Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
‘Tree – tree’ interactions are important structuring mechanisms for forest community dynamics. Forest management takes advantage of competition effects on tree growth by removing or retaining trees to achieve management goals. Both competition and silviculture have thus a strong effect on density and distribution of tree related microhabitats (TreMs) which are key features for forest taxa at the stand scale (e.g. Bouget et al. 2013, 2014). In particular, spatially explicit data to understand patterns and mechanisms of TreM formation in forest stands are rare. To train and eventually improve decision making capacities related to the integration of biodiversity aspects into forest management to date more than 100 usually 1 ha (100 m x 100m) permanent plots were established in different forest communities of Europe. Due to their demonstration character the selection of plots was non-systematic. They do, however, cover a broad range of forest types (e.g. beech-oak, beech-fir (-spruce), oak-hornbeam, pine-spruce, etc.), altitudinal gradients (from 25 m – 1850 m) and site conditions (e.g. oligotrophic Luzulo-Fagetum or Vaccinio-Pinetum to mesotrophic Galio-Fagetum or Milio-Fagetum). For each plot the following data is collected: (1) tree location as polar coordinates (stem base map), (2) tree species, (3) forest mensuration data (dbh in [cm], tree height in [m]), (4) tree related microhabitats (TreMs) and (5) tree status (living or standing dead). In addition to the spatial dendrometric data we provide information on plot establishment, forest type, plot location (state, region, country), elevation, means for annual precipitation and temperature, and the natural forest community (Kraus et al., 2018).
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
This data publication contains urban tree growth data collected over a period of 14 years (1998-2012) in 17 cities from 13 states across the United States: Arizona, California, Colorado, Florida, Hawaii, Idaho, Indiana, Minnesota, New Mexico, New York, North Carolina, Oregon, and South Carolina.
Measurements were taken on over 14,000 urban street and park trees. Key information collected for each tree species includes bole and crown size, location, and age. Based on these measurements, 365 sets of allometric equations were developed for tree species from around the U.S. Each “set” consists of eight equations for each of the approximately 20 most abundant species in each of 16 climate regions. Tree age is used to predict a species diameter at breast height (dbh), and dbh is used to predict tree height, crown diameter, crown height, and leaf area. Dbh is also used to predict age. For applications with remote sensing, average crown diameter is used to predict dbh. There are 171 distinct species represented within this database. Some species grow in more than one region. The Urban Tree Database (UTD) contains foliar biomass data (raw data and summarized results from the foliar sampling for each species and region) that are fundamental to calculating leaf area, as well as tree biomass equations (compiled from literature) for carbon storage estimates. An expanded list of dry weight biomass density factors for common urban species is made available to assist users in using volumetric equations.Information on urban tree growth underpins models used to calculate effects of trees on the environment and human well-being. Maximum tree size and other growth data are used by urban forest managers, landscape architects and planners to select trees most suitable to the amount of growing space, thereby reducing costly future conflicts between trees and infrastructure. Growth data are used to develop correlations between growth and influencing factors such as site conditions and stewardship practices. Despite the importance of tree growth data to the science and practice of urban forestry, our knowledge is scant. Over a period of 14 years scientists with the U.S. Forest Service recorded data from a consistent set of measurements on over 14,000 trees in 17 U.S. cities.These data were originally published on 03/02/2016. The metadata was updated on 10/06/2016 to include reference to a new publication. Minor metadata updates were made on 12/15/2016. On 01/07/2020 this data publication was updated to correct a few species' names and systematic errors in the data that were found. A complete list of these changes is included (\Supplements\Errata_Jan2020_RDS-2016-0005.pdf). In addition, we have included a list of changes for the General Technical Report associated with these data (\Supplements\Errata_Jan2020_PNW-GTR-253.pdf).
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
The database deals with the trees of the treeline ecotone worldwide. The ToTE (Trees of Treeline Ecotone) includes data on 208 tree species distributed across 34 mountain regions of the world. The database on the global tree species richness of the treeline is based on systematic review of 1202 studies published from 1962-2022. The database follows the scientific nomenclature as per Plants of the World Online (2022), the mountain classification as per Global Mountain Biodiversity Assessment (GMBA) Mountain Inventory v_2.0 (2022) and the biome classification as per Koppen and provides the current conservation status of the taxa as per IUCN (2022) ver. 2
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
The database deals with the trees of India. The ToI, Ver.-I (Trees of India, Version-I) includes data on 3708 tree species distributed across 35 states/union territories of India. The database is based on systematic review of 313 literature sources published from 1872-2022. The database follows the scientific nomenclature as per Plants of the World Online (2022). The database also includes 609 species endemic to India, and 347 species currently threatened as per IUCN (2022).
This data publication contains urban tree inventory data for 929,823 street trees that were collected from 2006 to 2013 in 49 California cities. Fifty six urban tree inventories were obtained from various sources for California cities across five climate zones. The five climate zones were based largely on aggregation of Sunset National Garden Book's 45 climate zones. Forty-nine of the inventories fit the required criteria of (1) included all publicly managed trees, (2) contained data for each tree on species and diameter at breast height (dbh) and (3) was conducted after 2005. Tree data were prepared for entry into i-Tree Streets by deleting unnecessary data, matching species to those in the i-Tree database, and establishing dbh size classes. Data included in this publication include tree location (city, street name and number), diameter at breast height, species name and/or species code, and tree type.
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
The Fire and Tree Mortality (FTM) database includes standardized observations of fire injury and survival or mortality for 171,177 individual tree-level observations, representing 142 tree species across the United States. Of these, 7,191 trees have burned twice. These trees were burned in 420 prescribed fires and wildfires occurring in 35 years, from 1981 to 2016. The database was developed using 41 contributed datasets from researchers, managers, and archived data products. At a minimum, datasets had to contain measurements of individual trees, size, fire injury, and post-fire survival, but some datasets include additional data such as bark beetle attack. Only trees that were alive before the fire were included in the database. We included any trees where post-fire status was measured within 10 years of the fire. If a tree re-burned in a subsequent fire, and post-fire injury and status information were available after that fire, then a new record (row) was made for that tree after the second fire.The purpose of the FTM database is to provide access to data on individual tree mortality or top-kill from wildland and prescribed fire. By pooling as many individual datasets as possible and creating consistent variables, data analysis with a much larger sample size is feasible. The FTM database also allows easy identification of data gaps to direct future data collection efforts. The FTM database also allows evaluation of post-fire mortality models, such as the First Order Fire Effects Model (FOFEM), BehavePlus, and the Fire and Fuels Extension to the Forest Vegetation Simulator (FFE-FVS).This data publication is a 2nd edition of the FTM database. The first edition (https://doi.org/10.2737/RDS-2020-0001) was originally published on 05/14/2020. This 2nd edition includes data updates such as a change to the format of live / dead status for years where data were not collected in the field, updates to the format of unobserved (NA) values, and additional data corrections. A thorough description of these updates is described in the process steps below.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
The Tallo database (v1.0.0) is a collection of 498,838 georeferenced and taxonomically standardized records of individual trees for which stem diameter, height and/or crown radius have been measured. Data were compiled from 61,856 globally distributed sites and include measurements for 5,163 tree species.
For a full description of the database, see: Jucker et al. (2022) Tallo – a global tree allometry and crown architecture database. Global Change Biology, https://doi.org/10.1111/gcb.16302. If using the Tallo database in your work please cite the original publication listed above, as well as this repository using the corresponding DOI (10.5281/zenodo.6637599).
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Tree Trait Task Force (3TF) - Tree Functional Trait Database
Corresponding author : belluaumichael@gmail.com paquette.alain@uqam.ca messier.christian@uqam.ca
Our dataset was originally created to offer scientists and the public a “ready-to-use” functional trait database for trees. This dataset is the first step within a larger project to create a standardized tree functional trait database for applied projects. We aim to offer a clean and uniform database of traits with clear selection criteria for its retained values : that the trait value is original and can be traced back to a single publication (duplicates are removed); that the trait was measured on trees growing in their natural environment (not experimental); that measurement units are correct; that all remaining possible outliers are verified manually by going back to the original publication for confirmation.
Full dataset description will follow soon
Last updated 3/9/2016. In 2006, a complete inventory of all the City’s street trees, including trees located within sidewalks, between sidewalks and curbs, or within 6 feet of the street if no sidewalk existed was conducted. One hundred volunteers were trained to record address, location, tree species, tree diameter, condition, and other related information. Trees located in parks and other public property were not included. Approximately 25,000 street trees were counted and the data was loaded into a tree database that the Forestry Division uses daily to manage the trees, track tree work, and record constituent concerns.
In 2006, a complete inventory of all the City’s street trees, including trees located within sidewalks, between sidewalks and curbs, or within 6 feet of the street if no sidewalk existed was conducted. One hundred volunteers were trained to record address, location, tree species, tree diameter, condition, and other related information. Trees located in parks and other public property were not included. Approximately 25,000 street trees were counted and the data was loaded into a tree database that the Forestry Division uses daily to manage the trees, track tree work, and record constituent concerns.
http://opendata.victoria.ca/pages/open-data-licencehttp://opendata.victoria.ca/pages/open-data-licence
Tree Species information from the Parks Department. Data are updated by city staff as needed, and copied to VicMap and the Open Data Portal on a weekly basis. Parks Department tree species data are collected by GPS location. For surveyed trees maintained by the Engineering Department, please see the Surveyed Trees layer.Diameter at Breast Height (DBH) is in centimetres. Tree Canopy Height and Width are in metres.The "Last Updated" date shown on our Open Data Portal refers to the last time the data schema was modified in the portal, or any changes were made to this description. We update our data through weekly scripts which does not trigger the "last updated" date to change.Note: Attributes represent each field in a dataset, and some fields will contain information such as ID numbers. As a result some visualizations on the tabs on our Open Data page will not be relevant.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
TreeGOER (Tree Globally Observed Environmental Ranges) is a database that documents the environmental ranges (minimum, maximum, median, mean and 5%, 25%, 75% and 95% quantiles) for 48,129 tree species and for 51 environmental variables, including 38 bioclimatic variables, 8 soil variables and 3 topographic variables. These ranges were calculated after cleaning occurrence records and standardizing species names with the WorldFlora R package to World Flora Online or the World Checklist of Vascular Plants for a global GBIF occurrence download of 44,267,164 occurrences (GBIF.org 2021 GBIF Occurrence Download https://doi.org/10.15468/dl.77gcvq). The 5% and 95% quantiles were calculated separately for two methods of outlier detection and for the full data set. The process of compilation of TreeGOER with 30 arc-seconds global grid layers, two examples of BIOCLIM applications that investigated the effects of climate change on global tree diversity patterns and R scripts to repeat these analyses have been described by Kindt, R. (2023). TreeGOER: A database with globally observed environmental ranges for 48,129 tree species. Global Change Biology, 00, 1–16. https://onlinelibrary.wiley.com/doi/10.1111/gcb.16914.
TreeGOER can be used in combination with the CitiesGOER database (https://doi.org/10.5281/zenodo.8175429) that documents the conditions for the same environmental variables (except elevation) for 52,602 cities with a human population ≥ 5000. TreeGOER could also be used with the TreeGOER Global Zones atlas that can be obtained from https://doi.org/10.5281/zenodo.8252756. This high resolution atlas includes sheets with global zones for the Climatic Moisture Index (CMI) and the number of months with average temperature > 10 degrees C (Tmo10); these are zones for which presence of the 48,129 species was documented by TreeGOER.
Changes between different versions of the databases are documented in a specific sheet in the metadata file.
The development of TreeGOER was supported by the Darwin Initiative to project DAREX001 of Developing a Global Biodiversity Standard certification for tree-planting and restoration, by Norway’s International Climate and Forest Initiative through the Royal Norwegian Embassy in Ethiopia to the Provision of Adequate Tree Seed Portfolio project in Ethiopia, and by the Green Climate Fund through the IUCN-led Transforming the Eastern Province of Rwanda through Adaptation project. When using TreeGOER in your work, cite the publication (Kindt 2023) as well as this repository using the DOI (https://doi.org/10.5281/zenodo.7922927).
Attribution-NonCommercial-NoDerivs 4.0 (CC BY-NC-ND 4.0)https://creativecommons.org/licenses/by-nc-nd/4.0/
License information was derived automatically
a) Fully labeled images (i.e. the image has all the trees delineated and each polygon has species information)
b) Partially labeled images (i.e. the image has only some trees delineated, and each polygon has species information)
No. | Dataset name | Training images | Validation images | Fully labeled | Partially labeled |
1 | 12_RGB5cm_FullyLabeled | 1066 | 304 | x | |
2 | ObjectDetection_TreeSpecies | 422 | 84 | x | |
3 | 34_RGB_all_L_PascalVoc_640Mask | 951 | 272 | x | |
4 | 34_RGB_PartiallyLabeled640 | 917 | 262 | x |
A database of phylogenetic trees of animal genes. It aims at developing a curated resource that gives reliable information about ortholog and paralog assignments, and evolutionary history of various gene families. TreeFam defines a gene family as a group of genes that evolved after the speciation of single-metazoan animals. It also tries to include outgroup genes like yeast (S. cerevisiae and S. pombe) and plant (A. thaliana) to reveal these distant members.TreeFam is also an ortholog database. Unlike other pairwise alignment based ones, TreeFam infers orthologs by means of gene trees. It fits a gene tree into the universal species tree and finds historical duplications, speciations and losses events. TreeFam uses this information to evaluate tree building, guide manual curation, and infer complex ortholog and paralog relations.The basic elements of TreeFam are gene families that can be divided into two parts: TreeFam-A and TreeFam-B families. TreeFam-B families are automatically created. They might contain errors given complex phylogenies. TreeFam-A families are manually curated from TreeFam-B ones. Family names and node names are assigned at the same time. The ultimate goal of TreeFam is to present a curated resource for all the families. phylogenetic tree, animal, vertebrate, invertebrate, gene, ortholog, paralog, evolutionary history, gene families, single-metazoan animals, outgroup genes like yeast (S. cerevisiae and S. pombe), plant (A. thaliana), historical duplications, speciations, losses, Human, Genome, comparative genomics
TROPIS, the Tree Growth and Permanent Plot Information System, contains five elements: (1) a network of people willing to share permanent plot data and tree growth information, serviced by newsletters and information sources hosted at http://www.cgnet.org/cifor/research/tropis.html (or available from CIFOR), (2) an index of people and institutions holding permanent plot data, (3) a database management system to assist more efficient data management, (4) a system to facilitate site -matching by identifying comparable sites and allowing foreign data to be used when no local growth information exists, and (5) an inference system to allow growth estimates to be made in the absence of empirical data. The index or metadatabase contains references to 12,000 plots with 3,000 species provided by 100 contributors. Searches of the database are welcomed, and may be directed to the author.
See eLife manuscript for full details. Below, we provide a summary of how the dataset was collected and processed.
Data Acquisition We limited our search to the 150 largest cities in the USA (by census population). To acquire raw data on street tree communities, we used a search protocol on both Google and Google Datasets Search (https://datasetsearch.research.google.com/). We first searched the city name plus each of the following: street trees, city trees, tree inventory, urban forest, and urban canopy (all combinations totaled 20 searches per city, 10 each in Google and Google Datasets Search). We then read the first page of google results and the top 20 results from Google Datasets Search. If the same named city in the wrong state appeared in the results, we redid the 20 searches adding the state name. If no data were found, we contacted a relevant state official via email or phone with an inquiry about their street tree inventory. Datasheets were received and transform...
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
The GlobalUsefulNativeTrees database (GlobUNT; https://worldagroforestry.org/output/globalusefulnativetrees) was developed after a first step of combining native distribution data across 242 countries and territories from GlobalTreeSearch (accessed 8th May 2022; Beech et al. 2017; BGCI 2022) with information on ten categories of human usage documented in the World Checklist of Useful Plant Species (WCUPS; Diazgranados et al. 2020). GlobUNT was described in more detail in the following publication: Kindt et al. (2023) GlobalUsefulNativeTrees, a database of 14,014 tree species, supports synergies between biodiversity recovery and local livelihoods in restoration. Sci Rep 13, 12640. https://doi.org/10.1038/s41598-023-39552-1. Version v.2023.01 of the database includes 14,014 useful tree species, representing roughly a quarter of the known tree species (as listed by GlobalTreeSearch) and a third of the plant species from WCUPS. The data set included here provides the taxonomic names for all tree species included in GlobUNT together with details on the process of standardization via the WorldFlora package (Kindt 2020). This taxonomic standardization process was completed during the preparation of the third major release of the Agroforestry Species Switchboard (as a consequence, all species listed in GlobUNT are included among the 230,000+ species from the Switchboard).
The development of GlobUNT was supported by the Darwin Initiative to project DAREX001 of Developing a Global Biodiversity Standard certification for tree-planting and restoration and by Norway’s International Climate and Forest Initiative through the Royal Norwegian Embassy in Ethiopia to the Provision of Adequate Tree Seed Portfolio project in Ethiopia. When using the GlobUNT species list in your work, please cite the publication (Kindt et al. (2023) provided above) as well as this repository using the DOI (https://zenodo.org/record/7994433).
Sidewalk Management System is used to track and organize inspections, volitions and the status of New York City sidewalks. Tracks properties where all sidewalk defects on the taxlot are due to trees/tree roots (All Tree Defects - ATD) For more information please visit NYC DOT website: www.nyc.gov/sidewalks
Open Data Commons Attribution License (ODC-By) v1.0https://www.opendatacommons.org/licenses/by/1.0/
License information was derived automatically
🇺🇸 미국 English In 2006, a complete inventory of all the City’s street trees, including trees located within sidewalks, between sidewalks and curbs, or within 6 feet of the street if no sidewalk existed was conducted. One hundred volunteers were trained to record address, location, tree species, tree diameter, condition, and other related information. Trees located in parks and other public property were not included. Approximately 25,000 street trees were counted and the data was loaded into a tree database that the Forestry Division uses daily to manage the trees, track tree work, and record constituent concerns.
Street tree data from the TreesCount! 2015 Street Tree Census, conducted by volunteers and staff organized by NYC Parks & Recreation and partner organizations. Tree data collected includes tree species, diameter and perception of health. Accompanying blockface data is available indicating status of data collection and data release citywide.
The 2015 tree census was the third decadal street tree census and largest citizen science initiative in NYC Parks’ history. Data collection ran from May 2015 to October 2016 and the results of the census show that there are 666,134 trees planted along NYC's streets. The data collected as part of the census represents a snapshot in time of trees under NYC Parks' jurisdiction.
The census data formed the basis of our operational database, the Forestry Management System (ForMS) which is used daily by our foresters and other staff for inventory and asset management: https://data.cityofnewyork.us/browse?sortBy=most_accessed&utf8=%E2%9C%93&Data-Collection_Data-Collection=Forestry+Management+System+%28ForMS%29
To learn more about the data collected and managed in ForMS, please refer to this user guide: https://docs.google.com/document/d/1PVPWFi-WExkG3rvnagQDoBbqfsGzxCKNmR6n678nUeU/edit. For information on the city's current tree population, use the ForMS datasets.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
‘Tree – tree’ interactions are important structuring mechanisms for forest community dynamics. Forest management takes advantage of competition effects on tree growth by removing or retaining trees to achieve management goals. Both competition and silviculture have thus a strong effect on density and distribution of tree related microhabitats (TreMs) which are key features for forest taxa at the stand scale (e.g. Bouget et al. 2013, 2014). In particular, spatially explicit data to understand patterns and mechanisms of TreM formation in forest stands are rare. To train and eventually improve decision making capacities related to the integration of biodiversity aspects into forest management to date more than 100 usually 1 ha (100 m x 100m) permanent plots were established in different forest communities of Europe. Due to their demonstration character the selection of plots was non-systematic. They do, however, cover a broad range of forest types (e.g. beech-oak, beech-fir (-spruce), oak-hornbeam, pine-spruce, etc.), altitudinal gradients (from 25 m – 1850 m) and site conditions (e.g. oligotrophic Luzulo-Fagetum or Vaccinio-Pinetum to mesotrophic Galio-Fagetum or Milio-Fagetum). For each plot the following data is collected: (1) tree location as polar coordinates (stem base map), (2) tree species, (3) forest mensuration data (dbh in [cm], tree height in [m]), (4) tree related microhabitats (TreMs) and (5) tree status (living or standing dead). In addition to the spatial dendrometric data we provide information on plot establishment, forest type, plot location (state, region, country), elevation, means for annual precipitation and temperature, and the natural forest community (Kraus et al., 2018).