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566 results for “ponds”
Data from: Group size and dispersal ploys: An analysis of commuting behaviour of the pond bat (Myotis dasycneme)
<p>This study aimed to provide a description on how Pond bats (<em>Myotis dasycneme</em>) disperse, how to recognize a commuting route, and details about the effort needed to make a complete survey of one commuting route. The study area covered the provinces of Zuid-Holland, Overijssel, Friesland, Noord-Holland, and Utrecht. During 6 years of study between 2002 and 2009, researchers and bat volunteers studied pond bats along several waterways (all waterways wider than 10 m) between known roosts and their hunting areas. All the observations were made between April and September, starting 20 min before sunset. During the entire observation effort, the time (in hours and minutes) and direction of each bat was recorded. The time that each bat passed the observation location was later transformed to minutes after sunset. The number of animals on commuting route was related to the number of animals present in their respective roost.</p> <p> </p> <p>Data are organized in 3 files: <strong>commuting data 10 minutes.csv</strong>, <strong>commuting data.csv</strong> and <strong>observations waddinxveen.csv</strong>. The variables in these data files are explained here:</p> <p>Date: the observation date</p> <p>Location description: description of the location</p> <p>X Y: The coordinates of the location in RD. The RD (Rijks-Driehoek) system is the coordinate system used by the Dutch geographical service.</p> <p>Long Lat: The coordinates of the location in longitude and latitude.</p> <p>Distance over water: commuting distance over water. For each route, the distance (d) over water between roost and observation location was measured from a topographical map and expressed in kilometres.</p> <p>Moon cover: the amount of moon cover, expressed in percentages.</p> <p>Roost location: the assumed location of the roost of the bats passing on their commuting route</p> <p>Max N of bats in roost: the max number of bats observed emerging from a roost.</p> <p>Sum N of bats over 10-minute interval: the sum of all the observed bats passing in one direction within a 10-minute interval</p> <p>Time after sunset in 10 min: the begin time of each interval, measured in minutes after sunset</p> <p>Peak time after sunset: the time of the observed peak in numbers of bats, in minutes after sunset.</p> <p>Area: the municipality near the observation location.</p> <p>Total N of pond bats on route: the total number of pond bats observed on route, in the given observation time. Including foraging and returning bats.</p> <p>Total N of commuting pond bats: the total number of bats observed commuting (excluding all other behaviours).</p> <p>Time of first bat minutes after sunset: the time of the first bat, measured in minutes after sunset.</p> <p>Duration of commuting: the time in hours between the first and the last bat observed commuting.</p> <p>Observation time: the total duration (in minutes) of the observation period.</p> <p>Moon phases: a 1–3 scale, where c1 is the new moon, c2 is the first quarter, c3 half moon, c4 is the last quarter and c5 is the full moon.</p> <p>Cloud cover: estimation of the cover, using the following three categories: c1-0%–25% cover (clear night sky or some isolated clouds), c2-25%–75% cover (several scattered clouds but not covering more than 75% of the night sky), and c3- 75%–100% cover (scattered clouds covering more than 75% of the night sky to a completely overcast night sky</p> <p>Observation type: observation of either emerging bats from a roost (roost) or bats observed on commuting route (commuting).</p> <p> </p> <p>In addition, we also provide 2 pdf’s containing the observation protocols (in Dutch) for counting emerging bats (<strong>Handleiding tellen van een groep meervleermuizen.pdf</strong>) and bats along a commuting route (<strong>Handleiding vliegroute telling.pdf</strong>). The protocols are intended for professionals and citizen scientists.</p>
Data from: Male long-distance migrant turned sedentary; The West European pond bat (Myotis dasycneme) alters their migration and hibernation behaviour
<p>Winter survey data, temperature data and mark recapture data of <em>Myotis dasycneme</em>. This study aimed to better understand the migration, mating and hibernation choices of the pond bat.</p> <p> </p> <p>The study area covered the whole of the Netherlands, Belgium and East Frisia (northwest Germany). We defined two study periods, data collected between 1930 and 1980 (Sluiter and van Heerdt) and data between 1980 and 2015 (Haarsma). All available mark and recovery data (ringing) of both the historical and recent migration research were digitized. Observations include location and date of capture, species, sex and ring number. The latest observations in the recent dataset (Haarsma) also include biometric measurements (forearm length, body mass) and information about age and reproductive status. These biometric measurements show that male pond bats are on average smaller and lighter than females (body mass (g)/ forearm length (mm) females: 18.9/47.1, males: 16.4/46.4). The dataset shows changes in the fat mass of both sexes during a year.</p> <p>This study also compares migration data with winter monitoring survey data. We selected winter roosts with three or more records of three or more pond bats in one or both of the study periods. Only data from sites with long-term data series (from the hibernacula in the Dutch provinces of Zuid-Holland, Gelderland and Limburg) were used to analyse trends and annual abundance. Our selection included 59 limestone mines in the province of Limburg and 16 WOII bunkers in Gelderland and 38 in Zuid-Holland. We divided the sites into 'core' and 'satellite' sites depending on the timing of first colonization.</p> <p> </p> <p><strong>Bunker limestone mine microclimate</strong></p> <p> </p> <p>Radiation temperature: radiation temperature of the wall, measured with a non-contact infrared thermometer</p> <p>How many bats: the group size of each bat/ group of bats observed, categorized as alone and group.</p> <p>Where: the hanging location of the observed bat, categorized as hidden (in crevice) or free (free on ceiling or wall)</p> <p>Date: date of the observation</p> <p>Xy-coord: The coordinates of the entrance of the bunker or limestone mine. The RD (Rijks-Driehoek) system is the coordinate system used by the Dutch geographical service.</p> <p>Type: Bunker or limestone</p> <p>Location description: description of the name of the site</p> <p> </p> <p><strong>Bunker monitoring core and satellite</strong></p> <p> </p> <p>Date: date</p> <p>Winter: the period between September and April is defined as the winter of the year starting in January.</p> <p>Location description: description of the name of the site</p> <p>N of pond bats: total number of observed pond bats</p> <p>Province: the province</p> <p>Type: hibernacula categorized as a core or satellite site, sites occupied by pond bats since 1977 and 1997 respectively.</p> <p>XY-coord: The coordinates of the entrance of the bunker or limestone mine. The RD (Rijks-Driehoek) system is the coordinate system used by the Dutch geographical service.</p> <p> </p> <p> </p> <p><strong>Supporting information (as referenced in the published paper, hence also available with plos one)</strong></p> <p><br> <strong>S1 Fig. The range of the West European pond bat population (TIF).</strong> The shaded areas indicate the<br> areas where the bulk of the surveys were carried out.</p> <p><br> <strong>S2 Fig. The distribution of the pond bat in Europe (country boundaries are only indicative) (JPG).</strong> Within the whole range of the species distribution seven groups can be separated.<br> A The Netherlands, Belgium and Northwest Germany (~the West European population),<br> B Jutland Peninsula,<br> C Central European lakelands,<br> D The Baltic States,<br> E Ural Mountains (hibernacula),<br> F Volga Valley (summer nurseries),<br> G Hungary and Romania.<br> <br> <strong>S3 Fig. The distribution of hibernacula used by the western pond bat population (TIF). </strong>These are<br> sites with three or more records of pond bats in one or both study periods. We identified four<br> roost categories: Roosts which have been used ever since 1900 (= green squares), roosts used<br> only between 1900–1980 (= open black squares), roosts occupied after 1980 (= purple circles),<br> roosts occupied after 1997 (= blue asterisks). Detailed maps, all with the same enlargement, of<br> the clusters in the provinces of Zuid-Holland (1), Gelderland (1) and Limburg (3) are provided.<br> <br> </p> <p><strong>S1 Table. Summary of the average weight of pond bats over the study period.</strong> The weight is averaged per week. The table gives average weight of females, males both adults and juveniles.</p> <p> </p> <p>Avg weight: average weight of pond bats of each sex, in a certain week</p> <p>Sex: male of female</p> <p>Week number: number of the week</p> <p>Age: juvenile (or young of the year). Defined as the from birth until the onset of first hibernation. Subadult or sexual immature, defined as individuals with no signs of (past) reproductive activity. Adult or sexual mature, defined as all individuals with signs of (previous) reproductive activity.</p> <p>N observations: number of observations within each subset.<br> </p> <p><strong>S2 Table. Mark and recapture data from the historical dataset.</strong><br> </p> <p>Ringnumber: the label of the ring</p> <p> Sex: male or female</p> <p>capture date: date of capture</p> <p>capture location: description of capture location</p> <p>x y coordinate: The coordinates of the capture location in RD. The RD (Rijks-Driehoek) system is the coordinate system used by the Dutch geographical service.</p> <p>recapture date: date of recapture</p> <p>recapture location: description of recapture location</p> <p>x y coordinate: The coordinates of the recapture location in RD. The RD (Rijks-Driehoek) system is the coordinate system used by the Dutch geographical service.</p> <p> </p> <p><strong>S3 Table. Mark and recapture data from the recent dataset.</strong></p> <p> </p> <p>Same dataset as the historical set, but now including age (see definition used in S1)<br> <br> </p>
The raw data of Souma, Katano, Doi et al. "Comparing environmental DNA with whole pond survey to estimate the total biomass of fish species in ponds" in Freshwater Biology
<p>The raw data of Souma, Katano, Doi, Takahara, and Minamoto. "Comparing environmental DNA with whole pond survey to estimate the total biomass of fish species in ponds" in Freshwater Biology.</p>
The first 10m resolution thermokarst lake and pond data set in the Lena basin during 2020 thawing season
<p>We present the first 10m resolution thermokarst lake and pond data set in the Lena basin during 2020 thawing season. A mapping workflow was proposed and implemented on the Google Earth Engine (GEE) platform. The accuracy assessment demonstrates a satisfactory overall accuracy of 93.63%, and comparing with several land cover and waterbody products, our results exhibited better consistency with TLPs under real conditions.</p>
Dataset - Drying out fish ponds, for an entire growth season, as an agroecological practice: maintaining primary producers for fish production and biodiversity conservation
<p>This dataset is based on samples taken from fish ponds in the Dombes region between 2007 and 2014. It includes sediment and water physio-chemistry data, as well as primary producer diversity, benthic invertebrate density and fish yield for 85 different ponds. All these data are linked to the distance to the last dry-out, a major practice in extensive fish farming in this region.</p> <p>There are two .tab and .csv files:<br> One containing the dataset<br> One containing the description of the different variables (Metadata)</p>
Pond data: physical, chemical, and biological characteristics with scientific and United States of America state definitions from literature and legislative surveys
Ponds are often identified by their small size and shallow depths, but the lack of a universal definition hampers science and weakens legal protection. In order to determine a working definition of ‘pond’, we conducted a literature search for scientific definitions, a U.S. state survey for management definitions, and looked at pond ecosystem function using data from the literature search. Our dataset includes physical, chemical, and biological data for 1327 waterbodies ≤ 20 ha in surface area and ≤ 9 m in maximum or mean depth from our literature review. These data have a global distribution, we include a table of latitudes and longitudes, and span many years (1946-2019). We have also included a table of 54 pond definitions from the literature review and a table of U.S. state definitions of ponds, wetlands, and lakes resulting from our survey.
Under-ice lake physicochemical data, Missisquoi Bay and Shelburne Pond, Vermont, USA, 2014-2015
This dataset contains under-ice physicochemical data from Missisquoi Bay and Shelburne Pond in Vermont, USA collected during the 2013-2014 and 2014-2015 winters and spring thaw periods. The main dataset contains data for ice depths, water column sampling depths, nutrient chemistry, chlorophyll a, and relevant physicochemical variables. Ancillary data includes nearby air temperature data for the study periods as well as river discharge data for contributing or nearby tributaries. Data collection is complete.
Northeastern Mountain Ponds Geochemistry Compilation 1978-2019
We compiled geochemical data from published, peer-reviewed sources, gray literature, online datasets, unpublished researcher datasets, and our own data from high-elevation ponds and small lakes. Mountain ponds were defined as lakes and ponds situated at elevation >500 m (460 m in the Berkshires), and ponds surface area <60 ha. Many of our data sets are part of the US EPA LTM (Long-Term Monitoring) Network and its predecessor projects (e.g., Maine HELM, ELS-II, various scoping efforts for LTM), and state data repositories. We queried data providers and EPA staff about mountain ponds datasets in the region. We defined the region of interest (“the northeastern US”) as the Northern Appalachian Region, plus the Adirondack Mountains in New York State, ranging from latitude 42◦–46◦ north and longitude 75◦–69◦ west. We classified ponds into their respective mountain regions within Level II Ecoregion 58 – Northern Highlands, within Eastern Temperate Forest: Western Mountains (Maine’s Mahoosuc and White Mountains, to the terminus of the Appalachian Trail in Baxter State Park); White Mountains (in New Hampshire); Green Mountains (in Vermont); Berkshires (Western Massachusetts), and Adirondacks (in Adirondack Park, NY), to aid in sub-regional comparisons and statistical trend analyses.
Sediment, C, N, and P Concentrations and Burial Rates in Three Southwestern Ohio Retention Ponds: 2006-2019
These datasets correspond to Rogers et al (2022) “Temporal patterns in sediment, carbon, and nutrient burial in ponds associated with changing agricultural tillage” published in Biogeochemistry (DOI: 10.1007/s10533-022-00916-w). We sampled three retention ponds in southwest Ohio in 2019 to compare sediment, carbon, nitrogen, and phosphorous burial rates to those calculated in 2006 to see the effect a watershed-wide shift to conservation tillage and to estimate the value of the ecosystem services these ponds provide via sequestration. Two methods were used to calculate burial rates: simple mean and spatially explicit. All datasets use simple mean except for the data set named “Spatially Explicit Sediment C N P Burial in SW OH Retention Ponds 2019”, which uses the spatially explicit method. For more information, please refer to our paper.
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.
South Bay Salt Pond Restoration Project – Phase-1 (2014-2017) Fish Sampling for Mercury Studies.
The South Bay Salt Pond Restoration Project, the largest wetland restoration project in the western United States, is conducting an adaptive management experiment to restore tidal flows to the tidally muted pond A8 complex. The A8 pond complex is a series of interconnected ponds (A8, A7, and A5) located at the interface of the Guadalupe River with Alviso Marsh in Lower South San Francisco Bay that has had a legacy of mercury contamination from cinnabar open-pit mining in the Guadalupe River watershed. As a result, restoration of salt pond habitats in the Alviso Marsh has taken an adaptive management approach whereby fish populations, water and sediment were monitored for mercury contamination before and after restoration actions and data was used to inform further restoration actions in the A8 complex. In this study, UC Davis conducted fish sampling to collect 2-sentinel species, the Three-spine Stickleback and Mississippi Silverside to assess whole-body mercury concentrations. Fish were collected seasonally (4-5 surveys-year) from spring 2014 through winter 2017 at two slough locations exchanging water with the A8 complex, one in upper Alviso Slough (ALSL-2) at the Alviso Municipal Marina boat launch and on in lower Alviso Slough (ALSL-3) near the pond A7 water control structure, and in two reference sloughs, Artesian/Mallard Slough just downstream from the San Jose-Santa Clara Regional Wastewater Facility outfall and Guadalupe Slough at the confluence with the Sunnyvale Wastewater Treatment Plant. Fish sampling consisted of beach seine, minnow trap and fyke netting with various levels of effort to capture the requisite number and size of sentinel fishes. Therefore, much of the sampling efforts were not conducted in a manor conducive of making fish abundance or species assemblage comparisons amongst the sampling locations. In addition to the slough sampling, we sampled for fish in tidal muted ponds A8, A7, A5, A3N, A3W and A16 from spring 2014 through winter of 201
South Bay Salt Pond Restoration Project – Phase-1 (2014-2017) Steelhead Outmigration and Entrainment in the A8 Complex.
The South Bay Salt Pond Restoration Project, the largest wetland restoration project in the western United States, is conducting an adaptive management experiment to restore tidal flows to the tidally muted pond A8 complex. The A8 pond complex is a series of interconnected ponds (A8, A7, and A5) located at the interface of the Guadalupe River with Alviso Marsh in Lower South San Francisco Bay that has had a legacy of mercury contamination from cinnabar open-pit mining in the Guadalupe River watershed. As a result, restoration of salt pond habitats in the Alviso Marsh has taken an adaptive management approach whereby the A8 complex was constructed with operable tide gates to facilitate a stepped approach to opening the pond to tidal action. Fish populations, water and sediment were monitored for mercury contamination before and after opening the tide gates and data was used to inform further restoration actions in the A8 complex. However, Central Coast Steelhead Trout, a threatened species inhabit the streams that enter into the Alviso Marsh and the A8 complex, causing management concern for entrainment of outmigration smolts into the A8 complex. In this study, UC Davis conducted back-pack electrofishing in the streams that enter the Alviso Marsh during the late-fall winter of 2013 and 2014. The primary objective of the electrofishing was to collect Steelhead Trout juveniles prior to outmigration to tag with Passive Integrated Transponder (PIT) tags for detection of outmigration and potential entrainment into the A8 complex. In addition to the capture and tagging of Steelhead Trout, we collected data on water quality and catch of non-target fishes. To detect outmigration Steelhead Trout we installed a RFID stream antennae in the lower reaches of the Guadalupe River and to detect entrainment into the A8 complex we installed RFID antennas on the A8 water control structure. A total of 106 Steelhead Trout were captured during the two years of stream electrofishing, and 1
Pond Area Estimates: Nine Study Regions in Alaska for 3 time periods (1950s, 1978-1982, 1999-2001) using remotely sensed images
The data are ArcGIS shapefiles by USGS quadrangle within 9 study regions: Arctic Coastal Plain, Stevens Village area, Yukon Flats, Minto Flats, Denali Flats, Talkeetna, Innoko Flats, Tetlin Flats, and Copper River Basin. Each shapefile polygon represents the shoreline of a pond as visually interpreted from each georectified remotely sensed image. All images were rectified based on at least 25 control points from 1:63 360 USGS digital raster graphics topographic maps using a second-order polynomial with a RMS error of less than one satellite image pixel (30 meters). All closed-basin ponds greater than 0.2 hectares were visually delineated and manually traced as polygons using ArcGIS. Each pond polygon has an ID and Hectares field representing the pond ID and area in hectares for the time period of the remotely sensed image.
Cone Pond Watershed: Soil Profiles (Pedons), 1988-2023
Cone Pond Watershed: Soil Profiles (Pedons), 1988-2023 This dataset documents pedons (soil profiles) sampled at Cone Pond Watershed, Thornton, New Hampshire. Since the early 1980’s, Cone Pond, on the Pemigewasset District of the White Mountain National Forest, has been an active research satellite site to the nearby Hubbard Brook Experimental Forest. In 1988, intensive monitoring began as part of a comprehensive watershed scale ecosystem study. A weir was built on the main inlet stream, just above its mouth at Cone Pond, to monitor streamflow. Two rain gages were installed to monitor atmospheric deposition and multiple studies of major ecosystem components were initiated. Soil profiles documented in this dataset were sampled between 1988 and 2003. All descriptive profile and horizon data as well as chemical analyses of samples of genetic horizons are included in this dataset. Samples from 123 of these horizons have been accessioned into the Hubbard Brook physical sample archive; the archived mass of each is included in the horizon table. In addition to these pedons sampled in detail, a number of reconnaissance observations, made at a lower level of detail, and without sampling, were made in 2023 in order to validate a hydropedologic soil model created at Hubbard Brook. These data are included in a separate table. These data were gathered as part of the Hubbard Brook Ecosystem Study (HBES). The HBES is a collaborative effort at the Hubbard Brook Experimental Forest, which is operated and maintained by the USDA Forest Service, Northern Research Station.
PIE LTER chlorophyll concentrations in the surface waters and sediments of six high marsh ponds, Rowley, MA, during the summer of 2016.
We measured chlorophyll concentrations in the surface waters and sediments of six ponds in three regions of the PIE-LTER marshes during summer 2016. The goal was to assess whether pond microalgal community abundances varied predictably with pond dimensions (e.g., surface area, volume) or geographic attributes (e.g., elevation, distance from upland, marsh region). Samples were collected from several locations in each pond in order to capture spatial heterogeneity.
PIE LTER 15-minute surface water dissolved oxygen, temperature, and salinity of six high marsh ponds, Rowley, MA, during the summer of 2016.
We estimated the oxygen metabolism of six ponds in three regions of the PIE-LTER marshes during summer 2016. The goal was to assess whether pond metaoblism rates varied predictably with pond dimensions (e.g., surface area, volume) or geographic attributes (e.g., elevation, distance from upland, marsh region). Sensors recording dissolved oxygen (DO), temperature, and salinity were deployed at mid-depth and rotated between the six ponds through the June - August study period. Metaoblism rates were calcluated based on a free-water diel oxygen approach.
PIE LTER abundances of macroalgae and Ruppia maritima in six high marsh ponds, Rowley, MA, during the summer of 2016.
We characterized the abundance of macroalgae and submerged grass in six ponds in three regions of the PIE-LTER marshes during summer 2016. Macroalgal communiteis were dominated by Ulva while Ruppia maritima was the only submerged grass present. Our goal was to determine whether macrophyte abundances varied predictably with pond dimensions (e.g., surface area, volume) or geographic attributes (e.g., elevation, distance from upland, marsh region). Samples were collected from several locations in each pond in order to capture spatial heterogeneity.
Via Sacra Pond YSI Data from 2019-11-20 to 2019-12-04
<p>General Metadata for Via Sacra Pond YSI Data</p> <p> </p> <p>Files</p> <p>Specific metadata for each deployment can be found as text files with the file format of:</p> <pre><code>via_sacra_pond_YYYY-MM-DD_metadata.txt </code></pre> <p>Where YYYY-MM-DD is the date that the deployment ended.</p> <p> </p> <p>File Created</p> <ul> <li>2020-01-14 by KF</li> </ul> <p> </p> <p>File Modified</p> <p> </p> <p>Description</p> <p>These data are from a YSI EXO3 multiparameter sonde deployed at approximatly 0.4 m in Via Sacra Pond (37.223340 N, -78.473026 W) in approximately 1 m of water.</p> <p> </p> <p>Sonde Specifics</p> <p>The specific sensors and SNs deployed are on the metadata specific to each deployment but generally the sonde has:</p> <ul> <li>Temperature</li> <li>Conductivity</li> <li>ODO</li> <li>Total Algae</li> <li>Turbidity</li> <li>fDOM</li> </ul> <p> </p> <p>Measurement Parameters, units, and Variable Names</p> <ul> <li>date.time = the combined date and time of the measurement (YYYY-MM-DD HH:MM:SS)</li> <li>date = the sampling date reported by the YSI (M/D/YYYY)</li> <li>time = the sampling time reported by the YSI (HH:MM:SS)</li> <li>fract_sec = the sampling fractions of a second reported by the YSI</li> <li>site_name = the site name on the YSI deployment (left blank)</li> <li>chl_RFU = the chlorophyll concentration (RFU)</li> <li>chl_conc = the chlorophyll concentration (ug/L)</li> <li>cond = the conductivity (uS/cm)</li> <li>nLF_cond = the nLF conductivity (uS/cm)</li> <li>perc_ODO = the percent oxygen saturation</li> <li>perc_local_ODO = the percent local oxygen saturation</li> <li>ODO_conc = the dissolved oxygen concentration (mg/L)</li> <li>sal = the salinity (psu)</li> <li>sp_cond = the specific conductivity (uS/cm)</li> <li>BGA_PC_RFU = the Blue-green algae Phycocyanin concentration (RFU)</li> <li>BGA_PC_conc = the Blue-green algae Phycocyanin concentration (ug/L)</li> <li>TDS = the total dissolved solids (mg/L)</li> <li>temp = the temperature (dC)</li> <li>turb_FNU = the turbidity (FNU)</li> <li>TSS = total suspended solids</li> <li>battery = the battery voltage</li> <li>cable_pwr = the cable power</li> </ul>
Via Sacra Pond YSI Data from 2019-12-18 to 2020-01-09
<p>General Metadata for Via Sacra Pond YSI Data</p> <p> </p> <p>Files</p> <p>Specific metadata for each deployment can be found as text files with the file format of:</p> <pre><code>via_sacra_pond_YYYY-MM-DD_metadata.txt </code></pre> <p>Where YYYY-MM-DD is the date that the deployment ended.</p> <p> </p> <p>File Created</p> <ul> <li>2020-01-14 by KF</li> </ul> <p> </p> <p>File Modified</p> <p> </p> <p>Description</p> <p>These data are from a YSI EXO3 multiparameter sonde deployed at approximatly 0.4 m in Via Sacra Pond (37.223340 N, -78.473026 W) in approximately 1 m of water.</p> <p> </p> <p>Sonde Specifics</p> <p>The specific sensors and SNs deployed are on the metadata specific to each deployment but generally the sonde has:</p> <ul> <li>Temperature</li> <li>Conductivity</li> <li>ODO</li> <li>Total Algae</li> <li>Turbidity</li> <li>fDOM</li> </ul> <p> </p> <p>Measurement Parameters, units, and Variable Names</p> <ul> <li>date.time = the combined date and time of the measurement (YYYY-MM-DD HH:MM:SS)</li> <li>date = the sampling date reported by the YSI (M/D/YYYY)</li> <li>time = the sampling time reported by the YSI (HH:MM:SS)</li> <li>fract_sec = the sampling fractions of a second reported by the YSI</li> <li>site_name = the site name on the YSI deployment (left blank)</li> <li>chl_RFU = the chlorophyll concentration (RFU)</li> <li>chl_conc = the chlorophyll concentration (ug/L)</li> <li>cond = the conductivity (uS/cm)</li> <li>nLF_cond = the nLF conductivity (uS/cm)</li> <li>perc_ODO = the percent oxygen saturation</li> <li>perc_local_ODO = the percent local oxygen saturation</li> <li>ODO_conc = the dissolved oxygen concentration (mg/L)</li> <li>sal = the salinity (psu)</li> <li>sp_cond = the specific conductivity (uS/cm)</li> <li>BGA_PC_RFU = the Blue-green algae Phycocyanin concentration (RFU)</li> <li>BGA_PC_conc = the Blue-green algae Phycocyanin concentration (ug/L)</li> <li>TDS = the total dissolved solids (mg/L)</li> <li>temp = the temperature (dC)</li> <li>turb_FNU = the turbidity (FNU)</li> <li>TSS = total suspended solids</li> <li>battery = the battery voltage</li> <li>cable_pwr = the cable power</li> </ul>
Via Sacra Pond YSI Data from 2020-12-04 to 2020-12-18
<p>General Metadata for Via Sacra Pond YSI Data</p> <p> </p> <p>Files</p> <p>Specific metadata for each deployment can be found as text files with the file format of:</p> <pre><code>via_sacra_pond_YYYY-MM-DD_metadata.txt </code></pre> <p>Where YYYY-MM-DD is the date that the deployment ended.</p> <p> </p> <p>File Created</p> <ul> <li>2020-01-14 by KF</li> </ul> <p> </p> <p>File Modified</p> <p> </p> <p>Description</p> <p>These data are from a YSI EXO3 multiparameter sonde deployed at approximatly 0.4 m in Via Sacra Pond (37.223340 N, -78.473026 W) in approximately 1 m of water.</p> <p> </p> <p>Sonde Specifics</p> <p>The specific sensors and SNs deployed are on the metadata specific to each deployment but generally the sonde has:</p> <ul> <li>Temperature</li> <li>Conductivity</li> <li>ODO</li> <li>Total Algae</li> <li>Turbidity</li> <li>fDOM</li> </ul> <p> </p> <p>Measurement Parameters, units, and Variable Names</p> <ul> <li>date.time = the combined date and time of the measurement (YYYY-MM-DD HH:MM:SS)</li> <li>date = the sampling date reported by the YSI (M/D/YYYY)</li> <li>time = the sampling time reported by the YSI (HH:MM:SS)</li> <li>fract_sec = the sampling fractions of a second reported by the YSI</li> <li>site_name = the site name on the YSI deployment (left blank)</li> <li>chl_RFU = the chlorophyll concentration (RFU)</li> <li>chl_conc = the chlorophyll concentration (ug/L)</li> <li>cond = the conductivity (uS/cm)</li> <li>nLF_cond = the nLF conductivity (uS/cm)</li> <li>perc_ODO = the percent oxygen saturation</li> <li>perc_local_ODO = the percent local oxygen saturation</li> <li>ODO_conc = the dissolved oxygen concentration (mg/L)</li> <li>sal = the salinity (psu)</li> <li>sp_cond = the specific conductivity (uS/cm)</li> <li>BGA_PC_RFU = the Blue-green algae Phycocyanin concentration (RFU)</li> <li>BGA_PC_conc = the Blue-green algae Phycocyanin concentration (ug/L)</li> <li>TDS = the total dissolved solids (mg/L)</li> <li>temp = the temperature (dC)</li> <li>turb_FNU = the turbidity (FNU)</li> <li>TSS = total suspended solids</li> <li>battery = the battery voltage</li> <li>cable_pwr = the cable power</li> </ul>
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