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181 results for “water relations”
Leaf water relations in epiphytic ferns
<p>Opportunistic diversification has allowed ferns to radiate into epiphytic niches in angiosperm dominated landscapes. However, our understanding of how ecophysiological function allowed establishment in the canopy and the potential transitionary role of the hemi-epiphytic life form remain unclear. Here, we surveyed 39 fern species in Costa Rican tropical forests to explore epiphytic trait divergence in a phylogenetic context. We examined leaf responses to water deficits in terrestrial, hemi-epiphytic, and epiphytic ferns and related these findings to functional traits that regulate leaf water status. Epiphytic ferns had reduced xylem area (-63%), shorter stipe lengths (-56%), thicker laminae (+41%), and reduced stomatal density (-46%) compared to terrestrial ferns. Epiphytic ferns exhibited similar turgor loss points, higher osmotic potential at saturation, and lower tissue capacitance after turgor loss than terrestrial ferns. Overall, hemi-epiphytic ferns exhibited traits that share characteristics of both terrestrial and epiphytic species. Our findings clearly demonstrate the prevalence of water conservatism in both epiphytic and hemi-epiphytic ferns, via selection for anatomical and structural traits that avoid leaf water stress. Even with likely canalized physiological function, adaptations for drought avoidance have allowed epiphytic ferns to successfully endure the stresses of the canopy habitat.</p>
Dataset (VII) related to publication: Decisive Role of Water and Protein Dynamics in Residence Time of p38a MAP Kinase Inhibitors
<p>MD simulation data of compound <strong>1</strong> in MSM <strong>2-<em>S</em><sub>3</sub></strong> conformations of the related to the publication Pantsar et al.: <em>Decisive Role of Water and Protein Dynamics in Residence Time of p38a MAP Kinase Inhibitors.</em></p> <p>Individual .zip files contain raw-desmond trajectories (-out.cms files and trj-files).</p> <p>All datasets related to this publication:</p> <p><a href="https://doi.org/10.5281/zenodo.4568113">https://doi.org/10.5281/zenodo.4568113</a>(compound <strong>1</strong>; dataset: I)</p> <p><a href="https://doi.org/10.5281/zenodo.4572444">https://doi.org/10.5281/zenodo.4572444</a> (compound <strong>1</strong>; dataset: II)</p> <p><a href="https://doi.org/10.5281/zenodo.4561797">https://doi.org/10.5281/zenodo.4561797</a>(compound <strong>2</strong>; dataset: III)</p> <p><a href="https://doi.org/10.5281/zenodo.4563896">https://doi.org/10.5281/zenodo.4563896</a> (compound <strong>2</strong>; dataset: IV)</p> <p><a href="https://doi.org/10.5281/zenodo.5563359">https://doi.org/10.5281/zenodo.5563359</a> (<strong>SB203580</strong>; dataset: V)</p> <p><a href="https://doi.org/10.5281/zenodo.5563655">https://doi.org/10.5281/zenodo.5563655</a> (<strong>SB203580</strong>; dataset: VI)</p> <p><a href="https://doi.org/10.5281/zenodo.5564118%20">https://doi.org/10.5281/zenodo.5564118 </a>(compound <strong>1</strong> simulated in compound <strong>2</strong> metastable state <strong>2-<em>S</em><sub>3</sub></strong>; dataset: VII)</p> <p><a href="https://doi.org/10.5281/zenodo.5564208%20">https://doi.org/10.5281/zenodo.5564208 </a>(compound <strong>1</strong> simulated in compound <strong>2</strong> metastable state <strong>2-<em>S</em><sub>3</sub></strong>; dataset: VIII)</p> <p><a href="https://doi.org/10.5281/zenodo.5564586">https://doi.org/10.5281/zenodo.5564586</a> (well-tempered metadynamics simulations of compounds <strong>1</strong> and <strong>2</strong>; dataset: IX)</p> <p><a href="https://doi.org/10.5281/zenodo.5570882">https://doi.org/10.5281/zenodo.5570882</a> (well-tempered metadynamics simulations of compounds <strong>1</strong> and <strong>2</strong>; dataset: X)</p> <p><a href="https://doi.org/10.5281/zenodo.5571352">https://doi.org/10.5281/zenodo.5571352</a> (well-tempered metadynamics simulations of compounds <strong>1</strong> and <strong>2</strong>; dataset: XI)</p> <p>The datasets include original Desmond raw-trajectories (datasets I–VIII), PDB-coordinates for the energy minimized metastable state derived structures (datasets II, IV and VI) and raw-trajectories of the well-tempered metadynamics simulations (dataset IX–XI).</p>
Dataset (VIII) related to publication: Decisive Role of Water and Protein Dynamics in Residence Time of p38a MAP Kinase Inhibitors
<p>MD simulation data of compound <strong>1</strong> in MSM <strong>2-<em>S</em><sub>3</sub></strong> conformations of the related to the publication Pantsar et al.: <em>Decisive Role of Water and Protein Dynamics in Residence Time of p38a MAP Kinase Inhibitors.</em></p> <p>Individual .zip files contain raw-desmond trajectories (-out.cms files and trj-files).</p> <p>All datasets related to this publication:</p> <p><a href="https://doi.org/10.5281/zenodo.4568113">https://doi.org/10.5281/zenodo.4568113</a>(compound <strong>1</strong>; dataset: I)</p> <p><a href="https://doi.org/10.5281/zenodo.4572444">https://doi.org/10.5281/zenodo.4572444</a> (compound <strong>1</strong>; dataset: II)</p> <p><a href="https://doi.org/10.5281/zenodo.4561797">https://doi.org/10.5281/zenodo.4561797</a>(compound <strong>2</strong>; dataset: III)</p> <p><a href="https://doi.org/10.5281/zenodo.4563896">https://doi.org/10.5281/zenodo.4563896</a> (compound <strong>2</strong>; dataset: IV)</p> <p><a href="https://doi.org/10.5281/zenodo.5563359">https://doi.org/10.5281/zenodo.5563359</a> (<strong>SB203580</strong>; dataset: V)</p> <p><a href="https://doi.org/10.5281/zenodo.5563655">https://doi.org/10.5281/zenodo.5563655</a> (<strong>SB203580</strong>; dataset: VI)</p> <p><a href="https://doi.org/10.5281/zenodo.5564118%20">https://doi.org/10.5281/zenodo.5564118 </a>(compound <strong>1</strong> simulated in compound <strong>2</strong> metastable state <strong>2-<em>S</em><sub>3</sub></strong>; dataset: VII)</p> <p><a href="https://doi.org/10.5281/zenodo.5564208%20">https://doi.org/10.5281/zenodo.5564208 </a>(compound <strong>1</strong> simulated in compound <strong>2</strong> metastable state <strong>2-<em>S</em><sub>3</sub></strong>; dataset: VIII)</p> <p><a href="https://doi.org/10.5281/zenodo.5564586">https://doi.org/10.5281/zenodo.5564586</a> (well-tempered metadynamics simulations of compounds <strong>1</strong> and <strong>2</strong>; dataset: IX)</p> <p><a href="https://doi.org/10.5281/zenodo.5570882">https://doi.org/10.5281/zenodo.5570882</a> (well-tempered metadynamics simulations of compounds <strong>1</strong> and <strong>2</strong>; dataset: X)</p> <p><a href="https://doi.org/10.5281/zenodo.5571352">https://doi.org/10.5281/zenodo.5571352</a> (well-tempered metadynamics simulations of compounds <strong>1</strong> and <strong>2</strong>; dataset: XI)</p> <p>The datasets include original Desmond raw-trajectories (datasets I–VIII), PDB-coordinates for the energy minimized metastable state derived structures (datasets II, IV and VI) and raw-trajectories of the well-tempered metadynamics simulations (dataset IX–XI).</p>
Dataset (V) related to publication: Decisive Role of Water and Protein Dynamics in Residence Time of p38a MAP Kinase Inhibitors
<p>MD simulation data of <strong>SB203580</strong> related to the publication Pantsar et al.: <em>Decisive Role of Water and Protein Dynamics in Residence Time of p38a MAP Kinase Inhibitors.</em></p> <p>Individual .zip files contain raw-desmond trajectories (-out.cms files and trj-files).</p> <p>All datasets related to this publication:</p> <p><a href="https://doi.org/10.5281/zenodo.4568113">https://doi.org/10.5281/zenodo.4568113</a>(compound <strong>1</strong>; dataset: I)</p> <p><a href="https://doi.org/10.5281/zenodo.4572444">https://doi.org/10.5281/zenodo.4572444</a> (compound <strong>1</strong>; dataset: II)</p> <p><a href="https://doi.org/10.5281/zenodo.4561797">https://doi.org/10.5281/zenodo.4561797</a>(compound <strong>2</strong>; dataset: III)</p> <p><a href="https://doi.org/10.5281/zenodo.4563896">https://doi.org/10.5281/zenodo.4563896</a> (compound <strong>2</strong>; dataset: IV)</p> <p><a href="https://doi.org/10.5281/zenodo.5563359">https://doi.org/10.5281/zenodo.5563359</a> (<strong>SB203580</strong>; dataset: V)</p> <p><a href="https://doi.org/10.5281/zenodo.5563655">https://doi.org/10.5281/zenodo.5563655</a> (<strong>SB203580</strong>; dataset: VI)</p> <p><a href="https://doi.org/10.5281/zenodo.5564118%20">https://doi.org/10.5281/zenodo.5564118 </a>(compound <strong>1</strong> simulated in compound <strong>2</strong> metastable state <strong>2-<em>S</em><sub>3</sub></strong>; dataset: VII)</p> <p><a href="https://doi.org/10.5281/zenodo.5564208%20">https://doi.org/10.5281/zenodo.5564208 </a>(compound <strong>1</strong> simulated in compound <strong>2</strong> metastable state <strong>2-<em>S</em><sub>3</sub></strong>; dataset: VIII)</p> <p><a href="https://doi.org/10.5281/zenodo.5564586">https://doi.org/10.5281/zenodo.5564586</a> (well-tempered metadynamics simulations of compounds <strong>1</strong> and <strong>2</strong>; dataset: IX)</p> <p><a href="https://doi.org/10.5281/zenodo.5570882">https://doi.org/10.5281/zenodo.5570882</a> (well-tempered metadynamics simulations of compounds <strong>1</strong> and <strong>2</strong>; dataset: X)</p> <p><a href="https://doi.org/10.5281/zenodo.5571352">https://doi.org/10.5281/zenodo.5571352</a> (well-tempered metadynamics simulations of compounds <strong>1</strong> and <strong>2</strong>; dataset: XI)</p> <p>The datasets include original Desmond raw-trajectories (datasets I–VIII), PDB-coordinates for the energy minimized metastable state derived structures (datasets II, IV and VI) and raw-trajectories of the well-tempered metadynamics simulations (dataset IX–XI).</p>
Dataset II related to the publication: In silico Evaluation of the Thr58-associated Conserved Water with KRAS Switch-II Pocket Binders
<p>Desmond trajectories of simulations conducted with TIP3P water model related to the publication:</p> <p>Leini R, Pantsar T: In Silico Evaluation of the Thr58-Associated Conserved Water with 2 KRAS Switch-II Pocket Binders. J. Chem. Inf. Model. [accepted] https://doi.org/10.1021/acs.jcim.2c01479</p> <ul> <li>Individual .zip files contain the Desmond trajectories and -out.cms -files.</li> </ul> <p>Related datasets: 10.5281/zenodo.7656467 and 10.5281/zenodo.7342311</p>
Dataset III related to the publication: In silico Evaluation of the Thr58-associated Conserved Water with KRAS Switch-II Pocket Binders
<p>Desmond trajectories of simulations conducted with TIP4P water model related to the publication:</p> <p>Leini R, Pantsar T: In Silico Evaluation of the Thr58-Associated Conserved Water with 2 KRAS Switch-II Pocket Binders. J. Chem. Inf. Model. [accepted] https://doi.org/10.1021/acs.jcim.2c01479</p> <ul> <li>Individual .zip files contain the Desmond trajectories and -out.cms -files.</li> </ul> <p>Related datasets: 10.5281/zenodo.7656467 and 10.5281/zenodo.7341954</p>
Tourists' perceptions of water quality in Finland, dataset, related to article "Browning of Boreal Lakes: Do Public Perceptions and Governance Meet the Biological Foundations?"
<p>Tourists' perceptions of water quality in Finland, dataset, related to article "Browning of Boreal Lakes: Do Public Perceptions and Governance Meet the Biological Foundations?" by Albrecht et al. (2022).<br> <br> <strong>Article abstract:</strong><br> "Surface water browning, also known as brownification, is an acute environmental issue concerning inland waters. We adopt an interdisciplinary perspective and combine limnology, ecology, environmental law, tourism, and economics to build a theoretical framework to understand the consequences and management needs concerning water browning, generate a research agenda, and pinpoint acute research needs. Using a systematic review approach, we identify gaps of knowledge and address the impacts of browning on lake ecosystem functioning. To support the biological information, we present primary survey data to define the recreational use and public perception of waters in Finland. We identified an urgent need for the development of indicators of brownification beyond EU’s Water Framework Directive (WFD) to be able to balance the costs of browning with terrestrial activities that increase browning. Despite a considerable body of research already exists, there is still a need for better understanding of the biogeochemical processes related to browning to progress towards ecosystem-based management of inland waters. Public perception of the quality of waterbodies in Finland was largely in agreement with the proportion of waterbodies classified to meet the good or excellent ecological status, but recreational fishers may value different aspects of water quality compared to the classification based on WFD. Consequently, to build an interdisciplinary understanding of how browning affects boreal lakes and their uses, we suggest improvements for environmental regulation concerning the impact assessment of terrestrial land use activities and ecosystem-based management of inland waters."</p>
New global dataset on historical water-related conflict and cooperation events
<p>The water-related conflict and cooperation events database was created as a part of a larger project: "The missing link: how does the climate affect human conflicts and collaborations through water?" where the goal is to increase understanding of how people and the climate affect water flows and how, in turn, these changes affect cooperation and conflicts over water. Formas, project 2017-00,608 support this project.</p> <p>The database includes a collection of cooperation and conflict events between 1951 and 2019. The Transboundary Freshwater Dispute Database (2010) and WCC (Pacific Institute, Oakland, CA, 2022) were used as data on water-related acts of cooperation and conflict over time. As TFDD cooperation data ends in 2008, cooperation events were extended following a similar methodology as was used in the creation of TFDD. Further, geographic locations and regional classifications were added to all events, which can be used to create visualizations and extract subsets of the database for different parts of the world. The database methodology flow chart included in the files gives a brief overview of steps taken to prepare and process the data into the database.</p> <p>The openly available scientific article in Science of the Total Environment (STOTEN) highlight findings using this dataset and gives further explanations relating to the database. The article can be found here: <a href="https://doi.org/10.1016/j.scitotenv.2023.161555">https://doi.org/10.1016/j.scitotenv.2023.161555</a>.</p>
Sea turtle relative abundance in nearshore waters adjacent to the Mississippi River delta, Gulf of Mexico, United States
<p><span>We measured the relative abundance of sea turtles using standardized transect surveys conducted during the summer and fall of 2013 in neritic waters surrounding the Mississippi River delta in Louisiana, USA. Data comprise sea turtle locations, observation circumstances, and environmental covariates recorded at the beginning of each transect and at the time of each turtle observation. Turtles were recorded by species and size class, as well as location in the water column and the distance the turtle was from the transect line. Transects were performed on an 8.2-meter vessel with two observers atop a 4.5-meter elevated platform, with vessel speed standardized at ~15 km/hr. These data are the first to describe relative abundance of sea turtles observed from small vessels in this region. Detection of turtles <45 cm SSCL and data detail are greater than aerial surveys. The data serve to inform resource managers and researchers regarding these protected marine species. </span></p>
Data, code, and output related to water lead levels
<p>The purpose of this research was to evaluate the need to repeatedly sample water from homes to identify infrequent, but high "spikes" in water lead levels due to the sporadic release of lead particulates. The Illinois and Pennsylvania data were used in establishing baseline (first round of sampling) water lead levels. The simulations were created using various assumptions of baseline prevalence and various probabilities of spike occurrence on the N+1 round of sampling, given the results on the N round.</p> <p>The findings of the research indicate that household tap water needs to be sampled at least 5–7 times to achieve a 50% probability of identifying hazardous spikes in water lead levels.</p>
Dataset I related to the publication: In silico Evaluation of the Thr58-associated Conserved Water with KRAS Switch-II Pocket Binders
<p>WaterMaps results related to the publication:</p> <p>Leini R, Pantsar T: In Silico Evaluation of the Thr58-Associated Conserved Water with 2 KRAS Switch-II Pocket Binders. J. Chem. Inf. Model. [accepted] https://doi.org/10.1021/acs.jcim.2c01479</p> <ul> <li>Individual .zip files contain the WaterMap results for each structure.</li> </ul> <p><em>Additional notes: there is a typo in the 5v90 file name (it is the 5v9o structure).</em></p> <p>Related datasets: 10.5281/zenodo.7341954 and 10.5281/zenodo.7342311</p>
Water-related vertical displacements for all GNET stations studied
<p>Water-related vertical displacements for all GNET stations studied. Vertical displacement time-series from the proposed analytic model, based on calibrated buffered water storage estimates.(1 column: Time; 2 column: Vertical displacement; 3 column: error)</p>
Data from: Species-specific variation in germination rates contributes to spatial coexistence more than adult plant water use in four closely-related annual flowering plants
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Leaf water relations in epiphytic ferns
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Fifteen physiological traits related to osmoregulation and reactive oxygen species metabolism in two life form aquatic plants under a natural water salinity gradient on the Tibetan Plateau and Northwest China
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Data from: Water the odds? Spring rainfall and emergence-related seed traits drive plant recruitment
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Data, code, and output related to water lead levels
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Sea turtle relative abundance in nearshore waters adjacent to the Mississippi River delta, Gulf of Mexico, United States
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Plant species percent cover data: Distribution of Wetland Plant Species in Relation to the Level of the Water Table
This study established permanent plots along transects in fifteen wetlands covering a range of wetland types. The plot are used to: 1) characterize the non-wooded wetlands at CCESR; 2) determine correlations of plant community type with environmental factors; 3) examine changes over a five year period.
RIBuild: Laboratory based investigations of the materials' water activity and pH relative to mould growth
<p>This dataset contains measurements of relative humidity and temperature in small test walls, from mycometer test and from measurements of moisture content in materials in the test walls.</p> <p>The objective of the study is to find the causes and conditions that lead to mould growth between a existing wall and installed insulation systems, and to suggest solutions to prevent mould growth.The study examines whether the alkaline environment (pH> 9), which may occur in the adhesive glue joint between the existing wall and the installed insulation is sufficient to prevent mould growth,even if the moisture (water activity (aw)) at the interface exceeds the levels (aw> 0.75) commonly considered critical for mould growth.</p> <p>The dataset also contains extensive photo documentation of preparations and carrying out the experiments.</p> <p>Further details to be found in appendix 5 of RIBuild deliverable 2.2 and in<br> Jensen, N.F., Bjarløv, S.P., Rode, C., Andersen, B., Møller, E.B. (submitted 2020). Laboratory based investigation of the materials’ water activity and pH relative to fungal growth in internally insulated solid masonry walls. Indoor Air. Wiley.</p> <p>Overview of data files to be found in 'RIBuild data WP2_DTU Small walls' as part of this dataset.</p>
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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.