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9,204 results for “tree”
Trees and alignments for: A robust phylogenomic framework for the calamoid palms
<p>Target file, alignments, gene trees and species trees from phylogenomic analyses in Kuhnhäuser et al. (2021), A robust phylogenomic framework for the calamoid palms, Molecular Phylogenetics and Evolution. <a href="https://doi.org/10.1016/j.ympev.2020.107067">https://doi.org/10.1016/j.ympev.2020.107067</a>.</p> <p>Raw sequence data are deposited in the European Nucleotide Archive of the European Bioinformatics Institute (<a href="https://www.ebi.ac.uk/ena">https://www.ebi.ac.uk/ena</a>) under project number PRJEB40689. Scripts for all phylogenetic analyses are available at <a href="https://github.com/BenKuhnhaeuser/PhyloFrame">https://github.com/BenKuhnhaeuser/PhyloFrame</a>.</p>
Presence observations for six tree species prioritized for forest landscape restoration in Ethiopia
<p><strong>Description:</strong></p><p>Geolocations of presence occurrences for a selection of six species (<i>Cordia africana</i>, <i>Croton macrostachyus</i>, <i>Eucalyptus globulus</i>, <i>Faidherbia albida</i>, <i>Grevillea robusta</i>, <i>Juniperus procera</i>) sourced from databases (GBIF, RAINBIO) and from the scientific literature.</p><p>Each record is associated with a DOI, link, or citation to the original source of the data. Observations were filtered using the R package <i>CoordinatesCleaner</i> (Zizka <i>et al</i>. 2019) with the <i>clean_coordinates </i>function to filter for errors that are common to biological collections.</p><p>The breakdown of the number of observations by species is: <i>Cordia africana</i> (84); <i>Croton macrostachyus</i> (129); <i>Eucalyptus globulus (</i>20); <i>Faidherbia albida </i>(31); <i>Grevillea robusta </i>(350); <i>Juniperus procera </i>(115).</p>
UAV time series and tree crowns
<p>This dataset contains:</p><p>-A UAV time series of mosaicked images of a woodland in Northeast UK. Complete detaisl are given in: "Elias Fernando Berra, Rachel Gaulton, Stuart Barr, Assessing spring phenology of a temperate woodland: A multiscale comparison of ground, unmanned aerial vehicle and Landsat satellite observations, Remote Sensing of Environment, Volume 223, 2019, Pages 229-242, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2019.01.010." </p><p>-Manual (reference) and automatic delinetaed tree crowns for the area covered by the UAV time series data. Complete details in: Elias F. Berra. Individual tree crown detection and delineation across a woodland using leaf-on and leaf-off imagery from a UAV consumer-grade camera. Journal of Applied Remote Sensing, Vol. 14, Issue 3, 034501 (July 2020). https://doi.org/10.1117/1.JRS.14.034501</p>
Fruit, seed dispersal, and life history traits of tropical rainforest trees of the Anamalai Hills, Western Ghats, India
<p>This dataset contains compiled Fruit, seed dispersal, and life history traits of tropical rainforest trees of the Anamalai Hills, Western Ghats, India. The list of species included are mainly from the following two related publications:<br>- Muthuramkumar, S., Ayyappan, N., Parthasarathy, N., Mudappa, D., Raman, T.R.S., Selwyn, M.A. and Pragasan, L.A. (2006), <a href="https://doi.org/10.1111/j.1744-7429.2006.00118.x">Plant Community Structure in Tropical Rain Forest Fragments of the Western Ghats, India</a>. <em>Biotropica</em>, 38: 143-160. https://doi.org/10.1111/j.1744-7429.2006.00118.x<br>- Osuri, A., Chakravarthy, D., Mudappa, D., Raman, T., Ayyappan, N., Muthuramkumar, S., & Parthasarathy, N. (2017). <a href="http://httpd//doi.org/10.1017/S0266467417000219">Successional status, seed dispersal mode and overstorey species influence tree regeneration in tropical rain-forest fragments in Western Ghats, India</a>. <em>Journal of Tropical Ecology</em>, 33(4), 270-284. doi:10.1017/S0266467417000219<br>The present dataset is an expanded and updated version of the related dataset available at <a href="https://doi.org/10.5061/dryad.vd0nn">https://doi.org/10.5061/dryad.vd0nn</a><br> <br>Species traits information was collated from <a href="http://www.biotik.org/">BIOTIK (http://www.biotik.org/</a>), <a href="http://www.flowersofindia.net/">Flowers of India (http://www.flowersofindia.net/)</a>, India Biodiversity Portal (http://indiabiodiversity.org/), <a href="https://doi.org/10.5061/dryad.234/1">Global wood density database (https://doi.org/10.5061/dryad.234/1)</a> and <a href="https://doi.org/10.1017/S0266467417000219">Osuri et al. (2014): https://doi.org/10.1017/S0266467417000219</a>. We also referred to the following previous studies that provided information on the successional status of rain-forest species in the Western Ghats (Chetana 2013, Pascal 1988, Raman et al. 2009, Sreejith 2005).</p> <p><strong>References:</strong><br>CHETANA, H. C. 2013. Assessing the ecological processes in abandoned tea plantations and its implication for ecological restoration in the Western Ghats, India. PhD thesis, Manipal University.<br>OSURI, A. M., KUMAR, V. S. & SANKARAN, M. 2014. Altered stand structure and tree allometry reduce carbon storage in evergreen forest fragments in India’s Western Ghats. <em>Forest Ecology and Management </em>329: 375–383.<br>PASCAL, J. P. 1988. <em>Wet evergreen forests of the Western Ghats of India: Ecology, structure, floristic composition and succession</em>. Institut Français de Pondichéry, Pondicherry.<br>RAMAN, T. R. S., MUDAPPA, D. & KAPOOR, V. 2009. Restoring rainforest fragments: survival of mixed-native species seedlings under contrasting site conditions in the Western Ghats, India. <em>Restoration Ecology</em> 17:137–147.<br>SREEJITH, K. A. 2005. Ecological and ecophysiological studies on the successional status of tree seedlings in tropical wet evergreen and semi-evergreen forests of Kerala. PhD thesis, Forest Research Institute, Dehradun.</p> <p><strong>Geographic Coverage:</strong><br>1. Location/Study Area: Valparai Plateau, Tamil Nadu, India; Anamalai Tiger Reserve, Tamil Nadu, India<br>2. GPS coordinates: Valparai Plateau (10°15'- 10°22'N, 76°52' - 76°59'E); Anamalai Tiger Reserve (10°12' - 10°35'N, 76°49' - 77°24'E)</p> <p><strong>Temporal Coverage:</strong><br>1. Begins: 2003-03-01 (Year, Month, Day)<br>2. Ends: 2024-02-10 (Year, Month, Day)</p> <p>Besides the <strong>README.txt</strong> file, the dataset includes the following comma-delimited text (csv) file with the data in columns as explained below:</p> <p><strong>Anamalai_tree_traits_2024.csv</strong></p> <p><strong>spec_name_ORIG:</strong> Scientific name of the species used during the data collection<br><strong>genus:</strong> Genus of the taxon<br><strong>specificEpithet:</strong> Specific epithet of the taxon in the Latin binomial name<br><strong>Accept_name_WFO:</strong> Updated scientific name of the species as in Plants of the World Online (POWO, https://powo.science.kew.org/)<br><strong>Habit:</strong> life form of the species(tree/shrub/cane/palm)<br><strong>Distribution:</strong> Distribution of the species in the study area (Native/Endemic/Introduced)<br><strong>IUCN_status:</strong> IUCN status of the species (CR-Critically Endangered,DD-Data deficient,EN-Endangered,LC-Least Concern,NT-Near Threatened,VU-Vulnerable,NA-Unknown)<br><strong>Wden_final:</strong> Wood density value assigned for the species (g cm^-3); NA - not available; sourced from Global wood density database (https://doi.org/10.5061/dryad.234/1)<br><strong>wd_level:</strong> Level in which the wood density value belongs (Species - wood density value is from species level; genus - wood density value assigned is the genus level average value)<br><strong>fruit_type:</strong> Morphological type of fruit<br><strong>fleshy_dry:</strong> Whether fruit is a dry fruit or fleshy, with aril or other parts <br><strong>seed_size:</strong> Species seed size: L = Large (>3 cm); M = Medium (1-3 cm); S = Small (<1 cm)<br><strong>disperser:</strong> Categories indicating seed dispersal mode: Bird, mammal, bird and mammal (Mammal_bird), gravity, wind, or unknown<br><strong>habitat:</strong> Habitat affinity category: EG_edg - evergreen forest edge; EG_for - evergreen forest; Dec_for - deciduous forest; Int – Introduced species; Unknown – Unknown<br><strong>habt_new:</strong> Habitat affinity new category: Mature – mature forest; Secondary – secondary forest, NA - unknown/Introduced species<br><strong>ad_ht:</strong> Species maximum adult height (m)</p>
Pawpaws prevent predictability: A locally-dominant tree alters understory beta-diversity and community assembly
<p>Data used in "Pawpaws Prevent Predictability: A locally-dominant tree alters understory beta-diversity and community assembly" (Wassel and Myers) accepted for publication in Ecosphere.<br><br><strong>Metadata for Zenodo.pdf </strong>contains more information on the following data files including descriptions of the columns. </p> <p>The file <strong>understory_abundance_data2021.csv</strong> contains all species abundances in 1x1m plots. This data was used for analyses in publication. Each row is a plot, each column is a speceis or plot descriptor, values for columns 5 and higher are species abundances. Data was collected July-August 2021 by Anna Wassel in Missouri, USA. </p> <p>The file <strong>understory_species_list2021.csv </strong>contains a list of the species codes used in the first file with their scientific names and their status as herbs or woody. This was used to filter out herbaceous species from the data set for herbaceous-only analyses. </p> <p> </p>
Land transformation on multi-decadal timescales reveals expanding croplands and settlements at the expense of tree-covered areas and mangroves in Nigeria
<p>A comparative assessment of the change patterns was conducted for seven categories using multi-decadal timescales in seven agroecological zones during three time-intervals (i.e., 1986 – 2000, 2000 – 2013, and 2013 – 2022). These selected periods cover important epochs in Nigeria’s recent history. To examine how much humans have appropriated natural cover (HANLC) in Nigeria over the last four decades, we differentiated natural covers (e.g., tree-covered areas, grasslands, wetlands, and waterbodies) from human activity-related uses (e.g., cropland, artificial surfaces and otherland). To identify trajectories of changes signifying human appropriation of land cover, we evaluated the drivers and processes underlying these major transitions, 1) Natural regeneration and afforestation, 2) Cropland expansion, and 3) Settlement and infrastructure development. Cropland expansion is Nigeria’s most widespread change process with much loss of croplands related to natural regeneration and settlement expansion. The transition matrix is provided showing the extent of land-cover changes in Nigeria over almost four decades (1986 - 2022). Major land cover transitions in each agroecological zone is presented. Analysis of land cover change in each agroecological zone is over 100% when areas of persistence (i.e., areas of no change) are not considered in the analysis.</p>
Taxonomic and ecological database of trees of Western Ghats - TreeGhatsData
<p><em>TreeGhatsData</em> is a compilation of lists of tree taxa found in Western Ghats, South India:</p> <ul> <li>taxa for which the word "tree" appears in habit description in the book <em>Flowering plants of the Western Ghats</em> edited by the Tropical Botanic Garden Research Institute (TBGRI), including planted or cultivated taxa (Nayar, Beegam, and Sibi. 2014);</li> <li>tree taxa described after 2014 in journal articles;</li> <li>taxon names used in forest surveys published by the French Institute of Pondicherry (IFP), in journal articles from 2000, and in the Atlas of endemics of the Western Ghats (Ramesh and Pascal 1997);</li> <li>taxon names reported with "tree" habit in Indian Biodiversity Portal (http://indiabiodiversity.org/).</li> </ul> <p>For each plant name, <em>TreeGhatsData</em> includes the following taxonomic information: family, genus epithet, species epithet, infrataxon rank, infrataxon epithet, authority. Both the family name used in TBGRI book and the corresponding family name according to Angiosperm Phylogeny Group system III (APGIII; Bremer et al. 2009) are provided.</p> <p><em>TreeGhatsData</em> includes the taxonomic status, the reference name and the authority according to TBGRI flora, along with taxonomic status from The Plant List version 1.1 (http://www.theplantlist.org/). From these two sources, a taxonomic status is suggested for each taxon name, with corresponding reference names and authorities.</p> <p><em>TreeGhatsData</em> also includes ecological and biogeographic information from TBGRI and completed by the botanists of French Institute of Pondicherry (IFP).</p> <p>Because most vegetation surveys do not provide taxon names at infraspecific level, <em>TreeGhatsData</em> includes both the infraspecific taxa mentioned in Western Ghats and the corresponding specific binomial names.</p> <p><em>TreeGhatsData</em> is provided as a CSV file with comma separator.</p> <p><strong>Related references</strong></p> <p>Bremer, B., Bremer, K., Chase, M. W., Fay, M. F., Reveal, J. L., Soltis, D. E., Soltis, P. S., Stevens, P. F., Anderberg, A. A., Moore, M. J., Olmstead, R. G., Rudall, P. J., Sytsma, K. J., Tank, D. C., Wurdack, K., Xiang, J. Q. Y. & Zmarzty, S. (2009) An update of the Angiosperm Phylogeny Group classification for the orders and families of flowering plants: APG III. Botanical Journal of the Linnean Society, 161, 105-121.</p> <p>Nayar, T., Rasiya Beegam, A. & Sibi, M. (2014) Flowering plants of the Western Ghats, India, Volume 1 Dicots; Volume 2 Monocots. Jawaharlal Nehru Tropical Botanic Garden and Research Institute.</p> <p>Ramesh, B. & Pascal, J.-P. (1997) Atlas of endemics of the Western Ghats (India): distribution of tree species in the evergreen and semi-evergreen forests. French Institute of Pondicherry, Pondicherry, India.</p>
Majadas de Tietar: Ecosystem level and understorey carbon, water, and energy fluxes in a Mediterranean tree-grass ecosystem
<p>This dataset contains a subset of measurements collected at the experimental site Majadas de Tietar. We collected ecosystem level and understorey carbon, water, and energy fluxes in a Mediterranean Savanna using the eddy covariance technique and a series of meteorological sensors for the time period December 2015 - February 2018. The dataset is used for the development of a series of R packages including 'bigleaf' (Knauer et al., 2018).</p> <p>The experimental site is collected in Majadas de Tietar (Casals et al., 2009) located in western Spain (39°56′25″N 5°46′29″W). The ecosystem is a typical “Iberic Dehesa”, which is characterized by an herbaceous stratum of native pasture and sparse trees, for the majority (~98%) Quercus ilex. The tree density is about 20–25 trees/ha, the fractional cover of trees is about 20%, mean DBH of 46 cm, and a canopy height of about 8 m. (El-Madany et al., 2018). The herbaceous layer is composed of native annual species of the three main functional plant forms (grasses, forbs and legumes), whose fractional cover varies seasonally and is characterized by important inter-annual variations in the seasonal dynamics related to the onset of the dry period.</p> <p>Fluxes were measured with the eddy covariance technique with two different systems, one at ecosystem scale to characterize the fluxes of the whole ecosystem (15.5 m above ground), and one at 1.65 m above ground in an open space to measure the fluxes of the well-established understory grass layer.</p> <p>The description of the set-up, equipment and processing used to calculate ecosystem scale fluxes are described in El-Madany et al., (2018), while for the understory tower can be found in Perez-Priego et al., (2017).</p> <p>The dataset is composed of two files: 'ESLMa_MainTower', which is the ecosystem eddy covariance system, and 'ESLMa_SubCanopy', which is the understory eddy covariance system. The dataset contains half-hourly, processed eddy covariance of the ecosystem and understory tower, as well as the main biometeorological data used in the big-leaf package (net radiation, soil heat fluxes, horizontal wind velocity, atmospheric pressure, precipitation, air temperature). All the processing was conducted with EddyPro software (version 5.2.0, LI-COR Biosciences Inc., Lincoln, NE, USA) and the ustar filtering, gap-filling and partitioning with the R package REddyProc (Wutzler et al., 2018). The variables and the units are described in the Readme.txt file released with the dataset.</p> <p><strong>References</strong></p> <p>Casals, P. et al., 2009. Soil CO2 efflux and extractable organic carbon fractions under simulated precipitation events in a Mediterranean Dehesa. Soil Biol. Biochem. 41, 1915–1922. <a href="https://doi.org/10.1016/j.soilbio.2009.06.015">https://doi.org/10.1016/j.soilbio.2009.06.015</a>.</p> <p>El-Madany, T.S.,et al., 2018. Drivers of spatio-temporal variability of carbon dioxide and energy fluxes in a Mediterranean savanna ecosystem 21. <a href="https://doi.org/10.1016/j.agrformet.2018.07.010">https://doi.org/10.1016/j.agrformet.2018.07.010</a></p> <p>Knauer, J., et al., 2018. bigleaf - An R package for the calculation of physical and physiological ecosystem properties from eddy covariance data. PLOS ONE, doi:10.1371/journal.pone.0201114</p> <p>Perez-Priego O, et al., 2017. Evaluation of eddy covariance latent heat fluxes with independent lysimeter and sapflow estimates in a Mediterranean savannah ecosystem. Agricultural and Forest Meteorology. 236: 87-99. doi: 10.1016/j.agrformet.2017.01.009.</p> <p>Wutzler, T., et al., 2018. Basic and extensible post-processing of eddy covariance flux data with REddyProc. Biogeosciences Discuss., p. 1-39.</p> <p> </p>
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>
Long-term (1935-2019) tree population data from remeasurements of a large network of permanent study plots in old-growth forest, Dukes Research Natural Area, Marquette Co., MI, USA
The Dukes Research Natural Area (Hiawatha National Forest, Marquette Co., MI) amounts to ca. 100 ha of minimally disturbed original forests, including a mix of mesic 'hemlock-northern hardwood' types and peaty wetlands dominated by several species of swamp conifers and black ash (Fraxinus nigra). The RNA hosts a regular grid of 250 0.2-acre (~0.08 ha) permanent monitoring (CFI) plots. This package includes tree censuses for subsets of CFI plots conducted in 1935, 1948, and 1974-1980, and repeated censuses with mapped stems from 1989 to 2019. This 84-year record constitutes one of the longest repeated-measurement, permanent-plot data-sets for old-growth temperate forest.
Life History Traits of Resprouting Puerto Rican Tropical Dry Forest Trees, Guánica Forest, 1981-2018
This dataset provides trait and demographic data for 44 tropical dry forest tree species from the Guánica State Forest in southwest Puerto Rico. The study area spans 4,500 ha of semi-deciduous TDF, where the sampled species represent over 90% of all individuals with a diameter at breast height (dbh) ≥2.5 cm. The dataset integrates ten functional traits, combining newly collected measurements (2017–2018) with previously published data (Vargas et al. 2021b). Previously published data includes xylem-specific hydraulic conductivity (ks), Huber value (hv), and hydraulic safety margin (HSM), with species-level data availability ranging from 19 to 44 species, except for HSM, which was measured for six species. Trait measurements were primarily collected during the wet season (August–November), except stomatal behaviour traits (psimax, psidv, and gsmax), which were assessed during the winter dry season before leaf fall. Demographic data encompass species-specific growth rates and annual survival rates for adult trees, derived from four permanent census plots (625 m² to 10,000 m²) distributed across the forest. These plots, established in mature upland TDF on limestone substrates with mollisol soils, were monitored between 1992 and 2019. Growth rate estimates are based on diameter increments recorded at regular censuses over 20.4–26.4 years. Survival rates were calculated over a 21-year period (1998–2019), mitigating the influence of extreme drought events. Standardised measurement protocols ensured data consistency, including repeated diameter assessments at multiple stem locations and the exclusion of wet-season measurements to prevent water-related swelling artifacts. Growth rates were derived from the regression slope of dbh against time, incorporating a minimum of two dbh measurements per individual (following Poorter et al. 2010). Annual survival rate was calculated over a 21-year timespan (1998–2019) to avoid bias introduced by an intense drought in 1997. The followin
Impact of Snowmelt Timing and Tree Proximity on Dutchman's Breeches Phenology and Performance in Mont Megantic National Park (Quebec, Canada; 2018-2019)
Data herein were collected in 2018 and 2019 in Mont Megantic National Park, Quebec, Canada, in a sugar maple-dominated temperate deciduous forest. Individuals of Dutchman's breeches (Dicentra cucullaria), a common understory spring ephemeral plant that is only active in the spring, were transplanted into a fully factorial experiment of snowmelt timing (early vs. late) and tree proximity (near vs. far) to determine the role of thaw circle formation in the local clustering of this species near canopy tree trunks. Plant phenology (emergence, senescence, and growing season length) and performance (stem abundance and leaf area) were tracked during two years of snow manipulation. Additionally, microclimate temperature data were collected in a subset of plots in 2018.
Crown Traits of Broadleaf Deciduous Trees at NEON Forest Sites (2018-2022)
Using NEON Airborne Observation Platform (AOP) measurements collected in 2018-2022 from nine broadleaf deciduous NEON forest sites, we quantified a broad suite of structural metrics and spectral reflectance indices for 305 tree crowns that were delineated in the field by NEON and met our data quality criteria. For each tree crown, we used 1-m^3 voxelated AOP LiDAR data to compute structural metrics, including plant area index (PAI), leaf area index (LAI), top rugosity, maximum canopy height (MAXCH), mean outer canopy height (MOCH), rumple, accumulative plant area density and accumulative LiDAR intensity at multiple tree heights. We used AOP imaging spectrometer to compute several spectral indices, including NDVI, NIRv, EVI, NDWI and chlorophyll index of red edge/green. The data are suitable for ecophysiological studies at tree crown and/or species level. The broad spatial extent allows for the exploration of variability in structure and function of common north American tree species across wide environmental gradients.
Leaf Angle of North America Broadleaf Deciduous Trees: 2021 - 2023
Leaf angle, defined as the angle between the leaf normal (perpendicular to the leaf surface) and the zenith, strongly influences albedo, photosynthesis, and evapotranspiration. We installed remote time-lapse cameras mounted level with the sunlit treetops at each of the ten National Ecological Observatory Network (NEON) tower to measure and track seasonal changes of leaf angle for 11 tree species across three years of 2021, 2022 and 2023. We measured the (x, y) coordinates of each leaf’s petiole and tip and tracked their changes over time on a weekly basis. From these coordinates, we computed the leaf angle for each leaf throughout the growing season across three years of weekly observations.
Environmental Data for Soil, Leaf, and Root samples Boston Street Trees and Massachusetts Rural and Urban Forests in Summer 2021
This dataset provides detailed environmental and tree-level data and metadata for over 850 samples collected from 91 trees across an urban-to-rural gradient in Massachusetts. The dataset captures key variables characterizing urban environmental gradients, including soil moisture, pH, temperature, and nitrogen availability. Tree-level attributes include species identification, diameter at breast height (DBH), and growth rate based on previous tree census data. Geographic coordinates and site-specific context (urban forest, rural forest, street tree, forest edge, forest interior) are included to enable spatial analyses. The microbial sequence data associated with this environmental metadata can be found in the NCBI SRA under BioProject accession number PRJNA1297772.
Data for: Can fire exclusion zones enhance postfire tree regeneration? A simulation study in subalpine conifer forests
Postfire tree regeneration in forests adapted to infrequent, stand-replacing fire is compromised by climate change and novel fire regimes. We used the individual-based forest simulation model iLand to ask whether mimicking spatial patterns of historical fire mosaics can sustain tree regeneration in a warmer future with more fire. We simulated forest and fire dynamics in Grand Teton National Park under four different climate scenarios, and with eight different scenarios (i.e. spatial configurations) of "fire exclusion zones" (Fx zones). Data were simulated for 2020 - 2100 period, and analyzed early (2026-2050) and late (2076-2100) in the simulation. Here, we present these simulated data and R-scripts to reproduce analyses presented in the associated manuscript (Keller et al. 2025, Ecological Applications). Specifically, our data deposit reproduces analyses for 1) differences in regeneration among scenarios at two different times in the simulation, 2) spatial patterns of regeneration in 2100 as a result of the operational fire exclusion zone scenario, and 3) supplemental analyses found in the appendixes.
Leslie Holdridge arboretum tree census, La Selva Research Station, Organization for Tropical Studies, Sarapiquí, Heredia, Costa Rica, 1972-2017.
This database is a collection of dendrometric and structural measurements for all the trees in the arboretum, it was compiled through the assessment of 10 census from 1972 to 2017 by O. Vargas and E. Castro for the Organization for Tropical Studies. The 3.5-hectare Holdridge Arboretum is located at La Selva Research Station. Leslie R. Holdridge, the original owner of the property, created the arboretum in 1968. Initially, it was a small cacao grove with an exceptionally rich overstory of native shade trees. To facilitate research in the arboretum, staff later removed the cacao. In 1970, Gary Hartshorn continued to plant seedlings of many native tree species. OTS continues to plant, tag, and measure trees. OTS maintains the arboretum by regular mowing and pruning to facilitate safe access. Courses, natural history visitors, students, and researchers use the arboretum for a wide range of observational studies, manipulations, dendrological practices, and taxonomy classes.
Tree Census Data of Tropical Dry Forest Succession in Permanent Plots at Palo Verde National Park, Costa Rica (1999–2004), Organization for Tropical Studies (OTS)
This data package contains tree census data from eight permanent forest plots established in 1999 across four successional sites within the tropical dry forest of Palo Verde National Park, Guanacaste, Costa Rica (10°21’N, 85°21’W). The plots were established to study forest structure, composition, and successional dynamics under different disturbance histories in the lowland dry forest ecosystem of northwestern Costa Rica. Each site represents a distinct successional stage, ranging from an early grass-dominated field (Jaragua) to an older partially disturbed remnant forest stand (Varillal). Two permanent 50×50 m plots were established at each site and subdivided into 10×10 m subplots. All woody stems with diameter at breast height (DBH) ≥ 10 cm were tagged, identified to species, and spatially referenced using X–Y coordinates within each plot. For multi-stemmed individuals, all stems meeting the diameter threshold were measured separately. Tree diameter, condition, and taxonomic identification were recorded during four measurement campaigns in 1999, 2001, 2002, and 2004. The dataset includes species identity, DBH, measurement year, individual condition, and subplot coordinates for each stem. These data provide a baseline for understanding forest regeneration, mortality, recruitment, and species composition changes in tropical dry forest succession under varying land-use histories. The dataset represents the historical component of an ongoing long-term monitoring program of forest succession conducted by the Organization for Tropical Studies at Palo Verde National Park, led, developed and supported by Eugenio González since its establishment in 1999.
Tree band growth data taken at BCEF sites (1989 -Present)
This file contains the yearly diameter of select trees within each of the forested LTER control plots. Diameter is calculated from adding the diameter increment based on circumference growth taken from dendrometer bands read each fall.
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.
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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.