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9,204 results for “tree”
Toklat River Fire in Denali National Park and Preserve: Site level environmental, soil, tree, vegetation, and fire characteristics measured in 2016
This dataset contains site-level average estimated of environmental, soil, tree, vegetation, and fire characteristics measured in 2016, three years after the Toklat River Fire in Denali National Park and Preserve. Measured parameters include latitude, longitude, slope, aspect, elevation, moisture classification, bulk density of the surface soil, residual organic soil depth, thaw depth, burn depth, density and basal area of all tree species pre-fire, the density of all tree species post-fire, estimates of above- and below-ground carbon combustion, and understory vegetation turnover from pre-fire to post-fire. There is also data on seed trap collection and experimental regeneration of seedlings collected in 2017 and 2018 at a subset of sites.
Alaska 2004 Burns: Growth and survival of tree seedlings in post-fire experimental transplant study across 39 sites
This dataset contains measurements of tree seedlings growth for an experimental transplant study started in 2005 at sites that burned in 2004 in interior Alaska. Records are from a set of 39 intensive study sites that were formerly dominated by black spruce along the Steese, Taylor, and Dalton highways. Seedlings were monitored for 10 years, with detailed measurements in 2006, 2008, 2011, 2013, and 2015. Aboveground biomass was harvested in 2011.
Overwintering Fires from 2009-2010 Burns near Fairbanks, Alaska: Pre-fire Tree Species Density and Combustion Collected 2023
This dataset contains data from adjacent overwintering and single-season burn sites. For the overwintering fires, we targeted locations that had burned in the summers of 2009, smouldered through the winter months, and reignited in 2010. Adjacent to these overwintering sites, we identified single-season burn sites from within portions of the 2009 fires that were unaffected by overwintering. A total of seven overwintering fire sites and four single-season fire sites were sampled. Data inlcudes within plot measurments of post-fire seedling composition and density, residual SOL, burn depth estimated by black spruce adventitious roots, thaw depth, and pre-fire tree species composition and estimates of combustion. This is one of three packages from this project; this one contains the pre-fire tree species density and combustion data.
Tree Health Conditions (mortality, damage, disease, bark beetles) in Fuel Reduction Treatments Located Near Communities in Interior Alaska and the Cook Inlet Region of Alaska - Observations from July-August 2023
This dataset contains tree-, transect-, and site-level observations of forest stands at sites that received a fuel reduction treatment. Tree-level observations include species, diameter, living status, damage, disease, and bark beetle presence. Transect-level observations include level of coarse woody debris and bark beetle presence. Sites are categorized by region (recent/ongoing spruce beetle oubreak or endemic spruce beetle population levels) and treatment type (hand-thinned or mechanincally felled and masticated). These observations are from July-August 2023. Sites are located near communities in Interior Alaska and the Cook Inlet Region.
Repeat photography of tidal fresh forest trees along the salinity gradient of the Altamaha River, GA
We established a transect of 42 stations for repeat photography of tidal fresh forest trees along the salinity gradient of the Altamaha River estuary. Target trees are located approximately every km on both the north and south banks, beginning at km 20 (with 0 at the mouth of the estuary) up to km 41, for a total of 21 km. We used a small boat to travel to each station and take digital photographs of target trees facing the river in Nov 2017, Feb, May, Aug of 2018. In Oct 2018 we extended the transect an additional 5 km downstream so that it now starts at km 16, with 5 more stations on the north bank and 5 on the south bank. All 52 stations were photographed in Oct 2018 and Oct 2019. These photos will be used to distinguish healthy, stressed and dead trees in each image and how they change over time.
Tree DBH response to nitrogen and phosphorus fertilization in the MELNHE study, Hubbard Brook Experimental Forest, Bartlett Experimental Forest, and Jeffers Brook
The Multiple Element Limitation in Northern Hardwood Ecosystems (MELNHE) project studies N and P acquisition and limitation of forest productivity through a series of nutrient manipulations in northern hardwood forests. This data set includes tree diameters at breast height (DBH) collected pre-treatment (2008, 2009, and 2010), and post-treatment (2011, 2015, 2019, and 2023). Additional detail on the MELNHE project, including a datatable of site descriptions and a pdf file with the project description and diagram of plot configuration can be found in this data package: https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-hbr&identifier=344 These data were gathered as part of the Hubbard Brook Ecosystem Study (HBES). The HBES is a collaborative effort at the Hubbard Brook Experimental Forest, which is operated and maintained by the USDA Forest Service, Northern Research Station. None
Tree Seed Data at the Hubbard Brook Experimental Forest, 1993 - ongoing
Tree seeds sorted and counted from long-term reference area litter traps are presented for 1993 until the present. These data are part of the LTER funded quantification of tree annual productivity. Our focal species for seed counts have been sugar maple, American beech and white ash. This data set allows comparison between seed production in reference sites (BB and TF) and the calcium addition watershed (W1) for these species. These data were gathered as part of the Hubbard Brook Ecosystem Study (HBES). The HBES is a collaborative effort at the Hubbard Brook Experimental Forest, which is operated and maintained by the USDA Forest Service, Northern Research Station.
Physical and chemical properties of soils on Watershed 5 of Hubbard Brook Experimental Forest, before and after whole-tree harvest
We sampled soils on watershed 5 at the Hubbard Brook Experimental Forest in 1983, prior to a whole-tree harvest conducted in the winter of 1983-84. We resampled in 1986, 1991, and 1998. All sampling was performed using a quantitative soil pit method. Samples of the combined Oi and Oe horizons; the Oa horizon; 0-10 cm, 10-20 cm, and >20 cm layers of mineral soil; and the C horizon were collected. Grab samples of pedogenic mineral horizons were also taken from the sides of a subset of pits in each year. Here we report soil chemistry, mass of soil, percent rock, bulk density, and organic matter. These data were gathered as part of the Hubbard Brook Ecosystem Study (HBES). The HBES is a collaborative effort at the Hubbard Brook Experimental Forest, which is operated and maintained by the USDA Forest Service, Northern Research Station.
Hubbard Brook Experimental Forest: Relations of the O-horizon with canopy tree species and hydropedologic soil types, 2021
As the interface between plants and soil, the organic horizon is the foundation of forest ecosystems. Two potential predictors of O-layer properties, vegetation and mineral soil type, are difficult to separate because they typically covary. We conducted a factorial study involving four canopy tree species and two soil types with distinctly different hydrology and topographic position to parse patterns in chemistry and microbiota of the O-layer in a north-temperate deciduous forest. These data were gathered as part of the Hubbard Brook Ecosystem Study (HBES). The HBES is a collaborative effort at the Hubbard Brook Experimental Forest, which is operated and maintained by the USDA Forest Service, Northern Research Station.
Hubbard Brook Experimental Forest: Watershed 1 Tree Inventory, 1996 - ongoing
In order to evaluate the role of Ca supply in regulating the structure and function of base-poor forest and aquatic ecosystems, the Ca content of soil was increased through the application of wollastonite (CaSiO3) in October 1999. The watershed is forested by typical northern hardwood species (sugar maple, beech and yellow birch) on the lower 90 % of its area, and by a montane boreal transition forest of red spruce, balsam fir and white birch on the highest 10%. Forest inventory surveys were initiated in 1996 and repeated at 5 year intervals. This data set includes 2016 inventory measurements. The data consists of a total inventory of all trees ≥10 cm diameter-at-breast-height (dbh) on the whole of the watershed (11.8 ha), as measured in each of the 200 25 m x 25 m plots. Trees ≥ 2 to ≤10 cm dbh were subsampled using a 3 meter wide strip along one edge of each 25 m x 25 m plot. With the addition of tree tags in 2006 on all trees ≥10 cm dbh, tracking of individual trees is now possible nd trees that grow into the ≥10 cm dbh size class are tagged each survey. The data consist of the diameters (dbh) of all the trees ≥10 cm dbh, live and dead, in the whole of the watershed (about 9000 individual stems) and an additional 3000-4000 saplings. These data were gathered as part of the Hubbard Brook Ecosystem Study (HBES). The HBES is a collaborative effort at the Hubbard Brook Experimental Forest, which is operated and maintained by the USDA Forest Service, Northern Research Station.
Hubbard Brook Experimental Forest: Watershed 5 Tree Inventory, 1982 - ongoing
A whole-tree harvest was conducted during the dormant season of 1983-1984 in order to assess ecosystem response to whole-tree logging operations. Pre-harvest forest inventory surveys were conducted in 1982 on the whole of the watershed. Post-harvest surveys were conducted in 1990, 1994 and every 5 years thereafter. This data set includes data for 1982 – 2019 surveys. The hydrology has been monitored since 1962 and stream water chemistry monitored since 1963. In 1982, before the clearcut, the watershed was forested by typical northern hardwood species (sugar maple, beech and yellow birch) on the lower 85 % of its area and by a montane boreal transition forest of red spruce, balsam fir and white birch on the highest 15%. These data were gathered as part of the Hubbard Brook Ecosystem Study (HBES). The HBES is a collaborative effort at the Hubbard Brook Experimental Forest, which is operated and maintained by the USDA Forest Service, Northern Research Station.
Hubbard Brook Experimental Forest: Watershed 6 Tree Inventory, 1965 - ongoing
The watershed is forested by typical northern hardwood species (sugar maple, beech and yellow birch) on the lower 90% of its area and by a montane boreal transition forest of red spruce, balsam fir and white birch on the highest 10%. Forest inventory surveys were initiated in 1965, repeated in 1977, and repeated at 5 year intervals after that. This data set includes all inventories from 1965 to 2022 (11 surveys). The inventory consists of a total inventory of all trees ≥10 cm diameter-at-breast-height (dbh) (over 11,000 individual stems overtime) on the whole of the watershed (13.23 ha, 549−792 m in elevation), as measured in each of the 208 grid cells (= plots; 25 m x 25 m, 625 m2). Trees ≥2 to <10 cm dbh were subsampled using a 3 meter wide strip along one edge of each 25 m x 25 m plot. While the specifics of the inventory design varied between watersheds and over time, the core measurements were consistent. Differences between exact inventory methods over time are detailed in the Methods. The surveys include 6000 – 7000 live trees and another 2000-3000 dead standing trees. These data were gathered as part of the Hubbard Brook Ecosystem Study (HBES) and funded largely through the Long-term Ecological Research (LTER) program through NSF since 1988. The HBES is a collaborative effort at the Hubbard Brook Experimental Forest, which is operated and maintained by the USDA Forest Service, Northern Research Station.
Tree ring data from the Niwot Ridge subalpine zone, 2017 - 2018.
Tree cores were collected across a range of diverse stand types and topographic positions in 2017 and 2018 to examine changes in tree growth as a response to changing climate in the subalpine forest of the Colorado Front Range, USA. Tree cores were collected for all present species in the subalpine zones; Engelmann spruce (Picea engelmannii), subalpine fir (Abies lasiocarpa), lodgepole pine (Pinus contorta) and limber pine (Pinus flexilis). We extracted core from ~180 trees from 3 large permanent plots across a range of species and sizes classes within each plot. The cores were then processed using WinDENDRO software. This dataset includes field data taken on each tree from which a core was extracted, the original WinDENDRO files for each coree.g. bark thickness, height, etc.), 2) MRS4 .txt fil output from WinDENDRO, 3) MRS5 .txt fil output from WinDENDRO, 4) MRS7.txt fil output from WinDENDRO, The WinDENDRO, outputs will be used to reconstruct a time series of radial growth for each tree in each plot to examine whether the topoclimatic position affects tree growth (by species and stand types) and whether tree growth has changed with warming temperatures.
Point cloud data from terrestrial laser scanning for stem volume modelling of Scots pine trees
<p>Stem volume is a key forest inventory attribute characterizing growth and yield of individual trees and forest stands. Three-dimensional information from terrestrial laser scanning (TLS) can be used to reconstruct tree stems and provide information on stem volume as well as stem shape. We collected diameter at breast height and height information with traditional field measurements as well as preprocessed TLS point cloud data on 230 Scots pine trees (<em>Pinus sylvestris L.</em>) from southern Finland. The data set here includes three-dimensional information on Scots pine tree stems derived from TLS point clouds. The usage of this data set can include, but is not limited to, development of point cloud processing algorithms for single tree stem reconstruction and investigations of of stem volume modelling for Scot pine. </p> <p>This data set includes two files: Scots_pines.txt includes DBH and height information based on field measurements from the 230 Scots pine trees. File includes the following columns: treeID, DBH, and h, where DBH is presented in cm and h (i.e. tree height) in m. Stem_points.zip, on the other hand, includes 230 laz-files where figure in the name of the laz-file refers to the tree ID in Scots_pines.txt-file. Laz-files include three columns that describe x, y, and z, coordinates (in meters) of stem points in a local coordinate system extracted from the normalized TLS point clouds (i.e. z coordinate describes height above ground).</p>
Data from paper: "Large-scale variations in the dynamics of Amazon forest canopy gaps from airborne lidar data and opportunities for tree mortality estimates"
<p>Data from the paper:</p> <p>Dalagnol, R. <em>et al.</em> Large-scale variations in the dynamics of Amazon forest canopy gaps from airborne lidar data and opportunities for tree mortality estimates. <em>Sci Rep</em> <strong>11, </strong>1388 (2021). https://doi.org/10.1038/s41598-020-80809-w</p> <p>Link: https://www.nature.com/articles/s41598-020-80809-w</p> <p> </p> <p>This repository contains:</p> <p>1) Data frame with data from static and dynamic gaps used in Figure 2 (Dalagnol_2020_Data_Multitemporal_gaps.csv). Each row is the aggregated measurement at 5-km resolution. The site component referes to the five site studied with multitemporal data. Site order from 1 to 5 is DUC, TAP, FN1, BON and TAL.</p> <p>2) Data frame with data from static gaps and environmental factors used in Table 1, Figure 3, 4, 5 (Dalagnol_2020_Data_Singledate_gaps_Modeling.csv). Each row is the aggregated measurement of one site observed by airborne lidar data.</p> <p>3) Raster file at 5-km resolution with dynamic gap fraction estimates presented in Figure 5 (dynamic_gap_fraction_amazon.tif).</p> <p> </p> <p>If you need anything else, please contact the corresponding author: Ricardo Dalagnol (ricds@hotmail.com).</p>
LAUTx - Individual Tree Point Clouds From Austrian Forest Inventory Plots
<p>This dataset contains manually segmented tree point clouds from Personal Laser Scanning (PLS) data, and additionally automatic segmented trees from the same point clouds. The raw point cloud data has been published in LAUT - Terrestrial and Personal laser scanner data from Austrian forest Inventory plots (<a href="https://doi.org/10.5281/zenodo.3698956">https://doi.org/10.5281/zenodo.3698956</a>) and six of those plots were processed for this data. Purpose of this data is to serve as benchmarking for automatic tree segmentation algorithms.</p>
Public sequence accessions from INSDC, COG-UK and CNCB and EPI_SET from GISAID for SARS-CoV-2 genome sequences in 2023-08-01 UShER tree
<p>Genome sequences and metadata for the accessions in the .tsv.gz (gzip-compressed tab-separated text) files are freely available from their corresponding sources:</p><ul><li>insdc.accessionNameDate.tsv.gz: INSDC (GenBank, ENA, DDBJ) sequences and metadata may be downloaded using NCBI Datasets: https://www.ncbi.nlm.nih.gov/datasets/taxonomy/2697049/ (7,361,734 accessions used on 2023-08-01)</li><li>cog.accessionNameDate.tsv.gz: COG-UK sequences and metadata may be downloaded from https://cog-uk.s3.climb.ac.uk/phylogenetics/latest (as of publication); most COG-UK sequences have been submitted to ENA and are available from INSDC/NCBI Datasets as well. (724,978 accessions used on 2023-08-01)</li><li>cncb.accessionNameDate.tsv.gz: Sequences and metadata from several databases at the China National Center for Bioinformation (CNCB) may be downloaded from GenBase: https://ngdc.cncb.ac.cn/genbase/ (26,604 accessions used on 2023-08-01)</li></ul><p>GISAID data are subject to restrictions on sharing described in https://gisaid.org/terms-of-use/. Genome sequences and metadata are available to registered GISAID users as part of EPI_SET_231106ax at https://doi.org/10.55876/gis8.231106ax (7,718,061 accessions used on 2023-08-01).</p>
Wollestraat 29, Bruges (BE): high-resolution images of dry wood cores taken form a medieval floor joists, for tree-ring analysis
<ul><li>Dry-wood cores taken from historical timbers of a floor joists in the medieval building 'De Oude Steen', Wollestraat 29, Bruges (Belgium).</li><li><a href="https://id.erfgoed.net/erfgoedobjecten/29956 ">https://id.erfgoed.net/erfgoedobjecten/29956 </a></li><li>The cores were sampled at 22/02/2023 with a dry-wood borer (internal diameter 12 mm, external diameter 19 mm).</li><li>The cores were surfaced with increasingly finer sanding papers, from P60 up to P4000.</li><li>The cores were photograpphed with a Sony alpha7R IV full frame camera and FE 90 mm F/2.8G macro lens.</li><li>The<a href="https://www.wsl.ch/en/services-produkte/skippy/"> Skippy</a> system served as the image capturing platform.</li><li>The individual digital macro-photos were stitched with PTGui into a mosaic image (.tiff).</li><li>The mosaic images have a resolution of ~4 µm.</li></ul>
Dataset of 400 pomegranate tree (Punica granatum L. 'Wonderful') images
<p>Dataset of 400 pomegranate tree (Punica granatum L. ‘Wonderful’) images, with the corresponding fruit masks.</p> <p>The dataset is designed for training artificial intelligence models for instance segmentation.</p> <p>The pictures were collected by means of mobile devices (smartphones), in random trees, from different distances, orientations and in varying lighting conditions. The resolution of the images and masks is 640x480 pixels. The dataset is divided into training (70%), validation (15%) and test set (15%). Stratification was performed in 3 periods of the season to ensure that all fruit ripening stages were present in each subset. Masks consist of a very detailed manual annotation of the visible part for each of the fruits in the images.</p>
Dataset of pomegranate tree (Punica granatum L. 'Wonderful') image times series
<p>Dataset of pomegranate tree (Punica granatum L. ‘Wonderful’) image times series. The pictures were collected by means of Raspberry Pi cameras with OV5647 sensor (5 MP, f2.9). Sensors were installed on fixed platforms for continuous measurement with zenithal orientation at a distance of approximately 1 metre from the canopy. Images were captured daily at 9 a.m. (GMT+2) from July to mid-October in 2021 and 2022. The resolution of the images is 640x480 pixels.</p>
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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.