Northeast Fisheries Science Center Reference Document 06-19
Estimated
Average Annual Bycatch
of Loggerhead Sea Turtles (Caretta caretta)
in U.S. Mid-Atlantic Bottom Otter Trawl Gear,
1996-2004
by Kimberly
T. Murray
National
Marine Fisheries Service, 166 Water St.,
Woods Hole MA 02543
Print
publication date September 2006;
web version posted September 11, 2006
Citation: Murray KT . 2006. Estimated Average Annual
Bycatch of Loggerhead Sea Turtles (Caretta
caretta) in U.S. Mid-Atlantic Bottom Otter Trawl Gear, 1996-2004.
U.S. Dep. Commer., Northeast Fish. Sci. Cent. Ref. Doc. 06-19;
26 p.
Download complete PDF/print version
Abstract
During 1994-2004, fisheries observers documented interactions between
bottom otter trawl gear and loggerhead (Caretta caretta), Kemp’s
ridley (Lepidochelys kempi) and leatherback (Dermochelys coriacea)
turtles in the U.S. Mid-Atlantic region (i.e. south of 41°30’N/66°W
to approximately 35º00’N/75°30’W). Most of these
interactions were with loggerhead turtles, although Kemp’s ridley
and leatherback turtles were also observed in small numbers. Due to the
low number of Kemp’s ridley and leatherback interactions, bycatch
rates and total mortality were only estimated for loggerhead turtles.
Vessel Trip Reports from fishermen operating bottom otter trawl gear
in the Mid-Atlantic were used to expand predicted bycatch rates to total
estimated bycatch. Due to reduced quality of VTR data in 1994 and
1995, bycatch is reported from 1996-2004 only. Significant factors
affecting sea turtle bycatch were latitude zone, depth, sea surface temperature,
and the use of a working Turtle Excluder Device (TED). A working
TED is defined as one which is not clogged (e.g., with fish or debris). Predicted
bycatch rates were stratified by the combination of significant variables. Estimated
average annual bycatch of loggerhead turtles in Mid-Atlantic bottom otter
trawl gear during 1996-2004 was 616 animals (C.V.=0.23, 95% C.I. over
the 9 year period: 367-890).
INTRODUCTION
Four species of sea turtles inhabit U.S. Mid-Atlantic waters seasonally,
emigrating north from southern latitudes in spring and returning south
in the fall (Shoop and Kenney 1992; Musick and Limpus 1997). All
of these species (loggerhead [Caretta caretta], Kemp’s ridley
[Lepidochelys kempi], leatherback [Dermochelys coriacea],
green [Chelonia mydas]) are listed as either endangered or threatened
under the U.S. Endangered Species Act of 1973. The spatial distribution
of turtles in the Mid-Atlantic is coincident with a number of fisheries
operating in both inshore and offshore waters during this period.
From 1994-2004, observers aboard commercial fishing vessels documented
interactions between turtles and bottom otter trawl gear in the region
from Cape Hatteras, NC to Long Island, NY. Most of these interactions
included loggerhead turtles, although small numbers of interactions with
Kemp’s ridley and leatherback turtles were also observed.
In this report bycatch rates of loggerhead turtles (defined as the number
of turtles caught per day fished, where day fished is equal to hours
fished/24) are derived from data collected by observers in the Mid-Atlantic
between January 1994 and December 2004, and applied to commercial fishing
activity (where effort is expressed as days fished) to estimate annual
loggerhead bycatch. Bycatch was estimated only for loggerheads
as there were too few documented interactions of other turtle species
to derive reliable bycatch estimates for these species. Fishing
effort data in 1994 and 1995 were excluded from the bycatch rate expansion
due to the lower quality of the commercial data in these years. Thus,
this report provides an estimate of the average annual bycatch of loggerhead
sea turtles in bottom otter trawl gear operating in the Mid-Atlantic
during 1996 through 2004.
METHODS
DATA SOURCES
Observer Data
Information collected by observers aboard vessels using bottom otter
trawl gear in the Mid-Atlantic was used to model the expected number
of turtles caught per day fished. This analysis uses data collected
from 18,665 hauls over 1,937 trips. For each haul, observers
recorded information such as location, average depth, tow duration,
tow speed, whether a Turtle Excluder Device (TED) was used in the trawl
net, whether obstructions blocked the TED opening, fish species targeted
on the haul, and whether a turtle interaction occurred. In this
analysis, the geographic location of a turtle interaction corresponds
to the location recorded for the beginning of the haul because observers
do not know when during the haul an interaction takes place[1]. Other sources of data were used when information collected
by observers was incomplete, or to refine the information recorded. For
instance, bathymetry data was acquired from a secondary source in order
to get a measurement of depth at the beginning of each fishing haul,
rather than the average depth over the length of the haul. This
was done so that depth information matched the location that was assigned
to each turtle interaction.
The model developed from observer data was used to predict loggerhead
bycatch rates in several strata. In this analysis, rates are
stratified in two latitude zones, with a combination of gear, sea surface
temperature, and depth categories (see Turtle Bycatch Model below). Predicted
bycatch rates are expanded using commercial fishing effort to estimate
total annual bycatch of loggerheads in Mid-Atlantic bottom otter trawl
fisheries.
Observer coverage of Mid-Atlantic bottom otter trawl gear during 1996-2004
was designed primarily to monitor fish discards and marine mammal interactions. During
the fall of 1998 and early 1999 there was some sampling dedicated to
observing turtle interactions in the southern Mid-Atlantic. Coverage
(% observed days fished/Vessel Trip Report [VTR] days fished) during
1996-2004 averaged 0.8% (Table 1a). Coverage per year ranged
from 0.2% to 4.8% between 1996 and 2004, with the most coverage occurring
in 2003 and 2004. Coverage in the two Mid-Atlantic latitude zones
in which bycatch rates were stratified was 0.7 and 1.1% (Table 1b).
Spatial Extent of Bycatch Estimates
In this analysis, the Mid-Atlantic was defined as the region from
the shoreline below 41°30’N/66°W to the southern extent
of the Northeast Fisheries Science Center observer data collection,
around 35°00’N/75°30’W.
Types of Trawl Nets
Bottom otter trawl nets used in the Mid-Atlantic include a variety
of net types. One type is a flynet, a high profile trawl used
for fish that school higher in the water column than typical groundfish,
and commonly used in depths less than 36 m (NCDMF, 2004). During
1994-1998, observers documented turtle interactions in flynets (see
Results below). Since 2000, however, observers no longer recorded
the type of trawl net used during a haul, so there was incomplete information
to assess differences in bycatch rates due to net type[2]. Instead,
other factors such as depth, head rope length, and target species were
examined to serve as a proxy for different net configurations.
The trawl nets analyzed here are designed primarily to target fish. Nets
designed to catch scallops are not included in the analysis because
a dedicated sampling program for scallop trawl gear did not begin until
mid-2004. Thus, any turtle bycatch which may have occurred during
1994-2004 in scallop trawl gear was largely unknown. Moreover,
there were no observer data to compare similarities in fishing practices
between nets designed to catch fish versus those designed to catch
scallops.
Source of SST and Depth Data for Observer Data
Observers did not record sea surface temperature (SST) information
on sixty-three percent of observed hauls. As a result, SST data
for each haul were obtained from 5-day SST composites derived from
a variety of satellite imagery sources, or 5-day climatology images
downloaded from NASA’s Jet Propulsion Laboratory[3]. The
climatology images are SST values averaged over 1985-1999 on a 9 km
grid. Satellite imagery sources
included AVHRR Pathfinder Version 5, Modis Aqua, Modis Terra, and GOES
satellites[4]. Available
data from these sources were combined to create a 5-day median composite
image for each calendar day. A Visual Basic for Applications
routine in ArcGIS 9.1 extracted SST values at point locations (or used
a median value from a 3x3 cell window) for both the 5-day median composites
and the climatology. When choosing which SST data to use in the
analysis, the 5-day medians were preferred over the climatology, and
point locations were preferred over the 3x3 cell medians. To
screen for anomalous temperature values derived from daily images,
a field was created by taking the difference between the best daily
5-day SSTs and the best climatology available. If the difference
was greater than +/-2.5°C (7% of data) then the best climatology
data was used instead of the daily images as the final SST.
Depth data for each observed haul were obtained using bathymetry information
acquired from the National Geophysical Data Center[5]. Like
SST, bottom depth was obtained via ArcGIS with the data representing
the depth at the beginning of each fishing tow recorded by the observer. The
NGDC data were used instead of the depth information recorded by the
observer, which for many locations represented the average depth over
the length of the tow[6].
Use of a Turtle Excluder Device
Under Amendment 2 to the Summer Flounder Fishery Management Plan (implemented
in 1992), all vessels using bottom trawls to fish for summer flounder
in specific times and areas off Virginia and North Carolina are required
to use NMFS-approved Turtle Excluder Devices (TEDs) in their nets (Final
Rule, FR 57:57358, 4 December 1992). The trawl fishery for summer
flounder is one of two fisheries operating in the Mid-Atlantic which
requires the use of TEDs[7].
Out of the 18,665 observed hauls used in this analysis, 224 hauls
(1.2%) did not record information about the use of a Turtle Excluder
Device (TED). For all hauls not targeting summer flounder, for
which it was unknown whether the trawl was equipped with a TED, it
was assumed the trawl was not equipped with a TED. Otherwise,
use of a TED was assumed based on requirements for TED use in the summer
flounder fishery (Interim Final Rule, FR 58:48797, 20 September 1993). That
is, an unknown haul was assumed to have an excluder if it operated
south of 37°05’N (Cape Charles, VA)
to 33°35’N (North Carolina-South Carolina border). After
January 1996, for the period Jan 15-Mar 15, the northern TED boundary
moved south to 35°46.1’N (Oregon Inlet) (Final Rule, FR 61:1846,
24 January 1996)[8]. Hence,
it was assumed that any unknown hauls targeting summer flounder north
of Oregon Inlet during these 3 months did not have an excluder, and
any unknown hauls during the remainder of the year did. If an
unknown haul operated south of Oregon Inlet, then the haul was assumed
to have an excluder.
After correcting for unknown values, 348 (1.9%) observed hauls (2.0%
days fished) used trawls equipped with TEDs. Almost all observed
hauls (99.5%) using TEDs were targeting summer flounder. Of these
348 hauls, 18 (5.2%) were clogged with debris. In this analysis,
a TED clogged with debris was assumed to be not working. To analyze
whether bycatch rates differed depending on a working or non-working
TED, hauls with non-working TEDs were grouped with hauls which did
not have TEDs.
Commercial Data
All federally permitted vessels operating under Fishery Management
Plans implemented by the NMFS Northeast Region are required to complete
VTRs providing information on area fished and fishing effort for each
fishing trip completed (Rago et al. 2005). Mandatory reporting
in some fisheries began in April 1994, and by 1998 most fisheries had
a mandatory VTR requirement[9]. Effort
data in VTRs from fishermen operating bottom otter trawl gear in the
Mid-Atlantic (i.e., south of 41°30’N) were
used in conjunction with predicted bycatch rates to estimate total
annual bycatch of loggerheads in the Mid-Atlantic bottom otter trawl
fisheries. Several adjustments were made to the VTR data. First,
missing data necessary for stratifying bycatch estimates were prorated
or predicted based on information from other trips. Second, VTR
effort was adjusted to account for effort which was not reflected in
the database (for instance, if fishermen did not file a logbook record). Lastly,
some assumptions were made about the proportion of trips using TEDs
in trawl nets as well as the proportion of trips using working TEDs,
because no information existed in VTR logbooks to indicate the use
or condition of these devices.
All dealers who buy and sell fish regulated by federal FMPs are required
to report 100% of their transactions (Rago et al. 2005). Thus,
landings data from the dealer database are considered to be a near
census of fishery harvests; however, the dealer reports do not contain
any information on the fishing effort associated with the landings
that they purchased or sold. A preliminary assessment of VTR
data during 1994-2004 revealed that data in 1994 and 1995 were of lower
quality compared to data from years 1996-2004 based on comparisons
with dealer data and observer sampling logs[10]. In
general, there were relatively large discrepancies in the number of
trips between dealer and VTR data in 1994 (this is understandable because
reporting did not become effective until mid-1994 for many FMPs). Furthermore,
discrepancies were apparent between the values recorded in some fields
in the VTR and observer sampling logs in 1994-1995 for the same trips. Additionally,
in the early years after trip reporting became mandatory, a large number
of discrepancies were evident between the information content of the
submitted logbooks and the representation of these data in the VTR
database (NEFSC 1996, Wigley et al. 1998). As a result of these
issues, bycatch estimates are provided only for 1996-2004.
Prorating VTR Effort
In this analysis, bycatch rates are stratified over two latitude zones. Twelve
percent of VTR trips were missing latitude zone information. For
these trips, the missing latitude zone was filled in from the statistical
area recorded on the VTR log. For trips missing statistical area
or where the statistical area bisected two latitude zones (1.6%), the
number of days fished were prorated across bycatch strata based on
the percentage of days fished in these strata from trips with known
coordinates[11].
Source of SST and Depth data for VTR
Sea surface temperature data at each fishing position recorded in
VTR logbooks were obtained from the same satellite or climatology data
sources used to obtain observer data. SST values could not be
obtained for 14.5% of VTR trips due to missing coordinate positions. For
these events, SST was predicted by using a linear regression based
on year, month, and statistical area (r2=0.93).
For each fishing position recorded in VTR logbooks, depth data were
obtained from the bathymetry data from the National
Geophysical Data Center. Thus, the source for depth data was
consistent across both the observer and commercial datasets.
Effort Adjustments
To assess shortcomings in the number of VTR trips reported during
1996-2004, the number of VTR trips (summed by year and state in which
catch was landed) was compared to the number of trips in the dealer
data (also summed by year and state). Comparisons between the
number of reported trips in the VTR and dealer databases revealed that
some states were underrepresented in the VTR database from 1996-2004. To
account for “missing” effort in the VTR database, total
days fished in the VTR data were adjusted upward to allow for proper
expansion of the observed bycatch rates. States with more dealer
reported trips than VTR trips had the VTR days fished increased based
on the percent difference between the two databases.
In this analysis, turtle bycatch rates are stratified by two latitude
zones. The percentage of effort represented by state in each
latitude stratum, combined with information obtained from comparisons
with dealer data, was used to adjust effort within each latitude zone. Thus
the total VTR effort within a stratum was adjusted as:
[Σ(Total Days Fished)ij * (% State Representation)ijk *
(State Adjustment factor)ijk] +
(Total Days Fished)ij
where i = latitude stratum, j = year, k = state and
The state adjustment factor = 1 + x,
where x represents the percentage increase needed for a particular
state based on comparisons with dealer data. VTR trips over all
states were adjusted upwards an average of 11%.
Use of a Turtle Excluder Device
In this analysis, turtle bycatch rates were stratified based on whether
a working TED was present; however, there is no information in VTR
logbooks to indicate use or condition of this device. For this
analysis, it was assumed that the amount of VTR effort with or without
a TED was the same as the percentage of observed effort with or without
a TED[12]. In
addition, it was assumed that the amount of VTR effort with a working
TED was the same as the percentage of observed effort with a working
TED.
To derive the amount of VTR effort that used a TED, the total adjusted
effort in each stratum was multiplied by the proportion of observed
hauls with a TED in the same stratum. The amount of effort using
a TED was then multiplied by the proportion of observed hauls with
a working TED in the same stratum. Approximately 2.0% of VTR
effort in the Mid-Atlantic used working TEDs (Table
2).
Turtle Bycatch Model
The bycatch rate of turtles was calculated as:
Number
of Observed Turtles
Days
Fished
where
Days
Fished = Hours Fished
24
and hours fished equals the amount of time the net is towed through
the water.
A Poisson regression (GAM function, SPLUS 7.0) was used to model the
expected turtle bycatch per day fished, because the number of turtles
caught on a haul ranged from 0 to 5. The model can be written
as:
where fi are smoothing functions, and xi are
predictor variables describing environmental, gear, or fishing characteristics.
Model Development
Identifying characteristics associated with bycatch rates can be used
to stratify observations, thus increasing the precision of estimated
rates by removing variability between strata (Dixon et al. 2005). In
a preliminary analysis, a full Generalized Additive Model (GAM) was
fit to the data in order to identify covariates associated with turtle
bycatch rates (Table
2). Depth and SST were entered into the
model as continuous variables. Due to low observer coverage,
all years were pooled in fitting the bycatch model. In the GAM,
parameters of the continuous prediction variables were estimated by
a smoothing spline. GAM smoothers summarize the trend of a response
measurement as a function of one or more predictor measurements (Hastie
and Tibshirani 1990), and can be used to guide the dichotomization
of continuous variables (Hin et al. 1999) or to consolidate categorical
variables into larger groupings. A forward stepwise selection
method selected variables that resulted in the greatest change in the
Akaike Information Criterion (AIC) value relative to all other variables
in the scope of the model (StepAIC function, SPLUS 7.0). The
AIC is defined as:
where log(
)
is the numerical value of the log-likelihood at its maximum point and K is
the number of estimable parameters (Burnham and Anderson, 2002). The
AIC is a measure of the goodness of fit that includes the level of
parsimony, defined as a model that fits the data well and includes
as few parameters as necessary (Burnham and Anderson, 2002). This
process suggested that latitude, depth, SST, and TED group resulted
in the greatest change in AIC.
Next, GAM smoothers were used to categorize latitude, depth, and
SST variables according to their effect on the bycatch rates (Figure
1). For
continuous variables (depth and SST), the effect of the variable on
the bycatch rate is higher at values where the curve is above zero. Sea
surface temperature was binned into two categories: high (>18°C
) and low (≤18°C). Depth was binned into two categories:
shallow (<50 m) and deep waters (≥50 m). For categorical
variables (latitude), values above zero were grouped together, and
values below zero were grouped together. Latitude was grouped
into two broader “latitude zone” categories: latzone3438
(34°N -38°59’N) and latzone3941 (39°N -41°30’N). Grouping
variables was done to prorate portions of commercial fishing effort
into appropriate bycatch strata, and to expand bycatch rates to a total
estimate.
Model Selection
To select the best-fitting model, variables were tested individually
in a forward stepwise selection. Depth and SST were entered as
categorical variables defined from the GAM smoothers, and latitude
zone was substituted for latitude. The order in which variables
entered the model corresponded to the order in which variables reduced
the AIC from most to least. The best-fitting model was determined
by evaluating the AIC in combination with p-values from a chi-squared
test (ANOVA function) to evaluate model improvement at each step. A
variable was retained if the p-value between two models was less than
or equal to 0.05 and the AIC value declined.
Possible overdispersion in the data was evaluated by examining the
ratio of the residual deviance to the residual degrees of freedom in
the final model (Hardin and Hilbe 2001).
Model Validation
The observed number of turtle interactions was compared to the expected
number of interactions from the model within each bycatch stratum. Goodness-of-fit
of the model was then evaluated using a Pearson chi-square statistic
(McCullagh and Nelder 1983).
Estimated Average Annual Bycatch
Bycatch rates were stratified based on significant factors found to
affect turtle bycatch in the Mid-Atlantic. The coefficient of
variation (CV) and 95% confidence interval (CI) for each stratum-specific
bycatch rate were estimated by bootstrap resampling (Efron and Tibshirani,
1993). The resampling unit was a single trip with its associated
hauls. Replicate bycatch rates were generated by sampling with
replacement 1000 times from the original data set. In each stratum,
the CV was defined as the standard deviation of the bootstrap replicate
bycatch rate divided by the mean bycatch rate from the original dataset.
Within each stratum, the estimated average annual turtle bycatch was
calculated as the product of the predicted bycatch rate for that stratum
and the average annual number of days fished by the trawl fishery in
that stratum from 1996-2004:
ΣPredicted Bycatchi x (Average
Days Fished per Year)i
ΣDays Fishedi
where i = stratum. Average annual bycatch was the sum of the
stratified bycatch estimates.
A CV and 95% confidence interval for the average annual bycatch aggregated
over all strata in each latitude zone were also calculated from the
bootstrap replicates. Average annual bycatch was first calculated
by stratum in each latitude zone:
where
is
the expected average annual bycatch in stratum s in bootstrap
replicate U in latitude zone i,
is
the predicted bycatch rate for stratum s in bootstrap replicate U,
and
is
the average annual VTR effort in stratum s in latitude zone i.
The average annual bycatch for bootstrap replicate U in latitude zone i,
, is then given by:
The CV and 95 % CI of the average annual bycatch estimate was computed
for .
RESULTS
Observed Catches
Observers documented 66 loggerhead turtle interactions with bottom otter
trawl gear from 1994-2004 (Table 3, Figure 2). In addition, observers
documented interactions with 2 Kemp’s ridley, 1 leatherback, and
3 unknown turtle species. These latter interactions were excluded
from the bycatch analysis due to the low number of observed interactions. Of
the 66 documented loggerhead interactions, 38 (57%) were alive and uninjured,
and 28 (43%) were dead, injured, resuscitated, or of unknown condition.
Observed loggerhead interactions occurred throughout most of the year,
with most in waters off the coast of North Carolina. Fifty-eight
interactions (88%) occurred in latitude zone 3438, and 8 (12%) in latitude
zone 3941. Twenty-one
(32%) of the interactions occurred in waters ≤18°C. Only
two (3%) of the interactions occurred in waters deeper than 31 m. No
interactions occurred in March, April, or May. The size of the
cod end mesh in nets which took turtles ranged from 1.7" to 6.6". Duration
of tows with bycatch ranged from a half hour to over 5 hours. Eight
interactions (12%) occurred on 4 vessels equipped with TEDs. Seven
of the eight interactions occurred when the TED was clogged with debris. No
interactions in TEDs (both working and non-working) occurred after 1999. At
least twenty-three interactions (35%) occurred in flynets targeting either
croaker or weakfish. Loggerhead turtles were captured on vessels
targeting summer flounder (50%), croaker (27%), weakfish (11%), long-finned
squid (8%), groundfish (3%) and short-finned squid (1%).
Loggerhead turtle interactions occurred on 27 trips, with 1 trip catching
12 turtles, and another trip catching 8 turtles. On these two trips
interactions occurred in flynets. Twenty-one (32%) of the interactions
occurred in 1994, and 15 (23%) occurred in 1999.
In addition to the 66 interactions, ten severely decomposed turtles
and 1 moderately decomposed turtle were caught incidentally in trawl
gear during 1994-2004. Three of the 11 interactions were with loggerhead
turtles and the other 8 were with unknown species. These 11 animals
were not included in the bycatch analysis because it was assumed that
these mortalities did not occur in the trawl gear. Four of the
ten severely decomposed turtles occurred on 1 trip in 2002 and were wrapped
in gillnet gear.
TURTLE BYCATCH MODEL
Factors Affecting Bycatch Rates
Significant factors affecting sea turtle bycatch were latitude zone,
depth, SST, and the use of a working TED (Table 4). Predicted bycatch
rates were stratified by the combination of these factors (Table 5). Because
TEDs were not used in latitudes north of 38°N, predicted bycatch
rates for hauls with a TED are only reported for latitude zone 3438. The
predicted number of catches was similar to the observed number of catches
in each stratum (Table 6), indicating the model fit the data reasonably
well (
= 9.04,
p = 0.11). Data also did not appear overdispersed (residual deviance/residual
df for selected model = 0.03).
The highest bycatch rate occurred between 34°N and 39°N in waters
shallower than 50 m and warmer than 18°C, and involved vessels using
either no TED or a non-working TED (Table
5). Bycatch rates were
much lower on hauls equipped with working TEDs. On average, the
model predicted that in any given latitude zone, depth, and SST stratum,
bycatch rates with a working TED were 11% of the bycatch rate without
a working TED.
Mesh size of the cod end, towspeed, and head rope length of the trawl
net did not significantly affect bycatch rates. Species targeted
on a haul also did not have a significant effect on turtle bycatch rates.
Estimated Average Annual Bycatch
Estimated average annual bycatch of turtles per year in Mid-Atlantic
bottom otter trawl fisheries, averaged over 1996-2004, is as follows:
| Latitude Zone |
Average Turtle Bycatch/
Year
1996-2004 |
CV |
95% CI* |
Lat3941 |
147 |
0.42 |
36-271 |
Lat3438 |
469 |
0.28 |
240-736 |
Total Mid-Atlantic |
616 |
0.23 |
367-890 |
*Confidence intervals represent
an average over nine years of data rather than a single year.
|
In the southern Mid-Atlantic (between 34°N and 38°59'N),
most of the estimated bycatch (443 of 469 estimated takes: 94%) took
place in waters shallower than 50 m in gear without working TEDs (Table
7).
DISCUSSION
FACTORS AFFECTING BYCATCH
RATES
The incidental capture of turtles in bottom otter trawl gear occurs
throughout most of the year in the Mid-Atlantic. Based on factors
examined in this analysis, the probability of interacting with a turtle
is driven by the overlap between fishing activity and turtles in various
thermal and bathymetric regimes. Highest bycatch rates in bottom
otter trawl gear during 1994-2004 occurred in shallow waters (<50
m) of the southern Mid-Atlantic (between 34°N and 38°59’N). Many
turtle interactions have been documented off the Outer Banks of North
Carolina in winter, when turtles are associated with warm Gulf Stream
waters occurring over shallow areas (<70 m) of the continental shelf
(Epperly et al. 1995). These favorable temperature and depth regimes
put the concentrated population at risk for interaction with fishing
gear (Epperly et al. 1995).
In this analysis, trawl nets equipped with properly functioning TEDs
had a lower bycatch rate than nets without TEDs. The Flounder TED
is a special hard TED designed for use in the summer flounder fishery
(regulations for the technical specification are at 50 CFR 223.207). The
Flounder TED must be installed into a cylindrical piece of webbing called
a TED extension, constructed of webbing no larger than 3.5” stretched
mesh (Interim Final Rule, FR 64:55860, effective 15 November 1999). Prior
to this requirement, the minimum mesh size for extensions in trawl nets
fishing for summer flounder was 5.5” (Amendment 10 to
the Summer Flounder, Scup, and Black Sea Bass Fishery Management Plan).
Observed loggerhead turtle interactions in nets equipped with TEDs occurred
prior to the changes in mesh size regulations in November 1999. On
some hauls, observers commented that turtles’ flippers became entangled
in the 5.5” mesh, preventing their escape through the TED opening. Skates
and large fish also blocked the TED opening, trapping turtles. In
addition, observers noted (from captains) that turtles had difficulty
exiting the TED because the larger mesh webbing had difficulty maintaining
the correct shape.
Based on observer data in this analysis, 5.2% of TEDs (18 of 348 hauls)
were not working (i.e., clogged with debris). The number of hauls
with non-working TEDs was too small over the 9-year time series to examine
whether the bycatch rate of non-working TEDs differed before and after
the mesh changes in 1999.
In the southern latitude zone between 34°N and 38°59’N, 12 interactions
occurred on a single trip, and 8 interactions occurred on another. All
of these 20 interactions occurred in flynets targeting either weakfish
or croaker. Surrogates
were used to analyze the effect of different net types on bycatch rates
because information on net type was lacking for most of these data. Still,
there may be other factors not examined here that could influence the
probability of catching a turtle, such as the wing mesh of the net or
where the net fishes in the water column.
Trawl gear in the Mid-Atlantic targets a multitude of fish species,
yet turtle interactions occurred on hauls targeting only six species
groups (Table
3). The lack of observed turtle interactions on hauls
targeting fish species other than these may be due to lower observer
coverage levels for that particular sector of the trawl fishery. For
instance, all documented takes in 1999 occurred on hauls targeting summer
flounder in latitude zone 3438. During 1999, there was observer
coverage dedicated specifically to monitoring turtle interactions with
vessels targeting summer flounder[13],
despite there being commercial fishing activity for other species in
this area. Based on this analysis,
the likelihood of interacting with a turtle depends on the time and area
in which fishing takes place rather than the fish species being targeted. Increased
observer coverage allocated over temporal and spatial strata may provide
more information about the likelihood of turtle bycatch in trawls targeting
other fish species.
The model developed in this analysis is an explanatory model that estimates
total bycatch of loggerhead turtles in Mid-Atlantic bottom otter trawl
gear during 1996-2004. Before this model can be used as a predictive
model to estimate the annual bycatch of turtles beyond 2004, several
factors should be considered, such as annual trends in fishing effort,
possible changes in turtle abundance and distribution, and SST patterns. Predicted
bycatch rates were derived from all observed hauls in the Mid-Atlantic
pooled over 9 years. This analysis assumes that bycatch rates follow
a constant trend across the 9-year period. If annual trends in
turtle bycatch rates are not constant, then applying long-term average
bycatch rates to estimate total bycatch in future years could be biased
depending on changes in fishing effort, turtle abundance and distribution,
or environmental anomalies.
The model used to predict bycatch rates in the trawl fishery grouped
the continuous variables (depth and SST) into discrete categories. This
was done to prorate commercial fishing effort that was missing latitude
information into appropriate bycatch strata, and to expand bycatch rates
to a total estimate. Because of grouping, bycatch rates in the
model are assigned a constant rate between 0-18°C, and are assigned
another rate value for temperatures greater than 18°C. While
these groupings may be appropriate for stratifying rates to estimate
total bycatch, a different approach should be explored for models intended
to inform mitigation strategies (such as time/area closures).
Future work should investigate other statistical models to evaluate
bycatch. This analysis assumed observed hauls were independent. However,
information collected on hauls within trips is hierarchical; with this
structure, one might expect bycatches within a trip to be more closely
related than bycatches across trips (McCracken 2004). An alternative
model suitable to this type of structure is the Generalized Linear Mixed
Model (GLMM) (McCracken 2004; Venables and Dichmont 2004). GLMMs,
however, require more information to support the complex algorithms necessary
to fit the model (McCracken 2004). Therefore, the use of GLMMs
for rare events such as turtle bycatch may be limited. Alternatively,
other sampling units could be used to expand the bycatch rates (Borges
et al. 2005). For example, modeling bycatch per trip may avoid
any dependence on hauls within trips, though some information concerning
the predictor variables may be lost at this level (McCracken 2004).
ACKNOWLEDGMENTS
Chris Orphanides provided data on depth and SST for observed haul and
VTR locations. Debra Palka, Marjorie Rossman, Heather Haas, Mark
Terceiro, Richard Merrick, and Fred Serchuk all provided valuable comments
on draft versions of the manuscript. Observers provided a wealth
of information regarding turtle interactions in trawl gear.
LITERATURE CITED
Borges L, Zuur AF, Rogan R, Officer R. 2005. Choosing the
best sampling unit and auxiliary variable for discards estimations. Fish
Res 75:29-39.
Burnham KP, Anderson DR. 2002. Model
Selection and Multimodal Inference: A Practical Information-Theoretic Approach,
2nd Edition. New York (NY):
Springer-Verlag; 488 p.
Dixon PM, Ellison AM, Gotelli NJ. 2005. Improving the precision
of estimates of the frequency of rare events. Ecology 86(5):1114-1123.
Efron B, Tibshirani R. 1993. An Introduction to the Bootstrap. New
York (NY): Chapman & Hall;
436 p.
Epperly SP, Braun J, Chester AJ, Cross FA, Merriner JV, Tester PA. 1995. Winter
distribution of sea turtles in the vicinity of Cape Hatteras and their
interactions with the summer flounder trawl fishery. Bull
Mar Sci 56(2):547-568.
Hardin J, Hilbe J. 2001. Generalized Linear Models and Extensions. College
Station (TX): Stata Press; 245 p.
Hastie TJ, Tibshirani RJ. 1990. Generalized Additive Models. New
York (NY): Chapman & Hall; 320 p.
Hin LY, Lau TK, Rogers MS, Chang AMZ. 1999. Dichotomization
of continuous measurements using generalized additive modelling – application
in predicting intrapartum caesarean delivery. Statist Med 18:1101-1110.
McCracken ML. 2004. Modeling a very rare event to estimate
sea turtle bycatch: lessons learned. US Dep Commer,
NOAA Tech Memo NMFS-PIFSC-3; 25 p.
McCullagh P, Nelder JA. 1983. Generalized Linear Models, 2nd
Edition. New York (NY): Chapman & Hall;
511 p.
Musick JA, Limpus CJ. 1997. Habitat utilization and migration
in juvenile sea turtles. In Lutz PL, Musick JA, eds. The
Biology of Sea Turtles. Boca Raton (FL): CRC Press; 137-163.
North Carolina Division of Marine Fisheries (NCDMF). 2004. Assessment
of North Carolina Commercial
Finfisheries, 2000-2003. Morehead City (NC): Division
of Marine Fisheries, Final Performance Report for Award Number NA 06 FI
0321 1-3, 27 p.
Northeast Fisheries Science Center (NEFSC). 1996. Report
of the 22nd Northeast Regional Stock Assessment Workshop (22nd SAW):
Public Review Workshop. Woods Hole (MA): National Marine Fisheries
Service. Northeast Fish Sci Cent Ref Doc 96-16; 45 p.
Rago PJ, Wigley SE, Fogarty MJ. 2005. NEFSC bycatch estimation
methodology: allocation, precision, and accuracy. Woods Hole (MA):
National Marine Fisheries Service. Northeast Fish Sci Cent Ref Doc 05-09; 44 p.
Shoop CR, Kenney RD. 1992. Seasonal distribution and abundances
of loggerhead and leatherback sea turtles in waters of the northeastern
United States. Herpetol Monogr 6:43-67.
Venables WN, Dichmont CM. 2004. GLMs, GAMs and GLMMs: an overview
of theory for applications in fisheries research. Fish Res 70(2-3):315-333.
Wigley S, Terceiro M, DeLong A, Sosebee K. 1998. Proration
of 1994-1996 USA commercial landings of Atlantic cod, haddock, and yellowtail
flounder to unit stock areas. Woods Hole (MA): National Marine Fisheries
Service. Northeast Fish Sci Cent Ref Doc 98-02; 32 p.
