flowcam_particle English utf8 dataset McMurdo Dry Valleys LTER Information Manager im@mcmlter.org pointOfContact 2024-03-05 ISO 19115-2 Geographic Information - North American Profile Metadata - Data with Biological Extensions ISO 19115-2:2009(E) Microplankton counts from discrete water column samples using flow imaging microscopy (FlowCam) from Lakes Fryxell and Hoare, McMurdo Dry Valleys, Antarctica (2007-2011) 2024-03-05 publication Joshua Darling University of Colorado Boulder http://www.colorado.edu/ joshua.darling@colorado.edu pointOfContact Diane McKnight University of Colorado Boulder http://www.colorado.edu/ diane.mcknight@colorado.edu pointOfContact documentDigital This data package consists of microplankton counts from discrete water column samples collected at various depths in Lake Fryxell and Lake Hoare in the McMurdo Dry Valleys region of Antarctica. Samples were collected and preserved during the austral summer-autumn transition in 2007-2008 and in addition to routine McMurdo Dry Valley Long Term Ecological Research (LTER) core limnological sampling in November and December of 2008, 2010, and 2011. Data were imaged using flow cytometry (FlowCam VS-IV) and classified with statistical image-based software (Visual Spreadsheet, v4.17.14). These data include haptorian ciliates, filamentous cyanobacteria, and coccoidal algae particle counts per milliliter that were automatically classified from user-built libraries and statistical filters based on the morphological characterizations of the plankton. Name: Katherina Hell Role: associated researcher Name: Sarah N. Power Role: associated researcher Name: Ryan Hoak Role: associated researcher Name: John C. Priscu Role: associated researcher Name: Renée F. Brown Role: data manager completed McMurdo Dry Valleys LTER Information Manager im@mcmlter.org pointOfContact population dynamics theme LTER Core Areas English The Lake Fryxell basin is formed by a moraine depression in a wider portion of the Taylor Valley. It has a number of moraine islands and shallower areas, as well as several relatively well developed deltas. The lake is fed by at least 10 meltwater streams with a total drainage catchment of 230 km2. The lake is dammed to the southwest by the Canada Glacier and is topographically closed. It is perennially ice covered; during summer months, an ice-free moat generally forms around much of the lake margin. Lake levels have risen ~2 m between 1971 and 1996. There are no surface outflows; the only known water loss is through ice ablation (evaporation, sublimation and physical scouring). Valley: Taylor Distance to Sea : 9 Maximum Length (km): 5.8 Maximum Width (km): 2.1 Maximum Depth (m): 20 Surface Area (km^2): 7.08 Ice Thickness Average Surface (m): 3.3 - 4.5 Volume (m^3 * 10^6): 25.2 163.259582519531 163.048782348633 -77.622711181641 -77.597076416016 Lake Hoare occupies a narrower portion of the Taylor Valley, dammed by the Canada Glacier. It would drain almost completely without this dam. There are a number of islands which may be related to an old terminal of Canada Glacier. The lake is fed primarily from direct runoff from the glacier, as well as meltwater streams. (Lake level rose ~1.5 m between 1972 and 1996). There are no surface outflows; the only known water loss is through ice ablation (evaporation, sublimation and physical scouring). Valley: Taylor Distance to Sea : 15 Maximum Length (km): 4.2 Maximum Width (km): 1 Maximum Depth (m): 34 Surface Area (km^2): 1.94 Ice Thickness Average Surface (m): 3.1 - 5.5 Volume (m^3 * 10^6): 17.5 162.935836791992 162.784423828125 -77.639259338379 -77.623085021973 ground condition 2007-11-11 2011-12-08 Funding for this work was provided by several awards from the National Science Foundation for Long Term Ecological Research, most recently #OPP-2224760. Additional NSF funding for this work was provided to John Priscu under awards #OPP-0631494 and #MCB-0237335. https://mcm.lternet.edu/sites/default/files/data/mcmlter-limno-flowcam_particle-20240305.csv flowcam_particle eng; US McMurdo Dry Valleys LTER flowcam_particle Number of Header Lines : 1 Number of Footer Lines : 0 Orientation : Column Quote Character : "Field Delimiter : , false dataset_code Internal dataset code. limno_run Internal code for core limnological sampling location, date, and run number. lake_name Name of the lake sampled. date_sampled Date sample was collected. Date Time Format: MM/DD/YY h:mm depth_m Depth from surface where the sample was collected in the water column. taxon_class Classified taxon of the sample (see methods for further details). size_class Classified size class of the sample, where relevant (see methods for further details). cell_count Particles counted per millilter. filename Filename of the FlowCam .lst file containing the associated image data. DBF https://mcm.lternet.edu/sites/default/files/data/mcmlter-limno-flowcam_particle-20240305.csv dataset Samples were collected and preserved during the austral summer-autumn transition in 2007-2008 and in addition to routine McMurdo Dry Valley Long Term Ecological Research (LTER) core limnological sampling in November and December of 2008, 2010, and 2011. Samples preserved in 1% Lugol’s solution and at 5 °C were homogenized on a shaker table (150 RPM for 5 mins) before subsampling 150 mL and settling for 24 hrs. The supernatant was then aspirated off to concentrate the sample by 5-fold. 1-5 mL of homogenized subsample was imaged on FlowCam model VS-IV with a 10X lens and a 100 µl flow cell. Images were captured using AutoImage Mode at 18-20 frames sec-1 at a flow rate ranging 0.15-0.20 mL min-1. The fluid volume that was imaged ranged from 5-20%. Files containing the imaged plankton from each sample were then used to sort and build statistical filters based on particle morphologies. The morphotypes of the imaged plankton were sorted and classified using the Visual Spreadsheet Software (version 4.17.14). From a select number of samples that covered a range of times and depths throughout the record, images of like-morphotypes, such as a specific taxon or class of phytoplankton, were manually grouped into taxon- and morph-based libraries. For a total of 27 libraries that covered the range of morphotypes found in the plankton, we built statistical filters based on the specific geometries (e.g., length, width, aspect ratio) of the given particles in each library. The statistical filters were then built into a classification template of seven classes based on broad morphologic characterizations of the plankton. This classification template, based on statistical filters generated by particle attributes, was then applied to all the samples of interest to automatically sort and classify the image-based data. We chose to assign taxonomic identifiers to only the classes in the classification template with high enough image resolutions for sufficient identification. This condition was met only for the haptorian ciliates of the genera Askenasia and Monodinium because these taxa are known to occur in these lakes and likely not to be confused with other protists. Whereas we assigned generic morphologic-based names to morphologically similar groups with overlapping attributes (e.g. round coccoidal or filamentous) that did not classify well at the FlowCam resolution used (i.e. 10x magnification). Moreover, taxonomic delineation between small bacteria and chlorophytes was unachievable with this method.  To overcome this challenge, we classified small coccoidal algae consisting of mostly small chlorophytes, cryptophytes, chrysophytes and some small ciliates as little green round things (LGRT) of small (<5 µm), medium (5-15 µm) and large (>15 µm) size classes based on their cell diameters. Libraries of filamentous cyanobacteria (mostly comprised of Oscillatoria sp. and Phormidium sp.) were classified as either short (<25 µm) medium (25-75 µm) or long (>75 µm) filaments based on lengths. A separate class with filters based on detritus, sediment, and air-bubbles was used to control for unwanted image data. Using our classification template, we were able to automatically compute plankton density (cells mL-1) and biovolume for each of the seven classes. Metadata Access Constraints: none Metadata Use Constraints: none annually McMurdo Dry Valleys LTER http://mcmlter.org/ pointOfContact