O'Malley, Brian P. Schmitt, Joseph D. Holden, Jeremy P. Weidel, Brian C. 20210324 tabular digital data Reston, VA U.S. Geological Survey https://doi.org/10.5066/P92B534W These data contain morphometric measurements collected on the left side of Cisco (Coregonus artedi) collected from Lake Ontario in 2018. Measurements were obtained by two methods, first by direct measurements made on the thawed specimens using a hand caliper by one person, then using a digital image technique. The digital image measurements were completed by two different measurers to evaluate how reproducible measurements extracted from digital images were between the two measurers. The purpose of this dataset was to compare two different methods for morphometric measurements in Cisco (Coregonus artedi). Additionally, this dataset can be used to assess variability between two different measurers to assess bias when performing morphometric measurements extracted from the same digital image taken from the left side of a Cisco. 2018 2019 ground condition Complete None planned Lake Ontario -79.9805 -75.9814 44.3628 43.0605 ISO 19115 Topic Category biota imageryBaseMapsEarthCover USGS Thesaurus morphology (biological) fish meristics Producer defined Coregonus artedi morphometrics Lake herring Cisco USGS Metadata Identifier USGS:5f57d9ee82cea1f95a61a77d Common geographic areas Lake Ontario Great Lakes None Coregonus artedi Kingdom Animalia animals Subkingdom Bilateria Infrakingdom Deuterostomia Phylum Chordata chordates Subphylum Vertebrata vertebrates Infraphylum Gnathostomata Superclass Actinopterygii ray-finned fishes spiny rayed fishes Class Teleostei Superorder Protacanthopterygii Order Salmoniformes salmons Family Salmonidae salmonids trouts and salmons salmons trouts Subfamily Coregoninae Genus Coregonus whitefishes Species Coregonus artedi cisco lake herring TSN: 623384 No data access constraints No data use constraints Brian P O'Malley U.S. Geological Survey, MIDCONTINENT REGION Research Fishery Biologist mailing address

Lake St W and 3rd St

Oswego NY 13126 US 315-343-3951 bomalley@usgs.gov Ontario Ministry of Natural Resources and Forestry; Great Lakes Restoration Initiative Coordinated Science and Monitoring Initiative; Canada-Ontario Agreement on Great Lakes Water Quality and Ecosystem Health and Ontario’s Great Lakes Strategy Brian P. O'Malley Joseph D. Schmitt Jeremy P. Holden Brian C. Weidel 20201123 publication Journal of Fish and Wildlife Management vol. 12, issue 1 n/a U.S. Fish and Wildlife Service ppg. 208-215 https://doi.org/10.3996/JFWM-20-029 Fish identifications were made in the field upon collection by professional fish biologists from U.S Geological Survey and Ontario Ministry of Natural Resources and Forestry with several years of experience. Fish identifications were also verified in the laboratory after thawing along with the sample information. Hand caliper measurements were made using a digital caliper with 0.01 mm accuracy. We verified that length and other morphometric measurements are within expected ranges for this species reported in the literatures. Plots of morphometric variables as a function of fish length were used to assess potential errors in the dataset and detect any outliers. Data were checked for duplication none of which were found. Data set is considered complete for the information presented, as described in the abstract. Users are advised to read the rest of the metadata record carefully for additional details. Specimens in this dataset were all collected from Lake Ontario. No formal positional accuracy tests were conducted No formal positional accuracy tests were conducted Eshenroder, Randy L. Vescei, Paul Gorman, Owen T. Yule, Daniel L. Pratt, Thomas C. Mandrak, Nicholas E. Bunnell, David B. Muir, Andrew M. 2016 tabular digital data Ann Arbor, Michigan Great Lakes Fishery Commission Digital and/or Hardcopy 2016 publication date Ciscoes (Coregonus, Subgenus Leucichthys) of the Laurentian Great Lakes and Lake Nipigon Guide/Key used U.S. Geological Survey, Great Lakes Science Center 2019 dataset https://www.sciencebase.gov U.S. Geological Survey https://doi.org/10.5066/f75m63x0 Digital and/or Hardcopy 2018 2019 ground condition RVCAT Samples used in this study are part of the larger RVCAT database. Note that the samples used in this study are not included in the RVCAT data release at the time of this data publication. Because these were all relatively large Cisco, which are easier to confidently identify to species that smaller juvenile coregonines, we do not anticipate there being any errors in species assignment. Furthermore, the careful lab workup and cross reference with image allowed for double-checking that each specimen was a Cisco (Coregonus artedi), though we do recognize that coregonine morphology can be variable and Cisco are known to hybridize in Lake Ontario with Lake Whitefish (Coregonus clupeaformis). No attempt was made to confirm our assignments with genetics, though fin clip samples have been archived for genetics in ethanol at USGS Lake Ontario Biological Station. 2018 Identifications were made in the field upon collection by vessel crews of the USGS R/V Lake Whitefish and OMNRF R/V Ontario Explorer 2019 Cisco (N = 99) were collected from Lake Ontario. Upon collection, each fish was individually bagged and frozen, and later thawed in the laboratory for morphometric measurements and imaging. Fish collections were made using two gear types to capture a wide range of body sizes. Cisco were collected during the spawning period using gillnets in Chaumont Bay, NY during November-December 2018, and from midwater trawling (Holden et al. 2019) in the eastern basin of Lake Ontario during September 2018. Larger Cisco were more common in gillnet collections whereas smaller Cisco were obtained from midwater trawl samples. We measured twelve morphometrics using two different methods. We selected twelve morphometrics based on those commonly used in previous studies on Cisco morphs (e.g., Muir et al. 2013; Yule et al. 2013; Eshenroder et al. 2016; Piette‐Lauzière et al. 2019). After fish were thawed in the laboratory, the caudal, dorsal, and ventral fins of each fish were pinned, while paired fins were laid along the body. A photograph was captured on the left side of each fish for digital extraction of morphometric measurements using a single lens reflex camera, following recommendations of Muir et al. (2012) to minimize effects of distortion. Prior to capturing the photograph, we placed foam pads under the anterior and posterior ends of the body to help force the lateral view into a single horizontal plane. A ruler was included in each image for scale. Next, measurements were made directly on the specimens using a digital caliper (accurate to ± 0.01 mm) by a single measurer, except for total length and standard length which were measured to the nearest mm using a measuring board. We refer to these direct measurements as the ‘specimen-based’ dataset. For the second, ‘image-based’ morphometric dataset, we placed landmarks on each fish image to calculate distances between landmarks, consistent with the twelve morphometrics in the specimen-based dataset. Our goal in applying these landmarks was to use the same criteria in placement of the start and endpoints used in the specimen-based measurements. Some landmarks were placed at homologous structures (e.g., insertion of a fin ray), while other semilandmarks (i.e., those that do not represent a homologous point) were placed by predefined criteria, sometimes dependent on the location of homologous landmarks. For example, pelvic-anal fin distance was measured along the lateral line in the specimen-based dataset. To repeat this measurement from an image, we placed semilandmarks along the lateral line that were vertically in-line with the y-coordinates of the pelvic and anal fin landmarks. We used the digitzeImages function from the R Package StereoMorph (Olsen and Westneat, 2015) to place digital landmarks. A known distance along a ruler placed in each image was used to convert landmark coordinate units from pixels to millimeters. Distance measurements between digitized landmarks were calculated using the formula: d\ =\sqrt{{{(x}_1-x_2)}^2+{{(y}_1-y_2)}^2} where d is the linear distance calculated between the starting (x_1,y_1) and ending (x_2,y_2) landmark coordinates. All calculations were carried out in R v3.5.3 (R Core Team 2019) on scaled landmark coordinates. References: Eshenroder RL, Vecsei P, Mandrak NE, Yule DL, Gorman OT, Pratt TC, Bunnell DB, Muir AM. 2016. Ciscoes (Coregonus, subgenus Leucichthys) of the Laurentian Great Lakes and Lake Nipigon. Great Lakes Fishery Commission Miscellaneous Publication 2016-01. http://www.glfc.org/pubs/misc/Ciscoes_of_the_Laurentian_Great_Lakes_and_Lake_Nipigon.pdf (Accessed August 2020). Holden JP, Connerton MJ, Weidel BC. 2019. Hydroacoustic and midwater trawl assessment of pelagic planktivores 2018. In New York State Department of Environmental Conservation, editor. New York State Department of Environmental Conservation, 2018 Annual Report 2018 Bureau of Fisheries Lake Ontario Unit and St. Lawrence River Unit to the Great Lakes Fishery Commission’s Lake Ontario Committee. Albany, NY. https://www.dec.ny.gov/docs/fish_marine_pdf/lourpt18.pdf (Accessed August 2020). Muir AM, Vecsei P, Pratt TC, Krueger CC, Power M, Reist JD. 2013. Ontogenetic shifts in morphology and resource use of cisco Coregonus artedi. Journal of Fish Biology 82:600-617. Muir AM, Vecsei P, Krueger CC. 2012. A perspective on perspectives: methods to reduce variation in shape analysis of digital images. Transactions of the American Fisheries Society 141:1161-1170. Olsen AM, Westneat MW. 2015. StereoMorph: an R package for the collection of 3D landmarks and curves using a stereo camera set‐up. Methods in Ecology and Evolution 6:351-356. Piette‐Lauzière G, Bell AH, Ridgway MS, Turgeon J. 2019. Evolution and diversity of two cisco forms in an outlet of glacial Lake Algonquin. Ecology and Evolution 9:9654–9670. R Core Team. 2019. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/. Yule DL, Moore SA, Ebener MP, Claramunt RM, Pratt TC, Salawater LL, Connerton MJ. 2013. Morphometric variation among spawning cisco aggregations in the Laurentian Great Lakes: are historic forms still present. Advances in Limnology 64:119-132. 2019 CiscoMethodMSDataset_20200429.csv dataset containing morphometric data collected on Cisco (Coregonus artedi) O'Malley, Brian P. SpecimenID A character identifier for the individual fish unique ID that corresponds to the USGS Great Lakes Science Center RVCAT database. The SpecimenID is defined by YEAR, VESSEL, SERIAL, and SAMPLE, each separated by a hyphen, in RVCAT. For example, the fish with SpecimenID "2018-50-886-20" in the dataset, corresponds to the individual fish in RVCAT where YEAR=2018, VESSEL=50, SERIAL=886, and SAMPLE=20. Producer defined character combination of YEAR, VESSEL, SERIAL, SAMPLE in RVCAT ImageFileName A character identifier for the image file name of the fish image that was digitized Producer defined A character identifier for the image file name of the fish image that was digitized Lake A character identifier for the lake from which the specimens were collected from. All fish in this dataset were collected from Lake Ontario. Producer defined A character identifier for the lake from which the specimens were collected from. All fish in this dataset were collected from Lake Ontario. CollectionDate A date identifier for the calendar date that fish were collected from Lake Ontario. Date is in the format: MM/DD/YYYY. Producer defined A date identifier for the calendar date that fish were collected from Lake Ontario. Date is in the format: MM/DD/YYYY. CollectionSite A character identifier for the site name from where fish were collected in Lake Ontario. Producer defined A character identifier for the site name from where fish were collected in Lake Ontario. Collector A character identifier for representing the agency that collected the fish from Lake Ontario, where "USGS LOBS" represents specimens that were collected by the U.S. Geological Survey's Lake Ontario Biological Station research vessel, and "OMNRF" represents specimens that were collected by the Ontario of Ministry and Natural Resources and Forestry's research vessel. Producer defined A character identifier for representing the agency that collected the fish from Lake Ontario, where "USGS LOBS" represents specimens that were collected by the U.S. Geological Survey's Lake Ontario Biological Station research vessel, and "OMNRF" represents specimens that were collected by the Ontario of Ministry and Natural Resources and Forestry's research vessel. Method A character identifier for the method of morphometric data collection where "specimenBased" represents measurements made directly on the specimen by hand using a caliper, and "imageBased" refers to measurements obtained from a digital image. " Producer defined A character identifier for the method of morphometric data collection where "specimenBased" represents measurements made directly on the specimen by hand using a caliper, and "imageBased" refers to measurements obtained from a digital image. MeasurerInitials A character identifier for the initials of each measurer that correspond to two different authors of the dataset. Producer defined A character identifier for the initials of each measurer that correspond to two different authors of the dataset (BPO = Brian O'Malley; JDS = Joseph Schmitt). MorphometricAbbreviation A character identifier for the abbreviated name of each morphometric measurement that was obtained on each fish. Definitions of each morphometric abbreviation are as follows: BDD = Body depth; CPL = Caudal peduncle length; DOH = Dorsal fin height; HLL = Head length; MXL = Maxillary length; OOL = Orbital length; PCL = Pectoral fin length; PVL = Pelvic fin length; PAD = Pelvic-anal fin distance; POL = Preorbital length; STL = Standard length; TTL = Total length. Producer defined A character identifier for the abbreviated name of each morphometric measurement that was obtained on each fish. Definitions of each morphometric abbreviation are as follows: BDD = Body depth; CPL = Caudal peduncle length; DOH = Dorsal fin height; HLL = Head length; MXL = Maxillary length; OOL = Orbital length; PCL = Pectoral fin length; PVL = Pelvic fin length; PAD = Pelvic-anal fin distance; POL = Preorbital length; STL = Standard length; TTL = Total length. Value A numeric identifier for the morphometric measurement obtained in millimeters. Producer defined 7.32558394 464.5751713 millimeters GS ScienceBase U.S. Geological Survey mailing address

Denver Federal Center, Building 810, Mail Stop 302

Denver CO 80225 United States 1-888-275-8747 sciencebase@usgs.gov Unless otherwise stated, all data, metadata and related materials are considered to satisfy the quality standards relative to the purpose for which the data were collected. Although these data and associated metadata have been reviewed for accuracy and completeness and approved for release by the U.S. Geological Survey (USGS), no warranty expressed or implied is made regarding the display or utility of the data on any other system or for general or scientific purposes, nor shall the act of distribution constitute any such warranty. Digital Data https://doi.org/10.5066/P92B534W None 20250124 Great Lakes Science Center mailing and physical

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Ann Arbor MI 48105 US 734-994-3331 GS_ASK_GLSC@usgs.gov FGDC Biological Data Profile of the Content Standard for Digital Geospatial Metadata FGDC-STD-001.1-1999