Changing Communities: Impacts of the Pisaster ochraceus Collapse on Intertidal Communities

An Honors Thesis Submitted to the Department of Biology in partial fulfillment of the Honors Program STANFORD UNIVERSITY

by Roberto Guzman November 2015

Acknowledgments

I’d like to thank Terry Root and the Woods Institute for their MUIR Grant that made this all possible. And also for teaching me on the importance of an interdisciplinary education.

I’d also like to thank my advisor, Fiorenza Micheli, for her assistance, expertise, patience, and ideas that helped throughout this project, every step of the way. Whether it was helping with setting up the projects, analyzing the results with me, or just coming out to the intertidal zone with me to help with field work, without you, this project and my thesis would not exist.

Thank you Mark Denny for your contribution to my thesis. I appreciate not only your help as a second reader, but as someone who was able to contribute fresh eyes to my thesis, providing me with valuable insight of things I may have missed after working on the thesis.

I am also grateful for the assistance of James Watanabe. Whether it was his expertise in the biology of the intertidal zone, or his quadrat camera setup, the success of the project lends itself to his efforts and generosity.

A lot of appreciation goes to Steve Palumbi for providing me with financial assistance this year. You have not only helped me with it, but also my family. Your generosity will not be forgotten.

For assisting me in fieldwork and making it more enjoyable, I’d like to thank Gracie

Singer. Your positivity and conversations lit up the lab.

I’d also like to thank Maria Castro ‘17 for serving as my unofficial assistant for the first summer of the project. Your help and uplifting energy in the field and in the lab made sure I stayed on top of my things, but it also made it pleasant. Sincerely, thank you and good luck in your academic future.

3 Table of Contents

List of Figures & Tables……………………………………………………………………..…..5

Abstract………………………………………………………………………………………...…7

Introduction…………………………………………………………………………………..…..8

Materials & Methods……………………………………………………………….………..…12

Results…………………………………………………………………………………………..16

Conclusion/Discussion………………………………………………………………………….34

References……………………………………………………………………………………….45

4 List of Figures & Tables

Figure 1: Map of the sites off of Point Cabrillo and of the Hopkins Marine Station.

Figure 2: Percentage of total quadrat space covered by mussel beds average over all of the plots by date.

Figure 3: Percentage of mussel bed cover of East and West quadrats categorized by initial size.

Figure 4: Percentage of mussel bed cover of East quadrats categorized by initial size.

Figure 5: Percentage of mussel bed cover of West quadrats categorized by initial size.

Figure 6a: Percent coverage of quadrat by mussel beds by individual plots in the East site.

2 Regression lines, R ​ values, and p­values for each plot are included. Asterisks indicate plots that ​ are significant after applying a Bonferroni correction to account for multiple tests (N=18 & p<0.003).

Figure 6b: Percent coverage of quadrat by mussel beds and individual plots in the West site.

2 Regression lines, R ​ values, and p­values for each plot are included. Asterisks indicate plots that ​ are significant with the Bonferroni correction (N=18 & p<0.003).

Figure 7a: Distance of the mussels averaged for each date done for East plots. Distance was measured by the distance between the mussels to the fixed line between the eye­bolts.

Figure 7b: Distance of the mussels averaged for each date done for West plots. Distance was measured by the distance between the mussels to the fixed line between the eye­bolts.

Figure 8a: Heights of the mussels averaged for each date done for the East A&B plots.

Figure 8b: Heights of the mussels averaged for each date done for the West A&B plots.

Figure 9: Heights of the individual mussels measured in Plot 2A.

Figure 10a: Heights of the lowest mussels found averaged for each date done for the East plots.

5 Figure 10b: Heights of the lowest mussels found averaged for each date done for the West plots.

Figure 11a: Lengths of the lowest mussels averaged for each date done for the East plots.

Figure 11b: Lengths of the lowest mussels averaged for each date done for the West plots.

Figure 12: Total counts of the whelks Ocinebrina sp. & Nucella sp. in both East and West plots. ​ ​ Figure 13a: Total counts of the whelks Ocinebrina sp. & Nucella sp. in East plots. ​ ​ Figure 13b: Total counts of the whelks Ocinebrina sp. & Nucella sp. in West plots. ​ ​ Figure 14: Number of dead mussels found in experimental containers by treatment.

Figure 15: Number of dead mussels in the treatment boxes by their length.

Figure 16: Total counts of Pisaster ochraceus by date. ​ ​ Figure 17: Pisaster ochraceus counts done by Pearse (2010) averaged for every 5­year periods ​ ​ from 1950­2010 with my counts for 2015 added.

Figure 18: Drill holes made by the predatory whelk Nucella sp. found on the dead mussels in the ​ ​ red boxes.

Table 1: Two­Factor ANOVA with Plots and Dates as the factors.

6 Abstract

The ochre sea star (Pisaster ochraceus) is a keystone predator that can control the ​ ​ structure and maintain the diversity of rocky intertidal communities. In 2013, a densovirus instigated a large sea star die­off that caused populations of Pisaster across the West Coast of ​ ​ North America to collapse. In the wake of their absence, the rocky intertidal zone faces potential change in community structures. For example, prey populations, specifically mussels, could now expand without predation by Pisaster to restrict them. Field surveys and experiments examined ​ ​ the possible impacts of the die­offs of the ochre sea star on the intertidal zone. Specifically, impacts were measured on the California Mussel (Mytilus californianus), and two predatory ​ ​ ​ ​

2 whelks Ocinebrina circumtexta and Nucella analoga compressa. Eighteen 0.5 m ​ plots within ​ ​ ​ ​ ​ mussel beds at two sites, within the Lovers Point State Marine Reserve, in Monterey Bay,

California, were photographed on seven dates between June 2014 and July 2015 to measure changes in mussel percent cover and tidal heights of the mussel beds. To examine whether whelks have the potential to replace P. ochraceus in controlling the M. californianus population, ​ ​ ​ ​ I conducted counts of the dominant species, Ocinebrina sp. & Nucella sp., in the plots on five ​ ​ ​ ​ dates and I performed a lab experiment to measure the mortality rates of M. californianus with ​ ​ and without the predatory whelk Nucella sp. Counts of P. ochraceus were also conducted at the ​ ​ ​ ​ two sites, on each monitoring date, and compared to J. Pearse’s (2010) historical counts done for the same areas since 1950. Percent mussel cover showed a small but significant increase over the

13­month monitoring. Plots that had a greater cover to begin with showed a slightly greater increase. However, some mussel patches with low cover but with recently recruited M. ​ californianus grew faster because smaller mussels grow faster than larger ones. The lower limit ​

7 of the mussel beds has shifted up to 32 cm lower in some plots, possibly due to recruitment and higher survival occurring at lower levels in the absence of sea stars. Whelk counts revealed a decrease in densities over the 15­month monitoring. The abundance of P. ochraceus is now the ​ ​ lowest it has been since 1950: sea star population size has seen a 90­95% decline over the past

25­50 years. Most of this mortality is not due to the 2013 outbreak of the sea star die­off. Finally, the presence of Nucella increases the mortality of M. californianus in laboratory feeding ​ ​ ​ ​ experiments, but there is little evidence for size selection. However, the potential for the whelks to fill in the niche left vacant by Pisaster population collapse seems limited based on my ​ ​ laboratory estimates of mortality from whelk predation and field estimates of whelk densities.

Overall, the predicted mussel expansion did occur, though patchily. However, processes other than predation could drive or limit mussel expansion. Continued monitoring and field experiments are needed to examine possible changes in intertidal communities and elucidate their drivers.

Introduction

A suite of abiotic and biotic factors, and their interactions, shape the structure and diversity of marine communities (Paine, 1974; Somero 2002). In rocky shores, fluctuating tidal heights change the physical conditions for intertidal communities and serve as the major driver of the distribution of organisms (Somero, 2002). The different tidal heights differ in their exposure to different biotic and abiotic factors. Above the waterline, organisms are exposed to desiccation, direct sunlight, high temperature, and crashing waves. The tolerance to these factors by different organisms dictate at what tidal height they can survive. Thus, rocky intertidal communities often exhibit distinct patterns across tidal heights (Paine, 1974; Somero 2002).

8 The rocky intertidal zone is an ecosystem where the most valuable resource is space.

Having sessile organisms make up most of the community found in the intertidal zone, space on a rocky substrate quickly becomes the most limited and important resource (Dayton, 1971).

Thus, competition for space is a major driver of diversity and community composition (Robles,

2002). Predation can control competitively dominant species, thereby mediating competitive interactions among intertidal species and allowing for the persistence of competitive inferiors

(Paine, 1974). Predators that maintain high diversity in intertidal communities by controlling competitively dominant species are referred to as keystone species (Mills, 1993). Keystone species maintain diversity by indirectly facilitating other species by preying on organisms that would otherwise eliminate them (Mills, 1993).

On the West Coast of North America, the Ochre Starfish, Pisaster ochraceus, can be ​ ​ keystone predator in its interaction with the California Mussel, Mytilus californianus. P. ​ ​ ​ ochraceus is often found on the beds of M. californianus in rocky shores. In the absence of sea ​ ​ ​ ​ ​ stars, mussels can come to dominate available space, preventing other organisms from growing on the rocky substrate. A slight drop in Pisaster abundance can cause large increases in M. ​ ​ ​ californianus populations (Power et al. 1996). Additionally, sea star predation often limits the ​ lower tidal heights at which mussels can settle and grow, thereby allowing other organisms to grow below this limit and increasing the overall diversity of intertidal benthic communities

(Paine, 1969, 1974).

Starting in June 2013, millions of sea stars wasted away due to the sea star wasting disease caused by the sea star densovirus, and though this was not the first time this disease broke out, it is regarded as the worst outbreak (Hewson, et al. 2014). This is due to its geographic

9 range (Baja California, Mexico to Southern Alaska), and the number of species it has impacted

(20) (Hewson, et al. 2014). By the Autumn of 2013, the wasting disease swept through and decimated the sea star population in Monterey Bay, California (Hewson, et al. 2014). The ochre sea star P. ochraceus was commonly found in Monterey Bay, but after the disease, their ​ ​ abundance has dropped dramatically and now Pisaster individuals are rarely found in rocky ​ ​ shores of Monterey Bay (personal obs.).

Since 1950, counts have been conducted of the sea star P. ochraceus in three areas, ​ ​

2 2 measuring respectively, 160 m ​ (Area 1), 84 m ​ (Area 2), and 270 m (Area 3), of the rocky ​ ​ intertidal habitat at the Hopkins Marine Station (HMS) in Monterey Bay. These counts include work from Feder in the mid­1950’s (1956, 1959, 1970) and, Pearse in 1986, 1996, 1997, 2001, and 2004­2006 (Pearse, 2010). All of the surveys were conducted in the same three areas using identical methods: going out to these areas during negative tides to count the sea stars. This historical record keeps track of Pisaster numbers in the HMS intertidal zone and shows the ​ ​ overall decline the sea star’s local population since 1950. The declines might be due to wasting events, more limited in scale compared to the 2013 event (Dungan et al. 1982; Bates et al. 2009).

Other intertidal predators of mussels include whelks, specifically Ocinebrina circumtexta ​ (Ocinebrina) and Nucella analoga compressa (Nucella) that feed by drilling a hole into the ​ ​ ​ ​ ​ ​ ​ ​ mussel’s shell, injecting digestive enzymes into the mussel, then sucking up the digested flesh.

This is done via the whelk’s proboscis that uses the radula and its chemical secretions to rasp away at the shell (Barnes 1980; Crothers 1985). These predators may also contribute to keeping the M. californianus population in check. ​ ​

10 My research aims to answer the question: What are the consequences of the ​ near­removal of the keystone Pisaster ochraceus for rocky intertidal communities? Specifically, ​ ​ ​ I conducted field sampling and lab experiments aimed at measuring the possible impacts of the die­off of the P. ochraceus on the population of M. californianus, its primary prey. In higher ​ ​ ​ ​ ​ ​ densities of mussels, higher rates of predation are observed, thus exerting a stronger control of mussel populations (Menge, 1994). However, with the elimination of Pisaster from the system, ​ ​ the mussel beds are allowed to grow unchecked by their primary predator. I hypothesized that the major decline of sea stars may result in decreased mussel mortality, particularly low in the intertidal zone where predation is generally greater, resulting in increased mussel abundance

(here measured as percent cover) and spread of mussels to lower tidal elevations. Such effect of sea star loss is potentially important for overall diversity on rocky shores, as mussels can competitively exclude other species and reduce diversity(Menge, 2004).

The first specific aim of my research is to measure whether or not the beds of M. ​ californianus are spreading to lower tidal heights as a response to the absence of the P. ​ ​ ochraceus, and whether this effect can occur over short time scales (months to one year). If this ​ occurs, mussels could outcompete the other sessile organisms in the intertidal zone.

The second specific aim of this study is to examine the possible response of predatory whelks, Nucella sp. & Ocinebrina sp., to the sea star decline. I hypothesized that whelk ​ ​ ​ ​ ​ ​ abundances may increase because whelks no longer compete with Pisaster for their shared prey, ​ ​ the mussels.

11 The third specific aim is to examine the potential of whelks filling in the niche of the sea star as a keystone predator, thereby compensating for sea star loss in controlling mussel populations. To this end, I measured the predatory rates and size preferences of the whelk

Nucella sp. on their mussel prey. Literature reports that mussel size preference of Nucella sp. is ​ ​ ​ about 20­25mm in shell length and for P. ochraceus is about 35­55mm (Hughes & Dunkin, ​ ​ 1984; Mcclintock & Robnett, 1986). I assessed the size preference of Nucella sp. in the lab using ​ ​ a range of mussel lengths between 22­58mm. I then used these data and my field measurements of whelk densities to estimate predation rates of whelks on mussels in the field and compared these estimates to those reported for Pisaster in the literature, which is about 80 mussels/year to ​ ​ examine whether whelks may play a comparable role to sea stars in controlling mussel populations, thereby maintaining intertidal diversity in the absence of the sea star.

Finally, I added onto the counts of P. ochraceus in the rocky intertidal zone that were ​ ​ started in 1950 by Pearse (2010). Having counts over the past 65 years helps put the recent mortality event and my findings regarding its possible effects on mussels into a larger context.

Specifically, it allowed me to address the question of how the recent population decline due to the wasting disease compares to previous declines.

Materials & Methods

Study Sites

The study sites where I conducted my work were two of the three study sites of Pearse

(2010) and Feder (1956, 1970) at the Hopkins Marine Life Refuge in Monterey Bay. The sites were labeled as West and East, and correspond with Pearse’s Area 1 and Area 2, respectively

(Figure 1). West is located to the West of Bird Rock and is a mussel­populated granite outcrop

12 that is partially exposed to the incoming waves. East is located 90 meters to the east of West, and is at Bird Rock, a protected granite outcrop covered in algae, barnacle, and algae (Pearse, 2010).

The two sites were chosen due to their differences in wave exposure. West is more wave­exposed (‘Exposed Site’) than East (‘Protected Site’). The GPS coordinates of the center of these sites are 36°37'18.4"N 121°54'12.5"W and 36°37'16.8"N 121°54'10.7"W, respectively.

Mussel Percent Coverage

To measure the change in the sizes of mussel beds within the intertidal zone, a series of photos were taken over time. Within each area, there are five locations marked by two metal eye­bolts placed ~60cm apart that are tagged with metal tags with the engraved number of the plot, making 10 total. During the summer of 2014, photos were taken at each of the ten locations every time a negative tide occurred in a tidal cycle. This occurred twice in June (Mid­June &

Late­June), July, and August. After, photos were taken every 3­4 months during a negative tide.

This occurred in December, March, and July. The photos are taken using a camera set­up in a

2 custom stand that serves as a quadrat framer that measured 0.50m ​ in area. The frame has ​

13 alternating black and grey bars that are 10cm long each and are used to scale in photographs. In the field, each location has a pair of photos (plots) taken: one where the eye­bolts are placed in the bottom corners of the framer, designated as the 'above' photograph or A plot, and the second where the eye­bolts are placed on the upper corners of the framer, designated as the 'below' photograph or B plot. Because Below (B) photos could not be taken at two of the locations (there wasn’t enough space), the total number of plots photographed on each date is eighteen (10 A and

8 B plots). I used the software ImageJ to measure exactly what percentage of the plots the mussel beds are taking up. By repeating these measurements over time for one year, I measured if and how much the mussel beds have expanded or contracted in the absence of predatory sea star.

Tidal Height of Mussels

From the photos, I also assessed whether mussels change their tidal height by moving to different heights. Using the same photographs and software from before, a straight reference line was drawn between the two metal stakes in the photograph. Then, ten mussels were chosen in the lower part of the mussel patches, along the edge of their respective bed. The selected mussels were evenly spaced out in the photograph. Once chosen, a straight vertical distance was measured, in centimeters, between the lowest point of the mussel and the reference line. If the lowest point of the mussel was above the line, the measured line would have a positive value, if it was below, the line would have a negative value. This process was repeated for every set of photographs using the same mussels that were chosen before. If the mussel was absent in later photographs, its measurement was marked as NA.

Additionally, I conducted measurements aimed at assessing whether the lower edge of the mussel beds was shifting downward through time. The height of the three lowest mussels in

14 the below (B) plots were measured the same way as before. The mussels measured in the subsequent photographs were always the lowest three mussels of that photograph, so they could be different mussels measured in each photograph.

Finally, to further establish whether or not the possibly changing tidal height of the mussel beds was due to recruitment of new individuals the shell length of the lowest five mussels in the B plots were measured from the photographs. Mussels measured were chosen by whether or not their length could be measured in the photos.

Predatory Whelk Abundance

On each photoquadrat sampling date, and in an additional date in October 26, 2015, I ​ quantified whelk abundance in the plots. Whelks were counted in each of the 10 plots within a

2 0.25 m ​ quadrat placed in the center of the eye­bolts but with its bottom lined up in between the ​ eye­bolts. Every Nucella and Ocinebrina was counted within the quadrat. ​ ​ ​ ​

Potential for Functional Compensation by Predatory Whelks

From October 15, 2015 to October 30. 2015, I conducted a lab experiment to measure the rate of predation of Nucella and its size preference of its prey, M. californianus. I placed 10 ​ ​ ​ ​ tupperware boxes (~15cm x 15cm) with small rocks (~8cm in length) in a sea­table. Ten mussels were placed in each box. The mussels' sizes ranged from 22mm to 58mm in shell length, with one mussel's size representing every 4mm. For example, from 22mm to 26mm, a mussel of length 24mm was chosen. I placed a single Nucella in half of the boxes, while the others did not ​ ​ receive any whelks and served as controls for mussel mortality not due to whelk predation. The whelks were all similar in sizes: their shell lengths measured from 22mm to 25mm. Every day the sea­tables were filled with water, submerging the mussels and whelks. Then, for three hours a

15 day, the sea table was drained. This mimics the tidal cycle the animals experience on a daily basis. Once a day, I checked the containers and recorded whether the whelk was on a mussel, if a whelk moved off of a mussel after it was on it, and the presence of empty mussel shells. I also measured the length of the empty mussel shells and how many there were by the end of the experiment (15 days).

In the end, the average predation rate on M. californianus of Nucella sp. was compared to ​ ​ ​ ​ the predation rate of P. ochraceus. The densities of the whelk and sea star were also compared. ​ ​

Historical Pisaster Counts

The counts of P. ochraceus conducted by Pearse (2010) were continued in the West and ​ ​ East sites. Within the granite outcrops, counts were conducted a total of four times over the course of the 16 months: Mid­June 2014, Late­June 2014, July 2014, and October 2015. The counts were averaged over the 16 months for each site, and compared to Pearse’s 5­year averaged counts.

Results

Mussel Percent Coverage

Over the course of 13 months, between June 2014­July 2015, percent mussel cover went up from 34.6% to 40.4%, averaged across the 18 plots (Figure 2). This small increase is statistically significant (Pairwise t­test: t = 5.15, df = 17, p = 4E­05). However, the variation in percent cover is very large among plots as indicated by the large error bars. I therefore conducted a further breakdown and reorganization of the data to get a better understanding of how trends vary among plots and sites, and where the statistical difference came from.

16

To more closely examine variation among plots, the plots were organized into four categories based on how much the mussel beds covered the initial quadrat in Mid­June. The four

2 2 categories were: 1­ initial coverage of 2,500+ cm ,​ 2­ initial coverage of 1,500­2,500 cm ,​ 3­ ​ ​

2 2 initial coverage of 1,500­500 cm ,​ and 4­ <500 cm .​ ​ ​ The temporal trends in percent mussel cover in the different plot categories are reported in Figure 3. Increasing trends are significant for categories 1, whose initial coverage was 2,500+

2 cm ,​ (Pairwise t­test one­tailed: t = 4.22, df = 6, p = 0.003) and 2, whose initial coverage was ​

2 1,500­2,500 cm ,​ (Pairwise t­test, one­tailed: t = 3.99, df = 3, p = 0.014), but not for categories 3, ​

2 whose initial coverage was 1,500­500 cm ,​ (Pairwise t­test, one­tailed: t = 1.21, df = 1, p = ​

2 0.440) and 4, whose initial coverage was <500 cm ,​ (Pairwise t­test, one­tailed: t = 1.99, df = 4, p ​ = 0.117) (Figure 3). These plots driving these trends were further highlighted by analyzing trends for the East and the West plots separately (Figure 4 & Figure 5, respectively). Category 4 for the East plots and Category 2 for the West plots are not represented because there was only one plot that fell in that category for each of them. The West plots also did not have any plots

17 that fell under Category 3. In the East plots, Category 2 plots had significant increasing trends

(Pairwise t­test, one­tailed: t = 5.13, df = 2, p = 0.036), while Category 1 (Pairwise t­test, one­tailed: t = 1.43, df = 2, p = 0.140) and Category 3 (Pairwise t­test, one­tailed: t = 1.21, df =

1, p = 0.220) did not. In the West plots, Category 1 plots had significant increasing trends

(Pairwise t­test, one­tailed: t = 6.24, df = 3, p = 0.004), while Category 4 (Pairwise t­test, one­tailed: t = 1.88, df = 3, p = 0.075) did not.

18

As a next step, I also examined temporal trends in percent mussel cover of the individual plots. The slope of the regression lines for both the East plots, Plots 1­5, (Figure 6a) and the

West plots, Plots 6­10, (Figure 6b) are all positive, but their magnitudes and significance varies.

The critical p­value was recalculated using the Bonferroni correction since each of the 18 plots were tested (10 ‘above’, A plots, and 8 ‘below’, B plots, see Methods), and each plot has its own test for significant increase in mussel cover. Each test increases the likelihood that the null

19 hypothesis would be falsely rejected. To decrease this probability, a more conservative critical value is calculated by dividing the 0.05 significance level by 18, the number of tests. The new critical p­value is therefore p<0.003. The plots had a significant positive slope (at p<0.003) were

Plots 2B, 7B, and 10A with p­values of 0.0002, 0.0019, and 0.0023, respectively. The p­values of the other plots can be found on Figures 5a & 5b.

20

Overall, percent cover of M. californianus did increase significantly over the 13 months. ​ ​ Mussel percent cover increased most in areas with an initially high abundance of mussel coverage, however when looked at individually, more plots showed significant increase in cover

(after a Bonferroni correction was applied).

Mussel Height Change

The relative height, measured as distance in centimeters from a fixed line drawn between the eye­bolts, by plot averaged over all of the mussels measured in that plot by date are represented by Figures 7a & 7b with standard error bars. The same 10 mussels were used in these measurements to track individual movement over the observation period.

21

22 By combining the A, ‘above’, & B, ‘below’, plots (Figure 7a & 7b), variation in mussel height was quite high, so the subplots were graphed separately for each of the 18 plots, i.e. for the A and B plots separately (Figure 8a & 8b).

23

By the end of the sampling period (July 2015), almost all of the subplots had lost about half of the individual mussels that I was tracking over time either due to being covered by another organism or because they were absent altogether. More often than not, the lower mussels were lost. For many of these plots, the mussel loss started as early as August 2014. For Plot 9b, no mussels were recorded due to kelp covering the whole plot. The only plots not impacted greatly by this were 2A & 2B, who only lost two mussels each by the end of the study.

Also, Plot 10B doesn’t have standard error bars due to only having one mussel being available to measure in Mid­June. That mussel was gone by the end, in July 2015.

Due to its minimal losses of mussels, Plot 2A is a suitable example to examine the movement of the 10 individual mussels that were tracked over the course of the project. By the end, most mussels moved between 2­4 cm downward (Figure 9).

24

Next, the heights of the lowest mussels were measured to see if there was a significant shift downward that was greater than could be explained by the small mussel movements observed. I tested the statistical significance of shifts in the lower mussel edge with paired t­tests comparing the first and last date for each of the plots. The predicted downward shift of the lower edge of the mussel bed was evident at the West but not the East site (Figure 10a & 10b). At the

East site, Plot 3 had a significant shift of the mussel edge to lower elevations (t = 130.87, df = 2, p = <0.0001) Plot 5 had a significant shift downward (Pairwise t­test, one­tailed: t = 19.39, df =

2, p = <0.001), and no other significant shifts were found in Plot 1 (Pairwise t­test, one­tailed: t =

0.39, df = 2, p = 0.37) or Plot 2 (Pairwise t­test, one­tailed: t = 1.76, df = 2, p = 0.11). At the

West site, significant shifts downwards were found for Plot 7 (Pairwise t­test, one­tailed: t =

4.05, df = 2, p = 0.03) and Plot 10 (Pairwise t­test, one­tailed: t = 5.31, df = 2, p = 0.02). There was no significant shifts downward in Plot 6 (Pairwise t­test, one­tailed: t = 0.73, df = 2, p =

0.27) and Plot 9 (Pairwise t­test, one­tailed: t = 1.93, df = 2, p = 0.10) However, kelp and algae

25 covered much of the lower portions of these plots, covering potentially lower mussels in July

2015 for 9B and covering all but one mussel in 10B in the August sampling date (Figure 10b).

Plot 4 and Plot 8 are not reported since these plots did not have ‘below’ (B) plots, and these measurements of the lower mussel edge were not conducted.

26

Lengths of the lowest mussels exhibited high variation through time (Figure 11a & 11b).

ANOVAs across the whole data set for each plot were used to measure statistical significance of mussel size changes over time. A two­factor ANOVA using Dates and Plots as factors showed ​ ​ significant variation in shell length between plots (F = 7.86, df = 7, p = <0.01) but no significant change in shell length between dates (F = 0.58, df = 6, p = 0.75), and no significant interaction between plots and dates (F = 0.86, df = 42, p = 0.71) (Table 1). In Plot 3, average shell length at the lower mussel edge decreased over time (Figure 11a) but all other plots did not exhibit this trend. Plot 4 and Plot 8 were not analyzed because they did not have B subplots.

27

28 Overall, some beds of M. californianus reached new low tidal heights. This was not due ​ ​ to the movement of already settled mussels, rather, the change in height was due to successful recruitment to these new tidal heights, as demonstrated by a significant decrease in shell length of the lowest mussels in some of the plots..

Whelk Counts

Over the course of the 16­month monitoring, the number of Ocinebrina & Nucella ​ ​ ​ counted in plots from both sites decreased from an average of 7.3 and 1.2 to 3.9 and 0.8

2 (No./0.25m )​ , respectively (Figure 12). This decline is significant for Ocinebrina sp.(Pairwise ​ ​ ​ t­test, one­tailed: t = 2.05, df = 9, p = 0.04) but not for Nucella (Pairwise t­test, one­tailed: t = ​ ​ 0.52, df = 9, p = 0.31). Ocinebrina’s decline was driven by the West plots, whereas densities ​ ​ varied among dates but with no overall trend at the East site (Figure 13a & 13b). Nucella sp. was ​ ​ more abundant at the East than West site (1.19 vs. 0.55) while Ocinebrina sp. had the opposite ​ ​ trend (3.06 vs. 5.84) (Figure 13a & 13b).

29

For the East Plots, the counts went from 3.8 average for Ocinebrina sp. and 1.8 average ​ ​ for Nucella sp. to 2.6 and 1.2, respectively (Figure 13a). There was no significant drop in counts ​ ​ for either Ocinebrina sp. .(Pairwise t­test, one­tailed: t = 0.47, df = 4, p = 0.34) or Nucella sp. ​ ​ ​ .(Pairwise t­test, one­tailed: t = 0.53, df = 4, p = 0.31). ​

For the West Plots, the counts went from 10.8 average for Ocinebrina sp. and 0.6 to 5.2 ​ ​ and 0.6 average for Nucella sp., respectively (Figure 13b). There was a significant drop in ​ ​

30 Ocinebrina sp. counts (Pairwise t­test, one­tailed: t = 3.05, df = 4, p = 0.04), but no significant ​ change for Nucella sp. (Pairwise t­test, one­tailed: t = 0.00, df = 4, p = 0.50). ​ ​ Overall, whelk counts did not increase. Instead, counts of Ocinebrine sp. decreased in the ​ ​ West plots and unchanged in East plots, and Nucella counts remained unchanged in both East ​ ​ and West plots.

Whelk Predation Experiment

In the laboratory experiment, the treatment group with Nucella had an average mortality ​ ​ rate of one mussel/container (out of ten mussels offered in each container) by the end of the 15 days, while the control group had no mortalities (Figure 14).

Within the treatment group, the mussels with a length between 42­46 mm had the highest mortality rate with two deaths, and next were the mussels with lengths between 22­26 mm,

38­42mm, and 54­58mm with one death each. Finally, the rest of the size classes had a zero mortality (Figure 15). These results indicate that whelks (ranging in 22­25 cm in shell length) are

31 able to consume mussels over the entire size range tested, up to 58mm in shell length, with no clear preference for a particular size bin.

Overall, mortality of M. californianus increased in the presence of Nucella sp. due to ​ ​ ​ ​ predation. However, the shell length of the dead mussels was not only wide but outside the reported size preference of Nucella sp. ​ Pisaster Counts

The Pisaster counts I conducted between June 2014­October 2015 went from 4 (3 in the ​ ​ East and 1 in the West) to 7 (6 in the East and 1 in the West) individuals (Figure 16). Counts were usually greater at the East than West site, except for late June 2014. In July 2014, the number of Pisaster included 5 sea star (4 in the East and 1 in the West) that were ~1 cm in radius ​ ​ while the rest of the sea star counted in every date were at least 7 cm in radius.

32

Using Pearse’s (2010) data, I was able to examine historical trends in sea star abundances at me sites (Figure 17). Each point of 5­years was calculated from the average of those 5 years from Pearse (2010). Averaging all of the counts, I produced a single estimate for each site, for

2015: two sea stars in the West (Area 1), and five sea stars in the East (Area 2).

Counts conducted between 1950­2015 show large declines in Pisaster abundance at both ​ ​ sites, from >100 individuals to 2­5 per site, but with different trajectories at the two sites (Figure

17). At the East site, abundance started to decline in 1955 and continued gradually for the whole time period. By 2010, before the 2013 mortality, counts were similar to those I obtained in 2015.

In contrast, abundances increased between 1950 and 1995 at the West site, then dropped over the past 20 years. Thus, at both sites, declines have preceded the recent region­wide mortality event, and Pisaster abundances were already very low, relative to historical values, in 2010, though a ​ ​ further decline (from 20 to 2 individuals, on average) occurred between 2010 and 2015 at the

West site.

33

The counts conducted for my research were the lowest ever seen in these sites. Pearse’s

(2010) historical counts show the decline of the sea star abundance started long before the 2013 die­off.

Discussion/Conclusions

In the absence of P. ochraceus, I hypothesized that percent cover of mussel beds would ​ ​ increase, and this was the case but in only some of the plots and for possibly reasons other than

Pisaster decline. I also predicted that the tidal height of the lower edge of mussel beds would ​ shift downwards due to movement of already settled mussels and/or recruitment of new mussels at lower elevations. New lows were reached by the mussels in some plots, but this change was highly variable among plots, and did not seem to be associated with the downward movement of already settled mussels. Furthermore, I hypothesized that whelk abundance would increase in response to the extremely low abundance of sea stars. Field data showed the opposite trend:

Ocinebrina sp. counts significantly declined over the 16 month monitoring and Nucella sp. ​ ​

34 counts showed no significant change. Predation rates of Nucella sp. on mussels, determined ​ ​ through a laboratory experiment, and Nucella sp. densities measured in the field indicate that it is ​ ​ possible for whelk predation to affect the expansion of M. californianus, but mussel control ​ ​ seems unlikely unless whelk numbers increase. Finally, by combining my counts of P. ochraceus ​ ​ with Pearse’s (2010) historical counts, I found that the impact of the recent sea star die­off in the rocky shores of Monterey Bay needs to be placed in a broader historical perspective. Historical counts show that the sea star population had already declined 90­95% from 1955 to 2010. The further decline after 2010 may not have had as much of an impact as predicted.

There are some caveats and possible artifacts associated with some of the methods I used in my research that could be addressed in future studies. More conclusive data on changing mussel heights could be obtained if measurements were conducted in the field rather than through the photographs. Macroalgae in the photographs often covered up mussels I tracked over time or mussels at the lower edge of mussel patches, which was an issue for almost all of the plots except for 2A & 2B. However, this problem would only risk finding no significant changes when in fact there were some, but if significant changes were found, as in this case, then this seems not to have greatly affected overall conclusions. Whelk counts were hindered by the complexity of the intertidal habitat; with so many cracks and hiding spots under mussel beds, whelks could easily be missed in field surveys. More accurate counts could be obtained via destructive sampling though my goal to monitor plots over time prevented me from using this technique. The predation experiment had two of the larger mussels whose mortalities seemed inconsistent with Nucella sp. predation because no drill holes were seen on their shells, possible ​ ​ inflating the mortality rate of mussels in the presence of Nucella sp. Repeating this experiment ​ ​

35 and monitoring whelk­mussel interactions through frequent visual inspection or continuous filming would ensure greater confidence in attributing mortality to whelk predation.

Overall, my results suggest that the intertidal communities of Monterey Bay may continue to change over time, with M. californianus slowly dominating the community via ​ ​ mussel bed expansion and recruitment to new tidal heights if the numbers of P. ochraceus ​ continue to stay low and whek abundance do not greatly increase.

Mussel Beds & Pisaster Counts

Mussel beds with higher initial percent coverages exhibited a higher rate of increase over the 13­month period (Figure 3, 4, & 5). Suitable habitat for M. californianus are areas where ​ ​ there are established mussel beds, since new recruits attach more easily to other mussels than to bare rock (Seed and Suchanek 1992). Recruitment typically starts in the winter months and peaks in the summer (Dayton 1971). However, a pattern of low recruitment with an occasional high recruitment event over the year is also common (Paine 1974; Robles et al. 1995). As a result, consistent with my results, sites that already have high abundance of M. californianus are ​ ​ expected to exhibit faster expansion than sites with a smaller initial presence.

In contrast with this general trend, when individual plots were analyzed separately, a statistically significant increase in percent cover over time was found in plots that had an initial coverage of less than 10%. These plots contained mussels that were smaller in size than the mussels in the plots with higher mussel cover, on average. Mussel growth rates decrease with mussel size. Smaller mussels (<30mm in length) can grow up to two and half times faster than mussels that are over 70mm in length (Seed 1976; Seed and Suchanek 1992). However, other conditions, like water temperature, salinity, food availability, and relative crowding of mussel

36 beds can also impact growth rates (Coe and Fox 1942; Seed 1976; Yamada and Peters 1988;

Yamada and Dunham 1989; Seed and Suchanek 1992), possibly contributing to the high variation in mussel expansion among plots through time. Growth of already established mussels may have contributed more than new recruitment to mussel expansion due to the short time­scale of the study, though percent cover increase through mussel recruitment is also possible. It takes about 12 months for a mussel to reach a shell length of about 30 mm, once it has settled on a suitable substrate (Yamada and Peters 1988; Yamada and Dunham 1989). So unless mussels recruited around the start or before the field monitoring, mussel bed growth from new recruitment would be small. However, it is also possible for percent coverage to increase if a lot of small mussels recruited. Unfortunately, my analyses could not tease apart these two mechanisms for mussel cover growth.

The surviving individual mussels I tracked over time demonstrated little, a few centimeters at most, to no movement, regardless of exposure or specific plot location. This was expected since M. californianus is a sessile species that often stays in one spot its entire life ​ ​ (Seed and Suchanek 1992). Thus, changes in the lower edge of mussel beds over time are most likely due to mortality, growth, and/or recruitment of new mussels.

It is interesting to note that the main mussel predators, Pisaster and the whelk Nucella ​ ​ ​ sp., had lower abundance at the West than East site during my study. Lower predation pressure ​ may explain the large shift downward of the mussel edge documented at some of the West plots.

Thus, both variation in mussel recruitment or growth, and differences in predation may underlie the observed large spatial variability (among plots and between sites) in mussel bed dynamics

37 over the past year. Continued monitoring and field experiments are needed to examine the possible role and relative importance of these mechanisms.

The height of the lowest mussels in the B plots dropped significantly for three of the eight plots, by 25­32cm over 13 months. This drop could be explained by recruitment of new mussels that occurred over the year. In the West plots, where this shift in the lower edge was most obvious, drops of tidal heights occurred around December, which is when the recruitment season starts. However, the drop sometimes continues into March, which is when recruited mussels would have grown by about 10mm (Paine 1974; Yamada and Peters 1988). This would have made them easier to see in the photographs. Algae and other organisms often covered up anything settled directly on the rock, preventing me from seeing potentially lower mussels if they were small. Once again, the short duration of this study is a limiting factor; additional lower mussels could potentially be found in the future due to them growing large enough to be seen.

The same limitation was present when the lengths of the lowest mussels in the B plots were measured; only the visible ones, not covered in algae, could be measured. The only obvious decrease in mussel lengths over time was detected in Plot 3, indicative of a local recruitment event during or preceding this study. This was also a plot that had a significant drop in height in the lowest mussels present in it. Together, the drop in height and decrease in length demonstrate that M. californianus patches at my study site can shift tidal heights via recruitment at these ​ ​ ​ ​ lower heights, as suggested by Seed and Suchanek (1992). Whether or not this will occur across the whole intertidal zone is unclear from my data since lower and smaller mussels in the other plots could have been hidden from view in the photographs. Thus my results indicate that the hypothesized shift downward of the lower edge of the mussel beds can occur, via recruitment

38 and survival of mussels at low elevations, even over a relatively short time frame (months).

However, the generality of this response remains to be established with continued monitoring, over longer time frames.

Pisaster counts varied among sampling dates at both sites. Data from Pearse ​ (2010) show that counts, regardless of site, can also vary greatly year to year, fluctuating between +/­5 to +/­20 from one year to the next. Thus, it is difficult to assess short term (months to a few years) changes in Pisaster abundances. Longer term counts are needed to assess ​ ​ population trends..

The short term fluctuations in Pisaster numbers during my study are very small compared to the historical change revealed by the 65­year long monitoring of sea stars at my sites. My P. ​ ochraceus counts are the lowest across the historical time series of Feder (1956, 1959, 1970) and ​ Pearse (2010) for both sites. While sea star are under predation pressure from sea otters and seagulls (Raimondi 2007), sharper declines in local populations can occur from the outbreak of diseases (Eckert et al. 1999; Sanford & Menge 2007). The sea star wasting disease that affected

P. ochraceus and other sea star species in 2013 was also present in sea stars in the late­1900’s, ​ ​ ​ and ever since 1978, disease has periodically affected sea star populations along the west coast of

North America (Eckert et al. 1999; Hewson et al. 2014).

Whelk Counts & Predation

Both Ocinebrina and Nucella did not increase in abundance as predicted. Whelk counts ​ ​ ​ ​ dropped for Ocinebrina sp. and stayed the same for Nucella sp. over the 16 month monitoring. ​ ​ ​ ​ One common behavior of whelks is to seek shelter in a crevice after feeding for up to nine tides

(Bayne & Scullard 1978; Hughes & Drewett 1985). This shelter­seeking behavior could have

39 impacted the counts as some of the whelks which could have been hidden from sight during surveys. Thus, counts could reflect changes in both abundance and behavior. However, it is unlikely that this behavior could have increased in frequency over time, thereby explaining the declining trend. Whelk decline over the short duration of this study could instead be driven by a number of factors, including variability in recruitment and survival driven by environmental conditions and biotic interactions. Detecting actual population trends for whelks, similar to sea star, will require continued monitoring over longer time frames.

Mortality of M. californianus in the presence of Nucella was expected since the whelk is ​ ​ ​ ​ known to prey on the mussel (Barnes 1980; Crothers 1985). Moreover, Nucella used in the ​ ​ experiment (22­25mm in length) were expected to prey on mussels whose length were less than

20mm (Bayne & Scullard 1978; Crothers 1985). Contrary to these previous findings indicating a preference of whelks for small mussels, the lab experiment suggested a wide variety of mussel lengths are susceptible to whelk predation, up to 58mm in shell length, the largest size used in the experiment. Nucella are known to eat mussels that are larger than their ‘preference range’ in ​ ​ laboratory settings (Hunt & Scheibling 1998) possibly because larger mussels are easier for whelks to find due to their size than smaller ones. Additionally, the deaths of two of the mussels, whose lengths were 42­45mm and 54­58mm, cannot be conclusively attributed to whelk predation in my experiment. Their shells did not exhibit any holes like the other mussels did from when the Nucella drilled into them (Figure 18), and nearly all of their flesh was still inside ​ ​ of their shells. This could be due to physical stress or the presence of a pathogen in their box since both mussels were in the same box. If mortality of these larger mussels is not due to predation the size range of mussels consumed in the experiment would become closer to the

40 ‘preference range’ of the whelk reported in the literature. The feeding preference experiment should be repeated to further investigate size selectivity and possible size refuges of mussels from whelk predation..

Even under the assumption that whelks are capable to feed on mussels over the same size range as sea stars, Ocinebrina & Nucella show limited potential in replacing P. ochraceus in ​ ​ ​ ​ ​ ​ controlling the abundance of M. californianus. The feeding rate of a single P. ochraceus is about ​ ​ ​ ​ 80 mussels/year (Mcclintock & Robnett, 1986). From my lab experiment, the feeding rate of

Nucella sp. is 1 mussel/15 days, which translates to 24.3 mussels/year. The average densities of ​

2 2 Nucella in the plots of East and West sites were 1.36 whelks/0.25m ​ and 0.56 whelks/0.25m ,​ ​ ​ ​

2 2 respectively, which translates to 5.44 whelks/m ​ and 2.24 whelks/m ,​ respectively. This indicates ​ ​ that at these sites, the number of M. californianus that will be consumed by Nucella over one ​ ​ ​ ​ year is estimated to be at 11,118 mussels at the East site and 8,720 mussels at the West site.

41 However, this is assuming that the whole area (160 m and 86 m, respectively) is suitable for

Nucella sp, which is not the case due to high and dry rocks and deep waters in the sites, where ​ Nucella sp. is not found so these numbers are overestimates. The abundance of P. ochraceus ​ ​ dropped from 19 and 6, in the East and West sites, respectively, in 2010 (Pearse, 2010) to 2 and

5, respectively, in 2015 (Note: These numbers do not include sea stars that were ~1 cm). These numbers also assume that the whelks would feed at the same rate for all sized mussels, which would not be the case for larger mussels whose thicker shells would slow down predation (Hunt

& Scheibling 1998). At 80 mussels/year for each sea star, that is an approximate gain of 1,360 mussels in the East site and 80 in the West site. Though these numbers could easily be made up for by the Nucella sp., based on my estimates above, these estimates are also based on another ​ ​ assumption: that Nucella sp. exclusively eats M. californianus. This is not the case since Nucella ​ ​ ​ ​ ​ sp. also prey on barnacles (Barnett, 1979), leading to further overestimation of the potential ​ mussel mortality caused by Nucella in the field.. Moreover, if mortality from sea star predation is estimated from the historical sea star counts, then the number of mussels would have been

11,040 mussels for the East site and 11,840 mussels at the West site according to the highest

Pisaster abundances recorded by Pearse and the feeding rate of 80 mussels/year for each sea star ​ (Mcclintock & Robnett, 1986). In conclusion, the question of whether whelks may compensate decreased mussel mortality from sea star decline remains open, but based on my data and estimates it seems unlikely that whelks play this role at HMS, given their low numbers and low predation rates. Addressing this question will require field experiments and continued monitoring of whelks and mussels.

42 If the observed trends of expansion of mussel beds documented for some of the plots continue, M. californianus may outcompete other organisms in the mid and low intertidal zones. ​ ​ Trends observed so far suggest these changes may be stronger at the West site than at the East site. Within these areas, vertical surfaces may be less affected; once M. californianus reaches a ​ ​ certain size, they can no longer survive on vertical faces (Paine 1974). Also, some red algae could still coexist with the mussel, but only in areas protected from wave exposure. (Peterson

1984; Dittman and Robles 1991; Wootton 1992; Meese 1993; Robles and Robb 1993; Robles et al 1995).

Overall, my research provides some evidence that changes in intertidal communities might be occurring, possibly in response to P. ochraceus decline. In particular, the beds of M. ​ ​ ​ californianus have increased their percent coverage at some locations, and their lower edge has ​ in some cases shifted downward, as predicted under the assumption that the abundance and distribution of mussels are controlled by sea star predation. However, these effects are patchy, and the role of sea star decline as a driver of these changes need to be further examined because historical data indicate that Pisaster decline has occurred gradually over the past decades, not only recently during the 2013 mass mortality that has affected other abundant populations. This could mean that the short­term changes in the intertidal communities I documented in this study could be driven by processes other than a sudden decrease in predation rates, which have likely been in decline decades ago. Whether or not the die­off of 2013 furthered these effects is unclear.

Future directions for additional research include continued monitoring of the same plots and sites and an examination of long­term trends of benthic community change, as well as responses to possible sea star recovery. Additional and longer­term laboratory and field

43 experiments are also needed to elucidate interactions and drivers of change. Overall my research shows that intertidal ecosystems are highly dynamic and that understanding what drives change requires a long­term perspective and combining monitoring with experiments.

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