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907 results for “Pines”
Model data for "Melt sensitivity of irreversible retreat of Pine Island Glacier"
<p>Model inputs and outputs for the experiments in Reed et al., 2024 "Melt sensitivity of irreversible retreat of Pine Island Glacier".</p>
Data from: Seed origin and warming constrain lodgepole pine recruitment, slowing the pace of population range shifts
Open the record for dataset details and reuse information.
Instrinsic water use efficiency of Ponderosa Pine of the southwestern U.S.
Tree rings were collected from 17 populations of ponderosa pine forests across the southwestern U.S. Carbon isotope of early wood and latewood were then analyzed for each annual ring, from 1960-2017. Intrinsic water-use efficiency (A/gs) chronologies were calculated with adjusted latewood chronologies as used in Strange et al. (2023) Global Change Biology. Details regarding the process of calculating adjusted latewood chronologies can be found in the methods section of Strange et al. (2023) Global Change Biology.
The North American Monsoon Climate System and its influence on Ponderosa pine water use and water use efficiency
All data in this package are presented as used in Strange et al. (2023). Earlywood (EW) and Latewood (LW) isotope chronologies are presented in the delta (d) notation relative to Vienna Peedee Belemnite (VPDB) standards. Further details regarding data collection, processing, α-cellulose extraction, etc. can be found in the Global Change Biology manuscript associated with these data.
Xylem water oxygen and hydrogen isotopes of Ponderosa Pine trees and soil samples in the southwestern U.S. 2018 and 2021
Across seven sites in southern Utah and northern Arizona, we collected precipitation, xylem water, and soil water isotope samples during two years: 2018 and 2021. All xylem water samples were collected from mature Ponderosa pine forests. At each site, xylem water samples were collected from the same 15 trees during two periods during 2018, and three periods during 2021. Soil pits were dug close to the trees and soil samples were collected at 5, 25, and 45cm depth close to the tree xylem samples. In 2021, we also collected precipitation isotopes using a rain gauge that was topped with mineral oil to prevent evaporation.
Analysis of aboveground biomass in longleaf pine forests in southeast United States, 2015 to 2019
I obtained inventory data from the USDA Forest Inventory and Analysis (FIA) program, covering 1999 to 2022, focusing on eight southeastern states in the U.S. (Alabama, Mississippi, Florida, Georgia, North Carolina, South Carolina, Texas, and Louisiana). For this study, I filtered the data for 2015-2019, during which the FIA captures 20% of plots in each state annually. Using R, I converted aboveground biomass (AGB) from pounds to kg/ha, tree height from feet to meters, and diameter at breast height (DBH) from inches to centimeters to align with the metric system. Structural diversity of tree height and diameter was calculated using the Shannon diversity index based on tree height and diameter classes. Climate data from PRISM and soil carbon to nitrogen data from the World Soil Database were integrated with the FIA data using the nearest neighbors method in the SF package in R. The combined dataset was standardized for Structural Equation Modeling (SEM) analysis.
Watersheds 1 and 17 white pine survey in 2001
This study involves the resampling of 40 0.2 acre plots throughout the two 35 year old white pine stands to determine the changes in stand structure over time (other survey dates include 1967, 1969, 1972, 1984, and 1989). Live and dead stems of each tree in a plot were measured (diameter at breast height, DBH). In addition, due to the recent infestations in both watersheds by the southern pine bark beetle, current status of trees was also noted.
Coweeta Watershed 1 Litter and Soil Temperature for White Pine Decomposition Study from 2002 to 2004
These data are the hourly readings of litter and soil temperature in the center of each litter decomposition plot. The study was conducted at the Watershed 1 Permanent Census Plot Locations: 14, 15, 22, 28, 62, 70, 74, 90.
Forest floor mass and nutrient content by layer in Coweeta white pine watershed 1 from 2001 to 2003
The forest floor was sampled in 4 beetle-infested and 4 non-beetle-infested white pine plots in watershed 1. Fresh litter (Oi) was separated from decaying litter (Oe). Total litter mass, fresh versus decayed litter, and litter nitrogen content was compared between treatments for years 2001, 2002, 2003.
Litter decomposition rates and litter nutrient content in Coweeta white pine watershed 1 from 2001 to 2004
Litterbag mass remaining in litterbags and rate of decay were compared between 4 beetle-infested and 4 non-beetle-infested white pine plots in watershed 1.
Herb coverage on southern pine beetle and non-southern pine beetle impacted permanent plots in Coweeta white pine watershed 1 from 2001 to 2003
Percent cover of herb layer species was compared between beetle-impacted and non-beetle-impacted white pine plots in watershed 1.
Seedling regeneration density on southern pine beetle and non-southern pine beetle impacted permanent plots in Coweeta white pine watershed 1 from 2001 to 2003
Seedling density was compared between beetle-impacted and non-beetle-impacted white pine plots on watershed 1.
Photosynthetically active radiation (PAR) on southern pine beetle and non-southern pine beetle impacted permanent plots in Coweeta white pine watershed 1 from 2002 to 2003
Light availability (photosynthetically active radiation, PAR) was compared between beetle-impacted and non-beetle-impacted white pine plots watershed 1.
Percent soil moisture on southern pine beetle and non-southern pine beetle impacted permanent plots in Coweeta white pine watershed 1 from 2002 to 2003
Soil moisture was compared between beetle-impacted and non-beetle-impacted white pine plots in watershed 1.
Physical characteristics and GPS data for 21 permanent plots in Coweeta white pine watershed 1 from 2003 to 2004
A GPS receiver was used to acquire UTM coordinates and elevation for each plot center. Aspect and slope were also measured.
Short-term effects of biochar on soil CO2 efflux in boreal Scots pine forests
<p>This dataset includes all the data we collected at the first summer after biochar application in boreal forests. Our paper“ the effect of biochar on soil CO<sub>2</sub> efflux in boreal forests“ now is under review in Annals of Forest Science. Biochar prepared at two reaction temperatures was applied at three rates (including non-amended controls). During the first year after treatment, efflux increased with higher rates of biochar, but the reaction temperature had no effect. o explain char effects on efflux, soil moisture and temperature were also added to the model testing treatment effects. These environmental variables explained more of the variation in efflux and caused treatment to no longer have a significant effect. Based on this result, we concluded that soil temperature explains the effect of char on efflux.</p>
Ponderosa Pine smoldering study at Oregon State University
<p>Images and other supplemental data for project used to identify the significance of moisture content, inorganic content, organic bulk density, and fuel thickness in influencing horizontal spread rate and surface temperatures within smoldering ponderosa pine (Pinus ponderosa) duff.</p> <p>These images and data were used for the publication, effects of fuel characteristics on spread rate and surface temperatures of smoldering duff</p>
Data for "Age effect on tree structure and biomass allocation in Scots pine (Pinus sylvestris L.) and Norway spruce (Picea abies [L.] Karst.)"
<p>VAPU dataset for tree biomass was collected from southern Finland in 1988-1990 by the Finnish Forest Research Institute (Metla, now Natural Resources Institute Finland, Luke) (VAPU data set).</p> <p>Those sample trees (162 Scots pine and 163 Norway spruce) are originated from the whole VAPU data set. The sheet 'Pine' and 'Spruce' data have been matched between 'sample branch measurements' and the 'biomass' information (by cluster X, Y, and plot, tree number).</p> <p>Biomass estimation for foliage and branches has been described here: https://doi.org/10.1016/j.ecolmodel.2004.04.024 and https://doi.org/10.1093/treephys/25.7.803<br> </p>
Raw and analyzed data for manuscript: "Superhydrophilic coating of pine wood by plasma functionalization of self-assembled polystyrene spheres"
<p><strong>Abstract: </strong></p> <p>Self-assembling films typically used for colloidal lithography have been applied to pine wood substrates to change the surface wettability. Therefore, monodisperse polystyrene (PS) spheres have been deposited onto a rough pine wood substrate via dip coating. The resulting PS sphere film resembled a polycrystalline FCC-like structure with typical domain sizes of 5 – 15 single spheres. This self-assembled coating was further functionalized via an O<sub>2</sub> plasma. This plasma treatment strongly influenced the particle sizes in the outermost layer, and hydroxyl as well as carbonyl groups were introduced to the PS spheres’ surfaces, thus generating a superhydrophilic behaviour.</p>
Data from: Association genetics of growth and adaptive traits in loblolly pine (Pinus taeda L.) using whole-exome-discovered polymorphisms
In the United States, forest genetics research began over 100 years ago and loblolly pine breeding programs were established in the 1950s. However, the genetics underlying complex traits of loblolly pine remains to be discovered. To address this, adaptive and growth traits were measured and analyzed in a clonally tested loblolly pine (Pinus taeda L.) population. Over 2.8 million single nucleotide polymorphism (SNP) markers detected from exome sequencing were used to test for single locus associations, SNP-SNP interactions and correlation of individual heterozygosity with phenotypic traits. A total of 36 SNP-trait associations were found for specific leaf area (5 SNPs), branch angle (2), crown width (3), stem diameter (4), total height (9), carbon isotope discrimination (4), nitrogen concentration (2), and pitch canker resistance traits (7). Eleven SNP-SNP interactions were found to be associated with branch angle (1 SNP-SNP interaction), crown width (2), total height (2), carbon isotope discrimination (2), nitrogen concentration (1), and pitch canker resistance (3). Non-additive effects imposed by dominance and epistasis account for a large fraction of the genetic variance for the quantitative traits. Genes that contain the identified SNPs have a wide spectrum of functions. Individual heterozygosity positively correlated with water use efficiency and nitrogen concentration. In conclusion, multiple effects identified in this study influence the performance of loblolly pines, provide resources for understanding the genetic control of complex traits, and have potential value for assessing with breeding through marker assisted selection and genomic selection.
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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.