NORTH PACIFIC RESEARCH BOARD PROJECT FINAL REPORT
Estimating movement rates of Pacific cod (Gadus macrocephalus) in the Bering Sea and the Gulf of
Alaska using mark-recapture methods.
NPRB Project 620 Final Report
Yunbing Shi 1, Donald R. Gunderson 1, Peter Munro 2, Joseph D. Urban 3
1
University of Washington, School of Aquatic & Fishery Sciences, 1122 NE Boat St., Box 355020,
Seattle, WA 98195. (206) 364-6508, ybs1688@yahoo.com
2
National Oceanic & Atmospheric Administration, National Marine Fisheries Service, Alaska Fisheries
Science Center, Resource Ecology & Fishery Management Div. Sand Point Way NE, Seattle, WA 98115
3
Alaska Department of Fish & Game, 211 Mission Road Kodiak, AK 99615-6399
October 2007
Abstract
Understanding Pacific cod movements and tempo-spatial distribution is critical to successful management
of Pacific cod stocks and protection of marine mammal populations. We compiled four Pacific cod
tagging datasets and attempted to quantitatively model cod movement in eastern Bering Sea and Gulf of
Alaska. Tag recovery indicates that Pacific cod exhibit great site fidelity with about 70% of the tags
recovered less than 50 miles from their release site. Nevertheless, some individuals undertook extensive
migrations of up to 675 miles.
We applied a Brownie model to tagging data to estimate Pacific cod survival, and exploitation rates.
Estimated annual survival rates of Pacific cod in the eastern Bering Sea ranged from 0.36176 to 0.5384,
exploitation rates from 0.1612 to 0.3224, instantaneous natural mortality rates from 0.4029 to 0.5033, and
instantaneous fishing mortality rates from 0.2162 to 0.5136.
Tag recovery rates by size group were used to quantify gear selectivity, and trawl, pot, and longline
selectivity curves each had a characteristic dome shape. Peak selection occurred at 55 to 70 cm for pot
gear, 55cm to 75 cm for trawls and 65 cm to 80 cm for longlines.
Tagging data were fit to a Von Bertalanffy growth model, and estimated growth parameters were in good
agreement with those from age determination.
The reliability of many of our estimates was compromised due to the opportunistic nature of tag releases.
We recommend that more controlled and well-designed tagging experiment be carried out in order to
quantitatively model Pacific cod movement and reliably estimate Pacific cod population parameters
Key Words: Pacific cod, tagging, statistical model, movement, survival, exploitation rate, growth,
selectivity, seasonal, mark-recapture
Citation: Shi, Y., D.R. Gunderson, P. Munro, and J.D. Urban. 2007. Estimating movement rates of
Pacific cod (Gadus macrocephalus) in the Bering Sea and the Gulf of Alaska using mark-recapture
methods. North Pacific Research Board Final Report 620, ??p
Table of Contents
Study Chronology
January 15, 2007. First progress report was submitted.
August 27, 2007. Second progress report was submitted.
September 30, 2007. Final report was submitted.
INTRODUCTION
Pacific cod, Gadus macrocephalus, is a transoceanic species, occurring at depths from the shoreline to
500 m extending from about 34° N latitude (Santa Monica Bay, California on North American coast and
south end of Korean Peninsula on Asian coast) to about 63° N (Bakkala, et al 1984, Zhang 1984). Pacific
cod are known to make seasonal long distance migrations in the eastern Bering Sea (Shimada & Kimura
1994).
Pacific cod is one of the most important species in the eastern Bering Sea, Gulf of Alaska, and adjacent
waters off Aleutian Islands. Pacific cod catches rank second among groundfish resources in Alaska
waters following walleye Pollock, Theragra chalcogramma. Fishery catch has steadily increased from
about 51,650 mt in 1980 to 206,130 mt in 1992, and was sustained at about 200,000 mt for the next five
years. The record catch was 240,590 mt in 1996. Since 1996, it declined. The most recent annual
catches have been about 170,000 mt. Recent resource survey results indicate a continued decline of
exploitable biomass (Witherell 2000).
One of the obstacles to accurate stock assessment of Pacific cod is stock delineation. Successful
management of exploited species requires the identification of self-recruiting populations, or stocks, as
differences in recruitment, growth or mortality may necessitate separate management and conservation
strategies. Pacific cod has been an important target fishery in U.S. waters since the mid-1980s, second
only to walleye Pollock (Theragra chalcogramma) in commercial landings, yet very little is known about
population subdivision within and between managed areas. In Alaskan waters two stocks are identified
for state and federal management purposes: the Gulf of Alaska (GOA) and Bering Sea/Aleutian Island
(BSAI) stocks. Genetic studies (Kathryn Cunningham, abstract of 16th SAFS Annual Graduate Student
Symposium, 2006) indicate that little differentiation exists within Alaska stocks or between Alaska and
Washington stocks.
In this study we analyzed four sets of Pacific cod mark-recapture data to depict exchange between large
ecosystems, and seasonal movement within these ecosystems. The first data set, presented by Shimada
and Kimura (1994), comes from tags that had been released as part of standardized trawl surveys
conducted by the Resource Assessment and Conservation Engineering (RACE) division at Alaska
Fisheries Science Center (AFSC). From now on it will be referred to as RACE I data set. The second data
set has resulted from tags that were released on an opportunistic basis as part of research cruises
conducted by the Alaska Department of Fish and Game (Urban, D., ADF&G, unpublished data). From
now on it will be referred to as the ADF&G data set. The third data set comes from tags released during
cruises for localized depletion studies conducted by the Fisheries Interaction Team (FIT) at AFSC. From
now on it will be referred to as the FIT data set. The fourth data set is from archival tags released on a
number research cruises carried out by AFSC RACE (Nichol and Chilton, 2006), and will be referred to
as the RACE II data set. All recaptures were from commercial fisheries.
OBJECTIVES
The original proposal of this study was to quantitatively model Pacific cod movement in eastern Bering
Sea. However, the data are too disjointed in time and place to allow estimation of movement rates among
regions of the Bering Sea or between EBS and GOA, due to the opportunistic nature of tag releases and
dependence on commercial fisheries for tag recoveries.
After studying the four sets of data, we present a summary of this study in this report, to accomplish
following goals:
1. Characterize Pacific cod movement between Eastern Bering Sea (EBS), Aleutian Islands (AI),
and Gulf of Alaska (GOA) and within EBS, AI, and GOA.
2. Estimate survival and exploitation rate when there is sufficient data available to fit a Brownie
Model.
3. Estimate von Bertalanffy growth parameters.
4. Summarize size specific recovery rate and discuss its use as an approximation for selectivity
curves.
MATERIALS AND METHODS
DATA
RACE I
The first (RACE I) data set was generated by NMFS during AFSC chartered fishing vessels engaged in
summer bottom trawl surveys off Alaska from 1982 through 1990. Pacific cod were tagged throughout
their eastern Bering Sea distribution. In addition, there were tag releases from cooperating Japanese,
Korean, and U.S. research vessels operating in the Aleutian Islands and Gulf of Alaska. Capture gear
included bottom trawl, pot, and hook-and-line. Two types of tag were used in this study: 3.5-inch anchor
tags and 8-inch lock-on spaghetti tags. The majority of releases (69%) were made with the lock-on
spaghetti tag (Shimada & Kimura, 1994).
Pacific cod were tagged across the entire size range available to the capture gears, although priority was
placed on the release of fish less than 55 cm. Most of the tags were released during summer months (June,
July, August, and September).
There were 12,396 tags released between 1982 and 1990. Of these, 375 tags were recovered and reported
by commercial fisheries between 1982 and 1992. Table 1 presents number of tags released by year and
area (NMFS statistical area), number of tags recovered and recovery rate (%) by release year and release
area.
ADF&G
The second set (ADF&G) of Pacific cod tagging data was provided by Alaska Department of Fish and
Game. ADF&G has been tagging Pacific cod since 1997. A total of 13,858 tags have been released,
mostly during the annual trawl survey conducted by the department. Most tags (10,334 out of 13,858 tags)
were released in state waters (<= 3 miles from shoreline). Tags have been released around Kodiak Island,
the south side of the Alaska Peninsula, and the eastern Aleutian Islands (Table 2). All tags were released
by experienced ADF&G staff. Released fish were observed from the vessel to assess their condition. If a
tagged fish is a “floater”, it is noted as such. Most tagged fish (12,164) were caught by survey trawls. A
small portion of the fish for tagging (1694) was captured by pots. Tags were recovered by commercial
fishermen using a variety of gear types. Over 800 tags have been recovered as of March 2007 (Table 2).
FIT
The third set (FIT) of Pacific cod tagging data was from AFSC Fisheries Interaction Team (FIT). FIT
scientists released a total of 6,871 tags. Most (6,393) of the tags were released directly from tagging table.
478 of these were released after being held for a mortality study or monitoring in a portable live tank or
fish hold supplied with continuously flowing fresh sea water (Table 3). All live specimens were captured
using scientific pots designed for Pacific cod research. There were 683 tagged fish in mortality
study/monitoring. Release date was recorded for 478 of these. It is assumed that those that did not have a
release date were dead at or before evaluation. Some of the specimens with release dates were
categorized as dead. Tags were pulled from dead specimens before the carcasses were discarded. Only
the tags released directly from the tagging table were used in this movement and survival analysis. As of
end of 2006, there were 2,487 tags recovered and reported from tags released directly. The average
recovery rate was 38.9%.
RACE II
The last data set (RACE II) was provided by the AFSC Resource Assessment and Conservation
Engineering Division (RACE). RACE scientists along with FIT scientists released a total of 634 archival
tags in the Gulf of Alaska and eastern Bering Sea between 2002 and 2005. There were 329 tags released
around Kodiak Islands and 305 in Unimak Pass waters. Live specimens were captured by pot (529) and
jig (105). As of end of 2006, there were 287 recoveries reported. The average recovery rate was 45.3%
(Table 4).
Tags reported without location information (statistical area or latitude and longitude) were not included in
movement analyses. However, those tags were included in tag recovery rate analyses. Tags recovered
and reported with size information were included in size specific recovery rate analysis, regardless of
availability of location information.
DATA ANALYSIS
MOVEMENT
The movement between strata can be modeled by an expanded Brownie Model (Brownie et al., 1993).
We proposed a model based on a Halibut movement model described in Anganuzzi et al. (1994):
M lt  Rlt
Riklt
I
K
 M lt  I K


L(mlkt | M lt , Piklt )   
  Piklt 
1  Piklt


i t k 1
l 1 t 1  Riklt  i t k 1
 

L
T
Where,
M lt = number of fish tagged and released in area l (l = 1,2,…,L) during time period t (t = 1,2,…,T);
Riklt = number of fish (tags) recovered in area k (k = 1,2,…,K) during time period i (t = 1,2,…, I)
from group M lt released in area l (l = 1,2,…,L) during time period t (t = 1,2,…,T);
mlki = the probability of movement of a fish being tagged and released in area l (l = 1,2,…,L) and
recovered in area k (k = 1,2,…,K) during time period i (i = 1,2,…, I);
Piklt = probability of a fish (tag) being recovered in area k (k = 1,2,…,K) during time period i (t =
1,2,…, I) from group M lt released in area l (l = 1,2,…,L) during time period t (t = 1,2,…,T);
i 1
Piklt   S j (1  U kj )mlkiU ki rki
j t
U ki = utilization rate in area k (k = 1,2,…,K) during time period i (i = 1,2,…, I), given a fish
survived natural causes to time i;
rki =
reporting rate in area k (k = 1,2,…,K) during time period i (i = 1,2,…, I), given a fish is
harvested;
Si =
probability of a fish surviving all sources of mortality during time period i (i = 1,2,…, I);
Rlt =
sum of the group M lt fish released in area l (l = 1,2,…,L) during time period t (t = 1,2,…,T)
and consequently recovered: Rlt 
I
K
 R
i t k 1
iklt
The parameter we wish to estimate is mlki , the probability of movement. The data that we have are
represented by M lt , and Riklt . There are three critical parameters for which we must either assume or
estimate values: U ki , the utilization rate by area and time period, rki , the reporting rate by area and time,
and Si , overall survival rate by time period. The last parameter, Si , can be estimated by fitting a Brownie
model to the mark-recapture data, which we will discuss in next section.
After diligently examining the four sets of tagging data, we concluded that due to lack of key input
information, such as area and time specific exploitation rates and reporting rates, it is not practical to fit
existing data sets to our proposed movement model. Instead, we applied the following quantitative
estimator to describe tagged fish movement between strata.
M ij 
Rij
I
R
i 1
ij
Where, Mij = movement rate of tagged fish from strata j to strata i.
Rij = number of tagged fish recovered in strata i, that were released in strata j.
This is a rough qualitative measure of fish migration between strata. However, Mij would be a good
indicator of movement rate between areas, under the following assumptions:
1. Tagged fish are fully mixed (intermingled) with the untagged population before tagged fish were
captured by fishery in both receiving system and releasing system.
2. Exploitation or utilization rates are in all areas at all times, i.e. there is no spatial or temporal
variation in exploitation rate;
3. Natural mortality is constant, i.e. there is no spatial or temporal variation in natural mortality;
4. Recovery and reporting rates are constant, i.e. there is no spatial or temporal variation in recovery
and reporting rates.
When these assumptions are violated, independent information concerning the assumptions is necessary
to overcome the assumption, in order to reliably model Pacific cod movement.
ESTIMATES OF SURVIVAL AND EXPLOITATION RATE WHEN THERE IS SUFFICIENT DATA AVAILABLE TO FIT
A BROWNIE MODEL.
The primary goal of the FIT tagging program was aimed at ascertaining localized short-term movement
during a before-and-after study designed to evaluate local depletion impact on Steller sea lion prey
availability. Nevertheless, the tag recovery information generated interest and sometimes anxiety among
fisheries professionals due to the high exploitation rate implied for eastern Bering Sea cod.
In responding to this concern, we used the same set of data to fit a mark-recapture model (Brownie Model
I) to estimate Pacific cod survival and exploitation rates in the eastern Bering Sea. We also estimated
instantaneous natural and fishing mortality.
Since the tagging studies were designed to qualitatively describe short-term localized movement, some of
the assumptions for the Brownie Model I were not met. A detailed discussion and suggestion for further
studies is presented.
MODEL DESCRIPTION
In this work, the Brownie Model I (Brownie, et al, 1985) for estimation of survival and exploitation rates,
and the basic fishery catch equation will be adapted to estimate Pacific cod natural and fishing mortality
rates. Software program MARK (Cooch & White, 2006) developed for the analysis of data from markrecapture studies will be used fitting the Brownie model with the FIT data set.
Brownie Model

L S j , tj | N t , Rtj

Nt


R
  tt  tt
 


R
,
N

R
t
t 1
 tj t

T
Rtj
j 1
J

 j 1  

S
1





 tj  i  

tt
tj  Si 
j t 1
j t 1 
i t
i t
 

J
Nt  Rt
 tj  (1  t )u j
(1)
(2)
Where:
Nt = Number of fish marked and released in year t;
Rtj = number of fish recovered in year j that were released in year t;
J
Rt .   Rtj , total number of tags recovered from release group (year) t.
j t
u j = exploitation rate in year j;
t = tagging induced mortality at the time of release in year t; t is estimated outside the model;
 = tag reporting rate, estimated outside model by comparing recovery rates of high reward tags,
archival tags and assumed to be constant.
S j = survival rate in year j including survival from natural and fishing mortality.
For simplicity, we assume that tagging induced mortality at release, t , is known. We also adjust the
number of tags released during each cruise by a factor of ( 1  t ) to estimate the effective releases, i.e.
Nˆ t  (1  t ) Nt . We also assume that the reporting rate is 100%. Equation 2 then becomes:
 tj  u j
and Equation 1 becomes:

L S j , u j | Nˆ t , Rtj



Nˆ t

  ut  Rtt

ˆ
t 1  Rtj , N t  Rt  


T
Rtj
j 1
J


 
 u j  Si  1  ut   u j  Si 

j t 1
j t 1 
i t
i t
 

J
j 1
Nˆ t  Rt
(3)
The FIT study had three years of tag release (T =3) and fours year of tag recovery data (J = 4). Therefore,
the likelihood Equation 3 can be re-written as:
L( S j , u j | Nˆ t , Rtj )


Nˆ 1
R
R
R
R
Nˆ  R

  u  11  S1u2  12  S1S 2u3  13  S1S 2 S3u4  14 1  u1  S1 (u2  S 2 (u3  S3u4 ))  1 1
 R , R , R , R , Nˆ  R  1
1 
 11 12 13 14 1
ˆ


N2
R
R
R
Nˆ  R

  u  22  S 2u3  23  S 2 S3u4  24 1  u2  S 2 (u3  S3u4 )  2 2
 R , R , R , Nˆ  R  2
2 
 22 23 24 2
ˆ


N3
R
R
Nˆ  R

  u  33  S3u4  34 1  u3  S3u4  3 3
 R , R , Nˆ  R  3
3 
 33 34 3
Where, Ri 
J
R
j i
tj
for t = 1, 2, 3; J = 4.
To obtain maximum likelihood estimates for u j and S j , We take the derivative of log[L(…)] with
respect to S j s and u j s, and solve the derivative equations (Brownie et al 1985) to obtain:
uˆ j 
Rt C j
Nˆ T
t j
1
1
1
1
Var (uˆ j )  (uˆ j ) 2  

 
 Rt  Nˆ t C j T j 
Sj 
Rt   T j  C j

Nˆ t  T j
 Nˆ t 1  1

 Rt 1  1
1
1
1
1
1
1
Var ( S j )  ( S j ) 2  



 
 Rt  Nˆ t Rt 1 Nˆ t 1 T j 1  Rt 1 T j 

 1
1
1
uˆ j S j 

  ,h  0

 R j Nˆ j T j 

 1

1 
Cov(uˆ j  h , S j )   S j uˆ j 1 

 ,h 1 .
ˆ

 R j1 N j 1 
0
,h 1



ASSUMPTIONS
In Brownie Model, it is assumed that both recovery rate and survival rate are year-specific, but
independent of the year of tagging and age of the animal tagged. Here we summarize the assumptions
pertaining to this study:
1. The tagged fish are representative of the population, i.e. the tagged fish are mixed thoroughly
with the untagged ones. Ideally, the mark-recapture study would be designed to let the
tagged fish disperse widely over the study areas before fishing starts, avoiding their being
subject to heavy fishing pressure immediately after releasing.
2. There is no tag loss. There are generally two types of tag loss. One is initial tag loss. When
initial tag loss occurs, the number of tagged fish released will be effectively reduced. The
second type of tag loss is chronic tag loss. When there is a chronic tag loss, mortality rate
estimates will be positively biased. That is, the estimated mortality rates will be higher than
the actual mortality rates.
3. Survival rates are not affected by tagging, i.e. there is no tagging induced mortality. Like tag
loss, there are two types of tagging induced mortality, the initial short-term mortality and
chronic mortality. When there is substantial initial short-term mortality, exploitation rate
estimates will be negatively biased, while survival estimates may be biased positively.
However, if the initial short term mortality is consistent among all release batches, the total
survival rate estimates will not be biased, fishing mortality estimates will be biased
negatively and natural mortality estimates will be positively biased. When there is chronic
mortality due to tagging, the survival estimates will be negatively biased and the mortality
estimates will be positively biased. The exploitation estimates should not be biased.
4.
The fate of each tagged fish is independent of the fate of other tagged fish. This assumption
is probably violated in almost all practical applications of mark-recapture models. Fish are
not independent entities in terms of survival, harvest, and other characteristics. Whether this
violation causes any biases needs further study. Pollock and Raveling (1982) conclude that
violation of this assumption does not cause bias, although it compromises the precision of
estimates.
5. The year of tag recovery is correctly reported and tabulated. Erroneous reporting or
tabulation of the year of tag recovery will cause bias in survival and recovery rate estimates
either negatively or positively depending on the error. If fishermen report tags from fish
caught in previous years, the survival estimates will be positively biased for the year tag was
recovered but not reported.
6. Recovery rates are homogenous within each year,
7. Natural mortality is time-specific, not age-specific, nor spatially specific
8. The exploitation rate is time-specific, not age-specific. This assumption may have been
violated when we extrapolate our estimates to the target population, especially when the
majority tagged fish were older fish.
AFSC FIT scientists tagged 6871 Pacific cod between April 2002 and November 2003 in Unimak pass
and its adjacent waters (Figure 1). Only a few fish were tagged in January and March 2003, and most
tags were opportunistically released in the Gulf of Alaska. Therefore, fish tagged and released in January
and March 2003 were excluded from this study. Fish used in the tag-induced mortality study probably
experienced different survival after release and were also excluded from this survival and exploitation
analysis. Releases carried out in November 2003 are treated as releases for 2004. All tags used in this
study (5870) were tagged and released during a study of localized fisheries impact on Pacific cod
abundance by NMFS scientists. All tags were recovered by commercial fishing fleets. Recovered tags
were returned to NMFS either via mail from fishermen or brought back by fisheries observers. To
encourage tag returns, a reward of a hat embroidered with a picture of a Pacific cod was sent to the
recipients who provided complete information on the Fish Tag Return Form. A total of 2312 usable tags
were reported by end of December 2005 (Table 5).
Catch Equation
For type II fishery, with fishing and natural mortality effecting fish survival concurrently, the exploitation
rate can be estimated using (Ricker, 1975):
uj 
Fj (1  e
Zj
Z j
)

Fj (1  S j )
 ln( S j )
Where, Sj is survival rate from all causes of mortality, customarily including natural and fishing mortality,
Sj  e
Z j
. Zj is total instantaneous mortality, Zj = Mj + Fj; Mj is instantaneous mortality due to natural
causes and Fj is instantaneous mortality due to fishing activities. From the catch equation, we derive:
Fj  u j Z j (1  e
Z j
)  u j ln( S j ) (1  S j )
F
F
F F
Var ( Fˆ j )  ( ) 2 Var ( S j )  ( ) 2Var (u j )  2
Cov(u j , S j )
S
u
S u
Where,
u j ln( S j )
F
u j


S S j (1  S j ) (1  S j ) 2
ln( S j )
F

u
(1  S j )
and,
M j  Z j  Fj   ln( S j ) u j ln(S j ) (1  S j )
M 2
M 2
M M
Var ( Mˆ j )  (
) Var ( S j )  (
) Var (u j )  2
Cov(u j , S j )
S
u
S u
Where,
u j ln( S j )
M 1
uj
 

S S j S j (1  S j ) (1  S j )2
ln( S j )
M

u (1  S j )
Cov( Mˆ j , Fˆ j )  Cov[m(u j , S j ), f (u j , S j )]
m(..) f (..)
m(..) f (..)
Cov(u j , u j ) 
Cov( S j , S j )
u
u
S
S
m(..) f (..)
m(..) f (..)

Cov(u j , S j ) 
Cov(u j , S j )
u
S
S
u
m(..) f (..)
m(..) f (..)

V (u j ) 
Var ( S j )
u
u
S
S
m(..) f (..)
m(..) f (..)

Cov(u j , S j ) 
Cov(u j , S j )
u
S
S
u

VON BERTALANFFY GROWTH PARAMETERS
All four sets of Pacific cod mark and recapture data contained length of tagged fish at release and at
recovery. Using length measurements at release and recovery, and days at liberty (i.e. number of days
between release and recovery) we fit the data to a von Bertalanffy growth curve to estimate Pacific cod
growth parameters. Based on von Bertalanffy equation, we have:

 

L2  L1  L  e K (t2 t0 )  e K (t1 t0 )   
Where, L1 = length at release, L2 = length at recovery, L∞ = maximum length, K = von Bertalanffy growth
rate, t1 = age at release (unknown), t2 = age at recovery (unknown), t0 = age at length 0,  = error. Let ∆t =
t2 – t1 (days at liberty or number of days between release and recovery) and ∆L = L2 – L1 (length
increment between release and recovery), we have:


Li   L  Li1  1  e  k ti   i ,
for i = 1, 2,3,…I (total number of specimen)
Using the Solver function within MS Excel to minimize
1  i 
I
2
, we obtained estimates of maximum
length (L∞) and growth rate (K). Only returns with length increment greater than 0 cm were included in
length and growth analyses.
SIZE SPECIFIC RECOVERY RATE AND APPROXIMATION OF SELECTIVITY CURVES
The validity of stock assessment has been often compromised due to lack of information concerning gear
selectivity and catchability. The need for direct estimates of selectivity outside of stock assessment
models such as Stock Synthesis II has been explicitly recognized in the NPRB Science Plan (p76), which
states “For example, routine stock assessments are questioned for some species owing to significant
uncertainty about gear selectivity and catchability. These include selectivity curves for Pacific cod that
imply a larger biomass of old/large fish than observed…” All tagged Pacific cod released had body
length measured at the time of tagging. The majority of Pacific cod tag recoveries were reported with
length measurements. Using the total number of tagged specimens released and recovered in a given size
group, we can estimate the recovery rates by size group. Myer & Hoenig (1997) applied a binomial
model and estimated gear selectivity of Atlantic cod (Gadus morhua) from multiple tagging experiments.
We scale the recovery rates by size by assuming that the maximum recovery rate equals one. We present
the scaled recovery rate by size as an approximation of gear selectivity, with the assumptions listed below.
1. Natural mortality is not size dependent, i.e. survival is constant over the size range observed in
tagging studies. Any size specific mortality will bias the selectivity estimate. For example, higher
natural mortality at older ages would reduce the number of older fish available to fishery, reduce
total number of tagged fish being recaptured, hence lower the estimated recovery rate. Therefore,
selectivity rate at older age would be negatively biased.
2. Tagging induced mortality is either negligible or size-independent. Like natural mortality, higher
tagging induced mortality will result in reduced number of tagged fish available for recovery, and
negatively bias estimates of selectivity rate.
3. Availability and spatial distribution are not size dependent. If Pacific cod distribution exhibits
size segregation and fishing effort distribution does not proportionally match cod distribution, the
estimated gear selectivity rate would be biased either positively or negatively, depending on
fishing intensity. However, a disparity of fish distribution and fishing effort distribution would
not bias the estimated fishery selectivity. [Note: There are two concepts of selectivity. One is
fishery selectivity and the other is fishing gear selectivity. Fishery selectivity can be achieved
through policy, regulations, and market, (such as area closures or market demand for large fish),
while gear selectivity can be achieved by altering fishing techniques and gear technology.]
RESULTS
MOVEMENT
We were unable to apply our proposed movement model to quantify Pacific cod movement, because all
data sets lacked the following information:
1. Lack of independent or direct estimates of exploitation rate on desired temporal or spatial scales.
There are catch statistics but no abundance estimates by strata and season. Therefore, we cannot
directly estimate the exploitation rate by strata or season.
2. Lack of independent estimates of tag reporting rate. Among all existing data sets, we can be
reasonably confident that the reporting rate for archival tags (RACE II) is near 100%. We can
also estimate the overall reporting rate for FIT spaghetti tags by comparing the recovery rate for
FIT tag returns with the recovery rate of RACE II (archival tags) tag returns. There are no data
available for independent estimates of either overall reporting rate or reporting rate by strata and
season in the RACE I and ADF&G data sets. None of the data sets could provide tag reporting
rate by strata and/or season, which is a required input data for the movement model.
3. Lack of tagging induced mortality estimates. Among the four sets of data, only the FIT study had
direct observations of tagging induced mortality. Many factors could affect the survival of a
tagged Pacific cod. Capture gear and culling criteria are the two most critical factors. Data
indicates that specimens captured by pot have much high recovery rates than those captured with
a trawl net. In ADF&G tagging experiments, cod captured with pots had a recovery rate of over
20% (21.2%), while cod captured with trawl had a recovery rate less than 4% (3.8%) (Figure 6).
A stringent culling practice also guarantees lower tagging-induced mortality. During the FIT
tagging experiments, more stringent culling was practiced during cruises FA200201 and
PS200302 than was practiced during Cruise AU200311. As a result the average tagging induced
mortality rate was an order of magnitude higher during cruise AU200311 (27.5%) than during
cruises FA200201 and PS200302 (1.2% and 2.7%). RACE II releases in the EBS were carried
out by the same scientists and crew members as those carried out FIT releases during cruises
FA200201 and PS200302. Therefore, it is probably safe to assume that the tagging induced
mortality is very low. No mortality studies or monitoring were implemented during RACE I and
ADF&G releases.
4. Lack of direct estimates of tag lose or tag retention. None of the data sets had information on tag
retention, such as double tagging experiments. However, we are quite comfortable in assuming
that the retention rate is 100% for archival tags (RACE II data set) and that it is very high for
lock-in type spaghetti tags used in the FIT and ADF&G studies. There were two types of
spaghetti tag (anchoring type and lock-in type) used in the RACE I study. Loss rates for a similar
type of tag used on Atka mackerel ranged from 5.3% to 27% (McDermott 2003).
Even though the existing data sets prevent us from quantitatively modeling Pacific cod movement, we can
still draw some qualitative conclusions regarding Pacific cod movement. Tagged fish showed great site
fidelity. All four sets of Pacific cod mark-recapture data showed that about 5% to 10% of tagged Pacific
cod moved from the Bering Sea to the Gulf of Alaska (Table 6). However, movement rates were less
consistent for tagged cod migrating from the GOA to BS (0% to 50%). The lower movement rate
occurred in ADF&G and RACE II data sets. Both of the data sets were collected from tags released
around Kodiak Island, which is relatively far away from any passages to the Bering Sea. The higher
movement rate (46.2%, FIT data set) was due to the fact that the tagged Pacific cod were released very
close to Unimak Pass and near the boundary between BS and GOA. In RACE I tagging studies, the
higher percentage of tags released in GOA and recovered in BS was due to the small sample size, since
only two fish were recovered (Table 6).
This site fidelity is also reflected on a much smaller scale. All data sets show that the majority (from 6688%) of tagged Pacific cod were recovered within the strata of release, except in two cases (Tables 7 & 8).
One of the exceptional cases was the FIT study. Tags released in NMFS area 610 were close to Unimak
Pass, and represents a boundary effect. The other case involves releases made on the EBS shelf, where
there were more recoveries (41.5%) made in Unimak Pass than in the area of release. There was also
significant portion (14.2%) of recoveries reported in the EBS slope area. This is probably due to a
disproportional distribution of fishing effect in different areas.
Using tag recovery information from tags recovered by the fishing industry to infer fish distribution
or/and movement is complicated by the fishing effort distribution. Fishing activities are dictated not only
by the centers (high density) of fish distribution, but also the location of processing plants. However, tag
recovery data showed a general pattern where a substantial proportion of tagged cod were recovered in
the area tagged and released (Tables 7 & 8). Of the four sets of data, tags released by FIT and RACE II
were on a major spawning ground and mostly during peak fishing season. Therefore, it is anticipated the
majority of recoveries will be in the area of release.
The data sets for the ADF&G and RACE I studies consist of tags released during survey cruises that
covered the Pacific cod distribution range in the Bering Sea and Gulf of Alaska. From these two data sets,
we observed a similar pattern of site fidelity, especially in the ADF&G data (Tables 7 & 8). We also
observe that tags released in the area of reduced fishing activities (Shelf) tend to be recovered
disproportionately in areas with heavier fishing activities (Unimak Pass). In the RACE I data set, we
observed that there were a relatively large number of recoveries from areas other than the area of release.
Tags released in NMFS statistical areas on the Eastern Bering Sea Shelf (Shelf) were more likely to be
recovered in Unimak Pass (U-Pass) than in the area of release (Tables 7 & 8).
On the other hand, our tagging data showed that Pacific cod do make transoceanic migrations. There
were two reported recoveries of AFSC FIT tags from Russia. Figure 1 depicts migration by one cod
tagged and released off Unimak Island, and recaptured by Russian fishermen in the Gulf of Anadyr. Plots
of release and recovery location showed that some of the tagged fish made substantial movement away
from release sites within the eastern Bering Sea (Figure 1). Due to a new regulation concerning graphical
presentation of Observer data, about 20% of the tags were left out of Figure 1, because less than 3 tags
were recovered in a given ADF&G statistical area. Figure 2 shows that the majority of the tagged cod
were captured within 100 nm of their release site. About 96% of the recoveries were within 100 nm for
both ADF&G and RACE II tags, 84% for FIT released tags, and about 62% for the RACE I data. There
appears to be some effect of fishing effort distribution on the tag recovery pattern. During the FIT,
ADF&G and RACE II studies, tags were released mainly on major fishing grounds, some during peak
fishing season.
During the RACE I study, tags were released over the entire geographical distribution of Pacific cod in
the Bering Sea during summer months, from June through September. Some of tagged cod were released
in the Shelf area, where there is typically very limited fishing activity. For those cod to be caught, they
need to migrate a substantial distance to where a fishery exists. As a result, we observed a relatively large
proportion of tags recovered more than 100 nm away from their release location (Figure 2). There is no
apparent correlation between minimum distance traveled (number of nautical miles between release and
recovery locations) and number of days at liberty (number of days between release and recovery) (Figure
3).
Release location and time likely effected recovery timing (days at liberty) and location (minimum
distance from release location). Tags released in summer months (ADF&G and RACE I) had more days
at liberty (both mean and median) than tags released in fall or winter (FIT, RACE II) (Table 10). Tags
released in the Gulf of Alaska (ADF&G and RACE II-G) were recovered closer to the release site than
those released in the Bering Sea (FIT, RACE I and RACE II-B) (Table 9). Most releases in the Gulf of
Alaska were inside state waters (ADF&G and RACE II-G), while most releases in the Bering Sea were in
federal waters (FIT, RACE I, and RACE II-B). Releases which covered the entire cod geographical
distribution (RACE I) had more days at liberty and longer distances between release and recovery
locations (Table 9).
For tags released in waters off Unimak Island, it appears that the median minimum distance migrated was
almost the same for releases made in November and February. However, the median days at liberty are
substantially different (Table 11). Releases made in mid-spring (April) had both longer minimum
distances moved and more days at liberty than those released later in fall and winter. Figure 4 shows that
the empirical distributions of minimum distance traveled are almost identical (up to the 82% percentile).
This similarity in the distribution of distance traveled indicates that majority of cod tagged in November
stayed at or around the Unimak spawning ground from later fall through the next spring. The
dissimilarity in both distance traveled and days at liberty between April releases and November-February
releases may indicate that tagged cod left the Unimak spawning ground soon after late March or early
April (Table 11, Figure 4).
ESTIMATES OF SURVIVAL AND EXPLOITATION RATE WHEN THERE IS SUFFICIENT DATA AVAILABLE TO FIT
A BROWNIE MODEL.
Tagging induced mortality
During FIT tagging experiments, AFSC scientists carried out a series of tagging induced mortality studies.
These studies monitored survival of tagged fish, with no control group (untagged) of fish being monitored
simultaneously. However, if we assume that the natural mortality of Pacific cod over a time period of 1
day to a week is negligible, then the observed mortality of those tagged fish held for monitoring could be
a robust approximation of tagging induced mortality. Table 12 shows the results of tagging induced
mortality monitoring studies during the three tagging cruises that will be included in survival and
exploitation analysis. For Cruise FA200201, the weighted mean tagging-induced mortality of 1.2% is
used.
Reporting rate
Reporting rate was computed by direct comparison of recovery rate of regular (spaghetti, with hat reward )
tags with that of high reward (archival, $200.00/tag returned) tags. During two of three FIT tagging
release cruises, the AFSC scientists also released high reward (archival) tags, which are included in the
RACE II data set. We assume that the reporting rate of high reward tags is 100%. The FIT data set
indicates that the FIT reporting rate is as high as the reporting rate of archival tags (Table 13). Therefore,
in this analysis, a reporting rate of 100% is assumed.
Survival and exploitation rate
The estimated annual survival rate of Pacific cod ranged from 0.3617 to 0.5384 and exploitation rate
ranged from 0.1612 to 0.3224 (Table 14). Model-predicted survival from 2002 to 2003 (0.4882 to 0.5879)
appears to be significantly higher than that from 2003 to 2004 (0.3091 to 0.4179). The higher apparent
survival from 2002 to 2003 probably resulted from later releases of tagged cod in 2002 (April, 2002).
Therefore, the model predicted survival rate is for the period from late April through the end of 2002,
rather than an estimate of annual survival rate.
Model-predicted exploitation rate is highest in 2003 (0.3224), and lowest in 2002 (0.1612), with 2004 in
the middle (0.2587). The predicted 95% confidence limits for exploitation rates during these three years
do not overlap (Table 14). Therefore, the model predicted exploitation rate appears to be statistically
different among the three years.
It appears that Brownie model is a robust model for predicting survival and exploitation rate. There is a
relatively low correlation between predicted survival and exploitation rate, ranging from 8% to 22%
(Table 15). Nevertheless, the model was unable to predict the exploitation rate in 2005 (Tables 14 & 15).
Instantaneous natural and fishing mortality estimates
The estimate of instantaneous natural mortality in 2002 is 0.4029 (SE = 0.0387), slightly lower than that
of 2003 (0.5033 with SE = 0.0754). Based on the point estimates and their standard errors, the estimated
the natural mortality rates are not statistically different.
The estimate of instantaneous fishing mortality in 2002 is 0.2162 (SE = 0.0122), less than half that of
2003 (0.5136 with SE = 0.0200). We believe that the fishing mortality in 2002 was significantly
negatively biased, because tagged cod released in 2002 were not exposed to the winter cod fishing season.
On the other hand, we think that the fishing mortality of 2003 was positively biased due to their location
and time of release.
There appears to be substantial correlation between estimates of natural and fishing mortality rate for each
year (Table 16). A correlation of coefficient of 33.1% (2002) is moderate, while 78.0% (2003) is rather
high, making the estimates of natural and fishing mortality rate less reliable.
Goodness of fit
The observed number of tags recovered and their expected values of number of tags recovered are
presented in Table 17. A chi-square goodness of fit test indicates that the data fit the Brownie Model very
well (  82 = 2.04, p = 0.98). We suspect that estimates of survival rate in 2004 and exploitation rate in
2005 are the least reliable. If we only consider the observed and predicted number of tags recovery in
2002 through 2004, the chi-square value is 0.77 with 5 degrees of freedom and still show same level of
statistical significance (  52 = 0.77, p = 0.98).
ESTIMATE VON BERTALANFFY GROWTH PARAMETERS
The estimates of Pacific cod maximum body length (L∞) ranged from 94.5 cm to 134.7 cm and estimates
for K ranged from 0.108 to 0.260 (Table 18). It appears that L∞ for Pacific cod in the eastern Bering Sea
(125.5 to 134.7 cm) is larger that in the Gulf of Alaska (94.5 to 112.7 cm). There does not appear to be
any obvious difference in K between cod of eastern Bering Sea (0.108 to 0.135) and that of Gulf of
Alaska (0.122 to 0.260) (Table 18, Figure 7).
SIZE SPECIFIC RECOVERY RATE AND APPROXIMATION OF SELECTIVITY CURVES
Recovery rates by size group show a dome shaped curve with a peak at around 70 cm for FIT data.
Recovery rates by size group for RACE I and ADF&G data are quite flat between 50 cm and 80 cm
(Figure 8). The RACE II data set does not have sufficient releases by size group, and is not analyzed for
recovery rates by size group.
After scaling or standardizing the recovery rate curve so that the maximum for each recovery curve equals
100%, we find that the standardized recovery curves are very close to a symmetrical dome shape for the
FIT data, while the recovery curves for RACE I and ADF&G data showed a slightly negatively skewed
dome shape (Figure 9). We believe that these standardized recovery curves could be a reasonable
approximation of the overall selectivity curve for the fisheries.
For the FIT data set, we have a large number of tag recoveries within each length group, by recovery
fishing gear. The results indicate that longline and trawl fisheries recovered almost equal numbers of tags,
while the pot fishery recovered a few less (Figure 10). The trends were similar when we considered only
those recoveries with days at liberty less than a year (Figure 11). If we assume the standardized recovery
curves to be an approximation of true selectivity curves, we can conclude that the selectivity curves for
pots and trawls conform to a symmetrical dome shape, and that longlines tend to select the largest cod
(Figures 12 & 13).
Discussion
MOVEMENT
The four original data sets are too severely disjointed, either in temporally or geographically, to allow
estimation of movement rates among regions of the Bering Sea or between the Gulf of Alaska and the
eastern Berng Sea. No subsets could be identified that permitted the model (Hilborn, 1990; Anganuzzi et
al, 1994) to be specified without irresolvable overparameterization. In order to apply our proposed
movement model to quantify Pacific cod movement, we need to have independent estimates of
exploitation rate and reporting rate by release batch, recovery area and period. In the movement model
the exploitation, reporting, and movement rates are confounded. Without independent estimates of
exploitation or reporting rates, the model will not be able to reliably estimate the movement rates. There
are catch statistics but no abundance estimates by strata and season. Therefore, we cannot directly
estimate exploitation rate by strata or season using a stock assessment program. However, fisheries
independent abundance survey could obtain a snapshot of fish abundance or index of abundance by strata.
We also need direct estimates of tagging induced mortality and tag loss rate by release batch or area.
There are two types of tagging induced mortality, i.e. acute and chronic. While acute tagging induced
mortality effectively reduces number of tagged fish available for recovery, the chronic tagging related
mortality would inflate model estimated natural mortality or negatively bias survival rate estimated by the
model. The tag-loss rate affects model estimates in the same manner as tagging induced mortality. There
are also acute and chronic components in tag loss. Data needed to obtain such independent estimates are
not available or are incomplete.
In order to obtain independent estimates of exploitation, reporting, tagging induced mortality and tag loss
rates, we propose a mark-recapture experiment to estimate movement rates. The experiment includes a
joint tag release and abundance survey cruise, followed by a fishery independent tag recovery and
abundance survey cruise. Included in the experimental design are mechanisms to ensure mixing of tagged
fish in the population, coverage of all geographic strata, estimation of ancillary parameters (in particular,
the exploitation rate), and means of defraying costs through directed research catches. The movement
rate estimation model would be simplified using the data from such an experimental design, yet still
remain close to being overparameterized. The assumption of a single, straight-line movement between
mark and recapture remains but the experiment is designed for a short enough time period to allow this
assumption to be valid. Within the overarching experiment, there will be several sub-experiments.
Before we discuss in details of each sub-experiment, we present a likelihood model based on a Halibut
movement model (Skalski, FISH 558 lecture notes).
I
JT
i t
j 1
L( )    lt   Pijlt 
L
T
l 1 t 1
Where,
xijlt
1   P 


I
JT
i t
j 1
Rlt  rlt
ijlt
l = 1, 2, 3, …, L, release strata.
t = 1, 2, 3, …, T, release time. In our proposed experiment, T = 1.
 lt = multinomial coefficient for release Rlt.
i = 1, 2, 3, …, I, recovery strata.
j = 1, 2, 3, …, JT, recovery time. In our proposed experiment, JT = 1.
Rlt = number of tags released in stratum l at time t.
rlt = total number of tags recovered from releases Rlt.
xljtl = number of tags recovered from release Rlt in stratum i at time j.
Pijlt
m S
( j 1)
li
U tij  , combined probability of movement rate from stratum l to i (mli),
reporting rate  = Pr(tag reported|harvested), and survival rate (S) assumed to be constant over a
short time period, utilization rate (Utij). Utij is Pr(harvested in time period j|escaped exploitation
from release time t (t = 1, 2, 3,…, T) to recovery time j (j = 1, 2, 3, …, Jt), i.e.
j 1
U tij  Vtij  (1  Vtig ) , Since in our proposed experiment T = 1 and JT = 1, U i  Vi . Vi is
g 1
exploitation rate at stratum i, Vi  Ci Nˆ i . Ci is total catch in stratum i and Nˆ i is population or
abundance in stratum i and is estimated from survey CPUE and stock assessment model
estimated overall abundance in entire eastern Bering Sea.
Sub-experiment 1: Direct estimate of exploitation rate by strata.
In this sub-experiment, we will carry out two cruises. The first cruise will be dedicated to releasing tags
over the entire geographical distribution of Pacific cod in the eastern Bering Sea in combination with an
abundance index survey in November. The second cruise will be in late March or early April and be
dedicated to tag recovery over the entire eastern Bering Sea, with disproportionally more effort allocated
to where no commercial fishery is present. As with the first cruise, we all also carry out an abundance
index survey. We will get estimates of average catch per unit effort (or area) (CPUE) by cruise and
stratum. Then we have:
 CPUE i   Ai 
Nˆ i  N 
 
 CPUE   A 
Where, N = total abundance of Pacific cod in entire eastern Bering Sea from stock assessment.
I
CPUE i = average CPUE of stratum i. CPUE  
i 1
in eastern Bering Sea, A 
Ai  CPUE i
= overall average CPUE of all strata
A
I
A
i 1
i
= area of stratum i and A = total area of all strata in eastern Bering Sea.
Hence, we can estimate exploitation rates by strata.
Sub-experiment 2: Direct estimate of reporting rate by strata
During the tag release cruise in November, we propose to release a small number of high reward tags in
each stratum. The number of high reward tags shall be proportional to number of regular tags released in
each stratum. During tag recovery cruise, we shall seed tags in catches and derive direct estimate of tag
reporting rate.
Sub-experiment 3: Direct observation of acute tagging induced mortality
During the tag release cruise, we will systematically hold tagged fish in a live tank for at least 24 hours to
observed tagged fish survival rate, using a consistent culling criteria. We actually do not need a control
sample (holding untagged fish). The main reason that no untagged fish are needed is that our goal is to
estimate tagging induced mortality, which includes mortality due to tagging, barotrauma, and handling
stress. Pacific cod mortality due to natural causes probably negligible over a few days.
Sub-experiment 4: Direct estimate of tag retention rate
Tagged fish held in live tanks for tagging induced mortality observation can also be used for acute tag
loss observation.
We will double tag a sufficient number of fish in order to directly estimate chronic tag losses (Gulland
(1963). Since funding and labor resources are limiting factor here, we will probably have to release as
many tags as possible whether they are single or double tagged.
SURVIVAL AND EXPLOITATION RATE
The estimated survival rate of Pacific cod varied from 0.3617 to 0.5384 and exploitation rate varied from
0.1612 to 0.3224 (Table 14). Model-predicted survival from 2002 to 2003 (0.4882 to 0.5879) appears
significantly higher than that from 2003 to 2004 (0.3091 to 0.4179). The higher apparent survival from
2002 to 2003 probably resulted from later releases of tagged cod in 2002 (April, 2002). Therefore, the
model predicted survival rate is for the period from late April through the end of 2002, rather than an
estimate of annual survival rate.
Model-predicted exploitation rate is highest in 2003 (0.3224), and lowest in 2002 (0.1612), with 2004 in
the middle (0.2587). The predicted 95% confidence limits for exploitation rates during these three years
do not overlap (Table 14). Hence, it appears that the model-predicted exploitation rates are statistically
different. However, this difference may actually be due to the timing of tag releases. The lower
exploitation rate for 2002 probably resulted from later releases (April 2002). The model assumes that the
tag releases were carried out at the same time and immediately before the fishing season each year.
Nevertheless, the tagged cod in 2002 were not exposed to the A fishing season during winter 2002
(January to March). Historically the A season landings comprise almost 50% of annual landings in the
Eastern Bering Sea. Therefore, the exploitation rate estimate for 2002 has substantially underestimated
the annual exploitation rate and instantaneous fishing mortality. The 2003 estimate may have
overestimated the real exploitation rate, because in 2003 tags were released during peak A fishing season
and the release location was a major spawning ground, cod alley. Cod alley is a major winter cod trawl
fishing ground, and cod released in February 2003 may have suffered a disproportionately high fishing
pressure. The model-predicted exploitation rate of cod in 2004 is probably the least biased. The tagged
cod were released in November 2003, which is about two months before the winter cod fishing season.
During these two months, the cod fishery in the eastern Bering Sea was insignificant. Therefore, the
tagged cod had sufficient time to mix with untagged cod before the fishing season. Due to the small
number of tags released and substantially high tagging-induced mortality, the estimate has a relatively
large standard error (Table 14).
To minimize the mixing and fishing effect on model-predicted population parameters, we suggest a markrecapture experiment to estimate survival and exploitation rates. The experiment should consist of at
lease three (years) releases. Each release should be carried out in November with equal number of tags
released. If the reporting rate and survival rate (from tagging) are maintained at the current level, 2000
tags should be sufficient. As with the mark –recapture experiment for modeling Pacific cod movement,
the experiment should include consistent culling practices, and on-deck live tank monitoring of tagging
survival. If resources permit, a small number of double-tagged fish should be released in order to
estimate tag retention rate.
The estimate of instantaneous natural mortality in 2002 is 0.4029 (SE = 0.0387), slightly lower than that
of 2003 (0.5033 with SE = 0.0754). Based on the point estimates and their standard errors, the estimated
natural mortality rates are not statistically different. On the other hand, the estimate of instantaneous
fishing mortality in 2002 is 0.2162 (SE = 0.0122), less than half that of 2003 (0.5136 with SE = 0.0200).
We believe that the fishing mortality in 2002 was significantly negatively biased, because tagged cod
released in 2002 were not exposed to the winter cod fishing season. We also think that the fishing
mortality of 2003 was positively biased due to their location (major trawl fishery fishing ground) and time
(peak fishing season) of release.
SIZE SPECIFIC RECOVERY RATE AND APPROXIMATION OF SELECTIVITY CURVE
Recovery rates by size group show a dome shape curve with a peak at around 70 cm for FIT data. After
scaling the recovery rate curve so that the maximum for each recovery curve equals 100%, these
standardized recovery curves could be a reasonable approximation of the overall selectivity curve for the
fisheries. However, this approximation was based on a suite of implied assumptions, i.e. size independent
natural mortality, size independent tagging related mortality, size independent availability and spatial
distribution, and size independent reporting rate.
The uncertainty related to some of the assumptions, such as size independent natural mortality, can be
addressed through experimental design. If we release sufficient number of tags in each size (length)
group, we can fit a joint Brownie model for each size group and predict survival and exploitation rates by
size group.
Conclusion and Recommendation
From this Pacific cod tagging data analysis, we conclude that tagging experiments are critical to
understanding Pacific cod biology and behavior as well as Pacific cod fishery. With proper study design,
one can model Pacific cod movement, survival and exploitation rate. With careful design, one also can
use tagging analysis to estimate fishery selectivity and/or fishing gear selectivity curves. A tagging study
for estimating survival could also be implemented as a long term population monitoring program. Such a
monitoring program would also accumulate a time series on cod survival. When it is executed with
archival tags, it is possible to collect tempo-spatial environmental data at the same time, which can be
applied to directly monitor the population impact of oceanographic and climate changes in the Bering Sea
(decrease in sea ice, increase in water temperature, etc.).
Therefore, we recommend following studies:
1. A mark-recapture experiment to estimate movement rates. The experiment includes a joint tag
release and abundance survey cruise followed by a fishery-independent tag recovery and
abundance survey cruise. If this experiment is successful, we further recommend multi-seasonal
release and recovery cruises to ascertain seasonal migration patterns.
2. A mark-recapture study to estimate natural and fishing mortality rates. The experimental design
should utilize at least three releases, one in each year before the major fishing season begins
(preferably in November before the winter cod fishery opening). Ideally, this mark-recapture
study would become a multiannual stock and oceanographic monitoring program.
3. Release tagged fish by size groups, in proportion to their population sizes so that the tag return
data can be use to estimate size specific survival and selectivity.
Publications
Shi, Y.B., P. Munro, D.R. Gunderson. (in prep.) Estimating Movement, survival and exploitation rates of
Pacific cod Gadus macrocephalus in the eastern Bering Sea and the Gulf of Alaska using mark-recapture
methods. NOAA Processed Report
Outreach
Dr. Libby Logerwell gave a talk at the Lowell Wakefield symposium in fall 2006 on "cod spawning,
movement and effects of commercial fishing".
Yunbing Shi gave a talk at Pacific cod workshop in June 2007 on “Pacific cod movement and survival”.
We are continuing sending out tag rewards to fishermen who report and send recovered tags to us.
Mr. Peter Munro met with longline fishery representatives in September 2007 to discuss cooperative
research opportunities.
Acknowledgements
We would like to thank Liz Conners and Sandi Neidetcher for their help with reward processing and data
entry. We would to thank all fishermen and observers for reporting and returning tags. We also would
like to thank NPRB for funding this project.
Table 1. Number of tags released by AFSC RACE summarized by release year and NMFS statistical area, number of tags recovered and recovery
rate (%) by release year and release area (Shimada & Kimura, 1994).
Release Area
508
509
512
513
514
516
517
518
519
521
524
541
542
543
610
620
630
Total
Number of tags released
1982
1983
1984
1985
1986
1987
1988
1989
1990
Total
141
38
141
23
348
164
492
49
47
116
228
1,357
26
55
188
199
135
63
15
15
615
116
195
40
44
22
417
20
105
251
439
102
23
8
8
956
322
241
69
37
20
744
88
5
247
537
40
130
30
21
65
379
1,440
233
492
784
2,165
143
499
36
367
248
27
27
5
1,352
45
6
34
95
101
1
29
5
316
327
23
6
12
22
6
34
1,971
1,735
36 1,714
64 1,198
4,561
696
198
290
33
100 12,396
425
21
1,133
698
316
1,483
1,144
316
Release Year
Number of tags recovered
1982
1983
1984
1985
1986
1987
1988
1989
1990
Total
10
5
6
6
1
14
1
6
7
10
2
4
2
8
14
12
6
10
3
3
1
3
8
1
3
1
74
14
17
2
4
11
36
8
41
22
9
1
2
23
10
28
25
11
19
13
0
0
0
0
2
96
39
68
45
97
20
3
7
0
375
--4.4%
0.0%
5.9%
9.5%
5.0%
0.0%
3.4%
0.0%
6.0%
--1.8%
0.0%
--0.6%
--------0.9%
--0.0%
0.0%
--0.0%
--------0.0%
--------0.0%
--------0.0%
------0.0%
----------0.0%
----0.0%
0.0%
----------0.0%
----2.8%
1.6%
----------2.0%
4.9%
2.2%
4.0%
3.8%
2.1%
2.9%
1.5%
2.4%
0.0%
3.0%
2
2
9
5
6
1
1
7
1
11
105
81
Recovery rate (%)
1982
1983
1984
1985
1986
1987
1988
1989
1990
Total
----13.2%
4.3%
--0.0%
--0.0%
--4.8%
7.1%
--1.7%
0.6%
2.8%
2.0%
0.0%
3.4%
--2.7%
----3.7%
5.0%
1.5%
6.3%
0.0%
--0.0%
3.7%
----1.7%
--4.1%
0.0%
0.0%
0.0%
--2.4%
--10.9% 3.4%
0.0%
--20.0%
0.0% 1.9%
--5.6% 4.1% 2.5%
2.7% 4.3% 2.3%
0.0% 0.0% 3.3%
8.7% 0.0% 0.0%
0.0%
--3.1%
0.0%
----2.9% 3.4% 2.9%
1.2%
1.5%
--------------1.4%
5.1%
6.0%
----3.5%
--------4.8%
--5.6%
8.2%
0.0%
6.0%
3.6%
3.7%
0.0%
0.0%
6.0%
Table 2. Number of tags released by ADF&G summarized by year and NMFS statistical area, number of
tags recovered and recovery rate (%) by release year and release area (D. Urban).
Release Area
512
518
519
610
620
630
Total
Number of tags released
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
Total
2
2
30
62
130
125
35
27
71
60
52
154
56
386
466
451
569
471
355
708
330
363
129
188
3,842
49
325
286
264
277
412
276
231
36
159
2,156
347
1,034
445
1,508
544
912
720
746
271
336
6,527
862
1,810
1,460
2,430
1,176
2,032
1,432
1,429
436
791
13,858
19
100
24
290
15
34
14
17
14
5
532
26
134
82
329
33
90
33
49
14
12
802
Release Year
Number of tags recovered
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
Total
0
1
8
10
5
1
2
4
10
2
23
7
11
19
11
12
35
10
13
1
119
23
28
15
6
21
6
15
4
118
Recovery rate (%)
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
Total
--------------0.0%
0.0%
--0.0%
----3.3%
12.9%
----2.9%
0.0%
0.0%
--6.5%
----7.7%
4.0%
----2.8%
6.7%
6.7%
--6.0%
1.5%
2.4%
3.3%
2.3%
3.4%
4.9%
3.0%
3.6%
3.6%
0.8%
3.1%
0.0%
7.1%
9.8%
5.7%
2.2%
5.1%
2.2%
6.5%
6.5%
11.1%
5.5%
5.5%
9.7%
5.4%
19.2%
2.8%
3.7%
1.9%
2.3%
2.3%
1.8%
8.2%
3.0%
7.4%
5.6%
13.5%
2.8%
4.4%
2.3%
3.4%
3.4%
2.8%
5.8%
Table 3. Number of tags released by AFSC FIT summarized by release month and NMFS statistical area, number of tags recovered and recovery
rate (%) by release month and release area. For mortality study fish, only those alive at end of each study were released.
Release Area
Regular Release
509
517
519
Mortality Study Fish Released
610
Total
509
517
519
610
Total
Release Year and Month
Number of tags released
2002-04
2003-01
2003-02
2003-03
2003-11
Total
112
1,365
1,570
104
882
77
314
1,156
105
1,477
708
3,264
1,233
419
1,759
418
3,403
105
708
6,393
89
41
2
97
97
76
16
35
216
75
31
147
30
9
16
18
130
2
248
32
66
478
Number of tags recovered
2002-04
2003-01
2003-02
2003-03
2003-11
Total
47
571
617
25
399
35
68
523
25
618
177
1,218
558
93
699
93
1,493
25
177
2,487
2
26
26
28
8
4
70
30
5
5
44
7
39
2
84
13
9
147
Recovery rate (%)
2002-04
2003-01
2003-02
2003-03
2003-11
Total
42.0%
--41.8%
----41.8%
39.3%
24.0%
45.2%
--25.0%
37.3%
45.5%
--45.2%
----45.3%
--21.7%
--23.8%
--22.2%
39.7%
22.2%
43.9%
23.8%
25.0%
38.9%
----26.8%
----26.8%
33.7%
--36.8%
50.0%
11.4%
32.4%
22.0%
--40.0%
--16.1%
29.9%
--100.0%
--31.3%
--38.9%
30.0%
100.0%
33.9%
40.6%
13.6%
30.8%
Table 4. Number of tags released by AFSC RACE summarized by release month and NMFS statistical
area, number of tags recovered and recovery rate (%) by release month and release area (D. Nichol).
Release Area
509
517
519
630
Total
Release Year and Month
Number of tags released
2001-10
2001-11
2002-04
2002-05
2003-01
2003-02
2005-01
Total
109
115
107
73
89
105
10
16
10
117
99
89
329
109
115
269
105
10
16
10
634
Number of tags recovered
2001-10
2001-11
2002-04
2002-05
2003-01
2003-02
2005-01
Total
70
82
28
33
40
173
70
82
101
21
3
6
4
287
----44.9%
--------44.9%
64.2%
71.3%
--20.0%
------52.6%
64.2%
71.3%
37.5%
20.0%
30.0%
37.5%
40.0%
45.3%
40
21
3
6
4
32
42
Recovery rate (%)
2001-10
2001-11
2002-04
2002-05
2003-01
2003-02
2005-01
Total
----26.2%
------40.0%
27.4%
----45.2%
--30.0%
37.5%
--42.4%
Table 5. Number of Pacific cod tagged, released by cruise and recovered by year in the waters adjacent to
Unimak Island during 2002 and 2003. Tags used in mortality experiments are excluded in this analysis
because those fish may experience different after release survival.
Time
Released
Number Released
Nt
Apr. 2002
1758
Feb. 2003
3403
Nov. 2003
709
Total (Cj)
Tj
( Nˆ t )
(1737)
(3311)
( 513)
2002
280
----280
691
Number Recovered, Rtj
2003
2004
2005
305
83
23
1064
319
72
--128
38
1369
530
133
1866
663
133
Total (Rt.)
691
1455
166
2312
---
Table 6. Number of tags released and recovered by areas (BS, AI, or GOA) and percentage of recoveries from areas outside of area of releases.
AFSC RACE Pacific cod tagging (1982 - 1992) data summary (Shimada & Kimura, 1994)
Release
Area
Number
BS
9,313
AI
2,943
GOA
140
Total
12,396
Number of Tags Recovered
BS
GOA
AI
Total
328
29
2
359
2
11
13
1
1
2
331
30
13
374
Recovery
Rate
3.85%
0.44%
1.43%
3.02%
Recvoery by Area (%)
BS
GOA
AI
91.36%
8.08%
0.56%
15.38%
0.00%
84.62%
50.00%
50.00%
0.00%
-------
ADFG Pacific cod tagging data summary as end of February 2007 (for releases through 2005)
Release
Area
Number
BS
542
GOA
12,551
Total
13,093
Number of Tags Recovered
BS
GOA
Unknown
Total
25
3
3
31
6
662
91
759
31
665
94
790
Recovery
Rate
5.72%
6.05%
6.03%
Recvoery by Area (%)
BS
GOA
Unknown
80.65%
9.68%
9.68%
0.79%
87.22%
11.99%
-------
AFSC FIT Pacific cod tagging data summary at end of 2006
Release
Area
Number
BS
5,975
GOA
419
Total
6,394
Number of Tags Recovered
BS
GOA
Unknown
Total
2,218
132
47
2,397
43
45
5
93
2,261
177
52
2,490
Recovery
Rate
40.12%
22.20%
38.94%
Recvoery by Area (%)
BS
GOA
Unknown
92.53%
5.51%
1.96%
46.24%
48.39%
5.38%
-------
AFSC RACE Pacific cod tagging (archival tag) data summary at end of 2006
Release
Area
Number
BS
305
GOA
329
Total
634
Number of Tags Recovered
BS
GOA
Unknown
Total
95
8
11
114
152
21
173
95
160
32
287
Recovery
Rate
37.38%
52.58%
45.27%
Recvoery by Area (%)
BS
GOA
Unknown
83.33%
7.02%
9.65%
0.00%
87.86%
12.14%
-------
Table 7. Number of tags released and recovered by areas shows great site fidelity as well as transoceanic migration capability of Pacific cod.
Release
Number
Area
Total
Rate
Shelf
Slope
U-Pass
AI
610
620
630
2,859
1,352
5,102
2,943
6
34
100
106
81
173
13
0
0
2
3.7%
6.0%
3.4%
0.4%
0.0%
0.0%
2.0%
U-Pass
610
5,974
419
2,397
93
40.1%
22.2%
Shelf
U-Pass
610
620
630
2
648
4,030
2,315
6,863
0
31
118
114
527
0.0%
4.8%
2.9%
4.9%
7.7%
Number of Tags Recovered
AI
U-Pass
Slope
Shelf
AFSC RACE 1982 -1992
0
44
15
38
0
0
18
59
2
0
2
127
5
20
1
11
0
2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
AFSC FIT (2002 - 2007)
1
2,067
78
73
45
40
3
5
ADF&G (1997 -2007)
0
0
0
0
0
0
24
0
1
3
0
4
0
1
15
0
0
0
0
22
0
0
1
0
54
AFSC RACE Archival Tags (2002 - 2006)
0
92
2
1
11
0
0
0
0
21
UA*
610
620
IW**
630
8
2
15
0
0
0
0
0
0
2
0
0
0
0
1
0
1
0
0
0
1
0
0
0
0
0
0
0
129
45
2
1
1
0
3
89
4
0
0
0
6
76
19
0
0
3
12
453
0
0
0
0
0
8
37.4%
114
305
U-Pass
630
0
52.6%
173
329
* UA = Unknown Area of recovery
** IW = International Water, one tag was recovered at 62°47'02" N and 179°58'07" E by Russian Fishery.
AI = NMFS statistical area 541, 542, and 543.
U-Pass = NMFS statistical area 509, 513, 517, 518, and 519.
Shelf = NMFS statistical area 508, 512, 514, 516, and 524.
Slope = NMFS statistical area 521and 523.
0
0
0
152
0
0
Table 8. Percentage of tag recovery by release and recovery area showed great site fidelity of Pacific cod in Alaska waters.
Release
Number
Area
Shelf
Slope
U-Pass
AI
610
620
630
2,859
1,352
5,102
2,943
6
34
100
U-Pass
610
5,974
419
Shelf
U-Pass
610
620
630
2
648
4,030
2,315
6,863
Revoery
Number
106
81
173
13
0 --0 --2
2,397
93
UA*
0.0%
0.0%
0.6%
0.0%
0.0%
1.9%
5.4%
0 --9.7%
31
12.7%
118
19.3%
114
10.2%
527
Percent of Tags Recovered
620
610
AI
U-Pass
Slope
IW**
630
AFSC RACE 1982 -1992
0.0%
0.9%
0.0%
7.5%
0.0%
41.5%
14.2%
35.8%
0.0%
0.0%
0.0%
2.5%
0.0%
22.2%
72.8%
2.5%
0.0%
0.6%
1.2%
8.7%
1.2%
73.4%
2.9%
11.6%
0.0%
0.0%
0.0%
0.0%
84.6%
0.0%
15.4%
0.0%
--------------------------------0.0%
50.0%
0.0%
0.0%
0.0%
0.0%
50.0%
0.0%
AFSC FIT (2002 - 2007)
0.0%
0.0%
0.1%
5.4%
0.0%
86.2%
3.3%
3.0%
0.0%
0.0%
0.0%
48.4%
0.0%
43.0%
3.2%
0.0%
ADF&G (1997 -2007)
----------------0.0%
0.0%
0.0%
9.7%
0.0%
77.4%
0.0%
3.2%
0.0%
2.5%
5.1%
75.4%
0.0%
3.4%
0.0%
0.8%
0.0%
10.5%
66.7%
3.5%
0.0%
0.0%
0.0%
0.0%
0.0%
86.0%
3.6%
0.0%
0.0%
0.0%
0.2%
0.0%
AFSC RACE Archival Tags (2002 - 2006)
0.0%
0.0%
0.0%
7.0%
0.0%
80.7%
1.8%
0.9%
0.0%
87.9%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
Shelf
9.6%
114
305
U-Pass
630
12.1%
173
329
* UA = Unknown Area of recovery
** IW = International Water, one tag was recovered at 62°47'02" N and 179°58'07" E by Russian Fishery.
AI = NMFS statistical area 541, 542, and 543.
U-Pass = NMFS statistical area 509, 513, 517, 518, and 519.
Shelf = NMFS statistical area 508, 512, 514, 516, and 524.
Slope = NMFS statistical area 521and 523.
Table 9. Minimum distance (rounded to the nearest nautical miles) between release and recovery
locations. Over 96% of recovered tags released by FIT were released in Bering Sea (BS). About 95% of
recovered tags released by ADF&G were released in the Gulf of Alaska (GOA). 96% of recovered tags
released during RACE I study were released in Bering Sea (BS). RACE II-G is for tags released in GOA
and RACE II-B for BS.
Count
Mean
Standard Deviation
Minimum
1st Quartile
Median
3rd Quartile
Maximum
FIT
2,423
57
81
0
11
31
63
675
ADF&G
533
19
36
0
3
7
18
331
RACE I
373
110
116
0
21
69
163
573
RACE II-G
102
2
5
0
0
0
1
29
RACE II-B
95
27
49
0
3
8
28
292
RACE I
373
435
428
3
150
286
588
2,096
RACE II-G
169
124
125
2
77
90
96
709
RACE II-B
106
209
172
1
58
170
309
783
Table 10. Number of days at liberty, by release group.
Count
Mean
Standard Deviation
Minimum
1st Quartile
Median
3rd Quartile
Maximum
FIT
2,583
250
276
1
24
167
362
1,767
ADF&G
764
333
283
2
146
266
440
1,636
Table 11. Minimum distance (rounded to the nearest nautical miles) between release and recovery
locations and number of days at liberty from FIT study. All tags were released in waters off Unimak
Island.
Count
Mean
St. Dev.
Minimum
1st Quartile
Median
3rd Quartile
Maximum
Minimum Distance Traveled (NM)
April
February
November
691
1,439
170
71
52
43
80
81
70
0
0
0
20
9
5
42
28
21
96
54
51
675
576
518
Number of Days at Liberty (Days)
April
February
November
727
1,543
186
332
209
260
273
272
225
2
1
4
146
14
79
295
61
164
365
357
410
1,767
1,509
1,084
Table 12. Tagging induced mortality by cruise.
*
**
Cruise No
Sample Size
No. Died
Days Captive
Mortality (%)
FA200201
79
0
3
0.0%
FA200201
91
2
8
2.2%
PS200302
37
1
4 – 7*
2.7%
AU200301
91
25
1**
27.5%
Specimen were collected from different tagging dates
Specimen were kept for monitoring survival 24 hours after tagging. Higher mortality rate was
probably due to differences in culling criteria used.
Table 13. Tag reporting rate by cruise.
Cruise
Archival Tags*
Spaghetti Tags
No
Na
Ra
Ra/Na
Ns
Rs
FA200201
269
101
37.5%
1758
710
PS200302
16
6
37.5%
3403
1474
*
Tag reporting rate for archival (high reward) tags is assumed to be 100%.
Rs/Ns
40.4%
43.3%
s
(≤ 100%)
100%
100%
Table 14. Model estimated survival (Sj) and exploitation (uj) rates. The model was not able to reliably
estimate S3 and u4, because the FIT data set had only three years of release cruises.
Parameters
(year)
S1 (2002)
S2 (2003)
S3 (2004)
u1 (2002)
u2 (2003)
u3 (2004)
u4 (2005)
Estimate
0.5384
0.3617
0.4527
0.1612
0.3224
0.2587
0.1434
Standard Error
0.0255
0.0279
>1.0000
0.0088
0.0078
0.0173
>1.0000
95% Confidence Limit
Lower
Upper
0.4882
0.5879
0.3091
0.4179
0.0000
1.0000
0.1446
0.1792
0.3074
0.3378
0.2263
0.2939
0.0000
1.0000
Table 15. Model estimated survival (Sj) and exploitation (uj) rates. Model was not able to reliably
estimate S3 and u4, because the FIT data set had only three years of releases.
Year
2002
2003
2004
2005
Estimate
0.5384
0.3617
0.4527
NA
Survival
Standard Error
0.0255
0.0279
>1.0000
NA
Exploitation
Estimate
Standard Error
0.1612
0.0088
0.3224
0.0078
0.2587
0.0173
0.1434
>1.0000
Covariance
-0.00005
-0.00002
NA
NA
Correlation
Coefficient
-22.2%
-8.1%
NA
NA
Table 16. Estimated fishing (Fj) and natural mortality (Mj).
Year
2002
2003
Natural Mortality
Estimate
Standard Error
0.4029
0.0387
0.5033
0.0754
Fishing Mortality
Estimate
Standard Error
0.2162
0.0122
0.5136
0.0200
Covariance
-0.000157
-0.001178
Correlation
Coefficient
33.1%
78.0%
Table 17. Observed vs model-predicted (expected) number of tags recovered by year of release and year
of recovery in the waters adjacent to Unimak Island during 2002 and 2005. Model predicted number of
tags recovered in 2005 are not as reliable as those of other years, because of high variances associated
with S3 and u4 (Table 14).
Year of Release
2002
2002
280 (280)
2003
--2004*
--* Actual release time was November 2003.
Number of Tags Recovered (Expected)
2003
2004
305 ( 302)
83 ( 88)
1064 (1067)
319 (310)
--128 (133)
2005
23 (22)
72 (78)
38 (33)
Table 18. Estimates of Pacific cod (von Bertalanffy) growth curve parameters from different tagging
studies, compared with results from age determination (Kimura, pers. Comm.) . Only positive growth
data were used in current analysis.
Study
Sample Size
L∞
K
t0
FIT (EBS)
1267
134.7
0.110
NA
ADF&G (GOA)
456
94.5
0.260
NA
RACE I (EBS)
255
125.5
0.135
NA
RACE II (EBS)
73
132.8
0.108
NA
RACE II (GOA)*
68
112.7
0.122
NA
Age Determination
105.4
0.237
1.06
* Returns with zero growth increment were excluded. If returns with zero growth were included, the
estimates of L∞ = 230.7 cm and K = 0.025. See text for detailed explanation.
Figure 1. A graphical presentation of minimum distance traveled and direction of movement of tagged Pacific cod in eastern Bering Sea. Data
presented here were based on FIT study only. Each arrow represents three or more recoveries, except the one fish captured in Russian waters.
Figure 2. Number of tags recovered by minimum distance traveled between release and recovery for all studies.
600
60
FIT
500
(N = 2414)
ADF&G (N = 533)
50
RACE I (N = 373)
400
40
300
30
200
20
100
10
0
0
100
200
300
400
Direct Distance Traveled (nm)
500
600
0
700
Number of Tags Recovered
(RACE I)
Number of Tags Recovered
(FIT, ADF&G, RACE II)
RACE II (N = 197)
Figure 3. Relationship between minimum distance traveled and number of days at liberty.
700
700
FIT
Minimum Distance Traveled (nm)
600
RACE I
600
500
500
400
400
300
300
200
200
100
100
0
0
0
500
1000
1500
2000
0
2500
500
1000
1500
2000
2500
700
700
ADF&G
600
500
500
400
400
300
300
200
200
100
100
0
0
0
500
1000
1500
2000
2500
RACE II
600
0
Days at Liberty (Days)
500
1000
1500
2000
2500
Figure 4. Cummulative percetile of minimum distance traveled (nm) by tagged Pacific cod between release and recovery for FIT studies, showing
release timing effect.
700
Minimum Distance Traveled (nm)
600
PS200302 (February 2003)
AU200301 (November 2003)
FA200201 (April 2002)
500
400
300
200
100
0
0%
10%
20%
30%
40%
50%
Percentile
60%
70%
80%
90%
100%
Figure 5. Cumulative percetile of minimum distance traveled (nm) by tagged Pacific cod between release and recovery, by tagging study.
700
Minimum Distance Traveled (nm)
600
FIT
ADF&G
500
RACE I
RACE II
400
300
200
100
0
0%
10%
20%
30%
40%
50%
Percentile
60%
70%
80%
90%
100%
Figure 6. Recovery rates by size group and capturing gear.
Recovery rate by release gear type
40%
Recovery Rate (%)
All Gear Type Release
Pot Release
Trawl Release
30%
20%
10%
0%
<45
45
50
55
60
65
70
Length (cm)
75
80
85
90
>=95
Figure 7. Predicted length-at-age curves based on various sets of tag recovery data compared with the length at age from aging results (Kimura et
al.
1993).
140
120
Length (cm)
100
80
60
FIT (EBS)
RACE I (EBS)
RACE II (EBS)
ADF&G (GOA)
RACE II (GOA)
Length-At-Age
40
20
0
0
5
10
15
Age (years)
20
25
Figure 8. Recovery rates by size group.
50%
FIT - all recoveries
FIT - DAL ≤ 365 days
RACE I
ADF&G (GOA)
Recovery Rate (%)
40%
30%
20%
10%
0%
>45
45
50
55
60
65
Length (cm)
70
75
80
85
>=90
Figure 9. Standardized recovery rates by size group, an approximation of fishery selectivity of all fish gear combined.
120%
FIT - all recoveries
FIT - DAL ≤ 365 days
RACE I
ADF&G (GOA)
100%
Selectivity (%)
80%
60%
40%
20%
0%
>45
45
50
55
60
65
Length (cm)
70
75
80
85
>=90
Figure 10. Recovery rates by size group and by recovery fishing gear type with all recoveries from FIT data.
25%
50%
Longline
Pot
Trawl
All Gear Type
40%
Recovery Rate (%) all Gear Type
Recovery Rate (%) by Gear Type
20%
15%
30%
10%
20%
5%
10%
0%
0%
>45
45
50
55
60
65
Length (cm)
70
75
80
85
>=90
Figure 11. Recovery rates by size group and recovery fishing gear type with records of days-at-liberty less than a year from FIT data.
20%
40%
Longline
Pot
Trawl
15%
30%
10%
20%
5%
10%
0%
0%
>45
45
50
55
60
65
Length (cm)
70
75
80
85
>=90
Recovery Rate (%) All Gear Type
Recovery Rate (%) by Gear Type
All Gear Type
Figure 12. Standardized recovery rates by size group and by recovery fishing gear type with all recoveries from FIT data. An approximation of
gear selectivity.
120%
Selectivity (%) by Gear Type
100%
80%
60%
40%
All Gear Type
20%
Longline
Pot
Trawl
0%
>45
45
50
55
60
65
Length (cm)
70
75
80
85
>=90
Figure 13. Standardized recovery rates by size group and by recovery fishing gear type with records of days-at-liberty less than a year from FIT
data. An approximation of gear selectivity.
120%
All Gear Type
Longline
Pot
Trawl
Selectivity (%) by Gear Type
100%
80%
60%
40%
20%
0%
>45
45
50
55
60
65
Length (cm)
70
75
80
85
>=90
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