Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
9,204
datasets available to search
ShareScore release 0.7.1
Dataset results
9,204 results for “tree”
Tree survey: Effect of Burning Patterns on Vegetation in the Fish Lake Burn Compartments
This study examines the effects of long-term prescribed burning treatments on vegetation structure and composition, productivity, and nutrient cycling in upland oak savanna and woodland vegetation. The basis for the study is an ongoing, experimental prescribed burning program begun in 1964 at Cedar Creek, and a similar program operating since 1962 on the adjacent Helen Allison Savanna property (owned by The Nature Conservancy). These prescribed burning programs are designed to subject upland oak communities (and some old fields) to different burn frequencies and patterns of burning, with the ultimate objectives of 1) restoring and maintaining the historically important savanna and open woodland vegetation, and 2) providing information about the effects of different burning patterns on vegetation structure and composition. This study addresses the latter of these two purposes and expands on it by also investigating possible influences of fire on resource availability (nutrients, water, and light) and net primary productivity. This study represents a continuation and expansion of experiments 015 and 094.
Tree survey:Effects of Long Term Fertilization and Oak Canopy Cover on Plant Communities and Ecosystem Processes
In 1996 E142 was established in field D on top of the E004 macroplots. E004 was conducted in fields A, B, C and D by Dave Tilman. The purpose of E004 was to see what effect NH4NO3 addition has on large areas over a longer period of time with exposure to naturally-occurring levels of herbivory. The nutrient addition treatments in E004, E142 plots have been applied annually since 1982. These experiments, along with others at Cedar Creek, examine the community and ecosystem consequences of chronic nutrient loading.
Tree mortality in Forest and Biodiversity 2: a tree diversity experiment to understand the consequences of multiple dimensions of diversity and composition for long-term ecosystem function and resilience
The Forest and Biodiversity (FAB2) experiment uses native tree species in varying levels of species richness, phylogenetic diversity, and functional diversity planted in 100 m2 and 400 m2 plots at 1 m spacing, appropriate for testing long-term ecosystem consequences. FAB2 was designed and established in conjunction with a prior experiment (FAB1) in which the same set of twelve species was planted in 16 m2 plots at 0.5 m spacing. Both are adjacent to the BioDIV prairie-grassland diversity experiment, enabling comparative investigations of diversity and ecosystem function relationships between experimental grasslands and forests at different planting densities and plot sizes. This data package examines mortality in the first six years of the experiment.
FAB2_sapling_volume_2021-2022 in Forest and Biodiversity 2: a tree diversity experiment to understand the consequences of multiple dimensions of diversity and composition for long-term ecosystem function and resilience
The Forest and Biodiversity (FAB2) experiment uses native tree species in varying levels of species richness, phylogenetic diversity, and functional diversity planted in 100 m2 and 400 m2 plots at 1 m spacing, appropriate for testing long-term ecosystem consequences. FAB2 was designed and established in conjunction with a prior experiment (FAB1) in which the same set of twelve species was planted in 16 m2 plots at 0.5 m spacing. Both are adjacent to the BioDIV prairie-grassland diversity experiment, enabling comparative investigations of diversity and ecosystem function relationships between experimental grasslands and forests at different planting densities and plot sizes. This data package examines mortality in the first six years of the experiment.
fab2_allometry_2016-2022 in Forest and Biodiversity 2: a tree diversity experiment to understand the consequences of multiple dimensions of diversity and composition for long-term ecosystem function and resilience
The Forest and Biodiversity (FAB2) experiment uses native tree species in varying levels of species richness, phylogenetic diversity, and functional diversity planted in 100 m2 and 400 m2 plots at 1 m spacing, appropriate for testing long-term ecosystem consequences. FAB2 was designed and established in conjunction with a prior experiment (FAB1) in which the same set of twelve species was planted in 16 m2 plots at 0.5 m spacing. Both are adjacent to the BioDIV prairie-grassland diversity experiment, enabling comparative investigations of diversity and ecosystem function relationships between experimental grasslands and forests at different planting densities and plot sizes. This data package examines mortality in the first six years of the experiment.
Consequences of non-random tree species loss on litter mass loss, nutrient dynamics, carbon cycling, and decomposer communities across a terrestrial-aquatic interface at Coweeta Hydrologic Lab, Otto, NC
Although litter decomposition is a fundamental ecological process, most of our understanding comes from studies of single-species decay. Recently, litter-mixing studies have tested whether monoculture data can be applied to mixed-litter systems. These studies have mainly attempted to detect non-additive effects of litter mixing, which address potential consequences of random species loss. The focus is not on which species are lost, but the decline in diversity per se. Under global change, species loss is likely to be non-random, with some species more vulnerable to extinction than others. Under such scenarios, the effects of individual species (additivity) as well as of species interactions (non-additivity) on decomposition rates are of interest. To examine potential impacts of non-random species loss on ecosystems, we studied additive and non-additive effects of litter mixing on decomposition. A full-factorial litterbag experiment was conducted using four deciduous leaf species, from which mass loss and nitrogen content were measured. Data were analysed using a statistical approach that first looks for additive identity effects based on the presence or absence of species and then significant species interactions occurring beyond those. It partitions non-additive effects into those caused by richness and or composition.
Water flow velocity data, Shark River Slough (SRS) near Chekika tree island, Everglades National Park (FCE LTER) from January 2006 to March 2021
Water velocity data measured every 5 or 15 minutes in Shark River Slough beside Chekika tree island, Everglades National Park, using Sontek Agronaut water flow sampler. Data collection is complete.
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
Biomass accumulation in trees and downed wood at Bartlett Experimental Forest, Hubbard Brook Experimental Forest, the Bowl Natural Research Area, and the White Mountain National Forest, NH, USA
Standing trees and downed wood were inventoried in all of the chronosequence stands in the White Mountains, New Hampshire to characterize biomass. Live and standing dead trees were inventoried in the chronosequence stands in 1994, 2004, 2012, and 2021. Coarse (≥ 7.6 cm diameter) and fine woody debris (3.0 – 7.6 cm) were inventoried at the same stands in 2004 and 2020. Twigs (FWD < 3.0 cm) were inventoried in 2004 and 2020. The Bowl and Mt. Pond old-growth sites were inventoried (standing trees and downed wood) in 2021.
Ten-year interval tree-remeasure of a Northern Hardwood Forest: Bird Area, 1981 - ongoing, Hubbard Brook Experimental Forest
These data depict change in the northern hardwood forest at mid-elevation (360-680 m a.s.l.) over 40 years from 1981 – 2021. The data set includes 7443 trees over time. During this period, there was no trend in basal area or biomass, but there was a decrease in tree density and diversity and an increase in quadratic mean diameter. 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.
Short-term disappearance of foliar litter of three tree species native to rain forest of Puerto Rico
Litter disappearance was examined before (1989) and after (1990) Hurricane Hugo in the Luquillo Experimental Forest, Puerto Rico using mesh litterbags containing abscised Cyrilla racemiflora or Dacryodes excelsa leaves or fresh Prestoea montana leaves. Biomass and nitrogen dynamics were compared among: i) species; ii) mid- and high-elevation forest types; iii) riparian and upland sites; and iv) among pre- and post-hurricane disturbed environments. Biomass disappearance was compared using multiple regression and negative exponential models in which the slopes were estimates of the decomposition rates subsequent to apparent leaching losses and the y-intercepts were indices of initial mass losses (leaching). C. racemiflora leaves with low nitrogen (0.39 %) and high lignin (22.1 %) content decayed at a low rate and immobilized available nitrogen. D. excelsa leaves had moderate nitrogen (0.67 %) and lignin (16.6 %) content, decayed at moderate rates, and maintained the initial nitrogen mass. P. montana foliage had high nitrogen (1.76 %) and moderate lignin (16.7 %) content and rapidly lost both mass and nitrogen. There were not significant differences in litter disappearance and nitrogen dynamics among forest types and slope positions. Initial mass loss of C. racemiflora leaves was lower in 1990 but the subsequent decomposition rate did not change. Initial mass losses and the overall decomposition rates were lower in 1990 than in 1989 for D. excelsa. D. excelsa and C. racemiflora litter immobilized nitrogen in 1990 but released 10-15% of their initial N in 1989, whereas P. montana released nitrogen in both years (25-40 %). Observed differences in litter disappearance rates between years may have been due to differences in the timing of precipitation. Foliar litter inputs during post-hurricane recovery of vegetation in Puerto Rico may serve to immobilize and conserve site nitrogen. Support for this work was provided by grants BSR-8811902, DEB-9411973, DEB-9705814 , DEB-00
El Yunque Chronosequence Tree Census data
The El Yunque Chronosequence plots consist of four sites, El Verde 1 (EV1), Sabana 1 (SB1), Sabana 2 (SB2), and Sabana 3 (SB3), which are located at the edges of El Yunque National Forest at sites to the south of El Verde and Sabana Field Stations. The plots represent a range of successional stages representing areas in agriculture or recently abandoned in 1936 but reforested after 1950, and areas in agriculture or recently abandoned in 1977 and reforested since that time. They range in size from ~0.5 to 1 ha, vary in elevation from ~150m to 550m a.s.l. and span a wide range of ages and land use histories (Table 1). Plot Name Size Age Elevation EV1 10,000 m2 (1 ha) >62 yrs but < 76 yrs ~ 550m SB1 4,625 m2 (~0.5 ha) >62 yrs but not primary forest ~100-150m SB2 6,400 m2 (~0.6 ha) >35 yrs but < 62 yrs ~100-150m SB3 4,800 m2 (~0.5 ha) Primary forest ~100-150m One of these plots (EV1) is south of El Verde Field Station, on Forest Service land just over the property boundary.  This area was in agriculture in 1936 but appeared forested in a 1950 aerial photograph, and there are differences in forest structure and species composition consistent with the known differences in land use history. The other three Chronosequence sites are just south of the Sabana Field Station on Forest Service Land on the opposite side of the forest from El Verde. One plot (SB2) is located in young secondary forest in an area immediately adjacent to an old teak plantation forest. Another plot (SB1) is located in an area that was sparsely forested in 1936 and which appeared reforested in 1950. The third plot in Sabana (SB3) is located in a patch of primary “tabonuco†(named for the abundance of this tree species) forest on a steep slope on the west side of the Sabana River. Support for this work was provided by grants BSR-8811902, DEB-9411973, DEB-9705814 , DEB-0080538, DEB-0218039 , DEB-0620910 , DEB-1239764, DEB-1546686, and DEB-1831952 from the National Science Foundati
Tree damage by Hurricane Hugo on the Luquillo Forest Dynamics Plot (LFDP), Puerto Rico
Hurricane Hugo struck the Caribbean national forest in September 1989. Files LFDP_HURRDAM.TXT and LFDP_HURRDAMa.TXT contain data on the damage to trees caused by the hurricane collected by Mr. R. DeLeon between August 1990 and September 1991. Mr. DeLeon walked throughout the plot to find stems >= 10 cm diameter that had apparently been damaged or killed by the hurricane in an effort to collect information before the damaged stems rotted. The information on these stems was later combined with the results of the first census to reconstruct the forest, as it would have appeared, at the time of Hurricane Hugo. This file contains the hurricane damage data collected for stems damaged by Hurricane Hugo combined with data for the stems recorded subsequently in the first complete LFDP census starting in 1990. Some stems that were measured in Census 1 survey 2 and survey 3 or Census 2 that were believed to have been missed in Census 1 survey 1, are also included (see census history above) and are assumed to have been undamaged by Hurricane Hugo. The structure of the data files is the same for both files LFDP_HURRDAM.TXT and LFDP_HURRDAMa.TXT but the diameter of the trees in LFDP_HURRDAMa.TXT have been calculated by extrapolating diameters backwards from subsequent measurements to the time of the Census 1 survey 1. Diameters in file LFDP_HURRDAMa.TXT can not be used for growth measurements. For our publications we treat files LFDP_HURRDAM.TXT and LFDP_HURRDAMa.TXT as one data set. The National Science Foundation requires that data from projects it funds are posted on the web two years after any data set has been organized and "cleaned". The data from each census of the LFDP will be updated at intervals as each survey of the LFDP shows errors in the previous data collection. After posting on the web, researchers who are not part of the project are then welcome to use the data. Given the enormous amount of time, effort and resources required to manage the LFDP, obtain these d
Tree Map for Census at the Luquillo Forest Dynamics Plot (LFDP), Puerto Rico
This data set shows the Tag number, Quadrat location, Species code, diameter and XY coordinates of stems >=10 cm D130 present at the time of Hurricane Hugo and in the first census. The data set is composed of two files both with the same file structure. In LFDP_C1treemap.txt the diameters (Fdiam) are as recorded in the field data. In LFDP_C1TREEMAPa.txt the stem diameters (Fdiam) were calculated to allocate "missed" stems (stems >=10 cm D130) that were found in survey 2, 3 or Census 2 to Census 1 survey 1. We calculated the diameter the stem would have had, if it had been recorded at the same time the quadrat it was located in was assessed, in the appropriate survey for that stem size. To extrapolate the stem size back in time, we used the actual growth rate of that individual stem if more than one measurement was available. If only one diameter measurement was available we used the median growth rate for that species in the appropriate size class stems >=10, <30 cm D130). In our publications we will combine data sets LFDP_C1treemap.txt and LFDP_C1TREEMAPa.txt to make Census 1 and to reconstruct the forest for stems >= 10 cm D130 at the time of Hurricane Hugo. We have divided the data into two separate files to ensure that when stem diameters are compared to future censuses the diameter data in LFDP_C1TREEMAPa.txt are not used to calculate growth rates. The last corrections to the Census 1 data were made in May 2001. The National Science Foundation requires that data from projects it funds are posted on the web two years after any data set has been organized and "cleaned". The data from each census of the LFDP will be updated at intervals as each survey of the LFDP shows errors in the previous data collection. After posting on the web, researchers who are not part of the project are then welcome to use the data. Given the enormous amount of time, effort and resources required to manage the LFDP, obtain these data, and ensure data accuracy, LFDP Princi
Phenologies of the Tabonuco Forest trees and shrubs
These data are being used to, among other things, (1) determine the seasonality of flowering and fruiting in Tabonuco forest and test hypotheses concerning the causation of seasonality (or lack thereof), (2) test the effect of annual variation in rainfall and other climatic variables on seed and fruit production of individual species, and (3) compare the relative dispersal of species on the Luquillo Forest Dynamics Plot by applying information on the spatial distribution of canopy trees to the data on seed and fruit fall. These data also serve as background information on the flowering and fruiting of individual species. Support for this work was provided by grants BSR-8811902, DEB-9411973, DEB-9705814 , DEB-0080538, DEB-0218039 , DEB-0620910 , DEB-1239764, DEB-1546686, and DEB-1831952 from the National Science Foundation to the University of Puerto Rico as part of the Luquillo Long-Term Ecological Research Program. Additional support provided by the University of Puerto Rico and the International Institute of Tropical Forestry, USDA Forest Service.
Earthworms in tropical tree plantations and secondary forests
We compared patterns of earthworm abundance and species composition in tree plantations and secondary forests of Puerto Rico. Tree plantations included pine (Pinus caribaea Morelet) and mahogany (Swietenia macrophylla King) established in the 1930s, 1960s, and 1970s; secondary forests were naturally regenerated in areas adjacent to these plantations. We found that (1) earthworm density and fresh weight in the secondary forests were twice those in either of the tree plantations, and did not differ between the plantations, and (2) the exotic earthworm species, Pontoscolex corethrurus M ller, dominated both plantations and the secondary forests, but native earthworm species, Pontoscolex spiralis Borges & Moreno, Estherella montana Gates, and E. gatesi Borges & Moreno, occurred only in the secondary forests. Our results suggest that naturally-regenerated secondary forests are preferable to pine and mahogany plantations for maintaining a high level of earthworm density, fresh weight, and native species. Support for this work was provided by grants BSR-8811902, DEB-9411973, DEB-9705814 , DEB-0080538, DEB-0218039 , DEB-0620910 , DEB-1239764, DEB-1546686, and DEB-1831952 from the National Science Foundation to the University of Puerto Rico as part of the Luquillo Long-Term Ecological Research Program. Additional support provided by the University of Puerto Rico and the International Institute of Tropical Forestry, USDA Forest Service.
Settlement Trees, Illinois Level 0, 1804-1849
We provide a Level 0 record of trees in Illinois transcribed from Public Land Surveys conducted by surveyors from the General Land Office of the United States in the 1800s. Posts were set every half mile in townships that were typically 6 miles by 6 miles square. Surveyors recorded details about the one to four trees closest (but typically recorded information for the two closest trees) to the posts and included information about the tree name (taxonomic specificity ranged by surveyor), tree diameter (inches), and distance and bearing from the post. Our records include the tree information and the location of the posts from which the tree information came from. For the msb-paleon.28.0 package, these Level 0 tree data were aggregated to the 8km grid resolution Level 1 product (see msb-paleon.26 package). That product was then statistically smoothed using a statistical model that accounts for zero-inflated continuous data with smoothing based on generalized additive modeling techniques and approximate Bayesian uncertainty estimates for the Level 2 products estimating aboveground biomass (msb-paleon.23), density (msb-paleon.24), and basal area (msb-paleon.25). The data processing steps and associated code are available in the GitHub repository: https://github.com/PalEON-Project/PLS_products. These products are used in the manuscript, Paciorek et al., 2021, The forests of the midwestern United States at Euro-American settlement: spatial and physical structure based on contemporaneous survey data. PLoS ONE 16(2):e0246473 (https://doi.org/10.1371/journal.pone.0246473). This material is based upon work supported by the National Science Foundation under grants #DEB-2213579 and 1241874.
Detailed point cloud data on stem size and shape of Scots pine trees
<p>This data set is comprised of three packed zip files and they include text files of 3D information from terrestrial laser scanning (TLS) and aerial imagery from unmanned aerial vehicle (UAV) from individual Scots pine trees within 27 sample plots from three test sites located in southern Finland.</p> <p>TLS data acquisition was carried out with Trimble TX5 3D laser scanner (Trible Navigation Limited, USA) for all three study sites between September and October 2018. Eight scans were placed to each sample plot and scan resolution of point distance approximately 6.3 mm at 10-m distance was used. Artificial constant sized spheres (i.e. diameter of 198 mm) were placed around sample plots and used as reference objects for registering the eight scans onto a single, aligned coordinate system. The registration was carried out with FARO Scene software (version 2018). Aerial images were obtained by using an UAV with Gryphon Dynamics quadcopter frame. Two Sony A7R II digital cameras were mounted on the UAV in +15° and -15° angles. Images were acquired in every two seconds and image locations were recorded for each image. The flights were carried out on October 2, 2018. For each study site, eight ground control points (GCPs) were placed and measured. Flying height of 140 m and a flying speed of 5 m/s was selected for all the flights, resulting in 1.6 cm ground sampling distance. Total of 639, 614 and 663 images were captured for study site 1, 2, and 3, respectively, resulting in 93% and 75% forward and side overlaps, respectively. Photogrammetric processing of aerial images was carried out following the workflow as presented in Viljanen et al. (2018). The processing produced photogrammetric point clouds for each study site with point density of 804 points/m<sup>2</sup>, 976 points/m<sup>2</sup>, and 1030 points/m<sup>2</sup> for study site 1, 2, and 3, respectively.</p> <p>The sample plots within the three test sites have been managed with different thinning treatments in either 2005 or 2006. The experimental design of the sample plots includes two levels of thinning intensity and three thinning types resulting in six different thinning treatments, namely i) moderate thinning from below, ii) moderate thinning from above, iii) moderate systematic thinning, iv) intensive thinning from below, v) intensive thinning from above, and vi) intensive systematic thinning, as well as a control plot where no thinning has been carried out since the establishment. More information about the study sites and samples plots as well as the thinning treatments can be found in Saarinen et al. (2020a).</p> <p>The data set includes stem points of individual Scot pine trees extracted from the point clouds. More about the method of extraction can be found in Saarinen et al. (2020a, 2020b) and Yrttimaa et al. (2020). The title of the zip file refers to the study sites 1, 2, and 3. The title of the text files includes the information on the test site, the plot within the test site, and the tree within the plot. The text files contain stem points extracted from the TLS point clouds. The columns “x” and “y” contain x- and y-coordinates in a local coordinate system (in meters), in column “h” is the height of each point in meters above ground, and treeID is the tree identification number. The columns are separated by space.</p> <p>Based on the study site and plot number, files from different thinning treatments can be identified by using the information in Table 1 in Saarinen et al. (2020b).</p> <p> </p> <p><strong>References</strong></p> <p>Saarinen, N., Kankare, V., Yrttimaa, T., Viljanen, N., Honkavaara, E., Holopainen, M., Hyyppä, J., Huuskonen, S., Hynynen, J., Vastaranta, M. 2020a. Assessing the effects of stand dynamics on stem growth allocation of individual Scots pines. bioRxiv 2020.03.02.972521. <a href="https://doi.org/10.1101/2020.03.02.972521">https://doi.org/10.1101/2020.03.02.972521</a></p> <p>Saarinen, N., Kankare, V., Yrttimaa, T., Viljanen, N., Honkavaara, E., Holopainen, M., Hyyppä, J., Huuskonen, S., Hynynen, J., Vastaranta, M. 2020b. Detailed point cloud data on stem size and shape of Scots pine trees. bioRxiv 2020.03.09.983973. <a href="https://doi.org/10.1101/2020.03.09.983973">https://doi.org/10.1101/2020.03.09.983973</a></p> <p>Viljanen, N., Honkavaara, E., Näsi, R., Hakala, T., Niemeläinen, O., Kaivosoja, J. 2018. A Novel Machine Learning Method for Estimating Biomass of Grass Swards Using a Photogrammetric Canopy Height Model, Images and Vegetation Indices Captured by a Drone. Agriculture 8: 70. <a href="https://doi.org/10.3390/agriculture8050070">https://doi.org/10.3390/agriculture8050070</a></p> <p>Yrttimaa, T., Saarinen, N., Kankare, V., Hynynen, J., Huuskonen, S., Holopainen, M., Hyyppä, J., Vastaranta, M. 2020. Performance of terrestrial laser scanning to characterize managed Scots pine (<em>Pinus sylvestris</em> L.) stands is dependent on forest structural variation. EarthArXiv. March 5. <a href="https://doi.org/10.31223/osf.io/ybs7c">https://doi.org/10.31223/osf.io/ybs7c</a></p>
Experimental data of the paper "Trial-based Heuristic Tree Search for MDPs with Factored Action Spaces"
<p>This data set contains the code of our planner and of the planner that was used as baseline, the benchmark set that was used to perform experiments as well as the parsed values and basic reports that are reported in the paper. More information can be found in the README that is also included.</p>
Tree measurements and summaries of the field plots used to develop Rojo and Montero (1996) yield tables for Pinus sylvestris L. in central Spain
<p>Tree measurements for principal trees and trees marked for thinning and summaries of the Pinus silvestris L. plots measured for the construction of Rojo and Montero (1996) Pinus sylvestris L. yield tables for central Spain. PRM_Functions.R contains R functions implementing parameter recovery methods to transform Rojo and Montero (1996) Pinus sylvestris L. yield tables into a diameter distribution model.</p> <p><strong>Trees.csv: </strong>Comma separated file with headers in the first row. Each record represents a measured tree. Fields:</p> <ul> <li>"PlotID": Identifier of the plot where the tree was measured</li> <li>"Type": Code indicating if the tree was marked for thinning.</li> <li>"ID_tree" Tree_Identifier</li> <li>"DBH1": First Diameter at breast height measurement for the tree.(mm)</li> <li> "DBH2" Second diameter at breast height measurement for the tree. The second measurement was taken in the direction perpendicular to the first measurement. (mm)</li> <li>"DBHmean": Mean of DBH 1 and DBH 2 <strong>and converted to cm</strong> (cm)</li> </ul> <p><strong>Plot_summaries.csv: </strong>Comma separated file with headers in the first row. Data digitized from Annex II of Rojo and Montero (1996). Each record contains different forest attributes of the plot. Fields:</p> <ul> <li>"PlotID": Identifier of the plot where the tree was measured</li> <li>"Age": Age of the plot determined from tree cores (Years)</li> <li>"Ho" Assman Dominant height for the plot (meters)</li> <li>"SiteIndex": Site index for the plot in meters. Site index is defined as the dominant height in meters measured or expected for the plot for an Age of 100 years.</li> <li>"MeanH" Mean tree height (m)</li> <li>"Dg" Quadratic mean diameter (cm)</li> <li>"Do" Dominant diameter. Mean diameter of the 100 largest trees of a hectare (cm)</li> <li>"N" Stand density (trees per hectare)</li> <li>"G" Plot basal area (m<sup>2</sup>/ha)</li> <li>"V" Total plot volume per unit area (m<sup>3</sup>/ha)</li> <li>"DeltaV" Periodic increment of merchantable volume (m<sup>3</sup>/ha)</li> <li>"Bark" Average percentage of total volume that is Bark. (%)</li> </ul> <p><strong>PRM_Functions.R: </strong>R functions to solve parameter recovery systems of equations based on mean and quadratic mean diameter and dominant diameter, quadratic mean diameter and stand density. Details provided as comments.</p> <p><strong>References</strong></p> <p>Rojo Alberto, Montero G (1996) El pino silvestre en la Sierra de Guadarrama: historia y selvicultura de los Pinares de Cercedilla, Navacerrada y Valsain. Ministerio de Agricultura, Pesca y Alimentación, Secretaria General Tecnica, Centro de Publicaciones, Madrid</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.