CALIFORNIA STATE UNIVERSITY, NORTHRIDGE Evaluating the Effects of Predation Risk on Reproduction of a Temperate Reef Fish a Thes

CALIFORNIA STATE UNIVERSITY, NORTHRIDGE

Evaluating the Effects of Predation Risk on Reproduction of a Temperate Reef Fish

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

By George Colebrook Jarvis

May 2019 The thesis of George Colebrook Jarvis is approved:

______Dr. Larry G. Allen Date

______Dr. Casey P. terHorst Date

______Dr. Mark A. Steele, Chair Date

California State University, Northridge

iii Acknowledgement

I would like to thank everyone whose support has allowed me to accomplish so much during the past three years. My advisor, Mark Steele, has been a stabilizing and supportive mentor, challenging me to become a better thinker, scientist, and handler of gobies. My committee members, Drs. Larry Allen and Casey terHorst, have been there to guide me through this process with sound advice, science-related or otherwise. I am thankful to Dr. Mia Adreani, who was there to help me with my field work and talk though logistics of my project. I would like to thank Dr. Nyssa Silbiger for all her help with statistics, specifically for advice on how to code more effectively. Thank you to all the staff at the USC Wrigley Marine Science Center for facilitating my research. Thank you to all the undergraduate students who helped me with this project, despite constant modifications to my experimental approach. I hope that you learned as much from me as

I have from all of you. To the members of the Steele Lab, past and present, I cannot thank you enough for your friendship and support over the years. I attribute my positive graduate experience to all of you.

This research would not have been possible without funding from the National

Science Foundation, the American Academy of Underwater Sciences, the PADI

Foundation, Sigma Xi, the International Women’s Fishing Association, the Southern

California Academy of Sciences, and the CSUN Office of Graduate Studies.

Lastly, I would like to thank my family, whose love and support during my academic pursuits has been instrumental in my development. I am hopeful that all this time away from home will pay off in the end.

v Table of Contents

Signature Page ii

Acknowledgement iii

List of Figures v

Abstract vi

Introduction 1

Materials and Methods 4

Results 13

Discussion 17

Literature Cited 26

Appendix A: Tables 31

Appendix B: Figures 38

vi List of Figures

Figure 1. Perching behavior of bluebanded gobies 38

Figure 2. Map of Santa Catalina Island and reef array in Big Fisherman Cove 39

Figure 3. Reef schematic and caging designs for each risk treatment 40

Figure 4. Reef designs and caging treatments in situ 41

Figure 5. Male nesting behaviors and evidence of nest sharing 42

Figure 6. Time-lapse photo and score classifications for assessment of predators 43

Figure 7. Reproductive output per reef compared among risk treatments 44

Figure 8. Proportion of gobies recollected at the end of each experiment, compared 45 among risk treatments

Figure 9. Number of gobies observed on reefs throughout experiments, compared 46 among risk treatments

Figure 10. Proportion of time gobies were exposed on reef structure, compared 47 among treatments

Figure 11. Total distance moved, compared among risk treatments 48

Figure 12. Foraging rates of bluebanded gobies, compared among risk treatments 49

Figure 13. Courtship rates of bluebanded gobies, compared among risk treatments 50

Figure 14. Movement rates of bluebanded gobies, compared among risk treatments 51

Figure 15. Predator abundances and scores, based on their relative distances to the 52 reef in time-lapse photos

vii Abstract

Evaluating the Effects of Predation Risk on Reproduction of a Temperate Reef Fish

By George Colebrook Jarvis Master of Science in Biology

How an organism responds to predation risk can greatly affect its reproductive success. When threatened by predators, prey often change their foraging and mating behavior, presumably to maximize current and future fitness. These responses have been studied in numerous terrestrial and aquatic taxa, yet how risk affects reproductive output in marine fishes is poorly understood. To determine whether risk directly affects fitness in nature, I tested the effects of predation risk on reproductive output and behavior of the bluebanded goby, Lythrypnus dalli. During three experiments, similar populations of gobies were established on artificial reefs and predator exclusion cages were used to manipulate perceived and actual risk of predation. Reefs were assigned one of three

viii caging treatments to alter the level of risk that gobies likely perceived from predators: large exclusion (low risk); small exclusion (no actual risk, but perceived risk); and no exclusion (actual and perceived risk). Reproductive output and behaviors of gobies were compared among risk treatments, and all gobies that remained on the reefs at the end of each experiment were recollected to assess any effects of risk and predation on survival of L. dalli. Remote video revealed that the treatments manipulated the presence and proximity of predators as intended. Gobies altered their behavior in the presence of predators, but despite this, reproductive output was similar among all risk treatments.

Similar numbers of gobies were present in all treatments, but they were observed less frequently in high-risk treatments because they spent more of their time hidden within the reef. These results indicate that sublethal effects of predators did not reduce fitness of L. dalli over periods of 1-4 weeks. Based on their relatively short lifespan and duration of lifetime spawning, L. dalli may be less affected by the sublethal effects of predators than other fishes, at least in terms of reproductive output.

1. Introduction

Predators shape prey communities through their lethal (density-mediated) and sublethal (trait-mediated) effects. In risky environments, parents face fitness trade-offs between survival and future reproduction (Williams 1966), and evolutionary theory predicts that prey should increase parental investment when the potential for future reproduction is low (Clark & Ydenberg 1990). The effects of increased risk can reduce prey fitness physiologically, through the production of increased stress hormones

(reviewed by Boonstra 2013), but also behaviorally, whereby changes in rates of conspicuous behaviors related to reproduction, such as foraging and courtship, alter

reproductive success in prey (reviewed by Sih 1994, Lima & Bednekoff 1999). Decisions made in risky environments can severely affect fitness and future reproductive success, but how prey respond to risk depends on a suite of exogenous and endogenous factors

(Reznick et al. 1990, Bårdsen et al. 2010, Ghalambor et al. 2013).

Whether prey alter foraging and mating rates in response to predation risk or maintain rates of each behavior despite the likelihood of predation, depends on the severity of risk cues perceived by prey (Peers et al. 2018) and the adaptive plasticity of an organism to cope with risk (Lima & Bednekoff 1999). The severity of perceived risk on fitness can manifest itself as the frequency (i.e. chronic or acute) and intensity of risk cues (i.e. more or less threatening), and prey typically respond to cues based on their condition and access to available refuge space (Matassa et al. 2016). In general, prey in poorer condition, with less access to suitable refuge space, will be more willing to suppress reproductive output and forage in risky areas to maximize current fitness

(reviewed by Schmitz & Trussell 2016). The effects of risk on fitness also depend on the

reproductive life history and plasticity of a threatened individual. Prey with lifespans that are relatively short have limited potential for future reproduction, generally exhibit more investment in reproduction than longer-lived prey when levels of perceived risk are high

(Magnhagen & Vestergaard 1991). This response can also depend on the reproductive mode of prey, as behaviors related to fitness (e.g., foraging and mating) typically increase the conspicuousness of prey to predators (Clark & Ydenberg 1990).

Although risk effects have been well studied in terrestrial and freshwater systems

(see reviews by Werner & Peacor 2003, Peckarsky et al. 2008), there are fewer studies that examine these effects in marine systems, particularly fishes (Magnhagen 2008). Of

the studies that do exist, most are correlative, speculating that predator avoidance behaviors may lead to reductions in fitness (Walsh et al. 2012, Rizzari et al. 2014,

Kindinger & Albins 2016). Such studies may misinterpret the effects of risk on fitness of fishes, at least in reef ecosystems (Davis et al. 2017), because they often only consider a single behavioral response to risk from predators (e.g. foraging rate), but the importance of behavior on fitness likely varies among fishes. Studies that have directly examined effects of predation risk in marine fishes have been limited to laboratory or shallow intertidal environments (Magnhagen 1990, Magnhagen & Vestergaard 1991). Those studies have revealed that responses of fishes to predation risk depend on reproductive life history and degree of parental care, where species with longer lifetime spawning periods and lower parental investment have higher reproductive plasticity and are more likely to suppress reproduction when perceived risk is high. Whether these responses differ in populations of free-living fishes is not known.

Manipulating predation risk in populations of free-living marine fishes could provide a more comprehensive view of the relative effects of lethal and sublethal effects of predators. However, testing the sublethal effects of predators on fishes is difficult in marine environments because of the transient nature of piscivores (Hixon 1991), and our lack of knowledge of the stimuli (e.g., visual or olfactory) by which prey perceive predators in the ocean (but see McCormick & Manassa 2008). For fishes that rely on visual cues to detect risk, limiting predator access to prey in areas where predators are naturally abundant might allow for a more effective assessment of the effects of risk in marine fishes.

I tested the effects of predation risk on reproductive output in a marine fish, the bluebanded goby (Lythrypnus dalli Gilbert). Previous field studies found reductions in foraging and increases in time spent hiding during high-risk periods (Steele 1998, Steele

& Forrester 2002), which may lead to reduced fitness in this species. Yet, whether predation risk affects reproductive output and associated mating behaviors in adult bluebanded gobies is unknown. Here I test the hypothesis that bluebanded gobies in high- risk environments spend more time hiding to reduce conspicuousness to predators, leading to reduced foraging and courtship behaviors that result in lower reproductive output.

2. Materials and Methods

2.1. Study species

The bluebanded goby is a small fish with high site fidelity that is highly abundant in complex, rocky reef habitats at Catalina Island. This species forms harems ranging from 24-58 individuals per square meter that are typically female-skewed (Behrents

1983). Spawning usually occurs between May and November, with peak reproduction occurring during June, July, and August (Wiley 1976). L. dalli exhibits a high degree of parental care, provided by males that guard nests. Females lay demersal eggs in nests established in abandoned shells and rock crevices, and males fertilize, guard, and aerate the eggs deposited in their nest (Behrents 1983). Eggs are laid in a single layer, and they hatch as free-floating larvae after 4-7 days (Archambeault et al. 2015). Bluebanded gobies readily spawn in artificial nests (St. Mary 1994, Kappus & Fong 2014), presenting an attractive model system for quantifying reproductive output in response to predation risk.

Bluebanded gobies spend most of their time perched on top of reef structure, which provides a vantage point for foraging on zooplankton, being vigilant of predators, and observing and interacting with conspecifics (Fig. 1). When threatened, individuals will hide within crevices or holes (Behrents 1987). The kelp bass, Paralabrax clathratus, is the most abundant piscivore at Catalina Island (Holbrook & Schmitt 1988) and is known to invoke hiding behavior in bluebanded gobies (Steele 1998). However, other species, including the rock wrasse, Halichoeres semicinctus, and California sheephead,

Semicossyphus pulcher, also induce a hiding response in bluebanded gobies, and are known to consume them opportunistically (Steele 1995). Courtship and foraging

behaviors of bluebanded gobies have the potential to increase conspicuousness to predators and thus decrease fitness (Lima 1998).

2.2. Study site

I conducted all experiments at Santa Catalina Island, USA (33°82′79′′ N;

118°82′99′′ W) in Big Fisherman Cove, a site with a subtidal sand plain bordered by rocky reefs (Fig. 2). Predators in Big Fisherman Cove are representative of those on adjacent natural reefs where bluebanded gobies were collected for this study. I conducted experiments on a set of 18 or 20 reefs, depending on the experiment, that I constructed in a single line along an 8-m-depth isobath along the southern edge of Big Fisherman Cove.

I built reefs with rocks (55 L, or ~40 rocks) ranging from 20-40 cm long, piled on top of acrylic mesh panels (0.75 x 0.75 cm, 2 x 2 cm mesh). I separated reefs from adjacent plots and nearby natural reefs by a minimum distance of 7 m to deter emigration of gobies from them (St. Mary 1994).

2.3. Experiments

2.3.1. General description

I conducted three caging experiments during the summers of 2017 and 2018, all aimed at examining the potential effects of risk on reproductive output in bluebanded gobies. I conducted Experiment 1 over week-long trials in 2017 and characterized relatively short-term responses of bluebanded gobies to risk from predators. I used a similar design in Experiment 2, but I conducted the study over two, month-long trials in

2018, with potential to capture longer-term responses to risk. In Experiment 3, where I tested the same responses as Experiment 1 and 2, but over a two-week period in August

of 2018, I included an uncaged treatment and compared reproductive output and behaviors of bluebanded gobies between caged (i.e. low, medium, and high) and uncaged reefs.

2.3.2. Fish collections and tagging

To examine the effects of risk on reproduction of bluebanded gobies, I established similar initial populations of marked gobies on all reefs. I collected gobies with hand nets from Isthmus Reef (33°44′89′′ N; 118°48′8′′ W), which is 0.6 km from Big Fisherman

Cove, and then transported them to the USC Wrigley Marine Science Center. I tagged fish subcutaneously (Visual Implant Elastomer, Northwest Marine Technology) to mark

their initial size. How fish were handled during tagging differed among experiments. For

Experiment 1, to establish known sex ratios, I briefly sedated the bluebanded gobies with tricane methanosulfate (MS-222, 0.7mg/1L seawater) to facilitate tagging and sexing (as in Kappus & Fong 2014). I gathered tagged fish into groups of 20 adult individuals (20-

35 mm) consisting of 5 males and 15 females, which was representative of sex ratios found on natural reefs during our collections. I then assigned these groups randomly to reefs and deployed them over the course of two days. In Experiment 1, each population had the same size structure, sex ratio, and number of visibly gravid females (Wiley 1976) to control for any size or sex-dependent responses to predation risk. In Experiments 2 and

3, I did not sedate or sex fish prior to tagging, because I suspected that some aspect of this process was causing high mortality rates of the fish after they were placed in the field. I standardized initial populations of gobies based on natural size distributions at the time of collections, which should, on average, have resulted in the same sex ratio in all treatments. I confirmed the sex ratio of fish by examining the extra collected fish not used

in the experiment; assuming similar sex ratios of fish that were collected, the sex ratio of extra fish was 1:3 male to female in Experiments 2 and 3, which was the same as in

Experiment 1. To limit handling stress, individuals placed on reefs were not weighed.

However, initial biomass placed on each reef was estimated from a length-weight relationship established from fish not used in the experiment.

2.3.3. Risk treatments

I covered reefs with one of three cage types to simulate risk from predators: no actual risk, and likely no perceived risk (hereafter referred to as “low risk”); no actual risk, but likely low perceived risk (hereafter referred to as “medium risk”); and actual

risk, with likely high perceived risk (hereafter referred to as “high risk”) (Fig. 3). I included an additional uncaged treatment in Experiment 3 to test for cage artifacts, where actual and perceived risk were likely most similar to those in the high-risk treatment.

Cages manipulated predator access to reefs, as well as the physical distance between predators and prey. Previous experiments have shown that bluebanded gobies increase their avoidance behavior (Steele 1998) and experience higher mortality rates (Steele

1999) when predators are allowed full access to prey habitats, so manipulating access and proximity stimuli was a logical way to test effects of perceived risk. Risk treatments were randomized in a constrained design before every trial within all experiments, where no adjacent reefs were assigned the same treatment.

I covered reefs with square PVC cages of two different dimensions: large

(1.5x1.5x1.0 m) for the low-risk treatment; and small (0.5x0.5x 0.5 m) for the high and medium-risk treatments. I wrapped cages for the low and medium-risk treatments entirely in monofilament netting (0.5 x 0.5-cm mesh), which excluded all predatory fishes but

allowed for movement of gobies on and off the reef (Fig. 4). The center of each reef structure was 0.75 or 0.25 m away from the nearest edge of the cage in the low, and medium and high-risk treatments, respectively. I chose these distances because common predators of bluebanded gobies elicit a behavioral response when they swim within distances of ~ 0.3 m of an individual on natural reefs (Jarvis, personal observation).

2.3.4. Nest surveys and egg counts I measured reproductive output by counting eggs deposited in artificial nests. Five nests, constructed from short PVC pipe tubes and lined with an acetate sheet, were evenly spaced on top of each reef (Fig. 4). The nest tubes were readily adopted by male

bluebanded gobies as nest sites (Fig. 5A and B). They had a 13-mm internal diameter, were 10-cm long, and one end was capped with a PVC end cap. I checked nests twice weekly (every 3-4 days) and any eggs present were photographed. I chose this frequency because fertilized bluebanded goby eggs can take anywhere from 4-10 days to hatch, depending on temperature (Archambeault et al. 2015). Surveying at this frequency ensured that all egg production was recorded. It also resulted in photographing some eggs that had previously been photographed but that had not yet hatched. I was able to distinguish these older eggs from newer eggs based on differences in their appearance

(Fig. 5C and D) and eggs that were photographed twice in one week were not added to the total count of eggs. To photograph eggs, divers would lift the cage from each reef, remove the acetate sheets from each nest, and photograph underwater any sheets with eggs present. Unlike previous studies in which eggs were cleared from acetate sheets to ensure only new eggs were photographed between sampling periods (Kappus & Fong

2014), I chose to leave the eggs in their nests because I did not want to affect courtship or

nest-guarding behaviors of the gobies. I counted eggs manually using the Cell Counter plugin in ImageJ (imagej.nih.gov/ij/plugins/cell-counter.html, De Vos), and I counted all eggs that were not observed previously in the nest. I did not attempt to distinguish among clutches from different females in a single nest.

2.3.5. Visual counts and recollections

Divers surveyed gobies on each reef at least twice a week during each trial.

Divers would carefully approach each reef and note the number of gobies seen without removing the cages. Divers came no closer than ~ 0.4 m to each reef, which is the minimum distance from which a diver could survey the low risk treatments with large

cages. All cages were scrubbed once a week to improve visibility of gobies on each reef.

At the end of each trial, all tagged fish that remained on the reefs were recollected to compare the number of observed gobies with the number that inhabited the reef.

2.3.6. Behavioral observations

To determine whether predation risk affected time exposed (i.e., not hidden), courtship, or foraging activities of gobies, divers conducted behavioral observations once a week on each reef. Observers would approach each reef, allow gobies to adjust to diver presence over a two-minute acclimation period, choose three focal individuals haphazardly to observe for five minutes each, and record the time exposed and frequency of behaviors during each observation.

Time exposed was measured as a proxy for prey boldness, and it was defined as total time each goby spent exposed (not hidden within refuge space). I recorded the total number of successful feeding strikes, number of moves, number of chases or jerks towards conspecifics (as signs of aggression or courtship, respectively; see St. Mary 1994

and Pradhan et al. 2014 for full descriptions of behaviors), as well as the total distance moved (linear). These behaviors were chosen because they are associated with energy acquisition (foraging rates), vigilance (moves, distance covered), and reproductive fitness

(aggression and courtship), which may be affected by predation risk. I used these observations to identify any mechanistic links between reproductive output and predator avoidance behaviors, and I conducted observations regardless of whether predators were present at each reef, as this most likely captured behavioral responses to intermittent risk

(Lima & Bednekoff 1999).

2.3.7. Remote surveys for predator presence and proximity

To assess any differences in predator abundance and proximity to gobies among treatments, and to ensure that predator risk treatments were effective at manipulating predator access to reefs, I monitored each reef remotely throughout the trials. A single camera was positioned 2.4 m from the edge of each reef to capture all predator activity within 1 m of the experimental plots (Fig. 6A). I deployed cameras between dawn and dusk, and shot photos at 10-second intervals for periods ranging from 30 minutes to 2 hours. Reefs were visited primarily by three different fish species, the kelp bass, rock wrasse, and California sheephead, all of which are known to induce a hiding response in bluebanded gobies at distances within 0.3 m (Table 1). These three species consume bluebanded gobies in nature, though the kelp bass actively hunt gobies whereas the others only incidentally consume them (Steele 1995). I counted these species and noted their relative distances to my experimental plots when they appeared in a time-lapse photo, to compare the level of perceived risk among treatments. The resolution of my time-lapse photos was not high enough to distinguish flight responses among species of predators, so

all predators were pooled. All counts were standardized by the duration of each time lapse.

To test whether the treatments manipulated predator exposure as intended, I analyzed time-lapse photos for each reef at 10-minute intervals (2 – 19 photos per reef, depending on duration of time lapse; with average number of photos per treatment: low

(12), medium (9), high (9), uncaged (7)), and recorded the total number of predators seen, along with their relative distance to the reef for each photo (Fig. 6B, Table 2). Photos were scored for presence and number of predators, and their positions relative to the focal reef. Position scores ranged from 1 – 5, with higher scores assigned to predators that were

observed closer to the reef. If a species was not observed in a time-lapse photo, it was scored a value of zero. Average abundances and scores for each reef were calculated for each time lapse. Time-lapse photos were pooled for all experiments because exploratory statistical analyses revealed that predator activity did not vary markedly among them.

2.4. Statistical analyses

2.4.1. Nest surveys and egg counts

To test for differences in total reproductive output among risk treatments, I used analysis of covariance (ANCOVA) with total eggs produced per reef as the response variable, treatment as the categorical predictor variable, and the average number of bluebanded gobies inhabiting the each reef as a covariate. This covariate was calculated as the average of the initial and final (i.e. recollected) number of gobies on each reef. I used this value as a covariate because there was some variation in number of fish left on reefs at the end of each trial, and it appeared that most of the loss of individuals occurred shortly after being placed on the reef. The assumptions of normality and

homoscedasticity were satisfied, as determined by visual examination of quantile-quantile plots and scatter plots for residuals versus estimates, respectively. Assumptions are also evaluated in the same way and met for all other analyses mentioned. Unless specifically noted, all statistical tests were run separately for each of the three experiments, as the methodology was slightly different among them. All statistical analyses were completed in RStudio v.1.1.383 (R Core Team 2018).

2.4.2. Visual counts, recollections, and behavioral observations

To test whether the number of gobies observed on each reef changed over time or differed among treatments, I compared counts with a Poisson-distributed generalized

linear model (GLM, due to a high number of reefs where zero fish were observed;

Experiment 1) and linear models (LM’s) (Experiments 2 and 3). Treatment and time were the categorical predictors in the model. To determine whether the lethal or sublethal effects of predators affected the number of gobies observed, I evaluated the number gobies recollected among treatments at the end of the experiments with the same model mentioned previously. GLM’s and LM’s were constructed with the lme4 package (Bates et al. 2015).

I tested for differences in bluebanded goby behavior among risk treatments with multivariate analysis of variance (MANOVA) for Experiments 1 and 2, with risk treatment as the predictor variable. Behavioral observations from Experiment 3 were not analyzed because too few were made to have reasonable statistical power. MANOVA’s were conducted using the jmv package (Selker et al. 2018).

2.4.3. Remote surveys for predator presence and proximity

I evaluated whether predator presence and relative position to each reef, differed among caging treatments with three separate permutational analyses of variance

(PERMANOVA’s). I used permutational analyses because the high proportion of photos without predators violated the parametric assumption of normality. The first

PERMANOVA compared the average number photos per reef that contained predators among all treatments. The second PERMANOVA compared the number of photos with predators that were likely perceived as a less-dangerous threat (i.e. received a score of 4) only among medium, high, and cage-control treatments. Predators in low-risk treatments

could not earn a score of 4 because they were likely never close enough to be perceived as a threat. The third PERMANOVA compared the number of photos with predators that were likely perceived as a more-dangerous threat (i.e. received a score of 5) between high and cage-control treatments, because these were the only treatments where predators were allowed full access to the reefs. PERMANOVA’s were conducted using the vegan package (Jari Oksanen et al. 2019).

3. Results

3.1. Nest surveys and egg counts

Populations of bluebanded gobies produced similar numbers of eggs per reef regardless of risk treatment or trial duration in all experiments. Experiment 1 revealed similar reproduction after week-long trials, and though, on average, gobies laid 19% fewer eggs in medium and high-risk treatments than in low-risk treatments, those differences were not statistically significant (F2,48 = 0.32, P = 0.73, Fig. 7A). The numbers of eggs laid by gobies over month-long trials in Experiment 2 did not vary among risk treatments (F2,30 = 1.77, P = 0.19, Fig. 7B). Average reproduction in

Experiment 3 was also similar among risk treatments (F3,12 = 0.39, P =0.76, Fig. 7C). The lack of significant differences among treatments in Experiment 3 also indicates that cage artifacts did not confound interpretation of the results, given that reproductive output did not differ between the treatment with no cage structure at all versus reefs enclosed in open cages (i.e. high-risk treatment).

Reproduction was positively associated with the number of gobies inhabiting each reef, regardless of treatment, in Experiments 1 and 2 (F1,48 = 6.37, P = 0.015 and F1,30=

90.27, P < 0.0001, respectively), and though similar trends in were found in Experiment

3, they were not statistically significant (F1,12 = 1.40, P = 0.26), likely due to low statistical power. There were no interactive effects of treatment and the number of gobies inhabiting each reef on reproductive output (P > 0.1).

3.2. Recollections and visual counts

Similar proportions of gobies were recollected from all reefs in each experiment, regardless of risk treatment (Experiment 1: F2,51 = 0.033, P = 0.97; Experiment 2: F2,33 =

0.52, P = 0.60; Experiment 3: F3,16 = 0.40, P = 0.75, Fig. 8, Table 4). These results suggest that there were no significant effects of lethal predation. Furthermore, similar recollections between caged and uncaged plots in Experiment 3 indicate that cage artifacts did not likely affect prey densities.

Though the numbers of gobies recollected at the end of experimental trials were indistinguishable among treatments, numbers of gobies observed by divers were 19% and

21% lower on high-risk reefs than on medium- or low-risk reefs in Experiments 1 and 2, respectively (Experiment 1: F2,168 = 8.24, P < 0.0039; Experiment 2: F2,549 = 15.86, P <

0.0001). The effects of risk on number of gobies seen by divers varied by time in

Experiment 3 (F3,72 = 4.76, P = 0.0044), likely due to differences between caged and open plots in the beginning of the experiment (Fig. 9, Table 5). The number of gobies observed on each reef decreased over time in all experiments, regardless of risk

(Experiment 1: F1,168 = 149.85, P < 0.0001; Experiment 2: F1,549 = 333.12, P < 0.0001) although this effect depended on treatment in Experiment 3. No evidence of cage artifacts was found in that there were no differences in the number of gobies seen between high- risk and completely uncaged treatments.

3.3. Behavioral observations

Behaviors of gobies differed among risk treatments in Experiment 2, but not in

Experiment 1. Multivariate differences in behaviors were detected in Experiment 2

(Pillai’s Trace (10,96) = 0.59, P = 0.018, Figs. 10 – 13, Figs. 10-14, Table 6), and univariate tests revealed that those differences were mainly driven by a 18% decrease in exposure time in high-risk treatments (F2,32 = 0.21, P = 0.009, Fig. 10). The findings from

Experiment 2 are consistent with results from the visual surveys, in which gobies were

observed less frequently on high-risk reefs. In Experiment 1 multivariate behaviors were statistically indistinguishable among risk treatments (Pillai’s Trace (10,96) = 0.29, P =

0.059), so no univariate tests were conducted.

3.4. Predator exposure of risk treatments

Time-lapse recordings showed that caging treatments were effective at manipulating access of predators to bluebanded gobies as intended. Remote photos taken to assess predator activity showed that predators were attracted more to some treatments than others (Pseudo-F3,581 = 8.49, P = 0.0099, Fig. 15, Table 7). Differences between low and high-risk treatments drove this trend, though some of the differences among treatments were attributable to differences in dispersion of the data (PERMDISP: P =

0.0027). Where predators were able to swim close enough to reefs that they would likely be perceived as threats by gobies, they did so similarly when they were perceived as less threatening (i.e. in medium-risk, high-risk, and uncaged treatments), and more threatening (i.e. high-risk and uncaged treatments) (Pseudo-F2,412 = 0.11, P = 0.91, and

Pseudo-F1,259 = 0.060, P ≈ 1.0, respectively).

4. Discussion

Despite evidence of behavioral responses to predation risk, my experiments revealed no large effects of predation risk on reproductive output in bluebanded gobies, and thus, did not support the hypothesis that predation risk reduces fitness. These results differ from those reported in other field studies of risk effects in terrestrial and aquatic taxa, where prey reduced reproductive output in risky habitats (Pankhurst 2001, Sheriff et al. 2009, Zanette et al. 2011). In those studies, prey exposed to higher levels of perceived risk exhibited lower frequencies of behaviors needed to maintain fitness, such as foraging and courtship. It is possible that the level of perceived risk from predators was not high

enough to alter these key behaviors in bluebanded gobies, allowing them to produce comparable quantities of eggs even on reefs where predators had greater access to prey

(e.g., medium and high-risk, and uncaged reefs). However, there may be alternative explanations as to why I saw similar reproduction among risk treatments, namely the hypothesis that bluebanded gobies may be preconditioned to maintain fitness in high-risk environments based on their reproductive life history.

Evolutionary theory predicts that organisms with limited potential for future reproduction should increase their investment in current reproduction (Williams 1966,

Clark & Ydenberg 1990). Previous laboratory studies on the effects of risk on reproduction of fishes have tested this theory by subjecting species that differ in their spawning duration and level of parental investment to elevated levels of predation pressure. Mukherjee et al. (2014) found that a short-lived fish produced similar numbers of eggs in high and low risk-risk environments at the end of its spawning season, potentially because their study species rarely survives to reproduce over multiple years.

Magnhagen (1990) compared two species of nest-brooding gobies that differ in their spawning duration and nest construction and found that the species with a shorter spawning period and less conspicuous nests was able to maintain breeding rates despite high levels of risk. In both of these studies, fishes with longer spawning durations, and more conspicuous mating and nesting strategies that likely make them more susceptible to predators when spawning, suppressed reproduction during periods when perceived risk was high.

Bluebanded gobies rarely survive to breed in more than one season, and that, coupled with the fact that adults and eggs are relatively safe from predators within

nesting spaces during egg development, may explain why I did not observe effects of risk on reproductive output in this species. St. Mary (1994) speculated that bluebanded gobies may be less likely to alter or delay their reproduction, given their relatively short lifespan, and a lifetime spawning period of only 8 months. In a field experiment, Kappus and Fong

(2014) reported no effects of sex ratio or female density on egg production of bluebanded gobies, reinforcing the idea that fitness responses in this species may be relatively robust to changes in their environment. Per capita reproduction is highly variable in this species, even among females of similar size (Behrents 1983, Solomon-Lane, unpublished), which, as has been suggested in other manipulative studies on gobies (Schram & Steele 2016), may have affected my ability to detect treatment effects based on my sample size. With the level of replication used in Experiment 2, I had a 60% chance of detecting the differences in reproduction between low and high-risk treatments based on the effect size of 17% that I observed. I would have needed an additional 3 reefs per treatment to have an 80% chance of detecting differences in reproductive output as large as those observed

in this study, which would not have been logistically feasible due to spatial constraints at my study site. However, isolated populations of bluebanded gobies, similar to those that I established on my reefs, are highly abundant in nature, so it is likely that the sublethal effects of predators may be detectable on natural reefs.

Another possible explanation as to why reproductive output of bluebanded gobies did not differ between risky and low-risk environments, is that reproductive output itself might not vary but offspring quality might vary between high and low-risk habitats. For example, Donelan and Trussell (2018) found that a marine snail produced similar numbers of eggs in high-risk and risk-free environments, but offspring from risk-

experienced parents had higher growth rates than offspring from parents with no risk experience, likely due to increased growth efficiency in risky environments. Elliott et al.

(2016) found comparable results in fruit flies, where parents produced similar quantities of offspring, regardless of risk level, but offspring were smaller and developed faster when their mothers experienced high-risk conditions. Evidence that risk effects that may not be detectable in behavioral responses was found in a study by Hall and Clark (2016), where damselfish in high-risk treatments were behaviorally indistinguishable from those in risk-free treatments, but had increased metabolic rates; suggesting that increased energy expenditure from chronic risk may lead to reduced fitness over time.

Bluebanded gobies behaved differently when faced with higher risk of predation.

In high risk treatments, they spent less time perched on top of reef structure and more time hiding. This response occurred in Experiments 1 and 2, but not in Experiment 3, likely due to low statistical power to detect differences in the latter. There were no differences in other observed behaviors (e.g., total number of movements, foraging rate,

and courtship displays), suggesting that prey either maintained these behaviors despite risky environments (Forsgren & Magnhagen 1993), allocated these behaviors to safer periods during the observation, resulting in equal frequencies regardless of risk (Lima &

Bednekoff 1999, Boersma et al. 2008, Catano et al. 2016), or were not affected by risk, at least for behaviors measured in this study (Hall & Clark 2016). Behavioral results from my study on bluebanded gobies differed from those reported by Steele (1998) and Gregor and Anderson (2016) in that I did not observe any suppression in foraging with increased risk from predators. However, some of this discrepancy in results may be because Steele compared behavior of bluebanded gobies only when predators were present or absent at

the time of the observations, whereas I conducted behavioral observations regardless of predator presence.

Habitat characteristics have also been shown to mediate the effects of risk on fitness responses in prey, driven mainly by competition for refuge and nesting space during periods of elevated predation pressure. In complex habitats, smaller-bodied prey may be less affected by risk from predators than larger individuals because they can occupy a greater proportion of available refuge space when threatened (Lima & Dill

1990). Catano et al. (2016) found that younger, smaller-bodied damselfish foraged more closely to predator decoys than larger-bodied conspecifics on coral reefs with high complexity but acknowledge that the implications of this study may be limited to fishes that exhibit more mobile and conspicuous foraging behaviors (e.g., herbivorous grazers and piscivores). In reef fishes with relatively small home ranges and high access to refuge space, the effects of risk on behaviors associated with fitness may be less impactful. Potts

(1984) suggests that nest-brooding gobies may be less likely to alter their reproductive

output in response to predation pressures in complex habitats, because their nests are typically formed in areas where adults and offspring are both protected from predators during spawning periods. Increased habitat complexity and shelter availability are known to reduce mortality rates and increase behaviors associated with fitness of bluebanded gobies (Behrents 1987, Steele 1999, Gregor & Anderson 2016). I suspect that the high amount of available refuge and nest space on each reef influenced reproductive output and behaviors in my experiments, in part because competition for these resources decreased over time as fewer gobies remained on the reefs. The numbers of gobies observed by divers declined over time in all experiments, and many fewer gobies were

recollected at the end of each experiment than were placed on the reefs. I expected to recollect fewer gobies in high-risk treatments as a result of lethal morality from predators, however, similar numbers recollected between caged and open plots suggest that number of inhabitants on each reef did not depend on predator access. Though the procedures for tagging bluebanded gobies used in this experiment have been shown to have minimal effects on their survival (Malone et al. 1999), gobies exhibited uncharacteristically high levels of mortality, among all risk treatments, especially in Experiment 1, presumably due to delayed stress from handling. To reduce handing stress and improve mortality rates, I changed my tagging procedures for Experiments 2 and 3. Specifically, I did not anesthetize gobies in MS-222 prior to tagging, which led to a higher number of gobies inhabiting the reefs over longer trial durations. It is possible that the effects of handling mortality confounded any potential responses of gobies to risk, especially at the end of experimental trials when reproductive interactions were likely limited due to low

densities alone; but because fish disappeared at comparable rates among reefs, it is likely that these effects were relatively similar for all treatments.

I did not simulate lethal removals of bluebanded gobies in medium-risk treatments, which may explain why reproduction and fitness behavior were more similar to that observed in low-risk treatments than high risk. A critique of many of the studies that attempt to characterize responses of prey to risk is that they do not effectively isolate the sublethal effects of predators (see reviews by Parsons et al. 2018, Peers et al. 2018).

Some studies, however have isolated sublethal effects and have shown that risk effects alone, can alter behaviors of prey (McCormick & Manassa 2008, Kimbro et al. 2017).

It is difficult to determine whether the lack of differences in reproductive output on my experimental reefs would exist on natural reefs, mostly because of potential differences in the severity and frequency of risk, and access to artificial nests that gobies experienced in this study. The predation pressures that gobies experienced on my isolated reefs may have been lower than what they would experience on natural reefs, because of the large distances between the reefs and natural structure. On the other hand, prey inhabiting isolated reefs (such as those used in this study), may experience predation rates higher than that on natural reefs, due to the tendency of predators to aggregate to structure in patchy areas (Steele 1999). Results from my time-lapse analyses revealed that predators visited low-risk reefs less frequently than the other treatments, suggesting that if predators were in fact preferentially visiting my experimental plots, they were more attracted to the complexity of reefs (potentially to use as refuge themselves) than to their structural size (e.g., larger cages in low-risk treatments). This hypothesis is supported by

the relatively high levels of predator activity on high-risk and uncaged plots, where access to more complex structure, and potentially prey, was greater.

Given that bluebanded gobies on my reefs appeared to only ever lay eggs in artificial nests, and that there never seemed to be any shortage of available nest space (i.e. there were always unused nests during sampling), total reproduction in response to risk may have been higher on my plots than occurs naturally. Competition for suitable nesting space in nature, combined with increased risk, may lead to reductions in reproduction in fishes (as shown in laboratory experiments by Wisenden (2011)). There is the potential that the characteristics of artificial nests used in this study (e.g., uniformly shape and

capped at one end) were more desirable or protective than the derelict shells and rock crevices that bluebanded gobies use for nesting in nature, which could have further promoted reproductive success on experimental plots. However, I may have also observed lower reproduction on my reefs in comparison to those in nature because my standardized populations of gobies were unfamiliar with each other at the beginning of each experiment; eliminating any previously-established mating tendencies that may have enhanced reproduction in natural harems (St. Mary 1994). Although these potential nest artifacts do not confound the interpretation of my experiments because they were equivalent on all reefs, I am hesitant to suggest that the lack of reproductive responses of bluebanded gobies to risk that I found is indicative of what occurs on natural reefs.

This study suggests that predation risk does not reduce fitness in bluebanded gobies as it does in some other taxa. It appears that bluebanded gobies prioritize current fitness regardless of risk level, which is consistent with life history theory, based on their relatively short lifespans and low future spawning success after a single breeding season.

There did, however, appear to be some negative, insignificant trends, in reproductive output in response to predation risk, which, over time, may negatively affect demographic rates in this species. Long-term investigations (i.e. multi-year and decadal) on the effects of risk on prey reproduction suggest that over time, risk may decrease parental condition, along with the quantity and quality of offspring produced. Two terrestrial examples include studies by Zanette et al. (2011), where songbirds in high-risk environments produced fewer offspring with higher mortality rates than those in low-risk environments, suggesting that the effects of risk are likely compounded over successive breeding seasons. Reznick et al. (1990) found that predation risk selected for earlier age

at maturity, and lower reproductive output in isolated populations of freshwater guppies over an 11-year study (i.e. roughly 30 generations), indicating that evolutionary effects of risk can develop quickly over decadal scales in fishes with short lifespans that experience strong selection pressures from predators.

In conclusion, bluebanded gobies produced similar amounts of eggs among all levels of risk, likely because they are predisposed to cope with predation pressures, especially during peak spawning periods and when competition for suitable nest and refuge space was not limited. These findings highlight the importance of field investigations of the impact of predation risk on reproduction because they are needed for a more realistic assessment of the sublethal effects of predators. This study emphasizes the fact that responses of prey to risk from predators are likely not uniform among fishes.

Future studies on the effects of risk in fishes should explore how life history of prey, particularly differences in reproductive mode, habitat use, and susceptibility to risk affect responses in fitness. A better understanding of the relative importance of lethal and

sublethal effects of predators on prey fitness could improve predictions of how practices affecting predator abundance (e.g. overfishing or protecting) may alter demographic rates of prey.

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Appendix A: Tables Table 1. Predator species quantified in time-lapse photos. All were abundant at the study site; and all have been observed to consume bluebanded gobies in nature.

Predator Family Feeding type Actively or opportunistically hunt gobies?

Paralabrax clathratus Serranidae Piscivore Actively Halichoeres semicinctus (female) Labridae Omnivore Opportunistically Halichoeres semicinctus (male) Labridae Omnivore Opportunistically Semicossyphus pulcher (female) Labridae Omnivore Opportunistically

Table 2. Criteria for scoring the locations of predators, relative to reef structure, in time-lapse photos.

Score Classification for predator location Distance from reef (m) Treatments where score was achievable

0 Not present in photo NA All 1 Not associated with reef or cage, but > 2 All present in photo 2 Beyond edges of large cage frame, but 1.1 - 2 All associated with cage 3 Directly on top of, or just outside of 0.5 – 1 All large cage 4 Directly on top or outside of small cage, 0.3 – 0.49 Medium, high, control but not within small cage area 5 Directly on top of reef structure, or 0 – 0.29 High, control

32 within small cage area

Table 3. Results of ANCOVA testing for differences among risk treatments in the total number of eggs produced per reef, with number of gobies recollected from each reef (density) as a covariate.

Factor SS df F P

Experiment 1 Treatment 4.27 × 106 2 0.32 0.73 Density 4.30 × 107 1 6.37 0.015 Treatment × Density 1.00 × 107 2 0.74 0.48 Error 3.24 × 108 48

Experiment 2 Treatment 6.26 × 107 2 1.77 0.19 Density 1.60 × 109 1 90.27 < 0.0001 7 33 Treatment × Density 5.93 × 10 2 1.68 0.20 Error 5.30 × 108 30

Experiment 3 Treatment 5.04 × 106 3 0.39 0.76 Density 6.09 × 106 1 1.40 0.26 Treatment × Density 1.83 × 106 3 0.14 0.93 Error 5.20 × 107 12

Table 4. Results of ANOVA testing for differences in the proportion of gobies recollected from each reef among risk treatments.

Factor SS df F P

Experiment 1 Treatment 0.0012 2 0.033 0.97 Error 0.93 51

Experiment 2 Treatment 0.057 2 0.52 0.60 Error 1.82 33

Experiment 3 Treatment 0.010 3 0.40 0.75 Error 0.14 16

Table 5. Results of ANOVA testing for differences among risk treatments in the number of gobies seen inhabiting reefs over time (see Fig. 9).

Factor SS df F P

Experiment 1 Treatment 141.05 2 8.24 0.0039 Day 1282.98 1 149.85 < 0.0001 Treatment × day 10.38 2 0.61 0.55 Error 1438.40 168

Experiment 2 Treatment 412.60 2 15.86 < 0.0001 Day 4333.90 1 333.12 < 0.0001

35 Treatment × day 12.20 2 0.47 0.63

Error 7142.50 549

Experiment 3 Treatment 15.45 3 1.28 0.29 Day 194.058 1 48.11 < 0.0001 Treatment × day 57.64 3 4.76 0.0044 Error 290.40 72

Table 6. Results of MANOVA testing for differences among risk treatments in behaviors of L. dalli in Experiments 1 and 2. Number of reefs surveyed for each treatment: Experiment 1: low (n = 18), medium (n = 18), high (n = 18); Experiment 2: low (n = 12), medium (n = 12), high (n = 11).

Factor Pillai’s SS df F P Trace

Experiment 1

Multivariate tests

Treatment 0.29 10 1.63 0.19 Error 96

Experiment 2

Multivariate tests

Treatment 0.59 10 2.40 0.018 Error 58 Univariate tests

Time spent exposed 0.15 2 5.52 0.009 Error 0.42 32 Movements per min. 0.44 2 2.65 0.086 Error 2.65 32 Bites per min. 0.15 2 0.75 0.48 Error 3.25 32 Courtship per min. 0.0011 2 0.091 0.91 Error 0.19 32 Total distance moved 24822.27 2 1.77 0.19 Error 252123.66 32

Table 7. Results of PERMANOVA and corresponding PERMDISP testing for effects of caging treatment on the number of time-lapse photos that (A) contained at least one predator, compared among all treatments; (B) contained predators that were likely perceived as a less dangerous threat (i.e. a score of 4), compared among medium, high and low treatments; and (C) contained predators that were likely perceived as a more dangerous threat (i.e. a score of 5), compared between high and cage-control treatments, based on their relative distances to experimental reefs.

Factor SS df Pseudo -F P

A. Predator presence Treatment 6.10 3 8.49 0.0099 Error 139.28 581

PERMDISP Groups 3.43 3 4.77 0.0027 Error 139.28 581

B. Low threat

Treatment 0.025 2 0.11 0.91 Error 44.71 412

PERMDISP Groups 0.025 2 0.11 0.89 Error 44.71 412

C. High threat Treatment 0.0047 1 0.060 ~1.0 Error 20.14 259

PERMDISP Groups 0.0047 1 0.060 0.81 Error 20.14 259

Appendix B: Figures

Figure 1. Bluebanded gobies perched on natural reef structure. This behavior improves foraging and mating success, as well as vigilance of predators. Photo credit: Griffin Srednick.

Figure 2. Map of Big Fisherman Cove, at Santa Catalina Island, California. Squares represent the reef array, where 18 reefs were used in Experiments 1 and 2, and 20 reefs were used in Experiment 3. Gobies used in this experiment were collected at Isthmus Reef, indicated by the red star on the map. Map credit: Larry G. Allen.

Figure 3. Schematic of experimental reefs and caging design for each risk treatment. Shading indicates mesh that excluded predators, and white cylinders represent the 5 goby nests per reef. Predators could fully access reefs in the high risk and uncaged treatements.

Figure 4. Designs of low-risk (A), medium-risk (B), high-risk (C), and uncaged (D) treatments. The number of rocks and nests, along with the spatial layout of each, were standardized among reefs, but access of predators to prey varied by treatment. See Fig. 3 for types of perceived predation likely perceived by bluebanded gobies in each treatment.

Figure 5. Bluebanded gobies guarding eggs laid inside artificial nests (A and B; photo credits: Scott Hamilton and Hunter Ramo, respectively). (C)A typical goby nest with eggs laid in a monolayer on an acetate sheet; this nest contained roughly 2500 eggs. (D) A close-up of eggs at different stages of egg development; eggs with black eyes visible are more developed than the pink and reddish eggs.

43 Figure 6. Photograph of a high-risk reef to assess predator presence and proximity (A). Scoring categories for predator proximity

based on their relative distance to reef structure. Higher scores were assigned to predators that were closer to the reefs, where they were likely perceived as a greater threat by gobies. This photo shows a female Semicossyphus pulcher directly on top of reef structure, receiving a score of 5. If predators were not seen in a photo, the observation was scored as zero. For a more detailed description of how photos were scored, see Table 2.

A) Experiment 1 B) Experiment 2 C) Experiment 3

Figure 7. Total egg production in bluebanded goby populations based on risk treatment and the average number of gobies inhabiting each reef. Note the difference in scale among experiments. For (A) Experiment 1, n = 18 for week-long trials, (B) Experiment 2, n = 12 for month-long trials, and (C) Experiment 3, n = 5 for a two-week-long trial. See Table 3 for statistical results.

A) Experiment 1 B) Experiment 2 C) Experiment 3

Figure 8. Proportion of gobies placed on reefs that were recollected at the end of experimental trials in different predator risk treatments. Bars represent mean proportions ± 1 SE. n = 18 for (A) Experiment 1; n = 12 for (B) Experiment 2; and n = 5 for (C) Experiment 3.

Figure 9. Number of gobies seen on each reef during visual surveys for each risk treatment. Error bars represent ±SE, where n = 18 for Experiment 1 (A), n = 12 for Experiment 2 (B), and n = 5 for Experiment 3.