370 
Multiscale analysis of factors that affect the 
distribution of sharks throughout the northern 
Gulf of Mexico 
J. Marcus Drymon (contact author )’- 2 
Laure Carassou 3 
Sean P. Powers 1 - 2 
Mark Grace 4 
John Dindo 2 
Brian Dzwonkowski 2 
Email address for contact author: mdrymon@disl.org 
1 Department of Marine Sciences 
University of South Alabama, LSCB-25 
Mobile, Alabama 36688 
2 Dauphin Island Sea Lab 
101 Bienville Boulevard 
Dauphin Island, Alabama 36528 
3 Department of Zoology and Entomology 
Rhodes University 
P.O. Box 94 
Grahamstown 6140, South Africa 
4 Mississippi Laboratories 
Southeast Fisheries Science Center 
National Marine Fisheries Service, NOAA 
3209 Frederic Street 
Pascagoula, Mississippi 39567 
Abstract— Identification of the spa- 
tial scale at which marine com- 
munities are organized is critical 
to proper management, yet this is 
particularly difficult to determine 
for highly migratory species like 
sharks. We used shark catch data 
collected during 2006-09 from fish- 
ery-independent bottom-longline 
surveys, as well as biotic and abiotic 
explanatory data to identify the fac- 
tors that affect the distribution of 
coastal sharks at 2 spatial scales in 
the northern Gulf of Mexico. Cen- 
tered principal component analyses 
(PCAs) were used to visualize the 
patterns that characterize shark 
distributions at small (Alabama and 
Mississippi coast) and large (north- 
ern Gulf of Mexico) spatial scales. 
Environmental data on tempera- 
ture, salinity, dissolved oxygen (DO), 
depth, fish and crustacean biomass, 
and chlorophyll-a (chl-a) concentra- 
tion were analyzed with normed 
PCAs at both spatial scales. The re- 
lationships between values of shark 
catch per unit of effort (CPUE) and 
environmental factors were then an- 
alyzed at each scale with co-inertia 
analysis (COIA). Results from COIA 
indicated that the degree of agree- 
ment between the structure of the 
environmental and shark data sets 
was relatively higher at the small 
spatial scale than at the large one. 
CPUE of Blacktip Shark (Carcha- 
rhinus limbatus) was related posi- 
tively with crustacean biomass at 
both spatial scales. Similarly, CPUE 
of Atlantic Sharpnose Shark (Rhizo- 
prionodon terraenovae) was related 
positively with chl-a concentration 
and negatively with DO at both spa- 
tial scales. Conversely, distribution 
of Blacknose Shark (C. acronotus ) 
displayed a contrasting relationship 
with depth at the 2 scales consid- 
ered. Our results indicate that the 
factors influencing the distribution 
of sharks in the northern Gulf of 
Mexico are species specific but gen- 
erally transcend the spatial bound- 
aries used in our analyses. 
Manuscript submitted 25 October 2012. 
Manuscript accepted 29 August 2013. 
Fish. Bull. 111:370-380. 
doi: 10.7755/FB. 11 1.4.6 
The views and opinions expressed or 
implied in this article are those of the 
author (or authors) and do not necesarily 
reflect the position of the National 
Marine Fisheries Service, NOAA. 
Paramount to the conservation of 
marine resources and ecosystems is 
the identification of proper spatial 
scales for management plans. Al- 
though long recognized as a central, 
if not universal, concept in ecology, 
the notion of scale more recently has 
begun a transition from qualitative 
description to quantitative assess- 
ment (Schneider, 2001). For marine 
systems, this transition is particu- 
larly important because choice of 
spatial scale directly affects the iden- 
tification of patterns (Perry and Om- 
mer, 2003). As fisheries management 
plans transition to an ecosystem- 
based approach, the identification of 
suitable spatial scales becomes even 
more important (Hughes et ah, 2005; 
Francis et al., 2007). 
For sharks, many of which are 
considered top predators and play a 
central role in regulation of marine 
ecosystems (Heithaus et al., 2008), 
the identification of appropriate spa- 
tial scales for management is made 
more difficult than the identification 
of spatial scales for bony fishes be- 
cause of their highly migratory na- 
ture and relative paucity. Traditional 
mark-and-recapture methods allow 
for examination of gross spatial- 
scale patterns in sharks, but these 
methods are limited by low recap- 
ture rates. Pop-up satellite archival 
tags circumvent this problem by ex- 
ponentially increasing the odds of 
retrieving data from tagged sharks. 
Unfortunately, their use is often 
cost prohibitive, and the algorithms 
presently employed to estimate geo- 
graphic locations are too coarse to 
provide reliable spatial pattern data 
on small scales (i.e., tens of kilome- 
ters) (Sims, 2010; Hammerschlag et 
al., 2011). Consequently, information 
