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289 results for “hydraulics”
Tradeoffs between leaf cooling and hydraulic safety in a dominant arid land riparian tree species
<p>Leaf carbon gain optimization in hot environments requires balancing leaf thermoregulation with avoiding excessive water loss via transpiration and hydraulic failure. The tradeoffs between leaf thermoregulation and transpirational water loss can determine the ecological consequences of heat waves that are increasing in frequency and intensity. We evaluated leaf thermoregulation strategies in warm (>40 °C maximum summer temperature) and cool-adapted (<40 °C maximum summer temperature) genotypes of the foundation tree species, <em>Populus fremontii</em> using a common garden near the mid-elevational point of its distribution. We measured leaf temperatures and assessed three modes of leaf thermoregulation: leaf morphology, midday canopy stomatal conductance, and stomatal sensitivity to vapor pressure deficit. Data were used to parameterize a leaf energy balance model to estimate contrasts in midday leaf temperature in warm- and cool-adapted genotypes. Warm-adapted genotypes had 39% smaller leaves and 38% higher midday stomatal conductance, reflecting a 3.8 °C cooler mean leaf temperature than cool adapted genotypes. Leaf temperatures modeled over the warmest months were on average 1.1 °C cooler in warm- relative to cool-adapted genotypes. Results show that plants adapted to warm environments are predisposed to tightly regulate leaf temperatures during heat waves, potentially at an increased risk of hydraulic failure. </p>
FIWARE-enabled smart solution for the optimal management and operation of raw-water supply hydraulic works
<p>This database includes the data used to produce the results for the following article:</p> <p>Kossieris, P., Pantazis, Bellos, V., C., Makropoulos, C., 2022. FIWARE-enabled smart solution for the optimal management and operation of raw-water supply hydraulic works. 7th IAHR Europe Congress, September 7th – 9th, 2022, Athens, Greece (accepted paper for oral presentation, in press). </p>
Experimental data set for hydraulic fracture interactions with discontinuities study
<p>Experimental data included in hydraulic fracture interaction with discontinuities study. The original images in high resolution and the pressure and cumulative acoustic emission activities recordings. </p>
Training data - Hydraulic Head Probabilistic MLP-NN
<p>Training data for paper on hydraulic head predictions using an MLP-NN.</p>
Supplementary material for "Can the anisotropic hydraulic conductivity of an aquifer be determined using surface displacement data? A case study"
<p>Supplementary material for ”Can the anisotropic hydraulic conductivity of an aquifer be determined using surface displacement data? A case study".</p> <p>The <a href="https://github.com/sonasalehian/AHC-Poroelastic-Model.git" target="_blank" rel="noopener">AHC-Poroelastic-Model</a> codes from repository is included in the AHC-Poroelastic-Model-main.zip file.</p>
Data for: Phenotypic variation of hydraulic traits for woody species
<p>Hydraulic traits are major determinants of plant fitness, thus exerting control over vegetation structure, function and distribution. Yet it remains unclear whether and how hydraulic traits respond to environmental stimuli (i.e., phenotypic variation of hydraulic traits; PVHT), and if the coordination between different hydraulic traits and the trait-climate relationship are affected by PVHT.</p> <p>Here, we synthesized data of PVHT (maximum hydraulic conductivity and water potential inducing 50% loss of hydraulic conductivity) as well as potentially related morphological and anatomical traits (e.g. sapwood density, branch Huber value, mean and hydraulic weighted conduit diameter). We analyzed the magnitude, direction and source of variation of the plastic response, as well as the influence of environmental factors on trait coordination. Additionally, we compared the intra- and inter- specific variation between key hydraulic traits and climate metrics (mean annual precipitation and mean annual temperature) at the site of growth, as well as across the population range.</p> <p>PVHT was highly variable in both magnitude and direction, which was contingent on the environmental factor. The variation in PVHT mainly occurred at high taxonomic levels (i.e., family and genus), whereas phenology explained little variation for PVHT. Despite the high variability, trait correlation remained robust in the presence of environmental stimuli. Moreover, trait-climate relationships differed at inter-specific and intra-specific levels. The intra-specific variation of hydraulic traits in most species showed no correlation with climate metrics compared with the high correlation of hydraulic traits with climate metrics across species.</p> <p>Our findings suggest that the high variability of PVHT does not affect the trait correlation which may be valuable in predicting vegetation dynamics under varying environments. The distinct trait-climate relationships highlight the need to unravel the driving force of PVHT, as well as the adaptive strategy across populations.</p>
Data from: Remote hydraulic fracturing at weak interfaces
<p>This repository contains the data and processing functions for the diagrams in the manuscript: <em>Remote hydraulic fracturing at weak interfaces</em>.</p>
Dataset for "Real-Time Hydraulic Interval State Estimation for Water Transport Networks: a Case Study"
<p>The dataset (EPANET file) which accompanies the publication </p> <p>Vrachimis, S. G., Eliades, D. G., and Polycarpou, M. M.: Real-Time Hydraulic Interval State Estimation for Water Transport Networks: a Case Study, Drink. Water Eng. Sci., 2018</p>
Supporting Information: Equivalence of Discrete Fracture Network and Porous Media Models by Hydraulic Tomography
<p>Supporting Information README</p> <p>2018-Jan-17</p> <p>"Equivalence of Discrete Fracture Network and Porous Media Models by Hydraulic Tomography"</p> <p>Yanhui Dong, Yunmei Fu, Tian-Chyi Jim Yeh, Yu-Li Wang, Yuanyuan Zha, Liheng Wang, Yonghong Hao</p> <p>This file contains the supplementary data for this manuscript, including the locations and properties of fracture networks, the locations of observation wells and validation wells, the water head used in inverse model and validation tests, as well as the executive file used in the inverse model.</p>
Seismic dataset in "Source-Independent Passive Seismic Reverse-time Structure Imaging with Grouping Imaging Condition: Method and Application to Microseismic Events Induced by Hydraulic Fracturing"
<p>This dataset contains the seismic data and the velocity model used in the manuscript entitled "Source-Independent Passive Seismic Reverse-time Structure Imaging with Grouping Imaging Condition: Method and Application to Microseismic Events Induced by Hydraulic Fracturing" submitted to Journal of Geophysical Research-Solid Earth.</p>
The source code for a new capillary and adsorption‒force model predicting hydraulic conductivity of soil during freeze‒thaw processes
<p>The source code is related to "A New Capillary and Adsorption‒Force Model Predicting Hydraulic Conductivity of Soil during Freeze‒thaw Processes" (Shufeng Qiao, Rui Ma, Yunquan Wang, Ziyong Sun, Helen Kristine French, Yanxin Wang)</p>
Dataset and R code for "Relationship between wind speed and plant hydraulics at the global scale"
<p><strong><span>Data collection</span></strong><strong><span> </span></strong></p> <p><span> Plant hydraulic traits and height data were obtained from three sources: (1) field measurements of plant hydraulics for 210 forest species in China; (2) the TRY Plant Traits Database (https://www.try-db.org/TryWeb/Home.php; Kattge et al., 2020); and (3) published literature. For the latter we conducted searches on Web of Science, Google Scholar, and China National Knowledge Infrastructure (http://www.cnki.net) using keywords such as “hydraulic traits,” “xylem hydraulic conductivity,” “xylem vulnerability,” “water potential at 50% loss of hydraulic conductivity,” “xylem embolism resistance,” and “plant water conductivity.” A substantial portion of data in our study were obtained from published literature (Choat et al., 2012; Gleason et al., 2016) and the Xylem Functional Traits Database (XFT; </span><span><a href="https://xylemfunctionaltraits.org/"><span>https://xylemfunctionaltraits.org</span></a></span><span>).</span></p> <p><span>To minimize ontogenetic and methodological variation, we only included 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; (d) trait data were calculated as the mean value for each species at the same site when data were from multiple sources; and (e) data values > 3 SD (standard deviation) were removed to reduce the effect of outliers (Carmona et al., 2021); (f) <span>height data were reported at the same site where plant hydraulic traits were measured.</span> </span></p> <p><span>Climate data were obtained either from the original reports or from WorldClim version 2 (http://worldclim.org/version2; Fick & Hijmans, 2017; Table 1) if the original data were not available. The following variables measured at ~1 km<sup>2</sup> scale were extracted from WorldClim: mean annual wind speed (<span>μ</span>), mean annual precipitation, mean annual temperature, precipitation seasonality, temperature seasonality, wind seasonality (<span>μS; </span>coefficient of variation across monthly measurements × 100), precipitation of driest month, and minimum temperature of coldest month. The VPD data were extracted from the TerraClimate dataset (http://www.climatologylab.org/terraclimate.html; Abatzoglou et al., 2018). Annual PET (potential evapotranspiration) data were extracted from the CGIAR-CSI consortium (http://www.cgiar-csi.org/data; Zomer et al., 2008). Moisture index (MI), which is the ratio of precipitation to PET. </span></p> <p><strong><span>Data analysis</span></strong></p> <p><span>Trait and environment data were log<sub>10</sub>-transformed to achieve approximate normality, except for <em>P</em><sub>50</sub> and temperature data. We first calculated correlations among all climatic variables and for subsequent analyses retained only those variables with correlation coefficients lower than |0.7| (Dormann et al., 2013). We then ran independent multiple linear models for each trait of interest using the retained climatic variables. Model selection based on a corrected Akaike information criterion and using the R package glmulti (Calcagno & de Mazancourt, 2010), identified the best linear model for each trait. The R package ‘visreg’ (Breheny & Burchett, 2017) was used to visualize the partial relationships between wind speed and hydraulic traits. Two-dimensional contour plots were then used to explore and visualise how plant hydraulic traits varied simultaneously with wind speed and moisture index.</span></p> <p><span>To quantify the strength of wind effects on plant hydraulics, models with wind parameters μ and μS included were compared to those without these wind parameters. </span></p> <p><span>To test for differences in the relationship between hydraulic traits and wind speed among species grouped into different climatic regions (i.e., dry <em>vs</em>. wet sites, and tropical <em>vs</em>. temperate regions), we used standardized major axis (SMA) analyses using the R package ‘smatr’ (Warton et al., 2012).</span><span> </span><span>A grouping factor was added in each SMA to test whether species groups share a common slope, with <em>p</em> > 0.05 indicating species groups share a common slope. </span></p> <p><span>Variance partitioning analysis was performed using the ‘rdacca. hp’ R package to quantify the degree to which the effect of wind speed was independent from other climatic variables (Lai et al., 2022). The individual contribution of each predictor was estimated in this analysis. This analysis also helped to illustrate the significant values of climatic variables on plant hydraulics. </span></p> <p><span>A Random Forest </span><span>machine-learning algorithm (implemented using the R package ‘randomForest’) was utilized to further assess the relative importance of environmental variables for each plant hydraulic trait (Breiman, 2001). To avoid multicollinearity, this analysis only included variables with correlation coefficients lower than |0.7|. A higher value of the mean decrease in accuracy (%IncMSE) indicates the increased importance of a variable (e.g., a %IncMSE value of 50 indicates that the overall mean square error would increase by 50% if that variable were to be excluded from the analysis). This provides a measure of a variable's importance in estimating the value of the target variable across the trees in the forest. </span></p> <p> </p>
Data from: Causes of ecological gradients in leaf margin entirety: Evaluating the roles of biomechanics, hydraulics, vein geometry, and bud packing
PREMISE OF THE STUDY: A recent commentary by Edwards et al. (Am. J. Bot. 103: 975–978) proposed that constraints imposed by the packing of young leaves in buds could explain the positive association between non-entire leaf margins and latitude but did not thoroughly consider alternative explanations. METHODS: We review the logic and evidence underlying six major hypotheses for the functional significance of marginal teeth, involving putative effects on (1) leaf cooling, (2) optimal support and supply of the areas served by major veins, (3) enhanced leaf-margin photosynthesis, (4) hydathodal function, (5) defense against herbivores, and (6) bud packing. KEY RESULTS: Theoretical and empirical problems undermine all hypotheses except the support–supply hypothesis, which implies that thinner leaves should have non-entire margins. Phylogenetically structured analyses across angiosperms, the El Yunque flora, and the genus Viburnum all demonstrate that non-entire margins are indeed more common in thinner leaves. Across angiosperms, the association of leaf thickness with non-entire leaf margins is stronger than that of latitude. CONCLUSION: We outline a synthetic model showing how biomechanics, hydraulics, vein geometry, rates of leaf expansion, and length of development within resting buds, all tied to leaf thickness, drive patterns in the distribution of entire vs. non-entire leaf margins. Our model accounts for dominance of entire margins in the tropics, Mediterranean scrub, and tundra, non-entire margins in cold temperate deciduous forests and tropical vines and early-successional trees, and entire leaf margins in monocots. Spinose-toothed leaves should be favored in short-statured evergreen trees and shrubs, primarily in Mediterranean scrub and related semiarid habitats.
Hydraulic architecture with high-fraction of root resistance
<p>The hydraulic architecture of plants constrains water transport and carbon gain through stomatal limitation to CO<sub>2</sub> absorption. Leaf, stem, and root organs are composed of plant hydraulic architecture, of which the root is the main bottleneck of water transport for a wide range of plant species. The present study aimed to assess the ecophysiological mechanism and importance of the high fraction of root hydraulic resistance. Biomass partitioning and hydraulic conductance of leaves, stems and roots were measured using Japanese knotweed (<i>Fallopia japonica</i>, perennial herb), and Japanese zelkova (<i>Zelkova serrata</i>, deciduous tall tree). Additionally, theoretical analyses examined whether the measured hydraulic architecture and biomass partitioning maximized plant photosynthetic rate, which is the product of leaf area and photosynthetic rate per leaf area. Root hydraulic resistance accounted for 86% and 76% of the total plant resistance for Japanese knotweed and Japanese zelkova trees, respectively. According to comparisons of hydraulic and biomass partitionings, high root-resistance fractions were attributable to low biomass partitioning into root organs rather than high mass-specific root conductance. The measured partitioning of hydraulic resistance closely corresponded to the predicted optimal partitioning maximizing plant photosynthetic rate for the two species. The high fraction of root resistance was still predicted to be optimal with variations in air humidity and soil water potential. <span>These results suggest that the hydraulic architecture of a plant growing in mesic and fertile habitats resulted in a high fraction of root resistance due to small biomass partition into root organ, but contributed to efficient carbon gain</span>.</p>
Effects of Application of Recycled Chicken Manure and Spent Mushroom Substrate on Organic Matter, Acidity, and Hydraulic Properties of Sandy Soils
<p>This study aimed at examining the effects of long-term application of<br> chicken manure (CM) and spent mushroom substrate (SMS) on organic matter accumulation, acidity,<br> and hydraulic properties of soil. Two podzol soils with sandy texture in Podlasie Region (Poland)<br> were enriched with recycled CM (10 Mg ha1) and SMS (20 Mg ha1), respectively, every 1–2 years<br> for 20 years. The application of CM and SMS increased soil organic matter content at the depths<br> of 0–20, 20–40, and 40–60 cm, especially at 0–20 cm (by 102–201%). The initial soil pH increased in<br> the CM- and SMS-amended soil by 1.7–2.0 units and 1.0–1.2 units, respectively. Soil bulk density at<br> comparable depths increased and decreased following the addition of CM and SMS, respectively.<br> The addition of CM increased field water capacity (at –100 hPa) in the range from 45.8 to 117.8%<br> depending on the depth within the 0–60 cm layer. In the case of the SMS addition, the value of the<br> parameter was in the range of 42.4–48.5% at two depths within 0–40 cm. Depending on the depth, CM<br> reduced the content of transmission pores (>50 m) in the range from 46.3 to 82.3% and increased the<br> level of residual pores (<0.5 m) by 91.0–198.6%. SMS increased the content of residual pores at the<br> successive depths by 121.8, 251.0, and 30.3% and decreased or increased the content of transmission<br> and storage pores. Additionally, it significantly reduced the saturated hydraulic conductivity at<br> two depths within 0–40 cm. The fitted unsaturated hydraulic conductivity at two depths within the<br> 0–40 cm layer increased and decreased in the CM- and SMS-amended soils, respectively. The results<br> provide a novel insight into the application of recycled organic materials to sequester soil organic<br> matter and improve crop productivity by increasing soil water retention capacity and decreasing<br> acidity. This is of particular importance in the case of the studied low-productivity sandy acidic soils<br> that have to be used in agriculture due to limited global land resources and rising food demand.</p>
Quantitative Assessment of the Impact of Future Land Use Changes on Flood Risk Using Remote Sensing, Machine Learning, and a Hydraulic Model
<p> </p> <p>The RF Machine learning code </p> <p>Topological, geomorphology, geology, metrological information of the Tajan watershed.</p> <p>Land use land cover images of the Tajan watershed</p> <p>River, transportation roads, villages map </p> <p>Global damage function datasets.</p>
Video simulations for paper "Rapid Spatio-Temporal Flood Modelling via Hydraulics-Based Graph Neural Networks"
<p>Videos of the comparison between numerical and deep learning simulations for test datasets 1, 2, and 3 for paper "Rapid Spatio-Temporal Flood Modelling via Hydraulics-Based Graph Neural Networks".</p>
Numerical results data of 'Impact of Injection Pressure and Polyaxial Stress on Hydraulic Fracture Propagation and Permeability Evolution in Greywacke: Insights from Discrete Element Models of a Laboratory Test'
<p>Numerical results data of '<strong>Impact of Injection Pressure and Polyaxial Stress on Hydraulic Fracture Propagation and Permeability Evolution in Greywacke: Insights from Discrete Element Models of a Laboratory Test</strong>'</p>
Raw datasets for paper "Rapid Spatio-Temporal Flood Modelling via Hydraulics-Based Graph Neural Networks"
<p>Raw datasets for paper "Rapid Spatio-Temporal Flood Modelling via Hydraulics-Based Graph Neural Networks".</p> <p>The zip folder comprises 4 subfolders (DEM, WD, VX, VY), containing the elevation, water depths in time, and velocities (in x and y directions) in time for all training and testing simulations. The overview.csv file provides the runtime of the numerical model on each different simulation, identified by its id.</p> <p>The simulations ids are divided as follows:</p> <p>- 1-80: Training and validation</p> <p>- 501-520: Testing dataset 1</p> <p>- 10001-10020: Testing dataset 2</p> <p>- 15001-15020: Testing dataset 3</p>
Exploring functional flow heterogeneity in regulated flow regime: fish species turnover along hydraulic gradients in an artificial waterway network
<p><span>Humans have altered river flows and lateral aquatic habitats. The expansion of agriculture in floodplains has resulted in landscapes dominated by irrigated farmland. A key challenge in water management is to conserve existing ecological communities and habitat heterogeneity, while simultaneously maintaining engineered infrastructure for agriculture. In this study, we focused on an artificial channel network for irrigation with a regulated flow regime and its function as habitat for various fish species. Differences of hydraulic conditions among channels and compositional changes in fish species were examined to clarify functional flow heterogeneity. Species turnover was analyzed using pairwise Simpson dissimilarity among sampling reaches. Species turnover was positively associated with Froude number (flow intensity) differences at intermediate discharges, and with differences in cross-sectional areas (flow magnitude) at low discharges. Drastic changes in inflows should be considered for the effective conservation of flow heterogeneity, even under a regulated flow regime. Improved engineering design to manage the hydraulic environment is one option for maintaining the ecological value of lateral waterbodies in human-dominated landscapes. Our findings provide insights into the importance of functional flow heterogeneity to conserve fish species diversity.</span></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.