92 
Fishery Bulletin 11 7(1-2) 
Table 1 
Comparison of observations of shark species between 2 methods used: 1) un¬ 
derwater visual census conducted by scuba divers and 2) analysis of videos 
taken with baited remote underwater video stations. This comparison includes 
only observations from the 5 sites at which sharks were detected by divers. 
Diver surveys and station deployments occurred in July 2014 on the conti¬ 
nental shelf off east-central Florida. A dash indicates that a shark was not 
observed in the video from this site. 
Site number 
Diver 
Video 
10 
Rhizoprionodon terraenovae 
— 
34 
Ginglymostoma eirratum 
G. eirratum 
44 
Carcharhinus plumbeus 
G. eirratum 
55 
G. eirratum 
- 
67 
G. eirratum 
G. eirratum, Galeocerdo cuvier 
0 16 -[ 
0.14 - - 
o 
£ 0.12 
Q) 
3 010 - 
O 
O 
^ 0.08 - 
£ 0 06 
CD 
13 
S' 0 04 - 
LL _ [ 
0.02 - 
o.oo -L—L-r-L-L,J—L-,-1 l -r- l—L-r-J—L^J—I—i 1_,- 
Nurse Tiger Spinner Sandbar Atlantic Bull Lemon Carcharhinidae 
sharpnose 
Species 
Figure 3 
Frequency of occurrence of the 7 shark species observed through 
analysis of video recorded with baited remote underwater video 
stations in July 2014 off east-central Florida: nurse (Ginglymos- 
torna eirratum), tiger ( Galeocerdo cuvier), spinner ( Carcharhinus 
brevipinna), sandbar (C. plumbeus), Atlantic sharpnose (Rhizo- 
prionodon terraenovae), bull (C. leucas ), and lemon ( Negaprion 
brevirostris) sharks. Frequency of occurrence for each species 
was calculated as the number of sites with observations of a 
species divided by the total number of sampled sites. Two sharks 
could be identified only to the level of family (Carcharhinidae). 
sharks observed through the use of these 2 sampling 
methods. In some cases, divers observed sharks that 
were not recorded in videos and vice versa, and in oth¬ 
er cases the same species of sharks were observed both 
by divers and in videos (Table 1). 
Comparing all 3 methods (entire video analyzed, 
only SERFS 20-min segment of video analyzed, UVC), 
a greater diversity and abundance of sharks were re¬ 
corded when the entire video was 
analyzed. As a result, estimates 
of rank abundance for shark spe¬ 
cies differed by the method used 
(Table 2). 
Discussion 
By rapidly analyzing an entire 
video rather than only the 20-min 
subsample required by the SERFS 
protocol (an average of 58 min of 
additional video combined, before 
and after the subsample), we were 
able to observe sharks in videos 
from 400% more sites and increase 
the number of species recorded by 
40%. Therefore, our estimates of 
relative abundance for these key 
fish community members changed 
from those determined by using the SERFS 
protocol. These findings confirm for species of 
sharks the results of Bacheler and Shertzer 
(2015), who suggested that fast-moving, soli¬ 
tary, infrequently encountered fish species had 
a higher probability of being missed in analysis 
of video subsamples and recommended increas¬ 
ing the number of video segments reviewed to 
target these types of species. Similarly, we ob¬ 
served sharks for more sites within the longer 
intervals (an average of 48 min of additional 
video) that followed the SERFS 20-min seg¬ 
ments than within other parts of videos, and 
longer sampling intervals have been associ¬ 
ated with increased arrival of targeted species 
in other studies that used underwater video 
(Watson, 2006; Watson et ah, 2010). 
Given the significant costs associated with 
large-scale marine research surveys, examina¬ 
tion of a complete video to gain additional in¬ 
formation on large-bodied, less-abundant spe¬ 
cies, such as sharks, represents a relatively 
simple way to add significant value to the al¬ 
ready successful SERFS (e.g., Link et al., 2008; 
Mitchell et al., 2014; Bacheler et al., 2016). In 
addition, the regional coverage of the SERFS, 
together with habitat and environmental data 
(e.g., depth, temperature, salinity, pH, turbid¬ 
ity) that are collected annually at a large num¬ 
ber of sites (-1500 sites per year), provides an 
important opportunity to collect relative abun¬ 
dance and habitat use information on relatively expan¬ 
sive spatial and temporal scales for a variety of shark 
species found in the Atlantic Ocean. For example, the 
distribution and biomass of sharks are influenced by 
physical factors, such as sea-surface temperature, oce¬ 
anic primary productivity, and reef complexity, and 
by biological factors, such as competition, reproduc¬ 
tion, lower-trophic-level biomass, and prey availability 
