http://lod.bco-dmo.org/id/dataset/891779 eng; USA utf8 dataset Highest level of data collection, from a common set of sensors or instrumentation, usually within the same research project Biological and Chemical Oceanography Data Management Office (BCO-DMO) Unavailable 508-289-2009 WHOI MS#36 Woods Hole MA 02543 USA info@bco-dmo.org http://www.bco-dmo.org Monday - Friday 8:00am - 5:00pm For questions regarding this resource, please contact BCO-DMO via the email address provided. pointOfContact 2023-03-13 ISO 19115-2 Geographic Information - Metadata - Part 2: Extensions for Imagery and Gridded Data ISO 19115-2:2009(E) Fish densities sampled by Dual Frequency Identification Sonar (DIDSON) within Artificial Seagrass Units (ASU) in Back Sound, NC from June to October 2018 2023-03-13 publication 2023-03-13 revision Marine Biological Laboratory/Woods Hole Oceanographic Institution Library (MBLWHOI DLA) 2023-03-28 publication https://doi.org/10.26008/1912/bco-dmo.891779.1 F. Joel Fodrie University of North Carolina at Chapel Hill principalInvestigator Lauren Yeager University of Texas - Marine Science Institute principalInvestigator James Morley University of North Carolina at Chapel Hill principalInvestigator Amy Yarnall University of North Carolina at Chapel Hill principalInvestigator Biological and Chemical Oceanography Data Management Office (BCO-DMO) Unavailable 508-289-2009 WHOI MS#36 Woods Hole MA 02543 USA info@bco-dmo.org http://www.bco-dmo.org Monday - Friday 8:00am - 5:00pm For questions regarding this resource, please contact BCO-DMO via the email address provided. publisher Cite this dataset as: Yarnall, A., Fodrie, F. J., Morley, J., Yeager, L. (2023) Fish densities sampled by Dual Frequency Identification Sonar (DIDSON) within Artificial Seagrass Units (ASU) in Back Sound, NC from June to October 2018. Biological and Chemical Oceanography Data Management Office (BCO-DMO). (Version 1) Version Date 2023-03-13 [if applicable, indicate subset used]. doi:10.26008/1912/bco-dmo.891779.1 [access date] Methods and Sampling: &lt;p&gt;This dataset represents fish densities (catch per unit effort; CPUE) sampled at three locations within each landscape on Oscar Shoal and an adjacent unnamed shoal in Back Sound, NC, USA (34°42′20&quot; N to 34°41′60&quot; N, 76°36′ 15&quot; W to 76°35′17&quot; W) during the summer of 2018. Benthopelagic fishes were sampled with Dual Frequency Identification Sonar (DIDSON). DIDSON allowed us to reliably detect fishes regardless of water visibility (compared to traditional video cameras) and diversify the size range of organisms we were able to sample. However, DIDSON did not generally allow for species identification.&lt;/p&gt; &lt;p&gt;DIDSON recordings (hereafter “samples”, n = 166), each 1 minute in length, were taken in each landscape's largest patch in July, September, and October, and in each matrix location (i.e., interpatch, near-patch) in July and September. The sampling field of view ranged from 2 meters to 6.5 meters from the DIDSON, and artificial seagrass unit (ASU) and mudflat habitats could be easily distinguished in samples. DIDSON samples were standardized by positioning the sample targets at a range of 4.5 meters in the center of the viewing field. The DIDSON was mounted to a kayak, held stationary by a person on the opposite side of the sampling field, and was operated at a consistent depth below the surface (approximately 10 centimeters) and oriented to include most of the water column and also the substrate.&lt;/p&gt; &lt;p&gt;&lt;strong&gt;Known Issues:&lt;/strong&gt;&lt;br /&gt; The study area and artificial landscapes were directly impacted by Hurricane Florence during 13-16 Sept 2018. Despite ASU re-enforcements made prior to Florence's landfall (i.e., additional lawn staples and cable ties), our landscapes experienced substantial disturbance akin to natural seagrasses in the vicinity, in many cases completely removing or burying ASUs which altered the landscape percent cover and fragmentation &lt;em&gt;per se&lt;/em&gt; parameters. Holding the original landscape 234 square meter footprint constant, post-Florence landscape percent cover and percolation probabilities were recalculated both including and excluding ASUs that were fully buried under sediment. DIDSON samples were taken both before and after Florence. Due to considerable landscape parameter alterations over this timeframe and potentially confounding disturbance influences, caution should be taken in examining post-Florence fish densities.&lt;/p&gt; Funding provided by NSF Division of Ocean Sciences (NSF OCE) Award Number: OCE-1635950 Award URL: https://www.nsf.gov/awardsearch/show-award?AWD_ID=1635950 completed F. Joel Fodrie University of North Carolina at Chapel Hill 252-726-6841 Institute of Marine Sciences & Department of Marine Sciences 3431 Arendell Street Morehead City NC 28557 USA jfodrie@unc.edu pointOfContact Lauren Yeager University of Texas - Marine Science Institute 750 Channel View Dr Port Aransas TX 78373 US laurenayeager@gmail.com pointOfContact James Morley University of North Carolina at Chapel Hill jwmorley@email.unc.edu pointOfContact Amy Yarnall University of North Carolina at Chapel Hill (601) 634-3772 Engineer Research Development Center, USACE 3909 Halls Ferry Rd. Vicksburg MS 39180 USA amyhyarnall@gmail.com pointOfContact asNeeded Dataset Version: 1 Unknown Site_ID Latitude Longitude Per_cov Frag MaxN Frames_sampled Frame FrameSample L_cm Time Date Month Class Reader Dual Frequency Identification Sonar (DIDSON 3000m) theme None, User defined Site_ID latitude longitude percent coverage site description image_analysis length time of day date month of year comments featureType BCO-DMO Standard Parameters Dual Frequency Identification Sonar (DIDSON 3000m) instrument BCO-DMO Standard Instruments otherRestrictions otherRestrictions Access Constraints: none. Use Constraints: Please follow guidelines at: http://www.bco-dmo.org/terms-use Distribution liability: Under no circumstances shall BCO-DMO be liable for any direct, incidental, special, consequential, indirect, or punitive damages that result from the use of, or the inability to use, the materials in this data submission. If you are dissatisfied with any materials in this data submission your sole and exclusive remedy is to discontinue use. Collaborative Research: Habitat fragmentation effects on fish diversity at landscape scales: experimental tests of multiple mechanisms https://osprey.bco-dmo.org/project/714026 Collaborative Research: Habitat fragmentation effects on fish diversity at landscape scales: experimental tests of multiple mechanisms <p>Amount and quality of habitat is thought to be of fundamental importance to maintaining coastal marine ecosystems. This research will use large-scale field experiments to help understand how and why fish populations respond to fragmentation of seagrass habitats. The question is complex because increased fragmentation in seagrass beds decreases the amount and also the configuration of the habitat (one patch splits into many, patches become further apart, the amount of edge increases, etc). Previous work by the investigators in natural seagrass meadows provided evidence that fragmentation interacts with amount of habitat to influence the community dynamics of fishes in coastal marine landscapes. Specifically, fragmentation had no effect when the habitat was large, but had a negative effect when habitat was smaller. In this study, the investigators will build artificial seagrass habitat to use in a series of manipulative field experiments at an ambitious scale. The results will provide new, more specific information about how coastal fish community dynamics are affected by changes in overall amount and fragmentation of seagrass habitat, in concert with factors such as disturbance, larval dispersal, and wave energy. The project will support two early-career investigators, inform habitat conservation strategies for coastal management, and provide training opportunities for graduate and undergraduate students. The investigators plan to target students from underrepresented groups for the research opportunities.</p> <p>Building on previous research in seagrass environments, this research will conduct a series of field experiments approach at novel, yet relevant scales, to test how habitat area and fragmentation affect fish diversity and productivity. Specifically, 15 by 15-m seagrass beds will be created using artificial seagrass units (ASUs) that control for within-patch-level (~1-10 m2) factors such as shoot density and length. The investigators will employ ASUs to manipulate total habitat area and the degree of fragmentation within seagrass beds in a temperate estuary in North Carolina. In year one, response of the fishes that colonize these landscapes will be measured as abundance, biomass, community structure, as well as taxonomic and functional diversity. Targeted ASU removals will then follow to determine species-specific responses to habitat disturbance. In year two, the landscape array and sampling regime will be doubled, and half of the landscapes will be seeded with post-larval fish of low dispersal ability to test whether pre- or post-recruitment processes drive landscape-scale patterns. In year three, the role of wave exposure (a natural driver of seagrass fragmentation) in mediating fish community response to landscape configuration will be tested by deploying ASU meadows across low and high energy environments.</p> Habitat Fragmentation largerWorkCitation project eng; USA biota oceans -76.603 -76.589 34.701 34.707 2018-06-29 2018-10-22 North Carolina 0 BCO-DMO catalogue of parameters from Fish densities sampled by Dual Frequency Identification Sonar (DIDSON) within Artificial Seagrass Units (ASU) in Back Sound, NC from June to October 2018 Biological and Chemical Oceanography Data Management Office (BCO-DMO) Unavailable 508-289-2009 WHOI MS#36 Woods Hole MA 02543 USA info@bco-dmo.org http://www.bco-dmo.org Monday - Friday 8:00am - 5:00pm For questions regarding this resource, please contact BCO-DMO via the email address provided. pointOfContact http://lod.bco-dmo.org/id/dataset-parameter/892028.rdf Name: Site_ID Units: unitless Description: <p>Artificial seagrass unit (ASU) landscape name (Percent cover value-Percolation probability value)</p> http://lod.bco-dmo.org/id/dataset-parameter/892029.rdf Name: Latitude Units: decimal degrees Description: <p>Latitude North (South is negative) of sampling site</p> http://lod.bco-dmo.org/id/dataset-parameter/892030.rdf Name: Longitude Units: decimal degrees Description: <p>Longitude East (West is negative) of sampling site</p> http://lod.bco-dmo.org/id/dataset-parameter/892031.rdf Name: Per_cov Units: percent (%) Description: <p>Percent cover of ASUs in 234 square meter landscape footprint (10, 22.5, 35, 47.5, 60)</p> http://lod.bco-dmo.org/id/dataset-parameter/892032.rdf Name: Frag Units: unitless Description: <p>ASU landscape fragmentation per se indexed by percolation probability (0.1, 0.225, 0.35, 0.475, 0.59)</p> http://lod.bco-dmo.org/id/dataset-parameter/892033.rdf Name: MaxN Units: unitless Description: <p>Indicates whether this frame has the max number of fish observed in the sample (y/n)</p> http://lod.bco-dmo.org/id/dataset-parameter/892034.rdf Name: Frames_sampled Units: unitless Description: <p>Sample size of frames per recording (10 for MaxN = n; 1 for Maxfish = y)</p> http://lod.bco-dmo.org/id/dataset-parameter/892035.rdf Name: Frame Units: unitless Description: <p>Frame number</p> http://lod.bco-dmo.org/id/dataset-parameter/892036.rdf Name: FrameSample Units: unitless Description: <p>Frame number assigned to fish length (within +/- 5 frames of &quot;Frame&quot; to find best view for measuring the fish length)</p> http://lod.bco-dmo.org/id/dataset-parameter/892037.rdf Name: L_cm Units: centimeters (cm) Description: <p>Total length of fish (L_cm = 0 indicates no fish were observed)</p> http://lod.bco-dmo.org/id/dataset-parameter/892038.rdf Name: Time Units: unitless Description: <p>Time of fish observation by DIDSON</p> http://lod.bco-dmo.org/id/dataset-parameter/892039.rdf Name: Date Units: unitless Description: <p>Date of fish observation DIDSON</p> http://lod.bco-dmo.org/id/dataset-parameter/892040.rdf Name: Month Units: unitless Description: <p>Month of sample round completion</p> http://lod.bco-dmo.org/id/dataset-parameter/892041.rdf Name: Class Units: unitless Description: <p>Focal sample location within ASU landscape (largest patch, near-patch, inter-patch)</p> http://lod.bco-dmo.org/id/dataset-parameter/892042.rdf Name: Reader Units: unitless Description: <p>Initials of data processor</p> GB/NERC/BODC > British Oceanographic Data Centre, Natural Environment Research Council, United Kingdom Biological and Chemical Oceanography Data Management Office (BCO-DMO) Unavailable 508-289-2009 WHOI MS#36 Woods Hole MA 02543 USA info@bco-dmo.org http://www.bco-dmo.org Monday - Friday 8:00am - 5:00pm For questions regarding this resource, please contact BCO-DMO via the email address provided. pointOfContact 482320 https://darchive.mblwhoilibrary.org/server/api/core/bitstreams/9e50d1c8-c9d3-46ee-ab2f-e5e5bf2711bd/content download https://doi.org/10.26008/1912/bco-dmo.891779.1 download onLine dataset &lt;p&gt;This dataset represents fish densities (catch per unit effort; CPUE) sampled at three locations within each landscape on Oscar Shoal and an adjacent unnamed shoal in Back Sound, NC, USA (34°42′20&quot; N to 34°41′60&quot; N, 76°36′ 15&quot; W to 76°35′17&quot; W) during the summer of 2018. Benthopelagic fishes were sampled with Dual Frequency Identification Sonar (DIDSON). DIDSON allowed us to reliably detect fishes regardless of water visibility (compared to traditional video cameras) and diversify the size range of organisms we were able to sample. However, DIDSON did not generally allow for species identification.&lt;/p&gt; &lt;p&gt;DIDSON recordings (hereafter “samples”, n = 166), each 1 minute in length, were taken in each landscape's largest patch in July, September, and October, and in each matrix location (i.e., interpatch, near-patch) in July and September. The sampling field of view ranged from 2 meters to 6.5 meters from the DIDSON, and artificial seagrass unit (ASU) and mudflat habitats could be easily distinguished in samples. DIDSON samples were standardized by positioning the sample targets at a range of 4.5 meters in the center of the viewing field. The DIDSON was mounted to a kayak, held stationary by a person on the opposite side of the sampling field, and was operated at a consistent depth below the surface (approximately 10 centimeters) and oriented to include most of the water column and also the substrate.&lt;/p&gt; &lt;p&gt;&lt;strong&gt;Known Issues:&lt;/strong&gt;&lt;br /&gt; The study area and artificial landscapes were directly impacted by Hurricane Florence during 13-16 Sept 2018. Despite ASU re-enforcements made prior to Florence's landfall (i.e., additional lawn staples and cable ties), our landscapes experienced substantial disturbance akin to natural seagrasses in the vicinity, in many cases completely removing or burying ASUs which altered the landscape percent cover and fragmentation &lt;em&gt;per se&lt;/em&gt; parameters. Holding the original landscape 234 square meter footprint constant, post-Florence landscape percent cover and percolation probabilities were recalculated both including and excluding ASUs that were fully buried under sediment. DIDSON samples were taken both before and after Florence. Due to considerable landscape parameter alterations over this timeframe and potentially confounding disturbance influences, caution should be taken in examining post-Florence fish densities.&lt;/p&gt; Specified by the Principal Investigator(s) &lt;p&gt;Using DIDSON software (V5.26.06), fishes were counted and measured on 10 randomly selected frames from each 1-minute sample. Random frame selection was constrained such that all frames were spaced a minimum of 25 frames apart to improve sub-sample independence. Fish counts for all 10 frames per sample were summed (i.e., number per sample) for further statistical analysis. This method does not differentiate between fishes that are maintaining position within the area versus transiting through, but represents a cumulative total of fish presences. In addition to the 10 frames per sample used to estimate fish presence, readers also selected and processed the frame with the maximum number of fish present (MaxN). All observe total fish lengths (in centimeters) were measured. If no fish were observed on a given frame, this is denoted by a length measurement of zero.&lt;/p&gt; &lt;p&gt;To account for potential reader bias in fish counts and length measurements (in centimeters), some samples were analyzed by two (n = 18) or three (n = 15) readers (reading identical sample frames). Readers counted statistically similar numbers of fishes per sample (paired two-sample t-test, P &amp;gt; 0.05), ruling out significant reader bias on fish counts.&lt;/p&gt; &lt;p&gt;Data output text files from DIDSON software were reformatted, reduced to relevant information, and output as a master Excel file using R statistical software (v3.6.2).&lt;/p&gt; &lt;p&gt;&lt;strong&gt;BCO-DMO Processing Description:&lt;/strong&gt;&lt;br /&gt; - Missing data identifier ‘NA’ replaced with blank (BCO-DMO's default missing data identifier)&lt;br /&gt; - Added &quot;Latitude&quot; and &quot;Longitude&quot; columns and rounded to three decimal places&lt;br /&gt; - Removed &quot;%&quot; symbol from data cells&lt;/p&gt; &lt;p&gt;&amp;nbsp;&lt;/p&gt; Specified by the Principal Investigator(s) asNeeded 7.x-1.1 Biological and Chemical Oceanography Data Management Office (BCO-DMO) Unavailable 508-289-2009 WHOI MS#36 Woods Hole MA 02543 USA info@bco-dmo.org http://www.bco-dmo.org Monday - Friday 8:00am - 5:00pm For questions regarding this resource, please contact BCO-DMO via the email address provided. pointOfContact Dual Frequency Identification Sonar (DIDSON 3000m) Dual Frequency Identification Sonar (DIDSON 3000m) PI Supplied Instrument Name: Dual Frequency Identification Sonar (DIDSON 3000m) Instrument Name: Dual Frequency Identification Sonar (DIDSON 3000m) Instrument Short Name:DIDSON 3000 Instrument Description: The Sound Metrics DIDSON 3000 (Dual-Frequency Identification Sonar) multibeam imaging sonar is an acoustic camera that provides almost video-quality images in turbid or dark water where optical systems are ineffective. DIDSON uses acoustic lenses to focus beams and form an acoustic image on the transducer array. DIDSON forms images differently than an optical camera. DIDSON sends out short acoustic pulses in 48 or 96 acoustic beams. These beams are very narrow in the horizontal dimension (0.3° to 0.8°) and wide in the vertical dimension (14°). The beams are adjacent to each other and together form a field-of-view 29° horizontal and 14° vertical. The Didson 3000 is rated to a depth of 3000 meters. It has both Detection and Identification modes. The max frame rate (window length dependent) is 4-21 frames per second.