Biophysical and Stable Isotopic Profiles of the Salmon Louse Lepeophtheirus Salmonis (Krøyer, 1837)

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Biophysical and stable isotopic profiles of the salmon louse Lepeophtheirus salmonis (Krøyer, 1837)

Emma Taccardi University of Maine, [email protected]

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Recommended Citation Taccardi, Emma, "Biophysical and stable isotopic profiles of the salmon louse Lepeophtheirus salmonis (Krøyer, 1837)" (2020). Electronic Theses and Dissertations. 3265. https://digitalcommons.library.umaine.edu/etd/3265

This Open-Access Thesis is brought to you for free and open access by DigitalCommons@UMaine. It has been accepted for inclusion in Electronic Theses and Dissertations by an authorized administrator of DigitalCommons@UMaine. For more information, please contact [email protected]. BIOPHYSICAL AND STABLE ISOTOPIC PROFILES OF THE SALMON LOUSE

LEPEOPHTHEIRUS SALMONIS (KRØYER, 1837)

Emma Y. Taccardi

B.A. Hamilton College, 2014

A DISSERTATION

Submitted in Partial Fulfillment of the

Requirements for the Degree of

Doctor of Philosophy

(in Marine Biology)

The Graduate School

The University of Maine

August 2020

Advisory Committee:

Ian Bricknell, Professor of Aquaculture, University of Maine, Advisor

Damian Brady, Associate Professor of Marine Sciences, University of Maine

Carrie Byron, Assistant Professor of Marine Programs, University of New England

Heather Hamlin, Associate Professor of Aquaculture, University of Maine

Gayle Zydlewski, Professor of Marine Sciences, University of Maine

Ó 2020 Emma Taccardi

BIOPHYSICAL AND STABLE ISOTOPIC PROFILES OF THE SALMON LOUSE

LEPEOPHTHEIRUS SALMONIS (KRØYER, 1837)

By Emma Y. Taccardi

Dissertation Advisor: Dr. Ian Bricknell

An Abstract of the Dissertation Presented

in Partial Fulfillment of the Requirements for the

Degree of Doctor of Philosophy

(in Marine Biology)

August 2020

The salmon louse Lepeophtheirus salmonis is a parasitic copepod that infects wild and farmed salmonids throughout the northern hemisphere. L. salmonis represents the largest economic hurdle of the Atlantic salmon (Salmo salar) industry, with an estimated annual cost of nearly $1 billion globally due to production losses and anti-parasitic control measures. Salmon farming in Maine has existed for decades and is a critical economic driver, yet the region is underrepresented in global sea lice research. The aim of this work was to examine parasites in the context of animal trophic transfer and characterize physiological condition by quantifying the flow of stable isotopes and seasonal energy reserves in sea lice, respectively.

A meta-analysis of fish host-parasite stable isotopes was conducted, as well as stable isotope analysis in a case study of farmed and wild S. salar in Maine and their respective parasites, L. salmonis and Argulus foliaceus. Across the literature, endoparasites were depleted in d15N relative to their hosts, ectoparasites demonstrated a range of d15N enrichment patterns, and

d13C enrichment varied extensively across taxa. L. salmonis and A. foliaceus demonstrated contrasting d15N and d13C enrichment patterns relative to their hosts, and none were in agreement with current animal standards. Results suggest that parasites do not conform to traditional predator-prey standards, and that, even among closely related ectoparasites, there does not appear to be a universal enrichment pathway.

To quantify lipid and thermal energy reserves in sea lice embryos, histology and differential scanning calorimetry were respectively employed. Both reserve types exhibited seasonal patterns, with peak lipid quantities in the spring and lower levels in colder seasons, and the highest thermal energy content (via specific heat capacity, Cp) in the summer. Daily changes in Cp varied between months, although values generally declined between initial and final sampling days. Collectively, maximal lipid reserves and energy content aligned with the beginning of typically observed annual infection surges on farms and optimal conditions for L. salmonis development. With the earliest opportunity for population forecasting at the understudied embryo stage, these indicators of condition may contribute to more accurate infection models that inform pest management.

DEDICATION

For my parents, who have tolerated my question-asking from the very beginning and have supported my endeavors ever since.

iii

ACKNOWLEDGEMENTS

I would like to thank my advisor, Ian, for supporting my curiosity at every junction throughout this exciting journey; thank you for discussing science with me over all of that coffee and encouraging my growth. I would also like to extend a huge thank you to the rest of my committee. Carrie, for your professional and personal mentorship, and a wonderful inter- university collaboration. Heather, for your infectious enthusiasm and optimism, and your thoughtful guidance throughout my shifts in research. Gayle, for your wide-ranging professional insight and your realism that was equal parts supportive and necessary. Damian, for always discussing the bigger picture and sharing effective tips that I will keep in my pocket.

Thank you to the many undergraduate and high school students who assisted me in labs at UMaine and UNE. Thank you to all of our partners at Cooke Aquaculture for their immense generosity with time and resources in the field. In addition, many thanks go out to Debbie

Bouchard, Scarlett Tudor, and the rest of UMaine Cooperative Extension, as well as Mike

Pietrak (USDA), for facilitating year-round fieldwork and connecting us to industry partners.

I would like to say thank you to Bobby Harrington and Neil Greenberg, as well as the rest of the ARC team, for all of your support, resources, and time over the years. Thank you to Justin

Crouse and the Advanced Structures and Composites Center for warmly welcoming a rogue sea lice researcher into the nano lab—I appreciate your time, generous guidance, and very enjoyable collaboration. Additionally, I would like to thank Joe Zydlewski (USGS), Ron Johnson (NOAA), and Denise Buckley (USFWS) for their exciting contributions to my stable isotope research, and

Dawna Beane for her support with histology methods.

I would like to acknowledge the National Science Foundation for funding my research through the Sustainable Ecological Aquaculture Network [#IIA-1355457] to Maine EPSCoR at

the University of Maine. I am extending a big thank you to the EPSCoR and SEANET teams, as well as the School of Marine Sciences, for the brilliant friends and colleagues with whom I will remain in touch. Thank you very much to Kristina Cammen for giving me the opportunity to teach (and learn), and to the rest of the SMS 203 teaching team and students for brightening my final semester.

Thank you to my mentors and colleagues at Hamilton College, Duke University Marine

Laboratory, The Nature Conservancy, and Lawrence Berkeley National Laboratory for fostering my growth leading up to the beginning of my graduate career. I continue to look back as I look forward.

Last but not least, thank you to my family and friends for always believing in me throughout this wild ride. Your support, nearby and from afar, has lifted me up.

TABLE OF CONTENTS

DEDICATION ...... iii

ACKNOWLEDGEMENTS ...... iv

LIST OF TABLES ...... x

LIST OF FIGURES ...... xi

Chapter

1. INTRODUCTION TO SEA LICE ...... 1

1.1. Overview ...... 1

1.2. Salmon louse biology and ecology ...... 4

1.2.1. Life cycle ...... 4

1.2.2. Pathogenic effects on host ...... 6

1.2.3. Reproductive biology and maternal investment ...... 7

1.2.4. Parasites (or lack thereof) in food webs ...... 11

1.3. Objectives ...... 13

2. STABLE ISOTOPES REVEAL CONTRASTING TROPHIC DYNAMICS BETWEEN

HOST-PARASITE RELATIONSHIPS: A CASE STUDY OF ATLANTIC SALMON AND

PARASITIC LICE ...... 15

2.1. Introduction ...... 15

2.2. Materials and methods ...... 18

2.2.1. Literature review ...... 18

2.2.2. Study sites ...... 18

2.2.3. Parasite collections ...... 19

2.2.4. Salmon tissue collections ...... 21

2.2.5. Stable isotope analysis ...... 22

2.2.6. Statistical analysis ...... 22

2.3. Results ...... 24

2.3.1. Host-parasite literature ...... 24

2.3.1.1. Enrichment across taxa ...... 24

2.3.1.2. Enrichment across tissues ...... 25

2.3.2. Enrichment in case study ...... 26

2.3.3. Farmed and wild salmon tissue ...... 26

2.3.4. Parasite comparisons ...... 28

2.3.4.1. Assessments within cohorts ...... 28

2.3.4.2. Parasites from farmed and wild S. salar ...... 29

2.3.4.3. Geographically distinct L. salmonis ...... 30

2.4. Discussion ...... 31

3. SEASONAL PROGRESSION OF EMBRYO SIZE, LIPID RESERVES, AND THERMAL

ENERGY IN SEA LICE (LEPEOPHTHEIRUS SALMONIS) COLLECTED FROM SALMON

FARMS ...... 35

3.1. Introduction ...... 35

3.2. Materials and methods ...... 40

3.2.1. Sea lice collection ...... 40

vii

3.2.2. Histology ...... 41

3.2.3. Lipid quantification ...... 42

3.2.3.1. Embryo and lipid standards ...... 42

3.2.3.2. Image processing ...... 42

3.2.4. Daily thermal energy sampling ...... 44

3.2.5. Calorimetry ...... 45

3.2.6. Dual reserves ...... 46

3.3. Results ...... 46

3.3.1. Embryo size ...... 46

3.3.2. Number of lipid droplets ...... 46

3.3.3. Lipid area ...... 47

3.3.4. Monthly and seasonal thermal energy ...... 49

3.3.5. Daily thermal energy ...... 50

3.3.6. Dual reserves ...... 52

3.4. Discussion ...... 53

3.4.1. Lipid droplet profiles ...... 53

3.4.2. Thermal energy profiles ...... 56

3.4.3. Concluding remarks: dual reserves ...... 58

4. CHARACTERIZING THREE PROFILES ...... 61

4.1. Discussion and future work ...... 61

viii

REFERENCES ...... 70

BIOGRAPHY OF THE AUTHOR ...... 84

LIST OF TABLES

Table 2.1. Sources of compiled enrichment data...... 20

Table 2.2. Sample sizes and isotopic grand means (+ SD) of farmed and wild Salmo salar,

Lepeophtheirus salmonis, and Argulus foliaceus...... 23

Table 2.3 d15N and d13C enrichment of Lepeophtheirus salmonis and Argulus foliaceus in

relation to farmed and wild Salmo salar tissue...... 29

Table 2.4. P-values of one-way ANOVAs (Tukey’s multiple comparisons) for Salmo salar,

Atlantic and Pacific Lepeophtheirus salmonis, Argulus foliaceus...... 30

Table 3.1. Date, site information, and mean measurements (+ SE) from

fertilized eggs of sea lice collected from commercial Atlantic salmon...... 43

Table 3.2. Sample sizes and mean heat capacities (+ SE) for monthly collections

in 2019...... 43

Table 3.3. Results from Wilcoxon comparisons of monthly heat capacities...... 51

LIST OF FIGURES

Figure 1.1. Atlantic salmon (Salmo salar) net pens in Jonesport, ME...... 3

Figure 1.2. Map of study area (NOAA National Centers for Environmental Information,

2019)...... 4

Figure 1.3. Life cycle of Lepeophtheirus salmonis, modified by Hamre et al. (2013)...... 5

Figure 1.4. Individual sea louse embryo comprised of several lipid droplets...... 8

Figure 2.1. Sampling sites on eastern and western coasts of the US...... 21

Figure 2.2. d15N and d13C enrichment of parasites relative to hosts from compiled

references (Table 2.1)...... 25

Figure 2.3. d15N and d13C enrichment across tissues of a. ectoparasites and b. endoparasites

from compiled references (Table 2.1)...... 27

Figure 2.4. Isotopic signals of Salmo salar, Lepeophtheirus salmonis, and Argulus

foliaceus...... 28

Figure 2.5. Isotopic signals of Argulus foliaceus and Atlantic and Pacific Lepeophtheirus

salmonis...... 31

Figure 3.1. Site map; red circles indicate collection points in Eastport (Cobscook Bay) and

Machiasport (Machias Bay), Maine...... 41

Figure 3.2. Mean length (µm) of L. salmonis embryos...... 47

Figure 3.3. Histological sections of sea lice eggs from a. May 2019 and b. November

2019...... 48

Figure 3.4. Mean lipid area (µm2) of sea lice embryos...... 49

Figure 3.5. Heat capacities (J/g°C) of sea lice embryos collected from 2019...... 50

Figure 3.6. Heat capacities (J/g°C) of embryos sampled daily from collections in

a. Summer: July and August, and b. Fall: October and November...... 52

Figure 3.7. Regressions of egg and lipid metrics and heat capacity (J/g°C) of paired

embryos sampled in July 2019...... 53

xii

CHAPTER 1

INTRODUCTION TO SEA LICE

1.1. Overview

The salmon louse Lepeophtheirus salmonis (Krøyer, 1837) is a marine parasite that infects populations of farmed and wild salmon throughout the northern hemisphere. Among other parasitic copepods, L. salmonis is the most widely investigated, due to its detrimental effects on host populations and its subsequent economic impact on the salmon industry (Costello,

2006; Wagner et al., 2007). Atlantic salmon (Salmo salar L.) are a culturally and economically important species in Maine and many coastal communities throughout the world. Capture fisheries are in heavy decline globally, and are non-existent in many cases due overfishing, destruction of spawning grounds, injury and predation imposed by dams, and pollution of the aquatic environment (Ruggles, 1980; Parrish et al., 1998; Guo and Woo, 2009; Holbrook et al.,

2011; Chaput et al., 2012; Susdorf et al., 2018). Conversely, salmon aquaculture has the potential to meet steadily growing animal protein demands, as its growth rate exceeds that of the global human population (Jansen et al., 2012). Salmon farming has become commonplace along cold temperate coasts (Dempster et al., 2009), with global production exceeding 2.3 million tons of fish per year (FAO, 2016).

In recent decades, however, the expansion of commercial aquaculture has consequently fostered the parallel growth of a variety of marine pathogens (Murray and Peeler, 2005).

Persistent, high-intensity, and biologically complex sea lice infections remain the greatest health threat and economic constraint of salmon aquaculture (Guo and Woo, 2009). The current global

cost due to sea lice is nearly $1 billion annually, and is primarily a result of production losses and expensive anti-parasitic treatments (Torrissen et al., 2013; Igboeli et al., 2014; Abolofia and

Wilen, 2017; Brooker et al., 2018). Given this threat to the sustainability of Atlantic salmon aquaculture, the industry continues to innovate by assimilating a wide range of research efforts.

Over the past five years, salmon aquaculturists in Maine have shifted away from their reliance on anti-parasitic chemical treatments. While these treatments were effective in the short term, they ultimately led to the development of resistance with succeeding generations of sea lice (Aaen et al., 2015; Jansen et al., 2016). Therefore, the industry continuously implements integrated pest management, which utilizes a diverse palette of control measures that include: physical barriers to infection (Stien et al., 2016; Wright et al., 2017; Grøntvedt et al., 2018), biological controls via cleaner fish (Skiftesvik et al., 2013; Imsland et al., 2014), freshwater treatments (Wagner et al, 2004), and mathematical models that predict infection timing and severity (Johnsen et al.,

2014; Rittenhouse et al., 2016; Salama et al., 2016; Sandvik et al., 2016; Samsing et al., 2017).

The state of Maine is a top-ranking national seafood supplier with an impressive reputation for high-quality and sustainably grown food products (Cole et al., 2017). Among all farmed species in the state, Atlantic salmon generate the highest sales (Gabe and McConnon,

2016; Cole et al., 2017; Stoll et al., 2019). The majority of net-pen aquaculture (Figure 1.1) sites in Maine are in Washington County, the northernmost coastal region of the state (Figure 1.2).

The location of this key economic driver is crucial, as Washington County is one of the poorest in the state and in the New England region, with approximately 18% of individuals living in poverty (United States Census Bureau, 2018).

Figure 1.1. Atlantic salmon (Salmo salar) net pens in Jonesport, ME.

Sea lice infection dynamics between farmed and wild salmonids comprise a controversial

“black box” that is difficult to assess. Consistently high host densities of farmed fish are often implicated in the decline of wild salmonids, although the extent of the effect is widely debated

(Costello, 2009; Kristoffersen et al., 2014; Skilbrei et al., 2013; Vollset et al., 2011) and there is a common failure to acknowledge that correlation between datasets does not necessarily signify a cause-and-effect relationship (McVicar, 2004; Torrissen et al., 2013). Thus, transmission dynamics heighten the pressing need to understand L. salmonis ecology and its physiological underpinning.

US CANADA

45°N Cobscook Bay Bay of Fundy

Machias Bay Grand Manan Island

Gulf of Maine Figure 1.2. Map of study area (NOAA National Centers for Environmental Information, 2019).

1.2. Salmon louse biology and ecology

1.2.1. Life cycle

Salmon lice have reportedly been abundant since the mid-1700s (Torrissen et al., 2013), yet the overall life cycle of the species (Figure 1.3) was not accurately uncovered until 2013

(Hamre et al., 2013). L. salmonis has a direct life cycle (i.e. requires one host species) and consists of eight phases that are each separated by a molt (Hamre et al., 2013; Svandlund et al.,

2018). Gravid female L. salmonis extrude paired egg strings that hatch into planktonic, non- feeding nauplius larvae. After molting through nauplius I and II phases, infective copepodid larvae must locate and attach to a suitable host using their frontal filaments. Research suggests that copepodids use a variety of sensory abilities to locate their hosts, primarily in response to light, mechanical vibration, and host-derived chemicals (Devine et al., 2000; Flamarique et al.,

2000; Hevrøy et al., 2003; Bailey et al., 2006; Mordue and Birkett, 2009). After attachment,

Figure 1.3. Life cycle of Lepeophtheirus salmonis, modified by Hamre et al. (2013). Image courtesy of Olivia Joyce (2018).

copepodids develop into immobile chalimus I and II stages before maturing through the mobile preadult and adult phases, which are sexually dimorphic and capable of host-hopping to maximize resource quality (Costello, 2006; Wagner et al., 2007; Hamre et al., 2009).

Development times and survival rates across L. salmonis life stages are strongly influenced by temperature. Time to hatching incrementally varies from 8 days to 45 days at temperatures that range from 2 – 10°C (Boxaspen and Næss, 2000). Johnson and Albright (1991) documented that, in the Pacific, the first naupliar stage lasted 52 hours, 30 hours, and 9 hours at

5°C, 10°C, and 15°C, respectively. At the same temperatures, corresponding nauplius II phases lasted 170 hours, 56 hours, and 35 hours (Johnson and Albright, 1991a). With shorter generation

times and higher rates of infection success in warmer waters, higher lice abundances are observed in the spring and summer (Samsing et al., 2016). For improved pest management on salmon farms, it is essential to understand the effects of winter temperatures on L. salmonis development and condition. In Norway, Boxaspen and Næss (2000) revealed that successful progression through all stages occurred between 5 and 22°C, and that copepodids were obtained from 25% of egg strings at 2°C. However, Norwegian lice in a study by Samsing et al. (2016) evidenced that larvae failed to reach the copepodid stage at 3°C. Similarly, in Canada, previous research has demonstrated that growth rates were reduced under decreasing temperatures (Jones and Johnson, 2015).

Salinity also plays a role in both development timing and settlement success, as development is faster and copepodid settlement is significantly greater at 34‰ compared to 24‰

(Tucker et al., 2000). Furthermore, L. salmonis is a stenohaline organism with compromised survival at salinities below 29‰ due to osmoregulatory disruption and nerve transmission failure

(Bricknell et al., 2006). Crosbie et al. (2019) demonstrated that nauplii are even more sensitive and strongly avoid salinities that are less than 30‰.

The vast majority of L. salmonis developmental studies encompass sea lice from Europe and western Canada, emphasizing a lack of published data from Maine and eastern Canada.

Regional analysis of sea louse development and fitness is necessary, as relationships with temperature become less straightforward at the level of the population (Jansen et al., 2012).

1.2.2. Pathogenic effects on host

Sea lice use rasping mouth structures to feed on their hosts, and primarily consume salmon mucus, blood, skin, and underlying tissue (Costello, 2009). Because L. salmonis is found on few host species, it has evolved highly sophisticated strategies to evade the physiological

defenses of its hosts, much like many other specialist parasites (Lewis et al., 2002). In high numbers and/or with prolonged attachment, particularly in the later stages of the life cycle, sea lice cause decreased growth and food conversion efficiency of their hosts, as well as osmoregulatory disruptions and increased susceptibility to secondary infections, which often lead to mortality (Bowers et al., 2000; Costello, 2006; Wagner et al., 2007; Long et al., 2019). For example, S. salar post-smolts that host approximately 0.75 – 1.0 lice/g body mass at minimum are not likely to survive their migrations, as cortisol levels rise and osmoregulatory imbalance occurs (Wagner et al., 2003). More broadly, sea lice challenge the immune system of their hosts, often by evading defenses and secreting their own products that further increase access to host resources (Fast et al., 2004; Fast et al., 2007). Sea lice additionally elicit chronic stress responses in their hosts that further suppress the salmonid immune system (Mustafa et al., 2000b; Fast et al., 2002).

1.2.3. Reproductive biology and maternal investment

Another strategy that contributes to the ecological success of L. salmonis is its high reproductive capacity in paired egg strings, each of which contains between 100 and 1000 individual embryos (Costello, 1993). Although the underlying mechanisms are largely unknown, fecundity appears to be influenced by seasonality, with particular emphasis on water temperature. Existing literature has demonstrated that sea lice embryo size and viability are lower at reduced temperatures (Ritchie et al., 1993; Heuch et al., 2000; Costello, 2006), and gravid female lice may be more fecund (Jones and Johnson, 2015). These studies reflect L. salmonis in Europe and Canada, however, and physiological strategies likely differ by geographical region.

Measures of fecundity and embryo condition are key components of the overall maternal energy budget. Embryos, nauplii, and free-living copepodids all rely on maternally derived energy reserves for sustenance (Boxaspen, 2006; Costello, 2006). Therefore, gravid females must strategically allocate sufficient energy levels toward their eggs for offspring development and attachment to hosts for the switch to active feeding. Lipid droplets are the most well-known form of these reserves, perhaps because they are the most physically tangible (Figure 1.4).

Figure 1.4. Individual sea louse embryo comprised of several lipid droplets.

Energy storage in the form of lipid accumulation is a common strategy among zooplankton. Lipid reserves play critical roles in growth and development, buoyancy, and reproduction (Lee et al., 2006; Cook et al., 2010). Given its diverse applications, lipid content is a particularly strong variable within the comprehensive energetic budget, which varies according to life stage and likely individual condition. Gravid female copepods, for example, must primarily allocate resources toward reproduction and feeding, while early-stage organisms must metabolize reserves to grow and ultimately seek additional sustenance before endogenous reserves expire.

By the 1970s, the lipid morphologies and quantities of several copepod species were described (Lee et al., 2006). Existing studies indicate that lipid levels in copepod eggs influence

both hatching success and larval survival (Pond et al., 1996; Alonzo et al., 2001). However, most of the literature continues to highlight lipid reserves in free-living species that rely on phenologically driven cycles of food availability (Everson, 1984), and very few studies have assessed lipid quantities in parasitic copepods. Thus, despite their centrality in embryonic and larval survival, the quantities of these stores in sea lice remain poorly understood. Of the limited research on lipids in sea lice, these studies either focus on lipid classification (Tocher et al.,

2010) or center around quantities in copepodids or nauplii (Tucker et al., 2000; Cook et al., 2010;

Gonçalves et al., 2014; Khan et al., 2017; Thompson et al., 2019). Previous findings demonstrate that lipid quantities in copepodids govern their longevity and viability prior to and during host infection (Tucker et al., 2000; Cook et al., 2010; Gonçalves et al., 2014; Khan et al., 2017).

These investigations have focused on the infective stage under favorable laboratory conditions, limiting applications for overall population fitness as it relates to phenology.

Endogenous reserves in embryos may be manifested in multiple forms. One fully quantitative measure of these stores is the amount of thermal energy that is contained. Thermal energy is an essential resource, as its absorption, progression, and transmission supports metabolic activity in multicellular organisms (Blise, 2009). Although natural selection broadly maximizes rates of energy absorption and use (Lotka, 1922; Ware, 1982; Billerbeck et al., 2001), these reserves entail a metabolic cost that is affected by the quantity of energy that is stored and the rate at which the stores are used (Witter and Cuthill, 1993; Griffen, 2017).

Energy content exerts a strong influence over cascading life stages as an organism develops (Harrison et al., 2011), and, in part, regulates reproduction and metamorphosis

(Manzon et al., 2015; Mendo et al., 2016). Previous assessments have concluded that energy content (of dry biomass) varies from season to season within a species (Golley, 1961; Comita

and Schindler, 1963; Snow, 1972; Salonen et al., 1976). Although existing literature has been used to draw fundamental conclusions regarding energy content in a variety of organisms, these studies have used bomb calorimetry, which provides an indirect estimation (Tucker et al., 2000) and requires a very large amount of sample, particularly when analyzing small invertebrates at early life stages (Snow, 1972; Salonen et al., 1976).

Differential scanning calorimetry is a cornerstone of modern thermodynamics that offers direct assessment of thermal energy content with high precision, accuracy, and repeatability

(Höhne et al., 2003; Harvey et al., 2018; Yu et al., 2017). In addition, DSC generally requires less than 1 g of sample per experimental trial. In a basic DSC trial, sample and reference cells experience identical temperature ramps over time. When the sample is heated, a series of endo- or exothermic processes take place within, creating a temperature differential between sample and reference cells. The control system of the calorimeter accordingly administers more or less heat into the sample to maintain equal temperatures between the two cells, resulting in a thermogram of heat flow as a function of temperature/time (Cañadas and Casals, 2013).

Furthermore, these differences may be observed as fluctuations in specific heat capacity (Cp)

(Miles et al., 1986) that are derived from heat flow using the following formula:

Cp = ΔQ m ΔT where Q = heat flow, m = mass, and T = temperature of the sample.

The output from DSC gleans insight regarding the thermal stability of sample material, as well as degradation and other measures of thermal damage (Gauza-Włodarcyzk et al., 2017).

While data collection is routine and simple, interpretation of thermodynamic results currently has the potential for improvement, as commercially applied software does not articulate the behaviors of varying biological systems (Prislan et al., 2019). However, with growing insight

into the thermodynamic profiles of various species, particularly in the context of ectothermy, thermal analysis will increase its capacity to characterize biological systems.

Energy storage is an integral facet of biological systems, yet its benefits and costs are not expected to be equivalent across taxa (Griffen, 2017), which encourages research attention across species and environmental conditions. Prior to the work presented in this dissertation, there were no existing studies regarding differential scanning calorimetry of sea lice. However, conclusions from bomb calorimetry indicated that energy content, via calories per g dry weight, dropped substantially from one-day-old to seven-day-old copepodids in both summer and winter experimental temperatures (Tucker et al., 2000). In order to fully characterize energy availability and use for the species, on both shorter and longer time scales, it is necessary to understand seasonally changing energy budgets across all life stages.

1.2.4. Parasites (or lack thereof) in food webs

In a broader context, as one diverse group, parasites are often ignored in a wide array of ecological research, despite their widespread presence and influence on the life histories and evolution of marine organisms and their ecosystems (Blakeslee et al., 2019). Parasitic lifestyles themselves encompass a spectrum of interactions with respective hosts, and it is often difficult to assess the magnitude of parasitic impact on the host (Thieltges et al., 2019), as well as the flow of resources from host to parasite.

Stable isotope analysis (SIA) enables quantification of these exact trophic relationships that likely change throughout time and space, allowing data collection that would otherwise be impossible via gut content evaluation due to the small body sizes of parasites (Thieltges et al.,

2019). SIA explores the differences between isotopic ratios (13C/12C and 15N/14N) of consumers and their food items, which results from the process of isotopic fractionation (Fry, 2006). The

traditional delta notation (d) indicates the difference in the isotopic ratio of the sample from a reference standard. The difference is conventionally expressed in parts per thousand (‰) according to the following equation:

dX= [(Rsample – Rstandard)/Rstandard] x 1000 where X is 13C or 15N, and R is the respective isotope ratio 13C/12C or 15N/14N.

Across the animal kingdom, it is assumed that d13C values are conserved within less than

1‰ through trophic transfer (Michener and Lajtha, 2007) and that d15N values are enriched by approximately 3.2‰ – 3.4‰ from prey to predator (DeNiro and Epstein, 1981; Minagawa and

Wada, 1984; Post, 2002; Michener and Lajtha, 2007). Under these assumptions, diet composition and trophic level within a food web are inferred, respectively. However, d13C and d15N enrichment standards are very broadly applied and were initially derived from more traditional predator-prey interactions. There is a growing body of SIA literature surrounding parasitic relationships, as they consistently appear to be caveats that challenge these trophic standards, with particular evidence in the case of unusual d15N discrimination factors (Pinnegar et al., 2001;

Deudero et al., 2002; Eloranta et al., 2015; Thieltges et al., 2019).

SIA discrimination factors and other data may be used to strengthen bioenergetic models, which predict interspecific interactions by explicitly accounting for energy densities and size- dependent physiological rates under different environmental variables (Harvey et al., 2002; Caut et al., 2006). However, knowledge of isotopic fractionation between species is often lacking, which necessitates detailed laboratory studies of species-specific interactions across time and space (Caut et al., 2006). In order to effectively include parasites in ecosystem-based models of energy and nutrient flow, the precise interface between the host and parasite must first be fully understood rather than inferred.

A limited amount of research has documented stable isotopes in the salmon-sea louse relationship. Butterworth et al. (2004) suggested that d15N differs between L. salmonis collected from farmed and wild salmonids, and between lice from fish on different farm sites, while Dean et al. (2011) did not find initial differences in d15N between two host populations, and therefore did not recommend d15N values as tracers. Previous SIA of sea lice has mostly been conducted in the context of fingerprinting parasites from farmed versus wild salmonids. However, given the conflicting findings from prior studies and the currently limited literature, the discrimination factors between sea lice and salmon require more attention, particularly across sites.

Maine offers a suitable study system because of its strong presence of farmed salmon and its remaining wild salmon population. Although L. salmonis is the most prevalent parasite on salmon farms, its presence is restricted to the coastal and oceanic portions of the wild salmon life cycle, due to its stenohaline nature (Bricknell et al., 2006). The common fish louse Argulus foliaceus (L.) is a similarly prevalent ectoparasitic crustacean that tolerates a wider range of salinities, and is thus found on returning wild salmon in fresher waters (17-20 ppt). A. foliaceus is additionally a substantial economic threat to a variety of other wild and cultured fishes (Sahoo et al., 2013; AmbuAli et al., 2019). With two conspecific host cohorts that experience different habitats and prey items, and two species of ectoparasites, there is a unique opportunity to compare multiple aspects of trophic enrichment patterns.

1.3. Objectives

The work presented in this dissertation establishes innovative biophysical profiles of the salmon louse to advance regional knowledge and offer diverse approaches that may be applied to other sea louse populations. Chapter 2 discusses a meta-analysis of recent fish host-parasite SIA

data and a case study that introduces the isotopic profiles of L. salmonis, A. foliaceus, and farmed and wild S. salar in Maine, then contrasts the resulting trophic enrichment patterns. With these data and future studies, improved knowledge of trophic enrichment from host to parasite may improve the accuracy of bioenergetic models of ecosystems. Chapter 3 presents complementary studies that quantify two forms of endogenous reserves in embryos at seasonal, monthly, and daily scales. Levels of lipid stores were traced using a combination of semi-quantitative histological and image processing methods, while thermal energy was profiled using quantitative differential scanning calorimetry. Many aspects of the energy budgets and reproductive biology of L. salmonis remain poorly understood, particularly as they relate to changing environmental conditions. A thorough understanding of seasonal condition and how it may be indicated, beginning at the understudied embryonic stage, is required to enhance the infection model component of integrated pest management strategies on farms. The current studies suggest that trophic enrichment from host to parasite ranges in magnitude and direction across species, and provide evidence of juxtaposing fluctuations in two energy reserves in embryos across time.

CHAPTER 2

STABLE ISOTOPES REVEAL CONTRASTING TROPHIC DYNAMICS

BETWEEN HOST-PARASITE RELATIONSHIPS: A CASE STUDY

OF ATLANTIC SALMON AND PARASITIC LICE

2.1. Introduction

Despite the ubiquity of host-parasite relationships, the number of trophic studies that focus on parasites is incongruent with their biological significance. While it is often difficult to evaluate the degree of impact that a parasite has on its host and the resulting flow of nutrients, stable isotope analysis (SIA) provides a quantitative measure of the trophic relationship

(Deudero et al., 2002). Ectoparasites offer particularly feasible opportunities to study parasitic food webs, as they can be extracted without sacrificing their hosts (Demopoulos and Sikkel,

2015). Although there is interest in the incorporation of parasites into traditional food web models (Marcogliese and Cone, 1997), there does not appear to be a universal trend in isotopic enrichment or depletion from host to parasite (Pinnegar et al., 2001; Lafferty et al., 2008;

Pulkkinen et al., 2016), making studies that examine specific host-parasite links all the more important. The current investigation presents host-parasite isotope dynamics in Atlantic salmon

(Salmo salar L.) and parasitic lice (Lepeophtheirus salmonis, Krøyer 1837 and Argulus foliaceus

L.), as a limited number of investigations have implemented this tool in this context. In Maine, there is a strong presence of Atlantic salmon aquaculture and a remaining wild salmon population of the same species—this study is the first to document stable isotopes of both wild and farmed salmon, their corresponding parasites, and multiple host tissue types.

S. salar is an economically and culturally important species in coastal communities worldwide. Aquaculture continues to grow at a rate that exceeds that of the global human population; therefore, the industry as a whole has the potential to meet the marine protein and lipid needs of steadily increasing demands (Duarte et al., 2009; Jansen et al., 2012). However, the largest impediments to the growth of the salmon sector are frequent and high-intensity parasitic lice infections (Costello, 2009; Guo and Woo, 2009), which result in lowered marketability of the fish (Wagner et al., 2007), expensive anti-parasitic treatments (Costello,

2006; Costello, 2009), and negative public perceptions (Pike and Wadsworth, 1999; Guo and

Woo, 2009). L. salmonis is the most widely investigated species of sea lice due to its substantial economic impact on the salmon industry and its ambiguous transmission potential to wild salmon populations (Johnson and Albright, 1992; Boxaspen, 2006; Wagner et al., 2007).

Similarly, A. foliaceus is a prevalent ectoparasitic crustacean that is a substantial hazard to wild

S. salar (Sahoo et al., 2013), as well as a variety of other wild and cultured fish species (Taylor et al., 2006; AmbuAli et al., 2019). To the author’s knowledge, this research provides the first account of the isotopic signals of A. foliaceus.

Although the extensive and costly effects of parasitic lice on host fish have been well known for the past few decades, the details regarding their trophic ecology and roles in food webs remain unclear. Stable isotope analysis (SIA) is a tool that is used in a variety of ecological contexts, including studies of animal movement and food web dynamics in aquatic habitats

(Hesslein et al., 1991; Doucett et al., 1996; Dempson and Power, 2004). The ratios of many heavy and light isotopes, such as 13C/12C and 15N/14N, vary between organisms and habitats.

They may be used to track elements from potential food sources to individual consumers, food webs, and ecosystems, given that relative isotope abundances can be measured in all relevant

food sources and target organisms (Peterson and Fry, 1987; Post, 2002). Unlike traditional analyses of gut and faecal content that provide time-constrained snapshots of feeding and require visual interpretation, SIA provides an integrated, longer-term trophic history that varies by tissue type (DeNiro and Epstein, 1981; Dempson and Power, 2004; Michener and Lajtha, 2007). The delta notation (d) indicates the difference in the isotopic ratio of the sample from a reference standard. The difference is conventionally expressed in parts per thousand (‰) according to the following equation:

dX= [(Rsample – Rstandard)/Rstandard] x 1000 where X is 13C or 15N, and R is the respective isotope ratio 13C/12C or 15N/14N.

d13C values reflect diet composition, as they are often conserved within <1‰ through trophic transfer (Michener and Lajtha, 2007). d15N values are used to elucidate trophic levels within food webs, as those of consumers also reflect those of their diets; however, the animal tends to be enriched by approximately 3.2‰ – 3.4‰ compared to the prey item (DeNiro and

Epstein, 1981; Minagawa and Wada, 1984; Post, 2002; Michener and Lajtha, 2007). While these enrichment trends are often assumed across the animal kingdom due to their broad consistency across species and environments (DeNiro and Epstein, 1981; Minagawa and Wada, 1984), host- parasite linkages may not fall under the umbrella of traditional predator-prey relationships

(Pinnegar et al., 2001; Deudero et al., 2002; Eloranta et al., 2015). Therefore, although there is a need to include parasites in traditional food web models due to their widespread influence across ecosystems, their trophic relationships must first be comprehensively evidenced rather than inferred. Knowledge of trophic enrichment from host to parasite may then strengthen bioenergetic models, which predict interspecific interactions within ecosystems by additionally

accounting for energy densities and size-dependent physiological rates across time and space

(Harvey et al., 2002; Caut et al., 2006).

SIA of parasitic relationships remains relatively understudied compared to free-living and traditional predator-prey trophic interactions; therefore, we assessed original fish host-parasite isotopic relationships and previously published fish host-parasite data. The current study aims to:

1. Calculate d15N and d13C enrichment from fish host to parasite in existing literature; 2.

Quantify d15N and d13C enrichment by sampling host-parasite relationships (farmed S. salar-L. salmonis, and wild S. salar-A. foliaceus); and 3. Determine d13C and d15N values of muscle, fin, and skin of farmed and wild S. salar.

2.2. Materials and methods

2.2.1. Literature review

Fish host and parasite isotopic values were compiled from existing literature (Table 2.1) using combinations of the search words “stable isotope analysis”, “fish host”, “parasite”,

“carbon”, and “nitrogen” in the Web of Science Core Collection. The search timespan was from

2002 to present, focusing on results after the review by Pinnegar et al. (2001).

2.2.2. Study sites

L. salmonis were collected from farmed S. salar in Cobscook Bay (Eastport, ME) and the

Gulf of Maine (Jonesport, Crow Island, and Beals Island, ME) (Figure 2.1). Cobscook Bay is a boreal and macrotidal bay that is characterized by high natural productivity and ecological richness, with salinities of >30 ppt (Larsen, 2004). The Gulf of Maine is a well-studied ecosystem with similar salinities and intermediate levels of biodiversity (Incze et al., 2010). Sites in both regions consisted of offshore, open-net pens with pellet-fed farmed fish. L. salmonis were

also collected from a pool of wild pink and coho salmon (Oncorhynchus gorbuscha and

Oncorhynchus kisutch, respectively; collected by Dr. Ron Johnson, NOAA NWFSC) in Puget

Sound (Seattle, WA) to compare geographically distinct conspecific parasites.

A. foliaceus were collected from returning wild, sea-run S. salar in the summer at two sites on the Penobscot River (Old Town and Orland, ME) (Figure 2.1). The Penobscot River ranges in salinity from freshwater to marine conditions, with brackish waters at many locations.

Wild S. salar are a protected species with a low population size in Maine, which restricted parasite sampling—A. foliaceus was the only ectoparasite that was present in all Penobscot River sampling events, likely due to low salinity in the collection area, which is fatal to L. salmonis

(Bricknell et al., 2006).

2.2.3 Parasite collections

Parasites of all available stages were removed with forceps from anesthetized hosts (0.2 mg/L MS-222, Sigma). The majority of L. salmonis and A. foliaceus were adults or pre-adults.

When infection intensity was sufficiently high for replicates in stable isotope analysis

(approximately 5-6 lice), all parasites from a single host were placed in a tube and labelled as one sample. When intensity on one host was too low for replicates in analysis, lice were pooled across multiple hosts into one tube. All tubes were placed on ice during transport and stored in freezers until they were processed for stable isotope analysis.

Table 2.1. Sources of compiled enrichment data. The number of host-parasite species pairs is denoted by “n”. Reference Parasitism Class Parasite Taxon Host Tissue n Fin 2 Taccardi et al. (in review) Ectoparasite Arthropod Muscle 2 Skin 2 Gut 1 Behrmann-Godel & Yohannes, Endoparasite Cestode Liver 1 2015 Muscle 1 Blood 1 Demopoulos & Sikkel, 2015 Ectoparasite Arthropod Heart 3 Muscle 4 Eye 1 Ectoparasite Arthropod Gill 5 Skin 1 Cestode Peritonial cavity 1 Deudero et al., 2002 Gill 1 Intestine 3 Endoparasite Nematode Liver 5 Peritonial cavity 7 Stomach 2 Eloranta et al., 2015 Endoparasite Cestode Muscle 2 Fritts et al., 2013 Ectoparasite Mollusk Gill 1 Annelid Muscle 1 Ectoparasite Arthropod Muscle 2 Kanaya et al., 2019 Cestode Muscle 1 Endoparasite Eye 2 Trematode Muscle 3 Intestine 2 Nachev et al., 2017 Endoparasite Acanthocephalan Liver 2 Muscle 2 Persson et al., 2007 Endoparasite Cestode Muscle 1 Power & Klein, 2004 Endoparasite Cestode Muscle 3 Xu et al., 2007 Ectoparasite Arthropod Muscle 1 Blood 1 Yohannes et al., 2017 Endoparasite Cestode Liver 1 Blood 1 Acanthocephalan Intestine 1 Zhang et al., 2018 Endoparasite Blood 1 Trematode Intestine 1

Figure 2.1. Sampling sites on eastern and western coasts of the US.

2.2.4. Salmon tissue collections

Farmed S. salar from Eastport, ME were euthanized prior to arrival at the lab and were provided by Cooke Aquaculture for tissue analysis. Wild S. salar were provided by the Craig

Brook National Fish Hatchery in Orland, ME, and had not survived the run of the season due to natural causes. Experiments were conducted in accordance with the regulations of the

Endangered Species Act under the permit #TE-697823. Approximately 16 cm3 of white muscle, located dorsally to the lateral line and anteriorly to the dorsal fin, was each extracted with a scalpel. Each skin sample and caudal fin collection was approximately 6 cm2 in size and was removed using surgical scissors. All fish tissue was stored in separate tubes in a freezer prior to

preparation for stable isotope analysis. Sample sizes of all species and tissues are presented in

Table 2.2.

2.2.5. Stable isotope analysis

All parasite and fish samples were thawed, quickly rinsed with deionized water, removed from their tubes, and placed in a drying oven at approximately 60°C for 48 hours. Each dried sample was ground to a fine, homogeneous powder using a mortar and pestle or manual coffee grinder (S. salar skin and fin), and 1.0 (+ 0.2) mg of sample was manually encapsulated in 5x9- mm tin. Capsules were shipped to the University of California-Davis Stable Isotope Facility

(Davis, CA) for solid material analysis of d13C and d15N. A PDZ Europa ANCA-GSL elemental analyser interfaced to a PDZ Europa 20-20 isotope ratio mass spectrometer generated delta values that were expressed relative to VPDB and Air international standards for carbon and nitrogen, respectively.

2.2.6. Statistical analysis

Results were analysed using statistical packages in GraphPad Prism 8 and JMP 14 software. For d13C and d15N comparisons between two groups, an unpaired t-test with Welch’s correction was conducted. When d13C or d15N was compared across multiple groups, a one-way

ANOVA with Tukey’s multiple comparisons was used after testing for normality and homogeneity of variances (Shapiro-Wilk and Bartlett’s tests, respectively). For all statistical tests, a significance level of 0.05 (95% confidence level) was used.

Table 2.2. Sample sizes and isotopic grand means (+ SD) of farmed and wild Salmo salar, Lepeophtheirus salmonis, and Argulus foliaceus. The number of raw isotopic values that were measured and analyzed is denoted by “n”. “No. Replicated Groups” refers to the number of sampled host tissues or the number of replicated units of pooled parasites.

No. Species Date Farmed/Wild Site Tissue n Replicated 13 15 Sampled Collected d C (‰) d N (‰) Groups A. 06/2016 30 3 -20.07 (0.30) 12.14 (0.31) Old Town Whole foliaceus On wild host 06/2017 6 2 -20.75 (0.81) 12.80 (0.55) organism Orland 06/2018 3 2 -20.77 (0.31) 13.30 (0.37) 07/2016 40 10 -18.01 (0.19) 10.43 (0.31) 09/2016 17 5 -18.49 (0.07) 10.66 (0.19) Eastport 10/2016 19 5 -19.04 (0.11) 10.34 (0.19) On farmed 12/2016 12 3 -18.91 (0.09) 10.09 (0.22) L. host Crow Island 10/2017 Whole 15 5 -17.88 (0.07) 10.40 (0.20) salmonis organism Jonesport 12/2017 12 4 -18.48 (0.10) 9.53 (0.18) Beals Island 07/2018 12 4 -18.26 (0.15) 10.31 (0.13) 07/2017 3 1 -16.60 (0.22) 15.06 (0.32) On wild host† Seattle, WA 08/2017 12 4 -16.86 (0.33) 17.12 (0.49) 07/2018 3 2 -17.21 (0.76) 17.44 (0.96) Muscle 28 7 -20.05 (0.34) 8.30 (0.19) Farmed host Eastport 12/2016 Fin 24 6 -17.44 (0.35) 8.61 (0.33) Skin 23 6 -18.62 (1.03) 7.79 (0.29) S. salar Muscle 6 2 -20.51 (0.43) 12.53 (0.05) Wild host Orland 06/2018 Fin 6 2 -18.91 (0.36) 12.95 (0.03) Skin 6 2 -21.40 (0.27) 11.96 (0.11) †Combined Oncorhynchus gorbuscha and Oncorhynchus kisutch hosts

15 15 Nitrogen enrichment was calculated as d Nparasite – d Nhost (S.D.parasite + S.D.host) for each tissue type across parasite sampling events and compiled literature values. The same equation was applied for d13C enrichment. Grand means were used for host tissues and individual parasite collections, due to variability within both factors. Enrichment was considered significant when the result was greater than the long-term d15N and d13C standard deviations at the UC Davis

Stable Isotope Facility (0.3‰ and 0.2‰, respectively; https://stableisotopefacility.ucdavis.edu/13cand15n.html). Parasite d15N or d13C were considered

15 15 13 13 depleted if (d Nparasite – d Nhost) or (d Cparasite – d Chost) < -0.3‰ or -0.2‰, respectively.

2.3. Results

2.3.1. Host-parasite literature

2.3.1.1. Enrichment across taxa

All four endoparasitic taxa were depleted in d15N with respect to their hosts (Figure 2.2), with the highest discrimination amongst nematodes and their hosts (-3.45‰ + SE 0.56‰) and the lowest amongst cestodes and their hosts (-0.83‰ + 0.53‰). Endoparasites displayed a range of d13C patterns relative to their hosts, as acanthocephalans were relatively enriched on average, nematodes and trematodes were relatively depleted, and cestode values were similar to those of their hosts (Figure 2.2).

Ectoparasitic taxa showed a range of d15N relationships with their hosts, with relative depletion in annelids, enrichment in the mollusks, and, among arthropods, similar values to those of their hosts (Figure 2.2). Mollusks were enriched (1.8‰) in d13C compared to their hosts, and annelids were relatively depleted (-0.5‰) (Figure 2.2).

2.3.1.2. Enrichment across tissues

Ectoparasites were enriched in d15N relative to host blood and eye tissues, while endoparasite d15N signals were not significantly different from blood or eye values of their hosts

(Figure 2.3.a and b). Ectoparasites were enriched in d15N relative to four out of seven host tissues and were depleted in d13C relative to four tissues (Figure 2.3a). Ectoparasites displayed an expansive range of d15N enrichment values compared to host gill (Figure 2.3a), whereas

Figure 2.2. d15N and d13C enrichment of parasites relative to hosts from compiled references (Table 2.1). Represented data are grand means (+ SE when available).

endoparasites were the most depleted in d15N relative to their host gill. Endoparasites were depleted in d15N compared to their hosts in all but one host tissue. Enrichment patterns were more varied for d13C, however—out of the nine tissue types, four showed relative depletion in

endoparasites, three were relatively enriched, and two were not significantly different from host to parasite (Figure 2.3b).

2.3.2. Enrichment in case study

L. salmonis were enriched in d15N relative to all farmed S. salar tissues and across all parasite collections (Table 2.3). d15N values of L. salmonis were clustered approximately half of a standard 3.4‰ trophic level (Minagawa and Wada, 1984) above those of their farmed hosts across collections (Figure 2.4). In contrast, A. foliaceus displayed a range of patterns that included equivalent to, enriched, and depleted in d15N compared to their wild hosts (Table 2.3). d15N values of A. foliaceus were scattered within the spread of their host values across tissues

(Figure 2.4).

On average, L. salmonis were enriched in d13C relative to farmed muscle and skin, and were depleted relative to fin (Table 2.3). In two collections, however, L. salmonis and host skin d13C values were not significantly different. On average, A. foliaceus were enriched in d13C relative to wild skin, depleted compared to muscle values, and not significantly different from fin signals (Table 2.3).

2.3.3. Farmed and wild salmon tissue

d13C and d15N values differed significantly (P<0.0001) between Cobscook Bay farmed S. salar and Penobscot River wild S. salar in all but one case. Farmed and wild fish had similar collective spreads in d13C (4.05‰ and 3.28‰, respectively) and d15N (1.81‰ and 1.15‰, respectively) across all tissues. Within the farmed host group, both d13C and d15N were unique across tissues (Table 2.4). Similarly, all comparisons of d13C and d15N across wild host tissues yielded highly significant differences. For both farmed and wild S. salar, each tissue type had a range of approximately 1‰ in d13C, except for the larger spread of 3‰ in farmed skin.

a δN15 2 δC13

-1

-2

-3 Mean Enrichment (‰)

-4

-5

Fin Gill Eye Skin Blood Heart Muscle Ectoparasite Host Tissue b 3 δN15 2 δC13

-1

-2

-3 Mean Enrichment (‰) -4

-5

Eye Gill Gut Blood Liver Muscle Intestine Stomach

Peritonial cavity

Endoparasite Host Tissue

Figure 2.3. d15N and d13C enrichment across tissues of a. ectoparasites and b. endoparasites from compiled references (Table 2.1). Represented data are grand means (+ SE when available).

Figure 2.4. Isotopic signals of Salmo salar, Lepeophtheirus salmonis, and Argulus foliaceus. Farmed S. salar and L. salmonis are represented by closed symbols, and wild S. salar and A. foliaceus are represented by open symbols. Grand means (+ SD) are displayed.

2.3.4. Parasite comparisons

2.3.4.1. Assessments within cohorts

d15N signals were unique across Atlantic L. salmonis samples in approximately half of the comparisons, with no apparent temporal or spatial trend. d13C values also significantly differed between L. salmonis collections in the majority of comparisons (Table 2.4). Both d13C and d15N signals were unique across A. foliaceus collections in nearly all comparisons (Table

2.4). In all but one case, neither d13C nor d15N values differed across Pacific L. salmonis collections (Table 2.4).

Table 2.3. d15N and d13C enrichment of Lepeophtheirus salmonis and Argulus foliaceus in relation to farmed and wild Salmo salar tissue. Grand means (+ SD) were used for fish tissue types and parasite collections, with the exception of means (+ SD) for A. foliaceus MD Jun17 and CBH Jun18 data due to low numbers. * Indicates significant enrichment and † indicates significant depletion. Collection names include abbreviated site, and sampling month and year.

L. salmonis FARMED Collection Muscle Fin Skin d15N (‰) d13C (‰) d15N (‰) d13C (‰) d15N (‰) d13C (‰) CB‡ Jul16 2.13* (0.45) 2.04* (0.48) 1.82* (0.63) -0.57† (0.56) 2.62* (0.58) 0.67* (1.25) CB Sep16 2.40* (0.23) 1.55* (0.35) 2.09* (0.40) -1.06† (0.43) 2.89* (0.35) 0.18 (1.12) CB Oct16 2.05* (0.28) 1.01* (0.37) 1.74* (0.45) -0.36† (0.45) 2.54* (0.40) -0.36† (1.14) CB Dec16 1.79* (0.37) 1.14* (0.38) 1.48* (0.55) -1.47† (0.46) 2.28* (0.50) -0.23† (1.15) CI§ Oct17 2.10* (0.36) 2.17* (0.35) 1.79* (0.54) -0.44† (0.43) 2.59* (0.49) 0.80* (1.12) J¶ Dec17 1.23* (0.26) 1.57* (0.39) 0.92* (0.43) -1.04† (0.47) 1.72* (0.38) 0.20 (1.16) BI¥ Jul18 2.01* (0.24) 1.79* (0.40) 1.70* (0.42) -0.82† (0.48) 2.50* (0.37) 0.42* (1.17) Average 1.96* (0.31) 1.61* (0.39) 1.65* (0.49) -0.82† (0.47) 2.45* (0.44) 0.24* (1.16) A. foliaceus WILD Collection Muscle Fin Skin d15N (‰) d13C (‰) d15N (‰) d13C (‰) d15N (‰) d13C (‰) MD£ Jun16 -0.40† (0.36) 0.44* (0.89) -0.81† (0.36) -1.16† (0.75) 0.19 (0.47) 1.34* (0.63) MD Jun17 0.27 (0.58) -0.24† (1.37) -0.15 (0.58) -1.84† (1.23) 0.85* (0.69) 0.66* (1.11) CBH¦ Jun18 0.77* (0.40) -0.26† (0.87) 0.36* (0.40) -1.86† (0.73) 1.35* (0.51) 0.64* (0.61) Average 0.21 (0.45) -0.02 (1.04) -0.20 (0.45) -1.62† (0.90) 0.80* (0.56) 0.88* (0.78) *Significant enrichment †Significant depletion ‡Eastport, ME (Cobscook Bay) §Crow Island, ME (Gulf of Maine) ¶Jonesport, ME (Gulf of Maine) ¥Beals Island, ME (Gulf of Maine) £Old Town, ME (Penobscot River) ¦Orland, ME (Penobscot River)

2.3.4.2. Parasites from farmed and wild S. salar

Due to significant differences between several sampling events for both parasite species, each collection was analysed separately in multiple comparisons between L. salmonis and A. foliaceus isotopes. Each parasite population occupied a unique 2D niche space on a biplot of d13C versus d15N (Figure 2.5). Parasites from local farmed and wild S. salar differed in d15N values in all comparisons. Atlantic L. salmonis and A. foliaceus had significantly different d13C values in approximately 80% of all comparisons.

Table 2.4. P-values of one-way ANOVAs (Tukey’s multiple comparisons) for Salmo salar, Atlantic and Pacific Lepeophtheirus salmonis, Argulus foliaceus. Italicized components of titles represent italicized P-values. d13C: Farmed and Wild S. salar d15N: Farmed and Wild S. salar Muscle Fin Skin Muscle Fin Skin Muscle <0.0001 <0.0001 Muscle 0.0002 <0.0001 Fin <0.0001 <0.0001 Fin <0.0001 <0.0001 Skin 0.0004 <0.0001 Skin <0.0001 <0.0001 d13C and d15N: Atlantic L. salmonis CB Jul16 CB Sep16 CB Oct16 CB Dec16 CI Oct17 J Dec17 BI Jul18 CB‡ Jul16 <0.0001 <0.0001 <0.0001 0.0486 <0.0001 <0.0001 CB Sep16 0.0202 <0.0001 <0.0001 <0.0001 >0.9999 0.0003 CB Oct16 0.7622 0.0014 0.1059 <0.0001 <0.0001 <0.0001 CB Dec16 0.0004 <0.0001 0.0755 <0.0001 <0.0001 <0.0001 CI§ Oct17 0.9994 0.0387 0.9853 0.0149 <0.0001 <0.0001 J¶ Dec17 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001 0.0023 BI¥ Jul18 0.6395 0.0021 0.9998 0.2894 0.9367 <0.0001 d13C and d15N: Pacific L. salmonis d13C and d15N: A. foliaceus W Jul17 W Aug17 W Jul18 MD Jun16 MD Jun17 CBH Jun18 £ 0.3714 0.5753 MD Jun16 0.0020 0.0210 W† Jul17 W Aug17 0.0008 0.8276 MD Jun17 0.0006 0.9978 W Jul18 0.1130 0.9159 CBH¦ Jun18 <0.0001 0.1283 ‡Eastport, ME (Cobscook Bay) §Crow Island, ME (Gulf of Maine) ¶Jonesport, ME (Gulf of Maine) ¥Beals Island, ME (Gulf of Maine) £Old Town, ME (Penobscot River) ¦Orland, ME (Penobscot River) †Seattle, WA (Puget Sound)

2.3.4.3. Geographically distinct L. salmonis

Atlantic and Pacific L. salmonis significantly differed in d15N across all sampling events.

Atlantic and Pacific L. salmonis each had a range of approximately 2‰ in d13C, while the Pacific group had a greater spread in d15N (approximately 4‰) compared to the Atlantic group

(approximately 2‰) (Figure 2.5). Pacific L. salmonis in 2017 significantly differed in d13C from

Atlantic L. salmonis in all but one case. However, d13C values from Washington in 2018 were not unique compared to L. salmonis in Maine.

Figure 2.5. Isotopic signals of Argulus foliaceus and Atlantic and Pacific Lepeophtheirus salmonis. Raw data are displayed.

2.4. Discussion

Our results suggest that neither d15N nor d13C enrichment in fish host-parasite relationships conforms to standards that are assumed across the animal kingdom. Doucett et al.

(1999) claimed that host-parasite enrichment patterns fall under the d15N and d13C standards set by other predator-prey relationships, but Pinnegar et al. (2001) demonstrated that this was not the case, particularly regarding d15N enrichment, in any of the 20 fish host-parasite samples that were investigated. Therefore, we further analysed fish host-parasite linkages that were published after 2001. All endoparasitic taxa were depleted in d15N compared to their hosts, while ectoparasitic taxa demonstrated enrichment, equivalence, and depletion relative to their hosts.

Both ecto- and endoparasites exhibited a range of d13C enrichment patterns compared to their

hosts across taxa and tissues. Given the highly variable nature of these results, these studies did not elucidate new standards in host-parasite enrichment.

We also demonstrate that minute differences in parasitic life strategies may result in opposing trophic enrichment patterns from host to parasite—even among two ectoparasitic crustaceans that share a host species and region and employ similar feeding tactics. Both L. salmonis and A. foliaceus exhibited a variety of d13C patterns relative to their hosts, which included relative depletion, enrichment, and equivalence. L. salmonis were enriched in d15N relative to all host tissue types and demonstrated a variety of d13C patterns compared to their hosts. Butterworth et al. (2004) demonstrated that L. salmonis from farmed S. salar in Canada were enriched in d13C and d15N by 1.78‰ and 1.62‰, respectively, compared to host muscle.

Our local L. salmonis and host muscle samples exhibited enrichment values of 1.61‰ and

1.96‰, respectively. However, although Butterworth et al. found that L. salmonis differed in d15N between farmed and wild hosts and between the same host species across farms, they did not compare host-parasite enrichment for each cohort. In the current study, A. foliaceus were only enriched in d15N compared to wild S. salar skin, and their signals were not different from those of host muscle and fin.

Investigations into the comparative trophic ecology of geographically distinct L. salmonis have been scarce. To refine taxonomical relationships of L. salmonis in the Atlantic and Pacific

Oceans, previous studies have compared other biological facets, such as development time

(Johnson and Albright, 1991a; Heuch et al., 2000), size (Johnson and Albright, 1991b; Schram,

1993), salinity tolerance (Johnson and Albright, 1992; Bricknell et al., 2006), and host selection

(Jones et al., 2006; Skern-Mauritzen et al., 2014). We detected consistent differences in d15N between L. salmonis on opposite US coasts, which were expected due to the distinction between

migratory wild hosts in the Pacific and farmed hosts in the Atlantic. However, L. salmonis from

Pacific and Atlantic sites had contrasting d13C signals in 2017 and not in 2018. Dean et al. (2011) determined that adult female L. salmonis were enriched in d13C by 0‰ - 1‰ compared to wild

O. gorbuscha and did not find significant differences in d15N between wild O. gorbuscha and farmed S. salar. O. gorbuscha and O. kisutch samples were not accessible for the current study, and SIA of parasites and their directly linked individual hosts will prove most effective in future inquiries.

Fish host-parasite relationships are intriguing to assess through the lens of stable isotopes because they synthesize two individually complex life histories. When conducting SIA of parasites and their hosts, the timing of parasite extraction is crucial, as the isotopic values of progressing parasitic life stages and long-term residents approach those of their hosts (Dean et al., 2011; Hernández-Arciga et al., 2016). Further attention should be paid to host-hopping parasites, such as A. foliaceus, which may confound enrichment patterns by incorporating signals from multiple fish. For endoparasites, enrichment studies must consider diversity in amino acid selection and uptake, as many endoparasites have evolved metabolic pathways that adjust according to nutrient availability and favour isotopically-depleted nutrients (Pinnegar et al.,

2001). Host tissue sampling must remain consistent, as d13C and d15N varied across tissues within both S. salar cohorts in the current study. The majority of researchers sample white muscle from fish due to its ability to retain isotopic signals over the course of weeks to months

(Kennedy et al., 2005; Schröder and Garcia de Leaniz, 2011). However, in the case of parasites, host tissue should correspond to common parasitic feeding sites. Non-lethal sampling of fin clips and skin may also be more practical when sampling fish from declining and vulnerable populations.

Lastly, SIA should be conducted with an awareness that a changing environment may influence prey item availability and timing, and ultimately induce trophic shifts. Therefore, knowledge of trophic enrichment within an ecosystem may be coupled with bioenergetic models for accurate interpretation of interspecies interactions within an ecosystem (Caut et al., 2006).

However, fundamental inputs regarding trophic enrichment in parasitic relationships remain relatively sparse across taxa. Unlike traditional predator-prey interactions, among the studies that have documented d15N and d13C enrichment pathways from host to parasite, there do not appear to be widespread trends that can be applied across ecosystems. Furthermore, we assert that it is currently premature to deduce new standard values for parasites, and it is possible that these relationships will continue to be too variable to reasonably claim any universality across parasitic associations as a whole. Future studies of host-parasite linkages across species are necessary to continue to evaluate whether or not there is an existing pattern that may be applied before successful incorporation into food webs and bioenergetic models.

CHAPTER 3

SEASONAL PROGRESSION OF EMBRYO SIZE, LIPID RESERVES, AND

THERMAL ENERGY IN SEA LICE (LEPEOPHTHEIRUS SALMONIS)

COLLECTED FROM SALMON FARMS

3.1. Introduction

The salmon louse Lepeophtheirus salmonis (Krøyer, 1837) is a parasitic copepod whose infestations comprise the largest economic constraint to Atlantic salmon aquaculture (Costello,

2006; Guo and Woo, 2009), leading to its ranking as the most widely studied species of sea lice

(Boxaspen, 2006; Abolofia and Wilen, 2017). Its estimated annual cost to the industry worldwide approaches $1 billion, and is predominantly a result of treatment expenses and production losses

(Abolofia and Wilen, 2017). With prolonged attachment and feeding, L. salmonis causes external damage, reduced fish growth, and increased susceptibility to secondary infections, which are often the cause of host mortality (Boxaspen, 2006; Costello, 2006; Mustafa et al., 2001).

With each reproductive cycle, gravid female sea lice extrude paired egg strings, each containing approximately 100 to 1000 eggs (Costello, 1993). Embryos hatch as planktonic nauplius larvae, and both eggs and larval stages derive energy from maternal lipid reserves, with no additional investment from the female post-extrusion of egg strings (Cook et al., 2010;

Torrissen et al., 2013). Nauplii molt into infective copepodids, which must seek and attach to a host before endogenous energy stores are depleted, and actively feed through the adult stages

(Boxaspen, 2006; Hamre et al., 2009).

Sea lice abatement has been met with limited success, due primarily to the biological aptitude of the parasite for overcoming anti-parasitic tactics, both host- and human-induced, and its large reproductive capacity in paired egg strings (Boxaspen, 2006; Hamre et al., 2009).

Therefore, there is an urgent need to increase our understanding of sea lice biology, especially as it relates to ecological resilience, particularly the physiological mechanisms that underlie egg quality. Epidemiological models play a proactive and practical role in integrated pest management, yet the biology of L. salmonis embryo condition (and how it influences the ultimate output of infection capability) remains a gap in knowledge (Brooker et al., 2015; Jones and Johnson, 2015).

The accumulation of large amounts of lipid is a widespread strategy for energy storage among zooplankton, and is perhaps one of the most important metrics of egg quality (Witter and

Cuthill, 1993; Pond et al., 1996; Alonzo et al., 2001; Grote et al., 2011). Energy content is critical in predicting the quality of future planktonic larvae, and thus infection potential, as lipid levels in eggs influence hatching success and naupliar survival (Pond et al., 1996; Tucker et al.,

2000; Alonzo et al., 2001), and govern both the longevity and viability of copepodids prior to and during infection (Tucker et al., 2000; Boxaspen, 2006; Cook et al., 2010; Gonçalves et al.,

2014; Khan et al., 2017). Lipid droplets additionally play key roles in reproduction, development, buoyancy, and migration (Lee et al., 2006; Cook et al., 2010). Because of its diverse functions, lipid content exerts considerable influence on the complex energy budgets and trade-offs that vary throughout progressing life histories. In the total energy budget, egg-bearing copepods generally divert energy resources toward reproduction and feeding, as they undergo minimal somatic growth (Kiørboe et al., 1985); conversely, embryos and larval stages allocate more resources toward rapid growth and ultimately host location. Some copepod species exhibit

their highest lipid quantities in conjunction with their main reproductive events in the summer

(Ceballos and Álvarez-Marqués, 2006), while others demonstrate peak lipid levels prior to their reproductive episodes (Narcy et al., 2009). Other previous investigations have linked specific fecundity metrics with lipid volume, revealing opposing trends in embryo size and the quantities of reserves (Pond et al., 1996).

Energy storage in the form of heat is another widespread phenomenon across biological systems, as metabolic activity in multicellular organisms is supported by its absorption, evolution, and transmission (Blise, 2009). It is generally assumed that natural selection maximizes rates of energy uptake and usage (Lotka, 1922; Ware, 1982; Billerbeck et al., 2001).

However, in addition to their benefits, energy reserves entail a metabolic cost that is influenced by the quantity of energy stored and the temperature-dependent metabolism of the organism

(Witter and Cuthill, 1993; Griffen, 2017). Energy storage often has cascading effects on serial life stages (Harrison et al., 2011), and on central life history processes, including reproduction and metamorphosis (Manzon et al., 2015; Mendo et al., 2016). Therefore, energetic assessments warrant attention across taxa and under varying conditions, as the energy content of dry biomass varies from species to species (Cummins, 1967) and within a species across seasons (Golley,

1961; Comita and Schindler, 1963; Comita et al., 1966; Snow, 1972; Salonen et al., 1976).

Specific heat capacity (Cp) is a fundamental energetic property that exerts strong influence over the physiological limits of organisms, and is defined as the amount of energy required to raise the temperature of 1 g of material by 1°C under constant pressure. Animals must be able to stabilize their thermal energy requirements throughout fluctuations in environmental parameters (Halcrow, 1963) and operate at temperatures within certain ranges to remain functional (Hobbs et al., 2013). Within these temperature ranges, standard metabolic rate

(SMR) of the organism is considered a strong indicator of the overall costs of body maintenance

(Sibly and Calow, 1987; Ashby, 1998). The effects of temperature on SMR tend to positively covary with thermal responses in reproductive and growth rates in ectotherms and marine animals (Careau et al., 2014; Samsing et al., 2016). In the case of sea lice, it is well documented that individuals grow faster at higher temperatures (Johnson and Albright, 1991a; Heuch et al.,

2000; Boxaspen, 2006; Hamre et al., 2009) and abide by universal models of temperature dependence for egg string length and egg production (Samsing et al., 2016). Although existing literature has documented these critical physical measures of fecundity (Heuch et al., 2000;

Mustafa et al., 2000a; Hamre et al., 2009), there is a gap in knowledge regarding other vital indicators of sea louse condition, particularly at the embryonic phase. While the majority of prior investigations of embryos have employed semi-quantitative measurement, thermal energy assessments offer critical quantitative contributions.

Differential scanning calorimetry (DSC) is a fundamental tool in modern thermodynamics that offers rapid acquisition of thermal energetic data with high precision and accuracy (Höhne et al., 2003; Harvey et al., 2018). DSC implements known heating and/or cooling rates to directly assess energy flow between a sample and its environment (Harvey et al.,

2018). In a simple experiment, heat energy is introduced to sample and reference cells, which undergo identical temperature ramps over time, and heat flow of the sample is measured in reference to a temperature differential between cells (Gill et al., 2010). Cp can be calculated from

DSC output using the following formula:

Cp = ΔQ m ΔT where Q = heat flow, m = mass, and T = temperature of the sample.

DSC is commonly applied in materials science, food science, and the pharmaceutical industry, emphasizing phase transitions to characterize properties and assess the purity of substances (Morad et al., 2000; Chiu and Prenner, 2011; Zhu, 2015; Prislan et al., 2019). A limited number of DSC studies have been conducted in an ecological context at the level of the organism, resulting in physicochemical studies that are largely missing the biological component of the systems in question (Werner, 2007). Of the existing literature on copepod energy content, research is heavily weighted toward diapausing, freshwater, and/or free-living species, as well as the adult stage in the life cycle (Wissing and Hasler, 1971; Comita et al., 1966; McAllen and

Block, 1997; Pond and Tarling, 2011).

Although the energy budgets of free-living copepods are frequently studied due to their well-defined roles in food webs, the dynamics of their parasitic relatives remain ambiguous.

Within the research that has addressed lipid stores in sea lice, most studies have placed the infective copepodid and naupliar stages at the forefront (Tucker et al., 2000; Cook et al., 2010;

Thompson et al., 2019), and have documented these dynamics solely under biologically favorable culture conditions without incorporating phenological influences. Maternal investments must balance a variety of variables, including egg size and number, and the energy reserves that are allocated to each. Previous studies have demonstrated that sea lice egg size and viability are reduced at lower temperatures (Ritchie et al., 1993; Heuch et al., 2000; Costello,

2006); however, these investigations represent L. salmonis from Europe and Canada. Average sea temperatures in Europe are generally higher than those in Maine year-round, which may encourage a range of physiological strategies that are unique among geographies, highlighting the importance of sharing novel data from our region.

Obligate lecithotrophy, in which the embryo receives no maternal investment post- extrusion, provides a unique opportunity to investigate energetics in response to environmental factors, as organisms cannot compensate for metabolic changes through consumption of additional items (Thompson et al., 2019). Furthermore, lack of mobility at the egg stage enables quantification of energy reserves that are not reduced by swimming or other behaviors, creating a closed system that does not gain nor lose reserves through confounding activity.

The current study investigates embryo size, lipid profiles, and thermal energy content of sea lice on monthly and seasonal scales. Thermal energy values are also presented as preliminary data on a daily scale. To the author’s knowledge, this is the first study of lipids and thermodynamic properties in L. salmonis embryos (defined as eggs and their developing larvae) throughout progressing seasons, each of which presents environmental conditions that may directly influence embryo quality and/or influence maternal allocation of energy reserves. These data and their implications regarding reproductive success may contribute to more biologically accurate models of larval dispersal and infection at the earliest phase, enabling considerable forecasting to inform integrated pest management strategies on salmon farms.

3.2. Materials and methods

3.2.1. Sea lice collection

Sea lice were collected on a monthly basis from Machiasport and Eastport, ME in 2018 and 2019 (Figure 3.1) (Tables 3.1 and 3.2). Gravid female L. salmonis were removed with forceps from farmed S. salar, and sea lice were stored in seawater on ice during transport to the

University of Maine. After arriving at the laboratory, egg strings were carefully detached from

females. Light-colored egg strings were chosen in order to target early development, as sea lice embryos become increasingly pigmented with maturity (Hamre et al., 2009).

45°N

Machias Bay

Figure 3.1. Site map; red circles indicate collection points in Eastport (Cobscook Bay) and Machiasport (Machias Bay), Maine. Adapted from Chang et al. (2014).

3.2.2. Histology

Upon detachment, egg strings were immediately fixed in Davidson’s solution for 24 hours and were transferred to 70% ethanol for storage until further processing. Samples were dehydrated in a graduated ethanol series, cleared with CitriSolv, and embedded in paraffin in a vacuum oven (Fisher Scientific, Isotemp 281A). Blocks were trimmed and sectioned at 6 µm using a rotary microtome (Thermo Scientific, Shandon Finesse 325). Approximately 10-15 eggs were analyzed for each egg string (Table 3.1). Slides were dried on a hotplate for 24 hours prior

to staining. Slides were stained using a modified Masson’s protocol (Presnell et al., 1997).

Micrographs were captured at 100x using a Nikon Eclipse E200 light microscope and an

AmScope C-mount digital camera.

3.2.3. Lipid quantification

3.2.3.1. Embryo and lipid standards

Embryos that were ellipsoid and displayed an unbroken cuticle were used in analysis.

Fertilized eggs were classified as Stage A or B according to presence or absence of substantial nucleated tissue, as an indication of developmental progress. The first five eggs at proximal and distal ends of egg strings were excluded due to their abnormal lengths and shapes. Samples that displayed artefacts of sectioning within the body of the egg were also removed from analysis.

Throughout histological processing, lipids themselves largely dissolve from samples; it is generally assumed that the remaining vacant, ovular spaces are proxies for previously existing droplets (Pastorinho et al., 2003; Messick et al., 2004); therefore, we measured lipid droplets by proxy. Droplets became increasingly difficult to quantify in embryos that were farther along in development; therefore, only Stage A embryos were analyzed. Only lipid droplets that were a minimum size of 10 µm2 were measured due to tracing accuracy and visibility.

3.2.3.2. Image processing

Embryo images were processed in Fiji (ImageJ) software. Contrast was optimized and a scale was set for each image. For each fertilized egg, we measured: length (µm); width (µm) at the middle of its length; number of lipid droplets; and areas (µm2) of individual lipid droplets.

Table 3.1. Date, site information, and mean measurements (+ SE) from fertilized eggs of sea lice collected from commercial Atlantic salmon. Each egg string corresponds to an individual gravid female louse.

Date Site Egg Eggs (n) Egg Area (µm2) No. Lipid Lipid Droplet Lipid Collected Strings (n) Droplets Area (µm2) Area/Egg (mm.dd.yy) 10.30.18 Machiasport 7 10 (2.8) 13109 (787) 15 (1.5) 2682 (180) 0.21 (0.02) 11.5.18 Eastport 2 18 (14) 14114 (2057) 16 (6.5) 2327 (634) 0.16 (0.02) 12.5.18 Eastport 2 7 (3.5) 13178 (474) 16 (2.5) 2769 (87) 0.21 (0.00) 5.2.19 Machiasport 14 14 (2.5) 14598 (656) 27 (2.7) 4792 (465) 0.32 (0.02) 6.19.19 Machiasport 17 19 (4.5) 14099 (399) 22 (1.7) 3474 (210) 0.25 (0.02) 7.10.19 Machiasport 29 7 (1.0) 13288 (434) 21 (1.3) 3287 (236) 0.25 (0.01) 8.13.19 Machiasport 24 6 (1.3) 12686 (357) 23 (1.7) 3022 (206) 0.24 (0.01) 10.18.19 Eastport 12 9 (2.3) 13216 (714) 25 (2.5) 3547 (311) 0.27 (0.02) 11.15.19 Eastport 9 10 (2.2) 12189 (688) 22 (3.3) 2915 (420) 0.23 (0.03)

Table 3.2. Sample sizes and mean heat capacities (+ SE) for monthly collections in 2019.

Month Egg Mean Cp SE Collected Site Strings (n) (J/ gºC) (J/gºC) May Machiasport 8 2.83 0.69 June Machiasport 31 4.61 0.62 July Machiasport 40 5.97 0.58 August Machiasport 37 11.58 1.29 October Eastport 40 8.00 0.89 November Eastport 40 4.20 0.62

Egg area was calculated assuming an ellipsoid shape using the following formula: A= π

(length/2) x (width/2). Due to the range of shapes, area of each lipid droplet was manually measured using the “Freehand selection” tool.

All data were analyzed using statistical packages in JMP 14.0 from SAS®. Means (+ SE) were calculated for egg areas and lipid quantities across embryos to statistically compare individual egg strings, representing individual female lice. Lipid area/egg data were arcsine transformed for analysis. We found no significant differences in embryo size nor lipid quantities between paired egg strings after running one-way ANOVAs with Tukey’s HSD post hoc test

(alpha level = 0.05); therefore, we sampled one string per gravid female. In addition, we did not find consistent differences in the majority of metrics between sampling sites. For monthly and seasonal analyses, we ran Bartlett’s and Shapiro-Wilk tests for equal variances and normality, respectively, and conducted one-way ANOVAs with Tukey’s HSD tests. Welch’s correction was applied when the assumption for homogeneity of variance was not met. The alpha level was set at 0.05 in all cases. Seasons were defined as spring: May 2019; summer: July – August 2019; fall: October – November 2018 and 2019; and winter: December 2018.

3.2.4. Daily thermal energy sampling

A portion of egg strings that were collected in July, August, October, and November

(2019) were maintained for thermal energy assessments at a daily scale. For each month, egg strings were placed in one 1000-ml beaker (Pyrex) filled with aerated natural seawater in a refrigerated incubator (Thermo Scientific, Precision Model 815). Egg strings were kept at 10 +

0.5°C on a 12:12 h light:dark cycle. With respective sea lice collections (3.2.1) representing Day

0, each day post-collection, beakers were swirled and approximately 5 egg strings were

randomly sampled each day post-collection. Daily samples were stored frozen until further processing.

3.2.5. Calorimetry

A differential scanning calorimeter (TA Instruments, DSC 2500) was used to measure specific heat capacity of egg strings. The calorimeter was calibrated using sapphire as a Cp standard due to its high stability and purity. Egg strings were thawed and placed on filter paper to remove excess water. A standard aluminum pan and lid (TA Instruments) were weighed, one egg string was positioned in a coil in the pan, and sample weight was measured. For daily analyses, pooled egg strings were thawed and evenly distributed at the bottom of the pan. Each pan was hermetically sealed using a TZero Sample Press (TA Instruments) before placement in the DSC.

Each sample was heated from 0 – 12°C at a rate of 1°C/min and was run against an empty, sealed standard aluminum pan with continuous nitrogen flow. Cp (J/g°C) was recorded for each sample pan across the temperature ramp.

® Cp values were analyzed in JMP 14.0 software from SAS . Cp was not significantly different between paired egg strings (nonparametric Wilcoxon rank-sum tests, alpha level =

0.05); therefore, one string from each gravid female was assessed. Additionally, there were no distinct spatial patterns in Cp between the two sampling sites. Approximately 40 egg strings were analyzed for each sampling date and mean (+ SE) heat capacity (J/g°C) was calculated for each month (Table 3.2). Data were not normally distributed (Shapiro-Wilk test) and nonparametric

Wilcoxon rank-sum tests were conducted for monthly and seasonal comparisons, with an alpha level of 0.05 for all analyses. Seasons were defined as spring: May; summer: June – August; fall:

October and November, and all seasons were in the year 2019.

3.2.6. Dual reserves

Within each month from May – November 2019, egg strings from approximately 10 gravid females were separated such that one string in each pair was assessed for lipid droplet quantities and the other was analyzed for Cp values. General linear models were run in JMP 14.0 to explore the effects of individual and combined lipid variables on Cp in these paired samples by month. Model parameters included egg area, number of lipid droplets, and arcsine-transformed lipid area/egg. The alpha level was set at 0.05 for all analyses.

3.3. Results

3.3.1. Embryo size

Mean embryo area remained consistent across months and seasons. However, lengths of fertilized eggs in May and June were longer than that in the proceeding October (p=0.006 and

0.02, respectively). Embryo length was generally longer in warmer months compared to colder months (Figures 3.2 and 3.3). Within collections, there was a relatively high level of variability

(approximately 100 µm) in embryo size across egg strings.

3.3.2. Number of lipid droplets

Fertilized eggs in May contained a higher number of lipid droplets than those in the previous October (p=0.04), with an average difference of 12 droplets. More broadly, spring 2019 had a higher number of lipid stores compared to fall 2018 (p=0.006). Numbers of lipid stores remained similar throughout the fall and late winter of 2018, as well as the summer through fall of 2019.

450 Grand Mean A

A AB 400 AB AB AB AB m)

! AB B

350

Mean Egg Length ( 300

250

Oct Nov Dec May Jun Jul Aug Oct Nov 2018 2019 Collection Month/Year Figure 3.2. Mean length (µm) of L. salmonis embryos. Standard error is presented when sample sizes allow. Different letters indicate significant differences (p<0.05) between months.

3.3.3. Lipid area

Individual lipid droplet areas were highly variable and average values did not adequately represent collective egg strings; therefore, total lipid droplet areas were compared among embryos. Mean lipid area was greatest in May and differed from that of the preceding October, as well as the following summer months and November (Figure 3.4). In May, lipid stores comprised approximately one-third of total embryo area, which was double the lipid area/egg in

November 2018 (Table 3.1). Lipid areas did not differ between any respective months in fall

2018 and 2019. Spring lipid areas were higher than those in the previous fall (p<0.0001), as well as the subsequent summer (p<0.0001) and fall (p=0.0008).

When each embryo area was accounted for, transformed lipid area/egg displayed the same pattern as in Figure 3.3. However, lipid area/egg in May did not differ from that in June nor

November 2019. Lipid area/embryo in the spring was greater than that of fall 2018, summer, and fall 2019 (p=0.0009, 0.002, and 0.04, respectively).

a. b.

Figure 3.3. Histological sections of sea lice eggs from a. May 2019 and b. November 2019. Arrows point to exemplary proxies for lipid droplets. For both micrographs, scale bar = 100 μm, and magnification= 100x.

8000 A Grand Mean

7000

6000

B AB m^2) B

! 5000 B B

4000 B AB AB 3000 Mean Lipid Area ( Mean Lipid Area

2000

1000

Oct Nov Dec May Jun Jul Aug Oct Nov 2018 2019 Collection Month/Year Figure 3.4. Mean lipid area (µm2) of sea lice embryos. Standard error is presented when sample sizes allow. Different letters indicate significant differences (p<0.05) between months.

3.3.4. Monthly and seasonal thermal energy

Mean heat capacity was lowest in May and nearly doubled from July to August (Figure

3.5) (Table 3.2). Cp values then declined in October and November, and returned to levels that did not differ from those of the previous May (Table 3.3). The level of variability generally remained consistent from month to month, although standard error was approximately twice as large in August (Table 3.2). Heat capacities in the summer and fall were not significantly different, and summer Cp differed from that of the preceding spring (Z=2.700, p=0.007).

10 Heat Capacity (J/gºC)

May June July August October November Month Collected Figure 3.5. Heat capacities (J/g°C) of sea lice embryos collected from 2019. Raw data are displayed. Sample sizes are provided in Table 3.2.

3.3.5. Daily thermal energy

Heat capacity of embryos declined from the first to last sampling days in all months except for October, in which it increased by <1 J/g°C (Figure 3.6.b). Embryo Cp gradually declined each day post-collection in November, while it steadily increased before dropping on

Day 4 out of 5 in October (Figure 3.6.b). Thermal energy levels fluctuated in both July and

August, and patterns mirrored one another (Figure 3.6.a). Unlike in the fall, heat capacities in the summer drastically increased from penultimate to final sampling days (Figure 3.6). Cp values on

Day 1 were at least three times larger in summer months compared to fall months, and five times larger, at minimum, on final sampling days (Figure 3.6).

Table 3.3. Results from Wilcoxon comparisons of monthly heat capacities. *Indicates significance.

Score Mean Hodges- Lower Upper Level - Level Diff. SE Diff. Z p-Value Lehmann CL CL Aug Jun 21.16 4.81 4.40 <0.01* 5.18 3.00 8.35 Aug May 18.55 5.12 3.63 <0.01* 6.75 3.31 12.88 Aug Jul 18.31 5.10 3.59 <0.01* 4.10 1.68 6.91 Oct May 14.03 5.42 2.59 0.01* 4.17 1.03 8.39 Oct Jun 13.08 4.94 2.65 0.01* 2.60 0.72 5.07 Jul May 12.98 5.42 2.39 0.02* 2.66 0.41 4.57 Jul Jun 9.39 4.94 1.90 0.06 1.30 -0.06 2.63 Oct Jul 7.33 5.20 1.41 0.16 1.30 -0.55 3.67 Jun May 5.98 4.52 1.32 0.19 1.23 -0.96 3.50 Nov May 2.63 5.42 0.48 0.62 0.80 -1.44 2.76 Nov Jun -4.35 4.94 -0.88 0.38 -0.55 -1.93 0.57 Oct Aug -10.02 5.10 -1.96 0.05* -2.80 -5.59 0.03 Nov Jul -14.03 5.20 -2.70 0.01* -1.96 -3.20 -0.63 Nov Oct -18.00 5.20 -3.46 <0.01* -3.22 -5.50 -1.13 Nov Aug -24.74 5.10 -4.85 <0.01* -5.88 -8.57 -3.65

Figure 3.6. Heat capacities (J/g°C) of embryos sampled daily from collections in a. Summer: July and August, and b. Fall: October and November. Sampling began 24 h after respective monthly collections. August a. July

10 Heat Capacity (J/gºC)

0 1 2 3 4 5 6 7 8 9 10 b. Day October November

10 Heat Capacity (J/gºC)

0 1 2 3 4 5 6 7 Day

3.3.6. Dual reserves

General linear models revealed no significant correlations between lipid quantities and thermal energy content, nor egg size and thermal energy (Figure 3.7). P-values for parameter estimates ranged from 0.12 to 0.77 across all models.

a. b.

c. d.

Figure 3.7. Regressions of egg and lipid metrics and heat capacity (J/g°C) of paired embryos sampled in July 2019. Explanatory variables include mean: a. egg area, b. number of lipid droplets, c. lipid area/egg, and d. total lipid area. Pink areas indicate 95% confidence intervals and blue lines represent null hypotheses of no correlation between variables.

3.4. Discussion

3.4.1. Lipid droplet profiles

As the first study to profile seasonal lipid droplet quantities in sea lice embryos, these data highlight peaks in all examined lipid metrics in May, as well as consistent minima throughout the preceding fall and winter. The timing of these indicators of high reproductive investment from maternal sea lice coincides with the beginning of typically observed surges in infection on salmon farms. Specifically, under biologically favorable conditions that begin to

manifest in the spring and with high food availability, gravid females appear to invest the highest level of lipid stores in their growing oocytes.

Conversely, given reduced lipid quantities in embryos throughout the late fall and winter, adult females may retain and metabolize their own lipids to survive harsher conditions leading up to the spring. In addition to providing nourishment, lipid stores play a key role in buoyancy, which may be particularly crucial when lice are conjectured to overwinter at depth under warmer temperatures (Johnsen et al., 2014; á NorDi et al., 2015). Unlike a variety of other copepod species, L. salmonis lipid reserves are predominantly comprised of more dense triacylglycerides rather than more buoyant wax esters (Hagen, 1999), which may aid in downward migration.

Maternal L. salmonis may likewise utilize her own lipid stores to locate a suitable host and/or regenerate gonads during the winter period (Halvorsen, 2015). Alternatively, sea lice may use all of their food sources for growth and general maintenance in the winter, rather than store them as lipid reserves to begin with, as demonstrated by other zooplankton (Lee et al., 2006).

In most cases, summer lipid metrics resembled those in the fall more so than those in the spring, further highlighting the month of May. Although local sea lice infection prevalence and intensity generally remain high throughout the summer, the boost in reproductive investment in the spring appears to adequately support embryonic development through the following months, avoiding the need for a second wave of distinguished lipid allocation to the fertilized eggs. This peak in transferred lipid reserves provides sustenance for future nauplius and copepodid larvae, allowing them to remain in the plankton longer before attaching to a host for active nourishment

(Costello, 2006), particularly throughout months that present optimal conditions for sea lice development (Boxaspen, 2006; Jones and Johnson, 2015; Samsing et al., 2016).

Egg length conclusions from this study are in partial agreement with previous evidence that spring embryos tend to be larger than those in colder seasons (Heuch et al., 2000; Costello,

2006). In the current study, L. salmonis embryos in the spring were longer than those in early fall

2019, but did not differ from those in late 2018. Furthermore, with the incorporation of embryo width, embryo area did not differ across collection months, and three-dimensional analysis of egg size may prove useful in future investigations.

Lipid droplets in sea lice embryos are distributed in a range of patterns, with a relatively high level of variability across egg strings. A portion of the embryos in this study contained one or two large droplets that were located centrally and/or anteriorly or posteriorly, while others featured many small droplets that were evenly dispersed. Assessing intrapopulation variability in lipid quantities and studying at the level of the individual provide insight on population fitness

(Narcy et al., 2009), and these methods are applicable to other lecithotrophic copepods. Due to the relatively high variability across individuals in the current pilot study, future research may be conducted at a finer temporal scale and incorporate greater sample sizes across collections.

Although preliminary analysis did not reveal differences in lipid quantities between collections in the beginning and middle of June 2019, the effects of varying water parameters warrant investigation, as both temperature and photoperiod, likely among others, influence the reproductive output of sea lice (Ritchie et al., 1993).

The detailed mechanism behind lipid transfer from maternal L. salmonis to its embryos remains unclear. Females may modify their lipid stores or directly transfer them to oocytes (Pond et al., 1996), or employ a combination of methods according to environmental factors and individual condition. In laboratory settings, adult female L. salmonis are able to continuously extrude up to 11 pairs of egg strings after fertilization (Hamre et al., 2009). Generation number likely affects maternal trade-offs, as females in later reproductive cycles are expected to invest all of her lipid stores in her embryos prior to death (Halvorsen, 2015). In addition, complementary measures of reproductive success, such as the number of fertilized eggs produced per batch, hatching and survival rates through the infective copepodid stage, and other measures of egg viability warrant further attention (Kiørboe et al., 1988; Ianora et al., 1992;

Poulet et al., 1995).

3.4.2. Thermal energy profiles

These findings suggest that thermal energy in sea lice embryos peaks in August, aligning with the beginning of the window when local infection prevalence and intensity are typically the highest of the year (Jones and Johnson, 2015; Frederick, 2018). More broadly, the summer season yielded the highest mean Cp values, indicating that maximal energy content was associated with environmental parameters (particularly temperature) that are ideal for sea louse development and overall condition (Boxaspen, 2006; Jones and Johnson, 2015). Higher thermal energy levels that originate from maternal L. salmonis throughout the summer are likely required to fuel higher activity levels when conditions are biologically favorable. Heightened reserve levels in embryos may support rapid growth and molting between larval stages, swimming behavior and survival in the plankton, and ultimately attachment to a host for the requisite switch to active feeding, before reserves expire.

Given that L. salmonis follows a universal marine ectotherm model of temperature dependence for several measures of reproductive output and growth (Samsing et al., 2016), it is assumed that metabolic rates are substantially lower in colder seasons. Under this supposition, maternal lice would likely invest lower thermal energy levels in embryos in the late fall and winter, as one unit of energy would last much longer before being metabolized. These data support this conjecture, as embryos exhibited lower thermal energy levels in the late fall compared to the summer. Furthermore, on a daily scale, Cp values began and terminated at higher levels in the summer compared to the late fall when temperatures were notably lower

(6°C average difference in 2019; NOAA CWTG), and daily fluxes in the summer were more drastic, covering a wider range of thermal energy values. Future investigations may incorporate winter embryos to determine whether Cp continues to decrease in the winter and rise to spring values, or plateaus through the colder seasons, or follows a different pattern.

It is unclear why embryos in July and August displayed mirroring patterns on Days 1 – 5 of analysis at the finer temporal scale; however, these initial decreases and increases in August matched those in the second half of the July sampling period, and a 10-day timeframe for all months would be beneficial in the future. Additionally, on the monthly scale in August, 12.5% of sampled embryos yielded notably higher heat capacities, resulting in the larger spread in Cp values compared to other collection months. These embryos were dispersed across calorimeter trial dates and did not exhibit trends in sample weight; a possible explanation could be wider variety in exact developmental status or a higher degree of generational overlap, which could not be visually distinguished prior to testing.

A mechanistic understanding of the link between thermal energy reserves and metabolic rate in L. salmonis warrants future attention. A reduction in fitness, and subsequent population

growth, would be expected if a high-latitude ectotherm were unable to compensate for the challenges associated with lower temperatures, restricted growing seasons, and severe seasonality (Kreiman et al., 2019). However, the parasite continues to demonstrate long-term ecological success on salmon farms in Maine. Although the cold-season strategy of L. salmonis remains ambiguous, survival may be due to strict energy conservation and lowered activity levels, given the possibility of incipiently limited energy content in egg-bearing females.

Alternatively, reduced thermal energy content in embryos under more challenging seasons may primarily be a result of maternal lice retaining their own energy reserves, rather than allocating it toward their eggs to begin with.

With an understanding of the behaviors that underlie a variety of biological systems, such as those documented in the current study, commercial DSC software will have increased capacity to provide more relevant tools that facilitate analysis and require less customization by the individual researcher (Prislan et al., 2019). DSC has the power to provide innovative data that synthesizes structural thermodynamics and systems biology, in which the objective is to discover emerging features that arise from the systematic perspective of a living structure (Gill et al.,

2010). In the context of the current study system, through a novel thermodynamic lens, these data contribute to an improved understanding of embryonic L. salmonis physiology and success amidst seasonal change. Specifically, thermal energy profiles are quantitative characterizations of biophysical condition that provide a unique opportunity to forecast population fitness on salmon farms.

3.4.3. Concluding remarks: dual reserves

In conjunction, lipid stores and thermal energy reserves, in part, cover the timing when sea lice typically return to salmon farms in higher numbers and reach their uppermost infection

rates, respectively. Although endogenous reserves in the form of lipid droplets and thermal energy are connected in an overall map of maternal investment and metabolism, there does not appear to be a consistent, direct correlation between the lipid quantities in question and Cp. This may be partially explained by the divergent timing of respective maxima in these reserves, as lipid quantities in embryos are highest in May and thermal reserves peak three months later.

Given that lipids contain approximately twice the energy content of proteins and carbohydrates

(Lee et al., 2006) and comprised a large proportion of embryo area in May, the relatively low thermal energy levels that were observed in the spring were a surprising finding. However, the relative energy values across lipids that serve different functions are not yet mapped out. It is possible that phospholipids (or structural lipids) may be more energy-rich than storage lipids, and could follow a different annual cycle based on growth. For example, lice may have reached a terminal size by the late summer, potentially accounting for the demonstrated maximal heat capacity in August. Additionally, thermal energy samples were directly analyzed at the level of the egg string, containing more external cuticle and internal and external biological material in general, compared to the individual embryos that were assessed for lipid quantities.

An improved understanding of embryo condition is critical for proactive sea lice management, particularly given the large reproductive potential in paired egg strings (Boxaspen,

2006), and thus recruitment prospect (Halvorsen, 2015). Maternally derived reserves are considered the central indicators of embryo and larval condition, as they are finite and obligate nutritional resources prior to host attachment. While many recent epidemiological models enhance global aims for the integrated, practical management of sea lice (Johnsen et al., 2014;

Rittenhouse et al., 2016; Salama et al., 2016; Sandvik et al., 2016; Samsing et al., 2017), they require a suite of biological inputs that are ideally evidenced in vivo. Although the effects of

seasonal parameters are consistently applied across projected development as a whole, the influence of specific indicators that can be rapidly detected has yet to be applied. These lipid and thermal energetic dynamics play a chief role in partially encoding population fitness at the earliest life stages, providing a unique opportunity for substantial forecasting.

Altogether, a comprehensive biological understanding of L. salmonis begins at the egg stage, which is often overlooked relative to planktonic larval phases. With more multifaceted knowledge of energy budgets and condition across all life stages, particularly in the context of a changing environment, the increased efficacy of infection models will improve the integrated pest management approach for more sustainable salmon aquaculture.

CHAPTER 4

CHARACTERIZING THREE PROFILES

4.1. Discussion and future work

The research presented in this dissertation establishes stable isotopic and biophysical profiles of L. salmonis to enhance understanding of host-parasite relationships within broader trophic ecology and explore complementary indicators of seasonal embryo condition, respectively. More broadly, the dynamics of sea louse populations in Maine are currently underrepresented in the literature, and this work aims to inform the international community of sea lice researchers and industry partners.

Among the data chapters presented in this dissertation, Chapter 2 is unique given its broader ecological context and diverse composition of samples, including L. salmonis from eastern and western US coasts, A. foliaceus, three tissue types of both farmed and wild S. salar, and a compilation of previously existing fish endo- and ectoparasitic data from the past two decades. The meta-analysis presented in Chapter 2 suggests that trophic enrichment in fish host- parasite relationships does not conform to predator-prey standards that are assumed across the animal kingdom, which has critical implications for inclusion of parasites in trophic models. The most consistent pattern that was observed was endoparasitic depletion in d15N relative to hosts across all four taxa, and seven out of eight host tissue types, which is in agreement with conclusions by Pinnegar et al. (2001). This trend warrants further attention in order to establish the degree of inclusivity among endoparasitic relationships. The work presented in Chapter 2 expands upon the review by Pinnegar et al. (2001) by revealing that d13C enrichment likewise

diverges from its assumed 0 – 1‰ standard. Furthermore, d13C enrichment appears to be highly variable among parasitic taxa and feeding sites. Enrichment standards of 3.4‰ and <1‰ for d15N and d13C (DeNiro and Epstein, 1981; Minagawa and Wada, 1984; Post, 2002; Michener and Lajtha, 2007), respectively, perhaps warrant further attention themselves as parasites and other less traditional animal predators are explored. These standards were principally calculated as average values and applied in a broad manner, yet many complex factors affect isotopic enrichment, including not only species and consumer diet, but environment (terrestrial, freshwater, or marine), feeding mode (Thieltges et al., 2019), and metabolic pathways that may adjust according to nutrient availability (Pinnegar et al., 2001).

Results from the SIA case study in Maine suggest that, among two fish host-ectoparasite relationships, neither d15N nor d13C enrichment conforms to the standards that are generally assumed across the animal kingdom. Furthermore, enrichment patterns of both d15N and d13C varied between the two host-parasite interactions. Although both L. salmonis and A. foliaceus exhibited a mix of d13C enrichment, equivalence, and depletion relative to their respective hosts, their d15N discrimination patterns differed. L. salmonis was enriched in d15N by an average of

2‰ compared to farmed salmon, while d15N values of A. foliaceus were equivalent to those of its host for the majority of feeding sites. The relatively high degree of mobility of adult sea lice and common fish lice introduces the confounding factor of host hopping. Given that the parasites presented here were collected from the field in both farmed and wild contexts, it was not possible to account for the timing of feeding nor the potential for signal representation from multiple salmon. Future research in the region may build upon the work by Dean et al. (2011), incorporating sea lice cultivation in the lab and infection trials, and documenting isotopic signals through a detailed time lapse for finer temporal analysis.

Given these findings and the fact that A. foliaceus and L. salmonis are closely related within the overall animal kingdom, feed on the same host, and utilize similar life strategies, it appears unlikely that a single pattern in d15N or d13C enrichment may be accurately applied across ectoparasites as a whole. These parasitic species also exhibit vastly different physiological tolerances that may, in part, explain differences in enrichment patterns. Stable isotope analysis of parasitic relationships must be finely tuned, as it inherently requires a meticulous understanding of the individual signals of the host and parasite prior to deducing discrimination factors and the variables that influence them. The current study demonstrates the challenge of obtaining this information in full, as the work presented here would benefit from wild Pacific salmon tissue and sea lice from wild Atlantic salmon to complete each parasitic relationship and address additional questions, such as the unknown comparison between L. salmonis signals in farmed and wild salmon in Maine. If we are to infer new enrichment standards among parasitic relationships in the future for inclusion in bioenergetic and other ecosystems models, stable isotope analysis must continue to expand its inclusivity across species.

Chapter 3 revealed that lipid quantities in local L. salmonis embryos change seasonally, with a clear emphasis on the month of May. Both the number of lipid droplets and lipid area per egg were highest in May, which is typically a defining time of the year in sea louse population dynamics (Jones and Johnson, 2015; Frederick, 2018). With warming conditions in the spring, sea lice tend to return to the upper layers of the water column and infection rates begin to surge on salmon farms, after largely remaining lower in the winter. It is beneficial for maternal lice to invest these maximal lipid quantities in embryos in the spring, at the beginning of the window when environmental conditions are favorable for larvae to develop in the plankton (Boxaspen,

2006; Jones and Johnson, 2015). Interestingly, summer lipid quantities were closer to those in

the fall than in the spring, suggesting that one substantial wave of lipid investment in the spring may be more effective than extended allocation in smaller quantities to fuel high levels of activity throughout the summer. Sea lice follow universal trajectories of temperature dependence in marine ectotherms (Samsing et al., 2016), and the consistent minima in lipid metrics in the late fall and winter support the assumption that the metabolism of L. salmonis is lower in colder seasons (Jones and Johnson, 2015). It is likely that lower quantities of reserves are needed to support lower activity levels in the late fall and winter.

Cook et al. (2010) examined lipid quantities in aging copepodids under consistent laboratory conditions, and demonstrated that droplet volume did not follow a straightforward decline throughout time. Accordingly, Cook et al. classified copepodids into early, mid, and late stages based on lipid volume and infective capability. Future investigations of embryonic lipid reserves on a daily scale may also conclude that embryos fall into specific classifications according to condition, and ultimately hatching success. Compared to the three-dimensional approach with confocal laser microscopy that was implemented by Cook et al., the methods presented in Chapter 3 are less time- and energy-intensive and higher-throughput. Additionally, histological workspaces are relatively widespread among laboratories and require less training to operate. Future research will ideally elucidate the mechanism of lipid transfer from maternal lice to embryos, and quantify these metrics from egg-bearing adults through the subsequent free- living copepodid stage under progressing seasons. Additional indices of fecundity warrant regional attention, as it is suggested that there is a reproductive trade-off between the number of eggs per egg string and egg size (Pond et al., 1996; Samsing et al., 2016). Previous analyses have demonstrated that fertilized eggs are larger and less numerous in the spring, while the opposite is true for winter embryos (Ritchie et al., 1993; Pond et al., 1996; Heuch et al., 2000). The majority

of these studies implemented one-dimensional analysis that was estimated from total egg string length, however. Egg lengths that were assessed in Chapter 3 partially support previous conclusions, although at the level of two-dimensional analysis, egg areas remained consistent across seasons.

Although lipid stores are perhaps the most critical known indicator of embryonic and larval condition (Witter and Cuthill, 1993; Pond et al., 1996; Alonzo et al., 2001; Grote et al.,

2011), they comprise one portion of an overall energy budget. Chapter 3 additionally unveils thermodynamic profiles of embryonic sea lice from the spring through late fall. Unlike conclusions regarding lipid reserves, thermal energy in the form of Cp reached a maximum in

August, during which local conditions are generally optimal for sea louse biology and infection

(Heuch et al., 2000; Boxaspen, 2006; Jones and Johnson, 2015). Higher Cp values in the summer are advantageous for sea lice across life stages, as developmental and metabolic rates of L. salmonis in the Bay of Fundy are affected by temperature (Jones and Johnson, 2015), much like other marine ectotherms (Samsing et al., 2016). These available energy reserves may be directly used for successful hatching, growth, and molting in the case of embryos and nauplii, host seeking and attachment at the copepodid stage, and feeding and reproduction for maternal lice.

Prior studies of energy content in copepods have employed bomb calorimetry to quantify reserves (Salonen et al., 1976; Tucker et al., 2000). However, bomb calorimeters require a very large sample size of several hundred animals for each trial when analyzing small invertebrates

(Snow, 1972; Salonen et al., 1976), presenting a logistical hurdle that is compounded by the particularly small sizes of embryos and larvae. Differential scanning calorimetry, on the other hand, requires less than 1 g of sample for each trial. Furthermore, bomb calorimetry provides an estimation of energy content (Tucker et al., 2000), while DSC enables high-precision, direct

energy output (Harvey et al., 2018) with high repeatability (Yu et al., 2017). Tucker et al. (2000) demonstrated that energy levels in copepodids declined dramatically between Days 1 and 2, and

5 and 7, post-molt. Paired with copepodid settlement experiments, Tucker et al. exhibited that settlement differed between summer and winter temperatures on Days 1 – 3 and Day 7. Daily analysis of thermal energy in Chapter 3 demonstrated similarly unpredictable changes in Cp levels, rather than a straightforward decline in reserves. While Tucker et al. conjectured that increased carbon proportions resulting from molting led to apparent increases in energy levels, organic carbon theoretically remained constant in embryos from the current study; instead, population-level variability most likely facilitated rises in heat capacity with elapsed time. Future investigations will ideally incorporate a higher degree of replication for assessments at a daily scale. Additionally, much like prospective investigations of lipid reserves, an understanding of thermal energy stores from egg-bearing females through successive larval stages would prove useful in order to identify vulnerable points in the life cycle. Reversing the temperature ramp and gradually cooling samples down to winter temperatures may additionally provide insight on cold tolerance and energy content in L. salmonis, as has previously been demonstrated in tardigrades and diapausing copepods (McAllen and Block, 1997; Hengherr et al., 2009).

Werner (2007) summarizes three approaches to understanding systems biology, each of which informs biophysical function in unique manners. Each approach entails a different level of organization, broadly including simple single-celled systems, genomic regulatory networks, and higher-level networks. Thermodynamic analysis at the level of the organism encompasses the highest-level approach, in which networks are collectively assessed at once. Although this approach is the most encompassing, its challenge is that results may be the most abstract to interpret, despite heavily quantitative data collection. In addition, the field of differential

scanning calorimetry is still developing how the understudied biological components across systems may smoothly be incorporated into commercial software (Prislan et al., 2019). In the act of applying organismal-level data to the population level, according to Slobodkin (1960), “it only remains for the ecologist...to develop her theories and concepts on a biological basis rather than by assuming the direct applicability of the laws developed for the simple systems of physics and electronics.” However, after output is customized to the research context, the resulting knowledge of thermodynamic properties, and how they change over time and under different conditions, is useful in accurately predicting biological function (Akinpelu et al., 2017).

Obligate lecithotrophs offer a unique opportunity to study a closed system with finite reserves that theoretically decline over time. Semi-quantitative assessment of lipids and quantitative analysis of thermal energy content offer complementary approaches to understanding embryonic condition and how it changes seasonally. An intriguing takeaway from this dissertation is that the data from Chapter 3 suggest that these two forms of endogenous reserves convey independent yet conceptually related stories. After general linear models were run, to explore potential effects of individual and combined lipid variables on Cp, there were no significant correlations between lipid quantities and thermal energy. However, results from

Chapter 3 suggest that these reserves both provide sustenance during the seasons that are associated with the highest sea louse activity. Maximal lipid metrics during the month of May align with the typically observed beginning of infection blooms on salmon farms. These stores may fuel longer-term activity that encompasses development and ultimately host seeking at the final larval stage. On the other hand, embryos contained the highest thermal energy content in

August, when the metabolic rate of L. salmonis is likely at its highest due to ideal environmental conditions (Jones and Johnson, 2015; Samsing et al., 2016). Given this timing, endogenous

reserves in the form of thermal energy may provide more immediately utilized support for larval activity that occurs under environmental parameters that are the most biologically favorable for the species. After observing a lack of direct correlation between these lipid and thermal energy reserves, each investigation would pair well with a concurrent development study in the future.

One egg string from each pair may be assessed for either lipid quantification or thermal energy, while the other may be cultured in conditions that mimic ambient seasonal parameters, with survival traced from hatching through the copepodid stage. The degree to which each type of reserve influences overall condition, via direct survival rates, would provide critical insight to elevate these independent studies.

Lipid stores and thermal energy comprise two components of a larger parasitic energy budget that must be modulated in a changing climate. Based on developmental and reproductive conclusions in previous literature (Boxaspen, 2006; Heuch et al., 2000; Hamre et al., 2009; Jones and Johnson, 2015; Samsing et al., 2016) and the energy reserve data from this research, each component of these energy budgets is phenologically influenced. High-latitude organisms must be particularly adept at compensating for the effects of challenging conditions on energy allocation. Although it is grounded in terrestrial ectothermy, the “climatic variability hypothesis” states that animals at higher latitudes require a wider range of tolerances and/or greater acclimation aptitude in order to survive at a given site (Kreiman et al., 2019). Sea lice in Maine are a cold-adapted regional population due to their modified physiology from season to season, as further evidenced by the current studies, and their unwavering ecological success on salmon farms in the northernmost areas of the state.

Although the detrimental effects of sea lice have been well documented for several decades, Lepeophtheirus salmonis remains the primary economic hurdle of Atlantic salmon

aquaculture because of its ability to adapt and overcome diverse anti-parasitic tactics. These strategies range from the immune responses of salmonid hosts, both wild and farmed, to the suite of control measures that the salmon industry employs to continuously withstand parasite levels.

As a result, an “arms race” between sea lice and salmon, in conjunction with the influence of human decision, continues to evolve. Integrated pest management on aquaculture sites will utilize a suite of biological, physical, chemical, and proactive mathematical tools that are continuously being enhanced by the growing international community of sea lice researchers.

Overcoming the parasite with longer-term success requires a comprehensive understanding of the biology of the species itself—particularly in its vulnerable, early life stages, from the understudied embryo through the infective copepodid. The current studies provide new and diverse stable isotopic profiles across species and regions, as well as novel characterizations of sea louse biophysical condition at the earliest life stage. These data and future research will ideally expand our understanding of physiological condition, particularly via embryonic quality and how it may be quantitatively assessed, in order to improve sea lice infection models that require biologically accurate inputs for effective forecasting. More broadly, continued innovations in sea lice ecophysiological research will uncover the multifaceted tactics that underlie the ecological success of this adaptable species.

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BIOGRAPHY OF THE AUTHOR

Emma Taccardi was born in Pusan, South Korea on July 8, 1992. She grew up in

Rochester, New York and graduated from Pittsford Sutherland High School in 2010. She attended Hamilton College and graduated in 2014 with a Bachelor’s degree in Biology and a minor in Music, and spent an undergraduate semester at the Duke University Marine Laboratory in Beaufort, North Carolina. After graduating, Emma was a coastal restoration intern for The

Nature Conservancy on Block Island, Rhode Island, and a hydroecological engineering intern at the Lawrence Berkeley National Laboratory in Berkeley, California. She began her graduate program at the University of Maine in the fall of 2015. Emma is a candidate for the Doctor of

Philosophy degree in Marine Biology from the University of Maine in August 2020.