CALIFORNIA STATE UNIVERSITY, NORTHRIDGE
THE INFLUENCE OF ENVIRONMENTAL VARIATION ON YEAR-CLASS
STRENGTH IN WHITE SEABASS, ATRACTOSCION NOBILIS, IN SOUTHERN
CALIFORNIA
A thesis submitted in partial fulfillment of the requirements
for the degree of Master of Science in Biology
By
Edwin Leung
December 2014
The thesis of Edwin Leung is approved by:
Michael P. Franklin, Ph.D.
Date
Mark A. Steele, Ph.D.
Date
Larry G. Allen, Ph.D., Chair
Date
California State University, Northridge
ii
ACKNOWLEDGEMENTS
First I would like to thank Dr. Larry G. Allen for his support and guidance throughout my
entire master’s thesis. For accepting me into his lab while knowing little about me, and
for letting me find my own path in the years to come. Thank you to Dr. Mark A. Steele
for giving me my start as an undergraduate and for the majority of what I know about
marine ecology, ichthyology, and statistics. Finally, a thank you to Dr. Michael P.
Franklin for support, jokes, and the grief we give each other, which made being in lab
very enjoyable.
Thank you to Jennifer Granneman for my first volunteer opportunity, exposure to
research, and what grunt work really is. Thanks to Heidi Block for the chance at reading
nearly a thousand otoliths, which came in handy later when it came to my thesis. To
Michael Schram, Barbara Sanchez, and Jeremiah Bautista whom have been with me since
the start, thank you for everything. Big thanks to Celeste Gottschalk for all her hard work
in helping me with data collection. To Parker House and JR Clark, thank you for all the
hilarious moments and good times, with many more years to come. For the fun times,
support, and all the Thai food, my time here would not be the same or possible without
Jennifer Smolenski and Ananda Ellis. To all the people I’ve met and friends I’ve made,
from both the marine and terrestrial side of the biology department, thank you.
Lastly this project would not have been possible without the otoliths that were collected
and archived by the efforts of past members of the Nearshore Marine Fish Research
Program and support from the Southern California Marine Institute. My graduate thesis
was made possible by the generous financial support provided by the California State
University, Northridge Research and Graduate Studies thesis support and the Association
of Retired Faculty memorial scholarship program.
iii
TABLE OF CONTENTS
Signature Page .................................................................................................................... ii
Acknowledgements ............................................................................................................ iii
Abstract ................................................................................................................................v
Introduction ..........................................................................................................................1
Materials and Methods .........................................................................................................8
Results ................................................................................................................................11
Discussion ..........................................................................................................................12
Literature Citied .................................................................................................................16
Appendix ............................................................................................................................26 iv
ABSTRACT
THE INFLUENCE OF ENVIRONMENTAL VARIATION ON YEAR-CLASS
STRENGTH IN WHITE SEABASS, ATRACTOSCION NOBILIS,
IN SOUTHERN CALIFORNIA
By
Edwin Leung
Master of Science in Biology
During warm climate events, growth rates can increase in fish, suggesting that
they benefit from the increase in sea surface temperature. Experienced around the world,
climate events such as El Niño Southern Oscillation and Pacific Decadal Oscillation can
greatly influence the growth of a species. Previous studies have shown that species of fish
can either thrive or dramatically decline during these shifts between warm and cool
phases. Proper management of fisheries requires information regarding the interaction
between a species and its environment.
White seabass (Atractoscion nobilis) is a prominent commercial and recreational
fishery species in Southern California. Largely attributed to overfishing, by 1982 the
population had dramatically declined and both fisheries collapsed. Recent studies have
shown signs that the native population is in recovery and may benefit from an El Niño
event through increased growth rates. I addressed the question, “do environmental
conditions cause variation in year-class strength in white seabass?”
This study determined the population structure of white seabass over a 12-year
period (1997 - 2008) and revealed that year-class strength was the greatest in 1996 and
v
1997. Reports of commercial landings for the species have shown a steady increase
following the strong 1997 El Niño event, suggesting a relationship between year-class
strength and commercial landings on a ten-year lag. Although year-class strength was
greatest around the El Niño event, it was not significantly correlated with sea surface
temperature or any climate index. Year-class strength estimation is an informative tool in
assessing population structure of a managed species over time. The information provided
in my study can inform fisheries, update management approaches, and help ensure the
persistence of white seabass as the marine environment continues to change.
vi
Introduction
Marine organisms have been sought out historically for food. Over time, fisheries
management was established to oversee the removal as demand and revenue increased.
Such management, however, has often failed, collapsing commercial fisheries, and
depleting native populations beyond what natural replenishment can make up for, due to
over-exploitation. The management of a species to ensuring from catch year to year is a
difficult business. Many fish species exhibit high interannual variability, dramatically
increasing or decreasing in abundance, such as has been seen in the Pacific sardine
(Sardinops sagax caerulea) and the northern anchovy (Engraulis mordax) (CisnerosMata et al. 1995). After years of fishing, many species around the world are now listed as
threatened and effective management more necessary than ever.
Off Southern California, there are several examples of established fisheries that
failed due to poor management. White abalone (Haliotis sorenseni), and abalone species
in general, were driven to near extinction through over-exploitation (Hobday et al. 2001).
The fishery for giant sea bass (Stereolepis gigas), an apex predator in the waters off
Southern California, collapsed in the latter half of the 20th century (Pondella & Allen
2008). Conservation efforts today are promising for some of these species that were
nearly driven to extinction.
The white seabass (Atractoscion nobilis) is an important species in commercial
and recreational fisheries in Southern California. This member of the croaker family
(Sciaenidae), reaches lengths up to 1.5 m, weights of up to 43 kg, and can live at least 20
years (Love 2011). Distribution of the species is throughout the west coast of North
America, extending from Alaska down to Baja California (Hervas et al. 2010). White
1
seabass are broadcast spawners, dispersing fertilized eggs that drift in the water column
for approximately 30 days (Aalbers 2008). Juveniles of the species prefer areas of
shallow water and sandy bottoms as nursery grounds (Allen & Franklin 1992). Field and
laboratory experiments have shown that the larvae and juveniles exhibit a preference for
structure, typically aggregating around macroalgae (Margulies 1989).
White seabass has been a commercial fishery species in Southern California since
the late 1800s and a popular recreational species since the mid-20th century (Hervas et al.
2010). A decline in their numbers was seen in the early 1900s and by 1982 caused the
commercial white seabass fishery to move operations offshore and abide by management
regulations. The decline in white seabass catch was dramatic and attributed to
overfishing, from a peak of 64,000 individuals in 1959 to 284 in 1978 (Vojkovich &
Reed 1983, Vojkovich & Crooke 2001).
Over the last few decades, the population of white seabass along the coast of
Southern California appears to be growing. There is little evidence that the development
of programs releasing hatchery raised young, which started in 1983, have contributed
much to this growth. On the other hand, the Marine Resource Protection Act in 1994
imposed restrictions by limiting fishing depth along the California coast and Channel
Islands in addition to the state wide ban in the use of gill and trammel nets, resulting in a
significant increase in white seabass numbers between 1995-2004 (Pondella & Allen
2008). White seabass commercial take was low in 1997 with 26 t and in 1998 greatly
increased to 70 t (CalCOFI 1999). Recent reports indicate that the combined commercial
and recreational catch during 2008 was 342 t (CalCOFI 2009), and increased slightly to
2
364 t in 2010 (CalCOFI 2011). The increase in catch during the 1997-1998 El Niño,
suggests that these climate events can boost population size.
Proper management of fisheries requires detailed information in order to make
meaningful decisions. Studies have argued that shifts in an ecosystem, alternating
between crashes and stable states, have important management implications due to the
loss of ecological and economical resources (Scheffer et al. 2001, Hsieh et al. 2010). One
alternative management approach is known as ecosystem-based management (EBM), a
method taking into consideration the interaction and relationship between a species and
the environment it resides in. For fisheries, ecosystem-based fisheries management
(EBFM) is a social-ecological approach that been purposed to be beneficial for the
Southern Californian coastline, with climate as an important consideration (Field &
Francis 2006). Californian fishermen have acknowledged that temperature is influential,
observing an increase in fish abundance particularly after a shift in climate (Scjolz et al.
2003).
In fisheries science, year-class strength is an index that uses measures of
abundance, survivorship, or recruitment rates to summarize the success of a species for a
given year (Landsman et al. 2011, Neuheimer & Gronkjaer 2012). Larval and juvenile
stages are arguably more susceptible to variations in the environment (Tolonen et al.
2003, Raventos 2009). Population structure can experience distinctive phases year to
year, shifting in relation to increases or decreases in sea surface temperature (Tolonen et
al. 2003, Lappalainen et al. 2009). Year to year variations in body size, growth rates,
even mortality in a population have been attributed to temperature (Ralston & Howard
1995, Watanabe & Yatsu 2004, Rätz & Lloret 2005). By organizing individuals into
3
cohorts, it has been revealed that specific age groups benefit the most from variation in
temperature, contributing the most to the overall fitness of the population through
increased growth and survival (Martinson et al. 2012). Year-class strength can be used
with tools such as population viability analysis (PVA) to measure species persistence or
sensitivity and elasticity analysis to model a population’s response to environmental
variability. Ideally, information gathered for conservation and management should
provide a greater understanding on both the individual and population level. For species
that are heavily exploited, life history information is sometimes sparse, but it is essential
to the development of effective management plans (Fairclough et al. 2011).
Physical oceanography of the Pacific Ocean is well documented, with two kinds
of major, recurring, climate events, El Niño Southern Oscillation (ENSO) and Pacific
Decadal Oscillation (PDO). ENSO has two opposite phases, El Niño and La Niña, which
are characterized of alternating warm and cool conditions, respectively. These phases
typically occur in intervals of 2 to 10 years, lasting between 12 to 18 months, with strong
events every 13 to 70 years (Lu et al. 1998, Thatje et al. 2008). During an El Niño event,
warm water currents from the equator shift northward along the southern California
coastline. El Niño’s dramatically change ocean water dynamics, causing both positive
and negative effects. Characteristics of ENSO events, for example, include an increase in
sea surface temperature (SST) and air temperature, a decrease in upwelling, and a change
in near shore currents (Davis 2000). PDO regimes last much longer than ENSO events,
about 20 to 30 years, where warmer SST caused by PDO is localized to the North Pacific.
Mechanisms for the PDO are relatively unknown, however characteristics are similar to
4
ENSO events, including variability in SST, wind patterns, and sea level pressure (Mantua
& Hare 2002).
Incorporating climate into ecosystem models shows promise, by accounting for
variability seen in populations and being able to attribute that variability to annual
climatic fluctuations, typically in temperature (Lima & Nyaya 2011). Climate events can
have strong impacts on early life stages, with residual effects lasting well into adult
stages (Jenkins 2005). Changes in temperature have been found to accelerate and even
inhibit the transition from larval, juvenile, and to adult stages (Green & Fisher 2004). A
decrease in growth in larval and juvenile fishes can increased mortality due to
underdeveloped mechanisms such as predator avoidance. Many species have specific
thermal tolerances, showing a temperature range where optimal conditions can increase
growth rates before peaking and decreasing in higher temperatures (Imsland et al. 1996,
Jonassen et al. 1998, Imsland et al. 2006, Handeland et al. 2008). These patterns suggest
that early life history stages are the most important when larval and juvenile fishes are
commonly found in shallow warmer waters compared to adults (McCauley & Huggins
1979). Growth and temperature have been intensely studied in marine science, extracting
great detail on the relationship between these two factors, but most studies have been
conducted over short time periods and in the laboratory. However, it has been shown that
long-term field studies are better suited in resolving the effect temperature has on growth
(Buckel et al. 1995).
Research involving otoliths has been used for multiple purposes such as age and
growth, chemical composition analysis, and evaluating environmental influences.
Otoliths are “ear stones” found in teleost fishes that are used in hearing and balance.
5
Otoliths are composed primarily of polycrystalline aragonite, which is a form of calcium
carbonate, with other elemental impurities incorporated through ambient sea water or diet
(Degens et al. 1969, Campana 1999). In the formation of an otolith, discernible rings can
be seen, in which the frequency and thickness of the rings can represent daily or annual
increments and summer/winter seasonal variation (Panella 1971, Black 2009).
Temperature is known to greatly affect otolith composition and growth rate. Fish
residing in low temperature environments have otoliths that are smaller in comparison to
otoliths of fish in warm temperature environments (Lombarte & Lleonart 1993, Otterlei
et al. 2002). Fish with slow somatic growth have otoliths that are consistently larger than
otoliths from fast-growing fish of the same size (Campana 1990, Casselman 1990).
Otolith growth and somatic growth, however, is generally well correlated, allowing
estimations of body size from known age and vice versa. Laboratory studies have shown
that otoliths from Herring (Clupea harengus) and Atlantic Cod (Gadus morhua) reared in
manipulated experiments increased in growth and deposition rate across a temperature
gradient (Otterlei et al. 2002, Folkvord et al. 2004). Changes to the environment brought
on by climate events can be physically seen in fish and are recorded as distinctive events
in their otoliths. Strong temperature fluctuations from an El Niño and La Niña have been
show to influence otolith growth rate respectively through distinct rings in the structure
(Lehodey & Grandperrin 1995).
The majority of publications based on otoliths since the early 1970s have focused
on the age and growth of fish. Otoliths have been used as proxy paleo-indicators in
conjunction with dendrochronology, the process of aging an organism by counting
growth rings that are formed. Age and growth studies have been an important part of
6
ichthyology by providing insight into life history and aiding stock assessments (Campana
& Thorrold 2001). Otolith microchemistry analyses have assisted in identifying inshore
habitats as important juvenile nursery grounds for many species (Swearer et al. 2003).
For over 40 years, otoliths have been used to help in understanding a population’s
dynamics with its environment, providing invaluable information for fisheries
management (Campana 2005).
The objective of my study was to assess the year-class strength in white seabass
and to address the question, “do environmental conditions effect variation in year-class
strength among cohorts in white seabass?” By using otoliths, I aged individuals to
determine year-class strength, thus providing insight into this species population structure
across time for an important species in commercial and recreational fisheries in Southern
California.
7
Materials and Methods
Otoliths used were collected as part of an independent assessment of the
abundance of juvenile white seabass off Southern California (Allen et al. 2007). Sagittal
otoliths that were whole and in good condition were used for aging. One hundred otoliths
were randomly sampled from each collection year, from 1997 to 2008 (n = 1200).
Length, width, and depth of each otolith were measured using Mitutoyo digital calipers
(± 0.01 mm) with weight recorded using an Ohaus Voyager Pro analytical balance (±
0.001 g). Otoliths were mounted on wooden blocks using commercially available
cyanoacrylate adhesive in preparation for cross-sectioning. A Buehler Isomet low-speed
saw equipped with two 0.3 mm diamond-edge blades was used to create 0.5 mm thick
cross-sections. Each section was mounted onto glass slides using Crystalbond 509
mounting adhesive and polished for clarity by alternating between 400 and 600 fine grit
sandpaper.
Cross-sections were digitally photographed using an Olympus SZX7 zoom stereo
microscope with a QImaging QICAM digital camera attachment. Aging of otoliths (to the
year) was based on two blind reads, i.e. having no prior knowledge of the fish itself, to
prevent biased estimates of age. If the initial and second read did not agree, a third read
was made to reach an agreement on age. Final age was taken as an average if an
agreement was not met after three reads. Reasonable assumption of annual bands will
follow an understanding of age validation established in Williams et al. 2007 and RomoCuriel et al. 2014. Translucent rings appear dark and opaque rings light when viewed by
reflected light against a black background. Each pair of opaque and translucent band is
8
often defined as one full year of growth (Chilton & Beamish 1982). Edge analysis was
also recorded to account for growth not represented by complete annual rings.
Aged individuals were organized into cohorts to represent the population’s age
structure based on birth years, which was determined by subtracting how old each
individual was when caught from the year it was caught. Due to sampling method, which
was size and age selective, only juvenile fish that were 5 years of age and younger were
used in the analysis. Due to the mesh size used, gillnets selected primarily for juvenile
white seabass and a few adults.
A growth curve was generated using the von Bertalanffy growth equation
1
, where lt = predicted length at time t, L∞ = maximum length predicted
by the equation, e = base of the natural log, t = time, t0 = the size at which the organism
would theoretically have been age 0, and K = the growth coefficient (instantaneous rate)
(Cailliet et al. 1996). Von Bertalanffy and length-weight relationships were determined
using Growth II v.2.1.2.51. The relationship between weight and length was fit to the
equation W = aLb, where W = weight in grams, L = total length in mm, and a and b are
constants. Using a traditional catch-curve regression (Ricker 1975), I conservatively
estimated annual mortality and survivorship for white seabass. Counts for each cohort
was adjusted for annual mortality using a modified equation for mortality and
, where N0 = number of fish in a year-
survivorship from Ricker (1975):
class at t = 0, Nt = estimated number of recruits at t years in the past, corrected for
mortality, and S = annual estimated survivorship (complement of mortality). Year-class
strength (annual recruitment index) was estimated by taking the average number of
individuals across age groups within each represented birth year. Only fish born after
9
1996 and before 2007 was used in the analysis, as this time period had the highest
resolution due to large numbers of fish in the samples that were born in those years.
To evaluate whether environmental conditions influenced year-class strength in
white seabass, I ran four separate regression analyses to assess if year-class strength was
influenced by sea surface temperature, El Niño Southern Oscillation, Pacific Decadal
Oscillation, and North Pacific Gyre Oscillation. Mean summer (June-August) sea surface
temperature was taken at the Scripps Pier though Scripps Institution of Oceanography’s
Shore Stations Program (shorestation.ucsd.edu) for the years 1996 to 2007. A
multivariate ENSO index was taken from the NOAA Earth System Research Laboratory
(esrl.noaa.gov/psd/enso/mei). The Pacific Decadal Oscillation index was taken from the
University of Washington Joint Institute for the Study of the Atmosphere and Ocean
(jisao.washington.edu/pdo). Lastly, the North Pacific Gyre Oscillation index was taken
from Dr. Di Lorenzo of Georgia Institute of Technology (o3d.org/npgo). All statistical
analysis was conducted using SYSTAT 13.1. Finally, time-lag comparisons were made to
assess if there was a relationship between year-class strength and commercial catch of
white seabass.
10
Results
Fifteen individuals from the original 1200 were excluded from the analysis due to
damaged otoliths. Sagittal otoliths from 1,185 individuals revealed a population structure
of fish primarily ages 1 to 5, with the oldest individual aged at 11 years (Figure 1).
During the 1997 – 2008 sampling period, the highest numbers of fish spawned occurred
in 1997, 2000, and 2004 (Table 1). 1,103 fish were used to calculate von Bertalanffy and
length-weight relationship for white seabass, excluding 85 fish that did not have
corresponding length and weight measurements. The predicted maximum length (L∞) was
1002.55, the growth coefficient (K) was 0.16517, and the theoretical size at age 0 (T0)
was -1.80054 (Figure 2). The relationship between length and weight (TL, mm, g) was W
= 0.0000180155L2.87237 (Figure 3). By estimating conservatively using catch-curve
regression, annual mortality (M) and survivorship (S) for white seabass was 0.6 and 0.4
respectively, with instantaneous annual mortality (-Z) at 0.991 (Figure 4).
Year-class strength was greatest in 1996 and 1997, which partly coincides with
the strong 1997-1998 El Niño (Table 2). Year-class strength was not significantly related
to mean yearly summer sea-surface temperature (r2 = 0.065 p = 0.42), despite a slight
negative relationship (Figure 5). Year-class strength also was not significantly correlated
with the Multivariate ENSO index (r2 = 0.004, p = 0.85, Figure 6), Pacific Decadal
Oscillation (r2 = 0.048, p = 0.49, Figure 7), and North Pacific Gyre Oscillation (r2 =
0.025, p = 0.62, Figure 8). Initial comparison suggested that commercial catch of white
seabass declined with increased year-class strength (Figure 9). By time lagging catch
data, commercial catch was positively correlated with year-class strength on a lag of ten
years (Figure 10).
11
Discussion
This study found no evidence of climatic effects on year-class strength. It is still
unknown if other abiotic factors or lesser-known climate indices can explain year-class
strength variability in the white seabass. Studies assessing year-class strength are
commonly based on annual sampling for larvae, juveniles, or aging a subsample of the
population to establish cohorts. For this study, catch-curve regression was used as it may
provide a more accurate estimate of year-class strength when compared to other methods
and considering the type of data collected (Tetzlaff et al. 2011). Catch curve regression is
able to detect very strong or weak year-classes, but is unable to detect small variations in
year-class strength through time. Further analysis or time lag manipulation was limited
due to the unavailability of year-class data for recent years. For example, otoliths
sampled were collected consecutively over 12 years from 1997-2008. From fish in their
birth cohort, year-class strength estimates have higher resolution for years 1997, 1998,
1999 and subsequently decreasing in confidence for later years. Thus, the lack of
evidence for year-class strength being affected by climate could be due to limited years of
data.
Other studies on the influence of environmental variability on various Southern
California species other than white seabass have shown mixed results. Yellowfin croaker
(Umbrina roncador) had highly variable year-class strength, decreasing after the 19971998 El Niño period (Pondella et al. 2008). Larval abundance of Pacific chub mackerel
(Scomber japonicus) was positively correlated with PDO, whereas jack mackerel
(Trachurus symmetricus) was negatively correlated with PDO. Rockfish (Sebastes spp.)
larval abundance was highly variable following multiple ENSO events (Hsieh et al.
12
2005). When observing larvae across time, through shifts in climate, exploited warmwater species have significantly higher variability in abundance and distribution when
compared to unexploited cold-water species (Hsieh et al. 2006, Hsieh et al. 2008, Hsieh
et al. 2009).
Similar in recreational importance to white seabass, kelp bass (Paralabrax
clathratus), barred sand bass (Paralabrax nebulifer), and spotted sand bass (Paralabrax
maculatofasciatus) are prominent species in the Southern California recreational fishery.
Spotted sand bass was found to exhibit a strong year-class due to an increase in annual
recruitment brought on by warmer sea surface temperature from an El Niño period (Allen
et al. 1995). Abundance of young-of-the-year P. clathratus and P. nebulifer were found
to be unrelated to any climate indices based on power plant entrapment monitoring data
(Miller & Erisman 2014). On the other hand, Hsieh et al. 2005 found that the abundance
of larval Paralabrax spp. was positively correlated with the Pacific Decadal Oscillation
index. The contrasting results in the two studies could be due to how year-class strength
is estimated, differences in sampling methods, or mathematical models used.
When evaluating fisheries impact or future catch for a species, year-class strength
estimation is often a key component, and its assessments can vary depending on the
methods used. Past studies have made estimates using mathematical formulas modified
from the traditional catch-curve regression (Ricker 1975). The term year-class strength
can refer to different aspects for a species or population; most commonly to represent
annual recruitment or total abundance. Estimations made around the world have had
fairly good success in explaining variation seen in fish species. In freshwater systems,
pikeperch (Stizostedion lucioperca) abundance was found to be negatively impacted by
13
wind indices as well as positively influenced by warm water surface temperatures,
resulting in weak and strong year-class strength respectively (Lappalainen & Lehtonen
1995). Northern cod (Gadus morhua) are a prime example of shifting year-class strength
in relation to fishing pressure, where weak year-class strength in the species was
correlated to a decline in eggs spawned in previous years, possibly from an unseen
increase in annual morality (Anderson and Rose 2001, Sinclair 2001). Fluctuations in cod
year-class strength have also been seen in response to changes in food availability
brought on by climate change (Beaugrand et al. 2003, Beaugrand & Kirby 2010a). This
phenomenon was coined the “gadoid outburst,” based on a dramatic shift in biomass and
recruitment. There is also evidence that with a high spawning stock biomass of cod, yearclass strength decreases when sea surface temperature increases, resulting in a negative
correlation (O'Brien et al. 2000).
Fluctuations in temperature can influence fish and invertebrate population, algal
density and reproduction, and recruitment rates. These changes can cascade down
through the trophic structure, increasing mortality rates through a collapse in the food
web. Takahashi et al. (2009) found that Japanese anchovy (Engraulis japonicus) benefit
from an increase in temperature while the population of Japanese sardines (Sardinops
melanostictus) declined due to a decrease in food availability. Increased catch per unit
effort (CPUE) has been seen to correlate to shifts in climate in various fish species.
Pacific herring (Clupea pallasii), Pacific saury (Cololabis saira), and Pacific halibut
(Hippoglossus stenolepis) were found to have increased growth rates and recruitment
during El Niño events, suggesting that the three species were influenced by warmer sea
surface temperature (Noakes & Beamish 2009). Previous studies on white seabass have
14
seen an increase in CPUE and juvenile abundance that could be attributed to the strong
1997 El Niño event in Southern California (Allen et al. 2007, Williams et al. 2007).
Results suggested that the year-class strength for white seabass was the greatest in 1996
and 1997, which agrees with the current study.
There is concern that the increase in white seabass abundance may not persist as
the positive influence from the 1997-1998 El Niño may begin to diminish. A question
remains as to whether a correlation exists between year-class strength and subsequent
commercial landings of white seabass. If so, year-class strength estimations could
conceivably be used to predict future commercial catch from year to year. The strong
year-class strength of white seabass around the 1997 El Niño is reflected in the gradual
increase in commercial landings on a 10-year lag. Interestingly, catch of white seabass is
made up primarily of individuals at least 10 years of age. The 2011-2012 annual review
of the white seabass management plan reports that half of the fish sampled commercially
were approximately 12.5 years old and likely 9 years old from the recreational fishery
(DFW 2013).
For many species around the world, changes in temperature brought on by shifts
in climate can influence abundance over time. Year-class strength estimation is an
informative tool for assessing population structure, which can be used to improve
management of fisheries. The results from this study provide insight into the cohort
structure of white seabass, which was largely unknown and deemed essential in the most
recent 2001 management plan. Information provided here can better inform fisheries and
update management approaches to ensure the persistence of the white seabass fishery as
the marine environment continues to change.
15
LITERATURE CITIED
Aalbers SA. 2008. Seasonal, diel, and lunar spawning periodicities and associated sound
production of white seabass (Atractoscion nobilis). U.S. Fishery Bulletin. 106(2):
143–151.
Anderson JT, Rose GA. 2001. Offshore spawning and year-class strength of northern cod
(2J3KL) during the fishing moratorium, 1994-1996. Canadian Journal of Fisheries
and Aquatic Sciences. 58: 1386-1394.
Allen LG, Franklin MP. 1992. Abundance, distribution, and settlement of young-of-theyear white seabass Atractoscion nobilis in the Southern California Bight, 1988-89.
Fishery Bulletin. 90: 633-641.
Allen LG, Hovey TE, Love MS, Smith JTW. 1995. The life history of the spotted sand
bass (Paralabrax maculatofasciatus) within the southern California bight.
CalCOFI Rep. 36: 193-203.
Allen LG, Pondella DJ, Shane MA. 2007. Fisheries independent assessment of a
returning fishery: Abundance if juveniles white seabass (Atractoscion nobilis) in
the shallow nearshore waters of the Southern California Bight, 1995-2005.
Fisheries Research. 88: 24–32.
Beaugrand G, Brander KM, A. LJ, Souissi S, Reid PC. 2003. Plankton effect on cod
recruitment in the North Sea. Nature. 426: 661-664.
Beaugrand G, Kirby RR. 2010a. Climate, plankton and cod. Global Change Biology. 16:
1268-1280.
16
Black BA. 2009. Climate-driven synchrony across tree, bivalve, and rockfish growthincrement chronologies of the northeast Pacific. Marine Ecology Progress Series.
378: 37–46.
O'Brien CM, Fox CJ, Planque B, Casey J. 2000. Fisheries: climate variability and North
Sea cod. Nature. 404(6774): 142-142.
Buckel JA, Steinberg ND, Conover DO. 1995. Effects of temperature, salinity, and fish
size on growth and consumption of juvenile bluefish. Journal of Fish Biology. 47:
696–706.
Cailliet GM, Love MS, Ebeling AW. 1996. Fishes: A Field and Laboratory Manual on
Their Structure, Identification, and Natural History. Waveland Press, Inc. 144-157
pp.
Campana SE. 1990. How reliable are growth back-calculations based on otoliths?
Canadian Journal of Fishery Aquatic Sciences. 47: 2219-2227.
Campana SE. 1999. Chemistry and composition of fish otoliths: pathways, mechanisms,
and applications. Marine Ecology Progress Series. 188: 163-297.
Campana SE, Thorrold SR. 2001. Otoliths, increments, and elements: keys to a
comprehensive understanding of fish populations? Canadian Journal of Fishery
and Aquatic Sciences. 58: 30-38.
Campana SE. 2005. Otolith science entering the 21st century. Marine and Freshwater
Research. 56: 485-495.
Casselman JM. 1990. Growth and relative size of calcified structures of fish.
Transactions of the American Fisheries Society. 119: 673-688.
17
Chilton DE, Beamish RJ. 1982. Age determination methods for fishes studied by the
groundfish program at the Pacific Biological Station. Department of Fisheries and
Oceans.
Cisneros-Mata MA, Nevárez-Martínez MO, Gregory Hammann M. 1995. The rise and
fall of the Pacific sardine, Sardinops sagax caeruleus girard, in the Gulf of
California, Mexico. CalCOFI Report. 36: 136-143.
Degens ET, Deuser WG, Hardrich RL. 1969. Molecular structure and composition of fish
otoliths. Marine Biology. 2: 105-113.
Department of Fish and Wildlife. 2013. White Seabass Fishery Management plan 20112012 Annual Review. Department of Fish and Wildlife. 1-6 pp.
Fairclough DV, Edmonds JS, Lenanton RCJ, Jackson G, Keay IS, Crisafulli BM,
Newman SJ. 2011. Rapid and cost-effective assessment of connectivity among
assemblages of Choerodon rubescens (Labridae), using laser ablation ICP-MS of
sagittal otoliths. Journal of Experimental Marine Biology and Ecology. 403: 46–
53.
Fisheries Review. 1999. Review of some California fisheries for 1998: pacific sardine,
pacific mackerel, pacific herring, market squid, sea urchin, groundfishes,
swordfish, sharks, nearshore finfishes, abalone, Dungeness crab, prawn, ocean
salmon, white seabass, and recreational. CalCOFI Report. 40: 9-24.
Fisheries Review. 2009. Review of selected California fisheries for 2008: coastal pelagic
finfish, market squid, ocean salmon, groundfish, California spiny lobster, spot
prawn, white seabass, kelp bass, thresher shark, skates and rays, Kellet’s whelk,
and sea cucumber. CalCOFI Report. 50: 14-42.
18
Fisheries Review. 2011. Review of selected California fisheries for 2010: coastal pelagic
finfish, market squid, ocean salmon, groundfish, highly migratory species,
Dungeness crab, spiny lobster, spot prawn, Kellet’s whelk, and white seabass.
CalCOFI Report. 52: 13-35.
Folkvord A, Johannessen A, Moksness E. 2004. Temperature-dependent otolith growth in
Norwegian spring-spawning herring (Clupea harengus L.) larvae. Sarsia. 89:297310.
Green DS, Fisher R. 2004. Temperature influences swimming speed, growth, and larval
duration in coral reef fish larvae. Journal of Experimental Marine Biology and
Ecology. 299: 115–132.
Handeland SO, Imsland AK, Steffansson SO. 2008. The effect of temperature and fish
size of growth, feed intake, food conversion efficiency and stomach evacuation
rate of Atlantic salmon post-smolts. Aquaculture. 283: 36–42.
Hervas S, Lorenzen K, Shane MA, Drawbridge MA. 2010. Quantitative assessment of a
white seabass (Atractoscion nobilis) stock enhancement program in California:
Post-release dispersal, growth and survival. Fisheries Research. 105: 237–243.
Hobday AJ, Tegner MJ, Haaker PL. 2001. Over-exploitation of a broadcast spawning
marine invertebrate: Decline of the white abalone. Reviews in Fish Biology and
Fisheries. 10: 493–514.
Hsieh C, Reiss CS, Watson W, Allen MJ, Hunter JR, Lea RN, Rosenblatt RH, Smith PE,
Sugihara G. 2005. A comparison of long-term trends and variability in
populations of larvae of exploited and unexploited fishes in the Southern
19
California regions: a community approach. Progress in Oceanography. 67: 160185.
Hsieh C, Reiss CS, Hunter JR, Beddington JR, May RM, Sugihara G. 2006. Fishing
elevates variability in the abundance of exploited species. Nature. 443: 859-862.
Hsieh C, Reiss CS, Hewitt RP, Sugihara G. 2008. Spatial analysis shows that fishing
enhances the climatic sensitivity of marine fishes. Canadian Journal of Fisheries
and Aquatic Sciences. 65: 947-961.
Hsieh C, Kim HJ, Watson W, Di Lorenzo E, Sugihara G. 2009. Climate-driven changes
in abundance and distribution of larvae of oceanic fishes in the southern
California region. Global Change Biology. 15: 2137-2152.
Hsieh C, Yamauchi A, Nakazawa T, Wang W. 2010. Fishing effects on age and spatial
structures undermine population stability of fishes. Aquatic Sciences. 72: 165178.
Imsland AK, Sunde LM, Folkvord A, Stefansson SO. 1996. The interaction of
temperature and fish size on growth of juvenile turbot. Journal of Fish Biology.
1996. 49: 926–940.
Imsland AK, Foss A, Sparboe LO, Sigurdsson S. 2006. The effect of temperature and fish
size on growth and feed efficiency ratio of juvenile spotted wolfish Anarchichas
minor. Journal of Fish Biology. 68: 1107–1122.
Jenkins GP. 2005. Influence of climate of the fishery recruitment of a temperate,
seagrass-associated fish, the King George whiting, Sillagiodes punctata. Marine
Ecology Progress Series. 288: 263–271.
20
Jonasen TM, Imsland AK, Steffansson SO. 1998. The interaction of temperature and fish
size on growth of juvenile halibut. Journal of Fish Biology. 54: 556–572.
Landsman SJ, Gingerich AJ, Philipp DP, Suski CD. 2011. The effects of temperature
change on the hatching success and larval survival of largemouth bass
Micropterus salmoides and smallmouth bass Micropterus dolomieu. Journal of
Fish Biology. 78: 1200–1212.
Lappalainen J, Lehtonen H. 1995. Year-class strength of pikeperch (Stizostedion
lucioperca L.) in relation to environmental factors in a shallow Baltic Bay.
Annales Zoologici Fennici. 32: 411-419.
Lappalainen J, Milardi M, Nyberg K, Venäläinen A. 2009. Effects of water temperature
on year-class strengths and growth patterns of pikeperch (Sander luciperca (L.))
in the brackish Baltic Sea. Aquatic Ecology. 43: 181–191.
Lehodey P, Grandperrin R. 1995. Influence of temperature and ENSO events on the
growth of the deep demersal fish alfonsino, Beryx splendens, off New Caledonia
in the western tropical South Pacific Ocean. Deep Sea Research. 43(1): 49–57.
Lima M, Naya DE. 2011. Large-scale climatic variability affects the dynamics of tropical
skipjack tuna in the Western Pacific Ocean. Ecography. 34: 597–605.
Lombarte A, Lleonart J. 1993. Otolith size changes related with body growth, habitat
depth and temperature. Environmental Biology. 37: 297–306.
Love M. 2011. Certainly More Than You Want to Know About The Fishes of The
Pacific Coast: A Postmodern Experience. Really Big Press. 393-396 pp.
21
Margulies D. 1989. Size-specific vulnerability to predation and sensory system
development of white seabass, Atractoscion nobilis, larvae. Fish. Bull., U.S.
87:537-552.
Manthua N, Hare SR. 2002. The Pacific Decadal Oscillation. Journal of Oceanography.
58: 35–44.
Martinson EC, Stokes HH, Scarnecchia DL. 2012. Use of juvenile salmon growth and
temperature change indices to predict groundfish post age-0 yr class strengths in
the Gulf of Alaska and eastern Bering Sea. Fisheries Oceanography. 21(4): 307–
319.
McCauley RW, Huggins NW. 1979. Ontogenetic and non-thermal seasonal effects on
thermal preferenda of fish. American Zoologist. 19(1): 267–271.
Miller EF, Erisman B. 2014. Long-term trends of southern California’s kelp and barred
sand bass populations: a fishery-independent assessment. CalCOFI Rep. 55: 1-9.
Neuheimer AB, Gronkjaer P. 2012. Climate effects on size-at-age: growth in warming
waters compensates for earlier maturity in an exploited marine fish. Global
Change Biology. 18: 1812–1822.
Noakes DJ, Beamish RJ. 2009. Synchrony of Marine Fish Catches and Climate and
Ocean Regime Shifts in the North Pacific Ocean. Marine and Coastal Fisheries:
Dynamics, Management, and Ecosystem Science. 1: 155–168.
Otterlei E, Folkvord A, Nyhammer G. 2002. Temperature dependent otolith growth of
larval and early juvenile Atlantic cod (Gadus morhua). ICES Journal of Marine
Science. 59: 401-410.
22
Pannella G. 1971. Fish otoliths: daily growth layers and periodical patterns. Science.
173(4002): 1124-1127.
Pondella II DJ, Allen LG. 2008. The decline and recovery of four predatory fishes from
the Southern California Bight. Marine Biology. 154: 307–313.
Pondella II DJ, Froeschke JT, Wetmore LS, Miller E, Valle CF, Medeiros L. 2008.
Demographic parameters of yellowfin croaker, Umbrina roncador (Perciformes:
Sciaenidae), from the southern California bight. Pacific Science. 62(4): 55-568.
Ralston S, Howard DF. 1995. On the development of year-class strength and cohort
variability in two northern California rockfishes. Fishery Bulletin. 93: 710–720.
Rätz HJ, Lloret J. 2005. Long-term variability of growth and recruitment of cod (Gadus
morhua) off Greenland. ICES Journal of Marine Science. 62: 1310–1321.
Raventos N. 2009. Relationships between population size, recruitment, and year-class
strength in a labrid fish in the Mediterranean Sea. Estuarine, Coastal, and Shelf
Science. 85: 167–172.
Ricker WE. 1975. Computation and Interpretation of Biological Statistics of Fish
Populations. Bulletin. Fisheries Research Board of Canada. 191, 382 pp.
Romo-Curiel AE, Herzka SZ, Sosa-Nishizaki O, Sepulveda CA, Aalbers SA. 2014.
Otolith-based growth estimates and insights into population structure of White
Seabass, Atractoscion nobilis, off the Pacific coast of North America. Fisheries
Research. 161: 374-383.
Scheffer M, Carpenter S, Foley JA, Folke C, Walker B. 2001. Catastrophic shifts in
ecosystems. Nature. 413: 591-596.
23
Scholz A, Bonzon K, Fujita F, Benjamin N, Woodling N, Black P, Steinback C. 2004.
Participatory socioeconomic analysis: drawing on fishermen’s knowledge for
marine protected area planning in California. Marine Policy. 28: 335-349.
Sinclair AF. 2001. Natural mortality of cod (Gadus Morhua) in the Southern Gulf of St
Lawrence. ICES Journal of Marine Science. 58: 1-10.
Swearer SE, Forrester GE, Steele MA, Brooks AJ, Lea DW. 2003. Spatio-temporal and
interspecific variation in otolith trace-element fingerprints in a temperate
estuarine fish assemblage. Estuarine, Coastal and Shelf Science. 56: 1111-1123.
Takahashi M, Watanabe Y, Yatsu A, Nishida H. 2009. Contrasting reponses in larval and
juveniles growth to a climate-ocean regime shift between anchovy and sardine.
Canadian Journal of Fisheries and Aquatic Sciences. 66: 972–982.
Tetzlaff JC, Catalano MJ, Allen MS, Pine WE. 2011. Evaluation of two methods for
indexing fish year-class strength: Catch-curve residuals and cohort method.
Fisheries Research. 109: 303–310.
Thatje S, Heilmayer O, Laudien J. 2008. Climate variability and El Niño Southern
Oscillation: implications for natural coastal resources and management.
Helgoland Marine Research. 62(1): 5-14.
Tolonen A, Lappalainen J, Pulliainen E. 2003. Seasonal growth and year class strength
variations of perch near the northern limits of its distribution range. Journal of
Fish Biology. 63: 176–186.
Watanabe C, Yatsu A. 2004. Effects of density-dependence and sea surface temperature
on interannual variation in length-at-age of chub mackerel (Scomber japonicus) in
the Kuroshio-Oyashio area during 1970-1997. Fishery Bulletin. 102: 196–206.
24
Williams JP, Allen LG, Steele MA, Pondella II DJ. 2007. El Niño periods increase
growth of juveniles white seabass (Atractoscion nobilis) in the Southern
California Bight. Marine Biology. 152: 193–200.
25
APPENDIX
Figure 1. Cross-sectioned sagittal otoliths of juvenile white seabass (Atractoscion
nobilis) representing ages 1-6.
26
1996
88
10
11
4
3
116
Age
1
2
3
4
5
Total
27
150
1997
80
42
16
11
1
89
1998
39
29
16
2
3
86
1999
51
16
10
7
2
143
2000
52
55
34
1
1
91
2001
30
46
12
3
65
2002
10
35
17
2
1
97
2
2003
50
32
13
130
2004
46
69
12
3
69
2005
16
38
15
89
2006
47
42
24
2007
24
Table 1. Cohort structure of white seabass (Atractoscion nobilis) for the 1996-2007 sampling period based on n =
1185 individuals representing ages 1-5.
1200
Total Length (mm)
1000
800
600
400
200
0
0
1
2
3
Age
4
5
6
Figure 2. Relationship between age and total length (mm) for Atractoscion
nobilis (n = 1103, r2 = 0.5081).
9000
8000
Weight (g)
7000
6000
5000
4000
3000
2000
1000
0
200
400
600
800
Total Length (mm)
1000
Figure 3. Relationship between total length (mm) and weight (g) for
Actractoscion nobilis (n = 1103, r2 = 0.8932).
28
1200
7
6.5
6
Frequency (ln)
5.5
5
4.5
4
3.5
3
2.5
2
0
2
4
6
Age
Figure 4. Catch-curve regression for relationship
between age and frequency (ln), based on n = 1185
individuals. R2 or instantaneous annual mortality (Z) 0.991.
29
1997
80
200
500
1250
3125
1031
1996
88
220
550
1375
3437.5
Strength 1134.1
Age
1
2
3
4
5
30
502.613 657.263 670.15 190.313 128.875 610.156 291.813
1998
1999
2000
2001
2002
2003
2004
39
51
52
30
10
50
46
97.5
127.5
130
75
25
125
115
243.75 318.75
325
187.5
62.5
312.5
287.5
609.375 796.875 812.5 468.75 156.25
718.75
1523.44 1992.19 2031.25
390.625 1953.13
Table 2. Mortality corrected year-class strength estimates for the 1996-2007 cohorts.
52
2005
16
40
100
82.25
2006
47
117.5
24
2007
24
1200
23
1000
22
800
21
600
20
400
19
200
18
0
17
Mean Yearly Summer SST (°C)
Year-Class Strength
A.
96 97 98 99 00 01 02 03 04 05 06 07
Year
B.
1200
Year-Class Strength
1000
800
600
400
200
0
19
20
21
22
Mean Yearly Summer SST (°C)
23
Figure 5. A) Estimated year-class strength (corrected for mortality) of Atractoscion
nobilis, 1996-2007, compared to mean yearly summer sea-surface temperature. B)
Relationship between mean yearly summer sea-surface temperature and year-class
strength (n = 12, r2 = 0.065, p = 0.424).
31
A.
2
1200
Year-Class Strength
1
800
600
0
400
-1
200
0
Multivariate ENSO Index
1000
-2
96 97 98 99 00 01 02 03 04 05 06 07
Year
B.
1200
Year-Class Strength
1000
800
600
400
200
0
-2
-1
0
Multivariate ENSO Index
1
2
Figure 6. A) Estimated year-class strength (corrected for mortality) of Atractoscion
nobilis, 1996-2007, compared to multivariate El Niño Southern Oscillation index. B)
Relationship between multivariate El Niño Southern Oscillation index and year-class
strength (n = 12, r2 = 0.004, p = 0.855).
32
A.
2
1200
Year-Class Strength
1
800
600
0
400
-1
200
0
Pacific Decadal Oscillation Index
1000
-2
96 97 98 99 00 01 02 03 04 05 06 07
Year
B.
1200
Year-Class Strength
1000
800
600
400
200
0
-2
-1
0
1
Pacific Decadal Oscillation Index
2
Figure 7. A) Estimated year-class strength (corrected for mortality) of Atractoscion
nobilis, 1996-2007, compared to Pacific Decadal Oscillation index. B) Relationship
between Pacific Decadal Oscillation index and year-class strength (n = 12, r2 = 0.048, p =
0.493).
33
1200
3
1000
2
800
1
600
0
400
-1
200
-2
0
-3
North Pacific Gyre Oscillation Index
Year-Class Strength
A.
96 97 98 99 00 01 02 03 04 05 06 07
Year
B.
1200
Year-Class Strength
1000
800
600
400
200
0
-3
-2
-1
0
1
North Pacific Gyre Oscillation Index
2
3
Figure 8. A) Estimated year-class strength (corrected for mortality) of Atractoscion
nobilis, 1996-2007, compared to North Pacific Gyre Oscillation index. B) Relationship
between North Pacific Gyre Oscillation index and year-class strength (n = 12, r2 = 0.025,
p = 0.622).
34
1200
700000
1000
600000
500000
800
400000
600
300000
400
200000
200
100000
0
Commercial Landings (lb)
Year-Class Strength
0
96 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13
Year
Figure 9. 1996-2013 commercial landings for white seabass (red) compared to
1996-2007 year-class strength (black).
1200
700000
2007
Year-Class Strength
500000
800
400000
600
300000
400
200000
200
100000
0
Commercial Landings (lb)
600000
1000
0
96 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13
Year
Figure 10. Comparison between 2006-2013 commercial landings (red) and 19962007 year-class strength (black) for white seabass, fitted with time lag of 10
years.
35