California State University, Northridge Selection on Larval Traits in Early Post-Settlement Temperate and Tropical Reef Fishes

Home , Chromis viridis

CALIFORNIA STATE UNIVERSITY, NORTHRIDGE

SELECTION ON LARVAL TRAITS IN EARLY POST-SETTLEMENT TEMPERATE AND TROPICAL REEF FISHES

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

Heidi Elise Block

December 2011

The thesis of Heidi Elise Block is approved:

Dr. Larry G. Allen Date

Dr. Mia S. Adreani Date

Dr. Mark A. Steele, Chair Date

California State University, Northridge

ACKNOWLEDGEMENTS

First of all, I would like to thank Dr. Mark Steele for helping me with all aspects of this project: from completing my scientific dive certification and teaching me how to catch gobies, to patiently editing many drafts of my thesis, I would not have been able to complete this project without his continuing support. In addition, I would like to thank my committee members Drs. Larry Allen and Mia Adreani for their help in editing my thesis, and general support during my project. I also would like to thank Dr. Steven

Dudgeon for providing me with a good statistical foundation, without which I would not have been able to complete the analyses required for my study.

I would like to acknowledge all of the people who helped me in the field and lab:

Katie Field, David Sinkiewicz, Edwin Leung, Mike Schram, Jenna Krug, Steve Doo,

Natalie Low, Jason Selwyn, Barbara Sanchez, Jessica Baker and Audrey Guzowski.

Without all of their help this project would not have been possible. I would like to give a special thanks to Katie Field and David Sinkiewicz, for spending many hours underwater helping me to collect fish and complete surveys, and to Edwin Leung and Mike Schram, for volunteering to read close to a thousand of my otoliths.

The Wrigley Institute for Environmental Studies provided me with financial and logistical support for the Catalina portion of this project, for which I am very grateful. I would also like to thank Northeastern University’s Three Seas Program for providing me with the opportunity and financial support to complete my study in Moorea; and the

Gump South Pacific Research Station for their logistical support. Lastly, I would like to acknowledge California State University, Northridge for providing additional funding for this project.

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TABLE OF CONTENTS

Signature Page ii

Acknowledgements iii

Abstract v

Chapter 1: General introduction 1

Chapter 2: Spatially and temporally inconsistent selection on 6 larval traits in two common kelp forest fishes Introduction Methods Results Discussion Tables and Figures

Chapter 3: Selective mortality on larval traits in two coral reef fishes 37 in Moorea, French Polynesia Introduction Methods Results Discussion Tables and Figures

Chapter 4: Conclusions 60

Literature Cited 63

ABSTRACT

SELECTION ON LARVAL TRAITS IN EARLY POST-SETTLEMENT

TEMPERATE AND TROPICAL REEF FISHES

Heidi Elise Block

Master of Science in Biology

In marine organisms with complex life histories it is possible for events occurring during earlier life stages to affect an individual’s subsequent survival. In fishes, it has been proposed that settlement, the transition from a pelagic habitat to a benthic one, is a critical period in determining survivorship. Selection (i.e., non-random mortality) may occur on specific larval traits, which could influence an individual’s probability of survival after settlement. Herein I examine the effects of larval traits on the survival of juveniles shortly after settlement in two temperate and two tropical reef fishes. This was achieved by comparing traits of individuals sampled just after settlement with those of individuals from the same cohort sampled one month later, which evaluated selective mortality occurring over a cohort’s first month of life on the reef.

The two temperate species studied were señorita, Oxyjulis californica, and blackeye goby, Rhinogobiops nicholsii. Collections were completed at four sites at Santa

Catalina Island, California, and two times between June and August of 2009. For señorita, I examined four larval traits: planktonic larval duration (PLD), size at settlement, metamorphosis band width, and pre-settlement growth rates. For the blackeye goby I examined two traits: size at settlement and pre-settlement growth rates. This study

v revealed that selection was inconsistent in both species. There were differences in both the direction and intensity of selection between the different sites as well as times.

Differences in selection intensity were not related to variation in habitat characteristics or conspecific densities. Unlike selection, I found some consistent differences in larval traits between cohorts in señorita. For the señorita I found that individuals settling earlier in the summer had longer PLDs and slower growth rates than those settling later in the summer.

In Moorea, French Polynesia I studied the blue green chromis, Chromis viridis, and the Gnatholepis species complex, Gnatholepis scapulostigma/anjerensis. This study was conducted at two sites on the North side of the island. Unlike the temperate study, only one cohort was examined due to logistical constraints. I examined three larval traits for both “species”: PLD, size at settlement, and pre-settlement growth rates. For the

Gnatholepis species complex, I did not find any evidence of selection or any differences between the two study sites for any of the larval traits measured. For Chromis viridis, I found that there was selection for larger sizes at settlement at both sites. However, selection on the other two larval traits was inconsistent between the two sites, with one site showing selection for faster pre-settlement growth rates and the other showing selection for longer PLDs. For this study I also explored whether differences in habitat characteristics or predator densities between the two sites might be influencing these patterns. These two sites were not significantly different in terms of habitat or predator densities and therefore these factors could not explain differences in selection between sites.

These two studies reveal that selection on larval traits can vary greatly on relatively small scales: with sites less than 3 km apart exhibiting differences in the direction or strength of selection on a larval trait. This small-scale variation in selection may be one reason why variability in larval traits is maintained in these species.

Understanding the causes of variation in larval traits in these populations and how variation is being maintained, through processes such as selective mortality, will help to understand and predict recruitment dynamics and ultimately community structure.

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Chapter 1

General Introduction

Many organisms exhibit complex life history strategies, e.g. amphibians, plants, insects, fishes, and marine invertebrates (Wilbur 1980). Complex life histories involve multiple life stages, which often provide individuals with the chance of higher dispersal during a particular phase. In many amphibians for instance, there is a larval (tadpole) life stage that is fully aquatic and has limited dispersal potential; whereas after metamorphosis into the terrestrial adult stage, individuals have much higher potential for dispersal (Wilbur 1980). The opposite of this pattern is usually seen in plants, in which the highest dispersal is for seeds as compared to sessile adults. Dispersal is important for populations because it can decrease crowding and competition, as well as increase genetic diversity and decrease inbreeding (Hedgecock 1986, Pechenik 1999).

Many benthic marine organisms have complex life histories with a benthic- associated adult stage and a planktonic larval stage. These different stages provide benefits, and present challenges for marine organisms. One of the major benefits of having multiple life stages is the possibility for dispersal to new environments. Dispersal to new locations can, as mentioned earlier, decrease crowding and potential competition at one location as well as increase genetic diversity within a population by providing a wider range of suitable mates. Although some mobile marine organisms disperse as juveniles and adults, many benthic reef based organisms rely on larval stages for dispersal. Dispersal of marine larvae is important in connecting populations, which can be important for sustaining them. For example, if one population experiences a decline, a nearby population can supplement that population through larval dispersal. Due to the

1 importance of larval dispersal in population sustainability, larval dispersal and connectivity have been widely studied for the purposes of fisheries management and conservation (Levin 2006, Cowen and Sponaugle 2009).

One of the challenges associated with larval dispersal is the possibility that the larvae will never find suitable settlement habitat, and will die in the plankton. When larvae leave their natal reef they are leaving behind known suitable habitat in order to find another potentially better location, which may or may not exist. Additionally, there is extremely high mortality of larvae in the plankton, as well as at the time of settlement

(Steele and Forrester 2002, Almany 2003, Doherty et al. 2004, Almany and Webster

2006). The settlement transition has been considered a critical period due to this high mortality (Searcy and Sponaugle 2001, Doherty et al 2004, Almany and Webster 2006).

For organisms with complex life histories there is the possibility that events occurring during one life stage might influence their success later in life. This is one reason that the settlement transition, the transition from pelagic to benthic, has received considerable attention (e.g., McCormick 1998, Searcy and Sponaugle 2001, Vigliola and

Meekan 2002, Doherty et al. 2004, Hoey and McCormick 2004, Grorud-Colvert and

Sponaugle 2011). It is possible that traits developed during an individual’s larval stage might influence their survival through the settlement transition and into their juvenile stage (Bergenius et al. 2002, Doherty et al. 2004, Hoey and McCormick 2004).

The differential persistence of particular traits in a population is often examined in the context of selective mortality. Selective mortality occurs when particular traits are selected against through higher mortality of individuals that possess those traits.

Selective mortality on larval traits is thought to occur around the time of settlement

(reviewed in Anderson 1988 and McCormick 1998).

In order for selection on larval traits to occur, there must first be variation in larval traits. Variation in larval traits has been shown in many species, including both temperate and tropical species, for example, the temperate wrasse Semicossyphus pulcher

(Cowen 1991), and the tropical wrasse Thalassoma bifasciatum (Sponaugle and Cowen

1997). There are several possible causes of this variation, including but not limited to parental effects (Chambers and Leggett 1996, McCormick 1999, Berkeley et al. 2004,

Green and McCormick 2005) and environmental effects (Macpherson and Raventos

2005, Bergenius et al. 2005, McCormick and Molony 1995, Findlay and Allen 2002,

Sponaugle and Grorud-Colvert 2006). Berkeley and colleagues (2004) found that larvae produced by older females had higher growth rates than those produced by younger females. This growth rate difference has the potential to influence their chances of survival to settlement. Environmental factors, such as wind, sea surface temperatures, atmospheric pressure, and annual climatic differences can affect settlement intensity as well as selective mortality, which can lead to variation in larval traits (Macpherson and

Raventos 2005, Good et al. 2001).

Some general hypotheses seek to explain the outcomes of selective mortality on variable larval traits. The “growth-mortality” hypothesis states that as fish grow larger they have fewer potential predators, so the individual that reaches a larger size faster will move through vulnerable stages more quickly and have a higher probability of survival than slower growers (Anderson 1988). There have been many studies testing this hypothesis, and there have been variable results (Campana 1996, Searcy and Sponaugle

2001, Good et al. 2001, Shima and Findlay 2002, Vigliola and Meekan 2002, Wilson and

Meekan 2002, Hoey and McCormick 2004, Raventos and Macpherson 2005, Sponaugle and Grorud-Colvert 2006, Meekan et al. 2010, Sponaugle et al. 2010). Many studies have supported parts of the “growth-mortality” hypothesis, particularly that faster growth rates increase survival; however, there is less support for the idea that a larger size at settlement increases survival. The “growth-mortality” hypothesis is a simple framework for understanding why certain individuals have better survival than others; however there are likely many different factors that influence the outcomes of selective mortality.

I had four main research objectives: 1) to determine if selective mortality was occurring in four species of temperate and tropical reef fishes; 2) to determine if the

“growth mortality” hypothesis is upheld in these species; 3) to see if selection was occurring in the same direction at different locations; and 4) to measure the intensity of selection and determine if it was influenced by habitat or population density. I tested these hypotheses in four fishes: two temperate and two tropical species. The two temperate species were Rhinogobiops nicholsii and Oxyjulis californica, which were studied at Santa Catalina Island, California. The two tropical species were Chromis viridis and Gnatholepis scapulostigma/anjerensis, which were studied in Moorea, French

Polynesia.

To determine if selection was occurring on larval traits, I examined individuals from the same settlement cohorts at different times, sampling just after settlement and again one month after settlement. Resampling the same cohort twice allowed me to evaluate how the mean and variation in larval traits changed during a cohort’s first month on the reef. If there was a change in the mean of a trait between when the cohort first

4 settles onto a reef and one month later, then directional selection has acted on that trait.

For the temperate species, two cohorts were examined in the same way to test for differences in selection through time.

In addition to testing for selective mortality, I also examined how differences in habitat characteristics and fish densities across time and among locations could influence the intensity of selection on larval traits. At Catalina, four locations were examined and habitat characteristics and densities of new recruits were determined at two times, one early in the summer and one later in the summer, to correspond to the two cohorts that were examined for each species. In Moorea, habitat characteristics as well as fish populations were examined only once as only one cohort was examined for each species.

Many studies have examined selective mortality and the “growth mortality” hypothesis, however, the influence of differences in habitat and fish densities on selective mortality has been largely overlooked. My thesis examines these topics and provides insight into how selective mortality acts between different environments, different locations within the same environment, and how selection changes through time.

Chapter 2

Spatially and temporally inconsistent selection on larval traits of two common kelp

forest fishes

Introduction

Many marine fishes exhibit a bipartite life cycle with two distinct stages: a benthic adult stage and a planktonic larval stage. The planktonic stage allows the possibility of dispersal to new habitats; however it is also associated with high levels of mortality and it requires larvae to locate suitable settlement habitats at the end of the planktonic phase. After locating a suitable habitat the larvae then must settle to the benthos, and this transition has been considered a critical period (Searcy and Sponaugle

2001, Doherty et al 2004) because there can be extremely high mortality at this stage

(Steele and Forrester 2002, Almany 2003, Doherty et al. 2004).

In fishes with a bipartite life cycle, events that occur during the larval stage as well as larval traits can influence population dynamics of the adult stage (Bergenius et al.

2002, Doherty et al. 2004, Hoey and McCormick 2004). The influence of larval traits on the survival of individuals through subsequent stages is a form of selective mortality.

Selective mortality occurs when specific traits are selected against through higher mortality of individuals possessing those traits. It has been proposed that selective mortality on early life history traits occurs near the time of settlement (reviewed in

Anderson 1988, McCormick 1998).

In order for selective mortality to occur, there must first be variation in larval traits. It has been shown that there is variation in larval traits of a variety of species

(Cowen 1991, McCormick 1994, Sponaugle and Cowen 1997, McCormick 1998,

Johnson et al. 2010). There are many possible causes of variation in larval traits, two of which include parental effects (Chambers and Leggett 1996, McCormick 1999,

McCormick 2003, Berkeley et al. 2004, Green and McCormick 2005) and environmental effects (McCormick and Molony 1995, Bergenius et al. 2005, Macpherson and Raventos

2005, Sponaugle and Grorud-Colvert 2006, Sponaugle et al. 2006, Gagliano et al.

2007a).

Both parental and environmental effects on larval condition can set the variation in larval traits and therefore can affect survival of those larvae. Berkeley and colleagues

(2004) found that larvae from older female fish had higher growth rates than those of younger females, which has the potential to increase their chances of survival to settlement. A study by Johnson et al. (2010) showed a tradeoff between the number of larvae a female produced and their size in the bicolor damselfish, Stegastes partitus.

They showed that a larger size at hatching was more adaptive in this species, but that size at hatching was constrained by an adaptive benefit for higher maternal fecundity. These differences in maternal investment can lead to differences in larval condition and increased variation. In addition to parental effects, many studies have started to examine how different environmental factors affect larval condition. Macpherson and Raventos

(2005) found that several environmental factors including sea surface temperatures, wind, and atmospheric pressure predicted yearly variation in settlement intensity. They also found that these factors influenced planktonic larval duration in one species in the study, the Mediterranean blenny Lipophrys trigloides. A study by Good et al. (2001) on

Atlantic salmon found that differences in annual climate can influence size-selective mortality. They studied Atlantic salmon fry two years in a row; in one year there were

7 drought conditions and in the next flood conditions. They found size-selective mortality during both years, but in different directions, with smaller individuals being selected against under drought conditions and larger individuals being selected against in flood conditions (Good et al. 2001). These studies, as well as others, have shown how influential environmental variability can be in driving variation in larval traits and selective mortality. There are, however, several other hypotheses that seek to explain the outcomes of selective mortality.

The “growth-mortality” hypothesis (Anderson 1988) states simply that as fish grow larger they decrease their number of possible predators, and so the faster a fish can reach a larger size, the less time it will spend in vulnerable stages, and the more likely it will survive. Many studies have tested this hypothesis and results have been mixed

(Campana 1996, Searcy and Sponaugle 2001, Good et al. 2001, Shima and Findlay 2002,

Vigliola and Meekan 2002, Wilson and Meekan 2002, Hoey and McCormick 2004,

Raventos and Macpherson 2005, Meekan et al. 2006, Sponaugle and Grorud-Colvert

2006). In many of these studies parts of the “growth-mortality” hypothesis have been upheld, particularly fast growth rates increasing chances of survival, while other aspects, such as individuals that were larger at settlement having higher survivorship, have received less support. The “growth-mortality” hypothesis works well as a simple explanation for why some individuals may have better survival, but it is likely an oversimplification of what happens in nature.

In addition to the “growth-mortality” hypothesis, competition has been shown to influence the survival of recently settled fishes (Carr et al. 2002, Almany 2003, Hixon and Jones 2005). Victor (1986) provided evidence that larvae that settled onto reefs with

8 low adult densities had faster growth rates than those on higher-density reefs. This was also supported in a study by Samhouri and colleagues (2009) who examined how increased shelter may influence the direction of selective mortality in a Caribbean goby.

They found that while the amount of shelter did not have consistent effects on selective mortality, different adult densities affected the direction of selective mortality. They found that with high adult densities, larger individuals were favored, whereas with low adult densities, smaller individuals were favored.

The quantity and quality of habitat may also affect the survival of fishes after settlement. It seems likely that locations with differing quality or quantity of habitat may show different patterns of selective mortality. In kelp ecosystems where there are large changes in kelp abundance both annually and seasonally, there may be differences in which individuals are selected for at the settlement transition depending on the quality and quantity of appropriate habitat that year. Carr (1994) examined how giant kelp influenced the recruitment of kelp bass, Paralabrax clathratus. He found that kelp bass recruitment was related to giant kelp density and blade biomass, which revealed that both quantity and quality of the habitat play a role in kelp bass recruitment. A study by

Johnson (2007) explored how habitat complexity influenced the importance of recruitment on population dynamics. He found that recruitment had more pronounced effects on population size when habitat complexity was increased. How habitat affects selective mortality is likely to vary greatly between species, as species have different habitat preferences (Holbrook et al. 1990). Selective mortality at a site may also vary among age classes within the same species, because if the habitat changes frequently, an appropriate habitat at settlement may not remain suitable as that individual matures. For

9 example, kelp forests, which change dramatically in kelp abundance throughout the year, may have adequate kelp when an individual settles but as the year progresses the kelp may decrease causing a decrease in suitable habitat for that individual.

Many factors likely play a role in determining survival of fishes with a larval stage, including both pre- and post-settlement processes. Parental effects as well as many environmental variables can have strong influences on larvae prior to settlement, whereas competition and habitat affect individuals at or after settlement. The idea that competition and habitat quality and quantity drive selective mortality has received less attention than effects of environmental variables and parental effects.

In this study, I examined how post-settlement factors, competition with conspecifics and habitat attributes, influenced selective mortality in two common kelp forest fishes. This was done by comparing larval traits of fish just after settlement with those of one-month-old juveniles from the same cohort, to test for selection occurring over a cohort’s first month of life on the reef. Larval traits were determined in this study using otoliths, often referred to as “ear stones.” Many fishes form daily rings on their otoliths, not unlike how trees form rings, and these rings allow age to be determined. In addition to daily ring formation, when a fish settles into a different environment, this transition is often exhibited in the otolith as a settlement mark (Victor 1982; Fig. 1).

Daily ring formation as well as settlement marks in the otoliths allow for the determination of the larval traits examined in this study: pre-settlement growth rates, size at settlement, planktonic larval duration (PLD), and metamorphosis band width.

This study had three main objectives. The first was to determine if there was selective mortality on larval traits of the study species. The second was to determine if

10 larger, faster growing individuals were favored, as predicted by the “growth-mortality” hypothesis, and if there were similar patterns between species and among sites. The final objective was to determine whether conspecific densities or habitat differences influenced the direction and intensity of selection.

Methods

Study Species:

In this study I examined two common California kelp forest fishes, señorita,

Oxyjulis californica, and blackeye goby, Rhinogobiops nicholsii. The blackeye goby has a range from British Columbia, in the North, to Baja California, in the South (Miller and

Lea 1972). The señorita has a slightly narrower range, from Sausalito, California, in the

North, to Baja California, in the South (Miller and Lea 1972). I chose these species because they are abundant and ubiquitous species in kelp forests in southern California, they were found to be settling in large numbers at all study sites, they differ in reproductive tactic, and they have very different larval durations. The blackeye goby is a demersal spawner, laying eggs in nests on the bottom, whereas the señorita is a broadcast spawner (Shanks and Eckert 2005). The planktonic larval duration (PLD) for the señorita is on average 34 days, whereas the blackeye goby has a PLD of on average 59 days (PLD estimates from this study). The differences in life history of these two species allowed me to assess how consistent selection on specific larval traits is between quite different species.

To determine which traits might influence survival shortly after settlement in these species, I collected both recently settled individuals and then survivors of the same cohort one month later as juveniles. I then repeated this collection scheme one more time, so that two cohorts were sampled. This collection schedule made it possible for me to look for changes in selective mortality over time. In order to evaluate how differences in habitat might influence selective mortality, I completed these collections at four different sites. I surveyed all of these sites around the same times as the collections to

12 quantify differences in habitat characteristics as well as conspecific densities to evaluate how potential site differences could influence selective mortality.

Sites:

The study sites are located on the Northeast side of Santa Catalina Island and were Little Geiger Cove (33°27’32” N, 118°30’59” W), Lion’s Head (33°27’08” N,

118°30’05” W), Ripper’s Cove (33°25’43” N, 118°26’11” W), and Little Gibraltar

(33°25’20”N, 118°24’40”W). These four sites were chosen because they had received high levels of recruitment of the two study species during the preceding settlement season

(Krug 2009). The distance between the two most widely separated sites, Little Geiger and Little Gibraltar, is approximately 10 km.

Collection Techniques:

I completed all collections between June and August of 2009. I used both

BINCKE nets (Anderson and Carr 1998) and hand nets to collect newly settled individuals and one-month-old juveniles. For newly settled individuals I collected the smallest individuals on the reef. For one-month-old juveniles I used an estimate of size- at-age to approximate the appropriate size to target for collection.

For each age group at each site, I collected approximately 50 individuals of each species for otolith analysis. I sampled new settlers in June and July and then I resampled these cohorts in July and August respectively. I categorized señorita as new settlers if they were between 0 and 7 days post-settlement, as determined from the settlement mark on the otolith, and juveniles if they were approximately 30-44 days post settlement. The

13 juvenile age group contained a larger range of ages due to low sample sizes. Low sample sizes were due to errors in estimating age in the field using individual sizes. For blackeye gobies, new settlers were between 0 and 12 days post settlement, and juveniles were between 30 and 44 days post settlement.

I measured all of the collected individuals for standard length (SL), to the nearest tenth of a millimeter using calipers, and weight, to the nearest hundredth of a gram. I measured and weighed all individuals after they were preserved in 95% ethanol.

Otolith Analysis:

I removed sagittal and lapillar otoliths (“ear bones”) from all individuals; however, I found that the lapilli were much clearer and easier to read, and therefore they were used in all analyses. I used these otoliths to determine specific larval traits for each species. For señorita, I measured planktonic larval duration, size at settlement, larval growth rates, and width of the metamorphosis band. For blackeye gobies I was only able to measure size at settlement and larval growth rates. I was not able to measure planktonic larval duration for many individuals of this species, due to difficulty in reading near the core of these otoliths. Settlement marks are apparent in both species

(Fig. 1). For the blackeye goby there is an abrupt change in the width of daily bands at the time of settlement (Fig. 1B). Señorita have a metamorphosis band which is a blurry multiday band formed at the time of settlement, much like that seen in other wrasses

(pers. obs., Victor 1982; Fig. 1A). In these two species, as well as many others, otolith size is closely related to the body size of the individual. In this study, there was a strong linear relationship between otolith radius and standard length for both species (señorita

14 n=541, r2=0.89; blackeye goby n=391, r2=0.82). Given these strong relationships, and in order to avoid error associated with back calculation, all analyses were completed on otolith traits as proxies for somatic traits. I determined planktonic larval duration (PLD) from a count of the number of rings from the center of the otolith to the settlement mark.

I used the width of otolith daily bands to estimate daily growth rates. I completed measurements of daily growth rates over the week prior to settlement to determine whether growth rates just prior to settlement influenced success of juveniles after the settlement transition. I estimated size at settlement by the size of the otolith from the core to the settlement mark. The metamorphosis band has been shown to relate to individual condition at the time of settlement in the bluehead wrasse (Hamilton 2008).

Due to this potential connection to condition, I also measured the width of the metamorphosis band for the señorita. I made all of these measurements using Image-Pro

Plus imaging software on a computer connected to a digital camera mounted to a compound microscope. I double read all of the otoliths, and if readings were more than

10% different they were read a third time. If after the third reading, two of the three readings were still not within 10% of each other, that individual was not included in any analyses. If the two readings were within 10% of each other but not identical, I used the mean of the two readings in statistical analyses.

These techniques allowed me to measure the initial mean and variation for each trait at settlement, and these were compared to those variables in survivors from the same cohort sampled one month later. The comparison allowed me to determine if survivors had a non-random subset of the initial traits, which would indicate there had been selective mortality.

Field Surveys:

I quantified habitat attributes during two surveys of the reefs, one in June and one in July, to characterize the conditions at the sites at the time collections of new settlers were completed for each cohort. During the habitat surveys I quantified both substrate type and macroalgal cover. I characterized the base substrate as well as the surface cover on that substrate using the random point contact (RPC) method. RPC was done by noting substrate and cover at a random point within each meter of a thirty-meter transect. I categorized the substrate as sand, cobble (<10 cm), small boulder (10-30 cm), medium boulder (30-75 cm), large boulder (>75 cm), or sheet rock. I described the cover as either live cover or bare substrate. When live cover was indicated, I identified the type of algae and, if not an alga, I listed it as “other”. When I listed bare substrate for the surface cover, it was categorized only by the underlying base substrate, as indicated above. I also examined the density of giant kelp, Macrocystis pyrifera, by counting the number of individuals as well as the number of stipes in a one-meter band along each of the 30-m transects. I completed a total of nine transects at each reef to characterize habitat attributes. I placed transects in sets of three, with one near the reef edge, one near the shore and one in the middle. I placed these sets of transects in three locations spread out along the length of the reef.

In order to determine if conspecific density affected selection, I completed surveys to characterize density at each site twice, once in June and once in July. Recruit densities were examined for señorita in order to evaluate how competition around the time of settlement might influence selection. For blackeye gobies it was not possible to use recruit densities due to very low observed numbers, therefore I examined total

16 conspecific densities. I sampled 27 transects at each site during each survey for señorita.

Transects were placed at 9 locations with 3 depth strata (bottom, midwater, and near surface) sampled at each location. The 9 locations included three zones (reef edge/ecotone, middle reef, and nearshore) at each of three areas spread evenly along the reef. Along each transect I counted all the señorita and I placed them into three size/age categories: new settlers, young of the year, and older individuals. Transects for señorita were 30-m long and individuals were counted within a 2 x 1 m window centered along each transect. Blackeye gobies were sampled on each of the 9 bottom transects, as they are not found in the midwater or canopy. Three 0.25-m2 quadrats were placed on each transect and all blackeye gobies within the quadrats were counted.

Data Analysis

I used permutational multivariate analysis of variance (PERMANOVA) to test differences in otolith traits among sites, cohorts, and age groups. I chose a permutational analysis because the data were not normally distributed and could not be transformed to be so. I used the software package PRIMER v6 with the PERMANOVA+ addition for all of the permutational analyses. Before analysis, I normalized the data to a mean of zero and unit variance in order to put the variables on the same scale.

The PERMANOVA model had three factors in it: site, cohort (June or July settlement), and age group (new settler or one-month old juvenile). I used a mixed model, with site as a random factor and cohort and age as fixed factors. I analyzed four otolith-derived traits for the señorita: settlement size, PLD, daily growth rates just prior to settlement, and metamorphosis band width. I examined two of these variables for

17 blackeye gobies, settlement size and growth rates just prior to settlement. I evaluated any statistically significant PERMANOVA results in more detail with univariate analyses

(also permutational). Due to the use of permutational analyses, all F values presented are pseudo-F values and all p values are permutational p’s derived from 9999 permutations of the data.

I also tested the hypothesis that fish with slower larval growth rates had longer larval durations. I was able to do this for señorita, for which I could estimate PLD by counting all pre-settlement daily bands in their otoliths. Mean daily growth rate for an individual was estimated by dividing the size at settlement by the PLD. I then regressed

PLD on mean daily growth rates to determine how mean daily growth rates affected an individual’s total time spent in the plankton.

To evaluate whether habitat differed among sites, I completed a PERMANOVA on the habitat as quantified by RPC, giant kelp plant density, and giant kelp stipe density.

I then used a principle components analysis (PCA) (in Primer v6), to visualize and summarize the variation in habitat characteristics. These differences could potentially influence selection in these species.

To determine whether conspecific densities differed between sites or surveys, I completed a PERMANOVA on recruit densities, for señorita, and a separate

PERMANOVA on conspecific densities for blackeye gobies. PERMANOVA was used to analyze fish densities as they were not normally distributed and could not be made normal through transformations.

In addition to these analyses, I measured the intensity of selection for specific larval traits by comparing the differences in trait means between the settler group and the

18 one-month-old group. I calculated directional selection intensity, S, following Endler

(1986) as:

S = (Xfinal – Xinitial)/ SDinitial

Where X represents the trait mean either before or after selection, and SDinitial represents the standard deviation of the population before selection.

I tested whether selection intensity (S) on each larval trait was related to recruit density or habitat quality using linear regression. I completed simple linear regressions using SYSTAT v12. Habitat quality was quantified as the PCA scores for each site at each time.

Results

For both señorita and blackeye gobies, the multivariate analyses indicated differences in larval traits among sites, cohorts, and age groups (Tables 1 and 2). For señorita, site, cohort, the site  cohort interaction, as well as the site  cohort  age interaction were all significant (Table 1). For blackeye gobies, site, age, and the site  age  cohort interaction were all significant (Table 2). The presence of significant three- way interactions for both species indicates that any selection on larval traits was inconsistent among sites and cohorts. Separate univariate tests were completed to determine which larval traits were contributing to the significant and complicated multivariate results.

Pre-settlement growth rates in señorita showed no clear patterns of selection among sites or times (Fig. 2a, Table 3). Complicated patterns were found that were influenced by all three factors, site, cohort and age; as indicated by the significant three- way interaction (p=0.027). There was no significant difference in pre-settlement growth between age groups, new settler or one-month-old juvenile, as indicated by the non- significant results in all terms that included the age factor; and therefore there were no clear signs of selection (Table 3). Pre-settlement growth rates, however, did differ between cohorts, with individuals settling in June having on average slower growth rates than those individuals settling in July (p<0.001).

No clear patterns of selection on PLD were found for señorita; the main age effect was not significant, nor were any of the interactions including the age effect (Fig. 2b,

Table 4). PLD did differ between cohorts (p<0.001), with individuals settling in June

20 having longer PLDs than those settling in July (Fig. 2B). No other significant effects were found for PLD (Table 4).

Señorita showed evidence of selection on size at settlement, the direction of this selection, however, was not consistent between sites (site  age interaction: p=0.005; Fig.

2c). The four sites showed significant differences in size at settlement, with Little Geiger having the smallest individuals at settlement and Lion’s Head having the largest

(p<0.001). There were also differences in size at settlement between the June and July cohorts, with individuals settling in June being larger than those settling in July

(p=0.036).

Differences in señorita metamorphosis band width did not have any consistent patterns (Fig. 2D). However, the univariate analysis detected a three-way interaction

(p<0.001; Table 6). This indicated that metamorphosis band width may differ among all three factors, but no clear patterns of variation were apparent.

I completed two univariate tests of larval traits of the blackeye goby to determine which variables were contributing to the significant differences in the multivariate test

(Fig. 3). Pre-settlement growth rates were found to be significantly different among the sites, with the highest growth rates at Lion’s Head and the slowest at Little Gibraltar

(p=0.001). No other significant results for pre-settlement growth rates were found, indicating that there was not strong selection for this trait (Table 7, Fig. 3a).

For size at settlement of the blackeye goby, some evidence of selection for larger sizes at settlement was found; however this result was marginally non-significant

(p=0.053) and difficult to interpret as there was also a significant three-way interaction

(p=0.001). In addition to this finding, there were differences in the direction of selection

21 between sites, demonstrated through differences between settler and juvenile groups that were inconsistent in pattern among sites (site  age interaction: p=0.031; Fig. 3b). The other factors and interactions for size at settlement were not significant (Table 8).

A negative relationship between PLD and mean daily planktonic growth rates in the señorita was detected(p<0.001; Fig. 4). A non-linear relationship (y = 91.14e-0.32x) fit slightly better than a linear relationship (r2=0.59 vs. 0.58), though both were highly significant (p<0.001). Individuals with faster pre-settlement growth rates had shorter

PLD’s than those with slower pre-settlement growth rates. I found that PLD in señorita ranged from 22 to 53 days, with an average of 34.3 days (n=541). For blackeye gobies only a fraction of the otoliths used in the study had interpretable increments near the core

(n=50), however from these, I found their PLD to be between 40 and 76 days with an average of 59 days.

PERMANOVA analyses indicated that habitat characteristics did not differ significantly among sites (Table 9). In addition, recruit densities for señorita, and conspecific densities for blackeye gobies, showed no significant differences among sites

(Table 10 and 11). Principal components analysis (PCA) was completed to summarize habitat composition at each site (Fig. 5). The PCA explained 74.4% of the habitat variation with 3 PC’s: PC1 explained 33.8% of the variation, PC2 added 25.7% and PC3 added an additional 14.9% (Fig. 5). Little Geiger was characterized by high giant kelp densities and also large boulders and cobble bottoms. Little Gibraltar was the most different from Little Geiger with more green algae and sand. The two surveys from

Lion’s Head were more different than the two surveys at other sites were, with Lion’s

Head 2 having more sand than the first survey, which could be due to the fact that the

22 transects were not permanent and were therefore in slightly different locations each survey. Ripper’s was best described as having small and medium boulders for benthic composition and brown algae, other than giant kelp, for surface composition.

The scores for PC1-3 for each site and time were used to characterize habitat differences between the four sites because they summarized the majority of variation in habitat characteristics. These scores were then used in regression analyses to determine if habitat influenced selection intensity for any of the larval traits. Habitat variation, however, did not significantly explain selection intensity in either study species (Table

12). Nor was selection intensity of either species related to conspecific densities. Given that habitat characteristics and population densities did not differ significantly among sites, this finding is perhaps not surprising.

Discussion

Selection on larval traits in the two common kelp forest fishes studied here, señorita and blackeye goby, was found to be weak and inconsistent between sites. In addition, variation in selection intensity could not be explained by differences among sites in habitat or density of conspecifics. These findings of weak or inconsistent selection may explain why variation in larval traits is maintained in many marine species; as strong directional selection would ultimately lead to a decrease in trait variation.

No consistent patterns of selection were apparent in senorita; however some differences were found between larval traits of the two cohorts, i.e., fish settling in June or July. Individuals settling in June had longer PLDs (36.04 days) and slower growth rates (3.66 um/day) than individuals settling in July (PLD: 30.25 days, growth rates: 4.40 um/day). In addition, señorita settling in July, with faster growth rates, were smaller than those settling in June (otolith size: 101.3 vs. 106.9 um; approximately 12.6 vs. 13.1 mm

SL, for July and June cohorts, respectively).

Sponaugle et al. (2006) found a similar result with increased growth rates corresponding to shorter PLDs and slightly smaller settlement sizes, in a tropical wrasse, the bluehead wrasse, Thalassoma bifasciatum. They were able to explain variation in growth rates through changes in temperatures, with individuals that experienced higher temperatures having faster growth rates and shorter PLDs. This mechanism could potentially explain the variation in growth rate and PLD found in señorita in this study.

Individuals settling in July (in the plankton in June), with faster growth rates and shorter

PLDs, experienced temperatures that were on average 1.15°C warmer (NOAA weather buoy #46222, San Pedro Channel) than individuals settling in June. It may be that the

24 warmer water experienced by the later settlers in this study contributed to increased growth rates and earlier settlement.

I also found an inverse relationship between PLD and daily planktonic growth rates, such that with faster growth rates PLD decreased. This finding implies that an individual will settle onto a reef once some target settlement size range is reached. With faster growth rates this size is reached earlier, resulting in decreased PLDs.

This pattern of variable growth rates affecting PLD has been discovered in other studies (Cowen 1991, Sponaugle et al. 2006, Grorud-Colvert and Sponaugle 2011).

Cowen (1991) found much more variation in PLD than in size at settlement. His explanation for this finding was that there is some minimum developmental size for settlement and once a fish reaches this size they can either settle, if they are near suitable settlement habitat, or prolong their PLD through a slowing of daily growth rates. I did not look for variable daily growth rates over the entire planktonic stage, I used an average, so I cannot say whether this occurs in señorita as well; however it is one possible explanation for longer PLD’s with slower average growth rates.

The PLD range and average I found in this study for señorita were different from those determined by Victor (1986). I found a range of 22–53 days, with an average of

34.3 days, whereas Victor (1986) found a range of 36–43, with an average of 39.4 days.

The large difference in range found in this study compared to Victor was likely due to sample size differences. Victor examined 7 individuals whereas I examined 541. The

PLD for blackeye gobies had not been specifically stated in previous literature; Steele

(1997) described the PLD as being between 2 and 3 months. From the newly settled

25 individuals in this study the PLD seemed to be slightly shorter than this previously noted range, with a range of 40-76 days and average of 59 days.

In this study, I found evidence of selection on size at settlement in both study species, but the direction and intensity of this selection was varied among sites or across times (Table 5, Figure 2). In relation to the “growth mortality” hypothesis, it appears that some sites upheld the concept that “bigger is better,” whereas others did not. These differences in the direction of selection were not expected as the four sites were not significantly different in terms of habitat characteristics or population densities.

Other studies have also found evidence that selection can be quite variable. A study by Johnson and Hixon (2010) showed that selection on size and growth was variable across four sites in the Bahamas, however, adult density explained some of the variation in selection on size. In addition, a review by Siepielski et al. (2009) showed that the direction and strength of selection is often variable in time as well as space.

Siepielski et al. (2009) found variable selection on inter-annual scales. Both of these studies reveal a similar outcome: selection can vary across a variety of scales. This concept is supported in the present study with highly variable selection across very short distances and small time scales.

In addition to selection for size at settlement, blackeye gobies showed differences among sites in pre-settlement growth rates, but there was no selection on this trait. These differences in pre-settlement growth rates may indicate that the larvae experienced different conditions a week prior to settlement. It may be that the larvae were already near their settlement sites during this time period and experienced small

26 changes in temperature or food availability associated with individual sites, separate from the conditions they are experiencing throughout the rest of their planktonic duration.

None of the variation in selection on larval traits could be attributed to changes in the measured habitat characteristics. It is possible that other environmental influences that were not measured could explain the changes in selection in these species, for example small-scale temperature differences between sites, shelter availability or prey availability.

There are several possible reasons why no clear patterns of selection were found for any of the measured larval traits in either species in this study. One possibility is that selection may be occurring during a different time period than the one I examined. In this study, I was looking at selection occurring within the first month after settlement on the reef. It is possible that selection is occurring outside of this period. It is also possible that selection was washed out within the time period I studied by my choice of age ranges for grouping new settlers and one-month-old juveniles. Another possibility is that there is no selection on the traits I measured, but instead selection acts on some other larval trait that was not measured. For example, I examined pre-settlement growth rates averaged over the week prior to settlement. I chose this time period to see how the effects of conditions just prior to their settlement influenced survival. But it may be that some other time period in their larval development influences post-settlement success more strongly.

In this study, I examined four sites and two cohorts, whereas many previous studies have only examined a single site, or averaged across sites to determine selective mortality (Vigliola and Meekan 2002, Gagliano et al. 2007b). For example, Gagliano et

27 al. (2007b) examined a single cohort, exploring how different traits had carry-over effects on survival. They studied six sites, but their results were not divided by site, instead being combined into the one settlement cohort that was then sampled through time. It would be interesting to see whether in other systems, such as the one studied by Gagliano et al. (2007b) at Lizard Island, similar differences among sites occur as in my study. If I take a single site approach and examine only one location from this study, patterns appear much clearer. For example, señorita at Ripper’s Cove experienced selection for larger sizes at settlement in July. When multiple sites are included patterns of selection become inconsistent. For example, at Lion’s Head, there was selection for smaller sizes at settlement, the opposite of the pattern at Ripper’s Cove. These conflicting forms of selection make it difficult to generalize about selection in the species as a whole.

This study emphasizes that the outcome of selective mortality can vary over relatively small scales of time and space. General hypotheses, such as the “growth- mortality” hypothesis, are likely insufficient for explaining how larval traits affect survival after settlement in marine organisms. The widespread observation that larval traits can be quite variable within species is evidence in itself that selection on these traits is not simple and directional. Such variation in larval traits likely ensures that some fraction of offspring will have traits suitable for the environment they encounter after settling. Further study will be required to gain a more sound understanding of which traits are favored under certain sets of environmental conditions.

Tables and Figures

Table 1: Results of PERMANOVA testing for differences in otolith-derived larval traits of señorita among sites, cohorts, and ages. This test included as the dependent variables the traits PLD, settlement size, metamorphosis band width, and pre-settlement growth rates.

Source df (num.,denom.) Pseudo-F P (perm) Site 3, 525 2.92 0.002 Cohort 1, 3 26.99 <0.001 Age 1, 3 0.51 0.602 Site*Cohort 3, 525 2.10 0.023 Site*Age 3, 525 1.78 0.064 Cohort*Age 1, 3 0.14 0.964 Site*Cohort*Age 3, 525 3.10 0.002

Table 2: Results of PERMANOVA testing for differences in otolith-derived larval traits of the blackeye goby among sites, cohorts, and ages. This analysis included as dependent variable size at settlement and pre-settlement growth rates.

Source df (num., denom.) Pseudo-F P (perm) Site 3,375 4.08 <0.001 Cohort 1, 3 0.36 0.77 Age 1, 3 11.36 0.027 Site*Cohort 3, 375 1.03 0.402 Site*Age 3, 375 1.79 0.102 Cohort*Age 1, 3 1.79 0.262 Site*Age*Cohort 3, 375 3.37 0.003

Table 3: Results from univariate PERMANOVA testing for differences in otolith derived pre-settlement growth rates among sites, cohorts and ages in señorita.

Source df (num., denom.) Pseudo-F P (perm) Site 3, 525 0.74 0.530 Cohort 1, 3 55.37 <0.001 Age 1, 3 0.32 0.634 Site*Cohort 3, 525 2.16 0.098 Site*Age 3, 525 0.16 0.925 Cohort*Age 1, 3 0.03 0.892 Site*Cohort*Age 3, 525 3.06 0.027

Table 4: Results from univariate PERMANOVA testing for differences in PLD among sites, cohorts and ages in señorita.

Source df (num., denom.) Pseudo-F P (perm) Site 3, 525 0.02 0.996 Cohort 1, 3 40.95 <0.001 Age 1, 3 1.89 0.303 Site*Cohort 3, 525 2.51 0.063 Site*Age 3, 525 1.68 0.176 Cohort*Age 1, 3 0.06 0.821 Site*Cohort*Age 3, 525 1.47 0.221

Table 5: Results from univariate PERMANOVA testing for differences in otolith derived size at settlement among sites, cohorts and ages in señorita.

Source df (num., denom.) Pseudo-F P (perm) Site 3, 525 7.83 <0.001 Cohort 1, 3 9.03 0.036 Age 1, 3 0.10 0.764 Site*Cohort 3, 525 2.50 0.058 Site*Age 3, 525 4.36 0.005 Cohort*Age 1, 3 0.89 0.427 Site*Cohort*Age 3, 525 1.39 0.239

Table 6: Results from univariate PERMANOVA testing for differences in otolith derived metamorphosis band width among sites, cohorts and ages in señorita.

Source df (num., denom.) Pseudo-F P (perm) Site 3, 525 2.32 0.073 Cohort 1, 3 2.39 0.224 Age 1, 3 0.23 0.694 Site*Cohort 3, 525 1.36 0.259 Site*Age 3, 525 0.65 0.579 Cohort*Age 1, 3 0.04 0.886 Site*Cohort*Age 3, 525 6.09 <0.001

Table 7: Results from univariate PERMANOVA testing for differences in otolith derived pre-settlement growth rates among sites, cohorts and ages in blackeye gobies.

Source df (num., denom.) Pseudo-F P (perm) Site 3, 375 5.65 0.001 Cohort 1, 3 0.59 0.527 Age 1, 3 7.74 0.062 Site*Cohort 3, 375 1.20 0.302 Site*Age 3, 375 0.60 0.617 Cohort*Age 1, 3 0.55 0.521 Site*Age*Cohort 3, 375 0.84 0.477

Table 8: Results from univariate PERMANOVA testing for differences in otolith derived size at settlement among sites, cohorts and ages in blackeye gobies.

Source df (num., denom.) Pseudo-F P (perm) Site 3, 375 2.41 0.089 Cohort 1, 3 0.01 0.988 Age 1, 3 12.13 0.053 Site*Cohort 3, 375 0.86 0.455 Site*Age 3, 375 3.06 0.031 Cohort*Age 1, 3 1.97 0.235 Site*Age*Cohort 3, 375 6.08 0.001

Table 9: Results of PERMANOVA testing for differences in habitat characteristics among sites and surveys. This analysis included as dependent variables the results from the RPC transects as well as giant kelp plant and stipe densities.

Source df (num., denom.) Pseudo-F P (perm) Site 3, 64 1.56 0.08 Survey 1, 3 1.32 0.26 Site*Survey 3, 64 0.91 0.55

Table 10: Results of PERMANOVA testing for differences in conspecific new recruit densities among sites and surveys for señorita.

Source df (num., denom.) Pseudo-F P (perm) Site 3, 64 0.41 0.76 Survey 1, 3 2.79 0.21 Site*Survey 3, 64 1.15 0.34

Table 11: Results of PERMANOVA testing for differences in conspecific densities among sites and surveys for blackeye gobies.

Source df (num., denom.) Pseudo-F P (perm) Site 3, 64 2.56 0.06 Survey 1, 3 4.58 0.13 Site*Survey 3, 64 1.44 0.23

Table 12: Results of simple regressions testing for relationships between selection intensity for each larval trait and site characteristics in both señorita and blackeye gobies. The three principle components that explained 74.4%of variation in habitat characteristics were used. All results were non-significant (p > 0.05).

Señorita Blackeye Selection Intensity Site Characteristics r2 values r2 values Pre-settlement growth PC1 0.057 0.123 rates PC2 0.001 0.009 PC3 0.045 0.014 Conspecific density* 0.059 0.020 PLD PC1 0.244 NA PC2 0.007 NA PC3 0.002 NA Conspecific density 0.011 NA Size at settlement PC1 0.132 0.091 PC2 0.017 0.033 PC3 0.064 0.029 Conspecific density 0.007 0.182 Metamorphosis band PC1 0.048 NA width PC2 0.030 NA PC3 0.021 NA Conspecific density 0.045 NA * For conspecific densities, recruit densities were used for señorita, whereas for blackeye gobies densities of conspecifics of all sizes were used because recruit densities were very low.

Figure 1: Settlement transitions, indicated by the black arrows, in a señorita lapillus (A), and a blackeye goby lapillus (B). The señorita otolith shows this transition as a multiday band whereas the blackeye goby has an abrupt transition.

Figure 2: Means (±1 SE) of four larval traits of señorita at four sites, in two cohorts (June and July), and two ages (settler or juvenile). Each bar represents the mean of n = 7-89 individuals.

Figure 3: Means (±1 SE) of two larval traits of blackeye gobies at four sites, in two cohorts (June and July), and two ages (settler or juvenile). Each bar represents the mean of n = 7-59 individuals.

60 y = 91.14e-0.32x 50 r² = 0.59

PLD (days) PLD 20

0 0 1 2 3 4 5 Mean Daily Planktonic Growth (um/day)

Figure 4: The relationship between planktonic larval duration (PLD) (days) and mean daily planktonic growth rate (um/day); n=541.

Figure 5: Results of Principal Components Analysis (PCA) of habitat characteristics at four study sites during two time periods. The rosette in the center shows loadings of the various habitat characteristics onto PC1 and PC2, and the mean value of each site-time period combination is shown. Codes for habitat characteristics are as follows: B-S = benthic composition; sand, B-C = benthic composition; cobble, B-SB = benthic composition; small boulder, B-MB = benthic composition; medium boulder, B-LB = benthic composition; large boulder, B-SR = benthic composition; sheet rock, S-S = surface composition; sand, S-C = surface composition; cobble, S-SB = surface composition; small boulder, S-MB = surface composition; medium boulder, S-LB = surface composition; large boulder; RA= red algae; BA = brown algae; GA = green algae; MP = Macrocystis pyrifera; SD = Macrocystis pyrifera stipe density; and PD = Macrocystis pyrifera plant density.

Chapter 3

Selective mortality on larval traits in two coral reef fishes in Moorea, French

Polynesia

Introduction

Complex life histories in marine organisms provide the possibility for earlier life stages to affect an individual’s subsequent survival. In fish it has been proposed that settlement, the transition from a pelagic habitat to a benthic one, is a critical period in determining survivorship (Searcy and Sponaugle 2001, Doherty et al. 2004). It is considered a critical period due to an extremely high level of mortality at this transition

(Steele and Forrester 2002, Almany 2003, Doherty et al. 2004). Due to the high levels of mortality at the time of settlement, it has been proposed that selective mortality may act on larval traits at this time (reviewed in Anderson 1988 and McCormick 1998). Selective mortality occurs when specific traits are weeded out by higher mortality of individuals in a population that possess those traits.

Variation in larval traits is required for selection to occur, and there are many potential causes of this variation in larval traits. Two commonly referenced mechanisms of variation include parental effects (Chambers and Leggett 1996, McCormick 1999,

Green and McCormick 2005, Berkeley et al. 2004) and environmental effects

(McCormick and Molony 1995, Bergenius et al. 2005, Macpherson and Raventos 2005,

Sponaugle and Grorud-Colvert 2006, Sponaugle et al. 2006, Gagliano et al. 2007a). Both maternal and paternal effects have been shown to have an effect on larval condition

(Green and McCormick 2005). Green and McCormick (2005) showed that 52% of the variance in growth prior to metamorphosis, in a tropical clownfish, was due to an

37 individual’s paternity, but when combined with maternal effects and temperature, 30% of the variance in larval growth was explained. This study, by Green and McCormick

(2005), and others have started to examine how different environmental factors affect larval condition. A study by Sponaugle et al. (2006) on a tropical wrasse found that water temperature had a strong influence on larval growth rates and planktonic larval duration. They found that average water temperatures on a reef explained 78% of the variation in growth among 13 cohorts. These studies, as well as others (McCormick and

Molony 1995, Bergenius et al. 2005, Macpherson and Raventos 2005, Sponaugle and

Grorud-Colvert 2006, Gagliano et al. 2007a), have shown how important environmental influences may be to the variability in larval traits and selective mortality; however there are several other hypotheses that seek to explain the outcomes of selective mortality.

The “growth-mortality” hypothesis (Anderson 1988) is one of the alternate hypotheses used to explain the outcomes of selective mortality. This hypothesis argues that as a fish increases in size it decreases its number of possible predators, and so the faster a fish can reach a larger size, the less time they will spend in vulnerable stages, and the more likely it will survive. This hypothesis has been examined in many studies; however results have been mixed (Litvak and Legget 1992, Campana 1996, Searcy and

Sponaugle 2001, Good et al. 2001, Shima and Findlay 2002, Vigliola and Meekan 2002,

Wilson and Meekan 2002, Hoey and McCormick 2004, Raventos and Macpherson 2005,

Meekan et al. 2006, Sponaugle and Grorud-Colvert 2006). Many studies have upheld parts of the “growth-mortality” hypothesis. For instance, there is substantial support for the idea that faster growth rates increase survival. There is less support for the idea that having a larger size at settlement increases an individual’s chance of survival. A

38 potential reason why larger size at settlement may not be adaptive is that having a larger size makes an individual more visible to predators. The “growth-mortality” hypothesis works as a simple explanation for why some individuals have better survival, but many other factors likely play a role in determining individual survivorship.

Habitat variation among locations may also cause changes in the direction or strength of selective mortality. It seems likely that locations with differing quality or quantity of habitat will have different patterns of selective mortality. In coral-reef environments, as in others, the ability for young fish to shelter from predators is very important as predators are a major cause of post-settlement mortality (Steele and

Forrester 2002, Almany and Webster 2006). A study by Lecchini et al. (2007) found that new settling Chromis viridis had the lowest rates of mortality on a live branching coral,

Porites rus, which is their preferred settlement habitat. It is thus possible that individuals settling to reefs with a lower abundance of P. rus colonies might have differentially higher mortality than those on reefs with high densities of this coral.

As different habitats can influence selective mortality through differences in resource availability, so too can differences in species composition among fish communities. These differences in species composition can influence selection through differences in densities of conspecifics or predators. Differences in conspecific densities can influence selection through competition, and differing predator densities can also potentially cause differences in selection due to varying levels of predation pressure.

Holmes and McCormick (2006) found that size-selective mortality differed among reefs with different predator assemblages. They found that reefs with the highest density of predators of small fishes had the strongest size selection, with larger individuals

39 surviving better than smaller ones. Competition has also been shown to influence the survival of recently settled fishes (Carr et al. 2002, Almany 2003, Hixon and Jones

2005). Samhouri et al. (2009) examined how increased shelter may influence the direction of selective mortality in a Caribbean goby and found that while the amount of shelter did not have consistent effects on selective mortality, different adult densities had an effect on the direction of selective mortality. They found that in areas of high adult densities, larger individuals were favored, whereas in areas with low adult densities, smaller individuals were favored.

Both pre and post-settlement processes play an important role in determining the survival of larval fishes. Many environmental variables influence fish both before and after settlement. For example, parental effects occur prior to settlement, whereas competition and habitat largely affect individuals at or after settlement. Less attention has been paid to how post-settlement factors influence selective mortality than the effects of pre-settlement processes. Gaining a better understanding of how competition and habitat characteristics influence the outcome of selective mortality is important in understanding recruitment patterns and ultimate community structure.

In this study I explored selection on three different larval traits in recently settled coral reef fishes. I used otoliths to examine these larval traits in post-settlement fishes.

Otoliths are calcium carbonate structures found in the ears of fish that are used to sense gravity and sound. Many fish form daily rings in their otoliths, which allows for easy age determination. In addition to daily ring formation, when a fish settles into a different environment, this transition is often recorded in the otolith as a settlement mark (Victor

1982). Using the combination of daily ring formation and the formation of settlement

40 marks it is possible to determine larval traits of an individual that has already settled from the plankton. The three larval traits I evaluated in this study were size at settlement, planktonic larval duration (PLD), and pre-settlement growth rates. I chose size at settlement and pre-settlement growth rates to evaluate the “growth-mortality” hypothesis, to determine whether a larger size at settlement and faster growth rates are selected for or against. I examined PLD to determine the amount of variability in timing of settlement, as well as to see if the time an individual spends in the plankton is influenced by their growth rates.

I tested for selective mortality in two species of coral reef fishes, a goby and a damselfish, through a comparison of larval traits from newly settled individuals and one- month-old juveniles belonging to the same settlement cohort. The purpose of this study was to determine whether or not selection was occurring on larval traits in both study species, and whether selection differed between two locations.

Methods

Study Species:

In this study I examined the blue green chromis, Chromis viridis, and the goby complex, Gnatholepis scapulostigma /anjerensis. The goby (or gobies) I examined in this study is one or two species, as recently settled individuals can only be distinguished by

DNA confirmation. As older juveniles or adults, these two gobies, G. scapulostigma, and

G. anjerensis, are differentiated by the appearance of a spot dorsal to the pectoral fin in

G. scapulostigma (Figure 1). This spot is not visible in newly settled individuals, which have little pigmentation on the body besides the distinguishing feature of the Gnatholepis genus, a line through the eye (Thacker 2004). In addition, although the two species were believed to segregate by depth (Thacker 2004b, Thacker et al. 2008), that is not the case at the location studied here (pers. obs.). These two Gnatholepis species are ecologically very similar: they are benthic spawners that lay eggs in nests on the bottom and they are found in sandy areas near reefs, often in reef rubble (Thacker 2004b). These gobies have a wide distribution, from the Red Sea to the South and Central Pacific (Thacker 2004b).

Planktonic larval durations have not been determined for either of the two species in this species complex (Thacker 2004b). A closely related Caribbean member of the genus,

Gnatholepis thompsoni, was found to have a larval duration between 59 and 122 days, by

Shulman and Birmingham (1995), and between 46 and 112 days, by Sponaugle and

Cowen (1994). Hereafter, I will refer to the gobies as Gnatholepis sp.

The other species I examined in this study was Chromis viridis, a small planktivorous damselfish, which is found throughout the Indo-Pacific (Lecchini et al.

2005, Allen et al. 2003). Chromis viridis shelters in branching corals, often in Porites

42 rus at the study locations (Lecchini et al. 2005, 2007). Chromis viridis have also been found to settle most often to corals with conspecifics, creating large aggregations

(Lecchini et al. 2005, 2007). The range for the planktonic larval duration of this species is 21-29 days, which is much smaller than that for Gnatholepis sp. (Thresher et al. 1989).

Similar to Gnatholepis sp., there is also another Chromis species that closely resembles

Chromis viridis. Chromis atripectoralis is distinguished from C. viridis by the presence of a black area at the base of the pectoral fin (Allen et al. 2003, Froukh and Kochzius

2008). I excluded any individuals that exhibited this black area at the base of the pectoral fin in order to avoid including any C. atripectoralis. In addition, during field collections

I avoided schools of Chromis that had older individuals of C. atripectoralis present.

I chose to study these two “species" because they were settling in large numbers at the time of the study. In addition, they were expected to have very different planktonic larval durations. With such different planktonic larval durations, this study can provide insight into how differences in larval duration might influence selective mortality after settlement.

Study Sites:

This study took place in Moorea, French Polynesia, at two sites on the North side of the island. I examined two sites in this study to determine if patterns of selection were similar in different areas. The two sites were located on the East (17°28'38.01"S,

149°49'2.35"W) and West (17°28'47.55"S, 149°50'6.31"W) sides of Cook’s Bay, in the back reef. These sites will be referred to as MRB (Melissa’s Red Buoy) on the East side and WCB (West Cook’s Bay) on the West side. I chose these sites because they provide

43 suitable habitat for both study species, which were recruiting in large numbers at these locations. The sites were characterized by shallow reefs in <4 m depth, branching coral habitat for Chromis viridis, as well as large sandy areas with small coral colonies and reef rubble, which provide suitable habitat for Gnatholepis sp.

Collection Techniques:

Collections were completed between January and March of 2010, during the austral summer. I collected individuals in two age groups, new settlers (0-7 days post settlement) and one-month-old juveniles (30-37 days post settlement), in order to test for selection occurring within the first month after settlement. I collected approximately 50 individuals from each site within each age group for each species, totaling around 200 individuals for each species. I collected new settlers at the end of January and the beginning of February, and then I collected survivors from these cohorts one month after these initial collections. I collected all individuals using hand nets while on SCUBA.

For the Chromis viridis collections, I used clove oil as an anesthetic. All of the collected individuals were measured for standard length (SL) to the nearest tenth of a mm using calipers, and weighed to the nearest hundredth of a gram. All individuals were measured and weighed after being preserved in 95% ethanol.

Otolith Analysis:

I used a dissecting scope to aid removal of otoliths from all fish. I then used the otoliths to determine planktonic larval duration, size at settlement, and larval growth rates. The species in this study exhibit a settlement mark, which is distinguished by a

44 change in ring width, as well as a dark band on the otoliths (Figure 2). Otolith size is linearly related to somatic size for these two species, as well as for many others, which allowed me to use otolith traits as proxies for somatic traits (Gnatholepis sp. n = 112, r2 =

0.93; Chromis viridis n = 141, r2 = 0.98). I analyzed otolith traits rather than back calculated traits in order to avoid errors associated with back calculation.

Several larval traits can be determined from the otoliths due to the daily formation of rings and the presence of settlement marks. I determined planktonic larval duration

(PLD) from a count of the number of rings from the center of the otolith to the settlement mark. I used the width of otolith daily bands to determine daily growth rates; and I completed these measurements of daily growth rates over the week prior to settlement. I calculated growth rates during this time period to determine whether growth rates just prior to settlement influenced success after the settlement transition. I used the size of the otolith from the core to the settlement mark as an estimate of size at settlement. I completed all of the measurements using a compound microscope with an attached camera and Image-Pro Plus imaging software. I read all otoliths twice, and if these readings were not within 10% of each other then I read them a third time. If the third reading did not match one of the prior two readings, the otolith was not used in the analysis. These techniques allowed me to measure the mean and variation of each trait at settlement, and then again one month later in survivors of that cohort, to see if survivors had a non-random subset of the initial traits.

Surveys:

I completed habitat and fish surveys at each site in order to characterize any potential differences between the two sites. I completed nine 30-m-long by 2-m-wide transects at each site. These transects were placed in three locations on the reef, East, mid, and West; and then in three habitat areas on the reef, the sand and rubble, the reef edge, and the reef. I chose these habitat areas to include all the different habitats experienced by the focal species. For the fish surveys, fish were counted within an area created by one meter on either side, and one meter above the transects. All of the fish that were encountered were identified and counted. This was done to look for any differences in potential predator or conspecific abundances, which could account for any differences in selective mortality. I used the random-point-contact (RPC) method to quantify the major substrate types at each site, categorizing the substrate at a random point in every meter along each transect. The substrate was defined as either live coral, dead coral, macroalgae, sand, or “other” for these habitat surveys.

Data Analysis:

In order to determine if selection was occurring on any of the larval traits measured, I completed a permutational multivariate analysis of variance

(PERMANOVA) for each species using the software package PRIMER v6 with

PERMANOVA+. PERMANOVA was required for Gnatholepis sp. because the data were not normally distributed and could not be transformed to approximate normality.

The PERMANOVA model had two factors, site (MRB and WCB) and age (new settler and one-month-old juvenile), with both factors fixed. Before multivariate analysis, the

46 data were normalized to a mean of zero and standard deviation of 1 in order to put all of the variables on the same scale. Due to the use of permutational tests, all of the F values presented in the Results represent pseudo-F values, and the p values were obtained from

9999 permutations.

I tested whether there were any significant differences in larval traits between sites, age groups (new settlers vs. one-month olds), or any significant interactions between sites and age. If either the age groups, or the interaction between sites and age groups were significant, this could indicate selection on one of the larval traits measured.

When significant multivariate differences were found, I then used univariate

PERMANOVA tests to determine which variables were contributing to the differences revealed by the multivariate tests.

I used a principle components analysis (PCA), completed in PRIMER v6, in order to characterize site differences in substrate composition. I used transects as replicates in this analysis so that any differences in habitat types (sand/rubble, ecotone, reef) would be evaluated. I also completed a PERMANOVA to see if there were any significant differences in substrate composition between the sites, or habitat types at each site.

Lastly, I compared differences in predator densities between these two sites using a two- factor ANOVA, with site and habitat type as fixed factors.

To see if there was a significant relationship between larval growth rates and time spent in the plankton, used linear regression to evaluate whether PLD varied as a function of larval growth rate. This analysis tested whether there was a growth-PLD tradeoff, with slow growing fish having longer PLDs. SYSTAT v12 was used to conduct the regressions and ANOVA.

Results

Multivariate analysis revealed no evidence for selection on any of the larval traits measured in Gnatholepis sp., as there were no significant differences in larval traits at the two sites or between the two age groups (Table 1, Fig. 3). Because the multivariate analysis for this species revealed no significant differences, further univariate tests were not justified.

The multivariate analysis for Chromis viridis indicated that there could potentially be selection on one or more of the larval traits measured. Larval traits of Chromis viridis differed significantly between sites and age groups, and these differences between age groups were not consistent between sites, i.e., there was a site  age interaction (Table 2).

Due to the potential for selection on one or more of the measured traits, separate univariate tests were completed to determine which larval traits were contributing to the multivariate significance (Tables 3-5).

There was consistent selection for larger size at settlement in Chromis viridis, but selection on pre-settlement growth and larval duration (PLD) was inconsistent between the two study sites. Individuals in the survivor (juvenile) group had on average larger sizes at settlement than those in the initial (new settler) group at both sites (age effect: p=0.001; Table 5, Figure 4). In addition to selection on size at settlement, individuals settling at WCB were generally larger than those at MRB (site effect: p=0.001; Figure 4).

There was more rapid pre-settlement growth in survivors (juvenile group) than the initial

(new settler) group at WCB, but no difference between age groups at MRB (significant site  age interaction, p=0.039; Figure 4). This result indicates that selective mortality on pre-settlement growth rates occurred at WCB but not at MRB. The survivor (juvenile)

48 group at MRB had higher PLDs than the initial (new settler) group, indicating selection for longer PLDs; however there was very little difference in PLD at WCB (age effect: p=0.016; site  age interaction: p=0.019; Figure 4).

The principle components analysis indicated that the habitat types surveyed were similar at the two study sites, with the edge and middle habitats being characterized mostly by sand with occasional coral, and the inner habitat characterized by more coral, either dead or alive (Figure 5). PERMANOVA indicated that there was no significant difference in substrate composition between the two study sites, but there were differences among the three habitat types: sand-rubble (edge), sand-coral ecotone

(middle), and reef (inner) (Table 6). The two sites showed the same pattern in substrate composition among the different habitats surveyed (site  zone interaction: p=0.42).

Because the habitat at two study sites was very similar, the variation detected in larval traits cannot be related to habitat variation.

Like the habitat characteristics, the sites were also very similar in predator densities, which also did not differ among habitat types (Table 7; Figure 6). The potential predators that were identified included two wrasses, Thalassoma hardwicke and

Halichoeres trimaculatus, two triggerfishes, Rhinecanthus aculeatus and Melichthys vidua, one grouper, Epinephelus merra, one emperor, Lethrinus olivaceus, and one jack,

Caranx melampygus. These results indicate that predator densities also seem unlikely to explain differences in selective mortality between the two sites. Differences in densities of conspecific were not analyzed because both of the study species were patchily distributed and I did not feel that the surveys accurately described the populations at the sites.

The analyses on growth rates mentioned above were done on pre-settlement growth rates over the week prior to settlement. In order to determine whether growth rates over an individual’s entire larval duration influenced the amount of time that individual spent in the plankton, regressions of larval duration on growth rate were completed for each species. For both species there was a negative linear relationship between mean daily growth rate and PLD; individuals with higher growth rates had shorter PLD’s. The relationships between growth rates and PLD appeared to be linear for both of the study species (Figs. 7 and 8). The range of PLD’s for Gnatholepis sp. was 38 to 76 days with an average of 54 days (n= 112); and 17 to 23 days with an average of

19.7 days for Chromis viridis (n= 141).

Discussion

For the species and potential species complex I examined in this study I found differing results in terms of selection. For Gnatholepis sp. I found no significant differences between sites or age groups across the three larval traits. No differences between the two age groups, settler and juvenile, indicates that there was no selection on the larval traits measured. In addition, there were no differences between the two sites, which would not necessarily be expected because the habitat characteristics and predator densities were similar between the two sites. In addition to the similarity of the two study sites, it is also possible that any differences could have been washed out by the presence of more than one species in the collection. It is possible that two Gnatholepis species that are morphologically indistinguishable as juveniles were collected, despite claims that the two species segregate by depth. If two species were collected, they might have experienced differed selection on larval traits, which could have obscured any patterns of selection within a species.

Unlike Gnatholepis sp., Chromis viridis exhibited significant variation in larval traits (Tables 2-5) that in some cases revealed selection on larval traits. I found that there was selection for larger size at settlement at both sites, but the cause for this larger size at settlement was possibly different between the two sites. At WCB there was selection for faster pre-settlement growth rates, but PLD remained the same between age groups. At

MRB, however, the opposite pattern was found, with no selection on pre-settlement growth rates but selection for longer PLDs. The different responses at the two sites indicate that there could be different mechanisms driving selection for larger sizes at settlement.

The results from Chromis viridis support part of the “growth-mortality” hypothesis, individuals that settle at larger sizes survive better. It is noteworthy that individuals at the two sites appeared to take different paths to achieve large size at settlement. As mentioned previously, at WCB, along with selection for larger size at settlement there was also selection for faster pre-settlement growth rates just prior to settlement. There is substantial evidence in the literature supporting selection for faster growth rates (Searcy and Sponaugle 2001, Vigliola and Meekan 2002, Wilson and

Meekan 2002, Sponaugle 2010, Grorud-Colvert and Sponaugle 2011), but faster growth rates do not always lead to larger sizes at settlement (Shima and Findlay 2002, Sponaugle and Grorud-Colvert 2006). At MRB on the other hand, selection for larger sizes was not coupled with selection on growth rate, but instead with selection for longer PLDs. These results differ from those found in other studies, which have more frequently found selection on PLD and growth rates, but no size selection. For instance, Shima and

Findlay (2002) found that individuals with faster growth rates settled earlier than individuals with slower growth rates, but at approximately the same size. They also found selection for faster growing individuals, but there was no size selection. The present study suggests that selection on size at settlement can be achieved via different pathways: selection on larval growth rates or larval duration. Differing selection regimes appeared to be unrelated to habitat characteristics or predator densities at the study sites.

In addition to the selection results, both species showed that individuals with faster growth rates, on average, had shorter PLDs. It may be that individuals have a specific size range at which they are capable of settling, and PLD is flexible and depends on how quickly an individual reaches the settlement capable size. This pattern of

52 variable growth rates affecting PLD has been seen in other studies (Grorud-Colvert and

Sponaugle 2011, Sponaugle et al. 2006, Cowen 1991). Sponaugle et al. (2006) found that increased growth rates corresponded with shorter PLDs in a tropical wrasse, the bluehead wrasse, Thalassoma bifasciatum, which is similar to what I found in both of the species in this study. A study by Cowen (1991) also showed variation in PLDs in a temperate wrasse, Semicossyphus pulcher. In this study he found that there was much higher variation in larval duration than in size at settlement. He attributed this to a slowing in daily growth rate after a minimum developmental time was reached in the plankton, allowing for extension of the planktonic phase with minimal change in size.

Size at settlement does not change predictably with PLD for the two species in this study.

This finding is more evidence for the need to reach some minimum size before settlement.

This study contributes to the growing body of knowledge on the effects of early life history traits on post-settlement survival. It provides further support for the “growth- mortality” hypothesis, indicating that individuals that settle at a larger size have better survival than individuals that are small at settlement. This study also shows that selection on larval traits can vary at a small scale, e.g., between two reefs less 2 km apart. These results highlight how important small-scale complexities can be in determining the outcomes of selective mortality, and they indicate that it may be difficult to use unreplicated small-scale studies to infer whole-population patterns.

Tables and Figures

Table 1. Results of PERMANOVA testing for differences in Gnatholepis sp. otolith- derived larval traits among sites, and ages. This test included as the dependent variables the traits PLD, settlement size, and pre-settlement growth rates.

Source df (num.,denom.) Pseudo-F P (perm) Site 1,108 1.20 0.293 Age 1,108 0.17 0.905 Site*Age 1,108 1.40 0.262

Table 2. Results of PERMANOVA testing for differences in Chromis viridis otolith- derived larval traits among sites, and ages. This test included as the dependent variables the traits PLD, settlement size, and pre-settlement growth rates.

Source df (num.,denom.) Pseudo-F P (perm) Site 1,117 5.74 0.003 Age 1,117 9.86 0.001 Site*Age 1,117 4.24 0.006

Table 3. Results from univariate PERMANOVA testing for differences in otolith derived pre-settlement growth rates among sites and ages in Chromis viridis.

Source df (num.,denom.) Pseudo-F P (perm) Site 1,117 0.41 0.539 Age 1,117 1.74 0.221 Site*Age 1,117 4.45 0.039

Table 4. Results from univariate PERMANOVA testing for differences in otolith derived PLD among sites and ages in Chromis viridis.

Source df (num./denom.) Pseudo-F P (perm) Site 1,117 0.02 0.887 Age 1,117 5.48 0.016 Site*Age 1,117 5.83 0.019

Table 5. Results from univariate PERMANOVA testing for differences in otolith derived size at settlement among sites and ages in Chromis viridis.

Source df (num.,denom.) Pseudo-F P (perm) Site 1,117 20.48 0.001 Age 1,117 26.74 0.001 Site*Age 1,117 1.89 0.16

Table 6. Results of PERMANOVA testing for differences in habitat characteristics among sites and zones. This analysis included as dependent variables the results from the RPC transects.

Source df (num.,denom.) Pseudo-F P (perm) Site 1,117 2.31 0.06 Zone 1,117 5.92 <0.001 Site*Zone 1,117 1.05 0.42

Table 7. Results from two-factor ANOVA comparing predator densities between the two sites.

Source df (num.,denom.) Pseudo-F P (perm) Site 1,12 0.85 0.38 Zone 2,12 0.45 0.65 Site*Zone 2,12 0.08 0.92

Figure 1. Gnatholepis anjerensis is pictured on the top and Gnatholepis scapulostigma on the bottom. These individuals were collected on the same day at the same site and depth. The spot dorsal to the pectoral fin on Gnatholepis scapulostigma is used to distinguish these species, and is noted with an arrow.

Figure 2. Sagittal otoliths from Chromis viridis (A) and Gnatholepis sp. (B). The settlement transition is noted with an arrow on each image. These images were captured at 200x magnification.

Figure 3. Means (±1 SE) of three larval traits (mean daily growth, PLD, and settlement size) of Gnatholepis sp. at two sites (MRB and WCB), and two ages (settler or juvenile). Each bar represents the mean of n = 12-51 individuals.

Figure 4. Means (±1 SE) of three larval traits (mean daily growth, PLD, and settlement size) of Chromis viridis at two sites (MRB and WCB), and two ages (settler or juvenile). Each bar represents the mean of n = 11-52 individuals.

Figure 5. Results from the location-level PCA for the two study sites in Moorea. The results from transects in each habitat location are plotted on the graph of principle components 1 and 2, which combined explain 89.5% of the variation in the data. Transects are labeled with the site (WCB or MRB) and the location on the reef: edge (E), the sand and rubble habitat, middle (M), the reef sand transition and inner (I), on the reef.

0.18

0.16

) 3 0.14 0.12 0.1 0.08 MRB 0.06 WCB 0.04 Predator Density (#/m Density Predator 0.02 0 sand and rubble reef edge reef Habitat Type

Figure 6. Mean densities (±1 SE) of potential predators between the two sites divided according to habitat type (sand and rubble, reef edge, and reef).

80 70 y = -11.29x + 100.61 r² = 0.53

60 50

40 PLD PLD (days) 30 20 10 0 0 1 2 3 4 5 6 7 Mean daily planktonic growth (um/day)

Figure 7. Relationship between mean planktonic growth rates and planktonic larval durations for Gnatholepis sp., n=112.

25 y = -0.95x + 34.24 r² = 0.53

10 PLD (days) PLD

0 10 12 14 16 18 20 Mean daily planktonic growth (um/day)

Figure 8. Relationship between planktonic larval duration (days) and average daily planktonic growth (um/day) for Chromis viridis, n=141.

Chapter 4

Conclusions

I examined selection on larval traits in four different fishes, two temperate and two tropical species. I found some trends that were consistent between both temperate and tropical environments. For the three species in which PLD was examined, including one temperate and two tropical species, it appears that average daily growth over the planktonic larval phase influences the duration of the planktonic phase. Individuals with faster growth rates tended to settle earlier than those with slower growth rates. The effects of growth rates on PLD have been examined in several studies and the results have been similar: individuals with faster growth rates tend to settle at younger ages

(McCormick and Molony 1995, Sponaugle et al. 2006, Sponaugle and Grorud-Colvert

2006, Grorud-Colvert and Sponaugle 2011).

The mechanism causing this relationship is less obvious. There is fairly strong evidence that temperature and food abundance influence growth rates; however less is known about how fishes time settlement and variation in this timing. A study by Cowen

(1991) showed that individuals could postpone settlement after reaching a minimum developmental stage by slowing growth rates. This mechanism for extending PLD could be useful in providing extra time to find suitable settlement habitat. I did not examine variation in daily planktonic growth rates over the entire larval stage in this study; however this mechanism may explain why there is often more variation in PLD than in size at settlement. Señorita in this study were found to have a wide range of settlement ages, from 22 to 53 days. It is possible that a similar mechanism to that found by Cowen

(1991), could be found working in this species, with growth slowing after some minimum

60 developmental stage causing the overall slower growth rates present in individuals with longer PLDs.

Both temperate and tropical studies also show evidence of variation in the direction or strength of selection acting at small scales. At Catalina, differences in the direction and strength of selection on larval traits were evident at different sites and times. Some sites exhibited strong selection for a trait whereas others showed little or no selection on that same trait. In addition, in the study done in Moorea, selection on different larval traits was evident between two reefs less than 2-km apart. One site had selection for longer PLD and no selection on growth rates, whereas the other site had selection for faster growth rates but no selection for PLD. A review by Siepielski et al.

(2009) also found that it was common for there to be changes in the direction and strength of selection through time. Additionally, a study by Holmes and McCormick

(2006) highlighted differences in size-selective mortality on reefs between 200-m and

1.2-km apart. These differences in the outcomes of selection may be important for maintaining variation in the population. Such variation helps to ensure that some subset of the larvae are capable of surviving the particular selection regime in a new potentially variable habitat. If strong directional selection were to occur at all sites, trait variation would be reduced, which could leave a population more vulnerable to extinction if there was a widespread change in conditions, e.g., global climate change.

My study emphasizes that selection on larval traits and the larval traits themselves can be highly variable in both space and time. General hypotheses, such as the “growth- mortality” hypothesis, although often supported, as in the study in Moorea, are likely too simplistic to be widely applicable. The fact that larval traits are highly variable provides

61 further evidence that selection is likely not strongly directional, as this would eventually decrease variation in these traits in the population. Understanding the causes of variation in larval traits in these populations and how variation is being maintained, such as through selective mortality, will help to understand and predict recruitment dynamics as well as subsequent population dynamics and community structure. Future research is needed in order to determine how more simplistic hypotheses, such as the “growth- mortality” hypothesis, can work together with more complex environmental conditions in order to be able to predict the outcome of selection on larval traits in populations.

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