Driggers et al.: Distribution of Squatinidae in waters of the western North Atlantic Ocean 
339 
Figure 1 
Locations of 104,957 trawls conducted during 7 fishery-independent surveys in the west¬ 
ern North Atlantic Ocean between 1950 and 2016. Black dots represent a single sampling 
station, and many dots overlap because of high sampling density, most notably in the 
northern and western parts of the sampling area. 
ural Resources and NMFS, Marine Resources Monitor¬ 
ing, Assessment, and Prediction (MARMAP) Survey 
(1973-1980); and 4) the Southeast Area Monitoring 
and Assessment Program-South Atlantic (SEAMAP- 
SA) Survey (1989-2015); and 5) NMFS, Mississippi 
Laboratories historical and exploratory trawl surveys 
(MSLABS) (1950-1997). Data collected from the GOM 
included the 1) MSLABS surveys, 2) the SEAMAP- 
GOM Survey (1982-2014), and the 3) NMFS, South¬ 
east Fisheries Science Center, Small Pelagics/Acoustics 
Trawl Survey (2002-2014) (Table 1). 
The position of each trawl and the locations where 
angels sharks were captured were plotted to determine 
the distribution of squatinids within the surveyed area. 
Median depth and depth distributions of all trawls con¬ 
ducted and locations where angel sharks were captured 
were compared for both regions by using Mann-Whit- 
ney-Wilcoxon (W) and Kolmogorov-Smirnov (K-S) 
tests, respectively. Results of the K-S test were used 
in conjunction with histograms to determine whether 
angel sharks were uniformly distributed throughout 
sampled depths. Additionally, bottom temperature and 
salinity (measured according to the practical salinity 
scale) information were available for a subset of the 
data and were compared, by using W and K-S tests, 
to determine whether these abiotic factors significantly 
affect the distribution of angel sharks in the two areas. 
To describe region-specific depth, temperature, and sa¬ 
linity preferences, the upper and lower quartiles are 
presented for each variable, as suggested by Magnu- 
son et al. (1979) for skewed data. Logistic regression 
was used to examine the relationship between bino¬ 
mial catch (i.e., no catch versus positive catch), depth, 
temperature, and salinity. Because of a significant col- 
linearity between depth and temperature within some 
seasons, logistic models were run that included and 
excluded depth. 
Data were obtained from the NOAA National Cen¬ 
ters for Environmental Information (Boyer et al. 2 ; Sei- 
dov et al. 3 ) to generate maps of bottom temperature 
and salinity off the southeastern EC and throughout 
the GOM in order to visualize potential barriers to 
movements between the two regions. Mean values for 
both variables were obtained for grids of 1/10° latitude 
by 1/10° longitude and plotted with ArcGIS 4 software, 
vers. 10.3.1 (Esri, Redlands, CA). Temperature data 
were limited to winter months (i.e., January, February 
and March), whereas salinity data was pooled over all 
months. 
Results 
Data were obtained from 104,957 trawls conducted 
from Nova Scotia to the Florida Keys (/? =66,161) and 
throughout the northern GOM (n=38,796) (Fig. 1). Off 
2 Boyer, T. P., M. Biddle, M. Hamilton, A. V. Mishonov, C. 
Paver, D. Seidov, and M. Zweng. 2015. Gulf of Mexico 
regional climatology (NCEI accession 0123320). Vers. 1.1. 
NOAA Natl. Cent. Environ. Inf. Data set. [Available from 
website, accessed March 2018.] 
3 Seidov, D., O. K. Baranova, D. R. Johnson, T. P. Boyer, A. 
V. Mishonov, and A. R. Parsons. 2016. Northwest Atlantic 
regional climatology, Regional Climatology Team (NCEI ac¬ 
cession 0155889). Vers. 1.1. NOAA Natl. Cent. Environ. Inf. 
Data set. website, accessed March 2018.] 
4 Mention of trade names or commercial companies is for iden¬ 
tification purposes only and does not imply endorsement by 
the National Marine Fisheries Service, NOAA 
