﻿Cetacean and sea turtle spatial density model outputs from visual observations
using line-transect survey methods aboard NOAA vessel and aircraft platforms
in the Gulf of Mexico from 2003-06-12 to 2019-07-31

Green turtle (Chelonia mydas) model version 2.2 (2022-10-05)

NOAA/NMFS Southeast Fisheries Science Center


Abstract
--------

The goal of this research was to develop Gulf-wide cetacean and sea turtle
spatial density models (SDMs) based on line-transect surveys conducted in the
U.S. waters of the Gulf of Mexico. Surveys used to develop the SDMs for
species occupying continental shelf and oceanic waters of the Gulf of Mexico
were conducted during the Gulf of Mexico Marine Assessment Program for
Protected Species (GoMMAPPS) project and comparable-prior-year surveys.
Aerial survey data from seasonal surveys conducted during 2011/2012 and
2017/2018 (GoMMAPPS Surveys) were used to develop SDMs for cetacean and sea
turtle species over the continental shelf. Data collected from vessel
surveys, including the two-team surveys conducted during summer 2017, winter
2018, and summer/fall 2018 (GoMMAPPS Surveys) and 2003, 2004, and 2009
(that included only one survey team), were used to develop SDMs for cetaceans
in oceanic waters. In addition, for Rice's whales, surveys conducted in 2018
and 2019 were also used in developing the SDMs specific for this species. 

Habitat-based SDMs were developed using a generalized additive modeling
(GAM) framework to determine the relationship between cetacean and sea turtle
abundance and environmental variables. Samples for modeling were created by
summarizing survey effort and environmental variables with a hexagon grid
developed by the Environmental Protection Agency expanded to fit the entire
Gulf of Mexico. The grid was created in a Lambert azimuthal equal area
projection and the area of each hexagon is 40 km2. For all hexagons that
contained survey effort segments, cetacean and sea turtle density was
calculated using total number of animals observed, segment effort length and
average sighting condition covariates in the hexagon, and the parameters
estimated in distance sampling abundance models. A total of 19 SDMs were
developed for individual or groups of species. For each modeled taxon,
predictions were made for the period 2015-2019 on the hexagon grid,
summarized into mean monthly densities for the 5-year period, and then
resampled into traditional raster grids. Models were extrapolated beyond the
U.S. waters of the Gulf of Mexico to provide insight into potential high
density areas throughout the Gulf. However, extrapolations of this type
should be interpreted with caution. 

This file contains the summarized predictions for green turtle as raster grids.
The hexagon predictions are available as shapefiles
at https://doi.org/10.25921/efv4-9z56.


Contents of this zip file
-------------------------

Reports: 20220803_Volume1_GoMMAPPS_final report.pdf and 220220803_Volume3_AppendixD_ST_SpatialDensityModels 
Reports from SEFSC to the BOEM documenting the modeling methodology and results for the 2020 model update cycle.

Rasters/

    *_MMM_density_v2.img - Rasters giving the estimated mean density for month
      (represented in file name by abbreviated month name (MMM)), expressed as 
      the number of individual animals per 100 square km.To convert from individuals 
      per 100 square km to the more traditional unit of density, individuals per 1 
      square km, divide the cell values by 100. Note that several taxa were modeled 
      with only static covariates and therefore will have the same predictions for 
      each month.

    *_MMM_cv_mask_v2.img - Rasters giving the estimated coefficient of variation of
      the density estimates for month (represented in file name by abbreviated 
      month name (MMM)). These values are unitless and were
      computed as standard error divided by density.

ArcGIS_Symbology/

    *_density_v2_nper100km2.lyr - ArcGIS "layer" files for symbolizing the
      density rasters using a Classified symbology that has logarithmic
      breaks suitable for showing variability in both high and low density
      areas. To use these, load the raster into ArcGIS and import the
      symbology from the file.

    *_cv.lyr - ArcGIS "layer" file for symbolizing CV using a classified
      symbology that ranges from 0 to >=1.


Citation
--------

When referencing our methodology or results generally, please cite our project
report:

Rappucci G, Garrison LP, Soldevilla M, Ortega-Ortiz J, Reid J, Aichinger-Dias L, Mullin K, Litz J. 2023. 
Gulf of Mexico Marine Assessment Program for Protected Species (GoMMAPPS): marine mammals. 
Volume 1: report. New Orleans (LA): US Department of the Interior, Bureau of Ocean Energy Management. 104 p. 
Obligation No.: M17PG00013. Report No.: OCS Study BOEM 2023-042.


Questions
---------

If you have any questions about this model or its files, please contact Lance
Garrison(lance.garrison@noaa.gov).


Model Version History
---------------------

Version 2.2 (2022-10-05):
  	First model for this species, developed as part of the Gulf of Mexico
        Marine Assessment Program for Protected Species (GoMMAPPS) and
        documented by Rappucci et al. (2023) and Garrison et al. (2023b). This model was
        incorporated into the U.S. Navy Phase IV Marine Species Density
        Database (NMSDD).


Copyright and License
---------------------

The files that accompany this document were developed by the National Oceanic
and Atmospheric Administration and are therefore a work of the United States
government that is in the public domain. As such this work may be freely
distributed and copied however, it is requested that in any subsequent uses
of this work, NOAA be given appropriate acknowledgement.