Contributors | Affiliation | Role |
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Fodrie, F. Joel | University of North Carolina at Chapel Hill (UNC-Chapel Hill-IMS) | Principal Investigator |
Yeager, Lauren | University of Texas - Marine Science Institute (UTMSI) | Co-Principal Investigator |
Lopazanski, Cori | University of North Carolina at Chapel Hill (UNC-Chapel Hill-IMS) | Scientist |
Poray, Abigail K. | University of North Carolina at Chapel Hill (UNC-Chapel Hill-IMS) | Scientist |
Yarnall, Amy | University of North Carolina at Chapel Hill (UNC-Chapel Hill-IMS) | Scientist, Contact |
Heyl, Taylor | Woods Hole Oceanographic Institution (WHOI BCO-DMO) | BCO-DMO Data Manager |
From June to October 2018, epibenthic faunae (primarily juvenile) were sampled 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) with baited (approximately 8 pieces of dry dog food, Able et al., 2015) Gee-style minnow traps (41-centimeters long, 22-centimeters wide, 0.3-centimeter galvanized mesh-wire cylinders, with 4-centimeter diameter funneled openings). One trap was deployed within the largest patch of each landscape on nine occasions and at each of two of the matrix locations on four occasions. Each minnow trap deployment lasted 24 hours, at which time all faunae were enumerated, identified to the lowest taxonomical level possible, and released.
Known Issues:
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 per se 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. Trap 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 faunal densities.
All data were entered electronically into an Excel spreadsheet.
BCO-DMO Processing Description:
- Adjusted field/parameter names to comply with BCO-DMO naming conventions
- Missing data identifier ‘NA’ replaced with blank (BCO-DMO's default missing data identifier)
- Converted dates to format (YYYY-MM-DD)
- Added "Latitude" and "Longitude" columns and rounded to three decimal places
File |
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asufrag_trapfaunalcpue.csv (Comma Separated Values (.csv), 109.88 KB) MD5:1612ebad8f96834b47df54d20c31f334 Primary data file for dataset 891859. |
Parameter | Description | Units |
Site_ID | Artificial seagrass unit (ASU) landscape name (Percent cover value-Percolation probability value) | unitless |
Latitude | Latitude North (South is negative) of sampling site | decimal degrees |
Longitude | Longitude East (West is negative) of sampling site | decimal degrees |
Per_cov | Percent cover of ASUs in a 234 square meter landscape footprint (10, 22.5, 35, 47.5, 60) | percent (%) |
Frag | ASU landscape fragmentation per se indexed by percolation probability (0.1, 0.225, 0.35, 0.475, 0.59) | unitless |
Date_In | Date of minnow trap deployment | unitless |
Time_In | Time of minnow trap deployment in format hh:mm (24 hour) | unitless |
Date_Out | Date of minnow trap retrieval | unitless |
Time_Out | Time of minnow trap retrieval in format hh:mm (24 hour) | unitless |
H_tide | Time of high tide proximate to minnow trap deployment in format hh:mm (24 hour) | unitless |
L_tide | Time of low tide proximate to minnow trap deployment in format hh:mm (24 hour) | unitless |
WaterTemp_C | Surface water temperature at time of minnow trap deployment | degrees C |
Sal_PSU | Surface salinity at time of minnow trap deployment | PSU |
Trap_class | Location type of minnow trap deployment within ASU landscape (largest patch, near-patch, inter-patch) | unitless |
Cell_coord | Cell coordinates designate a grid position within the ASU landscape. Each landscape was designed as a grid of 15 x 15 cells, each of which may or may not be occupied by an ASU. Landscape cell coordinates are identified by C (column; out of 15) number and R (row; out of 15) number. | unitless |
Cell_class | Habitat type of cell within ASU landscape (ASU = artificial seagrass unit; MTRX = mudflat matrix) | unitless |
Sp_name | Common name of fauna species | unitless |
Sci_name | Scientific name of fauna species | unitless |
Length | Total length of fauna | millimeters (mm) |
Dataset-specific Instrument Name | ExTech 39240 |
Generic Instrument Name | digital thermometer |
Generic Instrument Description | An instrument that measures temperature digitally. |
Dataset-specific Instrument Name | |
Generic Instrument Name | minnow trap |
Generic Instrument Description | shore fishing gear |
Dataset-specific Instrument Name | VeeGee STX-3 |
Generic Instrument Name | Refractometer |
Generic Instrument Description | A refractometer is a laboratory or field device for the measurement of an index of refraction (refractometry). The index of refraction is calculated from Snell's law and can be calculated from the composition of the material using the Gladstone-Dale relation.
In optics the refractive index (or index of refraction) n of a substance (optical medium) is a dimensionless number that describes how light, or any other radiation, propagates through that medium. |
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.
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.
Funding Source | Award |
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NSF Division of Ocean Sciences (NSF OCE) |