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8/13/2019 Stock-Recruitment Analysis for Escapement Goal Development: a Case Study of Pacific Salmon in Alaska
1/16
743
*Corresponding author: [email protected] email address: [email protected]
Stock-Recruitment Analysis for Escapement Goal
Development: a Case Study of Pacific Salmon in Alaska
ROBERTA. CLARK*, DAVIDR. BERNARD1, ANDSTEVEJ. FLEISCHMAN
Alaska Department of Fish and Game, Sport Fish Division
Research and Technical Services
333 Raspberry Road, Anchorage, Alaska 99518, USA
American Fisheries Society Symposium 70:743757, 2009
2009 by the American Fisheries Society
Abstract.
The constitutional mandate to sustain yields along with regulatory guidancefrom the Sustainable Salmon and Escapement Goal policies of the State of Alaska pro-
vide the impetus for development and implementation of escapement goals for salmon.
When appropriate, a stock-recruitment analysis can provide vital insight on the popula-
tion dynamics of a salmon stock. This insight can greatly facilitate the development of
a scientifically defensible escapement goal to sustain yields from the stock. However,
the role of stock-recruitment analysis in escapement goal development is often misun-
derstood and misapplied. Although many analysts focus on the quantity and quality of
the data needed to conduct a stock-recruitment analysis, other factors such as the spe-
cies of salmon, type and size of fishery, management constraints, social and economic
constraints, and information content of the data are also important. Much of the confu-
sion about stock-recruitment analysis arises because, while the analysis is primarily astatistical procedure, the actual development and implementation of an escapement goal
is primarily a scientific and practical endeavor. Many see the ultimate goal of a stock-
recruitment analysis as the identification of the escapement that produces maximum
sustained yield, although in many cases it may identify much more than that, or less.
Several case studies are used to illustrate the potential uses of stock-recruitment theory
in the development of escapement goals.
Introduction
Article VIII, section 4 of the Alaska Con-
stitution states that (from Harrison 1992):
Fish, forests, wildlife, grasslands, and
all other replenishable resources belonging
to the State shall be utilized, developed, and
maintained on the sustained yield principle,
subject to preferences among benecial
uses.
This mandate for sustainable manage-ment of Pacic salmon Oncorhynchus spp.
provided the impetus for development of a
scientically defensible escapement goal
policy in Alaska. Along with the statutory
duties and powers of the Commissioner of
the Alaska Department of Fish and Game
(ADF&G) and relevant management plans
for salmon stocks, the development of es-
capement goals is regulated by the policy
for the management of sustainable salmon
sheries and the policy for statewide salmon
escapement goals (Title 5 of the Alaska Ad-ministrative Code, Chapter 39).
These two regulatory policies dene four
8/13/2019 Stock-Recruitment Analysis for Escapement Goal Development: a Case Study of Pacific Salmon in Alaska
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744 Clark et al.
types of escapement goals, two of which are
most important to sustained yield manage-
ment of salmon stocks. The biological es-
capement goal (BEG) is dened as: the es-
capement that provides the greatest potentialfor maximum sustained yield (MSY). As an
alternative to management for MSY, the sus-
tainable escapement goal (SEG) is dened
as: the escapement that is known to provide
for sustained yield. Both of these escapement
goals must be described as ranges that take
into account our uncertainty in the data and
variation in stock productivity. The two regu-
latory policies also stipulate that BEGs and
SEGs for Pacic salmon be developed from
the best available data and be scientically
defensible.
The concept of scientic defensibility
is embodied in the well-known production
models and statistical formulations of stock-
recruitment theory. Much of the scientic dis-
course on salmon production and the mainte-
nance of yields is focused on model selection
(e.g., Schmidt et al. 1998), the effect of mea-surement error on model performance (e.g.,
Walters and Ludwig 1981), and the incorpo-
ration of accumulated knowledge about mod-
el parameters into the statistical formulation
(e.g., Hilborn and Liermann 1998) or what is
herein referred to as stock-recruitment analy-
sis. While these are important considerations
in the methodological development of the
theory, little of the peer-reviewed literature
on stock-recruitment analysis focuses on im-provements in data collection and the inter-
pretation of these data in relation to the sus-
tained yield principle in Alaskan law.
It is argued here that current salmon pro-
duction theory is sufcient to address the
question of sustaining yields of Pacic salm-
on in Alaska via the development of BEGs or
SEGs. When used judiciously, stock-recruit-
ment analysis is an important tool in this de-
velopment. It is also argued that factors such
as the species of salmon, type and size of sh-
ery, management constraints, social and eco-
nomic constraints, and information content
of the production data are as important as the
availability of data and sophistication of the
statistical machinery used for stock-recruit-
ment analyses. Four case histories from sh-eries on salmon stocks throughout Alaska are
presented to illustrate these often neglected
considerations in escapement goal analysis.
Methods
Brood year tables were constructed from
escapements (S) and subsequent production
(R) from the following stocks that likely rep-resent the range of information content and
shing power typical of salmon sheries in
Alaska (Table 1; Figure 1): early-run Chignik
River sockeye salmon O. nerka(Ruggerone
et al. 1999; Witteveen et al. 2005; Table 2),
Chilkat River Chinook salmon O. tshawyts-
cha (Ericksen and McPherson 2004; Table
3); Kenai River sockeye salmon, (Hasbrouck
and Edmundson 2007; Table 4); and Good-
news River Chinook salmon (Brannian et al.2006; Table 5).
Simple stock-recruitment analyses were
performed on each brood table using the lin-
earized form of the Ricker relationship with
multiplicative process error (Hilborn and
Walters 1992) to estimate parameters (equa-
tion (1) and reference points (equations (2)
through (4)). Beginning with the familiar
nonlinear form of the stochastic Ricker equa-
tion,
( ) ( )= expexp SSR , (1a)
and then dividing by S and taking natural logs
to form the linear regression recipe
( )2,0~;lnln +=
NSS
R(1b)
A linear regression of ln(R/S) on Swill
estimate the parameters ln (y-intercept),
8/13/2019 Stock-Recruitment Analysis for Escapement Goal Development: a Case Study of Pacific Salmon in Alaska
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745Stock-Recruitment Analysis for Escapement Goal Development
TABLE1.Salmon stocks used to illustrate the different techniques for developing an escapement goal
based on the number of years of stock-recruit data, information content of these data, and the shing
power of the sheries on these stocks.
Stock n(years) Information Content Fishing Power
Chignik sockeye 75 high high
Chilkat Chinook 7 low very low
Kenai sockeye 28 low very high
Goodnews Chinook 17 high low
Chilkat River
Goodnews River
Chignik River
Kenai River
Chilkat River
Goodnews River
Chignik River
Kenai River
FIGURE1.The state of Alaska with the location of major communities and four river systems discussed
in this paper.
8/13/2019 Stock-Recruitment Analysis for Escapement Goal Development: a Case Study of Pacific Salmon in Alaska
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746 Clark et al.
TABLE
2.Escapementsandsubsequentproductionofearly-runChignikRiversockeyesalmonOncorhy
nchusnerkaforthe1922-1996
broodyears
(fromRuggeroneetal.
1999andWitteveenetal.
2005).
BroodYear
Escapement
Produ
ction
BroodYear
Escapement
Production
Broo
dYear
Escapement
Prod
uction
192
2
86,4
21
96
3,8
14
1947
2,3
86,7
33
181,1
12
1
972
326,3
20
995,9
71
192
3
4,6
42
38
0,3
59
1948
3
84,6
37
327,2
95
1
973
538,4
62
1,1
72,4
28
192
4
121,9
83
1,32
2,5
57
1949
2
13,2
69
308,5
34
1
974
364,6
03
607,5
96
192
5
386,3
64
11
7,6
62
1950
2
06,2
70
392,6
27
1
975
319,8
90
655,8
27
192
6
289,0
09
53
0,1
94
1951
1
25,1
26
625,6
89
1
976
548,9
53
982,3
61
192
7
857,8
81
2,67
7,1
84
1952
34,1
55
230,8
20
1
977
364,5
57
2,2
33,7
83
192
8
507,3
53
82
0,9
81
1953
1
68,3
75
357,6
07
1
978
419,7
32
968,2
98
192
9
995,8
32
1,05
4,1
67
1954
1
84,9
53
142,4
21
1
979
491,4
67
3,6
12,1
07
193
0
92,9
55
37
7,4
85
1955
2
56,7
57
554,4
95
1
980
369,5
80
1,7
32,7
41
193
1
96,2
01
1,12
8,2
31
1956
2
89,0
96
208,1
68
1
981
570,2
10
1,8
33,4
32
193
2
2,1
51,7
34
34
1,2
98
1957
1
92,4
79
350,5
12
1
982
616,1
17
2,3
23,6
43
193
3
223,9
13
62
1,4
00
1958
1
20,8
62
242,3
70
1
983
426,1
78
564,1
74
193
4
866,8
90
1,65
8,4
66
1959
1
12,2
26
340,9
46
1
984
597,7
13
636,0
40
193
5
194,6
36
41
9,7
09
1960
2
51,5
67
774,7
56
1
985
373,0
40
772,9
20
193
6
548,0
39
64
5,9
85
1961
1
40,7
14
571,6
45
1
986
557,7
72
2,5
23,2
15
193
7
205,6
13
80
9,5
50
1962
1
67,6
02
693,4
73
1
987
589,2
99
1,4
34,0
36
193
8
175,9
72
1,02
5,5
70
1963
3
32,5
36
698,7
03
1
988
420,5
80
1,6
58,4
60
193
9
1,1
42,8
52
48
9,2
32
1964
1
37,0
73
755,7
26
1
989
384,0
01
1,7
06,4
00
194
0
176,3
07
50
5,3
79
1965
3
07,1
92
1,9
48,1
44
1
990
434,5
50
1,5
26,8
44
194
1
374,4
20
1,58
3,5
79
1966
3
83,5
45
1,3
03,5
67
1
991
662,6
60
1,4
95,5
03
194
2
442,9
81
3,05
9,1
05
1967
3
28,0
00
240,7
12
1
992
360,6
81
929,7
59
194
3
701,8
59
70
0,6
58
1968
3
42,3
43
1,2
10,9
27
1
993
364,2
61
903,5
37
194
4
291,8
44
33
4,0
93
1969
3
66,5
89
476,2
82
1
994
769,4
65
2,0
38,9
09
194
5
217,8
82
24
5,5
34
1970
5
36,2
57
441,6
85
1
995
366,4
95
2,1
17,1
30
194
6
774,1
30
22
4,1
63
1971
6
71,6
68
1,3
83,4
55
1
996
464,7
48
1,5
70,3
75
Average
430,2
54
983,9
14
SD
380,9
63
740,9
58
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747Stock-Recruitment Analysis for Escapement Goal Development
TABLE 3.Escapements and subsequent production of Chilkat River Chinook salmon Oncorhynchus
tshawytschafor the 19911997 brood years (from Ericksen and McPherson 2004).
Brood Year Escapement Production
1991 5,897 12,932
1992 5,284 5,542
1993 4,472 3,231
1994 6,795 1,645
1995 3,790 4,348
1996 4,920 5,637
1997 8,100 7,081
Average 5,608 5,774
SD 1,465 3,619
TABLE4.Escapements and subsequent production (in thousands) of Kenai River sockeye salmon Onco-
rhynchus nerkafor the 19681995 brood years (from Hasbrouck and Edmundson 2007).
Brood year Escapement Production
1968 82 916
1969 52 409
1970 72 520
1971 289 863
1972 302 2,1861973 358 1,995
1974 144 665
1975 129 895
1976 353 1,187
1977 664 2,811
1978 350 3,451
1979 246 1,111
1980 398 2,346
1981 359 2,268
1982 566 8,9301983 557 8,697
1984 310 3,252
1985 396 2,246
1986 400 1,741
1987 1,333 9,531
1988 839 2,120
1989 1,334 3,898
1990 439 1,334
1991 376 3,926
1992 752 3,469
1993 670 1,2871994 895 2,511
1995 521 1,421
Average 471 2,714
SD 328 2,455
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748 Clark et al.
(slope), and2 (residual error). Then ln is
adjusted for lognormal process error (Hilborn
1985),
2
2
lnln
+= (1c)
and to estimate the relevant reference points
for salmon management from the regressionparameters:
=
lnEQS
, (2)
ln07.05.0EQMSY SS , and (3)
ln07.05.0lnMSY . (4)
Statistical uncertainty about the param-
eters and reference points was assessed with
a bootstrap technique (Efron and Tibshirani
1993); resampling the residuals of the linear
regression with replacement, calculating all
parameter estimates and reference points for
each bootstrap replicate, and using percentiles
of the bootstrap values to obtain interval es-timates. Here, for comparison among stocks
a nonparametric analog of the coefcient of
variation (NPCV) is also calculated for each
parameter and reference point (Prager and
Mohr 1999):
; (5)
where an NPCV of 25% or less was consid-ered precise.
TABLE5.Escapements and subsequent production of Goodnews River Chinook salmon Oncorhynchus
tshawytschafor the 19811997 brood years (from Brannian et al. 2006).
Brood year Escapement Production
1981 11,454 16,538
1982 4,332 11,870
1983 20,420 9,479
1984 12,003 12,412
1985 10,810 6,030
1986 6,186 11,899
1987 6,762 10,150
1988 8,131 11,255
1989 4,806 18,849
1990 11,292 9,1341991 6,473 12,069
1992 3,757 7,466
1993 7,076 22,817
1994 11,722 7,006
1995 14,701 24,571
1996 8,907 9,532
1997 10,153 7,187
Average 9,352 12,251
SD 4,211 5,424
( )median
percentilepercentileNPCV
thth85.3015.69
=
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749Stock-Recruitment Analysis for Escapement Goal Development
Apart from this analytical recipe for es-
timating the reference points from the linear
regression parameters, it is important to note
that SEQ
is an estimate of the carrying capaci-
ty of a salmon stock, where carrying capacityis dened as the average escapement of the
stock when it is not being shed (Figure 2).
Moreover, ln is an estimate of the intrinsic
rate of increase of the stock, where intrinsic
rate of increase is dened as the natural loga-
rithm of average recruits per spawner as Sap-
proaches zero.
These denitions also have relevance to
the rate of harvest on a stock while stock-
recruitment data are being collected. Walters
and Hilborn (1976) showed that in the case
of very low harvest rate most of the stock-
recruitment data pairs are on the right-hand
side of the stock-recruit curve, the carrying
capacity of a stock is known, but not the in-
trinsic rate of increase. Conversely, they also
showed that in the case of a very high harvest
rate when most of the stock-recruitment data
pairs are on the left-hand side of the stock-re-
cruitment curve, the intrinsic rate of increase
is known but not the carrying capacity.
Using information from each of the four
salmon stocks as examples and the aforemen-tioned principles of stock-recruitment analy-
sis, recommendations for establishing a BEG
or SEG were developed for each stock that
are scientically defensible based on infor-
mation content of the stock-recruit data, the
denitions of carrying capacity and intrinsic
rate of increase, and the analytical relation-
ship between the two.
Case Studies
Early run Chignik River sockeye
salmon.The Chignik River is located on
the Alaska Peninsula near the community of
Chignik (Figure 1). Sockeye salmon are pri-
marily harvested in a commercial seine sh-
ery (Bouwens and Poetter 2006). Although
a long history of exploitation exists on this
Escapement
Pro
duction
Escapement
Pro
duction
FIGURE2.Graphical representation of reference points (SMSY
, SEQ
, MSY
) on a Ricker stock-recruitment
curve. The diagonal line is the replacement line and the shaded region is the area of surplus produc-
tion.
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750 Clark et al.
stock, recent rates of annual exploitation are
moderate and range from 51 to 85%, aver-
aging 69% during 19592003 (Witteveen et
al. 2005). Recent stock assessment consists
of escapements estimated by weir and har-vests estimated by allocation of age classes to
stream of origin based on the relative magni-
tude of escapements (Witteveen et al. 2005).
The brood table consists of 75 years (1922
1996) of escapement and subsequent produc-
tion estimates (Table 2). Sufcient shing
power occurs in the commercial seine shery
to harvest all available surplus production so
that a BEG was desired.
A plot of subsequent production on
brood-year escapement indicates that a broad
range of escapements have occurred, and that
production has not replaced escapement (i.e.,
data points below the replacement line) in 11
out of 75 years, most notably at the highest
levels of escapement (Figure 3). The infor-
mation content of these data are high because
there is information about the intrinsic rate
of increase at high exploitation rates and on
carrying capacity at lower exploitation rates.
The stockrecruitment analysis indicated that
estimates of ln and were relatively precise
with NPCV of 8% and 14%, respectively (Ta-
ble 6). Estimates of SEQ, SMSY, and MSYwerealso precise (NPCV of 11%, 11% and 5%, re-
spectively), indicating that a BEG based on
SMSY
could be developed from this analysis
(Table 7). A BEG appears to be a good t to
this shery as there is close correspondence
between the observed average exploitation
rate (69%) and MSY
(69%; Table 6).
Chilkat River Chinook salmon.The
Chilkat River is located near the city of Haines
in southeast Alaska (Figure 1). Chinook
salmon are harvested in commercial and ma-
rine sport sheries located in Lynn Canal as
well as in the commercial troll shery (Erick-
sen and McPherson 2004). Although a long
history of exploitation exists on this stock,
recent rates of annual exploitation are low
and ranged from 8 to 19%, averaging 12%
during 19881991. Recent stock assessment
Escapement
0
500,000
1,000,000
1,500,000
2,000,000
2,500,000
3,000,000
3,500,000
0 500,000 1,000,000 1,500,000 2,000,000 2,500,000 3,000,000 3,500,000
Produ
ction
Escapement
FIGURE3.Plot of subsequent production on brood year escapement and the estimated Ricker curve from
the early-run of Chignik River sockeye salmon Oncorhynchus nerka, 19221996 brood years.
8/13/2019 Stock-Recruitment Analysis for Escapement Goal Development: a Case Study of Pacific Salmon in Alaska
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751Stock-Recruitment Analysis for Escapement Goal Development
consists of escapements estimated by mark-
recapture and harvests estimated by coded-
wire tag recoveries. The brood table consistsof seven years (19911997) of escapement
and subsequent production estimates (Table
3). Prior to this analysis no escapement goal
was available for this stock. Although la-
tent shing power is available that could be
brought to bear on this stock, the initial de-
sire was to develop an escapement goal (SEG
or BEG) for this stock so existing sheries
could be liberalized when surplus production
was realized.A plot of subsequent production on brood-
year escapement indicates that a narrow range
of escapements have occurred and that pro-
duction has not replaced escapement in three
out of seven years, indicating that this stock is
at or near carrying capacity (Figure 4). Infor-
mation content of these data are low because
there is no information on the intrinsic rate
of increase, but there is on carrying capacity.
The stock-recruitment analysis indicated thatestimates of ln and were imprecise with
NPCV of 67% and 70%, respectively (Table
6). Estimates of SEQ
and SMSY
were notably
more precise (NPCV of 19% and 25%, re-
spectively) because there was good informa-tion about carrying capacity. The estimate of
MSY
was poor (NPCV of 53%) because of the
lack of production data at low escapements
and the resulting lack of information about
intrinsic rate of increase. The estimate of SEQ
is defensible; it differs little from the average
of escapements observed while shing power
was low (average S= 5,608; Table 3). From
the estimate of SEQ
, a conservative estimate of
SMSYcould be developed by assuming ln was0 (assumes return-per-spawner is 1 at low es-
capements) and solving equation (3) for SMSY
.
Alternatively, a less conservative estimate of
SMSY
could be calculated by using an estimate
of average ln from Chinook salmon stocks
in southeast Alaska (average ln = 1.92) as
was done by Ericksen and McPherson (2004).
Although these methods produced an estimate
of SMSY
, information was still missing on re-
turns at escapements near SMSY
for this stock,so that a SEG was recommended instead of a
BEG (Table 7).
TABLE6.Summary of parameter estimates, estimated reference points, and nonparametric CVs (in pa-
rentheses) from linear regression and bootstrapping of stock-recruitment data from four salmon stocks
in Alaska.
Stock
ln 2 SEQ SMSY MSY
Chignik
sockeye
1.87
(8%)
1.68 10-6
(14%)
0.60
(10%)
1,114,168
(11%)
410,940
(11%)
69%
(5%)
Chilkat
Chinook
0.91
(67%)
1.38 10-4
(70%)
0.49
(43%)
6,590
(19%)
2,875
(25%)
40%
(53%)
Kenai
sockeye
2.11
(8%)
5.71 10-4
(51%)
0.29
(13%)
3,698a
(48%)
1,303a
(50%)
74%
(5%)
Goodnews
Chinook
1.39
(19%)
1.08 10-4
(23%)
0.19
(16%)
12,843
(10%)
5,169
(12%)
56%
(14%)
ain thousands.
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752 Clark et al.
TABLE
7.Summaryoffourcasestudiesofsalmonescapementgoaldevel
opment.
Stock
n
Info
rmation
Fishing
ln
Goaltype
Basisforgoal
Con
tent
Power
Chignik
sockeye
75
high
high
kn
own
known
BEG
Rickerregression
to
estimateSMSY
ChilkatChinook
7
low
low
un
known
unknown
SEG
Discountfromca
rrying
capacitybasedon
averageescapement
Kenaiso
ckeye
28
low
high
kn
own
unknown
SEG
Exploitationrate
fromln
GoodnewsChinook
17
high
low
kn
own
known
BEGorSEG
Rickerregression
to
estimateSMSY
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753Stock-Recruitment Analysis for Escapement Goal Development
Kenai River sockeye salmon.The
Kenai River is located on the Kenai Pen-insula near the cities of Soldotna and Ke-
nai (Figure 1). Sockeye salmon are har-
vested in marine commercial, freshwater
sport, and personal-use fisheries (Shields
2006). Escapement is estimated with so-
nar near the mouth of the river, and ma-
rine harvests are estimated by allocation
of harvests by age-class to stream of ori-
gin based on the relative magnitude of
escapements (Hasbrouck and Edmundson2007). Stock assessments have occurred
since 1968, with annual exploitation
ranging from 48 to 94% and averaging
79%. The brood table consists of 28 years
(19681995) of escapement and subse-
quent production estimates (Table 4).
The current escapement goal is an SEG
of 500800 thousand (Hasbrouck and Ed-
mundon 2007). There is sufficient fishingpower in the currently configured fisher-
ies to harvest all available surplus pro-
duction so that a BEG was desired.
A plot of subsequent production on
brood year escapement indicates that a nar-row range of escapements have occurred
and that production has always replaced es-
capement, indicating a lack of information
about this stocks carrying capacity (Figure
5). Information content of these data are low
because there is information on the intrinsic
rate of increase, but little or none on carry-
ing capacity. The stock-recruitment analysis
indicated that the estimate of ln was pre-
cise (NPCV of 8%) as was the estimate of
MSY(NPCV of 5%; Table 6). Estimates of
(NPCV of 51%), SEQ
(NPCV of 48%), and
SMSY
(NPCV of 50%) were grossly impre-
cise (Table 6), which prohibited the devel-
opment of a defensible BEG. On the other
hand, the estimate of MSY
(74%) is lower
than the observed average exploitation
rate (81%), indicating that the current SEG
should be increased somewhat. Althoughno defensible BEG could be developed, ad-
vice to increase the current SEG is useful to
shery managers (Table 7). While likely not
Escapement
0
2,000
4,000
6,000
8,000
10,000
12,000
14,000
0 2,000 4,000 6,000 8,000 10,000 12,000 14,000
Spawning Abundance
Production
Escapement
FIGURE4.Plot of subsequent production on brood year escapement from Chilkat River Chinook salmon
Oncorhynchus tshawytscha, 19911997 brood years.
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754 Clark et al.
optimal in terms of producing MSY, the cur-
rent SEG has been shown to be defensible
and sustainable given that escapements ob-
served since 1968 have always yielded sur-
plus production.
Goodnews River Chinook salmon.The
Goodnews River is located near the commu-
nity of Goodnews Bay in southwestern Alaska
(Figure 1). Chinook salmon are harvested in
commercial, sport, and subsistence sheries(Jones and Linderman 2006) that primarily
target sockeye salmon. Escapement is esti-
mated with a weir, and marine harvests are es-
timated by allocation of harvests by age-class
to stream of origin based on the relative mag-
nitude of escapements (Brannian et al. 2006).
Recent stock assessments have occurred since
1981, with annual exploitation ranging from
16 to 71% and averaging 33%. The brood
table consists of 17 years (19811997) ofescapement and subsequent production es-
timates (Table 5). The initial desire was to
replace an SEG range based on escapements
indexed with aerial surveys with one (SEG or
BEG) developed from a brood table based on
weir-based counts of escapement.
A plot of subsequent production on
brood-year escapement indicates that a broad
range of escapements have occurred, and that
production has not replaced escapement (i.e.,
data points below the replacement line) in 5
out of 17 years, most notably at the highest
level of escapement (Figure 6). Informationcontent of these data are high because there
is information on the intrinsic rate of increase
at high exploitation rates and on carrying ca-
pacity at lower exploitation rates. The stock
recruitment analysis indicated that estimates
of ln and were relatively precise with
NPCV of 19% and 23%, respectively (Table
6). Precise estimates of SEQ
, SMSY
, and MSY
were estimated from the parameters (NPCV
of 10%, 12% and 14% respectively), indicat-ing that a BEG based on S
MSYcould be devel-
oped from this analysis (Table 7). However,
Escapement
0
2,000
4,000
6,000
8,000
10,000
0 2,000 4,000 6,000 8,000 10,000
Production
Escapement
FIGURE5.Plot of subsequent production on brood year escapement from Kenai River sockeye salmon
Oncorhynchus nerka (in thousands), 19681995 brood years.
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755Stock-Recruitment Analysis for Escapement Goal Development
estimated SMSY
(5,169 sh) was much lower
than the observed average escapement for
this stock (9,352 sh), so that the currently
congured shery may be unable to harvest
all available surplus production leading to achronic inability to achieve the BEG. A bet-
ter option for this shery might be an SEG
constructed around the range of escapements
shown to produce sustained yields.
Discussion
As illustrated by the four case studies,
the simple stock-recruitment analyses usedherein provide vital information regarding
population dynamics and information content
of the basic adult escapement and production
data. This information, when combined with
the practical considerations of the shery
such as shing power and prior knowledge of
a particular salmon species can help the ana-
lyst and shery manager develop a scienti-
cally defensible escapement goal that meets
the mandates of Alaskan law. As seen in the
example of Chignik sockeye salmon, shery
objectives and the information content of thedata match and all that is needed is a simple
stockrecruitment analysis to develop a BEG
that has the potential for producing MSY in
the long-term. More sophisticated models
and analytical techniques of these stock and
recruitment data are available to help rene
our analysis, but the basic premise of a de-
fensible BEG would remain. Our experience
with salmon stocks and sheries in Alaska is
that this situation is the exception rather than
the norm.
Situations similar to the Chilkat Chinook
salmon and Kenai sockeye salmon case stud-
ies are most often seen, where the results of
simple stock-recruitment analyses are in-
conclusive or partially conclusive, and the
Escapement
0
5,000
10,000
15,000
20,000
25,000
30,000
0 5,000 10,000 15,000 20,000 25,000 30,000
Pro
duction
Escapement
FIGURE6.Plot of subsequent production on brood year escapement and the estimated Ricker curve from
Goodnews River Chinook salmon Oncorhynchus tshawytscha, 19811997 brood years.
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756 Clark et al.
analyst must use theoretical considerations
and past knowledge of similar stocks to de-
velop a scientically defensible escapement
goal. In these cases, an SEG is most often
recommended to managers because escape-ment that produces MSY cannot be specied
from the available information. In the case
of Chilkat Chinook salmon this outcome has
little consequence for a shery that has very
low shing power which likely would not
harvest all available surplus production even
with generous shing time. If additional sh-
ing power could be brought to bear on this
stock, then information might be gained on
production potential at levels of escapements
lower than currently observed.
The lack of a BEG is also self perpetu-
ating in the Kenai sockeye salmon shery
because current shing power is more than
sufcient to harvest at rates higher than what
might be specied at MSY. This results in
production information that is conned to the
existing SEG with little potential for gaining
information on the carrying capacity of thisstock. In this case, it can be argued that the
current SEG or one slightly higher has suc-
cessfully sustained high levels of harvest and
is therefore a defensible escapement goal.
Situations similar to Goodnews Chinook
salmon are also seen where knowledge of es-
capement that produces MSY may not be the
proper objective for the shery. In this example,
stock assessment data are collected from a sh-
ery that harvests multiple species where shingpower may be adequate to harvest surplus pro-
duction of one species (sockeye salmon in this
example) and not the other species (Chinook
salmon). Sufcient information is possessed to
develop a BEG from simple stock-recruitment
analysis, but may not be elected to set an es-
capement goal based on this analysis because
there is insufcient shing power to harvest all
available surplus production. In this case, the
tradeoffs in harvest of two species in a single
shery may best be handled by a BEG for one
species and a SEG for the other.
These case studies also illustrate the
need for independent corroborative evidence
of carrying capacity and intrinsic rate of in-
crease in escapement goal development, es-
pecially when one or both pieces of this in-formation are missing or inconclusive in the
stock-recruitment analysis. Existing habitat-
based and paleolimnological approaches for
describing carrying capacity (e.g., Bradford
et al. 1997 for coho salmon O. kisutch, Parken
et al. 2004 for Chinook salmon, Schindler et
al. 2005 for lake-rearing sockeye salmon) are
valuable tools for the development of escape-
ment goals. The development of these ap-
proaches is encouraged for other salmon spe-
cies such as river-rearing sockeye salmon and
chum salmon O. keta. Similarly, meta analy-
ses of intrinsic rates of increase for salmon
species (e.g., Myers et al. 1999) can provide
helpful information on production dynamics
and scientic defensibility of an escapement
goal, especially when shing power is low.
While the continued statistical development
of stock-recruitment analysis is laudable, it isargued that the science of setting escapement
goals and understanding of production dy-
namics of salmon would be better served by
an increase in the collection of high quality
stock assessment data across a broad range
of salmon species, geographic settings, and
shing power.
Acknowledgments
The authors would like to acknowledge
the helpful comments and suggestions on
the content and presentation of this mate-
rial from the many Alaska Department of
Fish and Game staff that participated in the
Escapement Goal Analysis workshops held
from March 2006 through February 2007
in Anchorage and Juneau. We also greatly
appreciate the helpful external peer reviewsprovided to us by the AYK SSI Editorial
Board.
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757Stock-Recruitment Analysis for Escapement Goal Development
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