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19,365 results for “watering”
Data for Water deficit and potassium affect carbon isotope composition in cassava bulk leaf material and extracted carbohydrates
<p>This repository contains data and scripts to reproduce results that are presented in the manuscript: Van Laere, J., Merckx, R., Hood-Nowotny, R., Dercon, G. (2023) Water deficit and potassium affect carbon isotope composition in cassava bulk leaf material and extracted carbohydrates. <em>Front. Plant Sci</em>. 14:1222558 doi: 10.3389/fpls.2023.1222558</p>
ECHAM6-wiso nudged simulation water isotopes and precipitation for the period 1990-2020 at the EastGRIP drilling location, Greenland
<p>This model dataset contains output produced with the isotope-enabled atmosphere GCM ECHAM6-wiso at T127L95 spatial resolution, nudged to the ERA-5 reanalysis product. The 6-hourly model output is provided for the period 01/1990-12/2020 for the grid cell containing EastGRIP drilling location in Greenland, centered at 75.27N, -36.57 E.</p> <p>The complete description of the simulation can be found in:</p> <p><em>Cauquoin, A. and Werner, M., 2021. High‐Resolution Nudged Isotope Modeling With ECHAM6‐Wiso: Impacts of Updated Model Physics and ERA5 Reanalysis Data. Journal of Advances in Modeling Earth Systems, </em><a href="https://doi.org/10.1029/2021MS002532">https://doi.org/10.1029/2021MS002532</a></p> <p>The provided files (netCDF) contain the ECHAM6-wiso model data used as input for the SNOWISO snow pack model in:</p> <p><em>Dietrich, L.J., Steen-Larsen, H.C., Wahl, S., Jones, T.R., Town, M.S. and Werner, M., 2023. Snow-atmosphere humidity exchange at the ice sheet surface alters annual mean climate signals in ice core records. Geophysical Research Letters, </em><a href="https://doi.org/10.1029/2023GL104249">https://doi.org/10.1029/2023GL104249</a><em>.</em></p> <p>The provided variables are:</p> <p> d18O_vapor: delta value for <sup>18</sup>O (‰) in the vapor of the lowest atmospheric layer (ECHAM level 95).<br> dD_vapor: delta value for H<sub>2</sub> (D) (‰) in the vapor of the lowest atmospheric layer (ECHAM level 95).<br> aprt: total precipitation (mm water equivalent per month)<br> d18O_precip: delta value for <sup>18</sup>O (‰) in the precipitation<br> dD_precip: delta value for H<sub>2</sub> (D) (‰) in the precipitation</p> <p><strong>Data usage notice:</strong></p> <p>If you use<strong> any of these data</strong> you should refer to:</p> <p><em>Cauquoin, A. and Werner, M., 2021. High‐Resolution Nudged Isotope Modeling With ECHAM6‐Wiso: Impacts of Updated Model Physics and ERA5 Reanalysis Data. Journal of Advances in Modeling Earth Systems, </em><a href="https://doi.org/10.1029/2021MS002532">https://doi.org/10.1029/2021MS002532</a></p>
dynamic water contact angle measurements of metallic glass coatings
<p>dynamic water contact angle measurements of Zr-Cu-Ag metallic glass coatings. The file named PBT is the non-coated sample. The other three samples were metallic glass coatings.</p>
Data and analysis scripts for: Recent acceleration in global ocean heat accumulation by mode and intermediate waters
<p>The folder contains the MATLAB code and data to re-create Figures 1-9 and S1-3 within the publication by <em>Li, Z., England, M. H., & Groeskamp, S. Recent acceleration in global ocean heat accumulation by mode and intermediate waters, Nature Communications</em>, 2023.</p>
Methane and carbon dioxide fluxes from vegetated and open water zones of lakes in the Peace-Athabasca Delta, Alberta, Canada, 2019
Shallow areas of lakes, known as littoral zones, emit disproportionately more methane than open water but are sometimes ignored in upscaled estimates of lake greenhouse gas emissions. Littoral zone coverage may be estimated through synthetic aperture radar (SAR) mapping of emergent aquatic vegetation, which only grows in water less than ~1.5 m deep. In an accompanying publication, we combine airborne SAR mapping with field measurements of littoral and open-water methane flux to assess the importance of littoral zones to landscape-scale methane emissions. This dataset contains the field measurements of chamber methane flux from vegetated littoral zones and open water used for the accompanying publication. Measurements come from 24 distinct sampling events of 15 lakes in the Peace-Athabasca Delta, Alberta, Canada in July through August, 2019. The dataset also includes within-lake locations, carbon dioxide measurements, simple characterizations of vegetation type, and associated limnological and meteorological measurements, when available: water and air temperature, water depth, wind speed and direction, and relative humidity.
State Water Project, Genetic Determination of Population of Origin 2011-2021
Central Valley Chinook Salmon populations differ in their Endangered Species Act listing status. It is often difficult to distinguish individuals from the different Evolutionarily Significant Units. As such, many of the salmon monitoring and evaluation efforts in the Central Valley and San Francisco Bay-Delta are hampered by uncertainty about population (stock) identification and proportional effects of management actions (Dekar et al. 2013; IEP 2019). Studies have identified that the current identification method (length-at-date models) of juvenile Chinook salmon (Fisher 1992) captured in the watershed vary in their accuracy, particularly for spring-run (NMFS 2013; Harvey et al. 2014; Merz et al. 2014). The inaccuracy of the size-based methods is likely due to differences in fish distribution during early rearing, habitat-specific growth rates, and inter-annual variability in temperatures and food availability that lead to overlap in size ranges among stocks. The primary objective of this project was the genetic classification (to race; Evolutionary Significant Unit) of Chinook Salmon captured from State Water Project and Central Valley Project fish protection facilities and Interagency Ecological Program monitoring programs. The population-of-origin was determined for sampled fish by comparing their genotypes to reference genetic baselines. Genetic methods, having less statistical uncertainty that size-based models for population identification, were intended to directly target (and reduce) one source of uncertainty in the estimation of loss (take) from water diversions (operations) and develop the information necessary for understanding stock-specific distribution, habitat utilization, abundance, and life history variation. This project supports recommendations from the Interagency Ecological Program’s Salmon and Sturgeon Assessment of Indicators by Life Stage and Interagency Ecological Program Science Agenda efforts to improve Central Valley salmonid monitoring
Surface and bottom hourly water temperature from the San Francisco Estuary, 2012-2019
Projected temperature increases due to global climate change are likely to have localized impacts on the San Francisco Estuary (SFE). Increased water temperature in the SFE will lead to challenges for managing water resources. Many native species, such as salmon and smelt, rely on cooler water, and will be further stressed by increased water temperature, which may cause them to seek microrefugia. While several state and federal agencies in the SFE collect real-time water temperature data, most of the water temperature collection sites are at a fixed location or floating near the surface of the water column. This dataset includes four real-time water quality stations that provide water temperature data for both the surface and bottom positions in the water column. We obtained surface water temperature data from an integrated hourly water temperature dataset (https://doi.org/10.6073/pasta/7385985f68b02c0deb2a9e425a9f3ad8). This dataset included data downloaded from the California Data Exchange Center (CDEC; https://cdec.water.ca.gov/) and cleaned with a series of quality control (QC) checks (see integrated dataset metadata). We obtained bottom temperature data from the California Department of Water Resources (DWR) internal database Water Quality Portal (WQP). Data were integrated and standardized to hourly water temperature data in degrees Celsius, and the same series of quality control (QC) checks from the surface dataset were applied in a consistent manner to all stations. Bottom temperatures were selected from surface temperatures to provide measures of temperature difference. Datasets included in this package include source hourly surface and bottom data, both obtained from DWR’s WQP, as well as an integrated dataset of cleaned hourly surface and bottom data, with calculated surface-bottom temperature differences. Both datasets are filtered to the timeframe used in an analysis of surface-bottom temperature differences. Additionally, information regarding current
Sodium, chloride and specific conductance in stream water and groundwater in New Hampshire 1991, 2000 – 2021
Stream water was collected at weekly to monthly intervals at 29 stream sites in New Hampshire (USA). Ten of the stream sites were instrumented with high‐frequency sensors. Twenty-one of the stream sites (including 5 sensor sites) are in the Lamprey River Hydrologic Observatory (LRHO; Wymore et al 2021) and two stream sites were nearby the LRHO. Groundwater was collected from two riparian well fields (JF, 14 wells and WHB, 13 wells). Wells were installed in 2004 and sampled monthly through May 2007, then quarterly until December 2009, after which a subset (JF, 6 and WHB, 5) was generally sampled quarterly. Stream and groundwater samples span a 17-year collection period and were analyzed for sodium, chloride and specific conductance. Methods and findings are described in the associated Limnology and Oceanography Letters manuscript.
Southwest United States Wetland Water Quality and Macroinvertebrate Data 2018-2022
Water quality and macroinvertebrate data were collected between 2018 and 2020 from 14 different wetland and riparian sites spanning across West Texas, New Mexico, and Arizona. Water quality data such as Cl, SO4, and conductivity were collected as well as nutrients such as NO3, PO4, and Total Dissolved Nitrogen. Macroinvertebrate data were collected from all sites during the summer months (June, July, and August).
High-frequency water quality and air parameters from large lake Võrtsjärv, Estonia: 2010-2019
This high frequency water-air dataset was collected from large shallow Lake Võrtsjärv (Estonia) with an automated lake monitoring buoy system and was used in the analyses described in the manuscript by Thayne, M.W., B. Kraemer, J.P. Mesman, A. Laas, E. de Eyto, B. W. Ibelings, R. Adrian. “Trophic state effects on antecedent lake characteristics shape the resistance and resilience of lakes following extreme storms”. Dataset contains every 10-minute measurements from the open water periods in years 2010-2019. Underwater measurements were conducted with Yellow Springs Instrument multiparameter sonde model YSI 6600 V2-4. Underwater measurements contain the collected values of pH, dissolved oxygen, dissolved oxygen saturation, water temperature, specific conductance, water turbidity, chlorophyll concentration (calculated by the sensor from fluorescence values), and the abundance of the bluegreen algae (calculated by the sensor from phycocyanin fluorescence values). Air parameters were collected with the Vaisala multiparameter weather station model WXT520 and contain measurements of wind direction, wind speed, air temperature, atmospheric pressure, and cumulative amount of rain between measurement periods. All air measurements were collected 2 m above from the water surface. Additionally, solar irradiance measurements were collected from the automated buoy system with the Licor pyranometer model LI-200, those measurements contain values in two different columns: average solar irradiance in W/m2 and average photon flux density values in micromoles per square meter per second.
Water quality measurements, stream order, channel slope and hydraulic equations of conterminous USGS sites: 1919-2009.
Streams and rivers emit petagrams of CO2 yet there is little known about how discharge (Q) variability impacts stream CO2 at broad scales. Herein, we compiled historical water quality (including pH, alkalinity and temperature) measurements for conterminous USGS sites and coupled them with daily Q for this analysis (the water_quality.csv dataset, 10,822 sites). Based on this dataset, NHDplus channel slopes (NHDplus_slopeSO.csv, 24,764 sites) and hydraulic geometry equations (lm_vQ.csv, 12,854 sites), we calculated partial pressure of dissolved CO2 (pCO2), gas transfer velocity (k) and CO2 effluxes (F) for a total of 813 USGS sites across conterminous US. We derived hydrologic responses (log-linear regressions) for pCO2, k and F versus Q at each site and explored how these responses varied across stream order and different regions. Ancillary datasets provided coordinates (coor_sites.xls), hydrologic unit code (HUC.csv), and watershed area of conterminous USGS sites (watersheds_area.csv).
Greenhouse Gas and Water Chemistry Data from Ponds in the Twin-Cities area of Minnesota, 2021
Freshwaters are significant contributors of greenhouse gases to the atmosphere, including carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O). Small waterbodies such as ponds are now recognized to have disproportionate greenhouse gas emissions relative to their size, but recorded emissions from ponds have varied by several orders of magnitude. To assess drivers of variation in pond greenhouse gas dynamics, this study measured concentrations and emissions of CO2, CH4, and N2O across 26 ponds in Minnesota, USA during the ice-free season. The studied ponds ranged in land-use, from urban stormwater ponds to natural forested ponds. Water chemistry variables were measured with sonde profiles as well as surface water samples. Greenhouse gas emsisions of CO2 and CH4 were measured with a floating chamber at three locations on each pond, and gas concentrations of CO2, CH4, and N2O were measured using a headspace equilibrium technique in both the surface waters and bottom waters of each pond.
LAGOS-NE v.1.054.1 Lake water clarity time series (1987-2011), climate, and geophysical data for 601 lakes across a 17-state region of the United States
Time series of median summer water clarity (secchi) values from 601 unique lakes in the Midwest and Northeast United States. Water clarity observations were derived from the Lake Multi-Scaled Geospatial and Temporal Database LAGOS-NELIMNO version 1.054.1. These data were used to assess long-term changes in water clarity from 1987-2011, and the potential drivers of those trends (Lottig et al. in press). Summer open water period was used to approximate the stratified period in the study lakes, which was defined as June 15 to September 15. Over the 25-year time period, each lake had to have at least a single summer water clarity observation for 22 of 25 years. The median number of secchi measurements that were used to derive a single annual median value for each lake was approximately 9. Of the over 14,000 annual estimates of water clarity that we generated, only two percent of those annual values were generated from a single observation and median number of observations for each lake over the 25-year study period was 223. Each unique lake with water clarity data also has supporting geophysical data, including climate, land use, hydrology, and topography derived at multiple spatial scales. Lake-specific characteristics, such as depth and area, are also reported. The geospatial data came from LAGOS-NEGEO version 1.03 except for the annual climate data which was aggregated at the HUC8 spatial scale from monthly PRISM data. For more specific information on how LAGOS-NE was created, see Soranno et al. 2015. Citations: Lottig, N.R., P-N. Tan, T. Wager, K.S. Cheruvelil, P.A. Soranno, E.H. Stanley, C.E Scott, C.A. Stow, and S. Yuan. in press. Macroscale patterns of synchrony identify complex relationships among spatial and temporal ecosystem drivers. Ecosphere Soranno P.A., Bissell E.G., Cheruvelil K.S., Christel S.T., Collins S.M., Fergus C.E., Filstrup C.T., Lapierre J.-F., Lottig N.R., Oliver S.K., Scott C.E., Smith N.J., Stopyak S., Yuan S., Bremigan M.T., Downing J.A., G
Measurements of water column chemistry taken hourly over 24-hour periods at three sites in West Falmouth Harbor from 2006 to 2019
West Falmouth Harbor (West Falmouth, MA, USA) has been experiencing a dramatic increase in nitrogen loading from an upgradient municipal wastewater treatment facility since the early 2000’s. As part of a long-term study into the effects of this nitrogen enrichment, we have been measuring water chemistry at stations throughout the harbor to examine nutrient concentrations along the gradient from the highest loaded areas of the site to the most well-flushed. Water samples were taken hourly over 24-hour periods at 3 stations between 2006 and 2019. Due to covid restrictions on field and laboratory work, samples were not collected in 2020-2021; sample collection resumed in 2022 and data will be added after analysis. One station is in the well-flushed outer basin (OH) and one in the inner basin closer to the dominant groundwater N source (Snug Harbor, SH). These two were sampled at least once per year between 2006 and 2019. In two years, samples in the OH were taken at a location approximately 140m from the long-term site from this dataset. Those data can be accessed at doi:10.6073/pasta/73408abf801827966041c219f4222c1f. A third station is in the middle between the two, and was sampled in 2016 and 2018. Samples were processed for ammonium, phosphate, nitrate + nitrite, total nitrogen, and total phosphorus. On some dates, additional samples were run for silicate and chlorophyll. Salinity is reported for all samples. Samples were collected with an ISCO autosampler and stored on ice until analysis. Full analysis details and quality control methods are available in Hayn et al. 2014 (doi: 10.1007/s12237-013-9699-8).
Petit-lac-Saint-François surface water quality monitoring data
Water Quality samples were collected at Lake Inlet, Outlet, and In-Lake sites between October 2009 and September 2020. Water Samples were collected on a weekly, same-day-of-the-week basis, between 10 a.m. and noon, year-round. Field sampling was conducted by the same technician during the entire period to ensure method consistency and sampling frequency was maintained throughout, except for the winter of 2017, during which sampling was suspended. Epilimnion samples were collected using a swing sampler with a wide neck, polyethylene bottle (Nasco Sampling, Madison, WI, USA), and composited in an acid-washed, opaque, 4-L polyethylene bottle pre-conditioned with lake water. Four grab samples were taken to account for spatial heterogeneity that can be substantial within distances of a few meters, particularly when surface phytoplankton blooms are present. The grab samples were collected by tilting the swing sampler bottle approximately 45 degrees and allowing it to fill as it was submerged 8 to 15 cm below the surface. During periods of ice cover, access holes were drilled or cut through the ice to collect samples. For dissolved parameters, samples were filtered on the same day as collection. Quality control measures, including field, transport, and laboratory blanks, consisting of HPLC grade water and preservative where required, as well as split samples for interlaboratory comparisons, were included quarterly in the sampling program along with regular samples. These were used to establish practicable detection limits and to monitor for levels of contaminants to which field samples might be exposed.
Water quality, phytoplankton, and zooplankton in the Sacramento Deep Water Ship Channel, CA
Drivers of phytoplankton and zooplankton dynamics vary spatially and temporally in estuaries due to variation in hydrodynamic exchange and residence time, complicating efforts to understand controls on food web productivity. We conducted approximately monthly (2012 – 2019; n = 74) longitudinal sampling at ten fixed stations along a freshwater tidal terminal channel in the San Francisco Estuary, California, characterized by seaward to landward gradients in water residence time, turbidity, nutrient concentrations, and plankton community composition. We used multivariate autoregressive state space (MARSS) models to quantify environmental (abiotic) and biotic controls on phytoplankton and mesozooplankton biomass. The importance of specific abiotic drivers (e.g. water temperature, turbidity, nutrients) and trophic interactions differed significantly among hydrodynamic exchange zones with different mean residence times. Abiotic drivers explained more variation in phytoplankton and zooplankton dynamics than a model including only trophic interactions, but individual phytoplankton-zooplankton interactions explained more variation than individual abiotic drivers. Interactions between zooplankton and phytoplankton were strongest in landward reaches with the longest residence times and the highest zooplankton biomass. Interactions between cryptophytes and both copepods and cladocerans were stronger than interactions between bacillariophytes (diatoms) and zooplankton taxa, despite contributing less biovolume in all but the most landward reaches. Our results demonstrate that trophic interactions and their relative strengths vary in a hydrodynamic context, contributing to food web heterogeneity within estuaries at spatial scales smaller than the freshwater to marine transition.
New Hampshire Soil Sensor Network: Air Temperature, Soil Temperature, Soil Water Content, and Soil Electrical Conductivity, 2012 - ongoing
The goal of the New Hampshire Soil Sensor Network is to examine spatial and temporal changes in soil properties and processes as the climate changes. Data collected can also calibrate and validate models that examine how ecosystems may respond to changing climate and land use. To determine how soil processes are affected by climate change and land management, this soil sensor network measures snow depth, air temperature, soil temperature, soil volumetric water content, and soil electrical conductivity, as well as soil CO2 fluxes. This data package includes data from the air temperature, soil temperature, soil volumetric water content, and electrical conductivity sensors. Data were collected at the following sites: BRT = Bartlett Experimental Forest, Bartlett, NH; BDF = Burley-Demmerit Farm, Lee, NH; DCF = Dowst Cate Forest, Deerfield, NH; HUB = Hubbard Brook Experimental Forest, Woodstock, NH; SBM = Saddleback Mountain, Deerfield, NH; THF = Thompson Farm, Durham, NH; and Trout Pond Brook, Strafford, NH.
High-frequency water temperature, chlorophyll fluorescence, wind speed, and photosynthetically active radiation data for 18 globally-distributed lakes 2008 - 2013
Abstract: This dataset was used in the analysis described in the manuscript by Rusak, J. A.J. Tanentzap, J.L. Klug, K. Rose, L.A. Winslow R. Smyth, E. Jennings, D. Pierson, S. Hendricks, A. Laas, E. Ryder, D. White, R. Adrian, L. Arvola, E. de Eyto, H. Feuchtmayr, M. Honti, V. Istanovics, I. Jones, C. McBride, S. Schmidt, G. Zhu. Wind and trophic status explain the temporal and spatial variability of chlorophyll in lakes. In review: Limnology and Oceanography Letters. The variation in chlorophyll fluorescence from 18 globally distributed lakes, was tested at monthly, daily and hourly scales in related to high-frequency measurements of wind, water temperature and radiation within lakes as well as lake productivity and morphometry among lakes. Overall, monthly variation in algal biomass was greater than that expressed at either daily or hourly scales but, combined, these latter time scales were equivalent to seasonal variation. Among lakes, algal biomass variation increased with trophic status while, within-lake variation increased with increasing wind speed variation. Together, our results suggest that predicted changes associated with a changing climate, as well as widespread ongoing cultural eutrophication, have the potential to substantially alter the variability of algal biomass and thus the predictability of the services it provides. This dataset includes the data used in the analysis described above.
NEON Biorepository Surface Water Microbe Collection (Sterivex Filters) (repackaging of occurrences published by the NEON Biorepository Data Portal)
This collection contains surface water microbe samples collected on 67 mm long, 1.7 cm diameter, 0.22 um Sterivex capsule filters (NEON sample class: amc_fieldCellCounts_in.archiveID). Surface water microbe samples are collected at the same time and location as surface water cell count samples and surface water chemistry samples once per month in wadeable streams (12 times per year) and every-other month in lakes and rivers (6 times per year). Details on sampling locations and timing are provided in the NEON document titled Surface Water Chemistry Sampling in Aquatic Habitats (https://data.neonscience.org/documents). In wadeable streams, surface water microbe samples are collected near the downstream S2 sensor location. In lakes, microbial samples are collected near the the 'buoy', 'littoral 1', and 'littoral 2' sensors, and sampling depth(s) is dependent on lake stratification. In rivers, microbial samples are collected near the buoy sensor. Water samples are filtered on 0.22 um Sterivex capsule filters, capped and flash-frozen in the field. Sterivex filters are archived at the NEON Biorepository at -80 degrees Celsius. See related links below for protocol.
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.
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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.