Dataset: Fish measurements sampled by Dual Frequency Identification Sonar (DIDSON) within Artificial Seagrass Units (ASU) in Back Sound, NC from July to September 2018

Final no updates expectedDOI: 10.26008/1912/bco-dmo.891686.1Version 1 (2023-03-10)Dataset Type:Other Field Results

Principal Investigator: F. Joel Fodrie (University of North Carolina at Chapel Hill)

Co-Principal Investigator: Lauren Yeager (University of Texas - Marine Science Institute)

Scientist: James Morley (University of North Carolina at Chapel Hill)

Scientist, Contact: Amy Yarnall (University of North Carolina at Chapel Hill)

BCO-DMO Data Manager: Taylor Heyl (Woods Hole Oceanographic Institution)


Project: Collaborative Research: Habitat fragmentation effects on fish diversity at landscape scales: experimental tests of multiple mechanisms (Habitat Fragmentation)


Abstract

To parse the ecological effects of habitat area and patchiness on faunal community structure and dynamics of estuarine nekton, we employed artificial seagrass unit (ASU) landscapes at a scale relevant to habitat fidelity of common fish and macroinvertebrates in our temperate study system, Back Sound, NC. These ASU landscapes were designed along orthogonal axes of artificial seagrass area (i.e., percent cover of each landscape = 10-60 percent) and fragmentation per se (i.e., percolation probabili...

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This dataset represents fish measurements sampled at three locations within each landscape on Oscar Shoal and an adjacent unnamed shoal in Back Sound, NC, USA (34°42′20" N to 34°41′60" N, 76°36′ 15" W to 76°35′17" 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.

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.

Known Issues:
October fish lengths were excluded from this dataset, as we were interested in comparing z-scores across all three landscape locations (i.e., largest patch, near-patch, and inter-patch). DIDSON samples were only taken in the largest patch during October. 

 


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Related Publications

Results

Yarnall, A. H., Yeager, L. A., Lopazanski, C., Poray, A. K., Morley, J. M., Hurlbert, A., and Fodrie, F.J. Habitat area more consistently affects seagrass faunal communities than fragmentation per se.
Software

R Core Team (2019). R: A language and environment for statistical computing. R v3.6.1. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/