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21,983 results for “UNITE”
Genomics‐informed delineation of conservation units in a desert amphibian
<p>Delineating conservation units (CUs, e.g., evolutionarily significant units, ESUs, and management units, MUs) is critical to the recovery of declining species because CUs inform both listing status and management actions. Genomic data have strengths and limitations in informing CU delineation and related management questions in natural systems. We illustrate the value of using genomic data in combination with landscape, dispersal, and occupancy data, to inform CU delineation in Nevada populations of the Great Basin Distinct Population Segment of the Columbia spotted frog (<em>Rana luteiventris</em>). <em>R</em>. <em>luteiventris</em> occupies naturally fragmented aquatic habitats in this xeric region, but beaver removal, climate change, and other factors have put many of these populations at high risk of extirpation without management intervention. We addressed three objectives: (1) assessing support for ESUs within Nevada; (2) evaluating and revising, if warranted, the current delineation of MUs; and (3) evaluating genetic diversity, effective population size, adaptive differentiation, and functional connectivity to inform ongoing management actions. We found little support for ESUs within Nevada but did identify potential revisions to MUs based on unique landscape drivers of connectivity that distinguish these desert populations from those in the northern portion of the species range. Effective sizes were uniformly small, with low genetic diversity and weak signatures of adaptive differentiation. Our findings suggest that management actions, including translocations and genetic rescue, might be warranted. Our study illustrates how a carefully planned genetic study, designed to address priority management goals that include CU delineation, can provide multiple insights to inform conservation action.</p>
Canopy gaps facilitate upslope shifts in montane conifers but not in temperate deciduous trees in the Northeastern United States
<p>Many montane tree species are expected to migrate upslope as climate warms, but it is not clear if forest canopy gaps, which can facilitate tree seedling recruitment, serve as an important mechanism driving tree species range shifts. Patterns of tree seedling establishment can inform us about early stages of tree species migrations and are critical to examine in the context of global climate change.</p> <p>We contrasted elevational distributions of tree seedlings both within and outside of forest canopy gaps with the distributions of conspecific adults and saplings across the deciduous-coniferous ecotone on ten mountains in four states of the northeastern United States. We tested if seedling distributions of four dominant tree species (<em>Abies balsamea, Picea rubens, Acer saccharum</em>, and<em> Fagus grandifolia</em>) were shifted upslope of conspecific adult and sapling distributions. We also examined if this shift was facilitated by canopy gaps and what environmental drivers affected species distributions.</p> <p>There was limited seedling recruitment of dominant tree species at the temperate-coniferous ecotone, which we attributed to (i) an observed downslope shift of seedling distributions of the low-elevation deciduous species (<em>Acer saccharum, Fagus grandifoli</em>a) and (ii) an upslope shift in seedling distributions of the high-elevation conifers (<em>Abies balsamea, Picea rubens</em>). The upslope shift of conifer seedlings contrasts with our previous research at these sites which observed downslope shifts of sapling distributions in <em>Picea rubens</em>, suggesting that seedlings may be responding to more recent climate warming. Canopy gaps in high-elevation conifer forests facilitated these upslope shifts by promoting conifer seedling recruitment. However, gaps at lower elevations did not play a significant role in seedling recruitment or the observed downslope shifts of the dominant deciduous species. Climate was the dominant predictor of adult tree distributions whereas both climate and soil were important predictors of seedling distributions.</p> <p><strong><em>Synthesis</em></strong>. Our study illustrates that tree seedlings have the potential for monitoring the early stages of tree species migrations, and particularly so in canopy gaps in high-elevation conifer forests. Further, we stress that species range shifts are sensitive to local scale heterogeneity in light availability (i.e., canopy gaps) and other non-climatic factors.</p>
Herbaceous production lost to tree encroachment in United States rangelands
<p>Data products and modeling code supporting the publication:</p> <p><strong>Herbaceous production lost to tree encroachment in United States rangelands</strong> in the <em>Journal of Applied Ecology</em>.</p> <p>Manuscript DOI: 10.1111/1365-2664.14288</p> <p><strong>Abstract</strong></p> <ol> <li>Rangelands of the United States provide ecosystem services that benefit society and rural economies. Native tree encroachment is often overlooked as a primary threat to rangelands due to the slow pace of tree cover expansion and the positive public perception of trees. Still, tree encroachment fragments these landscapes and reduces herbaceous production, thereby threatening habitat quality for grassland wildlife and the economic sustainability of animal agriculture. </li> <li>Recent innovations in satellite remote sensing permit the tracking of tree encroachment and the corresponding impact on herbaceous production. We analyzed tree cover change and herbaceous production across the western United States from 1990 to 2019.</li> <li>We show that tree encroachment is widespread in U.S. rangelands; absolute tree cover has increased by 50% (77,323 km<sup>2</sup>) over 30 years, with more than 25% (684,852 km<sup>2</sup>) of U.S. rangeland area experiencing tree cover expansion. Since 1990, 302 ± 30 Tg of herbaceous biomass have been lost. Accounting for variability in livestock biomass utilization and forage value reveals that this lost production is valued at between $4.1 - $5.6 billion U.S. dollars.</li> <li>Synthesis and applications: The magnitude of impact of tree encroachment on rangeland loss is similar to conversion to cropland, another well-known and primary mechanism of rangeland loss in the U.S. Prioritizing conservation efforts to prevent tree encroachment can bolster ecosystem and economic sustainability, particularly among privately-owned lands threatened by land-use conversion.</li> </ol> <p><strong>Description</strong></p> <p>This archive contains data products and modeling code for production loss and tree cover change estimates provided in the accompanying refereed publication. The easiest way to view and use these data is in Google Earth Engine:</p> <ul> <li><a href="https://smorford.users.earthengine.app/view/yield-gap">https://smorford.users.earthengine.app/view/yield-gap</a></li> <li><a href="https://code.earthengine.google.com/8ad19c7f7a6e04b377953326b274f98d">https://code.earthengine.google.com/8ad19c7f7a6e04b377953326b274f98d</a></li> </ul> <p>Summary data products are included in the <em>data-products</em> folder, and include links and scripts to download all annual data discussed in the manuscript. The full dataset is roughly 660GB and cannot be achieved on Zonodo as of summer 2022.</p> <p>Similarly, the <em>model</em> directory contains the primary codebase for processing raw tree cover data and running XGBoost modeling training and inference for the production loss model. To recreate the production loss data will require downloading approximately 900GB of biomass data and 250GB of tree cover data; total project size will be approximate 1.8 TB after inference.</p> <p>Data can also be downloaded directly from the University of Montana web servers:</p> <ul> <li><a href="http://rangeland.ntsg.umt.edu/data/rap/rap-vegetation-biomass/v2/">http://rangeland.ntsg.umt.edu/data/rap/rap-vegetation-biomass/v2/</a></li> <li><a href="http://rangeland.ntsg.umt.edu/data/rap/rap-derivatives/yield-gap/v1/">http://rangeland.ntsg.umt.edu/data/rap/rap-derivatives/yield-gap/v1/</a></li> </ul> <p><strong>Journal citation:</strong></p> <p>Morford, S.L., Allred, B.W., Twidwell, D., Jones, M.O., Maestas, J.D., Roberts, C.P. and Naugle, D.E., <em>Accepted</em>. Herbaceous production lost to tree encroachment in United States rangelands. <em>Journal of Applied Ecology</em>, August 2022.</p>
An ensemble of 48 physically perturbed model estimates of the 1/8° terrestrial water budget over the conterminous United States, 1980–2015
<p>This dataset contains the 1980–2015 monthly terrestrial water budget simulated by a 48-member perturbed-physics ensemble configured from the Noah LSM with multi-physics options (Noah‑MP v3.6). Simulation outputs include total evapotranspiration and its constituents (canopy evaporation, soil evaporation, and transpiration), runoff (the surface and subsurface components), as well as terrestrial water storage (snow water equivalent, four-layer soil water content from the surface down to 2 m, and the groundwater storage anomaly). The file name has four parts: the abbreviation for "terrestrial water budget", the used parameterization, the time scale, and the suffix.</p> <p>The 48 physics configurations are generated by combining four runoff parameterizations (run1: SIMGM, run2: SIMTOP, run3: NOAHR, run4: BATS), two parameterizations of stomatal conductance (can1: Ball–Berry, can2: Jarvis), three parameterizations of soil moisture stress factor (btr1:NOAHB, btr2: CLM, btr3: SSiB), and two parameterizations of near-surface atmospheric turbulence (tub1: M-O, tub2: Chen97).</p> <p>The simulation domain covers the all of conterminous United States (25°–53°N, 125°–67°W), which is also called the NLDAS-2 testbed (Xia et al., 2012a, b). The simulations were performed at a spatial resolution of 0.125°, which is the same as for NLDAS-2 models. Details of the simulation settings and spin-up run can be found in Section 2.3 of Zheng et al. (2019) and Section 2.2 of Fei et al. (2021).</p>
A consolidated database of police-reported motor vehicle traffic accidents in the United States for actuarial applications
<p>The parameter estimates along with their 90% confidence intervals obtained for the 20 multinomial logistic regressions are shown here in two presentations. In 'Covariate trends' we show the annual trends for the 20 years of data by type of covariate. In 'Covariates magnitude for each year', we show for each year the magnitude that each covariate has in contrast with the other 23 covariates (the intercept is not included due to scaling issues).</p> <p>All parameter estimates and their confidence intervals can be found in a table format in 'allparameters.csv'.</p>
Text-fig. 3. Scanning electron micrographs of Normapolles flowers/fruits from Zliv-Řídká Blana locality. a: Budvaricarpus serialis, aggregation of laterally fused fruits supported by a common bract (br – bract, hp – hypanthium), no. NM-F 3160; b: Budvaricarpus sp., aggregation of laterally fused fruits supported by several bracts, no. NM-F 3619; c: Caryanthus trebecnsis, reproductive unit consists of three bisexual, epigynous flowers/young fruits, no. NM-F 3286; d: Dahlergeniantus sp., hypogynous flower with radial symmetry, no. NM-F 4495; e: Calathiocarpus sp., epigynous flower with radial symmetry, no. NM-F 4631; f: Caryanthus sp. 1, ribbed fruit–nut of deltoid shape, no. NM-F 3208; g: Zlivifructus vachae, bisymmetrical flower with four tepals and four stamens, no. NM-F 3172; h: Taxon 3, ribbed fruit of Normapolles affinity, no. NM-F 3724. in Plant Mesofossils From The Late Cretaceous Klikov Formation, The Czech Republic
Text-fig. 3. Scanning electron micrographs of Normapolles flowers/fruits from Zliv-Řídká Blana locality. a: Budvaricarpus serialis, aggregation of laterally fused fruits supported by a common bract (br – bract, hp – hypanthium), no. NM-F 3160; b: Budvaricarpus sp., aggregation of laterally fused fruits supported by several bracts, no. NM-F 3619; c: Caryanthus trebecnsis, reproductive unit consists of three bisexual, epigynous flowers/young fruits, no. NM-F 3286; d: Dahlergeniantus sp., hypogynous flower with radial symmetry, no. NM-F 4495; e: Calathiocarpus sp., epigynous flower with radial symmetry, no. NM-F 4631; f: Caryanthus sp. 1, ribbed fruit–nut of deltoid shape, no. NM-F 3208; g: Zlivifructus vachae, bisymmetrical flower with four tepals and four stamens, no. NM-F 3172; h: Taxon 3, ribbed fruit of Normapolles affinity, no. NM-F 3724.
Text-fig. 2. Distribution of different rock units in the turbidite facies in Majalengka area, West Java, Indonesia. in Lithofacies And Ichnofacies Of Turbidite Deposits, West Java, Indonesia
Text-fig. 2. Distribution of different rock units in the turbidite facies in Majalengka area, West Java, Indonesia.
Text-fig. 4. Correlations of the strata in the Urema Graben, the Cheringoma Plateau and other parts of Mozambique proposed by various authors. The positions of fossiliferous units such as the Grudja and Cheringoma formations have been reasonably stable, whereas correlations of other rock units, especially the Mazamba Formation and the volcanics, have varied a great deal. The time scale is from Gradstein et al. (2020). in Stratigraphy, Chronology And Palaeontology Of The Tertiary Rocks Of The Cheringoma Plateau, Mozambique
Text-fig. 4. Correlations of the strata in the Urema Graben, the Cheringoma Plateau and other parts of Mozambique proposed by various authors. The positions of fossiliferous units such as the Grudja and Cheringoma formations have been reasonably stable, whereas correlations of other rock units, especially the Mazamba Formation and the volcanics, have varied a great deal. The time scale is from Gradstein et al. (2020).
Fig. 1. The Neighbor Joining tree for 37 in Taxonomic Diversity Of The Genus Tor (Cyprinidae) From Aceh Waters In Indonesia Based On Cytochrome Oxidase Sub-Unit I (Coi) Gene
Fig. 1. The Neighbor Joining tree for 37 sequences of Tor from seven locations in Aceh Province estimated using 1000 bootstrap replications.
Random forest climatic modeling of agricultural insurance loss across the inland Pacific Northwest region of the United States
<p>We compared climatic relationships to insurance loss across the inland Pacific Northwest region of the United States, using a design matrix methodology, to identify optimum temporal windows for climate variables by county in relationship to wheat insurance loss due to drought. The results of our temporal window construction for water availability variables (precipitation, temperature, evapotranspiration, and the Palmer drought severity index [PDSI]) identified spatial patterns across the study area that aligned with regional climate patterns, particularly with regards to drought-prone counties of eastern Washington. Using these optimum time-lagged correlational relationships between insurance loss and individual climate variables, along with commodity pricing, we constructed a regression-based random forest model for insurance loss prediction and evaluation of climatic feature importance. Our cross-validated model results indicated that PDSI was the most important factor in predicting total seasonal wheat/drought insurance loss, with wheat pricing and potential evapotranspiration having noted contributions. Our overall regional model had a R<sup>2</sup> of 0.49 and a RMSE of $30.8 million. Model performance typically underestimated annual losses, with moderate spatial variability in terms of performance between counties.</p>
BRAIN Journal-Artificial Neuron Modelling Based on Wave Shape-Figure 1. Typical feedforward artificial neural network processing unit
<p>In Figure 1, each input X is weighted by a separate weight value w. These are then summed together to give a total input value for the neuron. This total can then be passed through a function, to transform it into the desired output value. This is then compared to the actual output value d; where the error or differences between the two sets is measured and used to correct the weight<br> values, to bring the two sets of values closer. One way to update the weights is after each individual pattern is presented and processed. Another option is to process the error after the presentation of the whole dataset, as part of a batch update.</p>
Figure 2. Catadioptric projection modelled by the unit sphere-Design and Implementation of a Fully Autonomous UAV's Navigator Based on Omni-directional Vision System
<p>Since the beginning of UAV, the map building was one of the most addressed problems by<br> researchers. Several researchers used Omni directional vision for robot navigation and map<br> building. Because of the wide field of view in Omni directional sensors, the robot does not need to<br> look around using moving parts (cameras or mirrors) or turning the moving parts. The global view<br> offered by Omni directional vision is especially suitable for highly dynamic environments. The<br> Omni directional vision system consists of a hyperbolic mirror, a USB color digital camera<br> (Logitech C905) and a regulation device.</p>
Compilation of Fe and ligand data along the West coast of the United States
<p>Compilation of Fe and ligand data along the West coast of the United States (Compiled by Anh Le-Duy Pham from current available literature as of April 2024)</p> <p> </p> <p><span>USWC_Iron_Ligand_Compilation.xlsx: an excel file containing all the combined dFe and ligand data</span></p> <p><span>USWC_IronLiganddata.mat: a MATLAB file containing all the combined dFe and ligand data</span></p>
FIGURE 16 in Medusapyga LaBonte and Maddison, a New Genus of Anillini (Coleoptera: Carabidae: Trechinae) from the Pacific Northwest of the United States
FIGURE 16. Maximum likelihood tree inferred from the concatenated, eight-gene matrix. Numbers of the branches are maximum likelihood bootstrap percentages. Outgroups omitted. Scale bar 0.1 units, as calculated by IQ-TREE.
FIGURE 12 in Medusapyga LaBonte and Maddison, a New Genus of Anillini (Coleoptera: Carabidae: Trechinae) from the Pacific Northwest of the United States
FIGURE 12. Parameres of Medusapyga chehalis, voucher JRL012. (A) left paramere, (B) right paramere. Scale bar 100 µm.
FIGURE 18 in Medusapyga LaBonte and Maddison, a New Genus of Anillini (Coleoptera: Carabidae: Trechinae) from the Pacific Northwest of the United States
FIGURE 18. Habitats of Medusapyga. (A) Habitat of Medusapyga alsea: USA, Oregon, Benton Co., Prairie Peak, 11 km south of Alsea, 44.2844°N 123.5858°W, 810 m elevation [Type locality] 20 March 2010. (B) Habitat of M. chehalis: USA, Washington, Thurston Co., 11 km NW of Littlerock, approximately 0.4 km SSW of the type locality, 46.9564°N 123.1366°W, 315 m elevation, 2 April 2022.
Figure 6 in Medusapyga LaBonte and Maddison, a New Genus of Anillini (Coleoptera: Carabidae: Trechinae) from the Pacific Northwest of the United States
Figure 6. Female genitalia of Medusapyga alsea from the type locality, ventral view. (A) Overview of voucher V101505. Scale bar 100 µm. (B) Closeup of voucher V101504, showing bifurcate setae on laterotergites. Scale bar 50 µm.
FIGURE 4 in Medusapyga LaBonte and Maddison, a New Genus of Anillini (Coleoptera: Carabidae: Trechinae) from the Pacific Northwest of the United States
FIGURE 4. Left profemora, anterior view. (A) Medusapyga alsea, male. (B) M. alsea, female. (C) M. chehalis, male. (D) M. chehalis, female. Scale bars 100 µm.
FIGURE 1 in Medusapyga LaBonte and Maddison, a New Genus of Anillini (Coleoptera: Carabidae: Trechinae) from the Pacific Northwest of the United States
FIGURE 1. (A) Female of Medusapyga alsea from the type locality. (B) Female of M. chehalis from USA, Washington, Thurston Co., 11 km NW of Littlerock, approximately 0.4 km SSW of the type locality, 46.9564°N 123.1366°W, 315 m elevation. Both specimens were freshly killed, and then posed and photographed on soil from their habitats. Scale bars 1 mm.
United States State Cancer Profiles data extract
<p>State Cancer Profiles (https://statecancerprofiles.cancer.gov) hosts an interactive website for tracking United States cancer incidence and prevalence. The dataset hosted here is an automated scraping from all locales for all demographic variables and diseases. </p> <p>Two tables are available:</p> <ol> <li>Cancer incidence</li> <li>Cancer mortality</li> </ol> <p>The dataset is meant for data mining or for building additional data products based on the state cancer profiles data, but without having to scrape the data yourself. </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.