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289 results for “hydraulics”
Data files for 'Tan et al., (2020). Hydraulic fracturing induced seismicity in the southern Sichuan Basin due to fluid diffusion inferred from seismic and injection data analysis'
<p>CEDC catalog.xlsx : the seismic catalog from China Earthquake Data Center (https://data.earthquake.cn/)</p> <p>Local network catalog.xlsx : the seismic catalog of the local seismic network</p> <p>Injection data of N5&N7.xlsx : the injection data of N5 and N7 (with permission of the operator)</p>
Hydraulic conductivity technical note
<p>Experimental data and code related to paper "<strong>A new experimental setup to measure hydraulic conductivity of plant segments":</strong> <a href="https://doi.org/10.1093/aobpla/plad024">https://doi.org/10.1093/aobpla/plad024</a></p><p>The interactive version can be found at: https://renkulab.io/projects/louis.krieger/hydraulic-conductivity-technical-note</p><p>Once there, you can start the project and interact.</p><p>If you would like to run it locally in a python 3.6 environment, you will need to install the <a href="https://renkulab.io/gitlab/louis.krieger/hydraulic-conductivity-technical-note/-/blob/cc1a351b1fb6e2a731fcc22d1fb406bd92d1ceb1/requirements.txt">requirements.txt</a> before using notebooks.</p><p> </p><p><strong>Contents:</strong></p><p>All <a href="https://renkulab.io/gitlab/louis.krieger/hydraulic-conductivity-technical-note/-/blob/cc1a351b1fb6e2a731fcc22d1fb406bd92d1ceb1/renku_commands">renku commands</a> are run from the home folder of the repository to create the graphs and the paper itself.</p><p>First the <a href="https://renkulab.io/gitlab/louis.krieger/hydraulic-conductivity-technical-note/-/blob/cc1a351b1fb6e2a731fcc22d1fb406bd92d1ceb1/notebooks/extra_calculations/Intrinsic_permeability.ipynb">equations</a> used in other notebooks were derived and exported.</p><p>Then the <a href="https://renkulab.io/gitlab/louis.krieger/hydraulic-conductivity-technical-note/-/blob/cc1a351b1fb6e2a731fcc22d1fb406bd92d1ceb1/notebooks/calibrations/P_sensor_calibration.ipynb">calibrations of the pressure sensors</a> were run.</p><p>Next the graph are created from the notebook <a href="https://renkulab.io/gitlab/louis.krieger/hydraulic-conductivity-technical-note/-/blob/cc1a351b1fb6e2a731fcc22d1fb406bd92d1ceb1/notebooks/paper/graphs_for_paper.ipynb">graphs_for_paper.ipynb</a> using the first renku command.</p><p>Followed by using those graphs to compile the paper itself from <a href="https://renkulab.io/gitlab/louis.krieger/plantwatertransport/-/blob/498ceaa281eda57ba6f53eb015d722182a142d80/writing/paper1/paper1.tex">paper1.tex</a> with the second command.</p><p>Finally, the <a href="https://renkulab.io/gitlab/louis.krieger/hydraulic-conductivity-technical-note/-/blob/cc1a351b1fb6e2a731fcc22d1fb406bd92d1ceb1/paper/SI.tex">SI latex</a> is created from the <a href="https://renkulab.io/gitlab/louis.krieger/hydraulic-conductivity-technical-note/-/blob/cc1a351b1fb6e2a731fcc22d1fb406bd92d1ceb1/notebooks/paper/SI.ipynb">notebook itself</a>.</p><p>Additional notebooks where the graphs are a bit more in context can be found in the <a href="https://renkulab.io/gitlab/louis.krieger/hydraulic-conductivity-technical-note/-/tree/cc1a351b1fb6e2a731fcc22d1fb406bd92d1ceb1/notebooks/additional_notebooks">subfolder in notebooks</a>:</p><p>All the <a href="https://renkulab.io/projects/louis.krieger/hydraulic-conductivity-technical-note/files/blob/data/my_data">raw data files</a> are also available, as well as <a href="https://renkulab.io/gitlab/louis.krieger/hydraulic-conductivity-technical-note/-/tree/cc1a351b1fb6e2a731fcc22d1fb406bd92d1ceb1/paper/images">additional images</a> used in the write-ups.</p><p> </p>
Data and R code for "Negative effects of wind on plant hydraulics at the global scale"
<p>To minimize ontogenetic and methodological variation, we only included trait data that met the following criteria: (a) plants were grown in natural ecosystems, excluding greenhouse and common garden experiments; (b) measurements were made on adult plants and not on seedlings; (c) hydraulic traits were measured on terminal stem or branch segments in the sapwood at the crown; and (d) trait data were calculated as the mean value for each species at the same site when data were from multiple sources.</p> <p>Climate data were obtained either from the original reports or from WorldClim version 2 (http://worldclim.org/version2) if the original data were not available. The following variables were extracted from WorldClim: mean annual wind speed, mean annual precipitation, mean annual temperature, precipitation seasonality, temperature seasonality, precipitation of driest month, and minimum temperature of coldest month. The VPD data was extracted from the TerraClimate dataset (http://www.climatologylab.org/terraclimate.html). Annual PET (potential evapotranspiration) data were extracted from the CGIAR-CSI consortium (http://www.cgiar-csi.org/data). The moisture index (MI) is the ratio of precipitation to PET.</p> <p>Simple linear regression was used to examine the relationships between two variables, utilizing the 'lm' function in R software. Partial regression analysis was conducted using the R package VISREG to investigate the relationships between wind speed and plant hydraulics while controlling for other variables. This analysis helped to illustrate the independent effect of wind on plant hydraulics. The Random Forest machine-learning algorithm (implemented using the R package randomForest) was utilized to assess the relative importance of environmental variables for each plant hydraulic trait. The Mean Decrease in Gini was calculated as the average of a variable's total decrease in node impurity, taking into account the proportion of samples that reach that node in each individual decision tree in the random forest. This provides a measure of a variable's importance in estimating the value of the target variable across all of the trees in the forest. A higher Mean Decrease in Gini value indicates greater importance of the variable. Multiple regression analyses were performed to develop predictive equations for plant hydraulic traits using environmental variables. To test for hydraulic traits-wind speed slope directions and differences among species groups in different climatic regions, we used standardized major axis (SMA) analyses. The R package SMATR was employed for these analyses. We considered <em>p </em>< 0.05 as the threshold for statistical significance in all models.</p>
Hydraulic model (HEC-RAS) of the Upper San Saba River between Fort McKavett and Menard, TX
<p>This is a 2D Hydraulic model (HEC-RAS) for the Upper San Saba River between Fort McKavett and Menard, TX. Model geometry is based on USGS 3DEP data (2018), with underwater bathymetry "burned" in using cross-sections sampled in the field in 2018. The model was calibrated based on water surface and velocities measured during data collection.</p>
Data for: Phenotypic variation of hydraulic traits for woody species
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Phytogeographic origin determines Tropical Montane Cloud Forest hydraulic trait composition
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Data from: Friction of Longmaxi shale gouges and implications for seismicity during hydraulic fracturing
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Data from: Linking coordinated hydraulic traits to drought and recovery responses in a tropical montane cloud forest
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Data from: Pushing the limits to tree height: could foliar water storage compensate for hydraulic constraints in Sequoia sempervirens
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Data from: Convergence in resource use efficiency across trees with differing hydraulic strategies in response to ecosystem precipitation manipulation
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Data from: Initial hydraulic failure followed by late-stage carbon starvation leads to drought-induced death in tree, Trema orientalis
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Data from: Quantifying in situ phenotypic variability in the hydraulic properties of four tree species across their distribution range in Europe
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Divergent responses of forest dominant trees species to the manipulated canopy and understory nitrogen additions in terms of foliage stoichiometric, economic and hydraulic traits
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Exploring functional flow heterogeneity in regulated flow regime: fish species turnover along hydraulic gradients in an artificial waterway network
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Data from: Causes of ecological gradients in leaf margin entirety: Evaluating the roles of biomechanics, hydraulics, vein geometry, and bud packing
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Tradeoffs between leaf cooling and hydraulic safety in a dominant arid land riparian tree species
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Data from: Radial variation of wood functional traits reflect size-related adaptations of tree mechanics and hydraulics
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Data from: Anatomical and hydraulic responses to desiccation in emergent conifer seedlings
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Hydraulic model (HEC-RAS) of the Upper San Saba River between Fort McKavett and Menard, TX
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Data from: Insular woody daisies (Argyranthemum , Asteraceae) are more resistant to drought-induced hydraulic failure than their herbaceous relatives
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Allen Brain Atlas
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DANDI Archive for NWB datasets
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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.