DOI: 10.5061/dryad.37pvmcvvf
title: Gearing up: Methods for quantifying gear density for fixed-gear commercial fisheries in the U.S. Atlantic

description: Fixed-gear commercial fisheries are unique due to their occupancy nature,
 claiming areas of the ocean for discrete periods. As space conflicts arise
 from competing ocean uses, there is an increased need to understand and
 categorize fixed-gear fisheries to incorporate into marine spatial
 planning (MSP) efforts. We used fishery-dependent data and input from
 stakeholders to discern fleet dynamics of all gillnet and trap/pot
 fisheries in U.S. waters of the Northwest Atlantic Ocean. A Fixed-Gear
 Fishery Layer (FGFL) was developed combining fishery subgroups that were
 categorized around gear type, gear configuration, and species landed.
 Fishing effort from each subgroup was spatially allocated onto a 1 sq nm
 (1.9 sq km) grid using methods that relied on the level of detail
 available from trip reporting and monitoring, each with differing degrees
 of spatial resolution. This stepwise process allowed trips reported with
 minimal spatial detail to be included while not compromising trips where
 greater spatial precision existed. We demonstrate how the FGFL has been
 used for two MSP projects focused on protected species conservation and
 wind energy development.
description: Fixed-gear fisheries existing in the Northwest Atlantic from
 Maine to Florida were summarized and allocated spatiotemporally based on
 the level of spatial precision in trip reports and vessel monitoring data.
 While the data used in the manuscript is not publicly available due to
 confidentiality restrictions, we provide simulated example fisheries trip
 reports (vtr_data_example.Rdata) and vessel monitoring system data
 (vms_data_example.Rdata) to demonstrate the methods described in the
 manuscript. These methods for allocating this example fixed-gear fisheries
 data are available and carried out in R and may be adapted to other areas
 and data worldwide. A central part of the methods utilizes a gridded data
 frame (MapRef.Rdata) that summarizes spatial variables within each grid
 cell and acts as a reference to fisheries data in the allocation process.
 This file is specific to the U.S. Atlantic waters, but similar grids could
 be generated for a given study area. Additional data files include
 shapefiles and other spatial and supporting data used in the methods and
 described in the R code and manuscript. The BuildFGFLMethods.R file is the
 main code used to perform the analysis.
description: # Gearing up: Methods for quantifying gear density for fixed-gear
 commercial fisheries in the U.S. Atlantic
 [https://doi.org/10.5061/dryad.37pvmcvvf](https://doi.org/10.5061/dryad.37pvmcvvf) ## Description of the data and file structure These files consist primarily of simulated fishery dependent data (actual vessel trip report (VTR) and vessel monitoring system (VMS) data could not be shared due to confidentiality restrictions) and R code. The intent of providing this code and data is to demonstrate our methods for allocating fishing gear densities spatially and temporally using fisheries dependent data sources. The user would likely take the data structure and code functions and adapt it to their own location specific details and alter it to adapt their data. The main fishery dependent data provided here are example fisheries VTR (vtr_data_example.Rdata) and VMS data (vms_data_example.Rdata). Our methods are carried out in R with a main code file (BuildFGFLMethods.R) which sources an additional file (InputDevFun.R) that contains functions for allocating fishing gear by four different methods - VMS locations, reported VTR coordinates, depth, and statistical reporting area. Additional data files include a fisheries management statistical reporting area shapefile (StatAreas) and a MapRef grid used as a spatial reference for relating all of the fisheries and management details along with basic spatial details specific to our work in the Northwest Atlantic region (e.g. depth, distance from shore). The StatAreas shapefile is publicly available at [https://www.northeastoceandata.org/data-download/?#CommercialFishing](https://www.northeastoceandata.org/data-download/?#CommercialFishing) and the depth within our MapRef grid was obtained by overlaying locations on a U.S. Coastal Relief Model that is also publicly available at [https://www.ncei.noaa.gov/products/coastal-relief-model](https://www.ncei.noaa.gov/products/coastal-relief-model). ### Files and variables #### File: vtr\_data\_example.Rdata **Description:** R data.frame containing simulated vessel trip report data. ##### Variables * Fishery: uses singular example fishery (ExampleFGFishery) but could identify different fleets or fishery types * VesselKey: a unique identifier for classifying certain vessel or fleet types to group similar sized vessels and fishing configurations * AreaKey: identifies the Greater Atlantic Statistical Reporting Area where the trip occurred * Year: numeric year * Month: numerical month of the year * Depth: numerical water depth (meters) * DistanceFromShore: numerical distance in nautical miles from coastline * GearFished: numerical value for total number of gear units fished (e.g. traps, nets) * GearPerString: average number of gear units per string/trawl * EndlinesPerString: number of endlines used in a string/trawl * GearHeight: numerical height (meters) of gear unit (e.g. net height) * GearLength: numberical length (meters) of gear unit (e.g. net length) * Soak: numerical duration that gear remains in the water (hours) * ReportId: unique identifier of the trip report * HullNum: unique identifier of a given vessel * Latitude: decimal degree latitude coordinate * Longitude: decimal degree longitude coordinate #### File: vms\_data\_example.RData **Description:** R data.frame containing simulated vessel monitoring system pings. Normally pings are recorded on a minute or hourly rate, but data has was pre-processed to determine fishing status and ping date/time was converted to month and year. ##### Variables * Fishery: uses singular example fishery (ExampleVMSFishery) but could identify different fleets or fishery types * Year: numeric year * Month: numerical month of the year * Status: indicator of vessel status (Fishing or Transitting) * Rate: a numerical ping rate that can be used to determine effort (elapsed minutes between pings) * Latitude: decimal degree latitude coordinate * Longitude: decimal degree longitude coordinate #### File: MapRef.Rdata **Description:** R data.frame of grid cells with unique identifiers at high and low resolution and various spatial attributes relating to their location ##### Variables * Index_HR: grid cell identifier corresponding to the high resolution (1 square nautical mile) grid * Index_LR: grid cell identifier corresponding to the low resolution (10 square nautical miles) grid * Region: region designation within the MapRef domain (GOM_GBK = Gulf of Maine and Georges Bank, MAB = Mid-Atlantic Bight, SE = Southeast, SNE = Southern New England) * State: two digit character abbreviation for U.S. state designation * StatArea: identifies the numeric Greater Atlantic Statistical Reporting Area where cell resides * LMA: identifies the Lobster Management Area where cell resides * StateFed: identifies whether cell is in state or federal waters * Distance: numerical distance from coastline * Depth: numeric water depth in meters * Fathoms: numeric water depth in fathoms * AreaKey: combines column StateFed and StatArea * Longitude: decimal degree longitude coordinate * Latitude: decimal degree latitude coordinate #### File: MapRefCellStatus.Rdata **Description:**  R data.frame containing Availability status of each monthly MapRef grid cell. ##### Variables * Index_HR: grid cell identifier corresponding to the high resolution (1 square nautical mile) in the MapRef grid * Month: numerical month of the year * Available: numeric value between 0 (cell is unavailable) and 1 (available the entire month) #### Files: StatAreas.dbf, StatAreas.prj, StatAreas.shp, StatAreas.shx **Description:** this group of files combines to form a shapefile of Greater Atlantic Region Statistical Reporting Areas. Individual files make up the feature attributes (.dbf), coordinate system (.prj), feature geometry (.shp), and index of feature geometry (.shx). These files are read in together with one line of R code that references the root name (StatAreas) and provide spatial boundaries for allocation of fishing gear when more precise coordinates are not reported. #### File: JulianDays.csv **Description:** spreadsheet associating Julian days of the year to the associated month and day. ##### Variables * Day: numerical day of the month * Month: numerical month of the year * Julian: sequential day count from the beginning of the year ## Code/software RStudio version 2022.07.1 or later is used to run the R code (provided) and process data. R version 4.2.1 or later is required as well as packages:  dplyr (dplyr_1.1.2 or later) raster (raster_3.6-23 or later) sp (sp_2.0-0 or later) sf (sf_1.0-14 or later) ggplot2 (ggplot2_3.4.2 or later) magrittr (magrittr_2.0.3 or later) lubridate (lubridate_1.9.2 or later) ## Access information Due to data confidentiality restrictions, the data used in this manuscript are not publicly available. The data provided here are simulated example data.