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48 results for “tree inventory”
Cooperative Alaska Forest Inventory (CAFI): I - Tree Inventory Data 1994-2024
The CAFI is a repeated forest measurement project established in forest stands throughout interior and southcentral Alaska. The CAFI was launched in 1994 and measurements were done at a 5-year interval until 2015. The project was on hiatus between 2016 and 2019 but picked back up again in 2020 and will continue at a 10-year interval. Total of 205 permanent plots have been established and each plot has been measured up to 6 times. The CAFI is the most extensive forest monitoring program, both in spatial and temporal scale, in interior and southcentral Alaska today. This is the tree data of the CAFI. The CAFI is a repeated forest measurement project established in forest stands throughout interior and southcentral Alaska. The CAFI was launched in 1994 and measurements were done at a 5-year interval until 2015. The project was on hiatus between 2016 and 2019 but picked back up again in 2020 and will continue at a 10-year interval. Total of 205 permanent plots have been established and each plot has been measured up to 6 times. The CAFI is the most extensive forest monitoring program, both in spatial and temporal scale, in interior and southcentral Alaska today.
Tree Inventories for Validating Terrestrial Lidar Measurements at Harvard Forest 2007-2014
Our objective is to improve the measurements of canopy structure and biomass of a forest stand and detect their annual changes via a ground-based laser scanning technology, also known as terrestrial lidar (TLS). A TLS instrument utilizes lasers to scan an environment, measure 3D locations of objects encountered by lasers and detect intensities of laser lights scattered by those objects back to the TLS instrument. TLS have shown abilities and is being further explored to retrieve stem diameter, stem count density, stand height, leaf area index, foliage profile, foliage area volume density, aboveground biomass and other useful forest structural parameters rapidly and accurately. Three TLS instruments used in this project include: (1) the Echidna (R) Validation Instrument (EVI), built by CSIRO Australia; (2) Dual-Wavelength Echidna® Lidar (DWEL), built by Boston University, University of Massachusetts, Lowell, University of Massachusetts, Boston and CSIRO Australia; (3) Compact Biomass Lidar (CBL), built by University of Massachusetts, Boston. To validate the forest structural parameters retrieved using these TLS instruments, we set up a one-ha (100 m by 100 m) forest site and collected tree inventory data including: tree location, tree species, DBH, tree height and crown dimension since 2007 with a two-year gap of 2008 and 2009. Lidar data are available from the ORNL DAAC (http://dx.doi.org/10.3334/ORNLDAAC/1045).
Forest Inventory for Tree Demography and Carbohydrate Reserves at Harvard Forest 2009-2011
The objective of this study is to establish a network of forest plots spanning the eastern U.S. focused on understanding how regional scale climate patterns affect patterns of tree demography (e.g. growth, mortality, dieback). Within each research site we also aim to understand the landscape-scale variability in demographic rates and how these rates are affected by edaphic variables by aligning plots along primary environmental gradients (elevation, soils, hydrology, fire return interval). The demographic data obtained will also be compared to regional and landscape-scale patterns in carbon reserves in adults and sapling by sampling root and stem concentrations of nonstructural carbohydrates (TNC) and relate these to demographic patterns, life-history traits, and plant C:N ratios. Besides addressing important ecological questions directly, this study is designed to improve the representations of vegetation dynamics and carbohydrate reserves in regional and landscape-scale forest ecosystem models--two of the least data-constrained processes in such models--by parameterizing and validating the modules for these processes in the Ecosystem Demography model (ED v2.1). This data set contains two years of census data for eight mapped plots distributed across Harvard Forest along the aforementioned primary environmental gradients.
Minneapolis-St. Paul Urban Tree Inventory
This dataset is a compilation of spatially explicit, species-specific urban tree inventories from across the seven-county Minneapolis-St. Paul (MSP) metropolitan area in Minnesota, U.S.A. The dataset was compiled to examine fine-scale patterns of tree biodiversity across MSP. Existing tree inventories were solicited from all municipalities, counties, park systems, and relevant non-profit organizations in the region for which we were able to find contact information, resulting in inventories from 35 municipalities, one county, one park system, three non-profit organizations and and two prior academic research efforts. The spatial and temporal scope of the inventories varies; for example, the inventories from some municipalities include data from a subset of only street trees at one timepoint, while other municipal inventories were continuously updated datasets with spatially comprehensive data for street trees in addition to some trees in parks and private lands. No inventory was fully comprehensive of all trees in an area. Data are assumed to have been collected between 2012-2022, although the timestamp on each data point is not explicit. Individual inventories were combined into one uniform database.
AVP-LAUT – Tree diameter data collected with Apple Vision Pro from Austrian forest Inventory plots
<p>This dataset consists of three zip archives containing valuable visual and measurement data related to tree assessments conducted using the Apple Vision Pro (AVP) technology. The first zip archive, <strong>images.zip</strong>, includes images taken in the forest, presented in .PNG and .JPG formats. These images capture various aspects of the study area and the measurement process.</p> <p>The second archive, <strong>videos_app_HR.zip</strong>, features videos recorded with the AVP using the "Handsruler" app, which focuses on measuring diameter at breast height (dbh) at 22 designated sample plots. Each video file is labeled with a numeric identifier that corresponds to the specific sample plot number, allowing for easy reference and organization.</p> <p>The third archive, <strong>videos_app_TM.zip</strong>, contains videos from the "Tape Measure" app, documenting dbh measurements taken at 17 sample plots. Similar to the previous videos, the file names indicate the respective sample plot numbers.</p> <p>In addition to the visual data, the dataset includes a comma-separated values (CSV) file named <strong>information_all_trees.csv</strong>, which consolidates all reference data regarding individual trees and sample plots. Each row in this file represents a single tree and includes several columns, each providing specific details about the measurements and observations.</p> <p>The column headers in <strong>information_all_trees.csv</strong> are as follows:</p> <ul> <li><strong>PLOT_ID</strong>: The numeric identifier for each sample plot.</li> <li><strong>tree_species_short</strong>: Abbreviation of the tree species.</li> <li><strong>caliper_dbh</strong>: The manually measured dbh of the tree in centimeters.</li> <li><strong>AVP_App1_dbh</strong>: The dbh measurement obtained from the AVP app "Handsruler" in centimeters.</li> <li><strong>AVP_App2_dbh</strong>: The dbh measurement obtained from the AVP app "Tape Measure" in centimeters.</li> <li><strong>res_App1</strong>: The difference between the dbh measured by the "Handsruler" app (AVP_App1_dbh) and the manual measurement (caliper_dbh), expressed in centimeters.</li> <li><strong>res_App2</strong>: The difference between the dbh measured by the "Tape Measure" app (AVP_App2_dbh) and the manual measurement (caliper_dbh), expressed in centimeters.</li> <li><strong>tree_species</strong>: The Latin name of the tree species, with genus and species connected by an "_".</li> <li><strong>tree_class</strong>: Classification of the tree into a species-specific category.</li> <li><strong>date</strong>: The date of the recordings.</li> <li><strong>time_App_1_min</strong>: The duration of all dbh measurements at the entire sample plot using the "Handsruler" app, in minutes.</li> <li><strong>time_App_2_min</strong>: The duration of all dbh measurements at the entire sample plot using the "Tape Measure" app, in minutes.</li> <li><strong>time_manual_caliper_min</strong>: The duration of all dbh measurements at the entire sample plot conducted manually, in minutes.</li> <li><strong>measuring_person</strong>: The individual field worker for conducting all dbh measurements (manual and both AVP apps) at the sample plot.</li> <li><strong>mean_slope_degrees</strong>: The average slope of the terrain across the sample plot, expressed in degrees.</li> </ul> <p>This comprehensive dataset provides essential insights into the effectiveness of the AVP technology for measuring tree dimensions and contributes to ongoing research in forest management and ecological studies. The included videos and images serve as a visual reference for the measurement processes, while the CSV file encapsulates the quantitative data necessary for analysis. Each row in the CSV file represents a single tree, facilitating detailed examinations of individual measurements and comparisons across different sample plots.</p>
Bonanza Creek LTER: Tree Inventory Data from 1989 to present at Core research sites in Interior Alaska
This is the data from the periodic (3-10 yr interval) tree inventory monitoring of tree growth within the vegetation control plots. In 2013 and 2014, an initial tree inventory was done on each site belonging to the Regional Site Network (RSN). Some young RSN sites had no, or very few trees. In general, inventory is every 5 years presently; the most recent collection was in 2018 and next scheduled collection is for 2023.
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.
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>
Tree inventory for adjacent stands of Picea mariana and Betula neoalaskana located in the 1958 Murphy Dome fire scar - 2012
This dataset contains the diameter of all trees measured as part of a project examining tree species affects on forest stand characteristics and plant-soil-microbial feedbacks. Study was conducted across 3 spatially explicit blocks containing adjacent stands of Picea mariana and Betula neoalaskana in forest that established following the 1958 Murphy Dome fire. All included tree diameter measurements were collected in Summer 2012.
Fire Self-Limitation (FiSL) Experiment: Quantifying Wildfire Carbon Combustion Losses in boreal Deciduous and Mixed Forests in Interior Alaska and the Boreal Cordillera II: Tree Inventory Data 2022
This dataset contains tree combustion measurements collected in the field for plots in 8 fire scars in Interior Alaska and the Yukon. Data was collected in the summer of 2022. Fire scars sampled included Shovel Creek (2019), Aggie Creek (2015), Hess Creek (2019), Baker (2015), Munson Creek (2021), Isom Creek (2020), 2019MA014 (2019), and 2019BC005 (2019). Tree species, diameters (DBH where possible, otherwise BD), condition (living/dead, standing/fallen, etc), and component combustion are recorded for every tree in each 10 m * 2 m plot.
Hubbard Brook Experimental Forest: Valleywide Plot Tree and Sapling Inventory – 1995, 2005, 2015
The valley-wide plots are a grid of 431 sites along fifteen N–S transects established at 500-m intervals spanning the entire Hubbard Brook Valley. The plot network was designed by Paul Schwarz for spatial analysis of tree species distribution patterns within the valley. Multiple above- and below-ground attributes have been measured on these plots. This dataset includes forest inventory data at 10 year intervals, for 1995, 2005, and 2015. The full survey takes three seasons to complete, with the datatable listing the exact measurement interval for each tree. Data are included for both trees and saplings on 371 core plots (all surveys) and 60 densified plots (1998, 2008). Locations of plots in this study can be found in the following dataset: Hubbard Brook Experimental Forest Valleywide Plots: GIS Shapefile (2022.) https://doi.org/10.6073/pasta/440b176372e0cdeb341731aea816b67c 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. These data have been used in a number of publications including: Schwarz, P.A., Fahey, T.J., Martin, C.W., Siccama, T.G., and Bailey, A. 2001. Structure and composition of three northern hardwood–conifer forests with differing disturbance histories. For. Ecol. Manage. 144(1–3): 201–212. doi:10.1016/S0378-1127(00)00371-6. Schwarz, P.A., Fahey, T.J., and McCulloch, C.E. 2003. Factors controlling spatial variation of tree species abundance in a forested landscape. Ecology, 84(7): 1862–1878. doi:10.1890/0012-9658(2003)084[1862:FCSVOT]2.0.CO;2. van Doorn, N.S., Battles, J.J., Fahey, T.J., Siccama, T.G., and Schwarz, P.A. 2011. Links between biomass and tree demography in a northern hardwood forest: a decade of stability and change in Hubbard Brook Valley, New Hampshire. Can. J. For. Res. <emphasis role="strong">41</emphasis>(7): 1369–1379. doi:10.1139/X11-063. C
Data from : Tree inventory data from permanent plots in French forest reserves
<p>We present a dataset resulting from the first round of a national monitoring program of forest reserves. It contains 9538 permanent plots, distributed across 111 study sites in mainland France (including Corsica). Notably focusing on dead wood measurement, this protocol has primarily been applied in strict forest reserves and special nature reserves (sensu Bollmann et Braunisch 2013), with 68% (6494) of the plots being currently located in strict forest reserves (unmanaged) and 24,7% (2363 plots) in forests unmanaged for at least 50 years. Sites cover a large variety of ecological conditions, from lowland to subalpine forests, but with an underrepresentation of Mediterranean forests (Table 1). The protocol assesses all the stages of a tree's life cycle, from seedling to decomposed lying dead wood. On each plot, a combination of three sampling techniques was used: (i) fixed area inventory for regeneration, standing dead trees, living trees and coarse woody debris (CWD) with diameter over 30 cm, (ii) transect lines for CWD with diameter < 30 cm, and (iii) fixed angle plot method for living trees with a diameter at breast height (DBH) > 30 cm (using a relascopic angle of 3%). Measurements include: exact tree location (azimuth, distance), species, diameter(s), tree-related microhabitats, decay stage and bark cover, seedling cover. With the ongoing climate change, the program network can also provide important information to monitor changes in forest ecosystems. It can also be used as forest management monitoring or conservation status assessment.</p>
Tree inventory data such as tree identity, position in the plot, height, architecture and biomass on Mt. Kilimanjaro
<p>This dataset describes position and sizes of all trees above 10 cm diameter at breast height in all plots, also fruiting and flowering events and if it is a canopy tree or not in KiLi project. -999999 represents NA in numeric variables. </p> <p>Within each plot, all trees wider than 10 cm diameter at breast height (dbh) were marked with aluminium tags and their dbh and height were measured. The dbh was measured with a diameter tape (Forestry Suppliers, USA) at 1.3 m for normally shaped trees and 20 cm below or above when branches or irregular shapes impeded measurement at that height. The 1.3 m height was measured from the highest ground level around the stem to standardize measurements taken on slopes. For trees which were strongly buttressed or too big to measure by hand, a laser dendrometer (Criterion RD 1000 with TruPulse 200/200, Centennial, USA) was used to measure the tree above the buttresses and at 1.3 m. Lianas above 10 cm in diameter were also marked and their dbh was measured. Tree height was measured using an ultra-sonic hypsometer (Vertex IV Hypsometer, Haglöf, Langsele, Sweden) or a laser rangefinder (TruPulse 200/200). The tree inventories were carried out between December 2010 and March 2013.</p> <p>The KiLi project (2010-2018) is a German Science Foundation (DFG) funded research unit (DFG research unit FOR1246) that focuses on biodiversity and ecosystem processes along altitudinal and disturbance gradients on Mt. Kilimanjaro (Tanzania, Africa), capitalizing on its world-wide unique range of climatic and vegetation zones. The research unit comprises 2 central projects and 7 subprojects from various disciplines. On a total of 60 study sites in both natural and human-disturbed ecosystems biodiversity (e.g. plants, soil arthropods, ants, bees, frogs, lizards, bats, birds), related ecosystem processes (decomposition, seed dispersal, pollination, herbivory, predation), and biogeochemical processes and properties of ecosystems (climate, soil properties and nutrient status, regulation of water and carbon fluxes, trace gas emissions, primary productivity, functional diversity) are analyzed.</p>
White spruce tree diameter vs age in mid-successional and late-successional long-term Bonanza Creek LTER inventory plots
This data lists age and diameter for white spruce trees of varying diameters growing in mid and late successional long-term BNZ LTER inventory plots in floodplain and upland landscapes.
Aspen tree diameter vs age in mid-successional long-term Bonanza Creek LTER inventory plots
This data lists age and diameter for aspen trees of varying diameters growing in mid successional long-term BNZ LTER inventory plots in upland landscapes.
Alaskan paper birch tree diameter vs age in mid-successional and late-successional long-term Bonanza Creek LTER inventory plots
This data lists age and diameter for Alaskan paper birch trees of varying diameters growing in mid- and late-successional long-term BNZ LTER inventory plots in upland and floodplain landscapes.
Balsam poplar tree diameter vs age in mid-successional and late-successional long-term Bonanza Creek LTER inventory plots
This data lists age and diameter for balsam poplar trees of varying diameters growing in mid and late successional long-term BNZ LTER inventory plots in floodplain and upland landscapes.
Interior Alaska managed sites: tree inventory measured one time in either summer 2012 or 2013
This dataset contains the diameter of all trees (diameter at breast height) and shrubs (basal diameter) measured in managed areas and adjacent unmanaged black spruce forest, in Summers 2012 and 2013.
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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.