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3,136 results for “Terrestrial”
KIC01 Konza Prairie terrestrial arthropods species list
Konza Prairie Terrestrial Arthropods Species List. This species list has been modified since 1977, last modified by Ellen Welti and Anthony Joern in 2014.
Ferns surveys of individuals of terrestrial ferns in Canopy Trimming Experiment (CTE) plots document changes in species richness and abundance over time in response to canopy opening and/or debris deposition
Whole plot surveys of Canopy Triming Experiment (CTE) plots were done to detect changes in the number of terrestrial fern species and individuals in response to canopy opening and debris deposition. Surveys were conducted annually prior to and after treatments. A count of all terrestrial ferns, identified to species on the CTE plots was recorded for each subplot in January during CTE1 (2002-2010) and in the fall during CTE2 (2014-present). The surveys document losses of individuals of shade tolerant fern species and the appearance of open canopy ferns such as the tree fern Cyathea arborea. 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.
Terrestrial gastropods abundance data along an elevational gradient within the Sonadora River watershed
The data set includes 3 files that contain abundance data for terrestrial gastropods along an elevational gradient within the Sonadora River watershed. Two files (1 and 2) contain data from the same transect but differ in the year during which they were collected (2007 and 2008). The third file (3) contains data from a separate elevational transect (sites were located at the same elevation as in files 1 and 2) in palm dominated forest within the same watershed that was collected during the same time period in 2008 as data from file 2. Note: Plots at 250 m of elevation were not sampled in 2008 on either transect and a plot at elevation 750 m in the palm transect was never sampled. 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.
Investigating terrestrial isopod abundance in sandplain grassland using a multiple linear regression
<p>Most North American species of terrestrial isopod (Isopoda) have been introduced from Europe. Sandplain grassland is a globally rare habitat that is abundant on Nantucket Island, Massachusetts and the abundance of terrestrial isopods in the habitat has never been studied. The objective of this project was to develop a model to explain isopod abundance based on vegetation characteristics within Sandplain grassland and use this model to test for land management effects (prescribed burning and mowing) on isopod abundance. I counted terrestrial isopods from 175 pitfall traps set for one week and used multiple linear regression with several selection algorithms to select the best model. The vegetation characteristics I used as regressors do not appear to explain terrestrial abundance well and the final model only contains the percent grass coverage as a regressor. The model suggests that terrestrial isopods decrease in abundance with increasing grass coverage and it explains 29 percent of the data. When management effects are incorporated, the model suggests that mowing significantly increases isopod abundance.</p> <p>Funding for this project came from the Nantucket Islands Land Bank, Nantucket Land Council, and the Nantucket Biodiversity Initiative.</p> <p>Associated vegetation data is in the published "Effects of Sandplain Grassland Management on Spider Richness and Abundance on Nantucket Island" dataset. Sampling methods are in the thesis linked from that dataset.</p> <p>allisopodData.csv - isopod counts by trap<br> dataDictionary.csv - descriptions of variables<br> mckenna-foster_2009.pdf - a report submitted to NBI and used as part of a statistics class at the University of Wisconsin-Green Bay</p> <p> </p>
Dataset for "Changes in Global Terrestrial Live Biomass over the 21st Century"
<p>Live woody vegetation is the largest reservoir of biomass carbon with its restoration considered one of the most effective natural climate solutions. However, carbon fluxes associated with terrestrial ecosystems still remain the largest source of uncertainty of the global carbon balance. Here, we develop spatially explicit estimates of global carbon stock changes of live woody biomass from 2000 to 2019 using measurements from ground, air, and space. We show live biomass has removed 4.9-5.5 PgC yr<sup>-1 </sup>from the atmosphere in this century, offsetting 4.6±0.1 PgC yr<sup>-1</sup> of gross emissions from land-use and environmental disturbances and adding substantially (0.23-0.88 PgC yr<sup>-1</sup>) to the global carbon stocks. Gross emissions and removals in the tropics were four times larger than temperate and boreal ecosystems combined. Although live biomass is responsible for more than 80% of gross terrestrial fluxes, soil, dead organic matter, and lateral transport may play important roles in terrestrial carbon sink.</p>
Terrestrial laser scanning - RIEGL VZ-1000, individual tree point clouds and cylinder models, Belgian hedgerows and tree rows
<p>Terrestrial laser scans were acquired for 69 trees (<em>Quercus robur</em>: 39 trees; <em>Alnus glutinosa</em>: 19 trees; <em>Betula pendula: </em>11 trees) in hedgerows and tree rows in agricultural lands in Flanders, Belgium. We used a RIEGL VZ-1000 terrestrial laser scanner (RIEGL Laser Measurement Systems GmbH, Austria) with a beam divergence of 0.35 mrad operating in the infrared (wavelength 1550 nm) with a range up to 1000 m. We scanned leaf-off and all recorded variables are valid for overbark measurements. Individual trees were manually extracted from the co-registered point cloud in RiSCAN PRO software (provided by RIEGL). To the extracted trees, quantitative structure models (QSM) were fitted. We used the QSMs to derive branch length (m), total wood volume (m³) and merchantable wood volume (m³, using only cylinders with diameter > 7 cm). From the point clouds, we extracted the tree structural features such as crown projection (m²), maximum crown diameter (m) and tree height (m). Biomass expansion factors (BEF) were calculated by dividing total tree volume to merchantable tree volume. We expressed the age dependency of the BEF values via non-linear regression models. See Van Den Berge et al. (2021) for further information (DOI: 10.1007/s12155-021-10250-y).</p>
GTWS-MLrec: Global terrestrial water storage reconstruction by machine learning from 1940 to present
<p>Terrestrial water storage (TWS) includes all forms of water stored on and below the land surface, and is a key determinant of global water and energy budgets. However, TWS data from measurements by the Gravity Recovery and Climate Experiment (GRACE) satellite mission are only available from 2002, limiting global and regional investigation of the long-term trends and variabilities in the terrestrial water cycle under climate change. This study presents long-term (i.e., 1940-2022) and high-resolution (i.e., 0.25°) monthly time series of TWS anomalies over the global land surface. The reconstruction is achieved by using a set of machine learning models with a large number of predictors, including climatic and hydrological variables, land use/land cover data, and vegetation indicators (e.g., leaf area index). The outcome, machine learning-reconstructed TWS estimates (i.e., GTWS-MLrec), fits well with the GRACE/GRACE-FO measurements, showing high correlation coefficients and low biases in the GRACE era. We also evaluate GTWS-MLrec with other independent datasets such as the land-ocean mass budget, large-scale water balance in 341 large river basins, and streamflow measurements at 10,168 gauges. We find that the proposed approach performs overall as well as or is more reliable than previous TWS datasets. Moreover, our reconstructions successfully reproduce the impact of climate variability, such as strong El Niño events. GTWS-MLrec dataset consists of three reconstructions based on JPL, CSR and GSFC mascons, three detrended and de-seasonalized reconstructions, and six global average TWS series over land areas, both with and without Greenland and Antarctica. Along with its extensive attributes, GTWS_MLrec can support a broad range of applications such as better understanding the global water budget, constraining and evaluating hydrological models, climate-carbon coupling, and water resources management.</p><p>Please cite the reference: <strong>Yin J, Slater L, Khouakhi A, et al. GTWS-MLrec: Global terrestrial water storage reconstruction by machine learning from 1940 to present. Earth System Science Data. 2023.</strong></p><p>For any inquiry about the dataset, welcome to contact Dr. Jiabo Yin (jboyn@whu.edu.cn).</p>
High-resolution, Decadal to Weekly Geomorphic Change Analysis of the Elbow River in Calgary, using Multi-temporal Lidar and Repeat Terrestrial Laser Scanning
<p>This directory contains files related to the scientific research project of Luc van Dijk at the Department of Earth, Energy, and Environment, University of Calgary. The project title is "High-resolution, Decadal to Weekly Geomorphic Change Analysis of the Elbow River in Calgary, using Multi-temporal Lidar and Repeat Terrestrial Laser Scanning". This project in the field of geomorphology was a collaboration between the University of Calgary and Utrecht University in the Netherlands. The project was completed on October 27, 2023. Below is a description of the files in this directory.</p><p> </p><p><strong>DisplacementVolumeDistributions_TLS.xlsx</strong></p><p>Excel file containing tabular data of the normalized sediment displacement volumes that were obtained using TLS. Each tab in the Excel file represents a period of interest in 2023. The data in this file were used to generate the 'histogram-like' figures in the report.</p><p> </p><p><strong>DoD_rasters.zip</strong></p><p>Folder containing the aerial lidar DEMs of Difference (DoDs) for each period of interest. The DoDs are 'waterless', i.e. the water surface is masked. The suffix of the file name before the file extension (e.g., ..._10cm.tif) indicates the maximum REM value that was used for the automated masking of the water surface extent (see report section 3.1.2). If the file name contains "large", it refers to the upstream greater area (see report section 3.1.3).</p><p>Within this folder is another folder called 'Clipped2AOIs'. This folder contains the same DoDs, but covering only the extents of the sites of interest ('AOIs' = Areas Of Interest).</p><p> </p><p><strong>FilteredPointClouds_TLS.zip</strong></p><p>Folder containing the processed and filtered point clouds that were acquired throughout the summer of 2023 using TLS. These point clouds have been pre-processed and filtered to remove vegetation (see report section 3.2). They are grouped in sub-folders per acquisition date. The filenames are numbered to location, i.e. 'elbow1', 'elbow2', 'elbow3' and 'elbow4'. These correspond to the sites of interest: Glenmore Dam, golf club, Sandy Beach and Riverdale, respectively.</p><p> </p><p><strong>PythonScripts_Discharge_Rainfall.zip</strong></p><p>Folder containing the Python scripts that were made to process the discharge and rainfall data that were sourced from Environment Canada and The City of Calgary (see report section 3.3). The scripts themselves contain descriptions of their purpose.</p><p> </p><p><strong>PythonScripts_DisplacementVolumeAnalysis.zip</strong></p><p>Folder containing the Python scripts that were made to process and analyze the aerial lidar DoDs and the TLS rasterized difference point clouds (M3C2 output). The 'convert2pickle' scripts converted the sizable rasters to smaller pickle files, which were easier and faster to work with. The 'chart' scripts load the data from the pickle files, analyze them and produce the 'histogram-like' figures in the report. The scripts themselves contain descriptions of their purpose.</p><p> </p><p><strong>RainfallDischargeData.xlsx</strong></p><p>Excel file containing the discharge and rainfall data from Environment Canada and The City of Calgary. The data came from different sources in different formats and were combined into this single table.</p><p> </p><p><strong>RasterizedDifferencedPointClouds_M3C2.zip</strong></p><p>Folder containing the rasterized results of the differenced TLS point clouds (M3C2 output) (see report section 3.2.4). The filenames are numbered to location, i.e. 'Elbow1', 'Elbow2', 'Elbow3' and 'Elbow4'. These correspond to the sites of interest: Glenmore Dam, golf club, Sandy Beach and Riverdale, respectively. The numeric sequence in the file name indicates the start and end date of the change analysis in a 'mm-dd' format. The suffixes '_dist', '_unc' and '_sig' refer to the three output layers of the M3C2 algorithm: distance, uncertainty and significance of change. The main files of interest are the '.tif' files. Files sharing the same name, but with different extensions (.tfw, .tif.aux.xml, .tif.xml) are supplementary/auxiliary files for the '.tif' file, generated by ArcGIS Pro.</p><p> </p><p><strong>ScarpsOfInterest_shapefile.zip</strong></p><p>Folder containing a polygon shapefile describing the extents and locations of the sites of interest. The main file of interest is the '.shp' file. The other files with the same name, but different extensions (.cpg, .dbf, .prj, .sbn, .sbx, .shp.xml, .shx) are supplementary/auxiliary files for the '.shp' file, generated by ArcGIS Pro.</p>
Model Outputs for Characterizing the Atmospheric Mn Cycle and Its Impact on Terrestrial Biogeochemistry
<p>Includes the model output files used in calculations regarding the research article "Characterizing the Atmospheric Mn Cycle and Its Impact on Terrestrial Biogeochemistry". Output files contains: 1) surface Mn concentrations, annual; 2) Mn deposition, monthly; 3) soil Mn map; 4) soil Mn "pseudo" turnover time.</p>
Mangrove terrestrial laser scanning (TLS) point clouds and quantitative structural models (QSMs)
<p>Datasets for a publication entitled, "Terrestrial laser scanning for the estimation of above ground biomass of mangrove roots by modelling them as inverted trees."</p> <p>See the file "Data dictionary for Mangrove terrestrial laser scanning.pdf" for a description of the datasets included in the zipped folder. </p>
Seasonal Terrestrial Water Load Modulation of Seismicity at the Southeastern Margin of the Tibetan Plateau Constrained by GNSS and GRACE Data
<p>Data Set S1. The earthquake catalog is used to decluster aftershocks and background events, and the time range is from July 2004 to July 2021. This data set includes 672585 events in the study area.</p> <p>Data Set S2. Focal mechanism solutions of M ≥ 4 earthquakes at the southeastern margin of the Tibetan Plateau. The data set includes 634 solutions of earthquakes M ≥ 4, and the time range is from 2009 to 2017.</p>
Terrestrial Ecosystem Research Network (TERN) Metadata Profile of ISO 19115-3:2016 and ISO 19157-2:2016
<p>This is the first release of Terrestrial Ecosystem Research Network (TERN) Metadata Profile of ISO 19115-3:2016 and ISO 19157-2:2016. The profile will be used by TERN data editorial system (SHaRED v4).</p>
Point clouds from terrestrial laser scanning from crowns of individual Scots pine trees
<p>Trees adapt to their growing conditions by regulating the sizes of their parts and their relationships. For example, removal or death of adjacent trees increases the growing space and the amount of light received by the remaining trees enabling their crowns to expand. Knowledge about the effects of silvicultural practices on crown size and shape as well as about the quality of branches affecting the shape of a crown is, however, still limited. Laser scanning (or Light detecting and ranging LiDAR) has provided new opportunities for characterizing trees in more detail in three-dimensional space. Especially terrestrial laser scanning (TLS) has increasingly been used in producing a variety of tree attributes. This data set includes 3D reconstruction of crowns of Scots pine (<em>Pinus sylvestris</em> L.) trees from sample plots with different thinning treatments. The thinning treatments include two intensities of thinning, three thinning types as well as control (i.e. no thinning treatment since the establishment). This data set can be used in developing point cloud processing algorithms for single tree crown characterization and for investigating variation in crown size and shape as well as the effects of various thinning treatments on crown size and shape of Scots pine trees grown in boreal forests.</p>
Dataset: Halving of Swiss glacier volume since 1931 observed from terrestrial image photogrammetry
<p>This is supplementary data for the article currently in review for The Cryosphere, titled "Halving of Swiss glacier volume since 1931 observed from terrestrial image photogrammetry".</p> <p><a href="https://doi.org/10.5194/tc-2022-14">See the preprint here</a></p> <p> </p>
Intraspecific variation in the sensitivity of bees to pesticides: a comparative analysis in Bombus terrestris and Osmia bicornis
<p>These files describe the archived CSV files associated with the publication "Intra-specific variation in sensitivity of Bombus terrestris and Osmia bicornis to three pesticides"</p> <p>By Alberto Linguadoca, Margret Jürison, Sara Hellström, Edward A. Straw1, Peter Šima, Reet Karise, Cecilia Costa, Giorgia Serra, Roberto Colombo, Robert J. Paxton, Marika Mänd, Mark J. F. Brown<br> </p>
Hourly LC impacts - Terrestrial Eutrophication - current mix and future scenarios, average demand
<p>Dataset on LCA results of electricity generation and supply in Italy for 2018, 2019 and 2020 (current mix) and two future scenarios (2030) - Terrestrial Eutrophication, average demand perspective.</p> <p>Modelling materials and methods are described in the paper "Life-cycle assessment of current and future electricity supply in Italy: addressing average and marginal hourly demand".</p>
GRAiCE: Terrestrial water storage anomalies reconstructions
<p>Terrestrial Water Storage (TWS) is the total amount of freshwater stored on and below the Earth’s land surface, including surface water, groundwater, soil moisture, snow, and ice. As a result, TWS is a crucial variable of the global hydrologic cycle, representing an essential indicator of water availability.</p> <p>Since 2002, the Gravity Recovery and Climate Experiment (GRACE) mission and its follow-on (GRACE-FO) have been measuring temporal and spatial variations of TWS, namely the Terrrestrial Water Storage Anomalies (TWSA), enabling the monitoring of global hydrological changes over the last two decades. However, the lack of observations prior to 2002 along with the temporal gaps in GRACE/GRACE-FO time series limit our understanding of long-term variations of global freshwater availability.</p> <p>In this study, we use Long Short-Term Memory (LSTM) and Bidirectional LSTM (BiLSTM) neural networks and two sets of predictors to develop four global monthly reconstructions of TWSA from 1984 to 2021 at 0.5º spatial resolution (GR<em>Ai</em>CE). The first set of predictors is given by a combination of five fundamental meteorological forcings and data on vegetation dynamics, whereas the second set of predictors includes the five meteorological forcings only. Specifically, the meteorological predictors are monthly averaged data of total precipitation, snow depth water equivalent, surface net solar radiation, surface air temperature, and surface air relative humidity. We derive data on vegetation dynamics from a long-term reconstruction of solar-induced fluorescence (SIF), which represents a proxy for photosynthesis. Each model is trained with monthly TWSA data from the GRACE JPL mascon dataset. The GR<em>Ai</em>CE dataset accurately reproduces GRACE/GRACE-FO observations at the global scale and across different climatic regions. Moreover, we found that our models predict observed TWSA better than a previous reference reconstruction and produce reliable estimates of the water budget at the river basin scale. Beyond generating long-term continuous TWSA time series, our models allow us to detect and examine TWS changes due to climate variability/change.</p> <p>This repository contains the GR<em>Ai</em>CE dataset and includes four files in netCDF format. The dataset provides monthly TWSA estimates from 1984 to 2021 at a 0.5º spatial resolution. TWSA values are expressed in terms of cm of equivalent water thickness. GRAiCE_LSTM.nc and GRAiCE_BiLSTM.nc files contain TWSA reconstructions obtained from LSTM and BiLSTM models fed with all predictors (i.e., including SIF data), respectively. GRAiCE_LSTMnoSIF.nc and GRAiCE_BiLSTMnoSIF.nc files contain TWSA reconstructions obtained from LSTM and BiLSTM models fed with meteorological forcings only (i.e., without SIF data).</p>
Data for "Excitation of Low- and High-frequency Magnetosonic Whistler Waves Associated with SLAMS in the Terrestrial Foreshock" by Yao et al.
<p>The database includes the plasma data used in instability analyses and the theoretical analysis results based on the linear model.</p> <h3>Captions:</h3> <div><strong>Plasma_input.mat</strong> file is the plasma data used in the instability analyses, which is used to plot Figure 2a-2d.</div> <ul> <li><strong><em>B</em></strong>: magnetic field strength</li> <li><strong><em>n</em></strong>: plasma number density</li> <li><strong><em>Te_para</em></strong>: parallel electron temperature</li> <li><strong><em>Te_perp</em></strong>: perpendicular electron temperature</li> <li><strong><em>Tp</em></strong>: proton temperature</li> </ul> <div> </div> <div><strong>WWs_theo_predictions.mat</strong> file is the calculation result of linear growth rate and wave frequency. The results are used to plot Figure 2e and 2f.</div> <ul> <li><strong><em>f_theo</em></strong>: wave frequency in theoretical predictions</li> <li><strong><em>gamma_theo</em></strong>: growth rate in theoretical predictions</li> </ul>
CarniTraits: Functional traits of the worlds Late Quaternary terrestrial mammalian predators
<p><em>CarniTraits, </em>a comprehensive functional trait database of all late Quaternary (~130,000 ybp) terrestrial mammalian carnivore species (149 species, >1kg body mass). The database contains the body mass, diet, locomotion, cooperative hunting, hunting habitat, hunting method, bone use, and hunting temporal activity patterns of all carnivores over the last ~130,000 years. We also include the IUCN status for all extant species and ground the database in a modern phylogeny and is thus compatible and easily interlinked with range maps published in PHYLACINE v1.2.1. CarniTraits is broadly applicable to assisting in local and macroecological studies, meta-analytic research, global syntheses, and paleoecological research.</p> <p><em>CarniTraits</em> includes data on:</p> <ul> <li>Body Mass</li> <li>Diet</li> <li>Scavenging behaviour</li> <li>Bone Consumption</li> <li>Locomotion</li> <li>Cooperative hunting</li> <li>Hunting habitat</li> <li>Hunting method</li> <li>Hunting time</li> <li>Brain mass</li> <li>Encephalisation Quotient</li> </ul> <p>Each of these traits is fundamental to the ecological impact that carnivores have on terrestrial ecosystems. Trait data compiled represents the best available knowledge on the functional traits of late Quaternary hypercarnivorous mammals. As such, <em>CarniTraits</em> provides a tool for the analysis of carnivore functional diversity both past and present, as well as their effects on ecosystem dynamics.</p> <p>Each trait is accompanied by columns that describes the confidence in the data (notes), whether it was inferred and what level it was inferred from and the reference that the data was collected from.</p>
Terrestrial water storage changes across the contiguous United States from GPS and GRACE, 2007–2017
<p>In this dataset, we provide terrestrial water storage anomalies (TWSA) from 2007-2017 at weekly time scales derived using Global Positioning System (GPS) displacements, further constrained by lower-resolution TWSA observations from the Gravity Recovery and Climate Experiment (GRACE).</p> <p>There are six fields in the HDF5 product provided here:</p> <ol> <li>'/cmwe', which provides terrestrial water storage in units of cm. of water equivalent.</li> <li>'/latitude', latitude at the center of each 0.5 degree grid cell</li> <li>/longitude', longitude at the center of each 0.5 degree grid cell</li> <li>'/time', time in days since January 1st, 2007. The resolution of our time series is weekly, and the first day in our record is January 3rd, 2007.</li> <li>'/signal_to_noise_ratio', the variance of the signal divided by variance of noise for each grid cell in the dataset. Please read the supplementary information document in the paper below for more details.</li> <li>'/uncertainty', 95% confidence interval for each grid cell in the dataset. Please read the supplementary information document in the paper below for more details.</li> </ol> <p>As a condition of using these data, we request that you acknowledge the authors of this data set by citing the following peer-reviewed publication. </p> <p>Adusumilli, S., Borsa, A. A., Fish, M. A., McMillan, H. K., & Silverii, F. (2019). A decade of water storage changes across the contiguous United States from GPS and Satellite Gravity. <em>Geophysical Research Letters</em>, 46, 13006-13015. <a href="https://doi.org/10.1029/2019GL085370">https://doi.org/10.1029/2019GL085370</a></p>
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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.