344 
Abstract — Estimating rare events 
from zero-heavy data (data with 
many zero values) is a common chal- 
lenge in fisheries science and ecology. 
For example, loggerhead sea turtles 
(Caretta caretta) and leatherback sea 
turtles (Dermochelys coriacea) account 
for less than 1% of total catch in the 
U.S. Atlantic pelagic longline fishery. 
Nevertheless, the Southeast Fisher- 
ies Science Center (SEFSC) of the 
National Marine Fisheries Service 
(NMFS) is charged with assessing the 
effect of this fishery on these feder- 
ally protected species. Annual esti- 
mates of loggerhead and leatherback 
bycatch in a fishery can affect fishery 
management and species conservation 
decisions. However, current estimates 
have wide confidence intervals, and 
their accuracy is unknown. We evalu- 
ate 3 estimation methods, each at 2 
spatiotemporal scales, in simulations 
of 5 spatial scenarios representing 
incidental capture of sea turtles by 
the U.S. Atlantic pelagic longline 
fishery. The delta-lognormal method 
of estimating bycatch for calendar 
quarter and fishing area strata was 
the least biased estimation method in 
the spatial scenarios believed to be 
most realistic. This result supports 
the current estimation procedure used 
by the SEFSC. 
Manuscript submitted 22 September 2011. 
Manuscript accepted 29 May 2012. 
Fish. Bull. 110:344-360(2012). 
The views and opinions expressed 
or implied in this article are those of the 
author (or authors) and do not necessarily 
reflect the position of the National Marine 
Fisheries Service, NOAA. 
Evaluating methods for estimating rare events 
with zero-heavy data: a simulation model 
estimating sea turtle bycatch 
in the pelagic longline fishery 
Paige F. Barlow (contact author)' 
Jim Berkson 2 
Email address for contact author: pfbarlow@uga edu 
1 Department of Fish and Wildlife Conservation 
Virginia Polytechnic Institute and State University 
100 Cheatham Hall, Blacksburg, Virginia 24061 
Present address: Warnell School of Forestry and Natural Resources 
University of Georgia 
180 E Green Street, Athens, Georgia 30602 
2 National Marine Fisheries Service 
Southeast Fisheries Science Center 
NMFS-RTR Program at Virginia Tech 
100 Cheatham Hall, Blacksburg, Virginia 24061 
Fishery scientists and ecologists often 
must make inferences from data with 
many zero values and high variance. 
For example, studies of the detection 
or capture of protected species or 
infrequently encountered commercial 
species result in data sets that contain 
many zeros and few positive values 
with a skewed distribution (Martin 
et al., 2005; Sileshi, 2006). Analyz- 
ing such zero-heavy data sets (data 
sets with many zero values) poses 
unique challenges that are not always 
met, perhaps, because method suit- 
ability has not been explored fully 
or because of deference to familiar 
methods (Walters, 2003; Martin et al., 
2005; Sileshi, 2006). It is not uncom- 
mon for scientists to use familiar 
statistical methods even when it may 
be impossible to meet model assump- 
tions (Walters, 2003; Sileshi, 2006). 
Additionally, transformations often 
are employed to overcome violations 
of the errors’ assumed variance-mean 
relationship, but transformations will 
not ameliorate the problems associ- 
ated with zero-heavy data (Martin et 
al., 2005). Biased estimates and incor- 
rect conclusions can result from not 
accounting for excess zeros and using 
models with inappropriate assump- 
tions (Martin et al., 2005). 
However, interest is growing in an- 
alyzing data with excess zeros and 
in estimating rare events because 
more appropriate analyses can pro- 
vide more accurate results (Martin et 
al., 2005). If scientists use the most 
appropriate analysis method for a 
system, they are more likely to ob- 
tain the best available estimate for 
making management decisions for 
their study system. In this article, we 
evaluate several methods for making 
inferences from zero-heavy data sets 
in the context of estimating fleetwide 
bycatch of sea turtles. By evaluating 
method performance, we identify the 
most suitable estimation method in a 
variety of fishery scenarios. 
The U.S. Atlantic pelagic longline 
fishery targets swordfish (Xiphias 
gladius) and tuna ( Thunnus spp.) in 
the Atlantic Ocean, Caribbean Sea, 
and Gulf of Mexico. From 2005 to 
2007, longlines were used to catch 
approximately 73% of swordfish, 84% 
of yellowfin tuna ( Thunnus albacares), 
and 90% of bigeye tuna ( Thunnus 
obesus) domestic landings by weight 
nationwide, where fishing gear was 
specified (NMFS 1 ). However, sword- 
fish and tuna constituted less than 
1 NMFS (National Marine Fisheries Ser- 
vice). 2009. Annual commercial land- 
ings by gear type, http://www.st.nmfs. 
noaa.gov/stl/commercial/landings/ 
gear_landings.html, accessed 12 May. 
