UC San Diego Electronic Theses and Dissertations

UC San Diego UC San Diego Electronic Theses and Dissertations

Title Large inter-annual variability of spawning in San Diego’s marine protected areas captured by molecular identification of fish eggs

Permalink https://escholarship.org/uc/item/6g03z4c0

Author Duke, Elena

Publication Date 2018

Peer reviewed|Thesis/dissertation

eScholarship.org Powered by the California Digital Library University of California

UNIVERSITY OF CALIFORNIA, SAN DIEGO

Large inter-annual variability of spawning in San Diego’s marine protected areas captured by

molecular identification of fish eggs

A thesis submitted in partial satisfaction of the

requirements for the degree Master of Science

Marine Biology

Elena Maria Duke

Committee in charge:

Professor Ron Burton, Chair Professor Eric Allen Professor Phillip Hastings

2018

Elena Maria Duke, 2018

The Thesis of Elena Maria Duke is approved, and it is acceptable in quality and form for publication on microfilm and electronically:

______

Chair

University of California, San Diego

2018

iii TABLE OF CONTENTS

Signature Page……………………………………………………………………………………iii

Table of Contents…..…………………………………………………………………………..…iv

List of Figures..……….…………………………………………………………………………...v

List of Tables..…………………………………………………………………………………....vi

Acknowledgements………………………………………………………………………………vii

Abstract of Thesis…………………………………………………………………………...…..viii

Introduction………………………………………………………………………………………..1

Methods ……………………………………………………………….…………………..4

Results……………………………………………………………………………………..6

Discussion………………………………………………………………………...……...20

References……………………………………………………...………………………………...26

iv LIST OF FIGURES

Figure 1. Value for each month is the average fish eggs collected in each weekly collection for that month in the San Diego-Scripps Coastal Reserve from 2012-2017 shown with SEM. The years 2012 and 2014 were taken with permission from Harada et al 2015……………………...13

Figure 2. Average number of fish eggs collected by month is shown for six species from 2012- 2017………………………………………………………………………………………………13

Figure 3. Non-metric multidimensional scaling from abundance of fish species averaged per month normalized to number of eggs collected from 2012-2017. Based on Bray-Curtis dissimilarity………………………………………………………………………………………14

Figure 4. Non-metric multidimensional scaling from abundance of fish species normalized to number of eggs identified between two sampling sites from February 2017 to August 2017. Based on Bray-Curtis dissimilarity………………………………………………………………15

Figure 5. Average sea surface temperature at the Scripps Pier on collection days from 2012- 2017. Average depicted is a moving average over three week period overlapping by one week……………………………………………………………………………………………...16

Figure 6. Cumulative upwelling totaled over one month period plotted against log transformed mean fish eggs collected over one month from August of 2012 to October of 2017 (R 2 =0.33, F=30.95, p<0.001)……………………………………………………………………………….17

Figure 7. Cumulative spring upwelling plotted against the average spring and summer (March- August) fish egg abundance per collection. Significant positive relationship between spring upwelling and spring summer fish egg abundance………………………………………………18

Figure 8. Average winter temperature (December -February) plotted against the following spring and summer (March-August) average fish egg abundance………………………………………19

v LIST OF TABLES

Table 1. For each collection year the date in which the highest species richness per collection is shown (excluding 2012 in which summer spawning was not recorded). Two dates are shown for 2015, because there were two collections with the highest species richness……………………10

Table 3. Average annual and average winter (December-February) sea surface temperatures are shown with standard error in Celsius. Data were collected approximately every six minutes at 2m depth from the Scripps pier………………………………………………………………………12

vi ACKNOWLEDGEMENTS

Thank you to my family for encouraging my love of the outdoors, the ocean and science from a young age. Thank you to my friends for encouraging my passion for marine science and offering words of support. I am incredibly grateful for my advisor Dr. Ron Burton, for allowing me to volunteer in his lab as an undergraduate, conduct an independent research project as an undergrad, and eventually having me as a master’s student in his lab. Thank you to the rest of the members of the Burton lab: Alice Harada, Thiago Lima, Reggie Blackwell, Por

Tangwancharoen, Satomi Tsuboko, Cindy Salmeron, Sumi Hunjan, and Tim Healy for incredible support and advice. Thank you to undergraduate volunteers: Gabriella Haddad, Emma Choi and

Katya Reshatoff for enthusiastically helping with sample processing. Thank you to collections manager Phil Zerofski, for collecting weekly plankton samples from the La Jolla kelp forest for our survey. Thank you to the Richard Grand Foundation for supporting costs of sequencing and helping to fund our research.

This thesis uses material currently being prepared for submission for publication as Large interannual variability of spawning in San Diego’s marine protected areas captured by molecular identification of fish eggs. Duke, Elena Maria: Harada, Alice; Burton, Ron. The thesis author was the primary investigator and author of this paper.

vii

ABSTRACT OF THE THESIS

Large inter-annual variability of spawning in San Diego’s marine protected areas captured by

molecular identification of fish eggs

Elena Maria Duke

Master of Science in Marine Biology

University of California, San Diego, 2018

Professor Ron Burton, Chair

Marine protected areas have become an important management tool that can provide data regarding human impacts on the ocean while protecting exploited species, enhancing biodiversity and protecting ecosystems. Long-term monitoring of reserves is critical to assess how global processes such as natural environmental variation and climate change affect marine populations.

viii We conducted fish egg surveys in both soft bottom habitat and kelp forest and identify fish eggs using DNA barcoding. We compared these data to baseline spawning data established by Harada et al 2015. We documented large inter-annual variability in fish egg abundance associated with climatic fluctuations, including an El Niño event captured during our sampling years.

Interestingly, we observed a phenological shift of peak spawning activity during 2017. We found inter-annual fish egg abundance may be linked with upwelling regimes and winter temperatures.

We found no distinct differences in community composition between habitats we sampled.

Through long-term monitoring of fish spawning we can understand how natural environmental variation such as El Niño events affect fish populations which will help us predict how temperature increases associated with climate change will affect marine fish populations.

Furthermore, long-term monitoring can help track trends in marine resource availability and evaluate marine reserve efficacy.

ix Introduction

Marine protected areas are widely used tool for management of marine resources and conservation efforts (Allison, Lubchenco, and Carr 1998). In general, marine protected areas are spatially delimited regions of the ocean that restrict human activities for conservation purposes with specific goals including: protecting biodiversity, protecting critical habitats, enhancing fisheries, protecting exploited species, protecting ecosystems, and assessing the scale of human impacts on the ocean (Airamé et al. 2003; Allison, Lubchenco, and Carr 1998). California’s coastline has one of the largest marine protected area networks in the world. In 1999 the

California legislature established the Marine Life Protection Act (MLPA) to set aside marine reserves, and in 2012 established new regulations for marine reserves in Southern California

(Airamé et al., 2003; Harada et al., 2015). Because there are inherent costs to implementing and enforcing marine reserves as well as conflicting user groups including recreational and commercial fishing industries, it is important to evaluate reserve efficacy to ensure reserves are reaching their conservation goals (Avasthi, 2005; Balmford, Gravestock, Hockley, McClean, &

Roberts, 2004).

During the past decade, there has been huge growth in scientific literature regarding marine reserve design. MPAs are designed to ensure population persistence, protect multiple habitats, and function within a network to account for dispersal patterns and allow for spill-over into non-protected areas (Airamé et al. 2003; Allison et al. 2003; Avasthi 2005; Burgess et al.

2014; Jones 2002; Parnell et al. 2006; Sala et al. 2002). One of the many challenges of designing marine reserves is that unlike terrestrial reserves, it is impossible to put boundaries around marine life or protect from large oceanic processes (Agardy, 2000). For example, marine larval dispersal patterns and connectivity to adjacent habitats are often unknown, yet these data are

1 critical for predicting population persistence of marine organisms (Burgess et al., 2014; McLeod,

Salm, Green, & Almany, 2009; Parnell et al., 2006) . One way to address this problem is to sample the larvae of marine populations from different sites or habitats to understand locations of spawning to ensure spawning sites are protected. Furthermore, oceanic processes such as El

Ni ño Southern Oscillation events and currents, as well as anthropogenic disturbances, such as pollution, ocean acidification, and temperature increases, act on much larger spatial scales than reserves can encompass, all of which can cause variable recruitment and alter population trajectories (Agardy 2000; Allison, Lubchenco, and Carr 1998; Parnell et al. 2006).

Through long-term monitoring we can track trends in resource availability to ensure marine reserves are reaching their resource enhancement goals, assess changes in the abundance or distribution of organisms, and assess human impacts on the ocean. For example, Perry et al.

(2005) documented pole-ward distribution shifts of fish populations associated with increased water temperature. In other cases, temperature increases have been shown to alter the phenology of fish spawning patterns or change duration of larval development in some fish species (Genner et al., 2010; Pauly & Pullin, 1988). Through long-term monitoring of reserves, we can document changes in distribution and abundance of marine fish populations in the context of larger global processes.

Fish egg and larval surveys can be a useful tool in assessing fish populations and their spawning patterns because they can: 1) assess abundance and distribution of fish, 2) assess multiple species of fish, and 3) assess larval life stages. The latter of these is particularly relevant to complement traditional diver surveys and trawls that are limited to adult and juvenile fish

(Alstrom & Moser, 1976; Harada et al., 2015). Ichthyoplankton surveys have been used to document the spawning grounds of many commercially important fish species such as the

2 northern anchovy in the Gulf of California, and cod and plaice in the North Sea (Fox, O’Brien,

Dickey-Collas, & Nash, 2000; Green-Ruiz & Hinojosa-Corona, 1997). However, because the eggs of many fish species are indistinguishable, it had been impossible until recently to accurately determine which species were spawning, with the exception of a few morphologically distinct species (Alstrom & Moser, 1976). New molecular techniques have made possible the accurate identification of fish eggs and larvae (Gleason & Burton, 2012; Harada et al., 2015;

Hyde et al., 2005).

This study documents spawning activity of fish populations in two of San Diego’s marine protected areas: the San Diego Scripps Coastal Reserve and Matlahuayl State Marine Reserve

(SMR) . The San Diego Scripps Coastal Reserve prohibits the take of marine resources except coastal pelagic species by hook and line and Matlahuayl SMR prohibits the take of all marine resources . Fishes present in our study area are well documented in the Scripps Marine

Vertebrates collection (Hastings, Craig, & Hyde, 2014); however, there is less information about species-specific spawning patterns. We continue the monitoring of fish spawning established by

Harada et al. 2015 by conducting fish egg surveys and identifying eggs using DNA barcoding.

Through the continued monitoring of ichthyoplankton in the San Diego-Scripps Coastal Reserve we aim to document any changes in spawning activity that might be associated with changes in oceanographic conditions, such as temperature increases associated with “The Warm Blob” event in 2014 and the 2015-2016 El Niño event (Bond, Cronin, Freeland, & Mantua, 2015). We document large inter-annual variation in spawning activity across sampling years 2012-2017.

Beginning in 2017, we further expand our survey area to include sampling from nearby kelp forest habitat adjacent to the Matlahuayl (SMR) to document spawning patterns of kelp associated fish species. By assessing both kelp forest and sandy beach habitat in our study, we

3 can collect information about how fishes use specific habitats to spawn. These long-term data are valuable for reserve management because they can help ensure spawning sites are protected such that marine reserves can meet their biodiversity and marine resource goals.

Methods

Sampling locations and techniques

Weekly plankton samples were collected from the end of Scripps Pier (32.8328° N, -

117.2713° W) from August 2014 to August 2017, building on previous work started in August of

2012 (Harada et al., 2015). Samples were collected by lowering a 505 micron-mesh one-meter diameter plankton net until the net reached the seafloor. This was repeated three more times for a total of four pulls, sampling approximately 16 cubic meters of water (based on average water depth of about 5m). Weekly plankton samples were collected from kelp forest habitat adjacent to the Matlahuayl reserve (32.85408ºN, 117.28105ºW) from February 2017 to August 2017.

Samples were collected by pulling a 333 micron-mesh one half-meter diameter plankton net behind a small boat at 0.5 knots for 5 minutes. The net was weighted for a sampling depth of about 1m. Although we used different mesh sizes at different sampling sites, both mesh sizes

(0.5 mm, and 0.3 mm, respectively) were smaller than the fish eggs we sample ~1mm. California

Department of Fish and Wildlife issued permit (#4564) was used for the collection of plankton from the MPA’s. Samples taken from the nearby kelp forest were outside of Matlahuayl SMR so no permit was required . In both sample locations, the collected plankton were manually sorted using a dissecting microscope and fish eggs were individually counted and removed. The northern anchovy (Engraulis mordax ) and Pacific sardine eggs (Sardinops sagax), both

4 morphologically distinct, were counted and removed from the sample. The remaining eggs were stored in 95% ethanol at 4 °C at least 12 hours prior to further processing.

Processing eggs

After storage in ethanol for at least 12 hours, individual fish eggs were rinsed with deionized water and placed in 15 μl of buffer (2/3 Qiagen AE buffer, 1/3 water). Eggs were then physically squished with a clean pipette tip to release the DNA. No further DNA extraction or purification was needed. Samples were stored at -20 °C prior to polymerase-chain reaction (PCR).

PCR and sequencing

To amplify DNA, universal fish cytochrome c oxidase subunit I (COI) primers were used

(Ward, Zemlak, Innes, Last, & Hebert, 2005): COI VF1 forward primer (5′-

TTCTCAACCAACCACAAAGACATTGG-3’) and COI VR1 reverse (5′-

TAGACTTCTGGGTGGCCAAAGAATCA-3′). These primers produced an amplicon of 710 bp. PCR was performed using 25 μl reaction volume, with 12.5 μl of GoTaq Green Master Mix

(Promega), 5 pmol of each primer, and 1 μl of DNA extract. Thermal cycling was initiated at 95 °C for 2 min followed by 35 cycles of 95 °C for 30 s, 50 °C for 45 s, and 72 °C for 1 min, followed by

72°C for 5 min. After PCR, samples were run on a 1.5% agarose gel and visualized with GelRed

(Biotium) or SybrSafe (Invitrogen) to detect presence of amplified DNA. Samples that failed to amplify with COI were amplified using the mitochondrial 16S ribosomal rRNA gene, using forward primer 16Sar (5’ CGCCTGTTATCAAAAACAT-3’) and reverse primer 16Sbr (5’-

CCGGTCTGAACTCAGATCACGT-3’) for a 570 bp amplicon (Palumbi 1996 ). Samples with either the COI or 16S product were purified using Sephadex G-50 Fine spin columns and sequenced using

Sanger sequencing (commercial sequencing service). Sequences were identified using BLAST searches of NCBI database, which contains DNA barcodes from over 500 species of California

5 marine fishes most of which are vouchered in the Scripps Institution of Oceanography Marine

Vertebrate Collection, allowing for nearly complete coverage of species in California marine waters

(Hastings & Burton, 2008). The top BLAST hit with 95% sequence similarity or greater was used for species identification if there were no closely related species.

Measurements of environmental variables

Sea surface temperature, chlorophyll, salinity and pressure are measured and recorded at 2m depth approximately every 6 minutes from the Scripps Pier. Data were accessed through the

Southern California Ocean Observing System and used for analysis of fish egg collections with respect to variation in ocean temperature. We estimated monthly upwelling using daily upwelling indices calculated at 33N, 119W from all collection years (2012-2017) by Pacific Fisheries

Environmental Laboratories (www.pfeg.noaa.gov).

Results

Abundance of fish eggs

We observed fish spawning patterns in San Diego’s marine protected areas in two different habitats over time and compared these data to baseline spawning data that was established in the

San Diego-Scripps Coastal Reserve (Harada et al . 2015). We found extensive inter-annual variability in fish spawning. During the years 2015 and 2016, we observed large declines in the average number of fish eggs collected per month during the summer (May through August) compared to the baseline data from the previous two years (Fig 1). Although we did observe seasonal increase in the number of fish eggs in the summer (compared to winter) across all four years consistent with Harada et al. (2015), there were significantly less fish eggs from 2015 &

2016 than from 2013 & 2014. Interestingly, during the summer of 2017 we observed a recovery of fish eggs numbers similar to numbers observed in 2013 and 2014. However peak-spawning

6 season during 2017 appears to have shifted to later in the year from May/June in 2013-2016 to

June/August in 2017 (Fig 1). September through January show no difference in the monthly average of fish eggs across all years. We show species-specific abundance through time for the five most common species in our samples, and one important sport fish the California corbina

(Menticirrhus undulatus ) in Figure 2. For each sampling year, the date of the highest number of species per collection were recorded shown in Table 1. The highest number of species recorded per sample occurred approximately one month later in 2017 compared with baseline spawning years (2013-2014; Table 1). For four species, seasonal spawning was observed to start approximately one month later in 2017 than in previous years: the Pacific sardine (Sardinops sagax ), queenfish ( Seriphus politus ), Pacific chub mackerel (Scomber japonicus ), and jack mackerel (Trachurus symmetricus ). Only species for which we found 50 or more fish eggs were examined for phenological changes in spawning.

Community composition

Overall, in collections from the Scripps Pier from September of 2014 to August of 2017 we collected 6939 fish eggs and of those 4150 eggs were identified as 37 fish species. During the collection period of the kelp forest from February 2017 to August 2017 we collected 11,163 fish eggs and identified 5546 as 35 species. There were seven species found by Harada et al. 2015 that we did not find: Ocean white fish ( Caulolatilus princeps ), California lizard fish (Synodus lucioceps ), California Opal Eye (Girella nigricans , Pacific pompano (Peprilus simillimus), mussel blenny ( Hypsoblennius jenkinsi), Giant Sea Bass ( Stereolepis gigas ), Pacific barracuda

(Sphyraena argentea). We documented five additional species: the yellowtail jack ( Seriola lalandi), flat-head grey mullet ( Mugil cephalus ), blackbelly eelpout ( Lycodes pacificus ), basketweave cusk-eel ( Ophidion scrippsae ), and California scorpion fish ( Scorpaena guttata ).

7 However, all of these newly documented species contributed to less than 0.2% of all fish eggs that were identified and represent rare species that contribute very little to overall community composition based on the eggs we sampled. Multivariate analysis of community composition shows there were no distinct changes in community composition over time, but distinct differences in seasonal spawning community between fall-winter and spring-summer months

(Fig 2). Note that warm years do not cluster together; rather all years overlap in Figure 2.

However, cool colors, which represent summer months and warms colors, which represent winter months, cluster together across years.

From February 2017 to August 2017 we sampled the kelp forest habitat and were able to compare community composition between kelp and pier habitats (Table 2). Nine species in the kelp forest plankton samples were not found at the Scripps pier in that time period: the hornyhead turbot (Pleuronichthys verticalis ), red-eye round herring (Etrumeus acuminatus ), opaleye (Girella nigricans ), diamond turbot (Hypsosetta guttulata), C-O sole (Pleuronichthys coenosus ), white seabass (Atractoscion nobilis ), bigmouth flounder (Hippoglossina stomata ),

Pacific barracuda (Sphyraena argentea ), and giant sea bass (Stereolepis gigas ). With the exception of two species: the bigmouth flounder (Hippoglossina stomata ) and red-eye round herring (Etrumeus acuminatus ), all other species had been observed in previous collections from the Scripps Pier. Five species were found in pier samples and absent from kelp forest plankton samples: zebra-perch sea chub (Hermosilla azurea ), spotted sand bass (Paralabrax maculatofasciatus ), Pacific pompano (Peprilus simillimus ), spotted cusk-eel (Chilara taylori ) and the California lizardfish (Synodus lucioceps ). Despite these differences in species presence or absence between sites, the differences accounted for 0.2% or fewer total eggs sampled and therefore did not appear to contribute substantially to overall differences in community

8 composition. Using multivariate analysis, we determined that both sampling sites showed similar spawning community during the period when collections were made at both sites (Fig 3). If communities between sites were different we would expect to see clustering of samples between sites, however we see both sites overlap in Figure 3. Species with the largest difference in percentage between our sampling sites were the northern anchovy (Engraulis mordax), speckled sanddab (Citharichthys stigmaeus) , Pacific sardine (Sardinops sagax) and California salema

(Xenistius californiensis ; Table 2) .

Environmental effects on spawning

Sea surface temperature data collected from the Scripps pier show variability in temperatures across sampling years (Fig 4). During winters 2014-2015 and 2015-2016 we observed warmer temperatures than previous years (Table 3). Additionally, these two years show the highest annual average temperatures. The data suggest that when winter temperatures were warmest the following spring and summer fish spawning was depressed. In order to examine the relationship to winter temperatures and spring and summer spawning we plotted the average winter temperature (December-February) against the average number of spring and summer

(March-August) fish eggs collected from the pier for each year. We found a significant negative correlation between winter temperatures and spring and summer spawning (R2= 0.83, p<0.5).

There was a significant positive relationship between spring (March-May) upwelling measured by cumulative sum of daily upwelling indices (cumulative upwelling index) and the average spring and summer fish egg abundance for each year (R2= 0.75, p<0.05; Fig 6). These results should be considered preliminary and further sampling should be continued in order to determine if spring upwelling or winter temperatures could predict spring and summer spawning activity.

Consistent with Harada et al. (2015), we observed abundant fish eggs when temperatures are

9 highest, coinciding with seasonal spawning. We also found a significant positive correlation between the cumulative upwelling index (CUI) and the log mean fish egg abundance by month grouped across all species and all years (R2= 0.33, p<0.001).

Table 2. List of species collected from weekly samples from two sites: Kelp and Pier during Feb- Aug 2017. Both number of eggs collected from individual species and percent of total eggs collected is shown for each site, listed in order of percent difference between sites. Eggs Eggs % of % of # of # of identified: Identified: total total collections collections % difference Species Site~ Kelp Site~Pier ~Kelp ~Pier ~Kelp ~Pier between sites Engraulis mordax 1946 106 35.09% 5.38% 13 12 29.71% Citharichthys stigmaeus 582 619 10.49% 31.39% 23 28 20.90% Sardinops sagax 891 97 16.07% 4.92% 15 6 11.15% Xenistius californiensis 307 271 5.54% 13.74% 7 4 8.21% Citharichthys xanthostigma/ sordidus 47 116 0.85% 5.88% 16 8 5.03% Roncador stearnsii 24 80 0.43% 4.06% 6 10 3.62% Seriphus politus 14 62 0.25% 3.14% 7 10 2.89% Oxyjulis californica 599 162 10.80% 8.22% 20 18 2.59% Menticirrhus undulatus 87 57 1.57% 2.89% 6 8 1.32% Halichoeres semicinctus 652 254 11.76% 12.88% 12 11 1.12% Genyonemus lineatus 2 22 0.04% 1.12% 3 5 1.08% Scomber japonicus 107 19 1.93% 0.96% 9 7 0.97% Paralichthys californicus 98 17 1.77% 0.86% 15 11 0.90% Umbrina roncador 16 21 0.29% 1.06% 4 3 0.78%

10 Table 2. List of species collected from weekly samples from two sites: Kelp and Pier during Feb- Aug 2017. Both number of eggs collected from individual species and percent of total eggs collected is shown for each site, listed in order of percent difference between sites, continued. % Eggs Eggs % of % of # of # of difference identified: Identified: total total collections collections between Species Site~ Kelp Site~Pier ~Kelp ~Pier ~Kelp ~Pier sites Paralabrax clathratus 35 4 0.63% 0.20% 10 4 0.43% Ophidion scrippsae 19 1 0.34% 0.05% 3 1 0.29% Xystreurys liolepis 1 6 0.02% 0.30% 2 2 0.29% Symphurus atricaudus 22 3 0.40% 0.15% 6 2 0.24% Anisotremus davidsonii 27 6 0.49% 0.30% 7 2 0.18% Paralabrax nebulifer 5 5 0.09% 0.25% 5 4 0.16% Semicossyphus pulcher 15 8 0.27% 0.41% 6 5 0.14% Cynoscion parvipinnis 11 2 0.20% 0.10% 3 1 0.10% Seriola lalandi 11 2 0.20% 0.10% 4 1 0.10% Mugil cephalus 1 1 0.02% 0.05% 2 1 0.03% Trachurus symmetricus 7 2 0.13% 0.10% 4 2 0.02% Cheilotrema saturnum 2 1 0.04% 0.05% 3 1 0.01% Hermosilla azurea 0 17 NA 0.86% 0 3 NA Paralabrax maculatofasciatus 0 4 NA 0.20% 0 3 NA Peprilus simillimus 0 3 NA 0.15% 0 1 NA Chilara taylori 0 2 NA 0.10% 0 2 NA Synodus lucioceps 0 2 NA 0.10% 0 1 NA Pleuronichthys verticalis 4 0 0.07% NA 3 0 NA Etrumeus acuminatus 3 0 0.05% NA 3 0 NA Girella nigricans 3 0 0.05% NA 2 0 NA Hypsopsetta guttulata 2 0 0.04% NA 3 0 NA Pleuronichthys coenosus 2 0 0.04% NA 3 0 NA Atractoscion nobilis 1 0 0.02% NA 2 0 NA Hippoglossina stomata 1 0 0.02% NA 2 0 NA Sphyraena argentea 1 0 0.02% NA 2 0 NA Stereolepis gigas 1 0 0.02% NA 2 0 NA

Table 3. Annual average and average winter (December-February) sea surface temperatures are shown with standard error in degrees Celsius. Data were collected approximately every six minutes at 2m depth from the Scripps pier. Average winter Annual average temperature ± Year temperature ± SEM ( ºC) Winter SEM ( ºC) 2012 17.50 ± 0.008 2012-2013 14.37 ± 0.005 2013 17.25 ± 0.006 2013-2014 15.47 ± 0.003 2014 19.57 ± 0.006 2014-2015 17.10 ± 0.005 2015 19.26 ± 0.009 2015-2016 16.06 ± 0.005 2016 18.25 ± 0.008 2016-2017 15.03 ± 0.003 2017 18.37 ± 0.010

Figure 2. Average number of fish eggs collected by month is shown for six species from 2012- 2017.

Figure 3. Non-metric multidimensional scaling from abundance of fish species averaged per month normalized to number of eggs collected from 2012-2017. Based on Bray-Curtis dissimilarity. Stress value of 0.10 indicates the plot gives an adequate representation of the data.

Figure 4. Non-metric multidimensional scaling from abundance of fish species normalized to number of eggs identified between two sampling sites from February 2017 to August 2017. Based on Bray-Curtis dissimilarity. Stress value 0.166 indicates plot gives an adequate representation of data.

Figure 5. Average sea surface temperature at the Scripps Pier on collection days from 2012- 2017. Average depicted is a moving average over three week period over lapping by one week.

Figure 6. Log transformed mean fish eggs collected over one month plotted against cumulative upwelling indices totaled over one month period from August of 2012 to October of 2017. (R 2= 0.33, p<0.001).

Figure 7. Average spring and summer (March-August) fish egg abundance per collection plotted against spring cumulative upwelling index. Significant positive relationship between spring upwelling and spring summer fish egg abundance (R2= 0.75, p<0.05).

Figure 8. Spring and summer (March-August) average fish egg abundance plotted against previous average winter temperature (December -February) for each year. Significant negative correlation between winter temperatures and spring-summer spawning (R2=0.83, p<0.05,).

19 Discussion

In this study we observed the spawning activity of fishes in or nearby San Diego’s marine protected areas to elucidate spatial differences in spawning activity across habitat types, and temporal differences in abundance and community composition of fish eggs. In the San Diego-

Scripps Reserve we observed significant declines in the number of average fish eggs collected in the summer months of 2015 and 2016 compared to baseline spawning data from 2013 and 2014.

The depressed spawning activity observed in 2015-2016 could be the result of changes in upwelling regimes, which could result in changes in bottom up processes impacting ecosystem productivity. In 2014, an anomalously warm water region, termed “The Warm Blob”, formed in the Gulf of Alaska and subsequently extended down the eastern Pacific coastline, accounting for

1-5 ºC higher than average SST that continued to persist until May of 2015 (Bond et al., 2015;

Kintisch, 2015; Zaba & Rudnick, 2016). The following year was an El Niño year and the winter of 2015-2016 experienced above average SST characteristic of El Niño events in the California current (Jacox et al., 2016). We similarly observed a 1-2 ºC increase in annual average temperature during these years (2014-2016) than compared to previous years (2013-2014) and the following year (2017; Table 3). These positive temperature anomalies increased vertical stratification and downwelling, which deepened the thermocline and nutricline (Jacox et al.,

2016; Zaba & Rudnick, 2016). Deepening of the nutricline limits fluxes of nutrient-rich deep water to the surface and decreases phytoplankton biomass (Cullen, 2015; Kahru & Mitchell,

2000; Zaba & Rudnick, 2016). These decreases in primary production would have negative consequences in terms of food availability for higher trophic levels, including fish. Decreased food availability or food quality can negatively impact growth rates, survivorship and reproduction, and could potentially decrease spawning activity the following spawning season

20 (Ruttenberg, Haupt, Chiriboga, & Warner, 2005). Additionally, during this time there were mass strandings of tuna crabs and starvation of sea lion pups that could indicate the far-reaching effects of decreased primary productivity (Zaba & Rudnick, 2016). Because sea lion pups feed on fish among other things, starvation of pups could indicate deceased fish biomass (Mcclatchie et al., 2016). Though we cannot definitively confirm that these temperature anomalies resulted in changes in primary productivity that significantly affected spawning activity, it is likely that fish populations felt effects similar to other organisms.

Decreased fish spawning could be directly related to physiological effects of increased temperature during 2014 and 2015. Changes in temperature can alter reproductive endocrine homeostasis, gametogenesis, and rates of gonadal development (Genner et al. 2010; Pankhurst and Munday 2011). Inhibition of reproduction at higher temperatures has been shown in a range of species. For example, laboratory studies have shown that both rainbow trout and Atlantic salmon held at higher temperatures had lower incidence of ovulation or failed to ovulate

(Pankhurst and Van Der Kraak 2000; Taranger and Hansen 1993). Ruttenburg et al. (2005) observed that white-tailed damselfish egg production declined at higher temperatures in the

Galapagos. These studies demonstrate that species are likely to show similar responses to increases in temperature however temperature thresholds will vary between species (citation).

The species of fish in our study are temperate species that have a wide range of thermal tolerances and have varying geographic distributions (Hastings et al., 2014). Species-specific analysis of the five most common species showed that species did not respond to temperature increases in the same way (Fig 2). It would be unlikely for increased temperature during warm years to affect all species uniformly, however there could be a range of responses including

21 altered spawning season, depressed spawning, or reproductive failure (Munday, Jones, Pratchett,

& Williams, 2008).

A third potential mechanism that could explain decreased fish egg abundance during

2015-2016 could be offshore spawning. If fish species moved offshore during this period to spawn, fish eggs may not be captured at our sampling site. This would be an equally interesting result because it would indicate behavior modification in response to changes in environmental conditions.

During 2017, we observed peak spawning and highest species richness approximately one month later than in previous years. This pattern for species richness was driven by delayed spawning in a relatively small number of fish species (four), as for most species spawning season remained unchanged, although the height of spawning was shifted to later in the year. For only a few species spawning started and ended approximately one month later. Surprisingly, relatively few studies have investigated how environmental variability can influence phenology in marine organisms (Genner et al., 2010). It has been shown that warmer temperatures are associated with delayed spawning in flounder ( Platichthys flesus ) and earlier spawning in capelin (Mallotus villosus ) and pacific herring (Clupea harengus pallasi ) (Carscadden, Nakashima, and Frank

1997; Sims et al. 2004; Ware and Tanasichuk 1989). In contrast, our data show that there was no change of seasonal spawning during warm years; however, peak spawning was shifted one month later during a cooler year (2017). Our results imply that climate fluctuations such as El

Ni ño can alter phenology of fish spawning in following years. If such changes in spawning phenology are asynchronous with larval food resources, there can be negative consequences for survivorship and recruitment (Cushing, 1990). These results highlight the importance of

22 understanding phenology of marine organisms in order to predict marine population dynamics and manage populations.

We found there was a significant positive relationship between cumulative upwelling index and average fish eggs by month. This is likely driven by seasonal upwelling in the

California current, occurring during the spring and summer that coincides with seasonal spawning activity (Robinette, Howar, Sydeman, & Nur, 2007). We found a significant positive relationship between spring upwelling and spring-summer fish egg abundance for each year, though additional sampling years could improve our ability to test this relationship. Similar to our study, Robinette et al. (2007) found that more persistent spring upwelling led to increased larval abundance in central California. We found a significant negative correlation between winter temperatures and spring and summer spawning for each year. Genner et al . (2010) found that cooler November and December temperatures were associated with fish spawning earlier in spring, and suggested that changes in temperature could lead to changes in developmental rate of gonads. Should temperature alter rates of gonadal development, we can infer this could alter energy available for egg production and lead to variability in fish egg abundance across years.

While five years of data require substantial sampling efforts, many additional years of data are needed to determine how inter-annual environmental variability affects fish spawning. If the patterns, we observe here are maintained across years, winter temperatures could be used to predict spring and summer spawning, which would have important applications in fisheries management.

In this study we document large inter-annual variability in fish egg abundance that is associated with large climatic fluctuations, including an El Niño event captured during our sampling years. Decreased abundance of fish eggs during anomalously warmer years was likely

23 due to changes in primary productivity, physiological effects of increased temperature on fish species or behavioral avoidance or a combination of these mechanisms. Furthermore, we document a phenological shift of peak fish egg abundance approximately one month later in the most recent cooler year. Lastly, we found annual fish egg abundance was negatively correlated with winter temperatures and positively correlated with annual spring upwelling. These results underscore the importance of understanding how natural environmental variation such as changes in temperature affect marine fish populations and these data will help us understand how temperature increases associated with climate change will impact populations and communities.

Temperature-mediated effects will likely depend on a variety of factors including physiological tolerances, behavioral response, dispersal capability, and capacity for adaption (Pankhurst and

Munday 2011). In order to predict population persistence, future research should target each of these areas. Future studies could include direct measurements of the effects of temperature on phenology of fish spawning and reproductive development. In order to confirm that changes in primary productivity caused decreased spawning, data are needed about larval food resources and larval survivorship. Sampling of fish eggs should continue in future years in order to further understand how environmental factors such as temperature and upwelling regimes affect annual spawning, and to assess the extent to which the patterns observed in the current study can be generalized through time. Long-term monitoring of reserves is critical to understanding how global processes such as natural environmental variation and climate change will affect marine populations. Marine protected areas are an important resource that can provide data regarding human impacts on the ocean while protecting exploited species, enhancing biodiversity and protecting whole ecosystems. Thus, assessments of abundance spawning activity within marine

24 protected areas, such as this study, are essential for assessing marine protected area efficacy

(Harada et al. 2015).

25 References

Agardy, T. (2000). Information needs for marine protected areas: scientific and societal. Bulletin of Marine Science , 66 (3), 875–888.

Airamé, S., Dugan, J. E., Lafferty, K. D., Leslie, H., Deborah, A., Mcardle, D. A., & Warner, R. R. (2003). Applying Ecological Criteria to Marine Reserve Design : A Case Study from the California Channel Islands McArdle and Robert R . Warner Source : Ecological Applications , Vol . 13 , No . 1 , Supplement : The Science of Marine Reserves Published by : Wiley. Ecological Applications , 13 (1), S170–S184. http://doi.org/10.2307/3100006

Allison, G. W., Gaines, S. D., Lubchenco, J., & Possingham, H. P. (2003). Ensuring persistence of marine reserves: Catastrophes require adopting an insurance factor. Ecological Applications , 13 (1 SUPPL.), 8–24. http://doi.org/10.1890/1051- 0761(2003)013[0008:EPOMRC]2.0.CO;2

Allison, G. W., Lubchenco, J., & Carr, M. H. (1998). Marine reserves are necessary but not sufficient for marine conservation. Ecological Applications , 8(1), S79–S92. http://doi.org/10.1890/1051-0761(1998)8[S79:MRANBN]2.0.CO;2

Alstrom, E. H., & Moser, H. G. (1976). Eggs and larvae of fishes and their role in systematic investigations in fisheries. Revue Des Travaux de l’Institut Des Pêches Maritimes , 40 (3–4), 379–398. Retrieved from http://archimer.ifremer.fr/doc/00000/1996/

Avasthi, A. (2005). California Tries to Connect Its Scattered Marine Reserves. Science , 308 (5721), 487 LP-488. Retrieved from http://science.sciencemag.org/content/308/5721/487.abstract

Balmford, A., Gravestock, P., Hockley, N., McClean, C. J., & Roberts, C. M. (2004). The worldwide costs of marine protected areas. Proceedings of the National Academy of Sciences , 101 (26), 9694–9697. http://doi.org/10.1073/pnas.0403239101

Bond, N. A., Cronin, M. F., Freeland, H., & Mantua, N. (2015). Causes and impacts of the 2014 warm anomaly in the NE Pacific. Geophysical Research Letters , 42 (9), 3414–3420. http://doi.org/10.1002/2015GL063306

Burgess, S. ., Nickols, K. ., Griesemer, C., Barnett, L. A. ., Dedrick, A. ., Satterthwaite, E. ., … Bostford, L. . (2014). Beyond connectivity : how empirical methods can quantify population persistence to improve marine protected area design: supplementary Information. Ecological Society of America , 24 (2), 8. http://doi.org/10.1890/13-0710.1

Carscadden, J., Nakashima, B. S., & Frank, K. T. (1997). Effects of fish length and temperature on the timing of peak spawning in capelin (Mallotus villosus). Canadian Journal of Fisheries and Aquatic Sciences , 54 (4), 781–787. http://doi.org/10.1139/cjfas-54-4-781

Cullen, J. J. (2015). Subsurface Chlorophyll Maximum Layers: Enduring Enigma or Mystery

26 Solved? Annual Review of Marine Science , 7(1), 207–239. http://doi.org/10.1146/annurev- marine-010213-135111

Cushing, D. H. (1990). Plankton production and year-class strength in fish populations: An update of the match/mismatch hypothesis. Advances in Marine Biology , 26 (C), 249–293. http://doi.org/10.1016/S0065-2881(08)60202-3

Fox, C. J., O’Brien, C. M., Dickey-Collas, M., & Nash, R. D. M. (2000). Patterns in the spawning of cod ( Gadus morhua L.), sole ( Solea solea L.) and plaice ( Pleuronectes platessa L.) in the Irish Sea as determined by generalized additive modelling. Fisheries Oceanography , 9(1), 33–49. http://doi.org/10.1046/j.1365-2419.2000.00120.x

Genner, M. J., Halliday, N. C., Simpson, S. D., Southward, A. J., Hawkins, S. J., & Sims, D. W. (2010). Temperature-driven phenological changes within a marine larval fish assemblage. Journal of Plankton Research , 32 (5), 699–708. http://doi.org/10.1093/plankt/fbp082

Gleason, L. U., & Burton, R. S. (2012). High-throughput molecular identification of fish eggs using multiplex suspension bead arrays. Molecular Ecology Resources , 12 (1), 57–66. http://doi.org/10.1111/j.1755-0998.2011.03059.x

Green-Ruiz, Y. A., & Hinojosa-Corona, A. (1997). Study of the spawning area of the Northern anchovy in the Gulf of California from 1990 to 1994, using satellite images of sea surface temperatures. Journal of Plankton Research , 19 (8), 957–968. http://doi.org/10.1093/plankt/19.8.957

Harada, A. E., Lindgren, E. A., Hermsmeier, M. C., Rogowski, P. A., Terrill, E., Burton, R. S., & Bernardi, G. (2015). Monitoring spawning activity in a Southern California marine protected area using molecular identification of fish eggs. PLoS ONE , 10 (8), 1–21. http://doi.org/10.1371/journal.pone.0134647

Hastings, P. A., & Burton, R. S. (2008). Establishing a DNA Sequence Database for the Marine Fish Fauna of California . Retrieved from https://escholarship.org/uc/item/1ck9b3qs

Hastings, P. A., Craig, M. T., & Hyde, J. R. (2014). Fishes of Marine Protected Areas Near La Jolla , California Fishes of Marine Protected Areas Near La Jolla , California. Southern California Academy of Sciences , 113 (3), 200–231.

Hyde, J. R., Lynn, E., Humphreys, R., Musyl, M., West, A. P., & Vetter, R. (2005). Shipboard identification of fish eggs and larvae by multiplex PCR, and description of fertilized eggs of blue marlin, shortbill spearfish, and wahoo. Marine Ecology Progress Series , 286 , 269–277. http://doi.org/10.3354/meps286269

Jacox, M. G., Hazen, E. L., Zaba, K. D., Rudnick, D. L., Edwards, C. A., Moore, A. M., & Bograd, S. J. (2016). Impacts of the 2015–2016 El Niño on the California Current System: Early assessment and comparison to past events. Geophysical Research Letters , 43 (13), 7072–7080. http://doi.org/10.1002/2016GL069716

27 Jones, J. S. (2002). Marine protected area strategies : issues, divergence and the search for middle ground. Rev. Fish Biol. Fisheries , 11 , 197–216. http://doi.org/10.1023/A:1020327007975

Kahru, M., & Mitchell, B. G. (2000). Influence of the 1997â•ﬁ98 El NiÃ±o on the surface chlorophyll in the California Current, 27 (18), 2937–2940.

Kintisch, E. (2015). Marine science. “The Blob” invades Pacific, flummoxing climate experts. Science (New York, N.Y.) , 348 (6230), 17–18. http://doi.org/10.1126/science.348.6230.17

Mcclatchie, S., Field, J., Thompson, A. R., Gerrodette, T., Lowry, M., Fiedler, P. C., … Vetter, R. D. (2016). Food limitation of sea lion pups and the decline of forage off central and southern California. Royal Society Open Science , 3, 150628. http://doi.org/10.1098/rsos.150628

McLeod, E., Salm, R., Green, A., & Almany, J. (2009). Designing marine protected area networks to address the impacts of climate change. Frontiers in Ecology and the Environment , 7(7), 362–370. http://doi.org/10.1890/070211

Munday, P. L., Jones, G. P., Pratchett, M. S., & Williams, A. J. (2008). Climate change and the future for coral reef fishes. Fish and Fisheries , 9(3), 261–285. http://doi.org/10.1111/j.1467-2979.2008.00281.x

Pankhurst, N. W., & Munday, P. L. (2011). Effects of climate change on fish reproduction and early life history stages. Marine and Freshwater Research , 62 (9), 1015–1026. http://doi.org/10.1071/MF10269

Pankhurst, N. W., & Van Der Kraak, G. (2000). Evidence that acute stress inhibits ovarian steroidogenesis in rainbow trout in vivo, through the action of cortisol. General and Comparative Endocrinology , 117 (2), 225–237. http://doi.org/10.1006/gcen.1999.7401

Parnell, P. E., Dayton, P. K., Lennert-cody, C. E., Rasmussen, L. L., & Leichter, J. J. (2006). Marine Reserve Design : Optimal Size , Habitats , Species Affinities , Diversity , and Ocean Microclimate MARINE RESERVE DESIGN : OPTIMAL SIZE , HABITATS , SPECIES AFFINITIES , DIVERSITY , AND OCEAN MICROCLIMATE, 16 (3), 945–962.

Pauly, D., & Pullin, R. S. V. (1988). Hatching time in spherical, pelagic, marine fish eggs in response to temperature and egg size. Environmental Biology of Fishes , 22 (4), 261–271. http://doi.org/10.1007/BF00004892

Perry, A. L., Low, P. J., Ellis, J. R. (2005). Climate change and distribution shifts in marine fishes. Science (New York, N.Y.) , 308 (5730), 1912–5. http://doi.org/10.1126/science.1111322

Robinette, D. P., Howar, J., Sydeman, W. J., & Nur, N. (2007). Spatial patterns of recruitment in a demersal fish as revealed by seabird diet. Marine Ecology Progress Series , 352 , 259–268.

28 http://doi.org/10.3354/meps07079

Ruttenberg, B. I., Haupt, A. J., Chiriboga, A. I., & Warner, R. R. (2005). Patterns, causes and consequences of regional variation in the ecology and life history of a reef fish. Oecologia , 145 (3), 394–403. http://doi.org/10.1007/s00442-005-0150-0

Sala, E., Aburto-oropeza, O., Paredes, G., Parra, I., Barrera, J. C., & Dayton, P. K. (2002). REPORTS A General Model for Designing Networks of Marine Reserves. Science , 298 (December), 1991–1993. http://doi.org/10.1126/science.1075284

Sims, D., Wearmouth, V., Genner, M., Southward, A., & Hawkins, S. (2004). Low-temperature driven early spawning migration of a marine temperate fish. Journal of Animal Ecology , 73 (333–341), 333–341.

Taranger, G., & Hansen, T. (1993). Ovulation and egg survival following exposure of Atlantic salmon, Salmo salar L., broodstock to different water temperatures. Aquaculture Research , 24 (2), 151–156. http://doi.org/10.1111/j.1365-2109.1993.tb00535.x

Ward, R. D., Zemlak, T. S., Innes, B. H., Last, P. R., & Hebert, P. D. N. (2005). DNA barcoding Australia’s fish species. Philosophical Transactions of the Royal Society B: Biological Sciences , 360 (1462), 1847–1857. http://doi.org/10.1098/rstb.2005.1716

Ware, D M, Tanasichuk, R. W. (1989). Basis of Maturation and Spawning Waves in Pacific (Clupea harengus pallasi). Canadian Journal of Fisheries and Aquatic Sciences , 46 .

Zaba, K. D., & Rudnick, D. L. (2016). The 2014-2015 warming anomaly in the Southern California Current System observed by underwater gliders. Geophysical Research Letters , 43 (3), 1241–1248. http://doi.org/10.1002/2015GL067550