CALIFORNIA STATE UNIVERSITY, NORTHRIDGE

AGE, GROWTH AND GENETIC DIVERSITY OF ,

GIGAS

A thesis submitted in partial fulfillment of the requirements For the degree of Master of Science in Biology

By

Holly A. Hawk

August 2013

The thesis of Holly Hawk is approved:

Dr. Virginia M. Oberholzer Vandergon Date

Dr. Cindy S. Malone Date

Dr. Michael P. Franklin Date

Dr. Larry G. Allen, Chair Date

California State University, Northridge

ii

TABLE OF CONTENTS

Signature Page ii

Acknowledgements iv

List of Tables v

List of Figures vi

Abstract vii

Introduction 1

Methods and Materials 6

Results 11

Discussion 13

Literature Cited 25

Appendix I: Haplotype Summary Table 31

Appendix II: Images of Selected Otoliths 32

iii ACKNOWLEDGMENTS

This study would not have been possible without the help and support of many people. Dr. Larry Allen gave me the opportunity to pursue a master’s degree. He has supported me and taught me to grow a thick skin. I would like to thank Dr. Gini

Vandergon for agreeing to serve on my committee and for nourishing my love of science education. I also thank her for giving me countless opportunities to educate others. I appreciate the support and guidance of my other committee members, Drs. Michael

Franklin and Cindy Malone. Dr. Franklin spent many hours answering many questions.

Dr. Malone has not only had invaluable input but has been incredibly supportive and always makes me laugh. Of course, none of this would have been possible without the love and support of my friends and family. I am so incredibly lucky to be surrounded by such wonderful people.

iv LIST OF TABLES

Table 1. Mitochondrial control region universal primers for Stereolepis gigas………………………………………...…………………...…………..19

Table 2. Results of the AMOVA among sampling locations of Stereolepis gigas..19

Table 3. FST values of Stereolepis gigas ………...…………………….…………..19

Table 4. ANCOVA for age and length relationships between Stereolepis gigas collected in California and Mexico...... 20

Table 5. Sample size of Stereolepis gigas at individual collection sites in the Southern California Bight...... 20

v LIST OF FIGURES

Figure 1. Sampling locations of Stereolepis gigas in California and Mexico...... …21

Figure 2. Haplotype Network of California and Mexico Stereolepis gigas .……....22

Figure 3. Transverse cross section of left sagittal otlolith of oldest verified Stereolepis gigas...... 22

Figure 4. Age at length frequencies and growth rate of Stereolepis gigas …...……23

Figure 5. Haplotype distribution of Stereolepis gigas within five-year age bins demonstrating the distribution of rare haplotypes among age classes...... 23

Figure 6. Standard lengths and age frequencies between Stereolepis gigas in California and Mexico...... 24

vi ABSTRACT

AGE, GROWTH AND GENETIC DIVERSITY OF GIANT SEA BASS, STEREOLEPIS GIGAS

By

Holly Hawk

Master of Science in Biology

The giant sea bass, Stereolepis gigas, is a large predatory fish that inhabits the southern California kelp forest community. S. gigas is a critically endangered species, yet little is known about its life history. A more complete knowledge of the life history of this once commercially viable fish is necessary before an effective management strategy can be proposed. Giant sea bass were collected through collaborative efforts with commercial fish landings, scientific gill-netting, and through catch-and-release methods employed by recreational fisherman. A total of 59 samples were used for both mitochondrial DNA and age-and-growth analysis. Genetic analysis of the mitochondrial control region indicated gene flow among all sampling sites, no phylogeographic structure, as well as low haplotype (h) and nucleotide diversity (π). Sagittal otoliths were cross sectioned and analyzed with digital microscopy techniques, resulting in the verification that S. gigas is a long–lived species growing to at least 76 years of age. The

-0.041(t+0.839) calculated von Bertalanffy growth function (lt= 2048.4(1-e ) for S. gigas was also characteristic of a slow growing, apex predator. Long-lived species that are slow to reach maturity often have a low resilience to over-fishing, therefore it is of paramount

vii importance that we continue to collect essential life history data on this species in order to more effectively protect and manage the S. gigas population.

viii INTRODUCTION

Fisheries provide a valuable food commodity, with over 80 million tons of fish caught commercially every year (Watson and Pauly, 2003). However, global catches began declining in the 1980s (Pauly et al., 2002) including the decline of large predatory species which have been suggested to have been fished down to only 10 % of their pre- industrialized fishing biomass (Myers and Worm, 2003). As larger predatory species decline, smaller fish species and invertebrates are often targeted in a practice known as

“fishing down the foodweb” (Pauly et al., 1998). The decline of large predators can result in fisheries targeting progressively smaller species of fish in a trophic system, thus decreasing the overall abundance of several species within an ecosystem.

Exploitation of a single fishery threatens not only the targeted species but the biodiversity of the marine ecosystem that species inhabits (Molloy et al., 2009). The removal of apex predators has profound effects on ecosystems through top-down effects, where the lack of a large carnivore or keystone predator elicits population explosions of herbivores resulting in kelp deforestation in temperate climates (Steneck et al., 2002).

Tropical ecosystems also benefit from biodiversity as coral reef habitats are shown to be more resilient to major disturbances and have decreased coral disease when fish biodiversity is high (Raymundo et al., 2009). Lack of biodiversity is associated with decreased productivity in marine systems and decreased ability to recover from abiotic and biotic perturbations (Worm et al., 2006). These perturbations include but are not limited to resource exploitation such as overfishing, habitat destruction and loss, pollution and effects on marine ecosystems from global climate change (Worm et al.,

2006).

1 Management and conservation of marine fisheries requires the consideration of many factors and consequent comprehensive data collection. Such factors may include, but are not limited to, age and growth data (Cailliet et al., 1996), interspecific interactions

(Jackson et al., 2001), stock structure and genetic variation (Rhodes et al., 2003) and species-specific life history traits (Pinsky et al., 2011). Large marine fish that are long- lived are particularly susceptible to over-exploitation (Reynolds et al., 2005) and recovery of a population after a decline can take well over a decade to even several decades, if at all (Hutchings, 2000; Russ and Alcala, 2004). The resilience of any population of fish and its subsequent recovery depends on a suite of variables, many of which will be species specific such as the longevity and growth rate of individuals, fecundity, larval duration and age at maturation. Russ and Alcala (2004) suggest that it may take 15 to 40 years for a predatory fish population protected by marine reserves to recover fully.

The giant sea bass is the largest teleost megacarnivore found in the southern

California kelp forest community, and was recently verified to reach at least 62 years of age (Allen and Andrews, 2012). Historically, giant sea bass are distributed from

Humboldt Bay into southern Baja California and the Sea of Cortez. Populations are concentrated south of Point Conception in shallow rocky reefs along the southern

California coast and offshore islands. Giant sea bass were commercially and recreationally sought after for most of the 20th century. Commercial fishers first attained giant sea bass by hand line then switched to gill netting, significantly decreasing their numbers in California. Commercial landings in California peaked at 115 metric tons in

1932 and then drastically declined. Mexican commercial landings remained higher as

2 California stocks declined, but fell below 200,000 pounds in 1964 (Domeier, 2001).

Commercial and recreational fishing depleted giant sea bass stocks to the point that a moratorium was declared in 1982. Although they are restricted from being targeted, commercial vessels are allowed to retain and sell one individual per trip as incidental catch. Giant sea bass caught in Mexican waters are allowed to be landed and sold in

California markets, however the limit is two fish per trip per angler. There are no commercial or recreational restrictions on giant sea bass in Mexico today (Baldwin and

Keiser, 2008). In 1994, gill netting was banned within three miles of mainland California and one mile from the Channel Islands. Following the commercial and recreational restrictions placed on giant sea bass and the closure of near-shore gill nets, recent reports indicate that S. gigas are returning to the Southern California Bight (Crooke, 1992;

Pondella and Allen, 2008).

Very little verifiable data has been collected on the life history traits of giant sea bass. Gaffney et al. (2007) suggest sex ratios of S. gigas are approximately 1:1, indicating that giant sea bass are not sequential hermaphrodites. A previous study on two widespread species also in the wreck fish family, americanus and P. oxygeneios confirmed that both species are not hermaphroditic, although some studies have suggested otherwise (Roberts, 1989). California Department of Fish and Game

(Baldwin and Keiser, 2008) have stated that females of the species mature between 7 and

11 years of age, however that estimate is unverified as there is no study confirming age at maturity. There is no estimate for age at maturity in males. A disparity in age at maturity between sexes could result in a skewed sex ratio favoring either sex (Lovich, 1990). A sex ratio favoring females could also explain previous findings of high haplotype

3 diversity and low nucleotide diversity (Domeier, 2001) given the matrilineal nature of mitochondrial inheritance. Mitochondrial molecular markers are particularly informative for evolutionary relationships between populations but an individual inherits mitochondrial DNA maternally.

Age and growth information is essential to the management of recreational and commercial fisheries and must be considered when assessing the status of a fishery

(Craig et al.,1999). A majority of age and growth data on S. gigas are estimates that are either poorly documented or unverifiable. Allen and Andrews (2012) are among the first to provide age data using bomb radiocarbon dating techniques. Radiocarbon dating of giant sea bass confirmed a 227 kg specimen to be 62 years of age, indicating that previous estimates that this species lives 100 years may be unsubstantiated (Allen and

Andrews, 2012). In the current study, I seek to provide a larger data set on the age and growth of this species as it is vital to the effective management of this exploited population. I also aim to confirm that this long-lived species has a slow growth rate (k), increasing its susceptibility to over-fishing. Furthermore, I intend to combine age and growth data with molecular analysis to determine if rare haplotypes are distributed equally among old specimens (>30 yrs) and young specimens (<30yrs).

Genetic diversity within populations of endangered species has been found to be lower than in populations of closely related species who are not endangered (Avise,

2004). Kenchington et al. (2003) suggest that genetic diversity not only enables a population or a community to remain adaptable to both natural and anthropogenic pressures, but that maintaining genetic diversity is paramount in any management strategy (Kenchington et al., 2003). Genetic variation should be taken into consideration

4 for fishery management as populations that have been reduced or become isolated have an increased risk for inbreeding (Caballero et al., 2009). Inbreeding depression increases the risk of extinction, particularly for species that are already threatened (O'Grady et al.,

2006). This study addresses genetic diversity of Stereolepis gigas in California and

Mexico by replicating the methods of Gaffney et al. (2007) to amplify the highly variable mitochondrial (mtDNA) control region (Gaffney et al., 2007). The mtDNA control region is the most variable region of the mitochondrial genome and has been extensively used to determine intraspecific genetic variation (Simon, 1991; Baker and Marshall, 1997;

Crochet, 2000). Mitochondrial markers are often applied in stock assessments by determining if there are shared or derived haplotypes among seemingly disjunct populations. The high variability due to a rapid rate of mutation within the control region makes it an excellent candidate for testing the connectivity and genetic variation of populations. The current genetic diversity of giant sea bass was expected to reflect a loss of variability due to over-fishing. I tested the following hypotheses:

H1: The giant sea bass population is panmictic with shared haplotypes in California and

Mexico;

H2: The genetic variation among sites will reflect no phylogeographic structure;

H3: The haplotype diversity (h) and the nucleotide diversity (π) will reflect a population that has recently experienced a bottleneck event, rapidly expanded and accrued mutations.

5

MATERIALS & METHODS

Genetic Diversity

The control region from mitochondrial DNA was sequenced to determine the genetic diversity of individuals collected at various locations off the coast of southern

California and Baja. Mitochondrial DNA is commonly used in phylogenetic studies and has been used to successfully differentiate populations and taxonomic groups of teleost fish at a species level. The mitochondrial control region is involved in the replication and transcription of mtDNA, however it is a neutral molecular marker (Avise, 2004). The control region is also commonly referred to as the displacement or d-loop region and is a hyper-variable, non-coding region found between the tRNAThr and tRNAPhe genes (Cheng et al., 2012). The reduced functional constraint of the control region is thought to result in a more rapid rate of evolution, making it a useful marker for population level studies (Lee et al., 1995). The control region consists of three domains; domain I, the central domain and domain II. The central domain is more highly conserved but the rapid rate of evolution in domain I and domain II make it an excellent candidate for intraspecific population studies (Saunders and Edwards, 2000). The amplified sequences in the current study are in the first domain of the control region, flanking the tRNAPro gene where nucleotide diversity is high and intraspecific relationships can be delineated (Lee et al.,

1994).

Archived specimens of Stereolepis gigas were obtained from the Natural History

Museum of Los Angeles and from the Scripps Institution of Oceanography. Fresh

6 specimens were collected through collaborative efforts with the Santa Barbara Fish

Market (SBFM). Brian Colgate, the owner of SBFM contacted us when giant sea bass were brought to market as incidental catch. The frozen heads were then transported to

California State University Northridge for processing. This arrangement allowed us to visually verify that specimens were the correct species. Samples were also collected through catch-and-release by local recreational fisherman. These fishermen were supplied with the necessary tools to take fin clips from live specimens and store them in vials of

100% ethanol. All gill filaments and cheek tissue are now archived (stored and frozen in either 90% isopropyl alcohol or 100% ethanol) in the Nearshore Marine Fish Research

Program’s laboratory at California State University Northridge. DNA was extracted from all tissue samples using DNeasy Blood and Tissue kits (Qiagen, Valencia, CA, USA).

Approximately 25mg of fin clips or gill filaments were lysed overnight in 180µl buffer

ATL and 20µl proteinase K. Proceeding steps in DNeasy tissue bench protocol were followed according to the manufacturer’s instructions. The mitochondrial control region was amplified via the polymerase chain reaction (PCR). PCR was performed in an

Applied Biosystems GeneAmp 9700 thermocycler with an initial denaturing step 95 °C for 5 min followed by 30 cycles of 30 s at 94 °C, 30 s at 48 °C, 30 s at 72 °C, and a final extension step of 72 °C for 10 min with universal primers for teleost fish for the control region previously used for the serranid, Paralabrax clathratus (Table 1). PCR products were purified and sequenced by Laragen Inc. (Culver City, CA). Nucleotide sequences were downloaded directly from Laragen (www.laragen.com) and aligned in Sequencher, then visually examined. Once points of variation were verified manually, sequences were exported in to Arlequin (Excoffier et al., 2005) to calculate pairwise nucleotide

7 differences, nucleotide diversity, an AMOVA (Analysis of Molecular Variance) and average nucleotide composition. Network 4.6.1.1 (fluxus-engineering.com) was used to construct a median-joining network based on haplotype pairwise differences (Bandelt et al., 1995) (Figure 1). I used DNAsp version 5.10.1 to calculate haplotype diversity (π) with default settings (Librado and Rozas, 2009).

Age and Growth

Sagittal otoliths were extracted from Stereolepis gigas heads obtained from the

SBFM between January 2010 and May of 2013 (n = 38). Head length (mm) was measured from the tip of the premaxilla bone to the tip of the operculum on each specimen. Otoliths were also obtained from specimens collected between 2006 and 2010 during a juvenile white sea bass gillnet survey conducted by Allen et al. (2007) for the

Ocean Resource and Hatchery Enhancement Program (n = 21) where standard lengths were recorded. Once extracted, sagittae were cleaned in 100 % ethanol, rinsed with deionized water and stored in padded envelopes. Each otolith was weighed using a digital scale to the nearest 0.1 mg. Width and length of both the left and right sagittal otolith were then measured and recorded to the nearest 0.01 mm using digital calipers. Length measurements were taken along the longest axis, perpendicular to the sulcus while width was measured across the shortest axis parallel to the sulcus.

Two methods of otolith sectioning were used in this study. In the first method, otoliths were embedded in epoxy mold (mixture of 20 grams of 20-3068RCL15 epoxy resin with approximately 4 grams of CAT.190CL13 catalyst). Each otolith was then placed sulcus side up into a preparatory pool and covered in epoxy. The otolith was then

8 removed from the preparatory pool, air pockets were removed and the otolith was placed into the mold sulcus side down and parallel to the length of the mold. The otolith sat in the mold for 24 hours before being removed from the mold tray and 72 hours before sectioning the otolith within the epoxy mold. A small batch (n=18) was sectioned using a

Buehler-Isomet double-bladed low speed saw and was visually inspected for any signs of cracking or breakage. Many otoliths were sectioned successfully, however breakage occurred so other protocols were explored for mounting the otoliths safely without threat of cracking during the sectioning process.

The second sectioning method followed that of Craig et al. (1999), where a cyanoacrylate adhesive was used to mount epinephelid otoliths to wood blocks. This method proved to be successful for giant sea bass otoliths as well and was employed for the remaining otoliths not sectioned in epoxy (n=41). The remaining otoliths were then mounted to approximately 5cm x 2.5cm x 1cm blocks with a fast-drying gel cyanoacrylate adhesive and allowed to set for 48 hours. A 0.5 mm section through the nucleus of the otolith was cross-sectioned using a Buehler-Isomet double-bladed low speed saw (Allen et al., 1995). Sections were mounted on glass slides with Crystalbond®

509 adhesive (SPI supplies, www.2spi.com) and polished with 3M® Wet/Dry 1000 grit sandpaper, proceeded by 3M® Wet/Dry 500 grit sandpaper by hand.

Slides were placed in a black bottom Petri dish and digitally photographed using

Image Pro 6.3 under a Wilde dissecting scope. Each photograph was calibrated according to the magnification at which it was imaged and annulus formations were identified and marked with Image Pro 6.3 Editing software. A total of 59 individuals were aged by viewing digital images along an established axis in the dorso-medial sulcus region

9 (Figure 2). Each otolith was read blindly by the author and Larry G. Allen (CSUN), and a consensus age was established for any aged otoliths where the readers were in disagreement. Head lengths (mm) were converted to standard lengths (mm) for each sample represented only by a head based on the equation: SL = (0.2822*HL) + 11.345

(R² = 0.9985) (L.G. Allen, unpublished data). The relationship between age (yr) and length (mmSL) data was estimated using the von Bertalanffy growth curve (von

Bertalanffy, 1957) in Vonbit (version 2005). An analysis of covariance (ANCOVA) was run in Systat v.13 to determine if variation in size and length of individuals differed between sampling sites in Mexico and California.

10

RESULTS

Genetic Variation

A total of 59 mitochondrial control region sequences were analyzed to determine the haplotype diversity within and among sampling sites (Figure 1). A 533 base-pair region of the mitochondrial D-loop was amplified, however only a 423 base-pair region was used for analysis (average composition = 21.29% cytosine, 29.78% thymine, 35.70% adenine and 13.24% guanine). Sequence data revealed four variable sites, all of which are transitions, resulting in four separate haplotypes. Of these haplotypes, one was common

(exhibited in 54 individuals) and found at all five sampling sites. The remaining three haplotypes were exhibited in only four individuals, two of which were found exclusively in Mexico while the third was prevalent in both Mexico and the Channel Islands (Figure

1).

Pairwise comparisons between sampling locations found no significant differences between Mexico and all other sampling sites (Table 3). A haplotype median joining network indicated shallow genetic divergence with little to no phylogeographic structure. This finding was further supported by AMOVA results, that indicated that

100% of the variation was within populations sampled (0% variation among populations)

(Table 2). Both nucleotide diversity and haplotype diversity are low (π < 0.0047 and h =

0.162, respectively). Overall, haplotype diversity (h) was low, with site specific values ranging from 0.000 ± 0.000 to 0.348 ± 0.128. Current mitochondrial gene frequencies

11 reflect a loss in genetic variability within the giant sea bass population, most likely as a result of a bottleneck event.

Age and Growth

A total of 59 otoliths were used for age and growth analysis. Giant sea bass in this study ranged from 130mm to 1980mm SL and ages from 1 to 76 years, although only

8.5% of our samples were over age 40. The otoliths of the giant sea bass have an opaque core with a width of the first year of growth estimated to be approximately 3 mm (Allen and Andrews, 2012). Using the estimated first year of growth as a reference point, opaque annual growth rings were validated along the axis of the dorso-medial sulcus.

Nearly 94% of the variation between age (years) and standard length (mm) was accounted for in the von Bertalanffy growth model (R2 = 93.6). The growth coefficient (K

= 0.041) indicate this species has a slow growth rate, however, the negative value for t0 (t0

= -0.839) can be indicative of a species that grows rapidly in their first year of growth and then has a decreased growth rate in the years following. A predicted maximum length

with indefinite growth (L∞= 2048 mmSL) confirms that given the opportunity to grow to its limit, giant sea bass can grow to a massive size (Figure 5). The theoretical age at length calculations agreed well with observed ages with few exceptions. The growth

-0.041(t+0.839) equation fit to back calculated lengths at age was lt= 2048.37(1-e ) (von

Bertalanffy, 1938). The analysis of covariance suggested no significant interaction between length and age of individual giant sea bass and sampling sites off California and

Mexico (d.f. = 1, F = 2.788 and p = 0.105) (Table 4 and Figure 6).

12 DISCUSSION

Managing a once heavily fished species such as Stereolepis gigas requires robust knowledge of the species. Life history traits such as age, growth and mortality, definition of the species ‘stock’ and genetic data such as genetic variability, gene flow and effective population size are factors that must be addressed. The stock of a fishery is often defined by managers as a species being exploited on a specific spatial scale (Carvalo and Hauser,

1994), however genetic stock structure analysis should be considered so that populations can be managed effectively. The current study suggests that the spatial scale at which giant sea bass should be managed is broad as it lacks genetic structure and is distributed widely throughout southern California, Baja California and the Sea of Cortez.

A haplotype can be described as a set of genes inherited from a single parent; in this study I used matrilineally inherited mitochondrial genes to detect giant sea bass haplotypes and address the spatial scale at which giant sea bass should be. I’ve identified one ubiquitous haplotype (haplotype A) present throughout the range of giant sea bass and present in previous studies (Gaffney et al., 2007). Haplotype D is not nearly as prevalent however, it is as widespread as haplotype A. Although not nearly as common, haplotype D is found in the most northern and most southern range of the sampling sites.

These patterns indicated a panmictic population with random mating and sufficient gene flow, but can also be the effect of ‘sweepstake’ events. Sweepstake events occur when only a few individuals successfully reproduce, resulting in a low effective population size and a disproportionately large census size that facilitates enough genetic exchange for a population to appear panmictic (Carvalho and Hauser, 1994). However, it remains a possibility that the apparent connectivity among giant sea bass populations is the result of

13 adult mitigated distribution through spawning aggregations. There is no study to date that has verified giant sea bass spawning in natural habitat, still unpublished data of gonad assessments confirm current speculation that giant sea bass spawn from June to

September (Baldwin and Keiser, 2008). A similar pattern of adult contact facilitating gene flow is suspected in the , Semicossyphus pulcher, which like S. gigas is found in the northern Gulf of California, southern California waters and the

Channel Islands. Bernardi et al. (2003) suggested that ongoing contact between these populations of S. pulcher is due to adult migration in deep, cold water. An unpublished tagging study on giant sea bass (n=6) in 2000 using acoustic tags and receivers showed that giant sea bass tagged at Anacapa Island traveled more than 50 miles (Baldwin and

Keiser, 2008). The mobility of giant sea bass in conjunction with mitochondrial haplotype data further support that the lack of genetic structure among sampling sites may be due to adult migration to aggregate spawning sites. Gaffney et al. report that giant sea bass have a 30-day larval duration feeding on plankton before settling. However, the shared haplotypes between California and Mexico are unlikely due to larval distribution alone. Coldwater upwelling events during the summer months, when giant sea bass are aggregating, such as the San Quintin upwelling zone tend to disrupt larval transport between nearshore populations of fish found in southern and Baja California (Selkoe et al., 2007).

Interestingly, the current study does not support previous findings of high haplotype diversity (h) in mitochondrial DNA. Gaffney et al. (2007) allocated giant sea bass into Category 2 of Grant and Bowen (1998) and inferred that the pattern of high (h) and low nucleotide diversity (π) is typical of species that had a low effective population

14 size and have since undergone an expansion several thousand years to one hundred thousand years ago. However, our results categorized giant sea bass in the first category of Grant and Bowen (1998). Species in this category are characterized by low effective population size in more recent history (late Pleistocene to within a few thousand years).

Kelp forests off California and Baja California in the late Pleistocene were abundant and probably inhabited by large populations of mega-carnivores such as Stereolepis gigas.

These kelp forests have since declined and given way to sandy shores within the last

4,000 to 6,000 years (Graham et al., 2003). Our results indicate that giant sea bass experienced a more recent bottleneck, which may be explained by paleogeographic patterns that suitable habitat has declined in the last 18,000 years, thus reducing the effective population size. Finally, the more recent collapse of the S. gigas population due to overfishing in the early 1900’s also remains a viable explanation for the low genetic diversity discovered herein.

Age verification through otolith analysis allows for a concrete understanding of age, growth and mortality of Stereolepis gigas. Fitch and Lavenberg (1971) published detailed accounts of the natural history of giant sea bass, including reports that a 435 pound giant sea bass was “verified’ between 72 and 75. Unfortunately, the methods used to determine the age of the 435 giant sea bass were not addressed. Otoliths were often read whole at the time (Allen and Andrews, 2012), which can lead to a skewed estimation of age. A more recent study using radiocarbon analysis methods verified annulus growth rings in giant sea bass, as well as confirmed the oldest known individual to be 62 years of age (Allen and Andrews, 2012). There has been much speculation and little information on the longevity of giant sea bass, but here I verify the oldest known individual aged at

15 76 years of age. There are reports that S. gigas reaches 90 to a 100 years of age and 600 pounds (Fitch and Levenberg, 1971), yet these reports remain unverifiable as in the current study individuals were collected at the upper size limit of giant sea bass’ expected growth and none exceeded 76. Combining age-and-growth data with haplotype results, the rare haplotypes were found in young individuals (N= 5, average age 21.6 yrs, range =

10 to 30). Recent reports have described the return of giant sea bass to the Southern

California Bight since legislation was enacted to protect this species in 1981 (Pondella and Allen, 2008; Baldwin and Keiser, 2008). The presence of rare haplotypes in individuals less then 30 years of age may be the result of increased population size since restrictions were put in place, however it is important to note that such assumptions are difficult to confirm as thirty years is at best a snap shot in evolutionary time. The lack of rare haplotypes in older individuals is most likely a by-product of the relatively low sample size of older individuals in the data set. Future genetic analysis using microsatellite markers may be better able to elucidate trends between age and haplotype frequency as microsatellites are nuclear loci that are highly variable and more rapidly evolving then mitochondrial loci. Microsatellites may also be able to detect discrete populations and can be informative for parentage studies as well.

Stereolepis gigas has only one congener, Stereolepis doederleini on which there is also very little life history data collected. Although there is little known about Stereolepis spp., other polyprionids have been studied for age and growth. In a study done by Peres and Haimovici (2004) on the Atlantic Polyprion americanus, the maximum age was also estimated at 76. Similar to my findings, the von Bertalanffy growth curves for both males and females of P. americanus indicated slow growth rates overall, with negative values

16 for t0. Unfortunately for the purposes of this study, I was unable to differentiate between males and females as S. gigas is not an obviously sexually dimorphic species and gonads are removed before they are brought to market. Sexual size dimorphism has been suggested for another species of , the New Zealand hapuku, Polyprion oxygeneios, where females grow larger and faster than males of the species (Francis et al.,1999). It would be beneficial to address possible variances in growth rates among males and females of giant sea bass because differences can have implications in sexual selection (Walker and McCormick, 2009).

In support of the recovery of giant sea bass, it may be advantageous if marine protected areas (MPAs) were established where spawning aggregations occur. It is illegal to target giant sea bass however, incidental catch-and-release of this species occurs regularly. A model of 5 different mortality regimes predicting the expected mortality of giant sea bass under varying degrees on catch-and-release mortality indicated that an aggregation of 100 giant sea bass with 20% mortality due to catch-and-release would be driven to local extinction after 16 years (Schroeder and Love, 2002.) Alternatively, with an estimated natural mortality rate of only 6% an aggregation of 100 giant sea bass would be reduced to 29 individuals after 25 years (Schroeder and Love, 2002). An unrealistic, yet important tenet in the aforementioned model is that no additional recruits are added to the aggregation over time. However, the model does illustrate the impact that catch-and- release mortality may have on this protected species and supports the proposal that MPAs could be useful in the management and recovery of this species.

Giant sea bass in California are currently protected, yet those in Mexico continue to be targeted both commercially and recreationally. Although the Californian and

17 Mexican giant sea bass populations may appear to be disjunct, this study confirms a lack of genetic diversity between the two regions. Unpublished data cited in the 2008 Status of the fisheries Report for giant sea bass (Baldwin and Keiser, 2008) suggested that giant sea bass may in fact migrate long distances, placing even more importance on protecting

S. gigas in California as they remain unprotected in Mexico (Gaffney et al., 2007). Giant sea bass in Mexico are subject to differential fishing pressure compared to those in

California due to lack of regulation. While fishing mortality can cause an adaptive response in growth rates of a population (Bevacqua et al., 2012), an analysis of covariance indicated there is no variation in growth among Californian and Mexican giant sea bass and that the variation found in length and age of giant sea bass is not due to any variation between individuals sampled in California and Mexico. However, the effects of any possible fishing pressure experienced by Mexican giant sea bass may be offset by genetic exchange with those protected in California.

Complete life history data is fundamental in fisheries management. The current study provides a more stable foundation on which to base the continued moratorium of this critically endangered fish. By determining the level of genetic variability in the existing population (stock) of giant sea bass, inferences can be made as to the impact of overexploitation and to what extent current populations should continue to be protected.

The haplotype and nucleotide diversity in the existing stock of giant sea bass indicated that this species has gone through a more recent bottleneck event than previously understood.

18

TABLES

Table 1. Universal primers for mtDNA control region of teleost fish.

Primer Sequence UTCRF1 (Forward) 5'-TTCCA CCTCT AACTC CCA AA GCTAG-3' UTCRR1 (Reverse) 5'-ACGCT GGAAA GAACG CCCGG CATGG-3'

Table 2. Results of AMOVA for mtDNA results show genetic variation is greater within populations than between populations.

Percentage of d.f. Variance Variation Among Populations 4 0 0% Within Populations 52 0.11 100%

Table 3. Population Pairwise Fst values indicating no significant variation between sampling sites, (-) show non-significant p-values.

Channel Palos Los Islands Verdes Angeles San Diego Mexico Channel Islands - - - - - Palos Verdes 0.000 - - - - Los Angeles 0.034 0.000 - - - San Diego -0.051 0.000 0.000 - - Mexico -0.065 -0.033 -0.013 -0.069 -

19 Table 4. Results of ANCOVA indicating no significant difference in length of giant sea bass sampled in Mexico and California.

Source of Variation d.f. F-Ratio p Site 1 1.19 0.284 Age 1 2.433 0.129 Site x Length 1 2.788 0.105

Table 5. Sample size of giant sea bass collected at all five sampling sites.

Location Sample Size Channel Islands 9 Palos Verdes 9 Los Angeles 12 San Diego 7 Mexico 22

20

FIGURES

Figure 1. Sample locations of Stereolepis gigas (Map credit: L. G. Allen).

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Figure 2. Median joining network depicting four haplotypes. Distances between circles represent number of mutations and size of circle represents haplotype frequency.

Figure 3. Transverse cross section of oldest verified otolith (age 76). Dotted line demonstrates dorso-medial axis along which all otoliths were aged.

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Figure 4. Observed standard length (SL) at age for giant sea bass in California and Mexico. The von Bertalanffy growth curve indicates giant sea bass are a slow growing species.

Figure 5. Observed haplotypes for giant sea bass within five year age bins, illustrating that rare haplotypes were found in individuals thirty and under.

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Figure 6. Average standard length and age of giant sea bass in Mexico compared to average standard length and age of giant sea bass in California. Data points represent averages of individuals within the same age class. Results indicate no significant difference length of giant sea bass found in Mexico than giant sea bass sampled in California.

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30 APPENDICES

Appendix I. Catalogued individuals from each sampling location and their respective haplotype.

Catalogue Number Haplotype Catalogue Number Haplotype North Channel Islands San Diego 085-60 A 068-44 A 086-61 A Mexico 087-62 D 034-13 A 088-63 A 061-39 A 089-64 A 062-40 A 090-65 A 064-41 A 091-66 A 065-42 A 001-01 A 069-45 D 102-73 A 070-46 A Palos Verdes 071-47 A 013-05 A 072-48 D 014-06 A 073-49 A 016-08 A 075-50 A 017-09 A 076-51 A 092-67 A 077-52 A 095-68 A 078-53 A 096-69 A 079-54 A 099-70 A 080-55 A 100-71 A 081-56 A Los Angeles 082-57 A 026-16 A 083-58 A 027-17 A 084-59 B 028-18 A 103-74 C 029-19 A 101-72 A 053-33 A 054-34 A 056-35 A 057-36 A 059-37 A 060-38 A 046-27 A 044-26 A San Diego S0374 A S01-196 A S04-180 A S04-179 A S09-289 A 066-43 A

31 Appendix II. Selected otolith image depicting annulus rings of growth. Each image has the magnification at which it was photographed, the final determined age and calculated standard length.

Catalogue ID SB061008 Catalogue ID 084-59 Catalogue ID 102-73 Age: 1 SL: 125mm Age: 18 SL: 1111mm Age: 35 SL: 1576mm Magnification: 1 x 3.2 Magnification: 1 x 2.5 Magnification: 1 x 2.0

Catalogue ID N082607 Catalogue ID 069-45 Catalogue ID 086-61 Age: 6 SL: 410mm Age: 19 SL: 1271mm Age: 41 SL: 1448mm Magnification: 1 x 3.2 Magnification: 1 x 3.2 Magnification: 1 x 2.5

Catalogue ID 10052 Catalogue ID 023-00 Catalogue ID 066-43 Age: 12 SL: 650mm Age: 25 SL: 1572mm Age: 54 SL: 1873mm Magnification: 1 x 3.2 Magnification: 1 x 2.5 Magnification: 1 x 2.5

Catalogue ID 040-19 Catalogue ID 040-24 Catalogue ID 10052 Age: 15 SL: 863mm Age: 28 SL: 1271mm Age: 76 SL: 1926mm Magnification: 1 x 2.5 Magnification: 1 x 3.2 Magnification: 1 x 2.0

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