AN ABSTRACT OF THE THESIS OF
Farzad Aleaziz for the degree of Doctor of Philosophy in
Fisheries Science presented on November 14,
Life-History
Organization
of
1996.
Herring
(Clupea
Title:
harengus
pallasi) in the Northeast Pacific.
Redacted for Privacy
Abstract approved:
William J. Liss
The distribution of herring (Clupea harengus pallasi) in
the Northeast Pacific extends from southern California to
northern Alaska. Studies on variation in herring life-history
local
characteristics and recruitment
are limited to
populations or relatively restricted regions of the Northeast
assessed herring life-history
patterns and recruitment variation among 14 sites extending
Pacific.
In this study
I
Channel in Alaska to San Francisco Bay in
California. Biological data were compiled from published and
unpublished technical reports
of state and provincial
fisheries agencies in the northeast Pacific. Multivariate
from Lynn
(PCA) and inferential statistical methods were applied in
Ordinations of length-and weight-at-age
data analysis.
revealed no latitudinal patterns among the 14 herring sites.
Among four sites for which environmental data were available,
there were significant negative correlations between first PC
scores of size and Ekman layer transport and sea-surface
salinity (SSS). Reproductive characteristics of herring
appeared
to
vary
latitudinally.
Herring
from the more
southerly sites tended to mature at an earlier age and
smaller size and have a longer duration of spawning than
herring from northerly sites. There were significant negative
correlations between
first PC scores of reproductive
variables and Ekman transport, sea-surface temperature, and
SSS. With the exception of Lynn and Seymour Channels in
Alaska, the most northerly sites in this study, asymptotic
size (Lm) tended to increase from southern
to northern
latitudes. With the exception of southern Strait of Georgia
(British Columbia) herring and Tomales Bay (California)
herring, growth coefficients (K) appeared to be higher in
populations from southern than northern
latitudes. Lw was
negatively correlated with SST.
Recruitment variation at
three sites was related to Ekman layer transport during the
periods of spawning. At San Francisco Bay recruitment was
negatively related to winter Ekman transport. At Sitka and
a
showed
recruitment
southwestern Vancouver
Island,
significant positive and negative correlation, respectively,
with spring Ekman transport.
Recruitment in northern and
southern Strait of Georgia were negatively correlated with
SST during fall. There was no correlation between recruitment
and SSS for all sites.
Life-History Organization of Herring (Clupea harengus pallasi) in the
Northeast Pacific
by
Farzad Aleaziz
A THESIS
submitted to
Oregon State University
in partial fulfillment of
the requirements for the
degree of
Doctor of Philosophy
Presented November 14, 1996
Commencement June 1997
Doctor of Philosophy thesis of Farzad Aleaziz presented
November 14, 1996
APPROVED:
Redacted for Privacy
lam
iss, representing Fisheries Science
Redacted for Privacy
7ri k K. Fritzell, Head
epartment of Fisheries and Wildlife
Redacted for Privacy
Dean of G
uate School
I understand that my thesis will become part of the permanent
collection of Oregon State University libraies. My signature
below autorizes release of my thesis to any reader upon
request.
Redacted for Privacy
Farzad Ale. iz,
Acknowledgements
I would like to acknowledge and thank my major professor
and a friend Dr. William J. Liss, without whom this thesis
would not have been completed, and I am very grateful for his
guidance and support during the course of this research. I am
very grateful
and
offer
special
thanks
to
Drs.
David
McIntire, David Sampson and David Thomas for their great help
on my thesis. I also thank my other committee members Drs.
William Pearcy and Mark Abbott for all their help.
I acknowledge and thank all individuals from various
fisheries agencies who provided me either with information or
with data on Pacific herring and who reviewed chapters of my
dissertation including, J. Muier, P. Larson, J. Collie and F.
Funk, J. Schweigert, D. Ware, R.W. Tanasichuk, D. Day,
M.
O'Tool, J. Spratt and D. Watters.
I also like to give special thanks to the Fisheries and
Wildlife
administrative staff and clerical, in particular
Jan Mosley, Charlotte Vickers, Lavon Mauer and Kelly Wildman
for their constant help and friendship. Finally, I would like
to thank my friends Rwangano Daniel Logan for their constant
encouragement, friendship and support throughout my research.
TABLE OF CONTENTS
Page
Introduction
Objectives
1
6
Chapter 1. Geographic Variation in Life History of
Herring (Clupea, harengus pallasi) in
the Northeast Pacific.
Introduction
Material and Methods
Result
Discussion
Reffrence
11
19
34
44
Chapter 2. Growth Variation in Herring (Clupea
harengus pallasi) in the Northeast
Pacific.
Introduction
Material and Methods
Result
Discussion
Reffrence
50
52
57
80
84
9
Chapter 3. Geographic Variation in recruitment of
Pacific herring (Clupea harengus
pallasi) in the Northeast Pacific.
Introduction
Method and material
Result
Discussion
Reffrence
86
88
100
107
112
Summary
117
Bibliography
120
Appendix
131
LIST OF FIGURES
Page
Figure
1.1.
1.2.
1.3.
1.4.
1.5.
Map of the Northeastern Pacific showing
spawning sites of Pacific herring
12
PC scores of individual samples of
Pacific herring length and weight from
14 sites in the northeast Pacific
(Seymour Channe1=Y, Sitka=S, Lynn
Channel =L, Kahshakes=k, Queen
Charlotte=Q, Prince Rupert=P, Central
Coast=C, southern Strait of Georgia =O,
northern Strait of Georgia=N,
southwestern Vancouver Island=V,
northwestern Vancouver Island=I, Cherry
Point=W, San Francisco Bays=F, and
Tomales Bay=T).
21
PC scores of individual samples of
Pacific herring length and weight from
each site in the northeast Pacific. See
Figure 1.2 for sites
23
PC scores of individual samples of
Pacific herring reproductive
characteristics from 14 sites in the
Northeast Pacific (Seymour Channel =Y,
Sitka=S, Lynn Channe1=L, Kahshakes=k,
Queen Charlotte=Q, Prince Rupert=P,
Central Coast=C, southern Strait of
Georgia =O, northern Strait of Georgia
=N, southwestern Vancouver Island=V,
northwestern Vancouver Island=I, Cherry
Point=W, San Francisco Bays=F, and
Tomales Bay=T)
26
PC scores of individual samples of
Pacific herring length and weight (A)
and reproductive characteristics (B)
from four sites (Sitka=S, northern
Strait of Georgia=N, southwestern
Vancouver Island=V, and San Francisco
Bay=F) for which Ekman layer transport,
sea-surface temperature, and sea-surface
salinity data was available
29
LIST OF FIGURES (CONTINUED)
Page
Figure
1.6.
1.7.
2.1.
Relationship between first axis PC
scores of size variables of herring
from four sites and Ekman layer
transport, sea-surface temperature and
salinity. (Sitka=S, northern Strait of
Georgia=N, southwestern Vancouver Island=V,
and San Francisco Bay=F)
30
Relationship between first axis PC
scores of reproductive variables of
herring from four sites and Ekman layer
transport, sea-surface temperature and
salinity. (Sitka=S, northern Strait of
Georgia=N, southwestern Vancouver
Island=V, and San Francisco Bay=F)
32
Map of the Northeastern Pacific showing
sites of herring used in this study.
53
2.2.
2.3.
2.4.
The relationship between growth
coefficient (K) and asymptotic size
(Lc.) estimated using the von
Bertalanffy growth model with length
and age data selected randomly from all
populations and years. The fitted line
represents the hyperbolic curve K(L0­
207.62)=11.282
58
Relationship between von Bertalanffy
growth coefficient (K) and asymptotic
size (Lw) estimated for sites in the
S.E. Alaska(Y=Seymour Channel, L=Lynn
Channel, S=Sitka, K=Kahshakes). The
fitted line shown for this region
represents the hyperbolic curve K(Lm­
207.62)=11.282
59
Relationship between von Bertalanffy
growth coefficient (K) and asymptotic
size (Lc.) estimated for sites in the
British Columbia-Washington region
(Q=Queen Charlotte, P=Prince Rupert,
C=Central Coast, 0=southern Strait of
Georgia, N=northern Strait of
Georgia, V=southwestern Vancouver Island,
LIST OF FIGURES (CONTINUED)
Page
Figure
I=northwestern Vancouver Island,
W=Cherry Point). The fitted line shown
for this region represents the
hyperbolic curve K(La-207.62)=11.282.
60
2.5.
2.6.
2.7.
2.8.
Relationship between von Bertalanffy
growth coefficient (K) and
asymptoticsize (La) estimated for
sites in the California region
(T=Tomales Bay, F=San Francisco Bay).
The fitted line shown for this region
represents the hyperbolic curve
K(Lm-207.62)=11.282
61
Von Bertalanffy growth curves for
northeast Pacific herring. The growth
curves are based on combined weighted
average K and La values for herring from
four different groups including
northern (Seymour Channel and Lynn
Channel) and southern (Sitka and
Kahshakes) parts of S.E. Alaska,
British Columbia (Queen Charlotte,
Prince Rupert, Central Coast, northern
and southern Strait of Georgia, north
and southwestern Vancouver Island, and
Cherry Point), and California (San
Francisco Bay and Tomales Bay)
70
Relationship between mean annual sea-
surface temperature and annual
estimates of growth coefficient (K) for
herring populations from Sitka (S),
northern Strait of Georgia (N),
southwestern Vancouver Island (V), and
San Francisco Bay (F)
71
Relationship between mean annual sea-
surface temperature and annual
estimates of asymptotic size (La) for
herring populations from Sitka (S),
northern Strait of Georgia (N),
southwestern Vancouver Island (V), and
San Francisco Bay (F)
72
LIST OF FIGURES (CONTINUED)
Page
Figure
3.1.
3.2.
Sites in the Northeast Pacific selected
for analysis of recruitment variation
in herring
89
Relationships between recruitment and
(A) spring Ekman transport in Sitka,
(B) spring Ekman transport in southwest
Vancouver Island, (C) winter Ekman
transport in San Francisco Bay, (D, E)
fall sea-surface temperature in
northern and southern Strait of Georgia.
Except for San Francisco Bay, these
regressions are based on filtered data.
98
3.3.
3.4.
3.5.
Two year lagged anamolies for yearclass strength and winter Ekman
transport (unfiltered) at San
Francisco
102
Three year lagged anamolies for yearclass strength and spring Ekman
transport (unfiltered) at Sitka
104
Three year lagged anamolies for yearclass strength and spring Ekman
transport (unfiltered) at southwestern
Vancouver Island.
105
LIST OF TABLES
Table
Table 1.1. Locations of spawning sites of northeast
Pacific herring and time periods of
biological data used in this study
Page
14
Table 1.2. Time periods for data for harvest rate,
escapement biomass (total biomass minus
harvest), Ekman layer transport (ELT),
sea-surface temperature (SST), sea-
surface salinity (SSS) for four sites in
the northeast Pacific
16
Table 1.3. Average harvest rate (HR), escapement
biomass (EB) and monthly mean Ekman
layer transport (ELT), sea-surface
temperature (SST), and sea-surface
salinity (SSS) for reproductive (R) and
growth (G) periods of four herring sites
in the northeast Pacific based on the
study periods that are presented on
Table 1.2
18
Table 1.4. Principal component analysis of
individual samples (N=146) of length and
weight at each age for Pacific herring
from 14 sites in the northeast Pacific.
The eigenvalues and eigenvectors on the
first two axes are listed
20
Table 1.5. Principal component analysis of
individual samples (N=146) of
reproductive characteristics of Pacific
herring from 14 sites in the northeast
Pacific. The eigenvalues and eigenvectors
on the first two axes are listed
25
Table 1.6. Reproductive characteristics of Pacific
herring at each site. Sites are grouped
according to the ordination in
Figure 1.4
28
Table 1.7. Pearson correlation coefficients and
P-values (in parenthesis) for
relationship between Ekman layer
transport (ELT), sea-surface temperature
(SST), and sea-surface salinity (SSS)
for the reproductive and growth
periods
33
LIST OF TABLES (CONTINUED)
Page
Table
Multiple
regression
model
of
first
axis
Table 1.8.
of PC scores of size as dependent variable
and harvest rate, escapement biomass,
year, sites as independent variables.
P-values less than 0.001 are marked by an
35
asterisk
Table 2.1. Location of spawning sites of Pacific
herring and time periods of mean length
-at-age data and sea-surface temperature
(SST).
54
Table 2.2. Pearson correlation analysis among
herring populations within each region
based on annual estimates of growth rat
(K). P-values are marked by asterisks
for P<0.05 (*) andP<0.01 (**)
62
Table 2.3. Pearson correlation analysis among
herring populations within each region
based on annual estimates of asymptotic
size (Lc.). P-values levels are in
parenthesis
63
Table 2.4. The weighted average estimates of von
Bertalanffy growth coefficient (K),
asymptotic length (Lc.), and age at Lt=0
(t0 for Pacific herring and annual mean
sea-surface temperature. The populations
are ordered from north to south
(Table 1.1).
66
Table 2.5. Annual growth parameter estimates that
were considered to be outlier and were
eliminated from calculations of weighted
averaged parameters, and von Bertalanffy
growth curves
67
Table 3.1. Time periods for which recruitment and
environmental data were available for
each site.
91
Table 3.2. Coefficient of variation for recruitment
and environmental factors at each site
95
Table 3.3. Seasonal averages of the unfiltered
environmental data for each site
97
LIST OF TABLES (CONTINUED)
Table 3.4. Regression models of recruitment and
environmental factors at each site
101
DEDICATION
I would like to dedicate this project to my wonderful
wife Roya, and all my beautiful sons, Alireza, Hamed and
Ahmadreza.
Geographic Variation of Life History Traits and Recruitment of
Herring (Clupea harengus pallasi) in the Northeast Pacific
Introduction
Understanding adaptive patterns of life histories of
fishes relative to geographical gradients has become a major
topic of fisheries research. Studies of migration patterns
among juvenile salmon populations (Riddell et al.
1981) and
the relationship of reproductive strategies of American shad
to differences in latitude of their home rivers (Leggett and
Carscadden 1978) indicate that life-history patterns of local
populations of fish species are related to geographical
variation in their environment. Andrewarth and Birch (1984)
believe that the occurrence of populations with different
life-history strategies
enables
species
to
signifies
overcome
adaptive capacity and
limitations
imposed
by
environmental conditions that vary in space and time.
Winemiller and Rose (1992) emphasized the importance of
variation
in
life
history traits
as
a
foundation
for
adaptation. The importance of variation can be understood
2
when population life-history characteristics are examined
because these characteristics represent adaptive successes of
populations
to
their
Therefore,
environments.
more
comprehensive knowledge of life-history performances and
their variation in time and space is necessary to understand
the response of fishes to changing environments (Cole 1954,
Alderdice and Hourston 1985, Gross 1991).
Herring
occur
mostly
in
the
Northern
Hemisphere,
including the Pacific, Atlantic, and Arctic Oceans (Haegele
and Schweigert 1985). At present two herring subspecies have
been identified, Atlantic herring (Clupea harengus harengus)
and Pacific herring (Clupea harengus pallasi) (Bailey et al.
1970) .
Atlantic herring were first thought to comprise one
population, but later researchers were able to distinguish
separate and distinct herring populations (Sinclair 1988).
This finding led to a wide range of studies on variation in
life-histories among Atlantic herring
(e.g.,
Parrish and
Saville 1965, Cushing 1975, Illes and Sinclair 1982). Several
comprehensive studies indicate that herring populations in
both the western and eastern part of the Atlantic Ocean tend
to have diverse life-history patterns that include variation
among populations in spawning time, spawning substrates, egg
size and egg production, and growth performance [expressed
through the Von Bertallanfy growth coefficient
(K)
and
3
asymptotic size
(L.,)]
(Parrish and Saville 1965, Cushing
1975, Anthony and Waring 1980, Jennings and Beverton 1991).
Jennings and Beverton (1991)
believed that herring life-
history is influenced primarily by latitudinal temperature
variation, while Cushing (1975) emphasized effects of spatial
and temporal variation of food production on herring life-
history characteristics.
The distribution of herring (Clupea harengus pallasi) in
the northeast Pacific extends from southern California to
northern
Alaska.
Within
this
area
herring
distinct
populations have been identified (Spratt 1980, Schweigert
1991, Haegele and Schweigert 1985, Hay 1985). Most herring
populations
are
concentrated
in
the
northern
latitudes
because the continental shelf is wider and there are many
more small inlets and islands that are used for spawning than
at southern latitudes.
Environmental conditions in the northeastern Pacific
such as Ekman layer transport, sea-surface temperature and
sea-surface salinity tend to vary with latitude.
In the
southern latitudes of the northeast Pacific, from Vancouver
Island
in
British Columbia
to
California,
Ekman
layer
transport is directed offshore during early spring to late
summer, while during fall and winter Ekman layer transport is
directed onshore (McFarlane and Ware 1989). During periods of
offshore Ekman layer transport, areas from Vancouver Island
4
to
upwelling
exhibit
California
temperature and high salinity,
with
sea-surface
low
while during periods
of
onshore transport these areas experience downwelling with
moderate to high sea-surface temperatures and salinities. In
more northerly latitudes of the Northeast Pacific, from Queen
Charlotte to northern Alaska, the Ekman layer is directed
onshore most of the year, but the intensity of onshore Ekman
transport
is
lower during spring and
summer
(Ware
and
McFarlane 1989). In general, sea-surface temperatures tend to
be more moderate with lower salinities in northern than in
southern latitudes.
Life history patterns of Pacific herring appear to vary
among
locations
response
to
in
the Northeast
variation
in
Pacific,
climatic
and
possibly
in
oceanographic
conditions, However, most of the studies on herring life-
history
characteristics
environmental
factors
and
involve
their
local
relationship
populations
to
within
limited areas such as British Columbia (Ware 1985, Ware and
Tanasichuk 1989, Schweigert 1991). Hay (1985) and Haegele and
Schweigert (1985) suggested that spawning time of Pacific
herring began earlier in southern than in northern latitudes.
Paulson and Smith (1977) found that size-specific fecundity
of Pacific herring tended to decrease from southern to
northern latitudes. Gonyea and Trumble (1983) studied growth
patterns of herring populations in Washington and showed that
herring in the southern part of Washington are smaller in
5
Rounsefell
body size than herring in the north.
(1930)
provided a broader scale comparison of growth among herring
populations from northern Alaska to southeast Alaska.
reported that herring in northern Alaska are
He
larger than
herring in southeast Alaska.
Herring recruitment in both the Atlantic and Pacific has
fluctuated severely. Recruitment variation in herring may be
by
influenced
biological
and
factors
physical
in
the
environment (Sinclair et al. 1985, Smith 1985, Burd 1990,
Wespestad and Gunderson 1990, Stocker et al.
1985,
Zebdi
1990, Ware 1991). Studies on Pacific herring indicates that
recruitment is influenced by density-dependent factors, air-
temperature,
sea-surface
transport (Stocker et al.
temperature,
and
Ekman
layer
1985, Zebdi 1990, Wespestad and
Gunderson 1990, Ware and Thompson 1991).
Although there have been a number of studies on local
herring
populations,
variation
of
life-history
characteristics and recruitment at larger geographic scale in
the Northeast Pacific and life-history variation in relation
to environmental variation is not well understood.
6
Goal and Objectives
The goal of this study is to increase understanding of
geographic variation in herring life-history and recruitment.
Specific objectives of this research study are as follows:
Chapter One
1.
Determine
differences
in
body
size
and
reproductive characteristics of herring from 14
spawning sites in the northeast Pacific, extending
from California to southeast Alaska.
2. Determine the relationships between variations
in body size and reproductive characteristics and
variations in latitude, Ekman layer transport, sea-
surface temperature, sea-surface salinity, harvest
rate and escapement biomass.
Chapter Two
1. Determine differences in growth coefficient (K)
and
asymptotic
length
(Lm)
among
herring
populations within the northeast Pacific including
California,
Washington,
southeast Alaska.
British
Columbia,
and
7
2. Examine the influence of sea-surface temperature
as
an
environmental
factor
governing
herring
growth.
Chapter Three
1. Examine geographical variation in recruitment
among five herring populations in the northeast
Pacific.
2. Determine the effect of Ekman layer transport,
sea-surface temperature, and sea-surface salinity
on interannual variation of recruitment for each of
the five herring populations.
8
Chapter 1
Geographic Variation in Life History Characteristics of Herring
(Clupea harengus pallasi) in the Northeast Pacific.
9
Introduction
The diverse life-history patterns of fish species may
represent
responses
adaptive
to
spatial
and
temporal
variation of their environments (Salon 1975, Jenning and
Beverton 1991, Andrewarth and Birch 1984). Variation in life-
history traits among populations of the same species are a
consequence of genetic variation among populations and of
phenotypic plasticity in response to different environmental
conditions (Berven and Gill 1983, Schaffer and Elson 1975,
Mann
et
al.
1984).
Variation
in
life-history patterns
reflects a trade-off among traits to balance the costs and
benefits
of
reproduction imposed by the differences
in
environmental conditions (Stearns 1976, Beverton 1987).
Studies of reproductive strategies of American shad
(Glebe and Leggett 1981), growth patterns in cod (Taylor
1958), longevity, growth, and age at maturity in brown trout
(Jonsson et al. 1991, l'Abee-Lund et al. 1989), and egg size
and clutch size of coho salmon (Fleming and Gross 1990)
suggest that life history traits within widely distributed
species often vary with latitude. Large-scale environmental
factors
such
as
offshore
Ekman
transport,
sea-surface
temperature and salinity also tend to vary with latitude, and
10
influence
often
life
history
of
patterns
fish
species
(Parrish et al. 1981, Taylor 1958, Alderdice and Velsen 1971,
Alderdice and Hourston 1985, Hay 1985).
The distribution of Pacific herring (Clupea harenqus
pallasi) in the northeastern Pacific extends from southern
California to northern Alaska. Pacific herring are important
in regional economies (Hourston 1980, Spratt 1980) and they
are considered an important element of the food chain in
marine ecosystems (Cushing 1975), often occurring in the diet
of species such as Pacific salmon and hake.
Despite their economic and ecological importance, life-
history variation among herring populations in the Northeast
Pacific is not well understood (Hourston 1980). The diverse
geologic,
and oceanographic
climatic
conditions
in
the
northeastern Pacific provides the opportunity for expression
of variation in herring life-history characteristics on a
broad spatial scale. Most of the studies on herring life
history traits involve local populations within limited areas
such
as
British
Columbia
(e.g.,
Ware
1985,
Ware
and
Tanasichuk 1989, Schweigert 1991). However, some studies have
described large scale variation in herring life history
traits.
Hay
(1985)
and
Haegele
and
Schweigert
(1985)
suggested that spawning time of Pacific herring begins
earlier in southern than in northern latitudes. Hay (1985)
found that a curve expressing the relationship between length
and weight is steeper among individual herring from southern
11
latitudes than from northern latitudes.
Paulson and Smith
(1977) found that size-specific fecundity of Pacific herring
tends to decrease from south to north. Similar variation in
life-history traits with latitude was described by Parrish
and Saville
(1965)
and Jennings and Beverton
(1991)
for
Atlantic herring (Clupea harengus harangus).
The
objectives
of
this
study
are:
(1)
determine
differences in body size and reproductive characteristics of
herring from 14 spawning sites in the Northeast Pacific,
extending from California to southeast
Alaska,
and
(2)
determine the relationships between variations in body size
and reproductive characteristics and variations in latitude,
Ekman
transport,
sea-surface
temperature,
sea-surface
salinity, harvest rate and escapement biomass.
Material and Methods
Biological data for herring from 14 sites (Figure 1.1)
were compiled from
reports of
published
fisheries agencies
and unpublished technical
in the northeast Pacific
(Appendix). The data pertain to migratory populations that
are important in the sac-roe industry for which at least four
consecutive years of data were available. We only used data
that were derived from purse seine sampling. The sites that
were selected for study and the corresponding years for which
12
-65 OON
Lynn Channel
60 00
Seymoie Channel
Prince Rupert
SItka
BC
C ntral Coast
Kahshakes
Strad of Georgia
55 00
Nk"h Outh
Queen Charlotte
Western Vancouver Island
Cherry .
. ?Point.
50 00
South
WA
45 00
40 00
Tamales Bay
San Francisco Bay
-
CA
..,; ;
35 00
North Pacific Ocean
00
I
180 00W
170 00
I
180 00
2500
I
I
150 00
140 00
130 00
120 00
110 00
Figure1.1. Map of the Northeastern Pacific showing
spawning sites of Pacific herring used in this study.
13
data were available are presented in Table 1.1. For British
Columbia,
the sites
are believed to represent
distinct
populations (Schweigert 1991).
Analysis of data on length and weight at each age was
restricted to fish from three to eight years of age because
information was available within this age range for all 14
sites. Reproductive variables included in the study were
spawning time,
spawning duration
(includes non-spawning
intervals), and age, length and weight at maturity. Estimates
of age at maturity (age at which 50% of females are mature)
were provided by herring specialists from the various regions
(personal communication, Paul Larson, Alaska Department of
Fish and Game; Jake Schweigert, Department of Fisheries and
Oceans Vancouver B.C.; Mark O'Toole, Washington Department of
Fish and Game; and Diann Waters, California Department of
Fish and Game). We used the average length and weight at the
estimated age at maturity as the length and weight at
maturity.
For some sites such as Seymour Channel,
Lynn
Channel, and Sitka in southeast Alaska, and Queen Charlotte
and Prince Rupert in British Columbia, the age at maturity
was estimated to be between three and four years. For these
sites we used 3.5 years as age at maturity. Since California
herring start spawning in early November, for data analysis
Table 1.1. Location of spawning sites of Northeast Pacific herring and time
periods of biological data used in this study.
Site
Southeast Alaska
1. Lynn Channel
2. Seymour Channel
3. Sitka
4. Kahshakes
British Columbia and Washington
5. Prince Rupert
6. Queen Charlotte
7. Central Coast
8. Northwestern Vancouver Island
9. Northern Strait of Georgia
10.Southern Strait of Georiga
11.Southwestern Vancouver Island
12.Cherry Point
California
13.Tomales Bay
14.San Francisco Bay
Latitude
Longitude
Period of Data
135°W
0
133 W
135°W
0
131 W
1971,72,73,75,81,83
1971-89a
1971-88b
1977-93
53-55:N
52-53 0 N
51-54 0
N
49-51 0
N
49-50 N
48-49:N
129-131:W
131-133 0
W
122-130 W
48 -49 N
48 N
125-128 W
122 W
1972-80b
1971-80d
1972-80e
1971-80
1971-80
1971-79f
1971-80
1976-1985
38°N
37°N
122°W
122°W
1972-76
1973-85g
:INT
r7
57:N
55 N
125-128°0 W
123-125 W
123-1240 °W
Missing biological data:
a:1976-80, b:1983, c:1972,1976, d:1979, e:1978, 1979, f:1973,1975, g:1979.
15
the initiation of spawning at each of the 14
sites was
expressed as the number of days after November 1.
and salinity (SSS)
Sea-surface temperature (SST)
for
four sites (Sitka, southwestern Vancouver Island, northern
Strait of Georgia, and San Francisco Bay) were obtained from
the U.S. Geological Survey file (Table 1.2).
Sea-surface
temperature and salinity at the stations at Amphitrite Point
and Entrance Channel were used to represent the southwestern
Vancouver Island and northern
of
Strait
sites,
Georgia
respectively. Monthly Ekman layer transport
indices were
based on data collected by the National Marine Fisheries
Service, Monterey, from stations at or near the four sites.
Harvest
rate
biomass
escapement
(the
total
to
harvest
of
(ratio
portion
of
the
biomass)
and
stock
that
participates in spawning or total biomass minus harvest) for
the
four
sites
were
gathered
from
published
reports
(Appendix).
Data
on
length-and
weight-at-age
and
reproductive
characteristics were analyzed by principal component analysis
(Winemiller and Rose 1992, Gauch 1982, Ludwig and Reynolds
1988, McGarigal and Stafford 1991).
This was followed by
ordination of herring populations based on the PC scores that
contained most of the variation. A separate PCA was performed
on the four populations (San Francisco, Sitka, southwestern
Vancouver Island, and northern Strait of Georgia) for which
environmental data were available. Pearson correlation
Table 1.2. Time periods for data for harvest rate, escapement biomass (total
biomass minus harvest), Ekman layer transport (ELT), sea-surface temperature
(SST),
and sea-surface salinity
(SSS)
for four sites in the northeast
Pacific.
Sites
Harvest Rate and
Escapement Biomass
ELT
SST
SSS
Sitka
(1971-88)
(1971-88)
(1971-81)a
N/A
San Francisco
(1973-86)
(1973-86)
(1973-86)b
(1973-86)c
Southwestern
Vancouver Island
(1971-80)
(1971-80)
(1971-80)
(1971-80)d
Northern Strait
of Georgia
(1970-80)
N/A
(1971-80)
(1971-80)
Years missing data:
a: 1979 and 1980, b: 1980, c: 1981, d: 1975-1976.
N/A: Not available.
17
analysis was performed to examine relationships between
PCscores
for
size
and
reproductive
variables
and
environmental factors.
The correlations were tested for
significance at a=0.05.
For the correlation analysis, we used monthly mean SST,
SSS, and Ekman layer transport indices over the growth and
reproductive periods. The growth period was from April to
September, as suggested by Haist and Stocker (1985). The
reproductive period extended from November to January for the
San Francisco Bay site and February to April for the other
three sites. Reproductive period was the time required for
completion of spawning activities. Average of environmental
factors over the growth and reproductive periods, and average
harvest rate and escapement biomass are presented in Table
1.3.
Pearson's correlation analysis was used
to examine
relationships among the three environmental factors.
Pearson
correlation
also
was
used
to
examine
relationships between the first principal component of the
length and weight analysis and annual harvest rate and log-
transformed escapement biomass for the
four sites where
environmental data were available. Multiple regression was
used to assess the relationship between PC scores of size as
the dependent variable and harvest rate, escapement biomass,
year, and site as independent variables. This analysis
Table 1.3. Average annual harvest rate (HR) and escapement biomass (EB), and
mean Ekman layer transport (ELT), sea-surface temperature (SST), and sea-
surface salinity (SSS)for reproductive (R) and growth (G) periods of four
herring sites in the northeast Pacific based on the study periods that are
presented on table 1.2.
SSS
SST
ELT
Sites
HR
EBa
Rb
Gc
R
G
R
G
Sitka
0.13
18580
-64
-16
5.4
7.9
N/A
N/A
Northern Strait
of Georgia
0.16
43057
N/A
N/A
7.1
12.1
25
27
0.38
Southwestern
Vancouver Island
23802
-53
-0.6
7.5
11.9
28
30
122
9.9
13.3
29
32
San Francisco
Bay
0.075
6832
-12
a.Total biomass minus harvest.
b.The reproductive period for Sitka,
southwestern Vancouver Island and
Strait of Georgia was from Feb.-April, and for San Francisco Bay from Nov.
March.
c.The growth period for all sites was April-September.
N/A=Not available.
19
assessed the influence of harvest rate and escapment biomass
on size variation among herring populations.
Results
Principal component analysis of length and weight data
from all 14 sites (146 individual samples) is presented in
Table 1.4. The eigenvalues are 9.57 and 0.9 for the first and
second components respectively, which together account for
87% of the total variation in the data set. The loadings
associated with the first principal component have similar
scores and all have a positive sign, which indicates that the
first PC expresses overall body size of fish among samples
(Figure 1.2). The first axis orders individual samples from
those with small fish on the left to those with large fish on
the right.
The second principal component separates age
classes and contrasts the length and weight of three, four
and five year old individuals with the sizes of six, seven
and eight year old fish. Samples toward the top of the second
axis have fish that are young and small but are relatively
heavy for their age, while samples that have heavier and
older fish are located toward the bottom of the second axis.
Although the sites intergrade, individual sites tend to
occupy particular regions along PC axis one.
Sites with
smaller fish tend to occur to the left on PC axis one (Figure
20
analysis of individual
Table 1.4.
Principal component weight at each age for
samples (N=146)
of length and
Pacific.
Pacific herring from 14 sites in the northeast
first two axes are
The eigenvalues and eigenvectors on the
listed.
Eigenvalue
%variance
Variables
L3
L4
L5
L6
L7
L8
W3
W4
W5
W6
W7
W8
PC1
PC2
9.57
80
0.9
0.241
0.297
0.305
0.299
0.299
0.277
0.261
0.291
0.299
0.306
0.293
0.285
7
0.327
0.166
0.043
-0.196
-0.265
-0.428
0.503
0.332
0.232
-0.087
-0.264
-0.276
V
2
Y
F
'q
L
0
F
L
G2/
v
S sTT
5Y 6 S) YN
.§K K S I
4
Lt
Y
T igt
C
YY
F
S
I
0
K CY
ie
SK w
N
N
fth VNW,
W%
"Jo
r
Pp lett
N
$
si WQ
1
0
CS
WQ
16
-2
0
0
P
0
-4
-10
-8
Small
-6
-4
-2
Axisl
0
2
4
6
Large
Figure 1.2. PC scores of individual samples of Pacific herring length and
weight from 14 sites in the Northeast Pacific (Seymour Channe1=Y, Sitka=S,
Lynn Channel =L, Kahshakes=K, Queen Charlotte=Q, Prince Rupert=P, Central
Coast=C, southern Strait of Georgia=0, northern Strait of Georgia=N,
southwestern Vancouver Island=V, northwestern Vancouver Island=I, Cherry
Point=W, San Francisco Bay=F, Tomales Bay=T).
22
1.2
and
1.3).
These include sites from California
(San
Francisco=F, Tomales Bay=T), which are the most southern
sites in the data set, sites from southeast Alaska
(Lynn
Channel =L, Seymour Channel =Y, Sitka=S, Kahshakes=K),
which
are the most northern sites, and the Central Coast of British
Columbia (C). Sites with larger herring, occurring to the
right on PC axis one, include most of the British Columbia
sites (Queen Charlotte=Q, Prince Rupert=P, northern Strait of
Georgia=N,
southern
Strait
of
Georgia=S,
northwestern
Vancouver Island=I, southwestern Vancouver Island=V), and the
Cherry Point site from Washington (W).
Principal
component
analysis
of
reproductive
characteristics is presented in Table 1.5. The first two
principal components with eigenvalues of 3.56 and 0.845,
respectively,
account for 88% of the total variation in
reproductive
characteristics
among
samples.
The
first
principal component accounts for most of the variation (71%).
The first principal component contrasts spawning duration
with spawning time, age at maturity, length at maturity, and
weight at maturity, whereas, the second principal component
contrasts spawning time and age at maturity with spawning
duration and length and weight at maturity.
The sites form three distinct groups in ordination space
relative to reproductive characteristics (Figure 1.4). The
first principal component indicated a latitudinal pattern in
reproductive characteristics. Herring from San Francisco Bay
Lynn Channel
23
Seymour Channel
2
Y
L
1.5
0.5
L
Y
Y
0
Y
0.5
to
Y
u)
L
f
y
Y
L
V
L
r
r
-0.5
V
-0.5
Y
L
-1.5
-6.5
-7
-4.5
-5
-5.5
-6
Axis 2
Axis 1
Sitka
Kahshakes
1.6
K
S
K
0.5
S
0
K
'SC
S
S
S
0.5
K
3
S
1
to
S
K
0
K
S
-0.5
S
S
S
-0.5
K
.
<
K
K
KK
S
-1.5
.
-25
-a
-3
.4
-5
7
K
S
S
.5
K
K
ss
-2
-1.5
as
0
-0.5
-1
1
2
1.5
Axis 1
Axis 1
Queen Charlotte
Prince Rupert
0.5
P
.
P
P
P
e
a
0.5
a
-as
a
o
N
a
P
1.5
-0.5
a
0
-2
-25
a
25
3
as
4
AXIS 1
4.5
5
5
P
-3
-3
-2
0
1
2
3
4
Axis 1
Figure 1.3. PC scores of individual samples of Pacific
herring length and weight from each site in the
Northeast Pacific. See Figure 1.2 for sites.
Northwestern Vanouver Island
Central Coast
24
3.5
1.5
3
C
2.5
C
2
C
0.5
1.5
CV
1
0
Xtn
C
F
0.5
C
-0.5
0
-0.5
-1
-1
C
C
1
-1.5
0.5
-1
Axis
05
5
1
1.5
2.5
2
3.5
3
45
4
Axis 1
1
Southwestern Vancouver Island
Northern Strait of Georgia
2
1.4
N
V
1.2
1.5
N
N
N
1
0.8
CV
V
CV
N
0.6
N
N
0.4
V
0.2
-0.6
0
V
V
V
-a2
V
V
N
N
-0.4
V
V
-1
-0.6
3
2
2
4
3
Axis 1
Axis 1
Point
Cher
Southern Strait of Georgia
2
0
0
0
CV
0)
-2
0
-3
0
0
.4
12
1.4
1.6
1.8
22
2
26
24
28
3
Axis 1
Axis 1
Tomales Ba
1.
San Francisco Ba
2
F
T
F
F
C
CV
F
F
T
=1
F
F
T
F
F
F
T
F
1
0. a
0
-1.5
05
Axis 1
(Figure 1.3 continued)
-5.2
F
-1.2
-3.2
Axis 1
08
25
Table 1.5. Principal component analysis of individual
characteristics
reproductive
of
(N=146)
samples
AM=age
at
SD=spawning duration,
(ST=spawning time,
at
WM=weight
and
LM=length at maturity,
maturity,
the
in
maturity) of Pacific herring from 14 sites
Northeast Pacific. The eigenvalues and eigenvectors on the
first two axes are listed.
Eigenvalue
%variance
PC1
PC2
3.56
71.2
0.845
17.0
0.432
-0.467
0.461
0.445
0.430
-0.519
0.385
-0.128
0.501
0.559
Variables
ST
SD
AM
LM
WM
26
3
V
2
00
F
T F
1
0
F
,TT
T
IN
V \tr
is
6
N_
S
y
6t
Qge
us0
0
F
Y
pi
is' S
CP
0
S.54
vc
ic rk
-1
ifeCitS9
Y
P
LI
LL
-2
L
P
3
-6
-5
Earlier spawning
Long duration
Earlier age at maturity
Smaller size at maturity
-1
0
Axisi
3
4
5
Later spawning
Shorter duration
Older age at maturity
Larger size at maturity
Figure 1.4. PC scores of individual samples of Pacific
herring reproductive characteristics from 14 sites in
the Northeast Pacific (Seymour Channel =Y, Sitka=S, Lynn
Prince
Queen Charlotte=Q,
Kahshakes=K,
Channel =L,
of
Strait
southern
Central
Coast=C,
Rupert=P,
Georgia=0, northern Strait of Georgia=N, southwestern
Vancouver Island=V, northwestern Vancouver Island=I,
Cherry Point=W, San Francisco Bay=F, Tomales Bay=T).
27
(F) and Tomales Bay (T), which are the most southerly sites,
tended to mature at an early age and small size, began to
spawn in November, and had a long spawning duration (Figure
1.4, Table 1.6). The southeast Alaska and British Columbia
sites were clustered to the right on axis one. Herring at
these sites tended to spawn between late January and early
May. Herring at these sites had a short spawning duration and
matured at a relatively older age
and larger size than
California herring (Figure 1.4, Table 1.6).
Herring from
Cherry Point, Washington (W) form an intermediate group.
PCA was performed on the four sites (Sitka, northern
Strait of Georgia, southwestern Vancouver island, and San
Francisco Bay) for which data on Ekman layer transport, SST,
and SSS was available. The results of PCA of length and
weight and reproductive characteristics for the four sites
was similar to results of PCA for all 14 sites (Figure 1.5).
The first principal component for length and weight for
the four sites showed a significant negative correlation with
Ekman layer transport (Figure 1.6; r=-0.59, P<0.0001) and SSS
(r=-0.60, P<0.004). The Sitka (S) and southwestern Vancouver
Island (V)
sites occur in areas where directions of Ekman
layer transport during the growth period are mostly onshore,
and fish are relatively larger than at the San Francisco (F)
site which occurs in a region of strong offshore divergence
during the growth period (Figure 1.6A). SSS is lower at the
northern Strait of Georgia site (N) than at the other sites
Table 1.6. Reproductive characteristics of Pacific herring at each site. Sites are
grouped according to the ordination in Figure 1.4.
Site
California
San Francisco Bay
Tomales Bay
Washington
Cherry Point
Southeast Alaska & British Columbia
Strait of Georgia (south)
Strait of Georgia (north)
Southwestern Vancouver Island
Northwestern Vancouver Island
Southeast Queen Charlotte
Prince Rupert
Central Coast
Kahshakes
Sitka
Lynn Channel
Seymour Channel
SD
LM
WM
AM
(d)
(mm)
(mm)
(Yr)
97
73
160
161
61
61
2
2
Early-Mid April
55
177
88
2-3
Late Jan.-Mid Feb.
Late Feb.-Early Mar.
Late Feb.-Early Mar.
Late Feb.-Early Mar.
March
Late March-Early Apr.
Late Marc.-Early Apr.
Late Marc.-Early Apr.
Late Apr.-Early May
Late Apr.-Early May
Late Apr.-Early May
47
25
25
15
180
192
188
191
190
180
182
181
201
178
185
80
98
92
93
97
85
82
89
101
75
106
3
ST
Early-Mid Nov.
12
16
11
11
12
5
8
3
3
3
3-4
3-4
3
3
3-4
3-4
3-4
Legends:
ST=Spawning time, SD=Spawning duration, LM=Length at maturity, WM=Weight at maturity, and AM=Age at
maturity for the 50% of population maturity.
29
A
4
V
3
2
F
FFF
cv
cn
F
FF
F
FF
F
FS
0
33
iV
8
V
-1
S
-2
Nrsi
N
V
V
N
N
V
S
VN
§
%S
N
SN
N
V
S
v
-6
8
6
Large
Small
B
V
2
F
N
1.5
IV
V
N
VV
F
CV
1
VN
F
U)
F
(
FF
0
S
V
S
S
S
SS
VN
F
Sg
N
N
S
S
SS
-0.5
V
-1
-6
-
Earlier spawning
Long duration
Earlier age at maturity
Smaller size at maturity
-
-
Axial
0
1
2
3
Later spawning
Shorter duration
Older age at maturity
Larger size at maturity
Figure 1.5. PC scores of individual samples of Pacific
herring
length and weight
(A)
and
reproductive
characteristics (B) from four sites (Sitka=S, northern
Strait of Georgia=N, southwestern Vancouver Island=V,
and San Francisco Bay=F)
for which Ekman
layer
transport, sea-surface temperature, and sea-surface
salinity data was available.
30
A8
P<O. 000l
V
4
V
N
V
V
0
t2
0
r=-0.59
Nt
6
0
-2
R ss
FF
FF
FIE
F
-4
F
-6
-50
200
150
50
100
Ekman layer transport index
0
B8
V
6
P>0.05
ki/
4
NN
N
4,5 2
is
0
0- 0
it
N
S
VA/
S SS
-2
S
FF
-4
F
F
-6
6
8
10
12
16
14
Sea-surface temperature (centigrade)
C8
6
N
N
4
N
N
V
N
N
15 2
vv
VV
N144
0
r---0.60
P<0.004
V
CI- 0
-2
F
F
-4
F
FF
F
F
F
F
F
-6
22
24
26
28
30
32
34
36
Sea-surface salinity (PPT)
Figure 1.6. Relationship between first axis PC, scores of
size variables of herring from four sites and Ekman layer
transport, sea-surface temperature and salinity. (Sitka=S,
northern Strait
of Georgia=N,
southwestern Vancouver
Island=V, and San Francisco Bay=F).
31
(Figure 1.6C). SST at the Sitka site is lower than at other
sites, although no significant relationship between size and
(r=-0.042,
temperature among sites was observed
P>0.786;
Figure 1.6B).
first
The
principal
component
for
reproductive
characteristics showed significant negative correlations with
Ekman layer transport
and SSS
P<0.001),
(r=-0.70,
P<0.0001),
SST
(r=-0.57,
(r=-0.90, P<0.0001; Figure 1.7).
Ekman
layer transport, SST and SSS indices are strongly correlated
during both the growth and reproductive periods (Table 1.7).
During
the
positively
growth
period,
correlated
with
Ekman
SST
layer
which
transport
appears
was
counter-
intuitive since offshore transport is usually associated with
upwelling ans low SST. The discrepancy may have resulted from
using monthly means for SST rather than daily SST and as a
result SST for the growth period tends to be higher during
offshore Ekman transport.
Herring populations in British Columbia to have the
largest
escapement
biomass
of
the
four
sites
and
San
Francisco Bay the smallest (Table 1.3). Also, average harvest
rates in British Columbia tend to be higher than in Sitka or
San Francisco Bay
(Table 1.3).
First PC axis scores for
length and weight showed a significant positive correlation
with both harvest rate
(r=0.44,
P<0.019)
and escapement
biomass (r=0.40, P<0.0048). However, in a multiple regression
model which included individual sites and years as well as
32
A
4
2
a)
S AY
§
S
cv
r=-0.70
P<0.0001
§
VV VV V
V
0
4- m
gs s
SS S
o >
LOU)
.> -2
CL
7.1)
F
F
-4
LI: 2
F
F
F
,F F
F
t­
FF
F
F
2 -6
-140
-120
-100
-80
B4
-40
-20
20
0
40
N
2
U)
-60
Ekman layer transport index
s
S §s
Ss s
P<0.001
,\YN
v
m0
v
cr, >
w -2
0_ >
F
= -4
FFFF FF
.15
Li_ -0
2
a.
6
2
2
4
4
a) 2
23
Cu
.c 0
ocv
0_
6
10
12
N
AN
v
r=-0.90
P<0.0001
NV
N
V
> -2
F
1;2 loc2 _4
F
it 2
2
8
Sea-surface temperature (centigrade)
Cr
ca
F
F
F
FFF
FF
F
-6
26
27
28
29
30
31
32
33
Sea-surface salinity (PPT)
Figure 1.7. Relationship between first axis PC scores of
reproductive variables of herring from four sites and Ekman
layer transport, sea-surface temperature and salinity.
(Sitka=S,
northern
Strait of
Georgia=N,
southwestern.
Vancouver Island=V, and San Francisco Bay=F).
33
Table 1.7. Pearson correlation coefficients and P-values
(in parenthesis) for relationships between Ekman layer
transport (ELT), sea-surface temperature (SST), and sea-
surface salinity (SSS) for the reproductive and growth
periods.
Growth
Reproductive
SST
ELT
SSS
SSS
SST
SSS
-0.65
-0.91
0.54
0.49
(0.009)
(0.0001)
(0.02)
(0.025)
0.53
(0.015)
0.62
(0.003)
34
harvest
rate
and
escapement
biomass
as
independent
variables,we found no significant effect of harvest rate and
biomass on size (P>0.05; Table 1.8). In this model, size was
significantly related only to site (P<0.0001).
Discussion
There was no general latitudinal trend in herring length
and weight-at-age among the sites included in this study. The
smallest herring occurred at the most northern and southern
sites. Among the 14 sites, herring from Lynn Channel and
Seymour Channel, the most northern sites in our study, have
the smallest size. The historical growth record from Lynn
Channel and Seymour Channel suggests that herring from these
two northerly sites have always had the slowest growth among
southeast Alaska herring,
migratory
tendency
which
possibly due
may
to
their
less-
their
chance
reduce
of
encountering productive feeding areas (Fritz Funk, Alaska
Department of Fish and Game, personal communication). Aleaziz
et al. (in review; see Chapter 2) found that the growth rates
of Lynn Channel (K=0.15 mm per year)
(K=0.17
per
year)
herring,
and Seymour Channel
calculated
using
the
Von
Bertalanffy model, were the slowest among the 14 northeast
Pacific sites. Herring are also small in San Francisco Bay
and Tomales Bay, the most southern sites. However, herring
Table 1.8. Multiple regression model of first axis of PC scores of size as
the dependent variable and harvest rate, escapement biomass, year, and sites
as independent variables. P-values less than 0.001 are marked by an
asterisk.
Source
Model
df
22
MS
F-Value
P-Value
19.67
9.66
0.0001**
Site
3
123.11
60.47
0.0001**
Year
17
3.57
1.75
0.0989
Harvest Rate
1
2.4
2.39
0.2882
Escapement Biomass
1
0.29
0.14
0.7082
Error
25
Corrected Total
47
2.036
36
from San Francisco Bay and Tomales Bay have higher growth
rate coefficients (K=0.30 and 0.21 mm per year, respectively)
than herring from Lynn and Seymour Channels (Aleaziz et al.
in review; see Chapter 2). Mortality rate of adult fish may
be
higher
in
California
than
in more northern
accounting for smaller average sizes
sites,
despite high growth
rates. According to Trumble and Humphreys (1985), the natural
mortality rate of herring in the Northeast Pacific ranges
between 0.15-0.45 annually and decreases from southern to
northern latitudes.
Herring from Sitka and Kahshakes in southeast Alaska and
Central Coast of British Columbia were also relatively small.
Length and weight data for the Sitka and Kahshakes sites were
from the late 1970's and 1980's when growth of individual
fish, especially of Sitka herring was very poor. Hence, the
sizes of individual herring particularly among the younger
age-classes (2,
3, and 4 years old) was small (Jim Muier,
Alaska Department of Fish and Game, personal communication).
Aleaziz
et
al.
(in review;
see Chapter
2)
found that,
although the growth rate of Kahshakes herring was relatively
high (K=0.24), herring from Sitka had a lower growth rate
(K=0.19 mm per year) than herring from most sites in British
Columbia, Washington, and California.
Aleaziz et al. (in review; see Chapter 2) found that the
sites with larger fish, including Queen Charlotte,
Prince
Rupert, northern Strait of Georgia, northwestern Vancouver
37
Island
and
southwestern
Vancouver
Island
British
from
Columbia, and Cherry Point from Washington tended to have
higher growth rate coefficients (K) than more northern sites
(except
Kahshakes),
which
is
consistent with
the
size
ordination (Figure 1.2 and 1.3). Sites with relatively high
growth coefficients such as southwestern Vancouver Island
(K=0.33) and northern Strait of Georgia (K=0.35) might have
high food productivity. The occurrence of
upwelling near
southwestern Vancouver Island and nutrient-rich runoff from
the Fraser River into the Strait of Georgia have made these
two areas biologically more productive for fish
species
(Thomson et al. 1989, Harrison et al. 1983). The relatively
large size and rapid growth (K=0.30) of the Cherry Point
herring in Washington could be explained by the proximity of
their spawning ground in northern Puget Sound to their
feeding ground in the Juan de Fuca Strait area, which may
result
in
less
energy expenditure by these herring in
reaching the feeding ground (Dwane Day, Washington Department
of Fish and Game, personal communication).
There were significant positive correlations between the
PCs of size and harvest rate and log-transformed escapement
biomass. However, when sites and years were incorporated as
independent variables in multiple regression analysis no
significant impact of harvest rate and biomass on the size of
herring was found, suggesting that differences in harvest
38
rate and biomass do not explain differences in size between
sites.
In contrast to size, reproductive
characteristics of
herring appear to vary latitudinally. Herring from the more
southerly sites tend to mature at an earlier age and smaller
size and have a longer duration of spawning than herring from
northerly sites.
In addition,
spawning
is
initiated
in
November in California, while spawning does not commence
until after January at more northerly sites.
We found significant correlations between some
life
history characteristics of herring and environmental factors,
especially Ekman layer transport and SST, although the number
of sites for which environmental data was
available was
small. We also found strong correlation between Ekman layer
transport, SST, and SSS indices. Castillo (1992) also found
strong correlation between SST and SSS off Oregon during
winter. Correlation among environmental factors confounds
interpretation of the influence of individual factors on life
history traits.
Ekman layer transport, sea-surface salinity, and sea-
surface temperature tend to vary with latitude (Bourke et al.
1971). In the southern latitudes of the Northeast Pacific,
Ekman layer transport during the growth (early spring-late
summer) and reproduction (late fall-early spring) periods is
directed offshore and onshore, respectively. Hence, during
the growth period (April-September), the San Francisco Bay
39
area exhibited upwelling but with relatively high monthly
mean SST and SSS, while during the reproduction period this
area experienced moderate downwelling with lower monthly mean
SST and SSS. During the study period, southwestern Vancouver
Island experienced weak downwelling during the growth period
Ekman
and strong downwelling during reproductive period.
layer transport in the northern latitudes is directed onshore
throughout the year with downwelling and moderate to low SST
and salinity (Bourke et al. 1971, Ware and McFarlane 1989,
Parrish et al. 1981). However, local anamolies may occur, for
example local runoff from coastal rivers tends to influence
SSS (Ware and Thompson 1991, Bourke et. al 1971).
We found significant negative correlations between PC's
of size-at-age and SSS and Ekman layer transport. However,
these results are inconsistent with the size ordination
(Figure 1.2 and 1.3) which showed no latitudinal pattern in
body
size.
The
sites
that
were
not
included
in
the
correlation analysis because they lacked environmental data
probably would have altered the relationship between body
size and environmental factors. For example, Lynn Channel and
Seymour Channel are the most northern sites and likely
experience onshore Ekman layer transport during the growth
period and relatively low SST and SSS, but herring from these
40
two sites are as small as San Francisco herring and smaller
than those at Sitka(1.6).
In this
study we found no significant correlation
between SST and size-at-age. Winters et al.
(1986), using
length-at-age data, found no significant correlation between
size and temperature for juvenile herring from St.Mary's-
Placentia in the northwest Atlantic.
Herring appear to have a wide range of tolerance to SSS
(Alderdice and Hourston 1985), hence, the effect of SSS,
especially on herring growth is not well understood. However,
an experimental study by Alderdice and Velsen (1971) suggests
that SSS and SST affect survival and development of Pacific
herring larvae mostly during early life stages, although
herring eggs tend to have a wide range of tolerance for SSS
(12-26 ppt) and SST (3-9 °C).
The effect of upwelling on growth of Pacific herring is
not well understood. Haist and Stocker (1985) indicate that
upwelling had no impact on the growth rate of juvenile
herring from British Columbia. Generally, areas with intense
upwelling are associated with occurrence of high levels of
biological productivity which benefits
fish
growth
and
survival (Cushing 1975). However, the occurrence of intense
upwelling also is an indication of high wind and turbidity
which tends to deepen the mixed layer. Lasker (1978)
and
Peterman and Bradford (1987) believe that the growth rate of
newly hatched fish larvae depends on periods of less intense
41
mixing and consequently concentration of more food particles
in the surface layer making food more available to the
larvae.
In contrast to body size, reproductive characteristics
varied with latitude and were significantly correlated with
Ekman layer transport, SST, and SSS. Parrish et al.
(1981)
and Stevenson (1962) suggested that strong divergence of sea-
surface water often has a detrimental affect on eggs and
newly hatched larvae. They suggested that to reduce egg loss
and high mortality early in life, most of the pelagic fish
species in California tend to spawn during the period of
onshore Ekman transport which occurs between late fall and
early spring. Consistent with this view, spawning of herring
in California begins in early November and continues until
early March when Ekman transport is onshore. In northern
sites spawning time also coincides with onshore Ekman layer
transport which occurs at lower intensity during the spring
reproductive period. Haldorson and Collie (1990) suggested
that the survival rate of newly hatched herring in Sitka is
higher during the years when larvae are transported to the
northern part of Sitka Sound via coastal currents which are
augmented by low intensity onshore Ekman transport
.
Haldorson and Collie (1990) believe that adjustment of
spawning time
to
coincide with
favorable
oceanographic
conditions is a response to natural selection that enhances
survival of progeny. If this is true, then spawning duration
42
could also be adjusted accordingly. Spawning activities of
November to early
California herring extends from early
March, while spawning activities of herring from southeast
Alaska lasts only 5 to 14 days.
Tanasichuk et al.
(1993)
found that herring from the Beaufort Sea in Alaska tend to
devote less energy to reproduction than herring from the
Strait of Georgia, especially among the older age-classes.
They also
instantaneous mortality rate
showed that
of
Beaufort Sea herring is lower than the mortality rate of
herring from Strait of Georgia.
Nevertheless,
the short
spawning duration of herring in northern latitudes suggests
that the window of opportunity for herring to reproduce is
short,
while
in the southern latitudes perhaps due to
variation in offshore Ekman layer transport, herring tend to
spread spawning activities over a longer period possibly to
increase chances that the progeny will encounter suitable
Alderdice
conditions.
and Velsen
suggested
that
(1971)
spawning occurrence and spawning success,
especially in
southern latitudes, tend to be lower during seasons of high
SSS.
Studies
on
walleye
(Stizostedion
vitreum
vitreum)
(Beverton 1987), tropical sardines (Sardinops sagax) (Garland
1993,
Holt 1960),
harengus)
temperature
and Atlantic herring
(Jennings
can
have
and
an
Beverton
important
(Clupea harengus
1991)
suggest
that
on
fish
influence
reproduction. Hay (1985) suggested that herring from southern
43
latitudes or warmer temperatures appear to mature and spawn
earlier than herring from northern or colder environments.
Ware and Tanasichuk (1989) reported that when SST were high
in British Columbia, herring tended to spawn
and mature
earlier and have a longer spawning duration. Tanasichuk and
Ware (1987) suggested that under warmer temperatures egg size
is smaller and fecundity is higher in herring. They further
suggest that such an adaptive trade-off tends to offset a
higher mortality/growth ratio under warmer temperatures.
The studies by Hay (1985), Ware and Tanasichuk (1989)
and Tanasichuk and Ware
results.
Our
study
(1987)
suggests
are consistent with our
that
herring
in
southern
latitudes with warmer temperatures tend to mature and spawn
at an earlier age and have a smaller size at maturity than
herring
from
temperatures.
latitudes
northern
This
geographic variation
is
water
pattern
of
life-history characteristics
of
consistent
in
colder
with
with
the
herring in the eastern Atlantic (Parish and Saville 1965).
Herring from southern latitudes in the eastern Atlantic
tended to mature earlier
(2-3 years old),
spawn during
summer-autumn, and have a smaller size at maturity than
herring from northern latitudes (winter-spring spawning, 3-9
years at maturity).
44
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48
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49
Chapter 2
Growth Variation in Herring (Clupea harengus pallasi)
in the Northeast Pacific.
50
Introduction
Variability in growth performance of individual fish
among populations of a single fish species often is more
pronounced among
populations that are widely separated
(Jonsson et al. 1991, L'Abee-Lund et al. 1989). Much of the
growth variation along latitudinal gradients is attributed to
differences in ambient temperature (Taylor 1958, Pauly 1980,
Beverton 1987). In some cases, temperature is regarded as an
indirect factor which influences the rate of photoperiod
response during seasonal changes in daylength (Clark et al.
1978). However, in the broader context of size differences
among poikilothermic vertebrates,
Bergmann's rule states
that, within a species races that inhabit colder areas tend
to be larger than races in warmer environments (Mayr 1956,
Ray 1960, Lindsey 1966).
In conjunction with size variation along a temperature
gradient,
Taylor
(1958)
postulated
that
fast
growing
poikilothermic animals often have shorter life spans and
conversely, animals attaining larger sizes, which are mostly
distributed in higher latitudes with colder environments,
grow more slowly and have longer life spans.
fishes, which are mostly poikilothermic,
Hence,
for
it appears that
individuals from populations in warmer environments should
51
have faster growth rates, but smaller asymptotic sizes and
than those in colder environments. As a consequence, along
temperature gradients there should be a negative relationship
between growth rate and asymptotic length
(Taylor 1958,
Beverton and Holt 1959, Holt 1960a, Beverton 1987).
the Northeast Pacific,
In
the geographic range of
herring (Clupea harengus pallasi) extends from California to
Alaska. Sea-surface temperatures in this latitudinal range
are generally highest in the south and decrease northward
(Wespestad 1991). Sea-surface temperatures in the Northeast
Pacific are often affected by oceanographic and climatic
events such as El Ninos that usually cause dramatic rises in
coastal water temperatures and have adverse
effects on
herring growth (Spratt 1987). Nevertheless,
differences in
the growth pattern among widely separated herring populations
in this region have received little attention.
The few
published studies have been limited in their geographic
scope. Trumble and Humphreys (1985)
(1983)
and Gonyea and Trumble
studied growth patterns of herring populations in
California and Washington respectively, but the study in
California was limited to single population. Also, Rounsefell
(1930) provides a larger scale comparison of growth among
herring populations from north to southeast Alaska.
Taylor
(1958,
1960)
suggested that the growth rate
parameter (K) from the von Bertalanffy growth model can be
used
to
examine
the
relationship between environmental
52
conditions and growth performance of fish. In this study we
explore differences in growth rate (K) and asymptotic length
(Lm) among herring populations within the northeast Pacific
including California,
Washington,
British
Columbia,
and
southeast Alaska, and examine the influence of sea-surface
temperature
(SST)
as
an
environmental
factor
governing
herring growth.
Material and Methods
The study area extends from California to southeast
Alaska, with 14 sites including four from southeast Alaska,
seven from British Columbia, one from Washington, and two
from California (Figure 2.1). One additional site at Yaquina
Bay, Oregon, was excluded from this study due to lack of
data.
The fish harvested from these sites are commonly
processed for their sac-roe. Length-at-age data for herring
from these sites were compiled from published and unpublished
technical reports of fisheries agencies in the Northeast
Pacific (Table 2.1). Data on sea-surface temperature (SST),
which were taken from the open-file of the U.S. Geological
Survey (1991-92, Menlo Park, CA), were only available for
Sitka, southwestern Vancouver Island, Strait of Georgia, and
San Francisco Bay (Figure 2.1, Table 2.1).
To estimate annual growth parameters for each site, mean
53
65 OON
Lynn Channel
.
.
60 00
Seymour Channel
BC
Prince Rupert
Sitka
C ntral Coast
Kahshakes
55 00
Strait of Georgia
North
Queen Charlotte
North
Western Vancouver Island
.
outh
.
'Cherry .
.;Poin
South
5000
WA- 45 00
40 00
Toma les Bay
: CA
.1
35 00
San Francisco Bay
:A
North Pacific Ocean
':
I
180 00W
170 00
I
160 00
I
150 00
I
140 00
I
130 00
I
120 00
Figure 2.1. Map of the Northeastern Pacific
spawning sites of herring used in this study.
i.2-30 00
-f:125 00
110 00
showing
Table 2.1. Location of spawning sites of Northeast Pacific herring and time periods of
length-at-age data and sea-surface temperature (SST).
Region
Southeast Alaska
1. Lynn Channel
2. Seymour Channel
3. Sitka Sound
4. Kahshakes
British Columbia-Washington
5. Prince Rupert
6. Southeast Queen Charlotte
7. Central Coast
8. Northwestern Vancouver Island
9. Northern Strait of Georgia
l0.Southern Strait of Georgia
11.Southwestern Vancouver Island
12.Cherry Point
California
13.Tomales Bay
14.San Francisco Bay
Latitude Longitude
SST'
(°C)
Time Period of Data"
(length-at-age)
58N 135W
N\A
N\A
1971,72,73,75,81,83
5714 13314
57°N 135)4
55°N 13114
53-5514
52-5314
51-5414
49 -51N
49-50*N
129-131)4
131-133)4
122-130)4
125-128)4
123-125)4
1971-81'
N\A
N\A
N\A
N\A
N\A
1971-80
1971-89d
1971-93e
1977-93
1972-80f
1971-80g
1972-80b
1971-80
48-49°N 123 -124'W
1971-80b
1971-80.
1971-79'
48-49°N 125-128)4
1971-80
N\A
1971-80
1976-86
38°N 122°W
N\A
3714 122)41
1973-81e
1972-76.
1973-85J
48'N 122)4
. Missing sea-surface temperature (°C) data:
'.1979,1980.h.The SST for this site were not included since the data were identical to northern Strait of Georgia site.`.1980.
. Missing length-at- age data:
d. 1976-80.*. 1983.'. 1972,1976.g. 1979.h. 1978,1979.'. 1973,1975'. 1979.
55
length-at-age data were fitted using the von Bertalanffy
growth model, which is regarded as an appropriately flexible
and accurate model for fitting
various forms of complex
datasets (Welch and McFarlane 1989, Vaughan and Kanciruk
1982). Studies of herring growth by Anthony and Waring (1980)
and
Gonyea
and
Trumble
(1982)
suggest
that
the
von
Bertalanffy model provides more accurate estimates than other
asymptotic models. The von Bertalanffy function for growth in
length is described by the following equation:
Lt=L.,(1-exp (-K ( t- to) )
)
where t denotes age, Lt denotes length at age, K is the
growth rate parameter,
and Lm is the average asymptotic
length. The non-linear regression routine NLIN of SAS (1985)
was used to fit the von Bertalanffy model to the mean length­
at-age data.
The iterative fitting process began with a
search for suitable initial values for K and Lm.
In addition to fitting the von Bertalanffy model to data
from each site for each year, we also fitted the model to 200
samples that were generated from the data set for all sites
and all years. Each sample contained 50 randomly selected
pairs of observed length and age data. This "bootstrap"
procedure (Efron and Gong 1983) provided estimates of the
relationship between
the growth parameter
(K)
and
the
56
asymptotic length (L) given the null hypothesis that the
separate populations shared the same growth parameters and
these parameters were constant through time. To summarize
what appeared to be a hyperbolic relationship between the
bootstrap estimates of K and
Lam,
the following
linear
regression model was fitted to the 200 pairs of estimates:
L,,,,,=a+b* (1 /K)
The growth parameters for the individual herring populations
were then compared to this average relationship between K and
L,
to
identify
populations
that
had
unusual
growth
parameters.
Pearson's correlation analyses were performed on the
annual estimates of K and Lop to detect growth synchrony among
the populations within each of three regions (Table 2.1). The
annual estimates of K and the annual estimates of L, were
compared among populations within each region. This procedure
was used to test whether interannual growth variation among
the populations within each region might have been caused by
common environmental factors acting region-wide. Correlation
analysis also was used to examine the relationship of mean
annual sea-surface temperature (SST) with growth rate (K) and
asymptotic length (kJ among the Sitka, southwest Vancouver
57
Island, northern Strait of Georgia and San Francisco Bay
sites.
Results
There was a strong nonlinear relationship between the
bootstrap estimates for K and Loo derived from the 200 random
samples taken from the complete data set (Figure 2.2). This
result demonstrates that random sampling alone will tend to
produce
inversely
related
estimates
and
K
for
L,
irrespective of the biological mechanisms postulated by
Taylor (1958). There was a 93% coefficient of determination
for the linear regression between the bootstrap estimates for
L0,
and 1/K,
and the data conformed well to the
rectangular hyperbola
(Figure 2.2).
fitted
The estimated growth
parameters for different populations within each geographic
region also showed inverse relationships between K and Lm
that were similar to the hyperbolic relationship observed in
the bootstrap estimates (Figures 2.3, 2.4, 2.5).
The separate correlation analysis of K (Table 2.2) and
L, (Table 2.3) between sites within each region showed few
Furthermore,
significant correlations among populations.
there was little consistency between the two analyses. For
example,
in
southeast
Alaska
there
was
a
significant
correlation between the annual estimates of K for Seymour
58
1
0.9­
0.8­
g 0.6­
0
"-I 0.5­
4-1
44
o 0.4­
0
0.3­
0
tiD 0.2­
0.1­
0
220
240
260
280
300
Lco
320
340
360
380
400
420
(rnm)
Figure 2.2. The relationship between growth coefficient (K)
the von
estimated using
(Lm)
and asymptotic
size
with
length
and
age
data
selected
Bertalanffy growth model
line
fitted
The
years.
and
randomly
from all sites
K(40-207.62)=11.282.
represents the hyperbolic curve
59
1.2
1
4i
z 0.8­
a)
-,--t
4
4-)
0.4­
3
O
P
LI
0.2­
0
200
220
240
260
La,
280
300
320
340
(min).
Figure 2.3. Relationship between von Bertalanffy growth
coefficient (K) and asymptotic size (Lm) estimated for
sites in the S.E. Alaska (Y=Seymour Channel, L=Lynn
Channel, S=Sitka, K=Kahshakes). The fitted line shown for
this
region represents
the
hyperbolic
curve
K(Lm­
207.62)=11.282.
60
0.7
0.6­
4) 0.5­
z
a)
a)
0
3
2 0.2­
0.1­
0
200
250
300
350
400
450
500
L. (mm)
Figure 2.4. Relationship between von Bertalanffy growth
coefficient (K) and asymptotic size (Lco)
estimated for
sites the British Columbia-Washington
region (Q=Queen
Charlotte, P=Prince Rupert,
C=Central Coast, 0=southern
Georgia,
of
Strait
N=northern
Georgia,
Strait. of
I=northwestern
Vancouver
V=southwestern Vancouver Island,
Island, W=Cherry Point). The fitted line shown for this
region represents the hyperbolic curve K(L,,-207. 62) =11.282.
61
0.8
0.7­
0.6­
0.5­
w
F
"r4
0.4­
(1-1
F
0
0.3­
0.2­
F
F
F
F
F
F
F
T
TF
0.1
220
225
230
235
240
245
250
F
255
260
265
270
LoD (mm)
Figure 2.5. Relationship between von Bertalanffy growth
coefficient (K) and asymptotic size (Lm) estimated for
sites in the California region (T=Tomales Bay, F=San
Francisco Bay). The fitted line shown for this region
represents the hyperbolic curve K(Lm-207.62)=11.282.
Table 2.2. Pearson correlation analysis among sites within each region based on annual
estimates of growth rate (K). P-values are marked by asterisks for P<0.05 (*) and P<0.01
(**)
I
Y
L
L
ISI
K
-0.67
(0.14)
0.88
(0.001)
-0.08
(0.80)
N=6
N=13
N=9
-­
-0.48
(0.42)
N/A
I
N
°I11/71/VI
P
C
-0.71
(0.12)
0.49
(0.26)
0.004
(0.99)
-0.39
(0.52)
0.51
(0.19)
0.15
(0.72)
-0.40
(0.32)
N=6
N=7
N=8
N=5
N=8
N=8
N=4
-0.10
(0.87)
0.21
(0.61)
0.57
(0.31)
0.05
(0.90)
0.25
(0.54)
-0.39
(0.34)
N=5
N=8
N=5
N=8
N=8
N=4
0.08
(0.86)
0.56
(0.44)
0.25
0.57
-0.49
(0.27)
-0.42
(0.34)
N=7
N=4
N=7
N=7
N=3
-0.07
(0.88)
-0.31
0.38
0.16
(0.64)
-0.19
(0.59)
N=7
N=I0
N=10
N=5
0.36
(0.43)
0.79
-0.30
(0.51)
N=7
N=7
N=4
0.23
(0.27)
-0.49
(0.15)
N=10
N=5
I
I
N=5
S
-
-0.05
(0.96)
N=15
Q
P
C
N
O
I
V
-
-
-
-
(0.03)
-
-0.51
(0.14)
N=5
T
0.20
(0.80)
N=5
of Georgia,
Legends: Y =Seymour Channel, L=Lynn Channel, S =Sitka, K=Kahshakes, Q=Queen Charlotte, P=Prince Rupert, C=Central Coast, N= Northern Strait
Cherry
Point,
F=San
Francisco
Bay,
T=Tomales
Bay.
O= Southern Strait of Georgia, I= Northwestern Vancouver Is!., V = Southwestern Vancouver Isl . , W =
Table 2.3. Pearson correlation analysis among sites within each region based on annual
estimates of asymptotic size (Lco). P-values are marked by asterisks for P<0.05 (*) and
P<0.01 (**).
Y
!Lis!
0.08
(0.87)
N=6
L
S
Q
C
N
O
I
V
-
0.51
(0.08)
N =13
-0.48
(0.42)
N =5
K
I
P
I
C
I N1011 I
\VI
-0.07
(0.86)
N=9
N/A
-0.21
(0.46)
N= 15
-0.37
(0.47)
N =6
0.14
(0.77)
N =7
0.08
(0.89)
(N =5)
0.16
(0.71)
-0.46
(0.43)
0.18
(0.66)
-0.31
(0.45)
-0.90
(0.10)
N=8
N=5
N=8
N=8
N=4
0.34
(0.40)
0.84
(0.07)
-0.22
(0.91)
0.43
(0.29)
0.83
(0.07)
N=8
N=5
N=8
N=8
N=4
0.06
(0.89)
N =7
0.38
(0.62)
-0.35
(0.44)
-0.07
(0.88)
N =7
-0.15
(0.68)
-0.09
(0.84)
N =7
0.31
(0.39)
0.41
(0.72)
N =3
0.80
(0.11)
N=7
N=10
N=10
N=5
0.05
(0.92)
0.97
(0.0003)
N=7
N=7
0.64
(0.36)
N =4
0.87
(0.06)
-
N=4
-
-
-0.19
(0.60)
N =10
--
N=5
0.72
(0.16)
N=5
T
0.11
(0.89)
N =5
Coast, N =Northern Strait of Georgia,
Legends: Y=Seymour Channel, L = Lynn Channel, S=Sitka, K = Kahsha kes, Q = Queen Charlotte, P= Prince Rupert, C = Central
=Southwestern
Vancouver
Isl.,
W
=Cherry
Point,
F
=San
Francisco
Bay,
T =Tomales Bay.
0= Southern Strait of Georgia, I= Northwestern Vancouver Isl., V
01
64
Channel and Sitka (r=0.88, P<0.001, Table 2.2), but there was
the
a relatively weak nonsignificant correlation between
annual estimates of Lm for these same populations (r=0.51,
P=0.08, Table 2.3). Hence,
it appears that the significant
correlations of the K values between these two sites may be
spurious, which suggests that similarities in herring growth
between the Sitka and Seymour Channel sites are not caused by
regional-scale environmental factors. Within the other two
regions, correlations for K and Lm were both significant only
for the southwestern Vancouver Island and southern Strait of
Georgia
in British Columbia
(r=0.79,
P<0.03
;
(r=0.97,
P<0.0003, respectively) which suggests that growth patterns
between these two populations tend to be synchronized and may
be influenced by common environmental factors.
In general, the results in Table 2.2 and 2.3 show little
evidence to suggest that regional environmental factors were
correlating growth patterns among herring populations within
each region over the time period covered by our study. The
observed interannual variation in growth parameters, at least
for most of the populations, may reflect the influence of
local rather than regional-scale
environmental factors or
simply random sampling error.
The scatterplots of K and Lm for southeast Alaska and
California regions (Figures 2.3, 2.4)
indicate that the sites
within
these
regions
appear
to
have
different
growth
parameters which may reflect a response to specific local
65
environmental conditions. For example, in southeast Alaska,
herring from Seymour Channel and Lynn Channel
on Figure 2.3)
(
"Y" and "L"
tend to have smaller values for Lm than
herring from the more southerly Sitka and Kahshakes sites
("S" and "K" on Figure 2.3). For the eight stocks in British
Columbia and Washington, the scatterplot of K and Lm values
closely
resembles
the
curvilinear relationship
for
the
bootstrap estimates (Figure 2.4). The annual estimates of
growth parameters for these populations are mostly clustered
along the fitted line which suggests these populations tend
to have a similar growth pattern. In California, differences
in growth parameters between San Francisco Bay and Tomales
Bay herring are clearly evident ("F" and "T" on Figure 2.5).
The San Francisco herring appear to grow faster
(higher K)
but reach smaller asymptotic size (Lm) than the Tomales Bay
herring.
The annual estimated growth parameters (K and Lm) were
combined across years into weighted averages using weights
that were inversely proportional to the estimated variances
(Table 2.4). Excluded from this averaging procedure were 14
pairs (K and Lm) with unusually high or low K values, which
were from the more northerly sites (Table 2.5). The weighted
average growth parameters for Seymour
Channel
and Lynn
Channel suggest that these herring from these sites have
66
Table 2.4. The weighted average estimates of von Bertalanffy
growth rate (K), asymptotic length (L6,), and age at Lt=0 (to)
for Pacific herring and annual mean sea-surface temperature.
The sites are ordered from north to south (Table 1.1).
Region
K
L6,
to
SSTa
(°C)
Southeast Alaska
Lynn Channel
Seymour Channel
Sitka
Kahshakes
0.15
0.17
0.19
0.24
223
229
275
265
-3.5
-3.0
-2.2
-1.8
N\A
N\A
British Columbia and
Washington
Prince Rupert
S.E.Queen Charlotte
Central Coast
Northwestern Vancouver Island
Northern Strait of Georgia
Southern Strait of Georgia
Southwestern Vancouver Island
Cherry Point
0.26
0.23
0.16
0.32
0.35
0.16
0.33
0.30
259
265
242
245
245
253
253
253
-1.0
-1.7
-1.9
-1.4
-1.5
-1.1
-1.1
-1.6
N\A
N\A
N\A
N\A
10-11
10-11
9-10
N\A
California
Tomales Bay
San Francisco Bay
0.21
0.30
248
233
-2.3
-2.1
N/A
7-8
N\A
12-131'
(N\A=Not available).
a Annual mean sea-surface temperature (°C).
Annual mean sea-surface temperature for the coastal water
of SanFrancisco bay area.
67
Table 2.5. Annual growth parameter estimates that were
considered to be outliers and were eliminated from
calculations of weighted averaged parameters and von
Bertalanffy growth curves.
Site
Year
Seymour Channel
1973
1974
0.41
0.38
219
218
Sitka
1974
1976
1981
0.40
0.40
0.60
218
234
219
Kahshakes
1990
1991
1992
1993
0.44
0.40
0.78
0.71
219
224
218
222
Prince Rupert
1978
0.06
361
Southwestern Vancouver Isl.
1978
1980
0.06
0.09
345
386
Washington (Cherry Point)
1976
0.65
246
68
smaller La, values than the Sitka and Kahshakes sites (Table
2.4). Within the southeast Alaska region K tends to increase
with decreasing latitude.
In the British Columbia-Washington region, the average
growth parameters are variable, with K ranging from 0.16/year
for the Central Coast and southern Strait of Georgia sites to
0.35/year for the northern Strait of Georgia site. La, is not
as variable as K, ranging from 242 mm for the Central Coast
site to 265 mm for the Queen Charlotte site.
In British
Columbia, herring from sites that are located in the north
appear to have smaller growth rates (K)
than herring from
more southern sites except the southern Strait of Georgia
(Table 2.4). However, these seven sites have roughly similar
La, values except for the Queen Charlotte stock, which has the
largest asymptotic size of all sites in the British Columbia-
Washington region (Table 2.4). In California, the Tomales Bay
herring tend to have a smaller average growth rate (K) but a
larger
asymptotic
length
than
the
San
Francisco
Bay
population (Table 2.4).
Von Bertalanffy growth curves were calculated for groups
of herring from California, British Columbia-Washington, and
north and southern S.E. Alaska. The growth parameters for
sites
within
averages.
each
group
were
In southeast Alaska,
combined
using
weighted
herring from the Seymour
Channel and Lynn Channel sites, which have low values for K
and Lm (Table 2.4), were combined as a northern group and
69
herring from the Sitka and Kahshakes sites were combined as
a southern group.
Herring from northern southeast Alaska (Seymour Channel,
Lynn Channel)
productive,
and the California group were
the
least
having the
lowest growth rate and smallest
asymptotic sizes (Figure 2.6).
Herring from the southern
southeast Alaska (Sitka and Kahshakes) and British Columbia-
Washington have larger asymptotic sizes.
We found no significant
correlation between annual
estimates of K and mean annual SST (r=-0.08, P>0.64; Figure
2.7). However, there was a significant negative correlation
between annual estimates of Lm and mean annual SST (r=-0.51,
P<0.001; Figure 2.8).
Discussion
Growth rate
length (La,)
study.
(K)
is negatively related to asymptotic
for herring from the 14 sites included in this
This is in agreement with studies on other fish
species (Beverton and Holt 1959, Taylor 1958,
However,
the
bootstrap
estimates
Holt 1960b).
from simulated random
samples demonstrate that such a relationship can result
simply from random sampling.
Lack of correlations between interanuual variation of K
and Lc, among most of the local populations suggests little or
70
300
250­
200­
E
E
.c
150­
cn
c
a)
_1
100
50­
5
1'0
1I5
20
25
Ito
Age
>K-- Seym.& Lynn
--A-- Sitka & Kahsh. ---x- California
--I-- B.C.& Wash.
Figure 2.6. Von Bertalanffy growth curves for northeast
Pacific herring. The growth curves are based on combined
weighted average K and L, values for herring from four
different groups including northern (Seymour Channel and
Lynn Channel) and southern (Sitka and Kahshakes) parts of
S.E. Alaska, British Columbia (Queen Charlotte, Prince
Rupert, Central Coast, northern and southern Strait of
Georgia, north and southwestern Vancouver Island, and
Cherry Point), and California (San Francisco Bay and
Tomales Bay).
71
0.6
N
0.55-
r=-0.08
P>0.64
S
N
0.5­
0.45­
S
S
F
V
0.4­
V
S
0.35­
N
V
N
V
VV
F
F
N
S
N
0.3­
F
F
N
0.25­
F
N
0.2­
N
F
S
0.15­
V
S
N
F
S
0.1
7
8
F
F
S
9
10
11
12
13
F
14
15
Mean Annual Sea-Surface Temperature (°C)
Figure 2.7. Relationship between mean annual sea-surface
temperature and annual estimates of growth coefficient (K)
for herring populations from Sitka (S), northern Strait of
Georgia (N), southwestern Vancouver Island (V), and San
Francisco Bay (F).
72
320
S
r=-0.51
P<0.001
V
300­
N
280­
S
Vs1
N
S
N
F
260­
V
a8
V
S
148
V vN
240­
F
NN
F
my
S
§
N
Ti
F
S
FF
S
220­
200
VVV
F
FF
F
F
7
8
9
10
11
12
13
14
15
Mean Annual Sea-Surface Temperature (°C)
Figure 2.8. Relationship between mean annual sea-surface
temperature and annual estimates of asymptotic size (Lm)
for herring populations from Sitka (S), northern Strait of
Georgia (N), southwestern Vancouver Island (V), and San
Francisco Bay (F).
73
no
effect
of
regional
environmental
factors
on
growth
variation within each region over the time period covered by
this study with the exception of the southwest Vancouver
Island and southern Strait of Georgia sites which showed
strong correlations in both K and L,. Harrison et al. (1983)
and Thomson et al.
(1989) describe the importance of runoff
water on biological productivity in this region. During late
spring, much of the freshwater runoff,
which is rich in
nutrients that support primary productivity, is supplied from
the Fraser River and other local rivers that flow first into
the Strait of Georgia, through the Juan de Fuca Strait, and
then to the southern portion of
west Vancouver
Island
(Thomson et al. 1989).
The weighted
average
asymptotic
for
the
size
San
Francisco Bay population was 233 mm, which is higher than
value (208) reported by Trumble and Humphreys (1985). The
weighted average Lc° (248 mm) for Tomales Bay is larger than
L0, of San Francisco herring. The estimated growth rates (K)
for the two California sites were similar to the values
estimated for sites in more northern latitudes
(Table 2.5).
The estimated growth rate (K=0.30 per year)
for the San
Francisco population is far below values (K=0.59 per year)
reported by Trumble and Humphreys (1985).
This discrepancy
may be due to the use of different types of data in the two
studies. In the Trumble and Humphreys study, the estimated
growth
parameters
were
based
on
a
set
of
individual
74
measurements of length and age (Trumble, Departmen of Fish
and Game Management,
whereas,
in
Washington, personal communication),
present
study,
the
the
estimated
growth
parameters were derived
from estimates of mean length-at­
age. Garland (1994)
showed that estimated von Bertalanffy
growth parameters depend on whether individual observations
or
averages
were
used.
Sainsbury
(1980)
infered
that
variability among the growth rates of individual fish often
resulted in underestimation of the average growth rate for
the whole population.
Indeed, when we estimated the von
Bertalanffy growth parameters from annual sets of individual
observations of length and age for San Francisco herring,
most of the estimated growth parameters ranged between 0.55­
0.67/year for K and 204-215 mm for Lm.
These values are
comparable to the values found in the Trumble and Humphreys
study. However, in the case of the Washington herring (Cherry
Point), the estimated growth parameters for the current study
were not very different from values reported by a previous
study
(Trumble
parameters,
1982),
even though the
reported growth
like those for San Francisco, were based on
individual length and age data (Trumble, Departmen of Fish
and Game Management, Washington, personal communication).
The estimated growth parameters for the herring from the
southeast Alaska were roughly similar to the values reported
by Funk (Alaska, Department of Fish and Game Management,
personal communiction). He estimated values for K and Lm for
75
0.204/year and 218 mm,
Seymour Channel of
for Sitka of
0.19/year and 263.5 mm, and for Kahshakes of 0.208/year and
261.6 mm, respectively. Funk's estimates were also based on
average
but
data,
length-at-age
Gompertz growth model.
were
fitted using the
For British Columbia populations,
Beverton (1963) reported that K ranged from 0.4-0.55\year and
46=270 mm for British Columbia herring.
These parameter
values, especially K, tend to be higher than most of the
estimated values from this study. This may be a reflection of
the higher productivity that occurred during 1950's and
1960's, which was reduced dramatically during later decades
by intense fishing activities
(Hourston,
1980).
However,
because length and age data were unavailable for individuals,
we cannot determine
whether the discrepancy between our
parameter estimates and those reported by Beverton is an
artifact of using different forms of data.
Herring
from
southeast Alaska had the
Lynn
Channel
and
Seymour
smallest
Lc,
Channel
in
relative to more
southern sites which appears to contradict Bergmann's Rule.
The Seymour Channel and Lynn Channel populations historically
have been characterized as being less migratory than other
southeast Alaska stocks with low productivity and small
individuals
(Fritz
Management,
Alaska,
(1930)
Funk,
and Wespestad
Department
of
personal
(1991)
Fish
communication).
and
Game
Rounsefell
in their studies of herring
populations in Alaska suggested that populations in the
76
northern part of Alaska, such as the Prince Williams and
Togiak populations, tend to reach larger sizes (Lm=360 mm,
Wespestad 1991) than populations in southeast Alaska. In our
study the asymptotic length (Lm) of herring tends to increase
from southern to northern latitude, except for Seymour and
Lynn Channels. It also appears that, with some exceptions,
herring in the south tend to grow faster than herring in the
north. Studies of Atlantic herring (Clupea harengus harengus)
(Beverton
1963,
Anthony
and Waring
1980,
Jennings
and
Beverton 1991) as well as of other fish species, including
tropical sardines
(Sardinops
sagax)
1960b), American pikeperch (walleye)
vitreum)
(Garland
1993,
Holt
(Stizostedion vitreum
(Beverton 1987), and brown trout (Salmo trutta)
(l'Abee-Lund et al. 1989, Jonsson et al. 1990) also indicate
that growth pattern varies with latitude.
Many studies have pointed to food availability as the
prime factor influencing growth variation among populations
(e.g., Cushing 1975, 1976; Fortier and Gange 1990). However,
a study on biological productivity in the Northeast Pacific
by Ware
and McFarland
(1989)
indicates
that,
although
biological productivity is lower in the offshore areas in
northern latitudes due to downwelling, the food resources
available in the coastal waters are roughly at the same level
as in coastal waters in southern latitudes where upwelling is
dominant. This suggests that food availability may not play
a significant role in influencing growth variation among
77
herring populations in the northeast Pacific. Hence, with the
exception of Seymour and Lynn Channels, the results from this
study are generally consistent with Bergmann's rule that
individual sizes tend to be larger in colder than in warmer
environments. This rule emphasizes the important influence of
temperature on growth. Documented studies on several fish
species
suggest that growth rates tend to
as
increase
temperature increases (Elliot 1975, l'Abee-Lund et al. 1989,
Jennings and Beverton 1991). Studies on brown trout from
streams in the Britain (Edwards et al. 1979), and American
pikeperch (walleye) (Beverton 1987) indicate that temperature
was the prime factor accounting for growth variation in these
species. The cause for this relationship may be different
energy requirements at different temperatures because the
standard metabolic rate in poikilothermic fishes tends to be
higher in warmer water than in cold water (Warren 1971).
In
this
we
study,
(r=-0.51,
correlation
found
a
negative
significant
P<0.001)
between
temperature
and
asymptotic length (La,). This is consistent with other studies
that have found a
similar relationship between
L, and
temperature for fish species such as cod (Gadus callariasa)
(Taylor
1958,
Holt 1960a),
American pikeperch
(walleye)
(Beverton 1987), and mackerel (Scomber scombrus) (Holt 1959).
However, we found no significant correlation between growth
rate
(K)
P>0.64).
and
annual
sea-surface
Studies by Taylor
(1958),
temperature
Holt
(1959,
(r=-0.08,
1960a),
78
Beverton (1987), and l'Abee-Lund et al.
(1989) found that
growth rate was positively related to ambient temperature. It
is possible that the reason for the lack of a significant
relationship in this study was the relatively low estimated
growth rate for San Francisco herring, which experience warm
water temperatures. When the data for San Francisco were
excluded from correlation analysis of K values with water
temperatures,
the
correlation
between
growth
rate
and
temperature increased (r=0.31) and the sign became positive,
but the correlation still was not significant (P>0.11).
One might suppose that biological characteristics such
as growth pattern could be used to help identify distinct
populations.
Grant
(1984)
and
Grant
and
Utter
(1984)
attempted to identify distinct stocks among Atlantic and
Pacific herring populations using electrophoresis and had
very little success. Eddy and Carlander (1940) postulated
that although differences in growth rate between species
could be accounted for by heredity, such differences within
a single species are mainly determined by environmental
variation. Experimental studies with transplanted fishes such
as sculpins (Cottus
clobig)
(Mann et al.
1984) and Arcto­
Norwegian cod (Godus morhua) (Godo and Moksness 1985, cited
in Beverton 1987) showed that biological characteristics of
the transplanted fish,
such as growth and reproductive
patterns, came to resemble those of the local populations.
For Atlantic herring and American
pikeperch
(walleye),
79
Jennings and Beverton (1991) and Beverton (1987) suggested
that intraspecific variation
in life-history traits are
mainly a manifestation of phenotypic plasticity induced by
local
environmental
conditions,
especially
ambient
temperature.
Based on the lack of geographical barriers among herring
populations in the Northeast Pacific and their ability to
make long-distance migrations and thus ensure gene flow among
populations, it would be reasonable to speculate that the
observed variations in life-history traits such as growth
performances are phenotypic expressions in response to local
environmental conditions, among which temperature seems to be
an important factor.
80
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Rounsefell, G.A. (1930). " Contribution to the biology of the
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Canadian Special Publication of Fisheries and Aquatic
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Ware, D.M. & McFarlane, G.A. (1989). Fisheries production
domains in the northeast Pacific ocean. In Effect of
84
ocean variability on recruitment and an evaluation of
parameters used in stock assessment models (Beamish,
Canadian Special
R.J. and McFarlane,
G.A., eds.).
Publication of Fisheries and Aquatic Science 108, 359­
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Warren, C.E. (1971). Bioenergetics and growth. In Biology and
Water Pollution Control (Warren, C.E., ed.), pp.135-167.
Philadelphia, London, and Toronto: Saunders Co.
Welch, D.W., & McFarlane, G.A. (1990). Quantifying the growth
of female Pacific hake (Merluccius productus): An
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parameter estimation. Canadian Journal of Fisheries and
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to eastern Berring sea oceanographic factors. Ph.D.,
Thesis. University of Washington.
85
Chapter 3
Geographic variation in recruitment of Pacific herring (Clupea
harengus pallasi) in the northeast Pacific.
86
Introduction
Despite extensive research on herring, the causes of
variation in abundances of herring populations remains poorly
understood (Wespestad 1991, Whitehead 1985). A large number
of distinct herring populations occur in the Pacific (Clupea
harengus pallasi) and Atlantic (Clupea harengus harengus)
Spratt 1980, Hay 1985,
Oceans (Schweigert 1991,
1988,
Cushing
Parish
1975,
and
Saville
Sinclair
Severe
1965).
fluctuations in Atlantic herring abundance has occurred and
in
some
cases
individual
populations
have
experienced
complete depletion at least once (Sinclair et al. 1985, Smith
1985, Burd 1990).
Herring in the northeast Pacific also have experienced
great variation in recruitment. Rounsefell (1930) documented
year-class variation
in Alaska herring
stocks from 1920-1927.
He suspected that air temperature was a factor causing
recruitment
variation
by
indirectly
influencing
food
productivity during the spawning season. Herring populations
in the eastern Bering Sea experienced a series of weak year-
classes during the 1980's, the weakest of which occurred in
1985 (Wespestad and Gunderson 1990). In southeast Alaska,
Zebdi
(1990)
found
that
recruitment
of
Sitka
herring
fluctuated severely during 1971-1989 and the weakest year­
87
class
occurred
in
1976.
The
herring
Cherry
Point
in
Washington have had three strong year-classes (1967, 1968,
1969) which dominated the period of peak abundance during the
early 1970's, and a subsequent weak recruitment period from
1970-73 which devastated herring production in the late
1970's (Trumble 1980). In British Columbia, large herring
production occurred from 1945-1965, and was followed by a
sharp decline in abundance from 1966-1968 (Hourston 1980).
Significant reduction in herring production in Tomales Bay
and San Francisco Bay,
especially in
resulted in
1990,
termination of fishing activities for herring in Tomales Bay
(Tom Moore, California Department of Fish and Game, personal
communication).
Various biological and environmental factors may be
responsible for variation in recruitment (Shepherd et al.
1984). Stocker et al.
(1985)
and Wespestad and Gunderson
(1990) suggested that some portion of interannual variability
in recruitment in Pacific herring is due to a density-
dependent relationship between recruitment
and parental
spawners. Zebdi (1990) found a positive relationship between
air
temperature
and
recruitment
of
herring
at
Sitka,
southeast Alaska. In British Columbia, Ware (1991) found that
sea-surface temperature and predation had negative effects on
recruitment. Wind driven onshore and offshore Ekman layer
transport had positive and negative effects, respectively, on
interannual recruitment of southwestern Vancouver Island and
88
Bering Sea herring populations (Stevenson 1962, Wespestad
1991, Wespestad and Gunderson 1990). As far as we know, no
specific study has been conducted on San Francisco herring to
evaluate the possible effects of environmental and biological
factors on recruitment variation.
The main objectives of this study were 1) to determine
geographical variation in recruitment among five herring
populations in the northeast Pacific, 2) and to determine the
effects of Ekman layer transport, sea-surface temperature,
and
sea-surface
salinity
interannual
on
variation
of
recruitment for each of the five herring populations.
Material and Methods
Time-series of herring recruitment data for
southwest Vancouver Island,
Sitka,
southern Strait of Georgia,
northern Strait of Georgia, and San Francisco Bay (Figure
3.1) were gathered from published and unpublished reports
from the Department of Fish and Game Management in southeast
Alaska,
California
Department
of
Department
Fisheries
of
and
Fish
Oceans
Game,
and
in
and
British
Columbia(Canada). The recruitment data for British Columbia
herring covers the period from 1951 to 1988, while for Sitka
and San Francisco the recruitment indices were available from
89
-65 DON
60 00
W
BC
Sift
,StrafteGeOmia
1-55 00
NOTO .
South
.
-
Southwestern Vancouver Island
50 00
*.
WA -4500
40 00
- .4.
CA
.1
35 00
N .
San Francisco Bay
:A
North Pacific Ocean
`---30 00
25 00
180 00W
170 00
160 00
150 00
140 00
130 00
120 00
110 00
for
Figure 3.1. Sites in the Northeast
Pacific selected
analysis of recruitment variation in herring.
90
1971-1990
and
1981-1992,
respectively
(Table
3.1).
Environmental data corresponding to recruitment years is
presented on Table 3.1.
Sea-surface temperature for all sites and sea-surface
salinity for four sites were obtained from the open files of
the U.S. Geological Survey (1991-92; Menlo Park, CA) which
includes data for sites in British Columbia
(Table 3.1).
Environmental data for the northern and southern Strait of
Georgia herring were collected at the Entrance Channel
station located southeast of Vancouver Island. Data from this
station have been used by Canadian researchers to evaluate
relationships between herring biological variables and sea-
surface temperature and salinity for both the southern and
northern Strait of Georgia herring populations (Daniel Ware,
personal communication, Department of Fisheries and Oceans,
Nanaimo, British Columbia, Canada).
Indices of Ekman layer transport were available only for
Sitka, southwest Vancouver Island, and San Francisco Bay. The
compiled indices of Ekman layer transport from 1947-67 were
based on monthly averages (Bakun 1973). From 1967-1990 the
Ekman transport data were collected by the National Marine
Fisheries Service, Pacific Grove, California, and expressed
as averages over six hour time periods based on cubic meters
of water transported perpendicular to the coast per second
per 100 meters of coastline. These six-hour Ekman transport
Table 3.1. Time periods for which recruitment and environmental data were
available for each site.
Area
R
EKT
SST
SSS
Sitka
1971-90
1968-87
1968-82b
N/A
Southwestern Vancouver
Island
1951-88
1948-85
1948-84
1948-84d
Southern Strait of
Georgia
1951-88
N/A
1948-82
1948-82
Northern Strait of
Georgia
1951-88
N/A
1948-82
1948-82
San Francisco Bay
1981-92a
1979-90
1979-86c
1979-86e
R=Recruitment, EKT=Ekman layer transport index, SST=Sea-surface temperature,
SSS=Sea-surface salinity.
N/A=Not available.
Missing data:
aRecruitment data for 1989, bSST for winter of 1979, cSST for winter of 1979,
dSSS for winter of 1975,1976, eSSS for all winter seasons.
92
indices were averaged for each month of the year from 1967 to
1990.
Since the spawning activities of herring at many sites
can
to
up
extend
three
months,
(September-November),
(December-February),
winter
spring (March-May), summer (June-August)]
Noakes 1991).
between
environmental data were analyzed by season
recruitment and
[fall
relationships
(Schweigert and
Because of missing values for sea-surface
salinity for October and November for San Francisco Bay, the
fall season for this site was not included in the analysis.
In
analysis
of
relationships
between
environmental
factors and recruitment, environmental factors were time-
lagged to correspond to the first year of life for each year-
class. Environmental variables for Sitka and British Columbia
sites were lagged three years since the herring at these
sites recruit at three years of age (Haegele and Schweigert
1985, Hay 1985). In San Francisco Bay, herring recruit at age
two (Spratt 1980), hence, environmental variables were lagged
two years.
Spurious correlations due
to
the effect
of
autocorrelation can mask the true relationship between
environmental variables and recruitment (Cohen et al. 1986,
Cohen et al.
1991).
To remove autocorrelation trends in
recruitment and in environmental factors, we utilized the
first-order differencing
Chatfield (1989)
(filtered)
and Cohen et al.
method
(1986).
suggested by
Since data on
recruitment indices for San Francisco Bay were available only
93
for a relatively short period (1981-1992), with missing data
for 1989, the filtering procedure was not possible for this
area.
Coefficients of variation
(CV)
for recruitment and
environmental variables for each season were calculated for
each area. Pearson's correlation analysis was performed to
evaluate relationships between recruitment and environmental
variables for both the unfiltered (original) and filtered
data set.
Correlations were considered significant at
a
<0.05. Annual anamolies for recruitment and Ekman layer
transport for Sitka,
southwest Vancouver Island, and San
Francisco Bay were computed as the actual value of a given
variable minus its long-term mean (Wespestad and Gunderson
1990, Castillo 1992).
Environmental variables with significant correlation
with recruitment were included in a simple linear regression
model to determine the magnitude of their individual effects
on interannual recruitment variation.
The utilization of
simple linear models was justified through a series of plots
which strongly
indicated
a
linear
relationship between
recruitment and some environmental variables.
The model
residuals were plotted against both predicted recruitment
values and environmental variables to determine if residuals
were normally distributed along the axes (Neter et al. 1989).
Through application of the Durbin-Watson test (D-test) (Neter
et al. 1989), the residual values from separate models of the
94
Significant
unfiltered and filtered data were compared.
values (a<0.05) from the D-test indicate successful reduction
in autocorrelations which justifies the use of the filtering
procedure (Neter et al. 1989). D-test was unnecessary for San
Francisco Bay since filtering procedure was not applied on
data for San Francisco Bay.
Results
A clear latitudinal pattern in recruitment variation is
not
apparent.
recruitment
The
occurred
highest
in
interannual
Sitka,
followed
variation
by
in
southwest
Vancouver Island (Table 3.2). Despite the proximity of the
northern and southern Strait of Georgia herring, the latter
population had higher variability in recruitment (Table 3.2).
The lowest variation in recruitment occurred at northern
Strait of Georgia and San Francisco Bay.
Variation in Ekman transport was highest during the
winter
in
both Sitka
and
San Francisco
Bay,
while
in
southwest Vancouver Island, the highest variation occurred in
spring (Table 3.2). The highest variation in sea-surface
salinity and temperature occurred during winter at all sites
(Table 3.2). Sitka, southwest Vancouver Island, and San
Table 3.2. Coefficient of variation for recruitment and environmental
factors at each
site.
Sea-surface
Salinity
Sea-surface
Temperature
Ekman
Transport
Area
Recruitment
W
S
SU
F
W
S
SU
F
W
Sitka
148
98
13
25
23
29
18
8
6
NA
Northern Strait
of Georgia
58
NA
NA
NA
NA
6
4
3
3.5
10
4
2
2
Southern Strait
of Georgia
91
NA
NA
NA
NA
6
4
3
3.5
10
4
2
2
Southwest
Vancouver
Island
101
49
91
62
16
19
6
5
12
3
2
1
2
San Francisco
Bay
63
88
38
25
16
17
10
4
8
27
10
11
NA
W=Winter, S=Spring SU=Summer, F=Fall.
NA=Not available.
S
SU
F
NA NA NA
96
Francisco Bay tended to have higher variation
in winter
temperatures than northern and southern Strait of Georgia.
The long-term seasonal means of Ekman transport (Table
3.3)
indicate
that
intense
onshore
transport
occurred
duringthe fall and winter at southwest Vancouver Island and
during the winter at San Francisco Bay. In Sitka, average
Ekman transport is directed onshore in all seasons, but it is
less intense during spring and summer (Table 3.3). Offshore
Ekman transport (upwelling) generally begins at the southern
end of the transition zone (45-50° N) with the minimum and
maximum at southwestern Vancouver Island and in the area
between
Cape
Blanco
and
Point
Conception,
respectively
(Parrish et al. 1981). Average SST was maximum at all sites
during the summer. The association of high SST with offshore
Ekman transport at San Francisco Bay and southwest Vancouver
Island appear counter intuitive since offshore transport is
usually
associated
with
upwelling
and
low
SST.
The
discrepancy may have resulted from using monthly means for
SST rather than daily SST.
Herring in San Francisco Bay spawn mostly during the
winter (i.e., end of November through January) (Spratt 1980).
For San Francisco Bay,
revealed
by
the only significant relationship
correlation
analysis
of
recruitment
and
unfiltered environmental data for each season was a negative
relationship between recruitment and Ekman transport during
winter (Figure 3.2C; r=-0.71, P<0.013). The fitted regression
97
Table 3.3. Seasonal averages of the unfiltered
environmental data for each site.
Ekman Transport (m3.sec-1.100m-1)
Area
Winter
Spring
Summer
Fall
Sitka
-146
-50
-9
-82
Southwest
Vancouver Island
-77
12
18
-60
San Francisco
Bay
-25
72
124
36
Sea-surface Temperature (e)
Winter
Spring
Summer
Fall
Sitka
4.9
6.9
12.5
9.4
Northern Strait
of Georgia
7.0
9.4
15.0
11.5
Southern Strait
of Georgia
7.0
9.4
15.0
11.5
Southwest
Vancouver Island
7.8
10.5
12.8
9.9
San Francisco Bay
10.9
12.7
15.9
13.8
Sea-surface Salinity(PPT)
Winter
Spring
Summer
Fall
Northern Strait
of Georgia
20
28
26
24
Southern Strait
of Georgia
20
28
26
24
Southwest
Vancouver Island
28.5
30
31
28.8
San Francisco
Bay
23.02
29.4
32.2
N/A
98
A
SITKA
15000
R2=0.23
10000
0
w
Ce
5000
.
0
ID
-5000
WAWM
0w
-15000
-20000
-40
-30
-20
-10
10
0
20
SPRING EKMAN TRANSPORT (FILTERED)
B
SOUTHWESTERN VANCOUVER ISLAND
6000
R2=0.26
4000
.
U.1
cc
LL1
1_2000
.
LL
1
Z
2
no
...
0
N
L.L1
m
.
IN
5 -2000
w
cc
w
cc
-4000
-6000
-2
1
SPRING EKMAN TRANSPORT (FILTERED)
Figure 3.2. Relationship between recruitment and spring
Ekman transport in Sitka (A), spring Ekman transport in
southwest Vancouver Island (B), winter Ekman transport
in
San Francisco Bay
(C),
and fall
sea-surface
temperature in northern and southern Strait of Georgia
(D, E). Except for San Francisco Bay, these regression
are based on filtered data.
C
99
San Francisco Bay
350
R2=0.51
LU
150
X 100
50
0
-100
D
-80
-60
-40
-20
0
20
40
WINTER EKMAN TRANSPORT (UNFILTERED)
Northern Strait of Georgia
6000
R2 =0.11
LU 4000
LI 2000
..
a
0
cc
tut) -2000
-4000
-1 5
E
-0.5
-1
0
0.5
1
FALL SEA-SURFACE TEMP. (FILTERED)
1.5
Southern Strait of Georgia
4000
MI
Ej 3000
OP
R2=0.16
U1
LLI 2000
J
LT-z--­
'
1000
.a
... .
II
I­
5 -1000
Ce -2000
-3000
-15
-1
-0.5
0
0.5
1
FALL SEA-SURFACE TEMP. (FILTERED)
(Figure 3.2. continued)
1.5
100
model indicated that 51% of recruitment variation in San
Francisco Bay herring is accounted for by winter Ekman
transport (Table 3.4). Although average Ekman transport was
onshore during winter (Table 3.3), in some years offshore
transport occurred. Anamolies for recruitment and winter
Ekman transport at San Francisco Bay show that weak year-
classes (1979,
1985, 1988-1990) coincided with years when
Ekman transport was offshore, while the three strong year-
classes (1980, 1984, 1986) occurred during years of strong
onshore Ekman transport (Figure 3.3).
Herring in Sitka spawn in the spring
(i.e.,
April
through May) (Haegele and Schweigert 1985). For Sitka, there
was no significant correlation between unfiltered recruitment
data and unfiltered Ekman transport during each season
(P>0.05). For the filtered data from Sitka, spring Ekman
transport was positively correlated with recruitment (Figure
3.2A;
r=0.47,
P<0.038).
The D-test indicated successful
reduction in autocorrelations using filtered data
(Table
3.4). The fitted regression model indicated that only 23% of
recruitment variation was accounted for by spring Ekman
transport
(Table 3.4).
At Sitka,
spring Ekman transport
(unfiltered) was onshore in each year for which data was
available.
Thus,
the
positive
relationship
between
recruitment and Ekman transport indicates that recruitment
tended to be greater in years when onshore transport was less
intense. At Sitka, the four strong year classes (1973, 1977,
Table 4. Regression models of recruitment and environmental factors at each site.
*.
a.
b.
c.
Area
Regression Model
R2
F
D -test
Sitka
R= 207.7 * (FET)a
0.231
0.035*
2.18*
Northern Strait of Georgia
R= -12024 * (FSSTF)b
0.112
0.009*
2.5*
Southern Strait of Georgia
R=-896 * (FSSTF)
0.160
0.041*
2.4*
Southwest Vancouver Island
R= -1206 * (FET)a
0.261
0.016*
San Francisco Bay
R= 109 - 1.8 * (UET)C
0.51
0.012*
Significant at a<0.05.
FET=Filtered Ekman transport during spring.
FSSTF=Filtered sea-surface temperature during fall.
UET=Unfiltered Ekman transport during winter.
2.21*
NA
102
San Francisco Bay
200 -'
7
150 -'
100 ­
afimffir
Asming
-=-7:
\\'1/4
-50-"
-150
84 85
YEARS
86
88
89
90
84 85
YEARS
86
88
89
90
82
83
.11111=1.1
79 80 81 82
83
79
80
81
60-/
40-."
20--/
-40-­
-60
Figure
3.3. Two-year lagged anamolies for year-class
strength and winter Ekman transport (unfiltered) at San
Francisco Bay.
103
1981, 1985) all occurred during years of less intense onshore
transport (Figure 3.4), however numerous weak year classes
also occurred during years of less intense onshore transport.
At southwest Vancouver Island, herring spawn during late
winter and early spring
(i.e.,
February through March)
(Haegele and Schweigert 1985). At this site no significant
correlations were detected between unfiltered Ekman transport
data and recruitment for each season (P>0.05). However, with
filtered data,
a significant negative correlation between
spring Ekman transport and recruitment was found
(Figure
3.2B; r=-0.48, P<0.03) and the D-test was significant (Table
3.4). In the fitted regression model, only 26% of recruitment
variation was accounted for by spring Ekman transport (Table
3.4). Anamolies for recruitment and spring Ekman transport
depict a mixed relationship between year-class strength and
Ekman transport (Figure 3.5). For example, Ekman transport
was onshore during years of both high recruitment (1951,
1956, 1961, 1970, 1972, 1973,1985) and low recruitment (1948,
1953,1954,
1950,
1962,
1963,
1977,
1978,
1979,1982).
Similarly, offshore Ekman transport occurred mostly during
years of low recruitment,
1976,
1967,
(1959,
1969,
1980,
1971)
1983,
(1952,
1984),
1957,
1964,
1965,
1966,
however there were years
when high recruitment coincided with
offshore Ekman transport (Figure 3.5).
Long-term average seasonal sea-surface temperatures in
the Northeast Pacific vary with latitude with the coldest
104
Sitka
1600
1400
1200
1000
0
800
E
600
Cr)
775
7
400
200
a)
0
7
1
-200
-400
&\
\i
I
\
I\
6869707172737475767778798081828384858687
Years
20
15
10
-10
-15
-20
-25
-30
68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87
YEARS
for year-class
Figure 3.4. Three-year lagged anamolies (unfiltered) at
strength and spring Ekman transport
Sitka.
105
Southwestern Vancouver Island
800­
\\
\\\
\\\
\\
\
600­
400-
'.
\\
\\`.\,\
\.\\
\\\ \\\\\
\\
\ \\.\\N,
..,
200-
\\
\'Ni
NI
-200--
0
\''
\ \ \\
:I
\ 01
\N.
\.\\,\\\
\N\\\\\
N\ \\\
\\\\\\N
\\\
,',\ N..
s\
\
N
;
i
\..Nk's
S,
s:\
\\
N'\
N
\
.
\\\\\
`
N\
\
,\
\\
111111111111111I1111111111111IIIIIIII
48 50 52 54 56 58 60 62 64 66 68 70 72 74 76 78 80 82 84
25
Years
20
15
10
5
0
-5
-10
-15
-20
-25
48 50 52 545 58 60 62 64s 68 70 72 74 76 78 80 82 84
Years
Figure 3.5. Three-year lagged anamolies for year-class
strength and spring Ekman transport
(unfiltered) at
southwestern Vancouver Island.
106
temperatures in the north and the warmest in the south (Table
3.3). Correlation analysis of both unfiltered and filtered
data for each season for Sitka, southwestern Vancouver Island
and San Francisco Bay revealed no significant association
between sea-surface temperature and recruitment (P>0.05).
For northern Strait of Georgia, a significant negative
correlation was detected between fall sea-surface temperature
and recruitment (Figure 3.2D; unfiltered r=-0.49,
P<0.03;
filtered r=-0.34, P<0.047). For southern Strait of Georgia,
the filtered data showed a significant negative correlation
between fall sea-surface temperature and recruitment (Figure
3.2E; r=-0.40, P<0.02). The D-test was significant for both
northern and southern Strait of Georgia (Table 3.4). However,
sea-surface temperature explains very little of the variation
in recruitment at these sites. The regression model indicated
that only 11% and 16% of recruitment variation in northern
Strait
of
respectively,
temperature
Georgia
were
and
southern
accounted
(Table 3.4).
for
Strait
by
fall
of
Georgia,
sea-surface
Analysis of the unfiltered and
filtered data for each season for four sites ( northern and
southern Strait of Georgia, southwest Vancouver Island, and
San Francisco Bay)
revealed no significant correlations
between sea-surface salinity and recruitment (P>0.05).
107
Discussion
A complexity of biological and environmental factors
operating at both local and regional scales affect herring
from the onset of spawning to maturation of progeny making it
difficult
to
isolate
variation
in
herring
individual
(Wespestad
causes
1991).
of
recruitment
Lasker
(1985)
described a variety of factors that are associated with
variation of herring recruitment. He suggested that factors
such as food availability during the first feeding period of
newly hatched larvae, competition for limited food, offshore
and onshore transport of larvae via Ekman layer transport,
predation, variation in herring egg production, and large
scale events such as El Nino are important factors which can
determine the success of herring recruitment.
Numerous
workers
have
suggested
that
recruitment
variation in marine fishes is influenced by Ekman transport.
Hjort (1914) evaluated year-class fluctuation in herring and
cod with emphasis on mortality during the early stages or
"critical period" due to poor feeding conditions.
(1926)
suggested that advection of eggs or
Hjort
larvae from
nursery grounds via ocean currents caused high mortality
during early stages of life. Parrish et al. (1981) postulated
that fish populations in areas of intense upwelling in the
Northeast Pacific reproduce during the winter when the
108
surface water is directed onshore, which helps maintain the
eggs and larvae in their nursery areas. Bakun and Parrish
(1980) and Parrish et al. (1981) suggest that a large portion
of natural mortality in pelagic fishes is caused by intense
offshore
transport,
through which eggs
and
larvae
are
passively displaced into unfavorable conditions in offshore
areas. They further postulate that the shift of spawning time
to the time of minimum intensity in offshore Ekman transport
is
an adaptive response of
pelagic
fishes
to minimize
mortality in the early stages of their life-history. Cury and
Roy (1989) define the "optimal environmental window" as a
window of opportunity within which the adverse effect of
Ekman transport on recruitment tends to be minimal.
The tendency for spawning to coincide with periods of
onshore Ekman transport appear to be consistent with the
"retention area" hypothesis developed by Iles and Sinclair
(1982).
Larval
retention
areas
determined
are
by
oceanographic features such as fronts and gyres within which
fish larvae are retained. Iles and Sinclair (1982) contend
that larger retention areas produce larger populations and
that annual changes in physical conditions in the retention
area are responsible for interannual recruitment variation.
Wespestad and Gunderson
(1990)
suggested that year-class
strength of herring in the eastern Bering Sea tended to be
strong
during years
of
low
velocity
transport. Taylor and Wickett (1967)
of
onshore
Ekman
and Stevenson (1962)
109
found that year-class strength in British Columbia herring
was positively associated with onshore water flow.
In our study we found that recruitment of herring at
three sites in the Northeast Pacific was influenced by Ekman
but the relative
transport during the spawning season,
importance of Ekman transport in accounting for interannual
variation in recruitment varied considerably among the sites.
In San Francisco Bay, where spawning occurred mostly during
winter, recruitment was negatively related to winter Ekman
transport,
which explained over
variation
in
recruitment.
50%
Strong
of
the
interannual
year-classes
in
San
Francisco Bay herring tended to occur during years of strong
onshore Ekman transport. In contrast, at Sitka and southwest
Vancouver Island, Ekman transport accounted for only 23% and
26% of recruitment variation,
respectively. At both San
Francisco Bay and
southwestern Vancouver
Island higher
recruitment tended to occur during years of onshore Ekman
transport. At Sitka, where Ekman transport is onshore all
year, recruitment was positively related to Ekman transport
with higher recruitment occurring during years when onshore
Ekman transport was less intense. Haldorson and Collie (1990)
suggested that the survival rate of newly hatched herring in
Sitka is higher during the years when larvae are transported
to the northern part of Sitka Sound via coastal currents
which are augmented by low intensity onshore Ekman transport.
In the Strait of Georgia, Stocker et al. (1985), through
110
application of a multiplicative, environment-dependent Ricker
spawner-recruit model,
found positive correlation between
spring monthly sea-surface temperatures and recruitment. They
postulated that moderate temperature tend to increase food
production and enhance egg and larval development. We found
correlation
no
of
spring
sea-surface
temperature
and
recruitment for Strait of Georgia herring. Instead we found
a
negative
between
correlation
fall
temperature
and
recruitment which accounted for 11% and 16% of recruitment
variation
northern
in
and southern
Strait
of
Georgia,
respectively. Perhaps fall temperature may reflect unsuitable
conditions for food production in the Strait of Georgia.
Harrison et al. (1983) found that during the fall the upper
20-50m of the water column seemed to have very low standing
stocks of major zooplankton species which are significant
food
items
in
the diet
of
larval herring
(Outram
and
Humphreys 1974). The main factor responsible for reduction of
food production was the level of discharge from the Fraser
River which was high during spring-summer as air temperature
increases and low in fall and winter when air temperature
decreases (Harrison et al. 1983, Thomson et al. 1989). The
low saline and nutrient-rich Fraser River water influenced
biological productivity as well as providing stability to the
water surface layer during the spring and summer seasons
(Harrison et al. 1983). Harrison et al. (1983) suggested that
by the beginning of fall, water temperature began dropping
111
the wind flow began to shift from a northeasterly to a
southeasterly direction, which caused entrainment of open
ocean waters from both south and north ends of the Strait,
creating tidal pulses and heavy turbulent mixing conditions.
We found no study that suggests an association between
recruitment of Pacific herring and sea-surface salinity.
Changes
in
sea-surface
salinity
usually
reflect
other
environmental changes including upwelling/downwelling
and
runoffs from local rivers and streams (Ware and Thompson
1991,
Castillo 1992).
In our study both unfiltered and
filtered data revealed no relationship between sea-surface
salinity and recruitment in herring from four sites.
112
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116
Whitehead, P. J. P. 1985. King herring: his place amongst the
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117
Summary
No latitudinal trend in length-and weight at-age was
found among herring populations in the northeast Pacific.
Seymour Channel in
Among the 14 sites, Lynn Channel and
southeast Alaska, central coast of British Columbia, and San
Francisco Bay and Tomales Bay in California had the smallest
herring. Among four sites for which environmental data were
there were
available,
significant negative
correlations
between first PC scores of size and Ekman layer transport and
sea-surface salinity.
In
contrast
to
body
the
size,
reproductive
characteristics of herring appeared to vary latitudinally.
Herring from the more southerly sites tended to mature at an
earlier age and smaller size and have a longer duration of
spawning than herring from more northerly sites. In addition,
spawning
is
initiated in November
in
California,
while
spawning does not commence until after January at more
northerly sites. There were significant negative correlations
between first PC scores of reproductive variables and Ekman
layer transport,
sea-surface temperature,
and
salinity.
Variation in life history characteristics of herring among
sites in the Northeast Pacific appears to be related to
variation of environmental conditions.
The
estimated von Bertalnffy growth
rate
(K)
was
118
inversely related to asymptotic length (Lm) for sites within
each geographic region. Lack of significant correlation in K
and
in Lm among herring populations within each region
suggested that growth patterns were not influenced by common
environmental factors operating on a regional scale. The
estimated asymptotic lengths (Lm) of herring from the Seymour
and Lynn Channel sites in southeast Alaska and San Francisco
Bay in California were the smallest among the 14
sites,
whereas herring from Sitka and Kahshakes, also in southeast
had the
Alaska,
Southern
Strait
largest
of
Lm.
Georgia
With the exception of the
site
British
in
Columbia-
Washington and the Tomales Bay site in California, growth
rates (K) appeared to be higher in populations from southern
than
northern
relationship
latitudes.
between
growth
There
was
no
significant
(K)
and
sea-surface
rate
temperature. However, asymptotic size
(Lm)
was negatively
related to sea-surface temperature. With the exception of the
Seymour and Lynn Channel sites, the northernmost stocks in
this study, the increasing trend in Lm from southern to
northern latitudes appeared to be consistent with Bergmann's
Rule which states that body size tends to be larger in colder
than in warmer environments.
Recruitment variation at three sites was related to
Ekman layer transport during the period of spawning. At San
Francisco Bay recruitment showed a
significant negative
correlation with winter Ekman transport which accounted for
119
50%
of recruitment variation as
determined by a fitted
regression model. At Sitka and southwestern Vancouver Island,
recruitment showed
correlation,
a
significant positive
respectively,
with
spring
and negative
Ekman transport.
Fitted regression models, however, indicated only 23% and 26%
of recruitment variation in Sitka and southwestern Vancouver
Island,
respectively,
are
accounted
by
spring
Ekman
transport. These results are consistent with the view that
recruitment of herring tends to be high during years of
onshore Ekman transport, especially in San Francisco Bay
where Ekman transport is onshore only during the winter. In
contrast, at Sitka, Ekman transport is onshore all year and
recruitment was higher during years of low intensity of
onshore transport.
Columbia,
Recruitment at two sites
in British
northern and southern Strait of Georgia, were
negatively correlated with sea-surface temperature
during
fall, which may reflect that low food availability at this
time. We found no significant correlation between recruitment
and sea-surface salinity at any site.
120
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Masters Thesis. University of Alaska, Fairbanks. 125p.
131
APPENDIX
Source of Biological Data
Region
Southeast Alaska
Larson, P. Unpublished biological data of Pacific herring (Clupea harengus
pallsi). Department of Fish and Game Management, Alaska,
Juneau.
British Columbia
Hourston, A.S. Summary tables for annual assessments of the status of
British Columbia herring stocks in the 1970's. Canadian Data
Report of Fisheries and Aquatic Science No. 250.
Hourston, A.S. British Columbia herring sampling data for the 1970-1980.
Canadian Data Report of Fisheries and Aquatic Science No.; 229,
230, 242, 243, 244, 245, 246, 247, 249.
Haist, V.,J.F. Schweigert, and D. Fournier. 1988. Stock assessments for
British Columbia herring in 1987 and forcast of the potential catch
in 1988. Canadian Manuscript Report of Fisheries and Aquatic
Science No. 1990.
Washington
O'Tool, M. Unpublished biological data of Pacific herring (Clupea harengus
pallsi). Department of Fish and Game Management, Washington,
Seattle.
Day, D. Unpublished biological data of Pacific herring (Clupea harengus
pallsi). Department of Fish and Game Management, Washington,
Seattle.
California
Spratt, J.D. Status of the Pacific herring (Clupea harengus pallasi) resource
in California from 1970-1980. California, Department of Fish and
Game.
Spratt, J.D. Biological characteristics of catch from the 1981-1986 for Pacific
herring (Clupea harengus pallasi) for roe fishery in California.
California, Department of Fish and Game, Marine Resource
Division.