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555 results for “Woody”
ReFAB 10,000 Year Statistical Estimate of Aboveground Woody Biomass, Midwest US, Level 2
How terrestrial biomass changed before the advent of industrial society is a major gap in our understanding of the Earth's carbon cycle. Here, we archive data used to reconstruct 10,000 years of aboveground woody biomass across the US Upper Midwest using statistical models based on historical forest surveys and fossil pollen assemblages. From our analyses we document a 5,000 year long carbon sink into vegetation, primarily caused by the range expansion of two late-successional species into the region during the late Holocene. The importance of such large slow-growing tree species in storing carbon during the pre-industrial past argues for protecting similar species in wild forests today. This material is based upon work supported by the National Science Foundation under grants #DEB-1241874, 1241868, 1241870, 1241851, 1241891, 1241846, 1241856, 1241930.
2019-2020 woody plants pollen dataset from automatic particle detector in Šiauliai
<p>Dataset acquired from Rapid-E device by testing it with anemophilous woody plants pollen collected in Lithuania. Data is sorted by pollen type.</p> <p>The sampling methodology can be found in publication "Automatic pollen recognition with the Rapid-E particle counter: the first-level procedure, experience and next steps", Šaulienė Ingrida, et al. Atmospheric Measurement Techniques, 2019, 12.6: 3435-3452. <a href="https://doi.org/10.5194/amt-12-3435-2019">https://doi.org/10.5194/amt-12-3435-2019</a></p> <p>The authors would like to hear from you at realtime@sa.vu.lt if you use this dataset.</p>
Metabarcoding reveals a high diversity of woody host-associated Phytophthora spp. in soils at public gardens and amenity woodlands in Britain
<p>This is the demultiplexed Illumina MiSeq raw sequencing data from two 96-well plates from the following recent publication, shared with permission of the corresponding author, Sarah Green:</p> <p>Riddell <em>et al.</em> (2019). Metabarcoding reveals a high diversity of woody host-associated <em>Phytophthora</em> spp. in soils at public gardens and amenity woodlands in Britain. https://doi.org/10.7717/peerj.6931<br> <br> It consists of 244 gzipped compressed plain text FASTQ format sequence files, grouped into 122 pairs by the widely used R1 and R2 suffix. The files have been renamed to use the anonymised site numbers (1 to 14) as in the paper, see also supplementary table one for site metadata. Additionally there are two negative controls, and positive control DNA mixtures of 10 and 15 species as described in the paper.<br> </p>
Fine woody debris inventory data from reference stands and inventory plots in the Pacific Northwest, 1992 to 2000
These data provide an inventory of the mass of downed fine woody debris stored within various forest types. This data is used to determine total organic matter, carbon, and nutrient stores in forests.
Fire Self-Limitation (FiSL) Experiment: Quantifying Wildfire Carbon Combustion Losses in boreal Deciduous and Mixed Forests in Interior Alaska and the Boreal Cordillera VII: Coarse and Fine Woody Debris Inventory 2022
This dataset contains characteristics of coarse woody debris and snags collected in the field for plots in 8 fire scars in Interior Alaska and the Yukon. Data was collected in the summer of 2022. Fire scars sampled included Shovel Creek (2019), Aggie Creek (2015), Hess Creek (2019), Baker (2015), Munson Creek (2021), Isom Creek (2020), 2019MA014 (2019), and 2019BC005 (2019).
Measurements of Coarse Woody Debris %C and %N at the Coweeta LTER Terrestrial Gradient Sites, Coweeta Hydrological Laboratory, Otto, NC.
Coarse woody debris (CWD) plays a critical role in nutrient retention and cycling, including the cycling and retention of carbon and nitrogen. However, comparison studies of CWD in different forest types and elevation gradients in the southern Appalachian Mountains are lacking. We measured CWD in five different forest communities/elevations at Coweeta Hydrologic Lab. A subsample of CWD in each plot was measured for percent C and percent N, as well as for cations.
Coarse Woody Debris Cations Measurements at the Coweeta LTER Terrestrial Gradient Sites, Coweeta Hydrological Laboratory, Otto, NC.
Coarse woody debris (CWD) plays a critical role in nutrient retention and cycling, including the cycling and retention of carbon and nitrogen. However, comparison studies of CWD in different forest types and elevation gradients in the southern Appalachian Mountains are lacking. We measured CWD in five different forest communities/elevations at Coweeta Hydrologic Lab. A subsample of CWD in each plot was measured for percent C and percent N, as well as for cations.
Measurements of coarse woody debris at 10 hillslope sites at the Coweeta Hyrdological Laboratory, Macon County, North Carolina
Coarse woody debris was measured at 10 hillslope sites representing a gradient of development, including forested, valley agriculture, and mountain housing developments in Macon County, NC. The length, diameters, decay class, and species of coarse wood was measured within each of the twelve 10 x 10-m plots located within each of the 10 sites. Volume of coarse wood was then calculated. Data from a subset of the sites were used as a covariate for Aphaenogaster spp. ant occupancy rates.
FWE01 Effects of browsing and fire on woody encroachment at Konza Prairie
Woody encroachment into grasslands, savannas, and steppes have become a management and conservation concern worldwide because of the ability of woody plants to change ecosystems through decreases in biodiversity, alterations in water and nutrient cycles as well as decreases in forage production and quality. In grasslands, woody encroachment can be categorized into two groups: non-resprouting species that can be killed with fire and resprouting species that cannot be killed with fire. Resprouting species require additional active management strategies to remove them from encroached grasslands. In this study we investigate physiological, population and community effects of continuous browsing and fire on Cornus drummondii, a resprouting woody species. Through monitoring the shrub’s physiology, population and the surrounding plant community composition within these treatments we hope to understand how to best prescribe restoration methods for restoring the tallgrass prairie.
GIS70 Konza Prairie Woody Plant Mapping in Core Watersheds (1D, 20B, and 4B) in 2019
This dataset contains the point and polygon boundaries of shrubs and trees mapped in watersheds 1D, 4B, and 20B from May to August 2019. Datatype one (GIS700) defines the point locations of all trees mapped in these watersheds. Datatype two (GIS701) defines the point locations of all shrubs less than one meter wide in these watersheds. Datatype three (GIS702) defines the boundaries of select shrub species greater than one meter wide in these watersheds. These data are available to download as zipped shapefiles (.zip), and compressed Google Earth KML layers (.kmz).
WER01 Elevated CO2 counteracts effects of water stress on woody rangeland-encroaching species at Konza Prairie
Woody plants are increasing prevalence and dominance in many rangelands around the world. The reason for their increase is various but two common drivers that have changed are an increase in CO2 concentrations and alteration to precipitation dynamics. We asked what the physiological growth dynamics of four juvenile woody plant species (Cornus drummondii, Rhus glabra, Gleditsia triacanthos and Juniperus osteosperma) when grown in elevated CO2 and chronically water stressed. We found that elevated CO2 counteracts much of the physiological effects of chronic water stress in the four different woody plant species measured. The alleviation of water stress from increased CO2 concentrations will result in juvenile woody plants continuing to expand and establish in North American rangelands. This information will aid land managers in making long-term management objectives for reducing woody plants in rangelands.
RIV07 Seeding rates woody removal of a tallgrass prairie stream and riparian zone after a decade of woody vegetation removal
In fall of 2010 in watershed N2B ( 39.088976°, -96.588599°), we established plant community plots to assess the potential ability of the riparian zone to shift to a grassland state based on cutting alone and cutting with replanting. The three treatments were 1) naturally open riparian grassland before the removal, 2) areas cleared of woody vegetation, and 3) areas cleared of woody vegetation and seeded with prairie plant species. The addition of the seeded treatment was designed to address if recovery of grassland vegetation is hindered by propagule limitation. The seeded and non-seeded removal plots were adjacent to each other and randomly assigned. In each community type, there were four plots, each of which was 10 m parallel along and 3 m perpendicular to the stream channel. Each plot had four plant composition transects along which we sampled four one m2 subplots along each transect. Vegetative cover of vascular plant species was determined using a modified Daubenmire scale (Gibson and Hulbert 1987).
WPE01 Assessing the value added of NEON for using machine learning to quantify vegetation mosaics and woody plant encroachment at Konza Prairie
Woody encroachment, or invasion of woody plants, is rapidly shifting tallgrass prairie into shrub and evergreen dominated ecosystems, mainly due to exclusion of fire. Tracking the pace and extent of woody encroachment is difficult because shrubs and small trees are much smaller than the coarse resolution (>10m2) of common remote sensed images. However, the US government has been investing in finer resolution (<2m2) remote sensing through USDA NAIP and the National Ecological Observatory Network (NEON), both of which cost multi-million dollars each year and contain different remote sensed products. We compared two methods of classification (random forests and support vector machines) with these two freely available remotely sensed aerial images to determine if and how much NEON adds to classification accuracy and determine which method of machine learning was more accurate. All models have very high overall classification accuracy (>91%), with the NEON image a few percent more accurate than NAIP. The NEON image significantly relies on canopy height (LiDAR) to make classifications, but the importance of bands is more evenly distributed during NAIP classification. Lastly, accuracy for Eastern Red Cedar specifically is high with NEON (78-84%), compared to the relatively low classification accuracy using NAIP imagery (55-61%).
WES01 Woody encroachment impacts on the subsurface at Konza Prairie
Soil sampling pits across three hillslope positions - toeslope, backslope, and summit - were dug in 2020 in watershed N4D (burned every 4 years) and N1D (burned annually) to characterize the impacts of woody encroachment on subsurface soil physical, chemical, and biological properties. Pits were hand-dug to 120 cm in the toeslope position and to 60 cm deep at the backslope and summit positions. Soil pits in N4D were dug directly under dogwood shrubs (Cornus drumondii) while pits in N1B were dug under grasses and forbs. Soil pit faces were photographed to determine root fractions with depth, soil monoliths were take to charaterize soil macroporosity with depth while soil cores were taken in each horizon for water retention analysis. Soil sensors were also installed at four soil depths at the toeslope position and 3 soil depths at the backslope and summit positions to record half hourly soil moisture, soil temperature, soil water potential, soil electrical conductivity, and soil carbon dioxide, and soil oxygen. In addition, geophysical measurements were taken in N4D using time-lapse electrical resistivity in 2023.
WEE01 Impacts of riparian and non-riparian woody encroachment on tallgrass prairie ecohydrology
Plant xylem water samples were collected from Cornus drummondii (rough-leaf dogwood), Andropogon gerardii (big bluestem), Quercus macrocarpa (bur oak), and Quercus muehlenbergii (chinquapin oak) during the summer of 2016. Soil cores were also collected during the summer of 2016 to collect soil water from the surface to 200 cm depth. Isotope values (δ18O and δ2H) were analyzed for each water sample to determine depth of plant water uptake.
ASS01 Suspended sediments in streams impacted by prescribed buring, grazing and woody vegetation removal at Konza Prairie
To determine effects of rotational burning and riparian vegetation removal on suspended solid concentrations in streams. Two sites are burned with a frequency of 2 (N02B) and 4 (N04D) years and grazed by bison. In 2011, N02B will have woody riparian vegetation removed along the entire stream length. The Shane Creek site (SHAN) is currently ungrazed and burned most years. In 2011 the treatment will be switched to grazing and burning of 1/3 of the watershed every year. The data include before and during-treatment sampling for both experiments.
PWV01 Cover of woody vegetation at Konza Prairie
This data set relates effects of soil, grazing intensity and burning treatments on the establishment and subsequent expansion of woody plants in prairie communities. The locations of woody vegetation are marked on a mylar overlay of an aerial photograph of the area being surveyed with an unique symbol for each species and a number for the size. For trees, size is the height to the nearest meter. For shrubs, the number of stems is recorded as a measure of size if the number is less than 25. For large patches of shrubs, the diameter is recorded and the shape of the patch is drawn on the overlay. Two forms of the data are archived. One of them is the actual mylar sheets. The other form is an electronic ascii data that is stored in the subdirectory woody on the lter Novell server. Files are named according to the name of the watershed and year the data was collected (e.g. 004b86.one = first data file for 004b in 1986). For 1986, the files also exist as coverages in PC ARC/INFO files.
Coarse Woody Debris in Bisley Experimental Forest and the Rio Icacos Basin
Organic matter pools appear to differ in composition between Bisley and Icacos. On average (n=30), 79% of Bisley organic matter was composed of coarse woody debris. Of the remaining 21% organic matter pool, approximately 2% was from leaves, 9% was from fruit, 9% was from miscellaneous matter, and 1% was from wood matter with diameters < 2.5 cm. In comparison, 57% (n=30) of Icacos organic matter was composed of coarse woody debris. Of the remaining 43% organic matter pool, approximately 0% was from fruit, 16% was from leaves, 10% was from miscellaneous matter, and 18% was from wood matter with diameters < 2.5 cm. The data suggest a less recalcitrant organic matter pool in the Icacos environment and higher rates of turnover than in the Bisley environment. It was also apparent that woody matter (< 2.5 cm diameter) deposition was a significant source of OM inputs in the Icacos plots. 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.
Regeneration after Hurricane Hugo, woody species > 10 cm tall (9Ha grid, El Verde) (9Ha Plots Small Data Set)
The purpose of this data set is to document vegetation damage and recovery following Hurricane Hugo, a borderline category 3-4 hurricane with winds from 130 to 160mph (110kts) and a pressure of 945 to 946.1 mb, which hit Puerto Rico in September 18th, 1989 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.
Regeneration after Hurricane Hugo woody species more than 1m tall (9ha grid, El Verde) (Large 9Ha Grid)
The purpose of this data set is to document vegetation damage and recovery following Hurricane Hugo, a borderline category 3-4 hurricane with winds from 130 to 160mph (110kts) and a pressure of 945 to 946.1 mb, which hit Puerto Rico in September 18th, 1989. 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.
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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.