, more snow-free pixels were found at Sodankylä than Saariselkä. During the measurements the sky was cloudless in Sodankylä (cloud cover 0/8) and cloudy (cloud cover 7/8) in Saariselkä. The data contains mosaics of the flight lines for the bands 555 nm, 645 nm, 858.5 nm and 1640 nm for both study sites.</p>
Mast-borne spectral reflectance measurements of boreal landscape during spring
<p>This dataset contains mast-borne spectral reflectance measurements (350-2500 nm / 350-1000 nm) measured with an ASD Field Spec Pro JR spectroradiometer and digital images of the measurement areas from the time of the measurements. The measurement targets are a boreal sparse pine forest and a forest opening located at the premises of the Arctic Space Centre of the Finnish Meteorological Institute in Sodankylä, northern Finland (N67.361833, E26.634154, WGS84).</p> <p>The dataset covers spring time periods during years 2010-2018 from the dry snow period until some time after the snow disappearance. The temporal coverage vary from year to year depending on the mounting date and due to technical problems. Measurements have been conducted every 30 min during fixed day-time period and based on set weather threshold values.</p> <p>The spectral reflectance data are organized in yearly CSV files the metadata information attached in the file header. Accordingly, the digital images from the measurement areas are organized in yearly folders and packed into zip files.</p> <p>For this version a data example plot (Data_example_mast.png) was added to have a quick visualisation of the sort of the data available.</p> <p>For further information contact Henna-Reetta Hannula (henna-reetta.hannula@fmi.fi) or Kirsikka Heinilä (kirsikka.heinila@ymparisto.fi)</p>
Tree ring width chronologies of four Pinaceae species in boreal forests in Yakutia in 2018
<p>Tree cores and discs were collected during fieldwork in Yakutia in 2018 by scientists from Alfred Wegener Institute (AWI), Helmholtz Centre for Polar and Marine Research and University of Potsdam, Germany, The Institute for Biological problems of the Cryolithozone, Russian Academy of Sciences, Siberian branch, and The Institute of Natural Sciences, North-Eastern Federal University of Yakutsk, Yakutsk, Russia (Kruse et al., 2019). The samples were dried, sanded, digitized and further processed by identifying the ring layers end exporting the tree ring width for each year. The site chronologies were established by cross-dating all samples to each other, which helped coping with small ring sizes but especially with missing rings, and frost rings.<br> We processed samples of four species, <em>Larix gmelinii </em>(LAGM), <em>Picea obovata </em>(PIOB), <em>Pinus sylvestris </em>(PISY) and <em>Pinus sibirica </em>(PISI). These were recorded at a variety of locations:</p> <ul> <li>LAGM from Lake Khamra sites EN18079, -80, -81, -83 (N59.974919° E112.958985°, N59.977106° E112.961379°, N59.970583° E112.987096°, N59.974714° E113.002874°)</li> <li>PIOB from Lake Khamra sites EN18079, -81, -83 (59.974919° E112.958985°, 59.970583° E112.987096°, 59.974714° E113.002874°)</li> <li>PISI from Lake Khamra site EN18080 (N59.977106° E112.961379°)</li> <li>PISY from different sites between EN18061 (N62.076376° E129.618586°) and EN18077 (N61.892568° E114.288623°)</li> </ul> <p><strong>Data format</strong><br> The data consists of one file in dendrochronological TUCSON format without header for each of the four tree species.</p> <p><strong>Additional information</strong><br> This data is linked to further information about individual trees and their sites as published in: van Geffen, Femke; Schulte, Luise; Geng, Rongwei; Heim, Birgit; Pestryakova, Luidmila A; Herzschuh, Ulrike; Kruse, Stefan (2021): Tree height and crown diameter during fieldwork expeditions that took place in 2018 in Central Yakutia and Chukotka, Siberia. PANGAEA, https://doi.pangaea.de/10.1594/PANGAEA.932817<br> and an extension to: Shevtsova, Iuliia; Kruse, Stefan; Herzschuh, Ulrike; Brieger, Frederic; Schulte, Luise; Stuenzi, Simone Maria; Pestryakova, Luidmila A; Zakharov, Evgenii S (2020): Individual tree and tall shrub partial above-ground biomass of central Chukotka in 2018. PANGAEA, https://doi.org/10.1594/PANGAEA.923784<br> Information about the expedition in 2018 in: Kruse, Stefan; Bolshiyanov, Dimitry Yu; Grigoriev, Mikhail N; Morgenstern, Anne; Pestryakova, Ludmila A; Tsibizov, Leonid; Udke, Annegret (2019): Russian-German Cooperation: Expeditions to Siberia in 2018. Berichte zur Polar- und Meeresforschung = Reports on Polar and Marine Research, 734, 257 pp, https://doi.org/10.2312/BzPM_0734_2019</p> <p> </p>
Individual tree aboveground biomass of four Pinaceae species in boreal forests in Yakutia in 2018
<p>Samples to estimate aboveground tree biomass for four boreal forest species (<em>Larix gmelinii</em>, <em>Picea obovata</em>, <em>Pinus sylvestris</em>, <em>Pinus sibirica</em>) were collected during fieldwork in Yakutia in 2018 by scientists from Alfred Wegener Institute (AWI), Helmholtz Centre for Polar and Marine Research and University of Potsdam, Germany, The Institute for Biological problems of the Cryolithozone, Russian Academy of Sciences, Siberian branch, and The Institute of Natural Sciences, North-Eastern Federal University of Yakutsk, Yakutsk, Russia (Kruse et al., 2019). From each of the visited site, three living trees (a small, a medium-sized and the talles tree) per each site were cut down after estimating the quantity of the different types to be sampled, namely branches, needles, cones, making up the tree. Further, to estimate the stem weight, tree discs were taken. The discs were taken at the base of a tree (0 cm, disc A), breast height (130 cm, disc B) and top/close to the top of a tree (260 cm, disc C). If the tree was small with <1.3 m, its stem is included as woody biomass in the branch sample. To estimate each tree's stem biomass, the stem was assumed to have a cone shape. Dead trees were also sampled, if present. All harvested samples were weighed fresh in the field and subsampled. The dry weight of all subsamples was recorded after oven drying (60 °C, 48 h for needle and branch samples, up to one week for tree stem discs). A detailed protocol for total tree and shrub AGB estimation can be found in Shevtsova, et al. (2020).</p> <p><strong>Data format</strong><br> The data consists of one table for each of the four species. The columns (N=13) contain the follwoing information:<br> 1. TreeDataBaseID -> unique Tree Data Base identifier of the individual<br> 2. Site -> Sampling site name<br> 3. SampleID -> Field name given to the individual<br> 4. Species -> Species name<br> 5. Height_cm -> Height of the tree individual in cm<br> 6. Vitality -> Estimate of the vitality state in 6 levels, ++ very good, + good, 0 mediocre, - bad, -- very bad, dead<br> 7. NeedleWeight_g -> Dry weight of needles in g<br> 8. StemWeight_g -> Dry weight of the stem in g<br> 9. BiomassBranchStatus -> 1 if branches are present and included in the biomass estimate or not<br> 10. TotalWeightNonStem_g -> Dry weight of all parts but the stem, which are needles, branches and cones in g<br> 11. DiameterBasal_cm -> Stem diameter at tree stem base (0 cm above ground) in cm<br> 12. DiameterBreast_cm -> Stem diameter at breast height (130 cm above ground) in cm<br> 13. CrownDiameter_cm -> Mean crown diameter in cm</p> <p><strong>Additional information</strong><br> This data is linked to further information about individual trees and their sites as published in: van Geffen, Femke; Schulte, Luise; Geng, Rongwei; Heim, Birgit; Pestryakova, Luidmila A; Herzschuh, Ulrike; Kruse, Stefan (2021): Tree height and crown diameter during fieldwork expeditions that took place in 2018 in Central Yakutia and Chukotka, Siberia. PANGAEA, https://doi.pangaea.de/10.1594/PANGAEA.932817<br> Information about the expedition in 2018 in: Kruse, Stefan; Bolshiyanov, Dimitry Yu; Grigoriev, Mikhail N; Morgenstern, Anne; Pestryakova, Ludmila A; Tsibizov, Leonid; Udke, Annegret (2019): Russian-German Cooperation: Expeditions to Siberia in 2018. Berichte zur Polar- und Meeresforschung = Reports on Polar and Marine Research, 734, 257 pp, https://doi.org/10.2312/BzPM_0734_2019<br> Aboveground estimation protocol and further data in: Shevtsova, Iuliia; Kruse, Stefan; Herzschuh, Ulrike; Brieger, Frederic; Schulte, Luise; Stuenzi, Simone Maria; Pestryakova, Ludmila A; Zakharov, Evgenii S (2020): Total above-ground biomass of 39 vegetation sites of central Chukotka from 2018. PANGAEA, https://doi.org/10.1594/PANGAEA.923719</p>
Indicative distribution map for Ecosystem Functional Group T2.1 Boreal and temperate high montane forests and woodlands
<p>This archive contains indicative distribution maps and profiles for <strong>T2.1 Boreal and temperate high montane forests and woodlands</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>
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>
Indicative distribution map for Ecosystem Functional Group TF1.7 Boreal and temperate fens
<p>This archive contains indicative distribution maps and profiles for <strong>TF1.7 Boreal and temperate fens</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>
Snowpack temperature profile dataset from a boreal forest watershed in eastern Canada.
<p>This dataset presents snow temperature profiles from nine different boreal forest sites in eastern Canada collected over two consecutive winters, 2016-17 and 2017-18. The dataset includes snowpack temperature profiles, snow depth, air temperature, and soil temperature. In addition, the two flux towers provided us with the additional heat and water vapour fluxes. We also present data extracted from intensive snow coring and snowpit surveys, conducted on a weekly and bi-weekly basis. Additionally, stable water isotope data collected from individual snowpack are presented here. </p> <p>To learn more about the additional information about the data, please read the "Readme.txt" file. </p>
Simulations for: The anthropogenic imprint on temperate and boreal forest demography and carbon turnover
<p>LPJ-GUESS model output underlying analysis in:<br> Thomas A. M. Pugh, Rupert Seidl, Daijun Liu, Mats Lindeskog, Louise P. Chini, Cornelius Senf, The anthropogenic imprint on temperate and boreal forest demography and carbon turnover, Global Ecology and Biogeography. 10.1111/geb.13773</p> <p>For a full description of the simulations, please refer to the above paper. If using the data please cite this dataset and the publication above.</p> <p>Files are provided as netcdf4 files. Basic metadata is included in the headers of the individual files.</p> <p># Simulation types<br> _standard_nat_2014 -> Best estimate simulation under natural disturbance. Averaging period 2001-2014<br> _high_nat_2014 -> Upper estimate simulation under natural disturbance. Averaging period 2001-2014<br> _low_nat_2014 -> Lower estimate simulation under natural disturbance. Averaging period 2001-2014<br> _standard_nat_1990 -> Best estimate simulation under natural disturbance. Averaging period 1961-1990<br> _standard_natcc_2014 -> Best estimate simulation based on closed-canopy forest area calculations under natural disturbance. Averaging period 2001-2014<br> _standard_anthro_2014 -> Best estimate simulation under natural and anthropogenic disturbance. Averaging period 2001-2014<br> _high_anthro_2014 -> Upper estimate simulation under natural and anthropogenic disturbance. Averaging period 2001-2014<br> _low_anthro_2014 -> Lower estimate simulation under natural and anthropogenic disturbance. Averaging period 2001-2014<br> _site_recovery_Eurasia_nodist -> Site simulations for 4 Eurasian sites looking at the successional sequence. 800 years long under constant spinup environmental conditions.<br> _site_recovery_America_nodist -> Site simulations for 5 North American sites looking at the successional sequence. 800 years long under constant spinup environmental conditions.</p> <p># Variables (for units see netcdf metadata)<br> Cveg -> Live vegetation carbon<br> Clitter -> Litter carbon<br> Csoil -> Soil carbon<br> LAI -> Leaf area index<br> NPP -> Net primary productivity<br> GPP -> Gross primary productivity<br> distprob -> Natural disturbance probability<br> age -> Stand age structure<br> temprange -> Annual temperature range (based on monthly means)<br> wooddensity -> community mean wood density</p> <p>Note:<br> All nat simulations assume that forest covers the whole grid cell.<br> All anthro simulations assume that forest only covers the primary and secondary fractions of the grid cell, as defined in the LUH2 dataset, however values are given relative to the whole grid cell. I.e. value_on_forest_area * (primary_area_fraction+secondary_area_fraction).</p>
Sherbo et al. 2023 Data Package. Data associated with study assessing effects of dissolved organic matter on phytoplankton productivity in boreal lakes. The majority of data was collected in 2018 at the IISD Experimental Lakes Area in Northwestern Ontario
Allochthonous dissolved organic matter (DOM) structures many physical, chemical, and biological properties of lakes, including key variables that control productivity at the base of freshwater food webs. We examined phytoplankton biomass and productivity and their drivers, across eight pristine boreal lakes with DOM ranging from 3.5 to 9.5 mg DOC L-1. Increases in DOM were associated with significant increases in epilimnetic nitrogen, phosphorus and chlorophyll a (Chl a) concentrations suggesting that nutrients associated with DOM stimulate phytoplankton biomass and productivity. Such results were misleading; there was no significant relationship between Chl a and phytoplankton biomass measured via microscopy, and results did not incorporate the effects of DOM on thermocline and euphotic depth. Chl a:biomass and Chl a: carbon ratios indicated that increases in Chl a with DOM were driven by photo-acclimation to declining light availability. Increases. Further, increases in DOM led to large declines in thermocline (~50 %) and euphotic (~75 %) depths, and depth-integrated phytoplankton biomass and primary production (~70 %).
Effect of Restoration on Physical and Chemical Peat Properties in Previously Drained Boreal Peatlands, latitude 57-63, Sweden, 2021
The major objective behind peatland restoration is to improve ecosystem services, such as increased biodiversity, increased carbon sequestration, increased groundwater storage, and improved surface water quality. However, a century or more of drained conditions has drastically changed the soil properties in relation to natural wetlands and this is likely to profoundly influence the potential for various biogeochemical peat processes. Thus, peatland restoration may result in undesired impacts and potential environmental threats. Two such undesired effects are increased methane production and increased mercury methylation. In this study, we investigated how nine boreal peatlands across a latitudinal gradient in Sweden have been affected by rewetting after up to a century of drained conditions. Each peatland was sampled for three 50 cm deep peat cores that were analyzed for carbon, nitrogen, δ13C, δ15N, bulk density, and organic matter proportion. Adjacent to each restored peatland, we sampled a corresponding pristine (natural) peatland to facilitate a comparison of how the peat properties have been affected by drainage and subsequent rewetting of the peatlands. Groundwater depth was monitored at all peatland locations to confirm restored conditions at the rewetted peatlands. The results indicate that a long period of drained conditions and subsequent rewetting have changed the peat properties, with differences shown in C/N ratio, dry bulk density, and organic matter content. Rewetting will thus not regenerate a pristine environment. Instead, it creates new conditions to which various biogeochemical processes will respond and these do not necessarily represent conditions prior to disturbance. Our study will provide background information to understand the biogeochemical dynamics in peatlands after restoration, especially since the study covers a large span of nutrient conditions and catchment settings. This understanding will be fundamental for the development of strat
Composition and biolability of dissolved organic matter from arctic and boreal streams April 2015 - May 2016
In this study, we collected samples throughout the year from up to eight streams along an arctic-boreal gradient in interior Alaska, ranging from discontinuous to continuous permafrost. We measured dissolved organic matter (DOM) biolability and nutrient limitation of decomposition through laboratory incubations of streamwater, and characterized DOM composition through optical properties and chemical analysis.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.