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375 results for “Boreal forests”
NPP Multi-Biome: Grassland, Boreal Forest, and Tropical Forest Sites, 1939-1996, R1
This data set contains one data file (.csv format) that provides net primary productivity (NPP) estimates for 34 grasslands, 14 tropical forests, and 5 boreal forest sites distributed worldwide. The NPP data were compiled from published literature. In addition to above- and below-ground NPP, and total NPP estimates, the file includes site name and location, biome type, mean annual precipitation, and mean annual temperature, where available. Aboveground net primary production (ANPP), ranged from 35 to 2,320 g/m2/year, belowground net primary production (BNPP) ranged from 20 to 1,832 g/m2/year, and total net primary production (TNPP) ranged from 182 to 3,538 g/m2/year. Revision Notes: This data file has been revised to add a negative sign to south latitude and west longitude decimal degree coordinates, and the compass direction (N, S, E, W) for coordinates has been removed. NPP data for Vindhyan, India; Atherton, Australia; John Crow Ridge, Jamaica; and La Selva, Costa Rica, have been revised to correct previously reported values. Additional data references for Kuusamo, Finland, and La Selva, Costa Rica, have been added. Please see the Data Set Revisions section of this document for detailed information.
ABoVE: Annual Aboveground Biomass for Boreal Forests of ABoVE Core Domain, 1984-2014
This dataset provides estimated annual aboveground biomass (AGB) density for live woody (tree and shrub) species and corresponding standard errors at a 30 m spatial resolution for the boreal forest biome portion of the Core Study Domain of NASA's Arctic-Boreal Vulnerability Experiment (ABoVE) Project (Alaska and Canada) over the time period 1984-2014. The data were derived from a time series of Landsat-5 and Landsat-7 surface reflectance imagery and full-waveform lidar returns from the Geoscience Laser Altimeter System (GLAS) flown onboard IceSAT from 2004 to 2008. The Change Detection and Classification (CCDC) model-fitting algorithm was used to estimate the seasonal variability in surface reflectance, and AGB density data were produced by applying allometric equations to the GLAS lidar data. A Gradient Boosted Machines machine learning algorithm was used to predict annual AGB density across the study domain given the seasonal variability in surface reflectance and other predictors. The data received statistical smoothing to reduce noise and uncertainty was estimated at the pixel level. These data contribute to the characterization of how biomass stocks are responding to climate and disturbance in boreal forests.
ABoVE: Boreal Forest Resilience Study 2020-2022, Fairbanks AK
This dataset includes five metrics of forest resilience (recruitment, invasives, permafrost change, tree damage, and radial growth) at five recently burned forest sites (2010-2019) near Fairbanks, Alaska. The sites were imaged by the Airborne Visible InfraRed Imaging Spectrometer (AVIRIS-NG) in 2017 and 2022 during the Arctic-Boreal Vulnerability Experiment (ABoVE). Field measurements were conducted in 2021. Random forest (RF) vegetation classification models constructed from key hyperspectral bands were validated with ground-truthing (GT) of 44 measured plots and 45 geotagged plots. GT included stem densities, understory cover, soil characteristics, radial growth of 51 spruce trees from cores, and visual damage assays of 668 conifers and deciduous trees. There are 10 data files in comma-separated values format (CSV) in this dataset.
NPP Boreal Forest: Superior National Forest, USA, 1983-1984, R1
This data set contains two files (.txt format). One file provides ground-based biophysical measurements and above-ground net primary productivity (ANPP) estimates for 31 black spruce (Picea mariana) and 30 quaking aspen (Populus tremuloides) stands in Superior National Forest (SNF) in northeastern Minnesota, U.S.A. (-92 W 48 N). The measurements were obtained during a 1983-1984 intensive field campaign. Non-destructive measurements were made in over 100 forest plots covering a 50 x 50 km area. Trees sacrificed for biomass and annual increment measurements were taken outside the plots. The second file provides climate data from nearby weather stations for the period 1976-1986. The data set provides stand structural measurements (diameter at breast height, tree height, crown depth, and stem density), above-ground biomass, leaf area index, bark area index, and ANPP estimates. ANPP data are based on a combination of allometric relationships and annual tree-ring (radial) increments for the 5-year period 1979-1983. In the spruce stands, above-ground biomass ranged from 700-15,100 g/m2, LAI varied between 0.5-4.3, and ANPP ranged from 39-572 g/m2/yr. In comparison, above-ground biomass among aspen stands ranged from 600-22,000 g/m2, LAI varied between 1.3-4.0, and ANPP ranged from 213-1,199 g/m2/yr. The purpose of the SNF campaign was to investigate the ability of remote sensing to provide estimates of ecosystem biophysical properties. In addition to the results presented herein, satellite, aircraft, and helicopter observations and other ground measurements for the study sites are available from the ORNL DAAC Superior National Forest (SNF) Project web site [http://daac.ornl.gov/SNF/snf.shtml]. Revision Notes: Only the documentation for this data set has been modified. The data files have been checked for accuracy and are identical to those originally published in 1997.
ABoVE: Tree Canopy Cover and Stand Age from Landsat, Boreal Forest Biome, 1984-2020
This dataset contains Landsat-derived locally-calibrated estimates of tree canopy cover (TCC) and forest stand age across global boreal forests from 1984-2020 in Cloud-Optimized GeoTIFF (*.tif) format. These raster data span the circum-hemispheric boreal forest biome between 47 to 73 degrees north at 30 m resolution. Machine learning models calibrated with data from the World Reference System 2 were used to predict TCC from Landsat data at 30-m spatial resolution at annual temporal resolution. Through analysis of TCC time series, forest change estimates of stand age from 1984-2020 were developed. The broad spatial and temporal coverage of these data provide insight into forest and carbon dynamics of the global boreal forest system. Boreal forests store a large proportion of global soil and biomass carbon and have experienced disproportionately high levels of warming over the past century.
NPP Boreal Forest: Kuusamo, Finland, 1967-1972, R1
This data set contains three files (.txt format). One file provides stand characteristics, biomass, and production allocation data for an old-growth boreal forest near Kuusamo, Finland. The research was conducted during the 1967-1972 growing seasons. The other two files provide climate data from a weather station about 60 km south of the forest. One record contains precipitation and mean average temperature data for the 1961-1994 period (excluding 1971-1980) and the other contains precipitation data for 1908-1994. The Kuusamo research site is located just south of the Arctic Circle (66.37 N 29.32 E) and belongs to the northern boreal zone of taiga forests. The forest is an old Hylocomium-Myrtillus type spruce forest which has remained in a natural state and reached climatic climax long ago. The average age of the dominant spruces (Picea abies) is about 260 years. There is a well-developed ground layer of vegetation, chiefly dwarf scrub and mosses (dominant species: Vaccinium myrtillus, V. vitis-idaea, Hylocomium splendens, and Pleurozium schreberi). The northerly location of the forest and the age of its trees are the main factors responsible for low biomass and net production figures in comparison with spruce forests further south. Total above-ground biomass (including tree, understory, and moss layers) was determined by harvest methods and estimated to be 10,194 g/m2. Below-ground tree biomass estimates, also determined by harvest methods, are less reliable, at 3,753 g/m2. Total net primary productivity (NPP) for this site was estimated to be 441 g/m2/yr (421 g/m2/yr above-ground, 20 g/m2/yr below-ground).
ABoVE: Peak Greenness for Canadian Boreal Forest from Landsat 5 TM Imagery, 1984-2011
This dataset provides a 28-year time series of peak greenness (NDVI) data derived from Landsat 5 TM imagery over the boreal forest region of Canada. Landsat 5 TM scenes were collected for 46 selected sidelap sites along gradients in climate, tree cover, and disturbance history from 1984 to 2011. Peak-greenness reflectance was computed for 30-m Landsat pixels using the maximum normalized difference vegetation index (NDVI) along with the normalized burn ratio (NBR) during the period between days of the year (DOY) 180 and 204. To facilitate trend analysis at each site, the NDVI and NBR data of the 30-m Landsat pixels were regridded to the coarser MODIS 500-m (463.3-m) spatial scale to reduce the effects of missing data and to enhance the significance of the trend. The regridded NDVI and NBR 28-year time series data at 500-m resolution are provided for each of the 46 sites. Two trend analyses were run on the 500-m resolution data and are reported for each site. Supplemental site metadata are also provided, including the number of valid Landsat pixels, land cover composition, and disturbance history, for each 500-m pixel.
NACP LiDAR-based Biomass Estimates, Boreal Forest Biome, North America, 2005-2006
This data set provides estimates of aboveground biomass (AGB) for defined land cover types within World Wildlife Fund (WWF) ecoregions across the boreal biome of Alaska and western and eastern Canada, roughly between 45 and 70 degrees N. The study focused on within-growing-season data, i.e. leaf-on conditions.The AGB estimates were derived from a series of models that first related ground-based measured biomass to Portable Airborne Laser System (PALS) LiDAR measurements, and a second set of models that related the airborne estimates of biomass to Geoscience Laser Altimeter System (GLAS) LiDAR canopy structure measurements. The GLAS LiDAR biomass estimates were extrapolated by land cover types and ecoregions across the entire biome area.The study compiled remotely sensed forest structure data collected in June of 2005 and 2006 from the GLAS LiDAR instrument aboard the NASA Ice, Cloud, and land Elevation (ICESat) satellite and from the PALS airborne instrument flown at various times from 2005-2009 over both the ground plots and the ICESat GLAS flight path. For a consistent biome-level analysis, ecoregions contained within the boreal forest biome were identified by the World Wildlife Fund's (WWF) ecoregion map of the world (Olson et al., 2001). Land cover maps were used to identify land cover types for stratification purposes within eco-regions. Land cover data for Canada were provided by the Earth Observations for Sustainable Development (EOSD) project centered on year 2000, with images from 1999 to 2002. The National Land Cover Data (NLCD) 2001 classification was used for Alaska based on data collected between 1999 and 2004. The ground-based measurements are not provided with this data set.
A natural expression variant reveals a novel mechanism of insect resistance in boreal forest trees.
GEO Series GSE57301. Picea sitchensis; Picea glauca. 42 samples. Type: Expression profiling by array.
Data files of Carteron et al. "Soil abiotic and biotic properties constrain the establishment of a dominant temperate tree into boreal forests" in Journal of Ecology
<p>There are five data files use for the analysis present in the article of Carteron et al "Soil abiotic and biotic properties constrain the establishment of a dominant temperate tree into boreal forests" in Journal of ecology. These files are used in R script available in GituHub.</p> <p>GPS_megantic.csv: contains locations of the study plots</p> <p>colo_as.csv: Contains a summary of the root colonization by fungi</p> <p>colo.csv : Contains all the data of the root colonization by fungi</p> <p>colo.rdata: Contains all the data of the root colonization by fungi in Rdata format</p> <p>soil_thick.csv : Contains soil horizon thickness measured on the field</p> <p>traits_as.csv: Contains the traits measured on the sugar maple seedlings</p>
Figure 1 from: Klimaszewski J, Morency M, Labrie P, Seguin A, Langor D, Work T, Bourdon C, Thiffault E, Pare D, Newton A (2013) Molecular and microscopic analysis of the gut contents of abundant rove beetle species (Coleoptera, Staphylinidae) in the boreal balsam fir forest of Quebec, Canada. ZooKeys 353: 1-24. https://doi.org/10.3897/zookeys.353.5991
Figure 1 - Map of ribosomal RNA genes and ITS regions.
"Four decades increase in gross photosynthesis of boreal forests balanced out by increase in ecosystem respiration" data and codes
<p>Data and codes related to the manuscript "Four decades increase in gross photosynthesis of boreal forests balanced out by increase in ecosystem respiration".</p>
Dataset for "Soil fluxes of carbonyl sulfide (COS), carbon monoxide, and carbon dioxide in a boreal forest in southern Finland"
Open the record for dataset details and reuse information.
Data from: Disturbance-mediated heterogeneity drives pollinator diversity in boreal managed forest ecosystems
Open the record for dataset details and reuse information.
IBAIRN data (Boreal forest, Hyytiälä Sept. 2016) Max-Planck-Institut, Mainz
<p>Time series (10 min averages) of trace gases measured by the Max-Planck-Institut für Chemie during the IBAIRN-campaign. </p>
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Allen Brain Atlas
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
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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.