An Examination of Possible Maternal Effects Due to Parasite and Density Stress on the Mealworm Beetle, Tenebrio Molitor

An Examination of Possible Maternal Effects due to Parasite and Density Stress on the Mealworm Beetle, Tenebrio molitor

Maria C. Bennell

A thesis submitted in conformity with the requirements for the degree of Master of Science Department of Ecology and Evolutionary Biology University of Toronto

An Examination of Possible Maternal Effects due to Parasite and Density Stress on the Mealworm Beetle, Tenebrio molitor

Maria C. Bennell

Master of Science

Department of Ecology and Evolutionary Biology University of Toronto

2011 Abstract

Few empirical studies examine the influence that the maternal parasite environment can have on offspring fitness (maternal effects) in invertebrates. Several recent studies have found that mothers can adjust offspring phenotype to counter the negative effects of parasite infection. In this thesis I subjected the parental generation of the host species, Tenebrio molitor (Insecta:

Coleoptera), to a high parasite, high density, or control treatment. Offspring were subsequently subjected to either the same stress, the alternate stress, or to the control, and fitness-related life history traits were measured in both generations. The results from this thesis do not support the hypothesis that T. molitor mothers influence offspring fitness in a positive way. Instead, maternal effects led to a reduction in offspring fitness under both types of stress. At least under some environmental conditions, females invest in their fitness at the expense of their offspring.

Acknowledgments

I would like to thank my supervisor, Rob Baker, for his expertise, knowledge, and financial support. Thank you Rob, your ability to turn my incoherent ramblings into coherent statements is truly a gift! Thank you to my other committee member, Locke Rowe, and my thesis defence examiners, Megan Frederickson, Maydianne Andrade, and Helen Rodd for their feedback and intellectual input. Helen, thanks for being such an amazing professor. You have had such a positive impact on my graduate and undergraduate experience. Thanks to Tonia Robb for help in the early stages of my project, and to Christopher Yourth for his help with my experimental design, getting my experiments started, and for his personalized stats lectures. Chris, I can‟t tell you how useful our chats about science and stats have been to me.

This thesis would not have been possible without the help of many undergraduate laboratory assistants and volunteers, especially Ali Feroz and Melissa Apostoli for taking on so much of the stress in the lab. Thank you to my fellow graduate student friends of past and present, especially Mersedeh Safa, Meghna Roy, Dorina Szuroczki, Crystal Vincent, Brie

Edwards, Caren Scott, Anna Price, Maggie Neff, Monica Granados, Meg St John, Bronwyn

Rayfield, and Cameron Weadick. My experience at U of T has been so much brighter having known and worked with you. Thanks for all the chats, fun, food, and Rum Wednesdays. I‟m going to miss you all terribly.

I would like to thank my parents, Bernard and Christina Bennell for their unbelievable support, and especially for feeding me as I wrote my thesis because I would never have survived through this on take-out. Thanks to my siblings, Sean and Kevin Bennell, and Marissa Largo for their encouragement, and to our family cat, Lulu, for all the fuzzy breaks (yes, I did thank my cat). To my best friends Barb Colonna and Kate Rogucka, thanks for your unwavering faith in iii my abilities. Last but not least, thank you to Ramtin Samie for motivating me and for keeping me smiling. I couldn‟t have done this without you.

Table of Contents Thesis Abstract………………………………………………………………………… ii Acknowledgements……………………………………………………………………. iii Table of Contents……………………………………………………………………… v List of Tables…………………………………………………………………………… viii List of Figures………………………………………………………………………….. ix List of Appendices……………………………………………………………………… x

Introduction………………………………………………………………………….... 1 Importance of Parasite-Mediated Maternal Effects……………………………. 3 Immune Priming within a Single Generation…………………………………... 4 Trans-generational Parasite Studies……………………………………………. 5 Current Study…………………………………………………………………... 7

Methods………………………………………………………………………………... 9 Host System…………………………………………………………………….. 9 Parasite System…………………………………………………………………. 11 Appropriateness of System……………………………………………………... 12 Parasite Manipulations………………………………………………………….. 13 Clearing Existing Gregarine Infections………………………………… 13 Parasite Source Populations…………………………………………… 13 Parasite Infection Procedure...... 14 Experimental Design……………………………………………………………. 15

Grandparental generation (F-1)………………………………………… 15

Maternal Generation (F0)………………………………………………. 17

Offspring Generation (F1)………………………………………………. 20 Overview of Statistical Analyses……………………………………………….. 22

Maternal Generation (F0) Analyses…………………………………….. 22

Offspring Generation (F1) Analyses…………………………………….. 23 Statistical Analyses…………………………………………………………….... 24 Larval Development…………………………………………………….. 24 Survival…………………………………………………………………. 24 v

F1 Larval Growth……………………………………………………….. 24 Timing of Eggs………………………………………………………….. 25 Adult Female Death…………………………………………………….. 26 Total Egg Number………………………………………………………. 26 Egg Size…………………………………………………………………. 26

Results…………………………………………………………………………………... 27 Larval Development…………………………………………………………….. 27

F0 Larval Development…………………………………………………. 27

F1 Larval Development…………………………………………………. 27

F1 Larval Development: Parasite Analysis……………………………... 28

F1 Larval Development: Density Analysis………………………………. 28 Survival………………………………………………………………………….. 29

F0 Survival……………………………………………………………….. 29

F1 Survival……………………………………………………………….. 29

F1 Survival: Parasite Analysis…………………………………………… 29

F1 Survival: Density Analysis……………………………………………. 30 Larval Growth…………………………………………………………………… 30

F1 Larval growth………………………………………………………….. 30

F1 Larval Growth: Parasite Analysis…………………………………….. 31

F1 Larval Growth: Density Analysis……………………………………... 31 Reproduction Analyses…………………………………………………………... 32 Timing of Eggs…………………………………………………………………… 32

F0 Timing of Eggs………………………………………………………… 32

F1 Timing of Eggs: Parasite Analysis……………………………………. 33

F1 Timing of Eggs: Density Analysis…………………………………….. 33 Adult Female Death……………………………………………………………… 33

F0 Adult Female Death…………………………………………………… 33

F1 Adult Female Death: Parasite Analysis……………………………… 33

F1 Adult Female Death: Density Analysis……………………………….. 34 Total Egg Number………………………………………………………………... 34

F0 Total Egg Number…………………………………………………….. 34

F1 Total Egg Number: Parasite Analysis………………………………… 35

F1 Total Egg Number: Density Analysis…………………………………. 35 Egg Size………………………………………………………………………….. 36

F0 Egg Size……………………………………………………………….. 36

F1 Egg Size: Parasite Analysis…………………………………………… 37

F1 Egg size: Density Analysis…………………………………………….. 37

Discussion………………………………………………………………………………… 38 Parasite Stress…………………………………………………………………….. 39 Impact of Parasites within a Single Generation of Hosts………………….. 42 Trans-generational Impact of Parasites on Hosts………………………… 43 Limitations of my Findings………………………………………………... 45 Density Stress…………………………………………………………………….. 46 Impact of Poor Environment………………………………………………. 47 Increase in Fecundity…………………………………………………….. 49

Mothers Faced with Different Types of Environmental Stress do not Adjust Offspring Phenotype for the Future Environment in Similar Ways………………………………………………………………. 51

Literature Cited…………………………………………………………………………… 54

vii

List of Tables

Table 1: MANOVA summary table for the offspring generation larval development. Comparison of parasite and control treatments…………… 62

Table 2: Repeated measures ANOVA summary table for the offspring generation larval growth. Comparison of parasite and control treatments………………………………………………………………… 62

Table 3: Repeated measures ANOVA summary table for the offspring generation larval growth. Comparison of density and control treatments…………………………………………………………………. 63

Table 4: Repeated measures ANOVA summary table for the offspring generation timing of eggs. Comparison of parasite and control treatments…………………………………………………………………. 63

Table 5: Repeated measures ANOVA summary table for the offspring generation timing of eggs. Comparison of density and control treatments………………………………………………………………… 64

viii

List of Figures

Figure 1: Experimental design predictions of the interactions

between the maternal (F0) and offspring (F1) generations……………………… 65

Figure 2: Gregarine infection procedure………………………………………………….. 65

Figure 3: Experimental schedule………………………………………………………….. 66

Figure 4: Analyses, including treatment combinations F0D F1P and F0P F1D……………. 67

Figure 5: Analyses, excluding treatment combinations F0D F1P and F0P F1D…………… 68

Figure 6: Effect of stress history (F0) on offspring development time for parasite vs. control treatments………………………………………… 69

Figure 7: Effect of treatments on larval survival in the maternal and offspring generations……………………………………………………… 70

Figure 8: Effect of time and treatments on offspring larval growth………………………. 71

Figure 9: Time for offspring exposed to current stress treatments (F1) of control vs. density to lay 50% and 100% of their eggs…………………… 71

Figure 10: Effect of treatments and body size on offspring total egg number for control vs. density treatments…………………………………………. 72

List of Appendices

Appendix A……………………………………………………………………………….. 73 1: Means, standard errors (s.e.), and sample sizes (n) for all

F0 generation analyses…………………………………………………….. 73

2: Means, standard errors (s.e.), and sample sizes (n) for all

F1 generation parasite vs. control analyses…………...... 74

3: Means, standard errors (s.e.), and sample sizes (n) for all

F1 generation density vs. control analyses………………………………… 78

x 1

Introduction

An individual‟s phenotype is the product of its own genotype and the interactions of those genes with the environment it experiences during development. In addition, an individual‟s phenotype can also be influenced by the environmental experiences of its mother (Mousseau & Fox 1998a).

The influence of maternal genotype or environment on offspring phenotype is known as a maternal effect (Mousseau & Dingle 1991; Mousseau & Fox 1998b), and occurs through one or both of the following routes: 1) indirect genetic effects or 2) indirect environmental effects.

While mothers directly contribute one half of the additive genetic effects that influence offspring phenotype, they also contribute indirect genetic effects, in that the genes that determine the maternal environment indirectly determine offspring phenotype and fitness (Moore et al. 1998).

Indirect environmental effects occur when non-genetic influences of the maternal environment indirectly determine offspring phenotype and fitness (Lacey 1998). These inter-generational effects are thought to be transmitted via abiotic, nutritional (e.g. egg provisioning), or other ecological aspects of the maternal environment (Rossiter 1996; Rossiter 1998; Wolf & Wade

2009). Maternal effects can be adaptive if they increase maternal fitness (Marshall & Uller

2007), and maternal effects may influence population dynamics through their contribution to population size and growth potential, thus, a population‟s response to an environmental change may be time-lagged (Rossiter 1994).

Mothers can adjust offspring phenotype according to changes in the environment in a way that increases offspring fitness; I will refer to this class of maternal effects as “anticipatory maternal effects,” (Marshall & Uller 2007). Conversely, some changes in the environment can result in maternal effects that reduce offspring quality or performance, and this class of maternal effects will be referred to herein as “selfish maternal effects” (Marshall & Uller 2007). There are

2 several other classes of maternal effects, as outlined by Marshall & Uller (2007), but they will not be discussed here. Marshall & Uller (2007) stress that while maternal effects affect the fitness of both mother and offspring (e.g. offspring size is a phenotypic trait of both mother and offspring (Bernardo 1996b)), researchers should focus on the fitness consequences of maternal effects for mothers, since selection should maximize maternal fitness; anticipatory maternal effects increase maternal fitness by increasing offspring fitness, while selfish maternal effects increase maternal fitness at the expense of offspring fitness (Marshall & Uller 2007).

Maternal environments influence many offspring traits. Here I present three examples: 1) maternal choice of oviposition site can affect the survival and growth of offspring (Bernardo

1996a; Mousseau & Fox 1998a). For plant dwelling insects, host plant quality can affect the composition of a female‟s eggs, in turn affecting not only her offspring, but also her grand- offspring (Rossiter 1996). 2) The amount and quality of resources allocated by mothers to eggs can also influence offspring growth and survival (Mousseau & Fox 1998a). Egg size variation depends on environmental conditions, and fitness differences between large and small eggs are greatest in unfavourable conditions, such as when offspring develop on a poor-quality host plant

(Fox & Mousseau 1996). 3) An environmental cue, such as photoperiod, temperature, or host availability, can lead mothers to switch from producing non-diapausing offspring to ones that diapause in response to deteriorating environmental conditions (i.e. short photoperiods associated with impending winter conditions) (Mousseau & Dingle 1991).

Importance of Parasite-Mediated Maternal Effects

Very few empirical studies examine the influence of maternal effects on host-parasite interactions. In order to understand why it is important to study parasite-mediated maternal effects, it is first essential to review how parasitism affects hosts. Parasites (organisms that live on or within other organisms, such as viruses, bacteria, fungi, protozoans, and metazoans (Sadd

& Schmid-Hempel 2009)) are damaging to their hosts, as they divert host nutrients away from host use toward their own growth, survival, and fitness. Hosts, in turn, invest in immunity to prevent or reduce the number of parasites and their negative impact. Investment in immunity is costly, as hosts are constrained by the amount of resources they can divert from other functions.

Therefore immunity may be traded off against fitness-related traits (Sheldon & Verhulst 1996), and infected hosts that invest in immunity may be fitter (Hurd 1998). Hurd (2009) reviews cases in which hosts reduce reproductive effort when parasites are in particularly virulent stages, which may increase host survival, and ultimately allow the host to reproduce for longer periods of time.

Other hosts may increase egg production if they are unlikely to survive infection (Hurd 2009).

There are many examples in the literature of trade-offs in fitness-related traits, and it is difficult to predict which traits will be traded off against which without an understanding of the molecular, biochemical, and physiological alterations underlying such tradeoffs (Hurd 2009).

Most of our knowledge about host-parasite interactions is the result of studies that examine the effects of parasitism on a single generation of hosts, and as such we know little about the effects of parasites on subsequent generations (Sorci & Clobert 1995). If changes in the parasite environment are predictable across generations, then mothers may be able to transmit information about the parasite environment to their offspring by means of a mechanism that alters offspring phenotype (Sorci & Clobert 1995). Therefore, in order to fully understand the

4 effects that parasites have on host life history traits, researchers must not examine only current host condition – they must additionally examine host condition in subsequent generations.

Immune Priming within a Single Generation

Studies investigating parasite-mediated maternal effects have focused primarily on vertebrates, where it has been widely accepted that antibodies of maternal origin reduce offspring susceptibility to parasites (Grindstaff et al. 2003; Patterson et al. 1962; Williams 1962). In contrast, little attention has been paid to parasite-mediated maternal effects in invertebrates, likely because invertebrates are considered to possess primitive innate immune systems that lack the acquired and memory type defences of vertebrates. However, the invertebrate immune system may be more complex than has been previously thought; studies have shown that the invertebrate immune system is able to provide long-term immunity to a host after an initial challenge. Moret & Siva-Jothy (2003) found that pre-challenge with lipopolysaccharides (LPS, a component of gram-negative bacterial cell walls that is highly immunogenic) protects the beetle,

Tenebrio molitor, from subsequent fungal infections. LPS is not found in fungi, thus exposure to

LPS likely upregulated components of the immune system to produce a general response in hosts, and hosts were better able to fight fungal infection. Kurtz & Franz (2003) found that prior exposure of the copepod, Macrocyclops albidus, to sibling tapeworm parasites, Schistocephalus solidus, resulted in fewer secondary infections than to unrelated tapeworms, indicating that M. albidus, has specific immunological memory to S. solidus. This type of immunity, one in which an initial immune challenge can lead to a better secondary response to the same or another parasite by a general immune response or by specific responses, is called „immune priming,‟ and

5 it suggests that compared to vertebrates, invertebrates may have a mechanistically-different but functionally-equivalent acquired response to infection.

Trans-generational Parasite Studies

The evidence for within-generation immune priming has led some researchers to test whether immune priming is also trans-generational, that is, whether individuals whose immune system is stimulated can transfer aspects of their immune response to their offspring. Most studies do not focus on immune response, per se, but indirectly study immunity by examining trans- generational parasite resistance and shifts in host offspring life history traits that often accompany trans-generational infections.

Bumblebee queens exposed to a bacterial-based immune challenge prior to colony founding produce worker offspring with higher levels of induced antibacterial activity (Sadd et al. 2005), which could protect offspring from future infections. Moret (2006) mimicked a heavy microbial infection with LPS in mothers and offspring Tenebrio molitor and also found that offspring had higher levels of induced anti-microbial activity. Additionally, Moret (2006) studied life history trade-offs resulting from immunity and found although the immune response reduced survival, the cost to survival in offspring was lower than the cost to their parents, indicating a survival benefit for offspring. Similarly, damselflies (Coenagrion puella) with abundant ectoparasites produced fewer offspring but larger larvae with a higher growth ratio

(Rolff 1999).

Daphnia magna infected with the pathogenic bacteria Pasteuria ramosa exhibited strain- specific immunity: infected populations in which both mother and offspring were exposed to the

6 same strain of P. ramosa showed lower overall infectivity and enhanced fitness (greater fecundity, and a higher population rate of increase) than infected populations in which mother and offspring were exposed to different bacterial strains (Little et al. 2003). This finding suggests trans-generational specific immunological memory, much in the way that Kurtz &

Franz‟ (2003) within-generation study did. Adamo (1999) showed that while the parasitoid

Ormia ochracea and the bacterium Serratia marcescens can both kill their cricket hosts, only females infected with S. marcescens (directly or through injection of LPS) increased their egg laying. This result suggests that invertebrates respond differently to invasive agents, and organisms that activate different components of the immune system may produce different responses in host behaviour.

A few studies have shown that offspring susceptibility to parasitism is context-dependent.

Daphnia magna mothers who were well provisioned during their development but experienced poor breeding conditions (low food and high density) produced offspring more resistant to parasites than did mothers who produced offspring under favourable environmental conditions

(Mitchell & Read 2005). Similar conclusions were drawn when Little et al. (2007) varied host temperature or food quantity in D. magna infected with P. ramosa for two generations. They found that while neither environmental variable had an effect on host infectivity levels, food level had an effect on the harm parasites inflict on their hosts: offspring survivorship was higher when their mothers were poorly-fed than when their mothers were well-fed.

Cumulatively, the literature shows that hosts can trans-generationally counter the negative effects of parasites by increasing resistance to parasites or reducing harm from parasites. The majority of these studies are examples of anticipatory maternal effects, in that maternal influence positively benefits offspring fitness-related life history traits.

Current Study

I used the yellow mealworm beetle, Tenebrio molitor, and its protozoan parasites (genus

Gregarina), to examine how invertebrate hosts respond to parasite stress through successive generations. I subjected the parental generation of the host species to one of two types of environmental stressors: high parasite stress or high density stress, or to a control treatment (low density and no parasites). Offspring were subsequently subjected to either the same stress, the alternate stress, or to the control, in a fully factorial design. Life history traits relating to longevity and reproduction were measured in both generations.

I tested two questions: 1) do mothers experiencing an environmental stress adjust offspring phenotype (display maternal effects)? My hypothesis is that environmentally stressed mothers distribute resources in such a way that their offspring will be better able to survive and/or reproduce in their environment (anticipatory maternal effects). 2) Do mothers faced with different types of environmental stress adjust offspring phenotype in similar ways, or does parasite stress affects populations in ways that differ from other stressors? I am exploring whether T. molitor hosts differentially alter their life history strategies depending on which type of stress they are exposed to, or whether they possess a more generalized trans-generational stress response – one that can differentiate between stress versus no-stress, but not one that can differentiate between different types of stress.

I expected there to be a cost of stress; the maternal generation should suffer reductions in survival and/or have less resources available for reproduction. However, they should invest more of their available resources per offspring than unstressed mothers. As with the maternal generation, in the offspring generation I expected there to be a cost due to the main effect of the current stress (the treatment applied to the offspring (F1 treatment)). I expected the main effect

of stress history (the treatment applied to the offspring‟s mothers (F0 treatment)) to positively effect offspring, because mothers should have invested more of their available resources in their offspring (anticipatory maternal effects). I expected that there might be an interaction between the positive effects of possessing a stress history and the negative effects of the current stress, such that the positive effects of having a stress history might reduce the negative effects of the current stress. In the following sentences, “C” refers to the control treatment, “Stress A” refers to either the parasite or density stress, and “Stress B” refers to the alternate stress of the two (Figure

1). Offspring who did not experience stress in either generation (F0 C_ F1 C) would possess optimal survival and/or fitness. Offspring who were exposed to a current stressful environment, but who did not possess a stress history (F0 C_ F1 Stress A) would suffer the most negative effects of stress. Research supports this prediction, as invertebrate mothers from good environments produced offspring that were less resistant to parasites than mothers from poor environments and/or had offspring that suffered more of the negative effects of parasites on life history traits than offspring possessing a stress history of infection (Little et al. 2007; Mitchell &

Read 2005). Offspring possessing both a history of stress and a current stress (F0 Stress A_ F1

Stress A) would be able to reduce the negative impact of stress; they would exhibit less negative effects of stress than F0 C_ F1 Stress A offspring, but because there is a cost to stress, they would not possess optimal survival and/or fitness as F0 C_ F1 C offspring. Offspring possessing a stress history but who were not exposed to stress in their current environment (F0 Stress A_ F1 C) might either fare as well as F0 Stress A_ F1 Stress A or better, since they would not have suffered the negative effects of the current stress, but they would not fare as well as F0 C_ F1 C. It is difficult to predict how offspring possessing a history of one type of stress (parasite or density) would fare when they were exposed to the alternate stress in their current environment (F0 Stress

A_ F1 Stress B); if mothers adjust offspring phenotype under different types stressors in similar

ways, then I would expect offspring to reduce the negative impact of stress in a similar way to F0

Stress A_ F1 Stress A offspring. If mothers adjust offspring phenotype to counter stress in unique ways, then I would expect offspring to not be able to reduce the negative impact of the current stress since they do not have the required stress history (a similar result to F0 C_ F1 Stress A offspring).

This study is the first to examine whether mothers under different types of environmental stress adjust offspring phenotype in similar ways, or whether different stressors produce life history shifts that are distinctly different from each other. It is one of the few studies to examine the effect of gregarine parasites on their host species. It is also one of the few studies to examine maternal effects beyond early offspring life history traits, and to make a large-scale life history assessment. The latter is important because it is difficult to make general conclusions about life history trade-offs associated with maternal effects without examining as much of the whole picture as possible. For example, if one were to examine the effects of stress on reproduction and measured only egg number, then one might conclude that stress had a negative effect on reproduction if fewer eggs were laid under stress. However, it may be the case that, while fewer eggs were laid, they were laid earlier, and egg size, and subsequently offspring size was larger, which can provide competitive benefits to offspring over their conspecifics.

Methods

Host System

Tenebrio molitor L. (Coleoptera, Tenebrionidae), the yellow mealworm beetle, is a cosmopolitan nocturnal scavenger that lives in dark, moist habitats (Robinson 2005). It resides in north

10 temperate regions (Robinson 2005), including Canada (Bousquet 1991). Tenebrio molitor is a common pest of stored grain, cereal, and mill products (Robinson 2005). In the natural habitat, it occupies bird nests (Woodroffe 1953), and tree hollows (Ranius 2002) and may be found feeding on animal materials, such as meat scraps, dead insects (Robinson 2005) and bird droppings

(French et al. 1994). Tenebrio molitor is seldom used as a study system in ecological and evolutionary research, although several studies have examined its learning (Sheiman et al. 2006) and mating behaviour and mate preference (Cole et al. 2003; Drnevich et al. 2002; Worden &

Parker 2001; Worden & Parker 2005). Tenebrio molitor is a host to the entomopathogenic fungus, Beauverra bassiana (Valtonen et al. 2010), gregarine protozoans (Clopton et al. 1992), and is an intermediate host to the rat tapeworm, Hymenolepis diminuta (Hurd et al. 2001).

Adults do not exhibit sexual dimorphism. They are elongate, brown to black, shiny in colour, and measure about 14 mm in length (Robinson 2005). Larvae are long (growing to about

25 mm), yellowish-brown, and sclerotized (Robinson 2005). Eggs are laid singly, and are covered in a sticky secretion (Robinson 2005). Tenebrio molitor can be relatively easily cultured in the laboratory, where development varies by such factors as moisture, temperature, and food; eggs hatch in 6 days at 30 -35 °C or in 17 days at 15 °C (Robinson 2005), the larval period is

131.3 +/- 36.2 days at 27°C and 60-70% relative humidity (Harry 1967), with an average of 13.2 molts at 25 °C and 19.1 molts at 30 °C (Ludwig 1955). The pupal period is about 15 days, but can vary between 7 days at 25-35 °C and 48 days at 15 °C (Robinson 2005), and the adult period is 60 – 90 days.

Parasite System

Tenebrio molitor is a host to parasitic gregarine protozoans of the Apicomplexa phylum; the phylum that contains some of the most important protozoan causes of disease in both invertebrates and vertebrates (e.g. Malaria). The class, Gregarinasina, is generally limited to a single species or a small group of hosts (Levine 1985). They parasitize the digestive tract or body cavity of invertebrates or lower chordates, destroying the host cells in which they develop

(Levine 1985). Host health is not compromised by light infections, but high infections can lead to the parasite destroying portions of the host gut (Abro 1974) and/or reducing nourishment of the host (Canning 1956; Weiser 1963).

Gregarine parasites of T. molitor belong to the largest gregarine family, Gregarinidae, and all but one species are members of the largest genus, Gregarina (Levine 1985). Tenebrio molitor has been documented to host five species of gregarines; Gregarina cuneata, Gregarina polymorpha, Gregarina steini, and Steinina ovalis are parasites of larvae (Clopton et al. 1992;

MacKinnon & Hawes 1961), and Gregarina niphandrodes is exclusive to adults, although

Gregarina cuneata has been found in adults in rare instances (Clopton et al. 1991). Multiple gregarine species are commonly found to infect the same larval host individual concurrently

(Clopton et al. 1992).

The life cycle of gregarines consists of ingestion of infective oocysts and exsporulation in the insect gut (Clopton & Janovy 1993; Clopton et al. 1992). Free sporozoites (infective trophozoites) migrate to the mid-gut epithelium where they attach to the epithelial wall by an epimerite and undergo intracellular and extracellular growth until they reach a mature gamont stage (Clopton & Janovy 1993; Clopton et al. 1992; Levine 1985). Gamonts undergo syzygy to form gametocysts, which are expelled through the host‟s feces (Clopton & Janovy 1993; Levine

1985). Outside the host, sexual recombination and asexual multiplication occur within gametocysts to form hundreds of infective oocysts (Levine 1985). Mature oocysts, each containing 8 sporozoites, sporulate through small openings called sporoducts into the environment to continue the cycle (Clopton & Janovy 1993; Levine 1985).

Appropriateness of System

Theory states that a maternal effect may occur if changes in the environment are predictable through time. I think that the T. molitor/gregarine host-parasite system is appropriate for studying maternal effects for several reasons: 1) Tenebrio molitor populations are often found in barns, where they both live in and feed on mass-produced stored grain products, or they scavenge in the natural environment on a variety of food sources, and should not have a need to disperse once a food source is found. 2) Tenebrio molitor have non-functioning wings, again making dispersal difficult and unlikely. 3) Generations of T. molitor overlap, and populations are composed of both younger and older individuals co-existing on the same food source.

Studies confirm that females readily lay their eggs throughout the layers of their food source

(Gerber & Sabourin 1984). Since T. molitor females are likely to produce their offspring in the same location and eat from the same food source, offspring should be exposed to the same parasite populations as their mothers. Therefore, it is expected that changes in the parasite environment will be predictable across generations.

Parasite Manipulations

Clearing Existing Gregarine Infections

I incubated Tenebrio molitor larvae at a temperature of ~ 37.5 ºC for 6 days in order to rid them of existing internal (trophic stage) gregarine infections (Clopton et al. 1992; MacKinnon &

Hawes 1961). Incubation does not destroy all gregarine stages, and so hosts that have been cleared of trophic stage gregarines can still pick up mild infections (Omoto, personal communication) by ingesting infective oocysts that reside in their food or feces. Destroying gregarine oocysts would require incubating hosts for many days at high temperatures (Clopton et al. 1992; MacKinnon & Hawes 1961), which would likely kill the hosts. To reduce the likelihood of re-infections, I only fed hosts with small quantities of food during incubation to prevent oocysts settling on food and subsequently re-infecting larvae, and prevented larvae from being in contact with their fecal matter (see experimental design section for details). I dissected a small subset of hosts ~ 10 days post-incubation to check for infections.

Parasite Source Populations

I maintained 11 non-experimental populations of T. molitor larvae separately from each other, and used them as sources of gregarine parasites. I obtained hosts and their gregarines from

Wards Biological Supply, St. Catharines, Ontario, Canada and local pet stores and suppliers, and housed them in a separate room from the experimental organisms to prevent contamination. In order to facilitate high infection rates, I kept each of the 11 host populations separately in high densities (100-150 larvae), in small containers (600 ml), and fed them on a nutrient poor diet

(wheat bran). This setup likely resulted in various levels of gregarine infections, infections by

14 different species of gregarines, and degrees of gregarine genetic diversity within each host population. I dissected small subsets of each population and identified Gregarina polymorpha and Gregarina steini trophozoites according to descriptions by Clopton et al. (1991).

To ensure a sufficient supply of larvae-infecting gregarines, I added 100 relatively uninfected young larvae (obtained from pet stores) to each container when the existing host populations neared pupation. The gregarine assemblages were likely altered when new larvae were introduced; i.e. I may have introduced new gregarine genotypes in low numbers, new larvae may have been more susceptible to certain gregarine species over others, and even within a single gregarine species some genotypes may have been more infective to the new hosts than others. Ideally, I would have isolated and maintained gregarines outside of their hosts (as has been done for gregarine parasites of a few other host species (Levine 1985)). However, to my knowledge this has not successfully been done with gregarine parasites of T. molitor.

Parasite Infection Procedure

I extracted gregarines from hosts by placing groups of ~ 50 larval T. molitor from each of the 11 populations in 100 x 15 mm petri dishes without food (Clopton et al. 1992). I collected frass from each population the following day and combined all frass from all 11 populations into a single dish. Following the procedure of Rodriguez et al. (2007), I freed gametocysts from the frass by vigorously shaking the frass in distilled water and then using a step sucrose gradient to band gametocysts between 10% and 35% sucrose. I pipetted gametocysts, rinsed them in distilled water to remove all sucrose, and pipetted them one at a time onto small circles (~9.5 mm) of black construction paper inside 100 x 15 mm petri dishes. A smaller petri dish (60 x 15

15 mm) containing distilled water was added to the larger petri dish to help maintain the high humidity conditions required to assist sporulation (Rodriguez et al. 2007). Most gametocysts sporulated 3 days after gametocyst incubation, although on a few occasions sporulation occurred up to 7 days after gametocyst isolation. I confirmed sporulation under a dissecting microscope

(Leica Wild M3C) and destroyed any gametocysts that failed to sporulate by removing them from their construction paper circles or by popping the underdeveloped gametocysts with a probe

(whichever was easier). I mixed the circles containing the sporulating gametocysts throughout the layers of the host‟s food, where T. molitor presumably ingested the infective oocysts while feeding (Figure 2). I confirmed successful gregarine infections by dissecting a small subset of the experimental animals.

Experimental Design

Grandparental generation (F-1)

My experimental design required the parents of hosts used in the experiment to be free of parasites; I refer to these organisms as the grandparental generation (F-1). I incubated two groups of ~400 T. molitor larvae (obtained from Wards Biological Supply, St. Catharines, Ontario,

Canada) in October 2007 at 37.5 ºC for 6 days to clear existing gregarine infections (Figure 3). I made two incubation containers by removing the bottom of two 8276 ml Rubbermaid rectangular containers, adhering plastic mesh (opening size 2 mm x 1 mm) to the bottom as flooring for the larvae, and stacking the containers into other 8276 ml Rubbermaid containers. Tenebrio molitor larvae were placed on top of the mesh surface and their frass fell through the mesh; frass was removed daily. I provided T. molitor larvae with small amounts of wheat bran, and two tubs of

16 water were placed inside the incubator for added moisture. A trial incubation on non- experimental larvae resulted in the deaths of 18% of the larvae.

Immediately following incubation, I confirmed that existing gregarine infections were cleared by dissecting 15 larvae from each of the two groups; no infections were present. I placed the remaining larvae in two un-manipulated (without mesh) 8276 ml containers with fresh wheat bran and kept them on a 12:12 L: D photoperiodic regime, at a temperature of 20 – 25°C. At day

16-17 post-incubation, I dissected a second set of larvae to check for possible re-infection with gregarine oocysts; one of the 20 individuals was infected. To minimize spreading the infection, I transferred experimental larvae to many 600 ml un-manipulated containers in small groups to minimize contact between individuals and any surviving gregarine oocysts. At pupation, I sexed individuals and females were separated from males and kept in several 600 ml un-manipulated containers.

Adults were permitted to mate in December 2007. I paired each of 225 adult F-1 females of age 7-11 days post-eclosion randomly with males from non-experimental lab populations

(males likely came from populations exposed to gregarines), and allowed ad libitum mating

(Drnevich et al. 2001) by keeping the pair together for 7 days in 61 ml rectangular containers

(6.3 cm x 2.6 cm x 2.6 cm) filled half way with whole wheat flour. I then removed the adults and allowed the eggs to hatch. I dissected twenty-nine females post-mating to confirm that they were clear of gregarine infections as adults. Many pairs died before the end of the 7 day period, and only ~40% (90 mating pairs) of the 225 mating pairs produced offspring. Offspring numbers ranged from 1 – 19 per mating pair over the 7 day period, which was much lower than the reported number of about 40 eggs per day (Robinson 2005). Production of young would likely

17 have been higher had I provided adult beetles with a water supply – a flaw that I corrected in the next generation‟s mating setup.

Maternal Generation (F0)

Offspring of the F-1 females (the maternal generation, or F0) were held with their siblings until they reached a size of 12-17 mm (in April 2008), at which point I removed them. I assigned larvae to incubation containers in groups of 10 by using a random number table. Ideally, I would have kept larvae with their siblings but I did not have a large enough sample size to do so. I constructed incubation containers by adhering a piece of plastic mesh (opening size 0.8 mm x 0.8 mm) to the bottom of a piece of plastic tubing (inside diameter 4.5 cm) and placed the tubing/mesh construct on an inverted 60 x 15 mm petri dish lid. The tubing had a bevelled edge and it sat on top of the petri dish lid, providing some space for the bottom of the petri dish lid to collect the frass droppings that fell through the mesh. I capped the tubing/mesh construct with a

60 x 15 mm petri dish bottom to prevent larvae from escaping the construct. I used a smaller mesh size than I did in the F-1 generation because I incubated the F0 larvae at a smaller size. I sealed incubation containers inside a 8276 ml container along with a 600 ml container filled with water for moisture. I incubated larvae at 37.5 ºC for 6 days (Figure 3). I fed larvae a small chunk of fresh potato (~0.5 cm3) daily; frass was removed daily.

Following incubation, I confirmed that existing gregarine infections were cleared by dissecting 3-6 larvae from each of the two groups; no infections were present. Larvae were assigned to experimental treatments. I randomly assigned larvae to 237 ml plastic treatment containers that held an ad libitum diet of 50 g of wheat bran, whole wheat flour, and brewer‟s

18 yeast in a 50:45:5 ratio (Weaver & McFarlane 1990) and a 2 ml centrifuge tube filled with water

(replaced every other day). Containers were held at a temperature of 20 – 25°C and on a 12:12 L:

D photoperiod. I placed larvae into one of 3 treatments: 1) a high density treatment (F0D) of 8 individuals per container without parasites, 2) a high parasite treatment (F0P) of 2 individuals per container with parasites, and 3) a control treatment (F0C) of 2 individuals per container without parasites (Figure 3).

Larvae were allowed to acclimate for 10 days post-incubation before the first parasite dose was administered to the parasite treatment. I added 15 sporulating gametocysts on small black circles of construction paper throughout the layers of the food of containers in the parasite treatment; I added small black circles of construction paper without parasites to the high density and control larvae. Two weeks later, I administered a second dose of 15 sporulating gametocysts to the parasite treatment and again added circles of construction paper without parasites to the high density and control treatment containers. I sexed all pupated individuals, separated females from males, and upon eclosion I recorded development time (from day of first treatment to eclosion date) and adult body size (length of left elytron) for all individuals. I then removed the males from the experiment.

Adults were permitted to mate beginning in May 2008. I randomly grouped each F0 female of age 6-9 days post-eclosion with two virgin males from non-experimental lab populations (males likely came from populations exposed to gregarines). I held adults in 100 x

15 mm petri dishes with a 2 ml centrifuge tube filled with water (changed every 4 days) and a 12 g mixture of whole wheat flour and brewer‟s yeast in a 19:1 ratio. I sifted flour using a sieve to a size of 1.0 mm or less to facilitate egg collection. Matings were permitted ad libitum (males

19 were replaced when they died) until females died. I collected eggs every other day for each female by sifting through the flour with a small strainer (opening size: 0.8 mm x 0.8 mm).

I examined each F0 female`s eggs on each collection day. I took digital images of eggs using a dissecting microscope (Leica M26) with an attached camera (Leica DFC280). I counted eggs on the images and used Image J software (version 1.42q) to measure egg area. Some eggs were damaged (e.g. dented, broken), and only undamaged eggs were measured. I measured a maximum of five eggs (less if there were less than 5 undamaged eggs laid) on each day of egg collection. I placed collected eggs from each female in a 150 ml petri dish with 12 g of a mixture of whole wheat flour and brewer‟s yeast (19:1 ratio), and added new eggs to the same dish after each collection day. I left the eggs to hatch.

Missing data for number of eggs occurred occasionally for each female (average of 4.3 measurements per female, or 8.2% of measurements per female), and resulted from my inability to count eggs that were clumped together and other logistical problems. It was important to develop a count for females on each measurement day because the counts were needed to measure total egg number per female. Missing counts were estimated by plotting average egg number over time for each treatment. Number of eggs generally declined after the first few measurement periods and I defined the maximum number of eggs in a treatment as the average of the first 4 egg number measurements. This allowed me to express the average number of eggs on all subsequent dates as a percent of the maximum. To estimate egg number for missing data for any particular female, I multiplied the percent for the day in question by the average of the first 4 egg number measurements for the female in question.

Offspring Generation (F1)

I incubated offspring of F0 females (the offspring generation, or F1) to clear any possible gregarine infections prior to experimental manipulation. Offspring from each female were housed with their siblings in the same petri dish until they reached a size of 12-17 mm (in

September 2008). I incubated larvae with their siblings at 37 ºC for 6.5 days (Figure 3) using the same setup as that used in the F0 generation. The slight change in incubation time and temperature was due to a logistical need to use a different incubator.

I placed larvae in experimental treatments after they were incubated. I randomly divided each group of siblings from each F0 treatment into 3 further treatments to produce a fully factorial design (Figure 4a). The high density treatment (F1D) consisted of 8 siblings per container without parasites. The high parasite treatment (F1P) had 2 siblings per container with parasites. The control treatment (F1C) had 2 siblings per container without parasites.

Photoperiod and temperature were identical to that of the F0 generation. Larvae were first housed in 60 x 15 mm petri dishes with 2 g of wheat bran for 11 days to acclimate. Some larvae died during this period (52.8% of dead larvae possessed a parasite stress history, 35.8% possessed a density stress history, and 11.4% possessed a control stress history). Dead larvae were replaced by additional sibling larvae possessing the same stress history that I had set aside in petri dishes of identical food, photoperiod, and temperature conditions as their experimental siblings. Some of these additional sibling larvae had been housed with more siblings than were in the experimental treatments, although this only occurred for the 10 days before they were added to the experimental treatments. I administered the first parasite dose of 30 sporulating gametocysts to the parasite treatment larvae; I added black circles of construction paper without parasites to the high density and control treatment larvae. I kept larvae of all treatments in the

21 same petri dishes for an additional 14 days. This was a procedural change in protocol from the infection procedure of the F0 generation. I had noticed that in the F0 generation larvae did not contract infections until they were larger larvae and I wanted to increase the possibility of young larvae contracting infections. I transferred larvae to 237 ml treatment containers that held the same diet as that of the F0 generation. Parasite treatment larvae received a second parasite dose of 30 sporulating gametocysts, and I administered a final dose 14 days later (again, I gave high density and control treatment larvae black circles of construction paper without parasites).

During the larval stage I recorded mortality and missing larvae every 2 - 4 days.

Mortality and cannibalism could not always be distinguished from each other because I could not infer whether larvae that “disappeared” were eaten after death or killed and then eaten by conspecifics. I took measurements of body mass and body size approximately biweekly, beginning with an initial measurement at day 0 (date that larvae received their first treatment), then at day 10, day 24, day 38, day 52, day 66, and day 80. I recorded body mass by measuring the mass of all larvae in each treatment container and calculating the average. I measured body size by taking digital images of all larvae in each container, using Image J software

(version1.42q) to measure the width of the base of each larva‟s head, and calculating the average value for each experimental container. At pupation, I sexed individuals, females were separated from males, and upon eclosion I recorded development time (from day of first treatment to pupation date) and adult body size (length of left elytron) for all individuals, and then removed males from the experiment.

Adults were permitted to mate beginning in November 2008. I grouped each adult F1 female with two virgin males from non-experimental lab populations (males likely came from populations exposed to gregarines). One female was 26 days post-eclosion and another was 22

22 days, all others were between 7 - 19 post-eclosion. Adults were held in 100 x 15 mm petri dishes with a 2 ml centrifuge tube filled with water that was changed every 5 days and 12 g of a mixture of sifted whole wheat flour and brewer‟s yeast (19:1 ratio). Matings were permitted ad libitum and I collected eggs every five days, as opposed to the 2 day intervals of the F0 generation. The change was necessitated by time constraints related to the greater number of females. I measured eggs following the same methods as that for the F0 females, and stored eggs in a separate petri dish from the adults. As with the F0 generation, occasionally females were missing egg number data on several days (average of 0.34 measurements per female, or 1.5 % of measurements per female), and missing data was estimated as before.

Overview of Statistical Analyses

I performed all statistical analyses using SPSS version 18 for Windows.

Maternal Generation (F0) Analyses

I used a priori planned contrasts to compare the control group to each experimental group exclusively (F0 control treatment and F0 parasite treatment, F0 control treatment and F0 density treatment). I did not include a parasite treatment and density treatment contrast in the designing of the experiment because it is not clear how such a contrast would be interpretable.

Offspring Generation (F1) Analyses

I tested the main effects of: 1) the stress history (the treatment applied to the offspring`s mothers

(F0 treatment), and 2) the current stress (the treatment applied to the offspring (F1 treatment)). I also examined the interaction between stress history and current stress.

I initially designed this experiment to be fully factorial (Figure 4a) and I analyzed the data for the offspring generation by means of a priori planned comparisons. These planned comparisons fell into two divided analyses; a F1 parasite analysis (Figure 4b) and a F1 density analysis (Figure 4c). It wasn‟t until I began analyzing the data in this way that I realized that two particular treatment combinations, F0D F1P (of the F1 parasite analysis) and F0P F1D (of the F1 density analysis), were problematic. I had included them in the experimental design because I wanted to determine whether mothers who were under one type of stress (Stress A) could adjust offspring phenotype in a way that would lead to improved offspring fitness in the current environment, even if the current environment would be different to that of their mothers (Stress

B). However, I was examining all of the same comparisons for the main effect of F0 treatment

(F0P vs. F0C and F0D vs. F0C) twice, since I analyzed them under both the F1 parasite analysis and the F1 density analysis. I also had largely unbalanced samples sizes per treatment under this type of analyses.

In an effort to rectify these issues I decided to exclude the treatment combinations of F0D

F1P and F0P F1D from the F1 parasite and density analyses, respectively, producing F1 parasite and density analyses that were fully factorial (Figures 5b and 5c). The revised analyses resulted in similar p-values and the conclusions drawn from each analysis were the same as they were in each of the initial analyses.

Statistical Analyses

Larval Development

For both the maternal and offspring generations, development time (mean development time per container, LN transformed) and adult body size (mean left elytron length, per container) showed

2 positive pearson correlations (maternal generation: r (35) = 0.140, p=0.027; offspring

2 generation: r (110) = 0.208, p < 0.001). Therefore MANOVAs were conducted to include both response variables. For the maternal generation, a one-way MANOVA was conducted, with F0 treatment as a fixed factor predictor variable. For the offspring generation analyses, two-way

MANOVAs were conduced, with stress history (F0 treatment) and current stress (F1 treatment) as fixed factor predictor variables.

Survival

I used a Kruskal-Wallis test to analyze effects of F0 treatments on survival (number surviving per container, from day of first treatment to eclosion) of the maternal generation. For each of the offspring generation analyses, I used a non-parametric equivalent to a two-way ANOVA (the

Scheirer-Ray-Hare test, an extension of the Kruskal-Wallis test; (Dytham 2003; Sokal & Rohlf

1995), with stress history and current stress as fixed factor predictor variables.

F1 Larval Growth

I decided against using head width measures in the analysis because the larvae often contracted their bodies and turned their heads on an angle, preventing me from capturing a picture of their

25 heads from a dorsal perspective. I was confident that the mass measurements (mean mass per container) adequately reflected larval growth measures. I used a repeated measures ANOVA on offspring larval mass, with time as the repeated measure and stress history and current treatment as the main effects factors.

The key assumptions of a repeated measures analysis are that there are correlations among the repeated measurements, equal correlations between pairs of treatments, and equality of group variances (Zar 1998). Together these assumptions relate to sphericity (Zar 1998), and statistical packages test sphericity with Mauchly‟s test. Where sphericity was met, I reported univariate results. When sphericity is violated, one can report univariate results with adjusted degrees of freedom due to the violation, or one can report multivariate results, which do not rely on the sphericity assumption (Maxwell & Delaney 2004; Zar 1998). Maxwell & Delaney suggest that the multivariate approach reduces Type I and Type II error rates, and is more powerful where n exceeds k (the number of levels of the repeated factor) by a few, and where n is not small. Therefore, where sphericity was violated I reported multivariate results.

Timing of Eggs

For the maternal generation, I performed a repeated measures ANOVA on timing of eggs (the number of days commencing from when females was first mated, LN transformed) measured as percent of eggs laid on each day after each female was first mated, with F0 treatment as the main effects factor. For the offspring generation analyses, stress history and current stress were main effects factors. Sphericity only applies when there are 3 or more levels of the repeated measure

(Maxwell & Delaney 2004). In these analyses there are only 2 levels of the repeated measure

(50% and 100% of eggs laid). Since the assumption of sphericity was not violated, univariate results were reported.

Adult Female Death

For the maternal generation, I performed a one-way ANOVA on age at which reproductive females died (per female, from day of post-eclosion to death) as the response variable, and F0 treatment as a fixed factor predictor variable. For the offspring generation analyses, two-way

ANOVAs were conduced, with stress history (F0 treatment) and current stress (F1 treatment) as fixed factor predictor variables.

Total Egg Number

For the maternal generation, I used an ANCOVA to assess if the total number of eggs females laid (per female) differed between F0 treatments, independent of female body size (left elytron length). For the offspring generation analyses, stress history and current stress were main effects factors. If I found the covariate was not significant in the model, I removed it and reanalyzed the data as an ANOVA.

Egg Size

For the maternal generation, I used an ANCOVA to assess whether or not egg size (mean egg size per female, measured halfway through egg laying) differed between F0 treatment,

27 independent of two possible covariates, female body size (left elytron length) and egg number

(per female, measured halfway through egg laying). For the offspring generation analyses, stress history and current stress were main effects factors. In all analyses, I tested whether each covariate was significant in the model separately. Where a covariate was not significant, I removed it from the model. Where both covariates were not significant, I reanalyzed the data as an ANOVA.

Results

Larval Development

F0 Larval Development

One or more larvae died prior to eclosion in 7 of the containers, but all 35 containers had at least one surviving larvae (see Appendix A1 for sample sizes). MANOVA indicated there was no significant difference in development time (LN transformed) and adult body size between larvae exposed to an environmental stress compared to those in the control treatment (Pillai‟s trace V =

0.151, F4, 64 = 1.305, P= 0.278).

F1 Larval Development

The available sample sizes/number of larvae measured per container for the F1 generation was reduced due to several reasons: 1) as with the F0 generation, 1 or more (sometimes all) larvae died prior to eclosion in several containers. 2) 4 larvae in 3 containers were misplaced sometime

28 between 8 and 10 weeks after initial treatment. 3) Several individuals grew deformed wings, so I could not take measurements of their body sizes (see Appendix A2 and A3 for sample sizes).

F1 Larval Development: Parasite Analysis

MANOVA (with a LN transformation of development time) showed a significant effect of stress history on the offspring (Table 1), therefore I conducted univariate analyses to determine which development parameters were influenced by which predictor variables. ANOVA indicated stress history did not significantly affect offspring adult body size, but did affect offspring larval development time (Table 1), indicating that offspring with a stress history of parasites took 11.2

% longer to develop than offspring with a stress history of the control group (Figure 6). Neither current stress nor its interaction with stress history affected offspring larval development parameters (Table 1).

F1 Larval Development: Density Analysis

MANOVA indicated no significant effect of stress history, current stress, or an interaction between stress history and current stress, on offspring larval development time (LN transformed) and adult body size (stress history: Pillai‟s trace V = 0.076, F2 , 55 = 2.264, p = 0.113; current stress: Pillai‟s trace V = 0.059, F2, 55 = 1.712, p = 0.190; current stress x stress history: Pillai‟s trace V = 0.007, F2, 55 = 0.205, p = 0.815).

Survival

F0 Survival

At most, one larva of the initial two died in each container in the control and parasite treatments, up to four of the initial eight died in the density treatment. Missing larvae were included as larvae that did not survive (see Appendix A1 for sample sizes).

A Kruskal-Wallis test revealed a significant effect of treatments on survival (χ2 = 11.314, p = 0.003). Post-hoc tests (Dunn 1964) comparing the control to each of the two stress treatments showed that there was a significant difference between the control group and the density group only (control and parasite: Q = -0.602, p > 0.500; control and density: Q = 2.572, p

<0.005), indicating that there was a 12.5 % reduction in median survival per container (or 1 of 8 larvae died per container) in the density treatment compared to 100% survival in the control treatment (Figure 7a).

F1 Survival

Survival in each of the treatments ranged from 100% - 0% per container. Missing larvae were included as larvae that did not survive (see Appendix A2 and A3 for sample sizes).

F1 Survival: Parasite Analysis

Stress history had a significant effect on the percentage of offspring per container that survived to adulthood (Scheirer-Ray-Hare test; df =1, SS = 2160.413, H = 15.317, p = 0.0001), indicating

30 that offspring who had a stress history of parasites had a 50% reduction in median survival (or 1 of 2 larvae died per container) and offspring who had a stress history of the control treatment had

100% median survival (Figure 7b). Neither current stress nor stress history x current stress had significant effects on survival (current stress: df = 1, SS = 3.049, H = 0.022, p = 0.8821; stress history x current stress: df = 1, SS = 3.049, H = 0.022, p = 0.8821).

F1 Survival: Density Analysis

Stress history had no overall effect on offspring survival to adulthood (Scheirer-Ray-Hare test; df

=1, SS = 4.739, H = 0.021, p = 0.8848). Current stress had a significant effect (df = 1, SS =

1355.128, H = 5.891, p = 0.0152), indicating that offspring who were currently in a density stress had a 12.5 % reduction in median survival (or 1 of 8 larvae died per container) and offspring who were currently in the control treatment had 100% median survival (Figure 7c). There was no interaction of stress history x current stress on offspring survival (df = 1, SS = 143.579, H =

0.624, p = 0.4296).

Larval Growth

F1 Larval Growth

Containers in which all larvae died prior to pupating were excluded from the analyses (see

Appendix A2 and A3 for sample sizes). I analyzed data from only the first 4 measurements

(days 0, 10, 24, and 38) in order to maintain a large sample size, since 58% (parasite analysis) and 52% (density analysis) of the larvae pupated between the fourth and fifth measurements.

F1 Larval Growth: Parasite Analysis

Offspring mass increased over time, and there was a significant effect of stress history, which indicated that offspring of mothers who were in the control treatment were significantly heavier than offspring of mothers who were in the parasite treatment (Figure 8a; Table 2). Stress history also interacted with time (Table 2); I conducted univariate ANOVAs at each measurement day

(with a bonferroni correction of p = 0.0125, since p = 0.005/4), and found that days 0, 10, and 24 were significant (day 0: F1, 36 = 13.077, p = 0.001, day 10: F1, 36 = 19.366, p < 0.001, day 24: F1

,36 = 16.360, p < 0.001), but day 38 was not (F1, 36 = 3.670, p = 0.063). Thus, mass may have increased at a slower rate in the stress history parasite treatment than the control until after day

24, when offspring with a stress history parasite treatment then increased their mass rapidly until they reached a similar mass to that of the control treatment as larvae began to pupate (Figure 8a).

In contrast, offspring mass was not affected by current stress, the effect of stress history on mass did not depend on the current stress, nor was there a significant interaction between the two factors over time (Table 2).

F1 Larval Growth: Density Analysis

Offspring mass increased over time (Table 3). Overall, there was a significant effect of current stress on mass, indicating that offspring whose current stress was density were lighter than offspring who were in the control group, and this was consistent across time (Figure 8b; Table

3). There was no significant overall effect of stress history on larval mass, the effect of current stress on mass did not depend on stress history, and there was no significant interaction between the two factors over time (Table 3).

Reproduction Analyses

Due to logistical constraints, I did not permit every female in the maternal generation to mate and lay eggs. Instead, I randomly chose one female per treatment container. In the case of F0 control and F0 parasite treatments, some containers did not produce any females or females died as larvae, so I occasionally chose 2 females per container to maintain a reasonable sample size.

One female from the F0 generation control treatment did not lay any eggs, and was excluded from the analyses related to timing of eggs, egg size, and total number of eggs, but was included in the analysis of adult female death. As with the maternal generation, I did not permit every female in the offspring generation to mate and lay eggs. Many larvae died in the offspring generation, which reduced the number of available females in certain F0 x F1 treatment combinations. Additionally, in both generations several individuals grew deformed wings, so I could not take measurements of their body sizes (see Appendix A1-A3 for sample sizes).

Timing of Eggs

F0 Timing of Eggs

There was no overall effect of F0 treatment on the timing of eggs (LN transformed) (F2, 32 =

1.559, p = 0.226), nor was there an interaction between the F0 treatment with percent of eggs laid

(F2, 32 = 0.91, p = 0.413).

F1 Timing of Eggs: Parasite Analysis

Timing of eggs (LN transformed) was not affected by either stress history or current stress, nor were there any interactions (Table 4).

F1 Timing of Eggs: Density Analysis

Current stress affected timing of eggs (sqrt transformed); offspring in the current density treatment took longer to lay their eggs than offspring of the control treatment; this was consistent across time (Figure 9). There was no effect of stress history, nor were there any significant interactions (Table 5).

Adult Female Death

F0 Adult Female Death

ANOVA showed that F0 treatments had no effect on age at which reproductive females died

(F2,33 = 1.708, p = 0.197).

F1 Adult Female Death: Parasite Analysis

Neither stress history (F0 treatment), current stress (F1 treatment), nor stress history x current stress affected age at which reproductive females died (LN transformed) (ANOVA; stress

history: F1, 16 = 0.339, p = 0.568; current stress: F1, 16 = 0.023, p = 0.883; stress history x current stress: F1, 16 = 1.862, p = 0.191).

F1 Adult Female Death: Density Analysis

Neither stress history (F0 treatment), current stress (F1 treatment), nor stress history x current stress affected age at which reproductive females died (LN transformed) (ANOVA; stress history: F1, 28 = 0.981, p = 0.330; current stress: F1, 28 = 3.667, p = 0.066; stress history x current stress: F1, 28 = 0.135, p = 0.716). Since current stress was almost significant, it suggests that there is a trend toward females in the current density treatment living longer adult lives than the current control treatment.

Total Egg Number

F0 Total Egg Number

Slopes of total egg numbers versus female body size per treatment were homogeneous (F2, 26 =

2.195, p = 0.132), therefore I removed the interaction term from the model and used a common within-group slope for the adjusted means. The common covariate of body size did not affect total egg number (F1, 28 = 2.162, p = 0.153) and was removed from the model. The final 1-way

ANOVA showed that F0 treatment had no effect on total egg number (1-way ANOVA; F2, 32 =

2.296, p = 0.117).

F1 Total Egg Number: Parasite Analysis

Slopes of total egg number (sqrt transformed) versus female body size were homogeneous (stress history x body size: F1, 11 = 0.660, p = 0.434; current stress x body size: F1, 11 = 0.558, p = 0.471; stress history x current stress x body size: F1, 11 = 0.479, p = 0.503), and were therefore removed from the model. The covariate, body size, did not have a significant effect on total egg number

(F1, 14 = 1.289, p = 0.275), and was removed from the model. The final model, a 2-way

ANOVA, showed that stress history had no significant affect on total egg number, (F1, 16 = 1.833, p = 0.195). Neither current stress, nor the interaction with stress history affected total egg number (current stress: F1, 16 = 0.139, p = 0.715; stress history x current stress: F1, 16 = 1.747, p =

0.205).

F1 Total Egg Number: Density Analysis

The slopes for the total egg number (sqrt transformed) vs. female body size per treatment were homogeneous for current stress x body size (Figure 10b; F1, 21 = 0.032, p = 0.860) and stress history x current stress x body size (F1, 21 = 0.012, p = 0.913) but were heterogeneous for stress history x body size (F1, 21 = 6.195, p = 0.021). Therefore, I removed the former two slopes from the model. The final model was a 2-way ANCOVA, with body size as a covariate and a stress history x body size interaction included in the model. The covariate, body size, was significant

(F1, 23 = 14.369, p = 0.001). Stress history had a significant effect on total egg number (F1, 23 =

7.214, p = 0.013). However, the effect of stress history on total egg number varied with body size in different ways in the different treatments (F1, 23 = 7.493, p = 0.012; Figure 10a); at smaller body sizes, the stress history density treatment resulted in more eggs than the control, but at

36 larger body sizes the stress history density treatment resulted in fewer eggs than the control treatment (Figure 10a). Current stress had a significant affect on total egg number (F1, 23 =

13.375, p = 0.001), indicating that offspring whose current treatment was density produced more eggs than those of the control treatment, and this affect was seen at all female body sizes (Figure

10b). There was no significant interaction between stress history and current stress (F1, 23 =

3.213, p = 0.086).

Egg Size

F0 Egg Size

I first tested if female body size explained some of the variation in egg size. Slopes of egg size vs. female body size were homogeneous (F2, 26 = 2.724, p = 0.084); I removed the interaction term from the model and used a common within-group slope for the adjusted means. Body size did not have a significant effect on egg size (F1, 28 = 0.074, p = 0.787) and was removed from the model.

I repeated the above steps to test if egg number explained some of the variation in egg size. The slopes of egg size vs. egg number were homogeneous (F2, 29 = 0.690, p = 0.510), and I removed the interaction term from the model. The covariate, egg number, did not have a significant effect on egg size (F1, 31 = 0.156, p = 0.695) and was removed from the model. The final model showed that egg size was not affected by F0 treatment (1-way ANOVA; F2, 32 =

0.163, p = 0.850).

F1 Egg Size: Parasite Analysis

The sample size in this analysis was reduced by one because there was a female in the F0C F1C treatment combination who only laid 3 eggs total, and I could not get a good estimate of how many eggs she laid halfway through her life.

As with the above F0 analysis, I determined whether body size and/or egg number could explain some of the variation in egg size. Body size did not explain any of the variation in egg size; the slopes for egg size vs. body size per treatment were homogeneous (stress history x body size: F1, 10 = 0.043, p = 0.840; current stress x body size: F1, 10 = 4.087, p = 0.071; stress history x current stress x body size: F1, 10 = 0.001, p = 0.979) and were removed from the analysis. The covariate did not have a significant effect on egg size (F1, 13 = 0.700, p = 0.418), so it was removed from the model. Egg number also did not explain any of the variation in egg size; the slopes for egg size vs. egg number per treatment were homogeneous (F0 treatment x body size:

F1, 11 = 1.851, p = 0.201; F1 treatment x body size: F1, 11 = 0.733, p = 0.410; F0 x F1 x body size:

F1, 11 = 2.496, p = 0.142), and when I removed them from the model, the covariate did not have a significant effect on egg size (F1, 14 = 0.085, p = 0.774), so it was removed from the model also.

The final model, a 2-way ANOVA, showed no significant effect of stress history, current stress, or an interaction between the two (stress history: F1, 15 = 0.438, p = 0.518; current stress: F1, 15 =

1.450, p = 0.247, stress history x current stress F1, 15 = 0.822, p = 0.379).

F1 Egg size: Density Analysis

Body size explained some of the variation in egg size; the slopes of egg size vs. body size were homogeneous (stress history x body size: F1, 20 = 0.474, p = 0.499; current stress x body size: F1,

20 = 1.572, p = 0.224; stress history x current stress x body size: F1, 20 = 0.007, p = 0.933). The covariate had a significant effect on egg size (F1, 23 = 5.309, p = 0.031). In contrast, egg number

(sqrt transformed) did not explain any of the variation in egg size; slopes of egg size vs. egg number per treatment were homogeneous (stress history x body size: F1, 23 = 1.009, p = 0.326; current stress x body size: F1, 23 = 0.211, p = 0.651; stress history x current stress x body size: F1,

23 = 1.018, p = 0.323), and the common covariate did not have a significant effect on egg size

(F1, 26 = 3.129, p = 0.089) and was removed from the model. The final model showed no significant effect of stress history, current stress, or an interaction between the two (2-way

ANCOVA with body size as the covariate; stress history: F1, 23 = 0.071, p = 0.793; current stress:

F1, 23 = 0.370, p = 0.549, stress history x current stress F1, 23 = 0.005, p = 0.944).

Discussion

The results from this study indicate that mothers under environmental stress influence offspring phenotype (display maternal effects), but the results do not support the hypothesis that Tenebrio molitor mothers under environmental stress distribute resources to their offspring in such a way that benefits offspring phenotype and fitness (anticipatory maternal effects). Under parasite stress, maternal effects led to a reduction in offspring performance (selfish maternal effects); maternal fitness occurred at the expense of offspring fitness. Under density stress, I found that maternal effects affected offspring reproduction, but in a way that generally did not appear to benefit offspring (selfish maternal effects). The current treatment had a more pronounced effect on offspring phenotype, and resulted in negative effects on larval performance, and an increase in offspring fecundity.

Parasite Stress

Contrary to my expectations, I found that there were no direct costs to having parasites. The maternal parasite treatment did not have a significant effect on the maternal generation versus the control treatment for larval development or survival, on adult female death, timing of eggs, egg number or egg size. Since there were no direct effects of parasites in the maternal generation, there was no evidence of trade-offs between any of these fitness-related traits. As with the maternal generation, there were no direct costs of the current parasite treatment (the offspring parasite treatment, F1P) on offspring. Offspring whose current treatment was parasites showed no difference from the control in terms of larval growth and development, larval mortality, adult female death, timing of eggs, or female egg number or size. However, the maternal parasite treatment did affect offspring phenotype. My expectations were that mothers under parasite stress would positively influence offspring fitness-related life history traits (anticipatory maternal effects). Contrary to my expectations, maternal effects due to parasite stress reduced offspring performance (selfish maternal effects). Offspring with a stress history of parasites took 11.2% longer to develop than those with a stress history of the control treatment as larvae, median larval mortality was 50% higher, and larvae grew at a slower rate until late in larval development, at which point they were able to catch up to offspring who had a stress history of the control. There was no evidence for any effects of maternal treatment on offspring adult female death, timing of eggs, egg quantity or quality; it appears that the maternal effects do not extend beyond offspring larval traits. Additionally, there was no interaction between stress history and current treatment for any of the life history measurements. Having a parasite stress history did not interact with the current treatment to reduce the negative impact of parasites.

In this study I found that maternal effects led to reduced offspring larval survival, longer development times, and slower growth rates until late in development. Offspring performance was reduced due to the maternal parasite environment regardless of the current environment offspring were subjected to. To the best of my knowledge, these selfish maternal effects are contrary to those findings in other trans-generational parasite studies in invertebrates that have found evidence for maternal effects; these studies show anticipatory maternal effects that benefit offspring phenotype by reducing susceptibility to parasites and reducing harm inflicted by parasites (Little et al. 2003; Moret 2006; Rolff 1999).

Perhaps there are factors at work that are limiting increased offspring fitness in Tenebrio molitor. Marshall & Uller (2007) suggest that selection on mothers may lead to reductions in offspring fitness when the maternal effect is costly to mothers. Mothers may suffer reduced current or future fecundity by investing more in reproduction, and it may instead be beneficial for the long term fitness of mothers to decrease investment in offspring (Marshall & Uller 2007).

Maternal survival may even be reduced if mothers invested more in reproduction (Marshall &

Uller 2007). Alternatively, selection on increased offspring fitness may be inefficient (Marshall

& Uller 2007); there may not be adequate genetic variation in the species for females to make adjustments to eggs. Also, gregarine parasite levels may be stable in the environment, and so females are already coping under gregarine parasite stress as best as they can. I do not think that the gregarine parasite environment is stable in the environment; infection levels should vary with food supply. Host frass containing infective gregarine gametocysts tend to settle to the bottom of the foodstuff, and as food levels dwindle, hosts are in closer physical contact with gregarine infective oocysts. This leads to greater probabilities of contacting infections. Even for hosts in the natural environment that live in bird nests, T. molitor should be food limited after birds

41 fledge, and it is possible that hosts may consume food that is in close contact with gregarines before searching for a new food source.

In this study I did not measure immunity or parasite resistance in mothers and offspring.

It is possible that mothers were providing aspects of their immunity to their offspring. Several studies have demonstrated that trans-generational immune priming occurs in insects (Moret

2006; Sadd et al. 2005), and it has certainly been shown that T. molitor mothers are capable of enhancing offspring immunity, at least under bacterial infections (Moret 2006). Whether T. molitor mothers can enhance offspring immunity to a parasite that produces a different immune response in hosts is unknown. While I found that offspring of parasitized mothers fared poorly in their current environment, it is possible that mothers provided their eggs with enhanced immunity and that offspring performed better than they would have had their mothers not done so. I suspect that mothers were not investing immunity in their eggs under gregarine parasitism, because if they were then offspring possessing a stress history of parasites would have had increased survival and/or fitness under the current parasite treatment (F0P F1P) versus offspring under parasite stress that did not possess a parasite stress history (F0C F1P). Instead, possessing a parasite stress history reduced offspring performance compared to offspring that did not possess a parasite stress history. Even if mothers were enhancing offspring immunity (perhaps if enhancing immunity was not costly to mothers) overall investment in offspring was still lower, which reduced offspring fitness. Only direct measures of immunity in this system could truly determine whether mothers were investing immunity into their offspring, although if mothers were, increased immunity did not appear to benefit offspring.

Impact of Parasites within a Single Generation of Hosts

My finding that gregarines did not inflict a direct cost to hosts is consistent with two other studies of gregarine infections in T. molitor. Rodriguez et al. (2007) showed that when T. molitor was infected with Gregarina niphandrodes, a gregarine species that infects adult T. molitor, there was no effect of gregarine infection on longevity measures within a single generation, except under severe infections. Using a similar diet and one of the same gregarine species that I used in this study, Harry (1967) found that under an optimal diet, there was no significant difference in the length of larval development or in pupal weight between T. molitor larvae that were infected with Gregarina polymorpha and those that were not infected.

The literature is strewn with conflicting views of the effect that gregarines have on invertebrate hosts. Sumner (1933) suggests that gregarines provide a necessary nutrient that is essential to host growth and longevity. Most other early studies report that gregarines are relatively harmless to their invertebrate hosts (Canning 1956), and Weiser (1963) suggests that gregarines that reside only in the gut lumen (as with the Gregarina genus of this study) are harmless commensals, while those that attack host tissues are pathogenic. More recent studies report that gregarines have a negative effect on host longevity and growth, although the effect is only seen under limited food availability. For example, T. molitor hosts fed a sub-optimal diet showed reduced larval growth when infected, but there were no effects when infected hosts were fed an optimal diet (Harry 1967). Likewise, infected field crickets, Gryllus pennsylvanicus, suffered reduced longevity and greater reductions in weight when under sub-optimal diet than control food-deprived crickets, but did not suffer when fed ad libitum (Zuk 1987). Additionally, the polymorphic damselfly, Mnais costalis Selys, did not suffer reduced longevity under high food availability when infected, while when food levels were low, survival was negatively

43 correlated with parasite abundance for both morphs (Tsubaki & Hooper 2004). Thus, from these studies it appears that the impact of gregarines on their host species is context-dependent.

Trans-generational Impact of Parasites on Hosts

The above studies draw their conclusions from the effects of gregarine infection on a single generation of hosts. This study goes a step further and examines the trans-generational effects of gregarines. Contrary to what has been found in the literature, I found that under a nutrient rich diet hosts infected with gregarines do in fact harm their hosts. However, the harmful effects are not direct; the negative effects aren‟t seen on the generation inflicted by the parasite (results that are comparable to the findings of Harry (1967) under a similar optimal diet). Instead the effects of the parental infection appear in host offspring, and the effects are quite drastic for development, growth and longevity. This result highlights the importance of studying parasitism from a trans-generational perspective.

It is unclear how offspring could be negatively affected by gregarines when there are no negative effects of infection acting on mothers. Egg size has traditionally served as a proxy for egg quality (i.e. larger eggs contain more organic matter) (Bernardo 1996b; McEdward &

Coulter 1987); smaller eggs often produce smaller offspring that suffer reduced survival and/or reproduction in their environment (Mousseau & Fox 1998b). Nevertheless, while I found poor offspring performance was related to a stress history of parasitism, I found no corresponding evidence for reduced egg size under parasitism.

Several studies have noted that egg size alone does not adequately predict offspring quality (Bernardo 1996b), as nutrient composition of eggs can vary independently of size (Giron

& Casas 2003). Embryo size in polychaete worms was found to be poorly correlated with nitrogen and carbon content; a large amount of variation in parental investment was unaccounted for by embryo size (Bridges 1993). Similarly, siblings of the starfish, Pteraster tesselatus, did not show a correlation between egg size and energetic content (McEdward & Coulter 1987).

Benton et al. (2008) therefore warns that maternal influence on eggs may be cryptic, such that aspects of propagule investment may go undetected from examining egg size.

Gregarines reside in the gut of their hosts and feed off of the nutrients that hosts ingest, and I suggest that poor offspring performance we see in this study is the result of parasitism causing a reduction in the amount of nutrients females have to devote to their eggs (Hurd 2009).

If this reasoning is correct then under maternal effects theory it is expected that, all else being equal, when there are fewer available nutrients, mothers would manipulate resource allocation to their eggs in response to parasitism. If mothers were able to alter egg nutrient content, then it might benefit their fitness if they laid fewer eggs that possessed more of the available nutrients.

In this way, the fewer offspring would be of better quality and be better equipped to compete against their conspecifics, survive, and reproduce. Yet the results of this study indicate that parasitized mothers do not alter egg number and quality; perhaps laying fewer, better quality eggs is not the best strategy for female fitness in this species, and instead females were investing less resources per egg to produce as many eggs as they would had they not been parasitized.

Evidence of this has not been detected in this study by measuring egg size, but would instead require measures of biochemical composition of lipids, proteins, and sugars in eggs.

It is also possible that offspring fare poorly because mothers are trading-off resources they devote to their eggs with investing immunity to parasites. If females are investing immunity

45 in their eggs, they may have less of other resources to devote to their offspring (e.g. essential lipids and proteins). This may also explain why offspring suffer reduced growth and survival.

Limitations of my findings

I recognize that the conclusions I draw from this study may be context-dependent and that had I subjected mothers to harsher environmental conditions, such as low food levels, I would have found that gregarines were more damaging to their maternal hosts, as Harry (1967), Zuk (1987), and Tsubaki & Hooper (2004) found. Perhaps only under much harsher environments, where parasites inflict extensive direct damage to their maternal hosts, do mothers differentially invest more resources in their eggs, leading to maternal effects that increase offspring fitness compared to their conspecifics. I do not rule out the possibility that anticipatory maternal effects can occur under gregarine parasitism, and future studies should examine how varying levels of other environmental stressors can lead to possible maternal effects of parasitism.

It could also be argued that had I instead (or additionally) chosen to infect adult T. molitor hosts during the reproductive stage, I may have seen anticipatory maternal effects. For example, Mitchell & Read (2005) found that Daphnia magna females that experienced a non- stresssful juvenile environment but a poor adult environment (crowded, low food, infrequent water changes) produced offspring that were less susceptible to bacterial infections. However, I do not think that adult infections in T. molitor would have more likely led to an anticipatory maternal effect. The gregarine assemblage is less diverse in T. molitor adults (Gregarina niphandrodes is the only species that commonly parasitizes T. molitor), and Rodriguez et al.

(2007) found that only under severe infections does G. niphandrodes affect its host, so

46 reproduction should not be impacted severely. Additionally, other studies have found that the maternal juvenile environment, rather than the maternal adult environment, has the most influence on offspring fitness (Taborsky 2006a; Taborsky 2006b) and so mothers should more likely enhance offspring fitness if they are exposed to a juvenile stress.

Density Stress

In line with my expectations, I found that there were direct negative costs to living in high densities as larvae. In the maternal generation, larvae suffered reduced survival, where 1 of 8 larvae died per container (a 12.5% reduction in median survival per container) under a high density treatment. Larval development time, adult female death, timing of eggs, egg number and egg size were not affected by a density treatment, nor was there any evidence for trade-offs between life history traits. In the offspring generation, the current density stress reduced larval survivorship by 1 of 8 larva per treatment container (a 12.5 % reduction in median survival per container) and also reduced larval growth. Larval development time was not affected by the treatment. As adults, females laid more eggs at all body sizes over a longer time period, and displayed a trend toward longer lives than the control treatment. Egg size was not affected by current density treatment.

Mothers under density stress influenced offspring fecundity, and the maternal effect generally led to a reduction in offspring fitness (selfish maternal effects). The effect of stress history on the number of eggs that offspring females laid changed with different body sizes; at smaller body sizes, offspring females with a stress history of density laid a greater number of eggs versus offspring females with a stress history of the control, but the effect was opposite at

47 larger (and at the majority of) body sizes. The positive effect on offspring female fecundity occurred only at the smallest of body sizes, therefore the overall pattern appeared to be that offspring females with a stress history of density laid less eggs. Selfish maternal effects due to density stress are contrary to my expectations, as I had expected that mothers with a density stress would produce offspring with increased fitness. Additionally, there were no interactions between maternal treatment and offspring treatment for any of the life history measurements.

Having a density stress history did not interact with the current treatment to reduce the negative impact of density on offspring.

In this study I found that maternal effects of density stress generally led to reduced offspring fecundity (with the exception of offspring females possessing small body sizes), which suggests that females were investing less in offspring fitness in order to enhance their own fitness. These results are contrary to those findings in other trans-generational density studies, as they have shown that mothers under density stress increase investment in offspring, leading to increased offspring fitness (Allen et al. 2008; Leips et al. 2009). As I discussed above under selfish maternal effects due to parasite stress, under density stress there could be factors at work that are limiting increased offspring fitness due to density stress in Tenebrio molitor. Mothers may be enhancing their fitness by reducing investment in their offspring, or selection on increased offspring fitness may be inefficient (Marshall & Uller 2007).

Impact of Poor Environment

Theory proposes that in general, larger offspring are fitter (Fox & Czesak 2000; Marshall et al.

2006), and that due to a finite number of resources, selection balances between fewer and larger

48 offspring, and a greater number of smaller offspring (Smith & Fretwell 1974). In competitive environments, larger offspring size can be beneficial to offspring fitness, while under favourable conditions offspring size has been found to have little influence on offspring fitness (Marshall et al. 2006; Parker & Begon 1986). Empirical studies show that in poor environments (i.e. high density, low food, or both), differences in initial offspring size can have important consequences for offspring growth and development. For example, in the frog, Bombina orientalis, at high densities and low food, smaller initial offspring size resulted in smaller larval size through to metamorphosis and longer larval periods (Parichy & Kaplan 1992). Similarly, in the brook trout,

Salvelinus fontinalis, mortality levels were highest for smallest eggs under low food conditions

(Hutchings 1991).

Consequently, mothers should invest in fewer, larger offspring in poor environments and more numerous, small offspring in favourable environments (Fox & Mousseau 1996; Fox et al.

1997; Marshall et al. 2006; Parker & Begon 1986). In the bryozoan, Bugula neritina, mothers in high densities produced larger larvae that were better competitors and had a higher dispersal potential (Allen et al. 2008), while at low densities they produced a higher number of smaller larvae. Female least killfish, Heterandria formosa, that experienced high density brooding environments also produced larger offspring (Leips et al. 2009). These results suggest that mothers are able to evaluate the quality of the environment and adjust offspring size in poor conditions. In the current study I did not find evidence that females adjusted their egg size or number in response to the poor environment to benefit offspring, as offspring eggs were as small and numerous as those produced in the maternal control treatment. The resulting small offspring fared poorly in the current density environment.

Increase in Fecundity

An unexpected result was that offspring females of the current density treatment produced more eggs at all body sizes, over longer time periods than offspring females of the control treatment.

Unfortunately, I did not collect data for the F2 generation, so I cannot speculate as to what class of maternal effect this increase in fecundity falls under. There are several possible explanations for the unexpected increase in reproductive investment of offspring of the current density treatment. One possibility is that in the density treatment the weaker offspring died, which selected for the strongest, most competitive females to mature and reproduce. In contrast, survival was high in the control treatment, and females of variable fitness could mature and reproduce, resulting in a lower overall fecundity. This scenario seems somewhat unlikely because survival differed only by 12.5% between the control and density treatments and because only 1 of 8 larvae died per container in the density treatment, and thus the majority of females in the density treatment lived to reproduce. Another possibility is that offspring females invested more of their resources in reproduction because they “expected” to die early as adults, given that larval survival suffered under the density treatment. Again, I think this possibility was unlikely because survival did not decrease drastically in the density treatment.

I think it more likely that due to high larval density, females perceived that density levels would continue to be high after maturation. Females may have produced more eggs in order to compensate for the fitness reduction that would occur if a portion of their eggs would be eaten by conspecifics. Indeed, high density levels during reproduction can be detrimental to female fecundity. For example, Gerber (1984) found that T. molitor conspecifics readily consumed 100

(20%) of 500 conspecific eggs buried in their foodstuff in as little as 4 days. A large body of studies on cannibalism have been conducted in the flour beetle (Tribolium genus), who is similar

50 to T. molitor in its feeding and egg laying behaviours and who also exhibits limited dispersal.

Studies show that cannibalistic behaviour increases with density, and conspecific cannibals can eliminate competitors, gain nutritional benefits (Fox 1975), accelerate their development, and increase their survival and fecundity (Via 1999). If females reared at high larval densities perceive a significant threat to their eggs then it may explain why females in this study did not lay fewer, larger eggs. Had females invested in more resources per offspring, their fitness may have been much lower if high density levels persisted in the adult environment because cannibalism on several high-investment eggs would reduce a female‟s fitness considerably more than cannibalism on several low-investment eggs.

Presumably there is a cost to this increased fecundity but I did not detect any costs in the reproductive traits I measured. Females did not suffer reduced adult survivorship due to an increase in fecundity, nor did they reduce their egg size. I suggest that one of two possible reasons can explain the lack of a detected trade-off: 1) As I suggested with the parasite analysis, egg size may not be a reliable indicator for nutrient content of eggs, and perhaps females were investing fewer nutrients per egg than the control treatment, as a trade-off for the increase in egg number. 2) Perhaps larval cannibalism provided surviving larvae with additional nutrients, which allowed females to lay more eggs at no cost to females. This would explain why a trade- off was not detected. If cannibalistic behaviour did in fact increase egg number, then this result is not due to a maternal effect, since maternal effects imply that mothers are adjusting offspring phenotype. When extra nutrients are available, females can simply producing more eggs without adjusting offspring phenotype. I cannot rule out either of these two possibilities from this experiment.

The increase in offspring female reproduction under density stress is the opposite response to that of the previous generation, where the maternal generation generally reduced fecundity compared to the control. I cannot explain with certainty as to why offspring generation females experienced increased fecundity under density stress but maternal generation females reduced fecundity. Density stress resulted in similar effects on larval traits; both the maternal generation and the offspring generation showed the same level of reduced survivorship. It is possible that the offspring generation perceived slightly higher density levels than the maternal generation, since for the offspring generation I had kept larvae of all treatments in small petri dishes for 24 days before transferring them to their bigger treatment containers (see Methods:

Offspring Generation for details), where they would have had greater contact between conspecifics as young larvae. Therefore, perhaps female T. molitor laid more eggs in response to greater perceived densities and fewer eggs at lower perceived densities. This is purely speculation and an experiment would have to be conducted to provide evidence that this is the case.

Mothers Faced with Different Types of Environmental Stress do not Adjust Offspring Phenotype for the Future Environment in Similar Ways

Maternal effects were seen under both types of environmental stressors. However, I did not find that environmentally stressed mothers influenced offspring in such a way that offspring fitness was enhanced (anticipatory maternal effects) under either type of stressor. Still, there were interesting similarities and differences in the way that populations responded to each type of stressor. Under both types of stress, it appeared that the maternal generation was selfishly maximizing its own fitness at the expense of its offspring; offspring chances of survival (parasite

52 stress) or fecundity (density stress) were reduced due to maternal influence. Under density stress, the current environment appeared to have a stronger influence over offspring than their stress history, as the current environment affected multiple larval and adult life history traits. It appeared that the offspring juveniles that faced high density conditions may have produced more eggs as adults in an attempt to compensate for the reduced fecundity they would experience if their conspecifics ate a portion of their eggs, as would occur under high adult density. Under parasite stress, maternal effects appeared to be short-lived (not extending beyond early offspring traits), and early offspring longevity and growth appeared to be completely dependent on maternal influence.

I recognize that for the offspring generation my samples sizes were low for the analyses pertaining to measures of reproduction. This was largely due to the reductions in sample size that occurred due to reduced larval survival, and seems to affect the parasite analyses particularly

(see appendix for sample sizes). As a result, my ability to detect interaction effects in the reproduction analyses may have been compromised. It is possible that the maternal parasite environment interacted with the offspring environment, although given the results that the maternal environment resulted in negative effects on offspring fitness-related larval traits, it seems unlikely that an interaction would have occurred.

The similarities and differences in results between hosts exposed to each type of stressor should be interpreted with caution, as I only tested host response to each type of stressor at one level. In order for the two types of stressors to be truly comparable, not only would I need to measure host response at varying levels of each type of stress (e.g. different parasite intensities or different density levels), but I would also need to combine both types of stressors (e.g. measure host response to parasite stress under varying levels of density). As I have pointed out

53 under parasite stress, maternal effects are likely to be context-dependent, and the strength and direction of maternal effects may differ depending on the level of the stress (high vs. low stress) and the harm of the stress to hosts. Organisms in their natural environment may be exposed to a multitude of stressors concurrently, and environments may change constantly, thus future studies should examine a multitude of varying environmental conditions.

Little is known about the extent that parasite-mediated maternal effects can affect invertebrate hosts. There is a need for continued empirical studies that determine which species exhibit maternal effects, and whether maternal effects can be generalized to include all invertebrates. In this study I found evidence for selfish maternal effects under each type of stressor, but I think that future studies should focus on what conditions lead mothers to selfishly maximize their own fitness at their offspring‟s expense, versus the conditions that lead mothers to contribute more resources to offspring fitness.

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Table 1. Results of MANOVA of stress history and current stress on development time and adult body size in the offspring generation for parasite vs. control treatments. Due to significant results, ANOVAs were carried out. Variable df F p MANOVA Stress History (Pillai's Trace = 0.339) 2, 27 6.929 0.004 Current Stress (Pillai's Trace = 0.108) 2, 27 1.641 0.213 Stress History x Current Stress (Pillai's Trace = 0.013) 2, 27 0.171 0.844

ANOVAs Stress History Development Time 1, 28 14.291 0.001 Adult Body Size 1, 28 0.132 0.719 Current Stress Development Time 1, 28 0.303 0.586 Adult Body Size 1, 28 3.058 0.091 Stress History x Current Stress Development Time 1, 28 0.090 0.766 Adult Body Size 1, 28 0.258 0.616

Table 2. Results of a repeated measures ANOVA on larval growth over time in the offspring generation for parasite vs. control treatments. Time is the within-subjects factor and stress history and current treatment are the between-subjects factors. Variable df F p Multivariate Within-Subjects Effects Time (Pillai's Trace V = 0.945) 3, 32 184.563 <0.00 1 Time x Stress History (Pillai's Trace V = 0.304) 3, 32 4.666 0.008 Time x Current Stress (Pillai's Trace V = 0.007) 3, 32 0.076 0.972 Time x Stress History x Current Stress (Pillai's Trace V = 0.081) 3, 32 0.94 0.433

Between -Subjects Effects Stress History 1, 34 11.647 0.002 Current Stress 1, 34 0.043 0.837 Stress History x Current Stress 1, 34 0.377 0.543

Table 3. Results of a repeated measures ANOVA on larval growth over time in the offspring generation for density vs. control treatments. Time is the within-subjects factor and stress history and current treatment are the between-subjects factors. Variable df F p Multivariate Within-Subjects Effects Time (Pillai's Trace V = 0.984) 3, 53 1111.086 <0.001 Time x Stress History (Pillai's Trace V = 0.014) 3, 53 0.25 0.861 Time x Current Stress (Pillai's Trace V = 0.085) 3, 53 1.636 0.192 Time x Stress History x Current Stress (Pillai's Trace V = 0.018) 3, 53 0.33 0.804

Between -Subjects Effects Stress History 1, 55 0.143 0.706 Current Stress 1, 55 5.775 0.020 Stress History x Current Stress 1, 55 0.191 0.663

Table 4. Results of a repeated measures ANOVA on the timing of egg laying in the offspring generation for parasite vs. control treatments. Percent of eggs laid is the repeated measure and stress history and current stress are the between-subjects factors. Variable df F p Univariate Within-Subjects Effects Percentage of eggs laid 1, 16 57.534 <0.001 Percentage of eggs laid x Stress History 1, 16 0.004 0.950 Percentage of eggs laid x Current Stress 1, 16 0.877 0.363 Percentage of eggs laid x Stress History x Current Stress 1, 16 0.498 0.491

Between -Subjects Effects Stress History 1, 16 1.016 0.328 Current Stress 1, 16 0.656 0.430 Stress History x Current Stress 1, 16 1.409 0.253

Table 5. Results of a repeated measures ANOVA on the timing of egg laying in the offspring generation for density vs. control treatments. Percentage of eggs laid is the repeated measure and stress history and current stress are the between-subjects factors. Variable df F p Univariate Within-Subjects Effects Percentage of eggs laid 1, 28 131.246 <0.001 Percentage of eggs laid x Stress History 1, 28 0.002 0.962 Percentage of eggs laid x Current Stress 1, 28 1.335 0.223 Percentage of eggs laid x Stress History x Current Stress 1, 28 2.368 0.135

Between -Subjects Effects Stress History 1, 28 1.976 0.171 Current Stress 1, 28 4.948 0.034 Stress History x Current Stress 1, 28 0.182 0.673

F0 generation F1 generation Control Stress A ≤ F0 C_F1 C and ≥ F0 Stress Control best A_F1 Stress A ≤ F0 C_F1 C and > F0 C_F1 Stress A worst Stress A Explorative; might = F0 Stress A_F1 Stress A or Stress B might = F0 C_F1 Stress A

Figure 1. Experimental design predictions of the interactions between the maternal (F0) and offspring (F1) generations on fitness indicators of F1 individuals.

Figure 2. Gregarine infection procedure. See text for details.

Figure 3. Experimental schedule. See text for details.

(a)

(b)

(c)

Figure 4. Analyses, including treatment combinations F0D F1P and F0P F1D. (a) Fully factorial experimental design, which includes all combinations of stress histories and current stresses. (c) F1 Parasite Analysis, which included planned comparisons for offspring whose current treatment was parasites, regardless of their stress history (F0C F1P, F0D F1P, F0P F1P), offspring who possessed a parasite stress history and whose current stress was a control treatment (F0P F1C), and offspring who possessed both a control treatment stress history and a control treatment current stress (F0C F1C). (c) F1 Density Analysis, which includes planned comparisons for offspring whose current treatment was density, regardless of their stress history (F0C F1D, F0P F1D, F0D F1D), offspring who possessed a density stress history and whose current stress was a control treatment (F0D F1C), and offspring who possessed both a control treatment stress history and a control treatment current stress (F0C F1C).

(a)

(b)

(c)

Figure 5. Analyses, excluding treatment combinations F0D F1P and F0P F1D. (a) Overall experimental design, which does not include all combinations of stress histories and current stresses. (b) F1 Parasite Analysis, which included planned comparisons for offspring whose current treatment was parasites (F0C F1P and F0P F1P), offspring who possessed a parasite stress history and whose current stress was a control treatment (F0P F1C), and offspring who possessed both a control treatment stress history and a control treatment current stress (F0C F1C). (c) F1 Density Analysis, which includes planned comparisons for offspring whose current treatment was density (F0C F1D and F0D F1D), offspring who possessed a density stress history and whose current stress was a control treatment (F0D F1C), and offspring who possessed both a control treatment stress history and a control treatment current stress (F0C F1C).

Figure 6. Effect of stress history (F0) on offspring development time (mean ± 1 s.e.) for parasite vs. control treatments. * indicates p <0.05.

Figure 7. (a) Effect of maternal treatment (F0) on larval survival in the maternal generation. (b) Effect of stress history (F0) on offspring larval survival for parasite vs. control treatments. (c) Effect of current stress (F1) on offspring larval survival for density vs. control treatments. Medians are plotted, and the boxes represent the interquartile range; vertical bars represent the range of values within 1.5 times the interquartile range of the median. Open circles represent outliers between 1.5 and 3 box lengths from the upper or lower edge of the box. Asterisks represent extreme values that are more than 3 box lengths from the upper or lower edge of the box.

Figure 8. (a) Effect of time and stress history (F0) on offspring growth for parasite vs. control treatments (mean mass ± 1 s.e.). (b) Effect of time and current stress (F1) on offspring growth for density vs. control treatments (mean ± 1 s.e.).

Figure 9. Time (mean number of days per female ± 1 s.e.) for F1 individuals exposed to current stress treatments (F1) of control vs. density to lay 50% and 100% of their eggs.

Figure 10. (a) Effect of stress history and body size on offspring total egg number (sqrt mean total egg number per female ± 1 s.e.) for density vs. control treatments. (b) Effect of current stress and body size on offspring total egg number in the density vs. control treatments (sqrt mean total egg number per female ± 1 s.e).

Appendices

Appendix Table 1: Means, standard errors (s.e.), and sample sizes (n) for all F0 generation analyses Treatment F0 C F0 D F0 P Variable Mean S.E. n Mean S.E. n Mean S.E. n LARVAL DEVELOPMENT Development Time 35.909 1.027 12 37.525 1.029 11 38.283 1.027 12 body size (mm) 11.528 0.128 12 11.401 0.133 11 11.405 0.128 12

SURVIVAL Proportion survival per container (median values) 1.000 n/a 12 0.875 n/a 11 1.000 n/a 13

TIMING OF EGGS 50% of eggs laid 28.820 3.115 11 29.080 2.028 12 37.000 5.002 12 100% of eggs laid 102.450 11.420 11 95.500 10.201 12 121.830 12.893 12

ADULT FEMALE DEATH Adult female death 117.750 12.102 12 112.667 12.102 12 142.250 12.102 12

TOTAL EGG NUMBER Total number of eggs per female 452.545 64.754 12 523.833 61.997 12 641.917 61.997 12

EGG SIZE mean egg size (mm) 1.361 0.042 11 1.359 0.036 12 1.386 0.037 12

Appendix Table 2: Means, standard errors (s.e.), and sample sizes (n) for all F1 generation parasite vs. control analyses Treatment Stress History Current Stress F0 Control F0 Parasite F1 Control F1 Parasite Variable Mean S.E. n Mean S.E. n Mean S.E. n Mean S.E. n DEVELOPMENT Development Time 57.743 1.018 19 64.200 1.022 13 61.375 1.018 18 60.401 1.021 14 body size (mm) 11.083 0.100 19 11.025 0.124 13 11.193 0.103 18 10.915 0.121 14

SURVIVAL Proportion survival per container (median values) 1.000 n/a 20 0.500 n/a 25 1.000 n/a 23 1.000 n/a 22

LARVAL GROWTH (g) day 0 0.045 0.003 20 0.030 0.003 18 0.037 0.003 19 0.038 0.003 19 day 10 0.059 0.003 20 0.039 0.003 18 0.049 0.003 19 0.049 0.003 19 day 24 0.110 0.006 20 0.074 0.007 18 0.091 0.006 19 0.093 0.006 19 day 38 0.173 0.009 20 0.149 0.009 18 0.162 0.009 19 0.162 0.009 19

Appendix Table 2: Means, standard errors (s.e.), and sample sizes (n) for all F1 generation parasite vs. control analyses Treatment Stress History Current Stress F0 Control F0 Parasite F1 Control F1 Parasite Variable Mean S.E. n Mean S.E. n Mean S.E. n Mean S.E. n TIMING OF EGGS 50% of eggs laid 45.377 1.091 13 51.78 1.135 7 53.464 1.101 10 43.992 1.127 10 100% of eggs laid 89.300 1.102 13 103.131 1.154 7 97.222 1.114 10 94.727 1.145 10

ADULT FEMALE DEATH Adult female death 112.393 1.090 12 122.732 1.134 4 118.748 1.126 15 116.164 1.126 21

TOTAL EGG NUMBER Total number of eggs per female 199.064 3.007 13 334.086 6.477 7 243.98 3.702 10 281.132 5.784 20

EGG SIZE mean egg size (mm) 1.113 0.029 11 1.081 0.040 7 1.127 0.032 9 1.067 0.038 9

Appendix Table 2: Means, standard errors (s.e.), and sample sizes (n) for all F1 generation parasite vs. control analyses Treatment Stress History x Current Stress F0 Control F1 F0 Control F1 F0 Parasite F1 F0 Parasite F1 Control Parasite Control Parasite Variable Mean S.E. n Mean S.E. n Mean S.E. n Mean S.E. n DEVELOPMENT Development Time 57.916 1.024 10 57.512 1.026 9 64.975 1.027 8 63.434 1.035 5 body size (mm) 11.182 0.137 10 10.984 0.145 9 11.204 0.153 8 10.846 0.194 5

SURVIVAL Proportion survival per container (median values) 1.000 n/a 10 1.000 n/a 10 0.500 n/a 13 0.500 n/a 12

LARVAL GROWTH (g) day 0 0.044 0.004 10 0.045 0.004 10 0.030 0.004 9 0.031 0.004 9 day 10 0.059 0.005 10 0.059 0.005 10 0.038 0.005 9 0.039 0.005 9 day 24 0.110 0.009 10 0.109 0.009 10 0.076 0.009 9 0.076 0.009 9 day 38 0.179 0.012 10 0.167 0.012 10 0.157 0.013 9 0.157 0.013 9

Appendix Table 2: Means, standard errors (s.e.), and sample sizes (n) for all F1 generation parasite vs. control analyses Treatment Stress History x Current Stress F0 Control F1 Control F0 Control F1 Parasite F0 Parasite F1 Control F0 Parasite F1 Parasite Variable Mean S.E. n Mean S.E. n Mean S.E. n Mean S.E. n TIMING OF EGGS 50% of eggs laid 47.608 1.146 5 43.250 1.113 8 59.979 1.146 5 44.701 1.240 2 100% of eggs laid 80.883 1.165 5 98.692 1.129 8 116.86 1.165 5 90.922 1.273 2

ADULT FEMALE DEATH Adult female death 102.412 1.145 5 123.224 1.112 8 137.827 1.145 5 109.399 1.237 2

TOTAL EGG NUMBER Total number of eggs per female 132.273 7.398 5 279.458 4.627 7 389.668 7.398 5 282.778 18.499 2

EGG SIZE mean egg size (mm) 1.121 0.048 4 1.106 0.034 7 1.133 0.043 5 1.028 0.068 2

Appendix Table 3: Means, standard errors (s.e.), and sample sizes (n) for all F1 generation density vs. control analyses Treatment Stress History Current Stress F0 Control F0 Density F1 Control F1 Density Variable Mean S.E. n Mean S.E. n Mean S.E. n Mean S.E. n DEVELOPMENT Development Time 58.148 1.020 18 56.261 1.013 42 56.600 1.016 33 57.801 1.017 27 body size (mm) 11.090 0.102 18 10.832 0.067 42 11.016 0.081 33 10.906 0.090 27

SURVIVAL Proportion survival per container (median values) 1.000 n/a 18 1.000 n/a 44 1.000 n/a 35 0.875 n/a 27

LARVAL GROWTH (g) day 0 0.041 0.002 18 0.037 0.001 41 0.041 0.002 32 0.037 0.002 27 day 10 0.053 0.003 18 0.052 0.002 41 0.057 0.002 32 0.048 0.002 27 day 24 0.102 0.005 18 0.102 0.003 41 0.108 0.004 32 0.095 0.004 27 day 38 0.174 0.005 18 0.174 0.003 41 0.180 0.004 32 0.168 0.004 27

Appendix Table 3: Means, standard errors (s.e.), and sample sizes (n) for all F1 generation density vs. control analyses Treatment Stress History Current Stress F0 Control F0 Density F1 Control F1 Density Variable Mean S.E. n Mean S.E. n Mean S.E. n Mean S.E. n TIMING OF EGGS 50% of eggs laid 51.898 0.101 12 43.112 0.059 4 42.772 0.088 15 52.273 0.071 21 100% of eggs laid 99.202 0.224 12 87.329 0.130 4 81.108 0.195 15 106.069 0.158 21

ADULT FEMALE DEATH Adult female death 116.629 1.095 12 104.167 1.071 4 98.889 1.089 15 122.978 1.079 21

TOTAL EGG NUMBER Total number of eggs per female 181.710 1.777 12 147.671 1.134 17 93.799 1.713 13 254.275 1.208 16

EGG SIZE mean egg size (mm) 1.090 0.031 11 1.100 0.024 17 1.107 0.030 12 1.083 0.025 16

Appendix Table 3: Means, standard errors (s.e.), and sample sizes (n) for all F1 generation density vs. control analyses Treatment Stress History x Current Stress F0 Control F1 F0 Control F1 F0 Density F1 F0 Density F1 Control Density Control Density Variable Mean S.E. n Mean S.E. n Mean S.E. n Mean S.E. n DEVELOPMENT Development Time 57.916 1.026 10 58.440 1.029 8 55.313 1.017 23 57.168 1.019 19 body size (mm) 11.182 0.136 10 10.998 0.152 8 10.850 0.09 23 10.813 0.099 19

SURVIVAL Proportion survival per container (median values) 1.000 n/a 10 0.875 n/a 8 1.000 n/a 25 0.908 n/a 19

LARVAL GROWTH (g) day 0 0.044 0.003 10 0.037 0.003 8 0.037 0.002 22 0.037 0.002 19 day 10 0.059 0.004 10 0.048 0.004 8 0.055 0.002 22 0.049 0.003 19 day 24 0.110 0.007 10 0.094 0.007 8 0.107 0.004 22 0.097 0.005 19 day 38 0.179 0.006 10 0.170 0.007 8 0.180 0.004 22 0.167 0.005 19

Appendix Table 3: Means, standard errors (s.e.), and sample sizes (n) for all F1 generation density vs. control analyses Treatment Stress History x Current Stress F0 Control F1 Control F0 Control F1 Density F0 Density F1 Control F0 Density F1 Density Variable Mean S.E. n Mean S.E. n Mean S.E. n Mean S.E. n TIMING OF EGGS 50% of eggs laid 48.303 0.235 5 55.622 0.168 7 37.577 0.118 10 49.028 0.118 10 100% of eggs laid 81.595 0.521 5 118.53 0.372 7 80.640 0.261 10 94.284 0.261 10

ADULT FEMALE DEATH Adult female death 102.412 1.148 5 132.821 1.124 7 95.393 1.103 10 113.863 1.103 10

TOTAL EGG NUMBER Total number of eggs per female 77.704 4.351 5 329.205 2.709 7 111.408 2.503 8 189.008 2.120 9

EGG SIZE mean egg size (mm) 1.100 0.049 4 1.080 0.037 7 1.113 0.035 8 1.087 0.033 9