The influence of host social system on host-

parasite evolutionary dynamics

Dissertation submitted for the degree of Doctor of Natural Sciences

Presented by Antoon Jacobus (Jaap) van Schaik

at the

Faculty of Sciences Department of Biology

Date of the oral examination: October 5, 2016 First supervisor: Martin Wikelski Second supervisor: Gerald Kerth

Konstanzer Online-Publikations-System (KOPS) URL: http://nbn-resolving.de/urn:nbn:de:bsz:352-0-370734

Towards an understanding of host-parasite evolutionary dynamics in a social world using bats and ectoparasites as a model system.

Supported by funding from:

Contents

Summary 1

Zusammenfassung 3

Chapter 1: General Introduction 8 Host-Parasite dynamics 12 Sociality and parasites 15 Simplifying the complexity: bat-ectoparasite model system 19 Research aims 24 Dissertation outline 26

Chapter 2: Host social organization and mating system shape parasite transmission opportunities in three European bat species 28 Abstract 30 Introduction 31 Methods 36 Results 40 Discussion 46 Supplementary materials 52

Chapter 3: The effect of host social system on parasite population genetic structure: comparative population genetics of two ectoparasitic mites and their bat hosts 56 Abstract 58 Introduction 59 Methods 64 Results 71 Discussion 82 Supplementary materials 87

Chapter 4: Host and parasite life history interplay to yield divergent population genetic structures in two ectoparasites living on the same bat species 92 Abstract 94 Introduction 95 Methods 100 Results 107 Discussion 113 Supplementary materials 118

Chapter 5: Synthesis and general discussion 122 Host sociality and parasite infection dynamics 123 Host sociality and parasite population genetic structure 125 A brief aside on the evolution of virulence and parasite induced restrictions to host sociality 128 Overall impact of host social system on host-parasite evolutionary dynamics 131 Future directions 132

List of publications and selected abstracts 135

Bibliography 141

Author contributions 160

Acknowledgements 161

Curriculum vitae 163

Summary

Parasites are ubiquitous in nature, and increased parasite pressure is one of the fundamental costs of sociality. In addition, sociality also affects host- parasite dynamics directly and indirectly at both ecological and evolutionary timescales. At the ecological level, host social contact shapes parasite infection intensity and transmission opportunities, while behavioural and social avoidance mechanisms allow hosts to reduce overall parasite pressure. On an evolutionary scale, the influence that host social system has on parasite genetic structure and the reciprocal selection pressure imposed by each species on the other can strongly influence the evolutionary outcome of host-parasite interactions. Although the role of host social system in shaping parasite infection dynamics is widely acknowledged, its additional role in shaping parasite genetic structure, and thereby influencing the evolutionary dynamics between the two interacting species, is comparatively understudied. In this dissertation, I use a multi-host multi-parasite comparative framework to explore the effects of host social system, and its interplay with parasite life history, on parasite infection dynamics and population genetic structure. Host-parasite dynamics are shaped by myriad factors including the abiotic and biotic environment, host and parasite life history and host social system. This complexity can be considerably reduced when studying permanent parasites, which do not leave their hosts, as the direct interaction between the parasite and the environment is limited. Furthermore, by investigating permanent parasites of closely related hosts with comparable life histories, it becomes possible to directly assess the effect and interaction between facets of host social system and specific parasite life history traits. European bats of the genus Myotis, and two of their common, permanent ectoparasites (wing-mites of the genus Spinturnix, flies of the genus Basilia), offer an ideal model to study this interaction. All host species share a similar life history, but differ in numerous aspects of their social system, including female colony size, male sociality, mating system and the degree of aggregation in winter. Likewise, while both permanent parasites of their bat hosts, the parasites differ in several key life history traits, most notably their reproductive rate and generation time. By using these species in a comparative framework, these differences in host social system and parasite life history can be exploited to attempt to elucidate the effect of individual social and life history traits. Specifically, I 1) characterize the effect that differences in host social system has on mite infection and transmission

1 dynamics, 2) compare the genetic structure of the mites of two bat species to explore the effects of host social system traits on parasite genetic structure, and 3) compare the genetic structure of a mite and fly species both infecting a single host species, to explore the interaction between parasite life history traits and host social system. Regarding parasite infection and transmission dynamics (chapter 2), I found substantial differences in mite infection intensity across three bat hosts, which correlated closely with the degree of sociality (aggregation size) of both host sexes. Additionally, the transmission rate of the different mite species was strongly correlated to the degree of contact between the sexes afforded by their differing mating systems. These differences at the ecological level also had readily visible effects on mite population genetic structure (chapter 3). In a comparison of population genetic structure between Spinturnix bechsteini and S. myoti, I found large differences in the level of genetic differentiation between, and degree of genetic turnover within, individual mite populations. These differences again closely correlated to those predicted based on host aggregation size and mating system. Finally, in a comparison of mite and fly population genetic structure on a single host (chapter 4), I showed that parasite reproductive rate and generation time interact with seasonal changes in host social organization to yield highly divergent genetic structures. In both investigations of parasite population genetic structure, the differences observed between parasite species were much larger than expected, and have significant implications for the evolutionary potential and the evolutionary trajectory of the host- parasite interaction. These differences are additionally remarkable given the narrow range of host social systems and parasite life histories that were investigated, emphasizing the effect that even subtle differences in facets of either host or parasite can have. Taken together, these results provide a compelling example of the influence of host social system in shaping host-parasite dynamics at both ecological and evolutionary timescales. In doing so, they contribute to our general understanding of the fundamental factors underlying the structure and function of animal sociality. Notably, understanding host-parasite eco- evolutionary dynamics additionally has direct conservation applications as it may aid in combatting emerging infectious diseases, as well as help understand the effects of the numerous ways in which anthropogenic change alters the social system and population dynamics of host animals.

2 Zusammenfassung

Die Allgegenwärtigkeit von Parasiten in jeder Form des sozialen Zusammenlebens stellt einen der grundlegendsten Nachteile sozialer Systeme dar. Enger Kontakt führt zwangsläufig auch zu einer größeren Parasitenbelastung und somit zu höheren Kosten für die Wirtsart. Zusätzlich beeinflusst soziales Verhalten die Ökologie und die Evolution der Interaktionsdynamik zwischen Wirt und Parasit sowohl direkt als auch indirekt. Auf ökologischer Ebene stellen Sozialkontakte eine Möglichkeit der Übertragung für nicht mobile Parasiten dar, der die Wirtsart mit Anpassung ihres Verhaltens sowie dem Vermeiden bestimmter Kontakte entgegenwirken kann. Im evolutionären Maßstab gesehen können sowohl der Einfluss des Sozialverhaltens der Wirtsart auf die genetische Struktur des Parasiten als auch der gegenseitige Selektionsdruck zwischen Wirt und Parasit einen enormen Einfluss auf das entwicklungsgeschichtliche Ergebnis von Wirt- Parasit Interaktion haben. Obwohl die Rolle unterschiedlicher Sozialsysteme von Wirtsorganismen als entscheidend für die Infektionsdynamik einer zugehörigen Parasitenart anerkannt sind, wurde der Einfluss verschiedener Sozialsysteme auf die genetische Beschaffenheit der entsprechenden Parasiten-Populationen und die damit einhergehende Einwirkung auf die evolutionäre Dynamik zwischen Wirt und Parasit jedoch bislang größtenteils vernachlässigt. In dieser Dissertation analysiere ich den Einfluss sozialer Wirtssysteme auf den Lebenszyklus, die Infektionsdynamik und die genetische Struktur der entsprechenden Parasitenarten mit Hilfe eines mehrere Wirts- sowie Parasitenarten umfassenden Vergleichsrahmen. Die Interaktionsdynamik zwischen Wirt und Parasit wird von unzähligen Faktoren beeinflusst, so zum Beispiel von abiotischen und biotischen Umweltfaktoren, vom artspezifischen Lebenszyklus von Wirt und Parasit, sowie vom Sozialsystem des Wirts. Parasitenarten, die dauerhaft auf ihrer Wirtsart verbleiben, bieten sich daher zum Studium solcher Systeme besonders an, denn der unmittelbare Kontakt zwischen Parasit und Umwelt ist stark eingeschränkt und somit gestaltet sich auch die Bewertung verschiedener Faktoren weniger kompliziert. Ein Vergleich von verschiedener stationärer Parasiten welche eng verwandten Wirtsarten mit ähnlichen Lebenszyklen befallen, erleichtert eine Analyse solch komplexer Systeme zusätzlich. Die möglichen Rückschlüsse auf den Einfluss verschiedenster Faktoren wie dem Sozialsystem des Wirts oder dem Lebenszyklus des Parasiten kann wichtige Einblicke in die Grundlagen des “Wettrüstens” zwischen Parasit und Wirt gewährt.

3 Die verschiedenen in Europa heimischen Fledermausarten der Gattung Myotis sowie zwei ihrer stationären Ektoparasiten (Milben der Gattung Spinturnix sowie Fledermausfliegen der Gattung Basilia) stellen ein ideales Modellsystem für das Studium solcher Wechselwirkungen dar. Die Fledermausarten dieser Gattung weisen einen ähnlichen Lebenszyklus auf, aber unterscheiden sich bezüglich Koloniedichte der Weibchen, Sozialverhalten der Männchen, Paarungssystem und Überwinterungs- strategie. Gleichzeitig unterscheiden sich die beiden im Fokus dieser Studie stehenden Parasitengattungen maßgeblich in verschiedenen Aspekten ihres Lebenszyklus und vor allem in der Reproduktionsrate sowie in der Generationsdauer. Somit erlaubt dieses System eine Gegenüberstellung der Sozialsysteme der Wirtsarten sowie der Auswirkungen unterschiedlicher Lebenszyklen der Parasitenarten. Insbesondere drei Aspekte fanden besondere Beachtung in der vorliegenden Arbeit: 1) der Einfluss der unterschiedlichen Sozialsysteme der verschiedenen Wirtsarten auf Infektions- und Übertragunsdynamik der parasitären Milben, 2) der Einfluss der Unterschiede im Sozialverhalten der zwei Wirtsarten auf die genetische Beschaffenheit ihrer Milbenpopulationen, 3) der direkter Vergleich zweier unterschiedlicher Parasitenarten auf dem selben Wirt und die Auswirkung ihrer verschiedenen Lebenszyklen auf ihre genetischen Populations- strukturen. In einen Vergleich der Belastung durch Parasiten sowie deren Verbreitungsdynamik (Kapitel 2) konnte ich erhebliche zwischenartliche Unterschiede in der Infektionsrate der drei Wirtsarten zeigen. Diese korrelierten erheblich mit Unterschieden im Sozialverhalten von Weibchen und Männchen. Besonders hatten das Maß an sozialen Kontakten zwischen den Geschlechtern sowie das Paarungsverhalten einen erheblichen Einfluss auf den Parasitenbefall der gesamten Population. Weiterhin zeigten sich, abgesehen von solchen Einflüssen auf ökologischer Ebene, abhängig vom Sozialverhalten der Wirtsart auch gravierende Unterschiede in der genetischen Struktur verschiedener Milbenpopulationen auf der gleichen Wirtsart (Kapitel 3). Bei einem Vergleich der genetischen Struktur der beiden Parasitenarten Spinturnix bechsteini und S. myoti zeigten sich große Unterschiede bei der genetischen Differenzierung zwischen unterschiedlichen Populationen sowie bei der Mutationsrate in einzelnen Populationen. Diese Unterschiede korrelieren wiederum eng mit den auf Grund von Koloniedichte und Paarungssystem der Wirtsart erwarteten Auswirkungen. Mit einem Vergleich der populationsgenetischen Struktur von Milben und Fledermausfliegen auf einer Wirtsart (Kapitel 4) konnte ich schlussendlich zeigen, dass Reproduktionsrate sowie Generationsdauer der Parasitenart stark mit jahreszeitlichen Veränderungen im Sozialverhalten der Wirtsart zusammenhängen, um möglichst hohe genetische Diversität zu

4 gewährleisten. Die Analyse beider populationsgenetischer Strukturen zeigte einen Unterschied zwischen den Arten, der weitaus höher war, als erwartet. Dies ist ein wichtiger Aspekt in Hinsicht auf Evolutionäres Potential sowie evolutionäre Zielsetzung von Wirt-Parasiten-Interaktionen. Gleichzeitig sind in Anbetracht der begrenzten Variabilität sowohl der untersuchten Wirts- Sozialsysteme als auch der Lebenszyklen der Parasitenarten die aufgedeckten Unterschiede bemerkenswert. Dementsprechend scheinen schon geringste Unterschiede im Wirts- oder Parasitensystem einflussreich zu sein. Folglich können die Ergebnisse dieser Dissertation zu einem besseren allgemeinen Verständnis fundamentaler Faktoren beitragen, welche Struktur und Funktion sozialer Systeme beeinflussen. Besonders im Zusammenhang mit der Bekämpfung neu auftretender Infektionskrankheiten kann das Verständnis von öko-evolutionärer Wirt-Parasit Dynamik von großem Nutzen sein und erläutern, wie anthropogene Veränderungen der Umwelt Sozialsysteme sowie Populationsdynamik der Wirtsarten beeinflussen.

5

6 7 Chapter 1

General Introduction

Parasites are an enigma. To some people they are an unpleasant but unavoidable fact of life. To others they are, like Victorian ankles, an embarrassing topic to be avoided in polite conversation. But to a small subset of human beings parasites are glorious creatures, no less a part of Darwin’s tangled bank than organisms more acceptable to anthropocentric idealization.

- Brooks & McLennan 1993

Parasitism is arguably the most common way of life (Price 1977). For hosts, the threat of parasite infection is ever-present and constitutes a strong selective force. Indeed, on an evolutionary scale, the reciprocal adaptation between a host and parasite is thought to be one of the primary generators of biodiversity (Hamilton 1982, Dybdahl and Storfer 2003). Although the consensus has progressed considerably from the avirulence hypothesis, which stated that parasites should always become less virulent as they adapt and coevolve with a host (Smith 1904), towards a recognition that virulence is often maintained at some non-zero level as parasite fitness is maximized (Anderson and May 1982, Ewald 1983, Lenski and May 1994, Alizon et al. 2009, Alizon and Michalakis 2015), it remains remarkable that the vast majority of host-parasite interactions go largely unnoticed as they do not cause obvious costs or mass mortality. This observation becomes even more

8 striking when considering that parasite life-cycles are often much faster, and population sizes much larger, than that of their hosts, thereby theoretically giving them the advantage in an evolutionary arms race. Understanding the factors that influence host-parasite evolutionary dynamics may help explain this observation. Increased risk of parasite exposure constitutes one of the initial and most fundamental costs of sociality (Møller et al. 1993, Altizer et al. 2003, Kappeler et al. 2015). Naturally, sociality also provides many benefits (e.g. increased foraging efficiency, reduced thermoregulatory costs in dense aggregations; Krause and Ruxton 2002), which may partially compensate for the increased cost of parasite infection. Notably, in addition to these overall benefits, sociality also affords a wealth of behavioral and social adaptations, which can be used to directly reduce parasite pressure (the behavioral immune system, cf. Schaller et al. 2015). At the population level, host sociality will also affect parasite dynamics by affecting transmission among host social units (i.e. metapopulation dynamics). Combined, these effects, in combination with host and parasite life history, also shape a parasite’s population genetic structure (Nadler 1995) and thereby its evolutionary potential (Gandon and Michalakis 2002). Finally, host sociality may also provide indirect benefits with regards to the evolutionary trajectory of the interaction by limiting parasite local adaptation (Gandon et al. 2008), or selecting for lower virulence (May and Anderson 1990). In sum, host sociality has a large effect on host-parasite dynamics at both the ecological and evolutionary level. Despite widespread recognition and investigation of the direct effects of sociality on parasite exposure risk and infection dynamics (e.g. Møller et al. 1993, Clayton and Moore 1997, Nunn and Altizer 2006), empirical investigations into the role of host social system in shaping parasite population genetic structure and especially the resulting evolutionary dynamics are comparatively rare (Poulin 2011). In this dissertation, I use a comparative multi-host multi-parasite framework to explore how host social

9 system interacts with host and parasite life history to shape parasite population genetic structure.

Terminology Before getting started, it is important to define several terms as used in this dissertation. For example, what precisely constitutes a parasite has been extensively disputed (e.g. Price 1977, Windsor 1998, Clayton et al. 2015). While some organisms are obviously parasitic, others (e.g. phytophagous insect, brood parasitic birds, blood-sucking insects) are debatable. In other cases, terms have been used synonymously by some (social organization / social structure), while denoting different characteristics by others (compare: Whitehead and Dufault 1999, Kappeler and van Schaik 2002). A complete list of terms as they are used in this dissertation is provided in the glossary below.

Glossary

Defense any strategy employed by a host to combat parasite infection. There are three primary types of defense: physical barriers (e.g. skin, mucus, gut lining), immune defense (e.g. inflammation, adaptive immune response) and behavioral defense (e.g. grooming, use of latrines). These defense types can be employed in three main defensive strategies: Avoidance defense strategy that reduces of the risk of exposure to a parasite 1 Resistance defense strategy that reduces the parasite burden of an infected host 1 Tolerance defense strategy that reduces the negative impact of infection on host fitness. Unlike resistance, tolerance does not directly affect pathogen burden 1 Evolutionary potential the ability of either host or parasite to incorporate genotypes able to overcome the weaponry put forward by the opposing species 2 Local adaptation the increased fitness of a population in its local habitat relative to its fitness in a remote habitat. 2 Within the context of host-parasite interactions: the increased fitness of a local population of a host or parasite with its sympatric parasite or host population relative to its fitness with host or parasite populations elsewhere

10 Infection the successful habitation of a host by a parasite Intensity the number of individuals of a particular parasite species on a single infected host 3 Prevalence the number of hosts infected with one or more individuals of a particular parasite species (or taxonomic group) divided by the number of hosts examined for that parasite species 3 Virulence the capacity of a parasite to inflict damage and reduction in host fitness 4 Metapopulation spatial substructuring of a population into local breeding populations (social systems) inhabiting discrete habitat patches where migration among populations to at least some other patches is possible. Notably, local dynamics within patches generally occurs at a much faster pace than overall metapopulation dynamics (e.g. local extinction / recolonization) 5 Parasite an organism living in or on another organism: the host – feeding on it, showing some degree of structural adaptation to it, and causing it some harm 6 While this definition is rather narrow, the themes and general principles discussed here are also generally applicable to a wide range of parasite-like species, including parasitoids (insects with free-living adult stages that lay eggs in hosts which ultimately sterilize or kill the host) and pathogens (microorganisms that cause disease in the host). Permanent a parasite that passes all stages of its life cycle on the body of the host 7 Mobile / non-mobile parasites that are able to disperse independently are considered to be mobile parasites, whereas non-mobile parasites primary depend on host movement for transmission 4 Horizontal transmission the transmission of parasites between hosts of the same population and generation (i.e. not to own offspring: vertical transmission)4. In cases where hosts form social units with limited interaction between conspecifics outside of these groups, horizontal transmission may be restricted to include only those events in which parasites are transmitted between social units. Social system (synonymous to social unit) the set of conspecific animals that interact regularly and more so with each other than with members of other such societies. Here I will use social system to refer to the general concept, and social unit or colony to refer to individual societies. Can be described using three characteristics: social organization, social structure and mating system 8 Social Organization the size, sexual composition and spatiotemporal cohesion of a society 8 Social Structure the pattern of social interactions and the resulting relationships among the members of a society 8 Mating system composed of a social and a genetic component. The social mating system describes the subset of social interactions between mating couples, whereas the genetic mating system describes the reproductive consequences of mating interactions 8

11 Sensu 1 (Medzhitov et al. 2012) 2 (Gandon and Michalakis 2002) 3 (Bush et al. 1997) 4 (Schmid-Hempel 2011) 5 (Hanski and Gilpin 1997) 6 (Poulin 2011) 7 (Clayton and Moore 1997) 8 (Kappeler and van Schaik 2002)

Host-Parasite dynamics

The epidemiological triangle, classically applied in veterinary medicine, states that three main components determine the persistence of an infectious species or agent within a host population: host, parasite/pathogen and environment (McNew 1960, Wobeser 2007). This framework can subsequently be extended to include the (co)evolutionary dynamics between the interacting species (Vander Wal et al. 2014a). Despite this apparent simplicity, myriad factors influence host-parasite infection and evolutionary dynamics. A summary of these effects is given in Box 1. Within this framework, the interaction between host and parasite can be subdivided into three levels: First and most obviously, the immediate infection dynamics at the level of the individual or populations. Second, the evolutionary potential of both species as shaped by their population genetic structure. Third, the ultimate evolution of adaptations (i.e. specialization), notably including the directionality (i.e. evolution of virulence) of the resulting co-evolutionary trajectory. Finally, in cases where there is spatiotemporal variation in these three levels across discrete host-parasite populations, a fourth emergent property will arise: behavioral and/or genetic differentiation across populations (i.e. geographic mosaic of adaptation), which may impose costs to dispersal and potentially lead to speciation. Although all properties of the host, parasite and environment will influence these dynamics, I will restrict the following discussion to the aspects directly influencing, and influenced by, host social system.

12 Box 1: Host-parasite interaction and evolutionary dynamics

 At an individual level, 1 host-parasite dynamics, Environment like all species inter- actions, are shaped by three main factors: the two interacting species and 2 4 2 3 3 their environment. Host Defense/Infection Parasite

The abiotic environment, Individual especially climate and seasonality, plays a major role in shaping the Selection pressure (temporal changes in) 6 resource and habitat Pop genetic Pop genetic availability for species. structure structure 5 5 Likewise, the biotic 7 environment adds a > multitude of other species Adaptation = Adaptation < inter-actions that must be dealt with concurrently, thereby often introducing dynamics evolutionary scale Local 8 Local adaptation trade-offs and limitations to adaptation as each individual interaction must Geographic mosaic be seen within the context 9 of all other interactions in Broad scale Broad Diversity / Speciation the local environment. ‚ Many characteristics of both host and parasite influence whether a parasite is able to infect a given host. Some characteristics are largely static, such as genotype, general life history and morphology, whereas others are more variable including health, behavior, and notably the social interactions of the host. ƒ,„ Based on (the current state of) all of the aforementioned characteristics, hosts can mount three basic types of defense: physical, immune and behavioral, which can be employed in three primary defense strategies: avoidance, resistance or tolerance. Correspondingly, a parasite’s ability to infect a host, and subsequently its reproductive rate, transmission potential and virulence, will depend on whether its physical, immune and behavioral traits can overcome the defense mounted by the host. Importantly, by shaping local population dynamics and transmission potential, the life histories of both species as well as the social system of the host also shape the population genetic structure (effective population size, genetic drift, gene flow) of the parasite. Conversely, parasite life history and infection dynamics may also play a role in shaping host genetic structure in the event that host mortality and reproduction are substantially affected, but in most cases its effect will be negligible (dashed line).

13 † Besides shaping population genetic structure, parasite infection dynamics will also determine the selection pressure exerted on both species by the opposing party. This will often be much stronger for the parasites as the fitness of a parasite is entirely dependent on successful infection, whereas host fitness is often influenced to a lesser extent. ‡,ˆ The evolutionary potential of a local population is determined by the number of new genotypes entering the population and is thus primary determined by their effective population size and gene flow. Subsequently, evolutionary potential, in combination with the strength of selection pressure, will determine the degree to which host and parasite populations adapt to the local population of the other species. Finally, depending on the relative selection pressure and evolutionary potential of the two species, whichever species is adapting at a faster rate will be able to locally adapt to the local population of the other. Vitally, the local adaptation of either host or parasite will not necessarily result in increased costs for the other species, as increased tolerance (host) and decreased virulence (parasite) can be adaptive under certain conditions. ‰ The local adaptation of populations at a microgeographic scale will lead to hetero- geneity at a macrogeographic scale. Such a geographic mosaic of coadapted populations may decrease the fitness of individuals migrating between populations, thereby potentially leading to increased differentiation and ultimately speciation. In this context it is important to note that a significant proportion of differentiation at a macrogeographic scale is not the result of adaptation, as isolation by distance and genetic drift will also lead to increased spatial substructuring and heterogeneity.

References and further reading:

 Abiotic: (Altizer et al. 2006, Real and Biek 2007, Lafferty 2009, Wolinska and King 2009, Nunn et al. 2014)  Biotic: (Rigaud et al. 2010, Alizon et al. 2013, Hafer and Milinski 2016, van Velzen et al. 2016) ‚ (Hart 1990, Côté and Poulin 1995, Loehle 1995, Poulin et al. 2011, Lion and Gandon 2015, Boulinier et al. 2016) ƒ (Parker et al. 2011, Cressler et al. 2015, Sears et al. 2015) „ (Miller et al. 2005, Alizon et al. 2009, Raberg et al. 2009, Medzhitov et al. 2012, Alizon and Michalakis 2015) (Nadler 1995, Sorci et al. 1997, Criscione et al. 2005, Barrett et al. 2008, Mazé- Guilmo et al. 2016) † (Gandon et al. 1998, Barrett et al. 2008, Gandon and Nuismer 2009b) ‡,ˆ (Gandon and Michalakis 2002, Greischar and Koskella 2007, Hoeksema and Forde 2008, Nuismer and Gandon 2008, Nuismer et al. 2010, Yeaman 2015) ‰ (Thompson 1994, Criscione 2008, Hoberg and Brooks 2008, Hoberg and Brooks 2015, Penczykowski et al. 2016)

14 Sociality and parasites

The following section provides an overview of how host social system, and interactions between social system and environment as well as parasite life history, influence host-parasite dynamics at each of the three levels of interaction (i.e. immediate infection dynamics of the individual or local population, genetic structure and evolutionary potential, directionality of the evolutionary trajectory).

Sociality and infection dynamics By far the most research has gone into how host social system affects parasite infection and transmission dynamics. These effects can be roughly subdivided into three categories. First, sociality provides several opportunities for social behaviors directly geared towards parasite defense (Altizer et al. 2003). Some, such as social avoidance, mate choice and mate fidelity, act as avoidance strategies that reduce the risk of exposure to parasites (Loehle 1995). Others, such as allogrooming or caring for sick conspecifics, function by reducing the severity of infection or parasite-induced mortality (Hart 1990). Second, by shaping host spatiotemporal organization and contact rates, social system also affects the distribution and transmission dynamics of their parasites (Ezenwa 2004). The formation of discrete social units (i.e. metapopulation dynamics; Hanski and Gilpin 1997) reduces overall contact among social units and therefore also restricts parasite horizontal transmission opportunities in proportion to the inter-social unit contact rate (Nunn and Altizer 2006). Within social units, however, transmission is facilitated and will increase as a function of intra-social unit contact rates (Nunn et al. 2015). Indeed, the size and density of social aggregations have been shown to correlate positively with parasite infection intensity across a wide range of systems (Côté and Poulin 1995, Patterson and Ruckstuhl 2013). Similarly, the structure and strength of associations within the social network have been shown to shape the transmission dynamics of contact

15 transmitted parasites in a wide variety of species (Godfrey et al. 2009, Zohdy et al. 2012, Reynolds et al. 2015, Rimbach et al. 2015, Tung et al. 2015, Springer et al. 2016, VanderWaal et al. 2016). Notably, these relationships often do not hold for mobile parasites or for non-mobile parasites that can persist off of the host or make use of vectors. In fact, the per capita infection intensity of mobile parasites may often be lower in aggregations (i.e. dilution effect; Rubenstein and Hohmann 1989, Krebs et al. 2014, Lehtonen and Jaatinen 2016). Third, a host’s social system influences, and is influenced by, many other characteristics relevant to host-parasite dynamics. For example, host social system is strongly influenced by climate and seasonality, often leading to large variations in social system, and thus parasite transmission opportunities, throughout the year (Altizer et al. 2006). How these changes affect parasite dynamics will additionally depend on the life cycle and persistence ability of the parasite in the “sub-optimal” seasons (Perez- Rodriguez et al. 2015). Social system also influences many aspects of host health and susceptibility (i.e. reduction in immunological defense) to parasite infection. Some of these influences are well established, such as the effect of dominance hierarchy on health and hormone levels (MacIntosh et al. 2012), whereas others, such as the effects of social isolation in a social species, are only recently being recognized (Hawkley and Capitanio 2015).

Sociality and parasite population genetic structure The wide array of effects of host social system on parasite infection dynamics is similarly reflected in their influence on parasite population genetic structure (Nadler 1995). Empirical studies of parasite population genetic structure in relation to host sociality are comparatively rare, but have become far more common in recent years (see Table S1 of Mazé-Guilmo et al. 2016). Critically, almost none investigate the temporal turnover / stability of local parasite populations, limiting their ability to quantify genetic drift and gene flow of local parasite populations. Nevertheless, several general conclusions can be drawn.

16 As previously described in relation to infection intensity, increases in the size and density of host social aggregations will generally lead to a larger local parasite population, and thus often leads to an increased effective population size (Criscione and Blouin 2005). A large effective population size reduces the influence of genetic drift, and generally also results in an increased amount of standing genetic diversity in the local gene pool. Likewise, as previously observed above with regard to parasite transmission dynamics, host social system will strongly influence parasite gene flow (Nadler 1995). Specifically, inter-social unit contact rates and dispersal will shape parasite gene flow across the metapopulation (Mazé-Guilmo et al. 2016), whilst parasite gene flow within social units will be unrestricted or follow patterns of intra-unit contact (Tung et al. 2015). In this context it is important to note that these two facets are not necessarily linked, and thus high levels of gene flow do not imply low levels of genetic drift and vice versa (e.g. a local parasite population may have a very large effective population size, but be almost entirely isolated from other populations). This is crucial as the evolutionary potential of a local population is primarily a function of its standing genetic diversity, gene flow and genetic drift (and to a lesser extent mutation rate). Specifically, high levels of genetic diversity and gene flow and relatively lower levels of genetic drift are suggested to result in maximal evolutionary potential (Gandon and Michalakis 2002). Finally, as the ability to locally adapt to the respective population of the other species is a function of evolutionary potential and selection pressure (Gandon and Nuismer 2009b), the influence of host social system on the evolutionary potential of its parasites plays a vital role in shaping host-parasite evolutionary dynamics.

Sociality and virulence evolution Perhaps the most poorly understood and underappreciated effect of host sociality on host-parasite dynamics is its effect on the evolutionary trajectory of virulence evolution (i.e. what happens if a parasite is able to locally adapt). While perhaps counterintuitive, local adaptation of the parasite may ultimately lead to lower overall costs for the host as optimal fitness of the

17 parasite is linked to both its virulence and its transmission (the transmission- virulence trade-off hypothesis; Alizon et al. 2009, Alizon and Michalakis 2015). Theoretical models and experiments involving lower order host- parasite interactions (e.g. bacteria-phage) suggest that virulence is principally influenced by two traits: host defense strategy and parasite transmission dynamics. Specifically, host resistance (almost exclusively determined by immune defense) is expected to lead to higher parasite virulence, while host avoidance and tolerance defense strategies (including social and behavioral adaptations) lead to the evolution of lower parasite virulence. Moreover, parasite virulence is expected to be higher when parasite transmission is primarily horizontal and lower when it is predominantly vertical (Boots et al. 2004, Best et al. 2011), as horizontal transmission allows for parasites to disperse more readily from terminal host individuals. Interestingly, in this reference frame, the metapopulation structure often created by host sociality would be more akin to vertical transmission as the parasite is strongly limited from dispersing horizontally outside of its own social unit (Boots and Sasaki 1999, Bonds et al. 2005). Although empirical studies exploring the evolution of parasite virulence in social host species are exceedingly rare, and it is also beyond the scope of the work presented in this dissertation, it is nevertheless important to keep in mind.

Synthesis and general notes In summary, sociality not only fundamentally increases the risk of exposure to parasites, but also can profoundly affect host-parasite infection and evolutionary dynamics at all three levels. In the context of the two levels investigated here, several outstanding questions remain. Despite the wealth of knowledge and general understanding of the effects of individual facets of host and parasite life history and host social system, how these components interact to shape host-parasite infection dynamics in individual systems remains complicated to predict. Moreover, accurately predicting how these components interact to shape parasite gene flow and genetic drift, and thus the evolutionary dynamics of the system, is

18 currently unfeasible. To make matters more complex, the sections above have focused exclusively on effects directly pertaining to host sociality, but as outlined in Box 1, many other parameters (e.g. the interaction between the parasite and the environment) will also influence host-parasite dynamics. To explore these questions requires a system where as many confounding influences as possible can be eliminated, but with variation in host social system, thus allowing for the characterization of the effects of individual parameter changes in host sociality on both host-parasite infection as well as evolutionary dynamics. Finally, by combining such studies from across a range of host systems, it may become possible to develop more comprehensive generalizations regarding the effects of host social system on host-parasite interactions.

Simplifying the complexity: bat-ectoparasite model system

In this dissertation I characterize parasite infection dynamics and population genetic structure in a comparative multi-host multi-parasite framework using four European bat species all belonging to the genus Myotis (Box 2) and their ectoparasites (Box 3) as a model system. This approach and model system satisfies the requirements necessary to be an informative system for exploring the effects of host social system described above, and has several additional advantages. The multi-host multi-parasite comparative framework is comprised of two interrelated components. In the first, I aim to isolate the influence of host social system by comparing the infection dynamics and population genetic structure of a single parasite type across several hosts with very similar life histories, but differing social systems. As both host and parasite life history are similar across the investigated species pairs, I posit that any differences in parasite infection dynamics or genetic structure should be primarily the product of host social system. In the second, I aim to isolate the effects of parasite life history within the context of a single host social system by

19 comparing the population genetic structure of two non-mobile parasites living on the same host populations. As they infect the same host species, they are afforded comparable direct transmission opportunities via host social interactions. Therefore, any difference in population genetic structure between the species should be the result of how different aspects of parasite life history interplay with characteristics of host social system.

Box 2: The four Myotis species investigated

Myotis bechsteinii Myotis nattereri Myotis daubentonii Myotis myotis ©René Janssen ©René Janssen ©René Janssen ©René Janssen

In this study, I examined four European bat species: Bechstein’s bat (Myotis bechsteinii), Natterer’s bat (Myotis nattereri), Daubenton’s bat (Myotis daubentonii) and the greater mouse-eared bat (Myotis myotis). All species have a comparable life history composed of a three phase annual cycle (summer maternity colonies, autumn mating and winter hibernation). They do, however, differ in several aspects of their social system as summarized in the table below.

The primary host species investigated in this dissertation, Myotis bechsteinii, has also been the most extensively studied in terms of behavior and social system (reviewed in Kerth and van Schaik 2012). In this species, contact between conspecifics outside of maternity colonies is severely limited, thus restricting opportunities for parasite horizontal transmission. Additionally, they display several (social) behaviors that further reduce parasite pressure such as (allo-)grooming (Kerth et al. 2003a) and frequent roost switching including the potential avoidance of parasitized roosts (Reckardt and Kerth 2007).

Contact among conspecifics increases in a gradient across the other three bat species (M. nattereri < M. daubentonii < M. myotis; see table above). Furthermore, as in M. bechsteinii, grooming is common in all species (Swift 1997, Giorgi et al. 2001), and roost switching is commonly observed in M. nattereri (Swift 1997) and M. daubentonii (when roosting in tree cavities; Lučan 2006), but absent in M. myotis.

20 Bechstein's Natterer's Daubenton's Greater mouse- bat bat bat eared bat M. bechsteinii M. nattereri M. daubentonii M. myotis Ref Social organization Summer Colony size ♀: small (10- ♀: small (10- ♀: small-medium (10- ♀: large (100-2000) 1 50) 100), rarely 200), sometimes including some ♂ including ♂ ♂: solitary ♂: solitary ♂: generally ♂: solitary or bachelor solitary groups (1-50)

Spatio-temporal ♀: fission- ♀: fission-fusion ♀,♂: fission-fusion and ♀: static (cave/ 1, 2 cohesion fusion and and roost roost switching building) roost switching switching (tree (tree cavity) or static (tree cavity) cavity) (cave/building) ♂: roost switching (tree cavity) or static (cave/building) Winter Aggregation ♀,♂: solitary, ♀,♂: solitary or ♀,♂: solitary or small ♀,♂: solitary up to 1, 3 size occasional small clusters clusters large clusters small clusters (1-20) (1-20) (1-1000) (1-10) Social structure Summer ♀: strong ♀: strong ♀: strong philopatry; ♀: philopatry; some 4, 5, philopatry; philopatry; rare inter-sex spatial inter-colony interaction 6, 7 inter-colony inter-colony segregation outside of maternity aggression interaction period Mating system Autumn Promiscuous; Promiscuous; Promiscuous; swarming Promiscuous; 1, 8, swarming swarming and local mating swarming and 9 temporary harems

References: 1: Krapp 2004, 2: Kerth 2008, 3: Wojechowski et al. 2007, 4: Kerth and van Schaik 2012, 5: Rivers et al. 2005 , 6: Angell et al. 2013 , 7: Castella et al. 2001 , 8: Encarnação and Reiners 2002, 9: Zahn and Dippel 1997

Sampling method

Several sampling approaches were used in this dissertation. For comparisons of parasite population genetic structure, parasites were collected from female maternity colonies in summer. In M. bechsteinii, female maternity colonies were “caught” from their roosting sites: an established network of hundreds of bat boxes across approximately twenty forest patches near Würzburg, Germany. Additionally, at sites where the colonies are monitored on a daily basis, freshly deposited puparia of the bat flies could be collected from the walls of the bat boxes. In M. myotis, maternity colonies in churches across western Switzerland were caught as they emerged in the evening. For comparisons of parasite transmission dynamics, bats were caught at three large swarming sites, two in northern Bavaria and one in North Rhine – Westphalia, in autumn. Naturally, such a sampling effort is only possible with the help of many collaborators; please refer to the acknowledgements of the respective chapters as well as the general acknowledgements for a complete overview.

21 The investigated bat species provide an ideal model system for investigating the influence of host social system on parasite dynamics, which compares favorably to other mammalian systems. They have a very slow life history, living upwards of 20 years, and giving birth to only a single young per year. Thus, they have a very comparable life history to that of many other larger mammal species such as ungulates and primates. Unlike these species, however, the small body size and dense colony formation of bats allows for comparatively rapid and comprehensive capture of entire host social units. Furthermore, bats display a wide variety of social systems, with large differences in group size and mating system (Box 2), thereby allowing for comparative studies. They are also commonly infected by several ectoparasite species (see below). Moreover, bats have been shown or implicated to be reservoirs or vectors of many pathogens and emerging infectious diseases, providing added direct relevance to understanding how host sociality affects parasite infection dynamics in this system. Like their bat hosts, wing mites (Spinturnix) and bat flies (Basilia), two highly specialized bat ectoparasite taxa, are well suited as model species. Both are obligate parasites, and thus the influence of environmental factors is greatly minimized as their environment is essentially reduced to their host and its immediate environment. Both are comparatively large (1-5 mm) ectoparasites, which greatly facilitates sampling. They are broadly similar in terms of life history but differ in several key aspects (Box 3).

22 Box 3: Wing mites (Spinturnix) and bat flies (Basilia)

Basilia nana Spinturnix bechsteinii © GK & JvS adapted from Weiden 1954

Wing-mites and bat flies are both highly specialized obligate ectoparasites that infect bats. Both are hematophagous, and constitute a low, but non-zero costs for their hosts (Giorgi et al. 2001, Dick and Patterson 2006). The population dynamics of both species closely follow the seasonal cycle of their host, generally being lowest in early spring, growing throughout the summer maternity phase and subsequently reducing again during the autumn mating season and winter hibernation. Similarly, while both species are transmitted rapidly within host social units, both species cannot disperse independently (but see flies below), thereby limiting inter-social unit transmission.

In this study, I investigate four closely related mite species of the genus Spinturnix (S. bechsteini, S. myoti, S. andregavinus and S. nattereri). These mites are broadly host-specific, and live exclusively on the tail and wing membranes of their host. They are oviviparous, with female mites giving birth to single adult-like protonymphs, which rapidly develop into adults (Rudnick 1960). They never leave the host and cannot survive off of the host for more than a few hours (Giorgi et al. 2004).

The bat fly investigated here, Basilia nana (Diptera: Nycteribiidae), is a wingless ectoparasite that inhabits the pelage of bats (Dick & Patterson 2006, 2007). It cannot disperse independently from its primary host, and female flies only briefly leave their host approximately every 5-10 days to deposit a single terminal (3rd- instar) larva on the wall of the roost (Reckardt & Kerth 2006). These larvae immediately develop into a puparium, and can emerge as fully developed imagoes in ca. 3 weeks (Dick & Patterson 2007). Developed imagoes wait inside the puparia and only emerge in the presence of a potential host (Reckardt & Kerth 2006). Therefore, while not able to freely disperse, they may be transmitted between colonies without direct host contact.

23 Research aims

In this dissertation I aim to contribute towards understanding the effects of host social system on host-parasite infection and evolutionary dynamics. The eventual goal being to understand how individual facets of host sociality affect, and are restricted by, the interaction between a host and its parasites. In this context, I address three main questions:

1) How do differences in bat social organization and mating system affect mite infection and transmission dynamics?

2) How do differences in bat social system affect the population genetic structure and evolutionary potential of their local mite populations?

3) How do differences in parasite life history traits interact with the same host social system to affect parasite (mite and fly) population genetic structure and evolutionary potential?

Predictions Based on our current understanding of the study species, and host-parasite interactions in general, several predictions regarding the effect that specific aspects of host social system will have in this system can be made:

Colony / aggregation size: increased size and density of host aggregations will increase parasite infection intensity and transmission between colony members, while solitary individuals will show lower levels of parasite prevalence and intensity due to a reduced exposure rate (Arneberg et al. 1998, Krasnov et al. 2002, Rifkin et al. 2012, Patterson and Ruckstuhl 2013).

Spatiotemporal cohesion: by reducing aggregation size, fission-fusion dynamics may reduce parasite infection intensity. However, as the subunits frequently interact, parasite transmission and prevalence are unlikely to be

24 affected. Roost switching will reduce the infection intensity of non-permanent parasites that spend part of their life cycle in the roost but are unable to disperse independently (e.g. bat flies) as hosts may not reuse parasitized roosts within the infective period of the parasite (Reckardt and Kerth 2006).

Colony structure: female philopatry and active exclusion of non-colony members will reduce/eliminate parasite transmission via dispersing or prospecting host individuals (Kerth and van Schaik 2012, Boulinier et al. 2016).

Mating system: promiscuity will increase parasite transmission as multiple sexual encounters increases the number of encounters with potentially parasitized conspecifics. Additionally, through successive contact with females from different maternity colonies, males may act as vectors for mite transmission between colonies. Mating systems that result in longer contact rates (e.g. temporary harems) are expected to further increase parasite transmission (Cross et al. 2009).

25 Dissertation outline

To draw informative conclusions regarding the evolutionary consequences of variation in individual facets of host social system and parasite life history, we must first understand how these facets interact to shape current infection dynamics. Therefore, in chapter 2, I investigate the effect of host social organization and mating system on mite infection and transmission dynamics across three bat species (Myotis nattereri, Myotis daubentonii and Myotis myotis) during the autumn swarming season.

In chapter 3 I quantify the effects of these differences in parasite infection and transmission dynamics by comparing the resulting population genetic structure and evolutionary potential in two mite-bat pairs (Myotis bechsteinii / Spinturnix bechsteini and Myotis myotis / Spinturnix myoti).

Next, in chapter 4 I compare the population genetic structure of two parasite species (Spinturnix bechsteinii, Basilia nana) both infecting M. bechsteinii. As both parasites concurrently infect the same host colonies, I posit that any difference in population genetic structure between the species should be the result of how different parasite life history traits interact with the same host social system.

Finally, in chapter 5 I synthesize the findings from the previous chapters and revisit the aims and research questions outlined above. Specifically, I summarize the observed interaction between host social system and parasite life history in shaping parasite infection and genetic structure, and discuss the broader consequences and possible adaptive use of host social system in the context of host-parasite (co)evolutionary dynamics.

26

27 Chapter 2

Host social organization and mating system shape parasite transmission opportunities in three European bat species

J. van Schaik, G. Kerth

Esperhöhle, Fränkische Schweiz, Germany

28

29 Abstract

For non-mobile parasites living on social hosts, infection dynamics are strongly influenced by host life history and social system. We explore the impact of host social systems on parasite population dynamics by comparing the infection intensity and transmission opportunities of three mite species of the genus Spinturnix across their three European bat hosts (Myotis daubentonii, Myotis myotis, Myotis nattereri) during the bats’ autumn mating season. Mites mainly reproduce in host maternity colonies in summer, but as these colonies are closed, opportunities for inter-colony transmission are limited to host interactions during the autumn mating season. The three investigated hosts differ considerably in their social system, most notably in maternity colony size, mating system and degree of male summer aggregation. We observed marked differences in parasite infection during the autumn mating period between the species, closely mirroring the predictions made based on the social systems of the hosts. Increased host aggregation sizes in summer yielded higher overall parasite prevalence and intensity, both in male and female hosts. Moreover, parasite levels in male hosts differentially increased throughout the autumn mating season in concordance with the degree of contact with female hosts afforded by the different mating systems of the hosts. Critically, the observed host-specific differences have important consequences for parasite population structure, and will thus affect the coevolutionary dynamics between the interacting species. Therefore, in order to accurately characterize host-parasite dynamics in hosts with complex social systems, a holistic approach that investigates parasite infection and transmission across all periods is warranted.

30 Introduction

Host-parasites interactions are omnipresent in biological communities (Schmid-Hempel 2011). The epidemiology and population dynamics of parasites are influenced by many abiotic and biotic factors, especially the interaction of host and parasite life histories (Nadler 1995, Barrett et al. 2008). For example, in non-mobile permanent parasites that spend their whole life cycle on their hosts, infection intensity and diversity increases with increasing host group size (Côté and Poulin 1995, Patterson and Ruckstuhl 2013) and host density (Krasnov et al. 2002). Moreover, in parasites that are unable to disperse independently of their host, horizontal transmission is dependent on host spatiotemporal dynamics (Nunn and Altizer 2006). As a result, in many permanent parasites, infections are biased towards one host sex and show strong seasonal fluctuations as a function of the dynamics of host social interactions (Krasnov et al. 2005, Altizer et al. 2006). The degree of parasite dispersal between host social groups will have strong consequences for the evolutionary dynamics between host and parasite. For example, genetic analyses of parasites on several bird species showed that parasite populations are largely undifferentiated among breeding grounds as a result of inter-colony contact and parasite transmission at communal wintering grounds or extensive prospecting by juvenile host individuals (Gomez-Diaz et al. 2012, Levin and Parker 2013). Parasite transmission between host populations are especially relevant from an evolutionary perspective, as the potential for parasite local adaptation is largely determined by the relative rate of gene-flow in host and parasite (Gandon and Michalakis 2002), and the effective population size of both (Gandon and Nuismer 2009a). Thus, when assessing host-parasite coevolutionary dynamics, it is essential to not only characterize the phases of the host’s annual cycle in which parasite infection levels are highest, but also parasite phenology and transmission opportunities throughout the rest of the annual cycle. The latter, however, has rarely been done so far.

31 European temperate zone bats offer an interesting system for investigating the effects of host social system and seasonality on the prevalence, intensity and transmission of permanent parasites. During summer, female bats typically form large, dense maternity colonies to raise their offspring (Kerth 2008). In addition to the large aggregation size, both females and juveniles show reduced immunocompentence and grooming compared to other times of the year (Christe et al. 2000). These conditions result in high levels of parasite infection intensity and parasite population growth in many bat colonies (Lučan 2006, Lourenço and Palmeirim 2008). In contrast to female bats, males are often solitary throughout the summer, although they may join female colonies or form male bachelor groups in some species (Safi and Kerth 2007). As a result, unlike most other mammalian systems (Zuk and McKean 1996, Schalk and Forbes 1997), females of most temperate zone bats have higher levels of parasite infection than males (e.g. Reckardt and Kerth 2009). Contact between the philopatric, closed female maternity colonies, and between females and males, is very rare during summer (Burland and Wilmer 2001, Kerth and van Schaik 2012). This results in limited horizontal transmission (used here as parasite exchange between different host colonies) opportunities for contact- transmitted parasites during this time (Bruyndonckx et al. 2009b, van Schaik et al. 2015a). In late summer and autumn, female maternity colonies disband and bats meet to mate, thereby also allowing for parasite transmission. Mating in temperate zone bat species is promiscuous and predominantly occurs either in temporary harems (Zahn and Dippel 1997), locally with males in the summer home range of the females (Senior et al. 2005), or during a behavior known as swarming, in which bats show intense flight activity at the entrance to underground sites used for hibernation in winter (Fenton 1969). During these encounters, parasites may be directly transmitted between females (in harems), or by males acting as a vector for parasite transmission between females from different colonies (van Schaik et al. 2014). In winter, bats hibernate either solitarily or in clusters (Dietz et al. 2007). In the latter case,

32 additional parasite transmission may take place during this time. However, the reduced temperatures and torpor of the hosts correspondingly also reduces the metabolism and activity of ectothermic parasites (Christe et al. 2007). Taken together, although parasite populations are largest during summer, effective transmission and subsequent survival throughout autumn and possibly winter is key to parasite persistence and dispersal within the host meta-population. However, comparative studies of parasite population dynamics and transmission on bats with different social organization and mating systems in autumn are lacking. In this context, we explore the transmission and temporal infection dynamics of a common genus of ectoparasite (wing-mites of the genus Spinturnix) on three common European bat species at swarming sites during the autumn mating period. The three bat species: Daubenton’s bat (Myotis daubentonii), the greater mouse-eared bat (Myotis myotis) and Natterer’s bat (Myotis nattereri) all follow the same annual cycle described above, but differ substantially in social system, as summarized in Table 2.1. Most notably, they differ in social organization during summer (female maternity colony size and male bachelor groups) and mating system (temporary harem formation and promiscuous mating at swarming sites), providing a comparative framework to explore the effects of these host characteristics on parasite prevalence and distribution across the host sexes. Wing-mites of the genus Spinturnix infect almost all European bat species, and show a clear coevolutionary pattern with their bat hosts (Bruyndonckx et al. 2009a). They are hematophagous and live exclusively on the wing and tail membranes of their host (Evans 1968). Larval stages develop inside the female mite, which gives birth to protonymphs that are able to move and feed independently (Evans 1968). Thus mites never have to leave the host. Reproduction occurs almost exclusively in summer maternity colonies, with strong peaks in the presence of gravid female mites during host pregnancy and lactation, and no gravid females observed at low temperatures in winter (Lourenço and Palmeirim 2008).

33 Table 2.1 Overview of the differences in host social system and their predicted effects on parasite transmission. * samples were taken from lactating females only. § for all species male bats are sporadically also observed in female maternity colonies. 1 (Krapp 2004), 2 (Lučan 2006), 3 (Postawa and Szubert-Kruszyńska 2014), 4 (Encarnação and Reiners 2012), 5 (Zahn and Dippel 1997)

M. daubentonii M. myotis M. nattereri Predicted effect Summer (Females) Social Organization Small colonies Large colonies Small colonies Larger colony size will (10-100)1 (50-2000)1 (10-100)1 yield higher parasite prevalence and intensity Parasite prevalence 100% / 100% / - / mean intensity 10.3±1.1*2 17.9±1.22 3

Summer (Males) Social Organization Solitary or male Solitary § Solitary § Male groups will yield bachelor groups higher parasite § prevalence and intensity Autumn Mating system Swarming and Swarming and Swarming 1 Temporary harems will Local mating 1, 4 Temporary yield higher parasite harems 1, 5 transmission than swarming

Mite infection has been observed to decrease during autumn and winter in M. daubentonii (Lučan 2006), although this pattern was not observed in autumn in the North American bat Myotis lucifugus (Webber et al. 2015). This reduction is presumably due a combination of reduced mite reproduction and increased grooming activity and immunocompentence in their hosts. Mites are able to distinguish between host species (Giorgi et al. 2004) and host sex (Christe et al. 2007) and show a preference for juvenile hosts in summer maternity colonies (Christe et al. 2000). Mite infection increases host grooming activity and metabolism (Giorgi et al. 2001), and thus may impose a substantial cost, especially to juvenile hosts in maternity colonies (Lourenço and Palmeirim 2007). A study of mite population genetic structure across maternity colonies in M. myotis and Myotis bechsteinii, the latter having a similar social organization as M. nattereri (Rivers et al. 2005, Kerth and van Schaik 2012), found contrasting levels of genetic diversity and genetic differentiation between the maternity colonies of the two host species (van

34 Schaik et al. 2014). Nevertheless, in both M. myotis and M. bechsteinii, substantial horizontal transmission of mites during the autumn mating season was implicated but could not be examined. In the present study, we investigated mite infection of bats captured at three swarming sites in Germany throughout the bats’ autumn mating season. As mite infection intensity reduces rapidly after the disbandment of summer maternity colonies in autumn, and as there is substantial contact between conspecifics in the bats during mating at this time, we expect most successful mite horizontal transmission to occur during this period. Using linear mixed effect models, we investigated the temporal dynamics of infection throughout the mating season in each of the different host age and sex classes. By comparing the results observed in each species, we aim to explore the effect of differences in host social system on parasite infection and opportunities for transmission. We hypothesize that differences in host female social organization will affect overall mite prevalence and intensity according to their summer maternity colony size, but that overall infection will decrease throughout the season in all species. Additionally, we predict that differences in host mating system and male social organization will affect the temporal dynamics of infection across host sexes during the autumn swarming season: with higher levels of mite prevalence and intensity in males of M. daubentonii as a result of their summer bachelor groups; moderate levels in M. myotis through extended contact with females in temporary harems; and low levels in M. nattereri through exclusive contact to females at swarming sites.

35 Methods

Study site and bat capture

The study was carried out at three large swarming sites in Germany (Table

2.2), during August and September in 2011 and 2012. Bats were caught

using mist-nets (Schönsteinhöhle and Esperhöhle) or a harp trap (Brunnen

Meyer) at the entrance of each site. In both years each site was sampled four

times (2011: 26 August - 29 September; 2012: 4 August - 27 September),

approximately every 7 (2011) to 14 (2012) days, depending on weather

conditions. This temporal range covers the peak swarming activity for all

three species (Piksa et al. 2011, van Schaik et al. 2015b).

Table 2.2 Overview of the three sampling locations, the number of individuals of each species caught at each site and the total number of mites collected per species.

Sampling Location Coordinates Year events M. daubentonii M. myotis M. nattereri Brunnen Meyer 51.96, 7.37 2011 4 111 1 175 2012 4 111 3 123 Esperhöhle 49.76, 11.29 2011 4 6 181 31 2012 4 36 245 39 Schönsteinhöhle 49.81, 11.24 2011 4 14 52 252 2012 4 38 43 137 Total 24 316 525 757 Total number of mites sampled 414 1873 241

36 For each individual bat, species, forearm length, mass, and age were recorded. Age was classified as either adult or young of year (YOY) based on the level of ossification of the epiphyseal joints (Kunz 1988). At the

Schönsteinhöhle and Esperhöhle, all captured bats were temporarily marked on the thumbnail using permanent marker to exclude recaptured individuals.

At the Brunnen Meyer, M. nattereri and M. daubentonii had been marked for a concurrent study (F. Meier, L. Grosche, unpublished data), thereby excluding recaptures. During our study, bats of ten other species were also caught (n=214); a summary of these captures (including mite prevalence and intensity) is given in the supplementary materials (Table S2.1). Notably, several species were caught in large numbers but were rarely or never infected with mites (see discussion).

Captured bats were placed in separate capture bags to avoid contamination of mites prior to sampling. Bat wing and tail membranes were systematically inspected and all mites were collected and stored in 96% alcohol.

Data analysis

Infection dynamics were investigated using two standard measures of parasite infection: prevalence, the proportion of hosts infected with one or more mites, and intensity, the number of mites on a single infected host excluding hosts which are not parasitized (sensu (Bush et al. 1997)), using generalized linear mixed effects models (package lme4 in R 2.14.1; (Bates et al. 2014, R Development Core Team 2015)). First, for each species and each

37 measure (prevalence, intensity) we ran a separate model in which we compared overall infection levels across the four host age and sex combinations (adult male, adult female, YOY male, YOY female; henceforth referred to as host classes), and a second set of models comparing the overall temporal trend of infection pooled across all host classes. In these models, host class or capture date (respectively) were used as fixed effects, and capture site and year were included as random effects. Subsequently, to investigate the change in infection level of each host class throughout the swarming season, the models were run with both host class and capture date as fixed effects and capture site and year as random effects.

In all cases, mite prevalence was modeled using logit-linked binomial errors. Mite intensity was modeled using a poisson distribution (log-link). As we intended to compare the temporal infection dynamics of male hosts to those of females, adult female hosts were used as the intercept for all models, and all other classes were evaluated relative to these estimates. To assess model output and to evaluate differences among host classes, we used the sim function (package arm; (Gelman et al. 2014)) to generate 95% credibility intervals based on 2000 simulations of the posterior distribution.

Credibility intervals that did not include zero were considered to be significant in the frequentist sense. For all models, the influence of the random effects (sampling location and sampling year) is summarized in the supplementary materials (Table S2.2).

As mite intensity (log-link) models were overdispersed, both with and without day as an additional fixed effect, they were also analyzed using a

38 zero-truncated distribution (pospoisson: package VGAM; (Yee and Wild

2010)). In this model host class was included as a fixed effect with no random effects included in the model. The additional models did not yield qualitatively different results (Supplementary materials, Table S2.3).

39 Results

Capture overview A total of 1598 bats of the three target species were caught, and 2528 mites were collected from them (Table 2.2). We caught more male than female bats in all three species, although male bias was stronger in M. daubentonii and M. nattereri than in M. myotis (0.66, 0.69 and 0.56 respectively). Approximately one third of the bats caught were identified as young of year (0.30, 0.37 and 0.37 respectively).

Myotis daubentonii In M. daubentonii, overall prevalence and intensity did not differ between host classes (Table 2.3; Figure 2.1). Pooled across host classes, mite prevalence and intensity all decreased over time during the swarming season (Table 2.3). The temporal decrease in both infection parameters was comparable across adult females, adult males and YOY males (Table 2.4; Figure 2.2a, 2.3a). However, a stronger decrease in mite prevalence was observed in YOY females relative to adult female hosts (Table 4).

Myotis myotis In M. myotis, overall prevalence and intensity were all higher in adult females than in both adult male and YOY male hosts (Table 2.3, Figure 2.1). Prevalence levels between adult females and YOY females did not differ, but mite intensity was lower in YOY females (Table 2.3). Pooled across host classes, mite prevalence did not change temporally, but mite intensity decreased throughout the swarming season (Table 2.3). Temporal dynamics of mite prevalence and intensity did not differ between adult females and both male and female YOY, with decreases in both parameters throughout the mating season (Table 2.4; Figure 2.2b, 2.3b). Conversely, mite prevalence and intensity increased over the swarming season in adult male bats (Table 2.4). Indeed, by the end of swarming

40 season, prevalence and intensity levels in adult male hosts approached those seen in the other host classes (Figure 2.2b, 2.3b).

Table 2.3 Estimated effect sizes and 95% credibility intervals for mite prevalence (binomial; logit-scale) and intensity (poisson; log-scale) for each host class pooled across all capture dates (top) and the overall temporal trend pooled across all host classes (bottom) with capture location and year as random effects. * denotes estimates where the 95% CI does not include zero.

Prevalence Intensity Species Fixed effect Estimate 95% CI Estimate 95% CI Host class M. daubentonii Intercept (Ad F) 0.33 (-0.35, 0.99) 0.76 (0.56, 0.98) Ad M -0.13 (-0.71, 0.42) 0.16 (-0.08, 0.41) YOY F 0.08 (-0.74, 0.87) -0.17 (-0.54, 0.19) YOY M -0.48 (-1.19, 0.22) 0.11 (-0.19, 0.43) M. myotis Intercept (Ad F) 2.42 (1.82, 3.04) 1.55 (0.73, 2.33) Ad M -3.15* (-3.82, -2.48) -0.88* (-1.05, -0.70) YOY F -0.42 (-1.37, 0.38) -0.14* (-0.26, -0.03) YOY M -1.86* (-2.59, -1.15) -0.57* (-0.70, -0.44) M. nattereri Intercept (Ad F) -0.91 (-1.33, -0.50) 0.58 (0.34, 0.80) Ad M -2.18* (-2.83, -1.54) -0.17 (-0.66, 0.28) YOY F 0.1 (-0.46, 0.69) 0.23 (-0.11, 0.57) YOY M -0.17 (-0.64, 0.32) -0.06 (-0.37, 0.27) Temporal M. daubentonii Intercept (1 Aug) 1.39 (0.76, 2.03) 1.28 (1.06, 1.50) Day -0.03* (-0.05, -0.02) -0.01* (-0.02, -0.01) M. myotis Intercept (1 Aug) 0.52 (0.06, 0.96) 2.26 (2.03, 2.49) Day 0.00 (-0.01, 0.01) -0.02* (-0.02, -0.02) M. nattereri Intercept (1 Aug) -1.08 (-1.90, -0.24) 1.13 (0.61, 1.64) Day -0.01 (-0.03, 0.01) -0.01* (-0.02, 0.00)

41 Figure 2.1 Overall (a) prevalence and (b) intensity of mites on bats captured (mean ± SE), subdivided by host class. N denotes the number of sampled individuals per host class. a N 71 149 37 59 147 184 84 110 143 332 88 194 1.00

0.75

0.50 Prevalence

0.25

0.00 Ad F Ad F Ad F Ad Ad M Ad M Ad M YOY F YOY F YOY F YOY YOY M YOY M YOY M YOY

M. daubentonii M. myotis M. nattereri b N 41 84 23 28 135 60 74 70 41 14 28 50 8

6

Intensity 4

2 Ad F Ad F Ad F Ad Ad M Ad M Ad M YOY F YOY F YOY F YOY YOY M YOY M YOY M YOY

M. daubentonii M. myotis M. nattereri

42 Myotis nattereri Overall prevalence and intensity in M. nattereri were low (Figure 2.1), and did not differ between adult females and YOY of both sexes (Table 2.3). Mite prevalence on adult males was drastically lower (Table 2.3), but mite intensity did not differ relative to the levels found in adult females. Similar to M. myotis, when pooled across host classes, mite prevalence did not change temporally, but mite intensity decreased throughout the swarming season (Table 2.3). Both prevalence and intensity decreased over the swarming season in adult females and both male and female YOY (Table 2.4, Figure 2.2c, 2.3c), whereas they increased over time in adult male hosts (Figure 2.2c, 2.3c), albeit insignificantly (Table 2.4).

Table 2.4 Estimated effect sizes and 95% credibility intervals for the temporal change of mite prevalence (binomial; logit-scale) and intensity (poisson; log-scale) per host class, with capture location and year as random effects. * indicates estimates where the 95% CI does not include zero.

Prevalence Intensity Species Fixed effect Estimate 95% CI Estimate 95% CI M. daubentonii Intercept (Ad F * day) -0.02 (-0.06, 0.02) -0.01 (-0.03, 0.00) Ad M * day -0.01 (-0.05, 0.04) 0.00 (-0.01, 0.02) YOY F * day -0.11* (-0.19, -0.02) -0.01 (-0.04, 0.02) YOY M * day -0.04 (-0.10, 0.02) 0.00 (-0.03, 0.02) M. myotis Intercept (Ad F * day) -0.05 (-0.09, 0.01) -0.02 (-0.02, -0.01) Ad M * day 0.11* (0.06, 0.15) 0.02* (0.00, 0.03) YOY F * day -0.01 (-0.07, 0.06) 0.00 (-0.01, 0.00) YOY M * day 0.05 (-0.01, 0.09) 0.00 (0.00, 0.01) M. nattereri Intercept (Ad F * day) -0.03 (-0.06, 0.01) -0.01 (-0.03, 0.01) Ad M * day 0.05 (-0.01, 0.10) 0.01 (-0.05, 0.06) YOY F * day -0.02 (-0.08, 0.03) -0.01 (-0.04, 0.02) YOY M * day 0.01 (-0.03, 0.05) 0.01 (-0.02, 0.04)

43 Figure 2.2 Temporal dynamics of mite prevalence during the autumn mating season in (a) M. daubentonii, (b) M. myotis, (c) M. nattereri.

a 1.00

0.75

0.50 Prevalence M. daubentonii 0.25

0.00

0204060

b 1.00

0.75 Age/Sex class

Adult F

Adult M 0.50

YOY F Prevalence M. myotis M.

YOY M 0.25

0.00

0204060

c 1.00

0.75

0.50 Prevalence M. nattereri M.

0.25

0.00

0204060 Day (1 = Aug 1)

44 Figure 2.3 Temporal dynamics of mite intensity during the autumn mating season in (a) M. daubentonii, (b) M. myotis, (c) M. nattereri. Points indicate average intensity per host class per sampling day.

a 5

4

3

Intensity 2 M. daubentonii

1

0

0 20 40 60 b

10 Age/Sex class

Adult F

Adult M Intensity

M. myotis M. 5 YOY F

YOY M

0

0 20 40 60

c 5

4

3

Intensity 2 M. nattereri M.

1

0

0 20 40 60 Day (1 = Aug 1)

45 Discussion

Through a comparative framework across three European bat species and their parasitic wing mites, we observed substantial differences in initial parasite infection of all host classes and the infection dynamics of male hosts between species as predicted based on the differences in their social systems.

Overall mite prevalence and intensity In female and YOY hosts, overall prevalence and intensity levels were highest in M. myotis, intermediate in M. daubentonii and lowest in M. nattereri. In male hosts prevalence and intensity was highest in M. daubentonii with lower levels of infection in the other two species. The observed relative infection rates of the hosts closely mirror the size of host summer aggregations, where M. myotis have larger maternity colonies than the other two species, and males of M. daubentonii form bachelor group aggregations while the males of the other species are almost exclusively solitary during summer. Notably, although overall prevalence and intensity values of females also broadly correspond to the differences in body size between the species (M. myotis > M. daubentonii and M.nattereri), this pattern does not hold for the males of these species and across the other bat species also captured at the same sites (compare in Supplementary materials; Table S2.1). Additionally, body size does not account for the marked differences observed between sexes within species, nor the different temporal dynamics of mite infection observed in the three host species. Therefore, we conclude that host social organization in summer, particularly aggregation size, shapes the overall level of mite infection seen during the autumn mating phase across these species.

Temporal dynamics Despite the difference in overall mite prevalence and intensity across species, the overall temporal dynamics of mite infection of female and YOY hosts (i.e. all host classes living in maternity colonies previous to our

46 sampling) were broadly similar between the investigated species. Overall mite prevalence and intensity levels at the beginning of the autumn mating season were already lower than peak infection levels observed in host summer colonies (Lučan 2006, Encarnação et al. 2012, Postawa and Szubert-Kruszyńska 2014). Additionally, mite intensity continued to decrease throughout the investigated period in all species, and in M. daubentonii overall prevalence also decreased. Presumably this decrease is the result of the disbandment of host maternity colonies during our sampling period, an increase in immunocompentence and grooming behavior of the hosts (Christe et al. 2000), and the cessation of reproduction in the mites (Deunff and Beaucournu 1981, Lourenço and Palmeirim 2008). Interestingly, in contrast to the decrease observed in this study, no decrease in parasite load was observed in Myotis lucifugus during the autumn mating season in Canada (Webber et al. 2015). This was suggested to be a result of the cold climate, which resulted in increased host aggregation during the mating season and a comparatively short mating season due to the earlier onset of hibernation (Webber et al. 2015), a pattern which is not observed in the three species studied here. Taken together, these results highlight the role of the abiotic environment in shaping host social organization and subsequently host-parasite dynamics. In contrast to female and YOY hosts, male temporal infection dynamics did differ between species. In M. myotis adult male bats were initially rarely infected, but by the end of the season, prevalence and intensity of mites reached similar infection levels to those seen in adult female and YOY hosts at this time, suggesting that substantial transmission is taking place during the autumn mating period. This transmission can either occur during contact between hosts at swarming sites, or in the temporary harems formed during this period in which adult males roost together with several females (either simultaneously or consecutively) for one or several days (Zahn and Dippel 1997). In M. nattereri mite prevalence and intensity on male bats was similarly low initially, but unlike the increase seen in M. myotis, only trended upward throughout the autumn mating period. This is likely due to

47 the lower overall prevalence and intensity observed across all host classes in M. nattereri, combined with the limited transmission opportunities afforded by the short inter-individual contact during mating at swarming sites in contrast to the relatively long contact time in harem groups in M. myotis. Finally, in M. daubentonii, temporal infection dynamics of male bats did not differ from those seen in female and YOY hosts, as predicted from their aggregation in male bachelor groups throughout the summer. As all host classes showed similar prevalence and intensity levels throughout the season, we cannot infer that transmission of parasites is taking place as in the other bat species, although it appears likely given that the majority of individuals are infected, and individuals must come into contact for mating. Altogether across the three systems, we find that the temporal dynamics of mite infection strongly reflect the variation in host mating system as well as the changes in host social organization during this period.

Host social system and parasite infection dynamics The observed correlations between host social system and mite infection dynamics have several important implications for parasite population structure. In M. myotis, the formation of temporary harems during the mating season is particularly likely to increase parasite transmission, as individuals remain in contact for much longer than during the brief mating events at swarming sites. In addition to resulting in higher infection levels of male bats, S. myoti mites may also be transmitted directly from female to female possibly originating from different colonies in harems where multiple females roost with a male simultaneously (Zahn and Dippel 1997). Moreover, the high overall prevalence of mites on all host classes is likely to facilitate further mite transmission during winter. As a result, the mite meta-population should be well mixed and its effective population size is expected to be much larger than in the other investigated species. Support for this prediction is found in an analysis of mite population genetic structure across six M. myotis maternity colonies, which found high overall genetic diversity and very little

48 genetic differentiation between mites from different M. myotis colonies (van Schaik et al. 2014). In M. daubentonii, the presence of male bachelor groups increases the number of host clusters available to mites during their reproductive period (summer). This should increase the overall parasite persistence within the local meta-population, making regional extinctions (see M. nattereri discussion below) far less likely. Additionally, it effectively increases the amount of transmission of mites during the bats’ mating season, as mites no longer need to transfer exclusively to female hosts, but can additionally persist on male hosts. Therefore, despite lower overall levels of mite infection than in M. myotis, mite (genetic) population structure is likely to be similarly well mixed and temporally stable across the mite meta-population. Interestingly, mites have previously been shown to have a preference for female hosts over male hosts in M. daubentonii (Christe et al. 2007), but this preference was not reflected in the mite prevalence and intensities observed here. However, we did find a slightly higher prevalence and intensity of mites on adult hosts of both sexes over YOY hosts. This may indicate a preference for adult hosts of either sex during the mating (and hibernation) phase, which would be advantageous as these host individuals are more likely to survive than YOY (Lentini et al. 2015). Finally, in M. nattereri, we observed low overall level of mite infection, and limited transmission during the swarming season. In combination with the small female maternity colony size, we therefore anticipate survival of mite populations from year to year in individual host populations to be much lower than in the other investigated mite species. As a result, local extinction/re-colonization events are expected to be frequent (Reckardt and Kerth 2009). Such local extinctions in individual host summer maternity colonies would further lower the overall prevalence and intensity of mites at the onset of autumn swarming in the subsequent year. This may explain the observed difference in prevalence and intensity between M. nattereri and M. daubentonii despite their similar summer maternity colony sizes. Indeed, if the density of host colonies in a particular area is low, and local mites

49 populations within several host maternity colonies go extinct, horizontal transmission of mites at swarming sites may be insufficient to prevent regional extinction of mites within the catchment area of those swarming sites. A comparison with Myotis bechsteinii, which has a similar social system to M. nattereri (Dietz et al. 2007), shows that such a scenario may be plausible. In this study we captured over 70 M. bechsteinii but we did not find any to be infected with mites (see Table S2.1), despite the fact that such mites are common in several nearby (±100 km) German regions (Bruyndonckx et al. 2009b, van Schaik et al. 2014). This stochasticity in local extinction patterns can also have strong consequences for parasite population genetic structure in regions where the parasite does not go regionally extinct. In M. bechsteinii, mite populations from different maternity colonies were temporally unstable as a result of the limited transmission and low number of founding individuals per host colony (Bruyndonckx et al. 2009b, van Schaik et al. 2014).

Conclusion Taken together, our findings illustrate several important effects of host social system on parasite population dynamics. As shown in many other vertebrate systems, host group size and density during the reproductive period of both host and parasite strongly influence parasite infection intensity (eg. Côté and Poulin 1995, Rifkin et al. 2012, Patterson and Ruckstuhl 2013). However, as a result of host social behavior restricting interactions between different host social units, horizontal transfer of parasites between such aggregations may be limited (Barrett et al. 2008). In hosts with strong seasonality, social structure may subsequently change drastically through the year, as is the case in temperate zone bats. These changes provide additional horizontal transmission opportunities for permanent ectoparasites. This could happen either via hosts of the opposite sex acting as vectors, or through direct contact of conspecifics from different colonies as shown here for bats and in other studies for migratory bird species with communal wintering grounds

50 (Gomez-Diaz et al. 2012). In addition, seasonal changes in the social organization of hosts are often coupled with changes in host behavior (eg. grooming rate) or physiology (eg. hibernation), which may also influence parasite survival. Therefore, both the social organization of hosts during the main reproductive season, as well as the transmission opportunities and challenges to parasite survival during the “suboptimal” seasons will combine to affect parasite population and genetic structure. Notably, the resulting parasite population structure will ultimately affect the coevolutionary dynamics between host and parasite (Boots et al. 2004, Gandon and Nuismer 2009a, Lion and Boots 2010). Therefore, in order to understand both the proximate and ultimate dynamics of parasite infection in hosts where the social organization changes throughout the year, a holistic approach that includes infection during the main reproductive period, but also the focal points of parasite transmission and the critical phases for parasite survival, is required.

Acknowledgements

This study was funded by a grant from the Volkswagen Stiftung (Az 84 871). We would like to thank Frauke Meier, Lena Grosche, Johannes Mohr, Matthias Hammer, Leonie Baier, Stefan Greif, and many other volunteers for their help in the field. We also thank Robin Abbey-Lee for her help with data analysis, and Susanne Seltmann for her critical comments on the manuscript. JvS is a member of the Max Planck Research School for Organismal Biology.

51 Supplementary Materials

Table S2.1 Overview of the other bat species caught at swarming sites during this study, including their mite prevalence and intensities. Notably, mites were entirely absent on M. bechsteinii despite moderately high sample sizes.

Species Sex - Age N Ninfected Nparas Prevalence Intensity B. barbastellus M Adult 35 9 17 0.26 1.88 M YOY 3 1 2 0.33 2 F Adult 7 3 3 0.43 1 E. nilssonii M Adult 3 1 1 0.33 1 M YOY 1 0 0 0 - E. serotinus M Adult 1 0 0 0 - M. alcathoe M adult 1 0 0 0 - F adult 1 0 0 0 - M. bechsteinii M Adult 45 0 0 0 - M YOY 21 0 0 0 - F Adult 2 0 0 0 - F YOY 7 0 0 0 - M. brandtii M Adult 6 1 2 0.17 2 M YOY 7 2 4 0.29 2 F Adult 5 3 4 0.60 1.33 M. dasycneme M Adult 7 0 0 0 - M YOY 1 0 0 0 - F Adult 1 0 0 0 - M. mystacinus M Adult 9 2 5 0.22 2.5 M YOY 12 1 2 0.08 2 F Adult 7 2 4 0.29 2 F YOY 5 2 7 0.40 3.5 P. auritus M Adult 12 1 4 0.08 4 M YOY 3 2 3 0.67 1.5 F Adult 2 0 0 0 - F YOY 2 2 5 1.00 2.5 P. pipistrellus M Adult 6 0 0 0 - M YOY 1 0 0 0 - F Adult 1 0 0 0 -

52 Table S2.2 Since mixed models of intensity were overdispersed when run using a poisson fit, these models were reevaluated using a zero-truncated fit (pospoisson VGLM, package VGAM; Yee and Wild 2010). In all tests, direction and significance did not differ from the initial model.

Intensity - Overall Intensity - Temporal Species Fixed effect Estimate P Fixed effect Estimate P M. daubentonii Intercept (Ad F) 0.6 <0.01 Intercept (Ad F * day) -0.02 0.02 Ad M 0.24 0.12 Ad M * day 0.01 0.42 YOY F -0.29 0.24 YOY F * day -0.03 0.14 YOY M 0.16 0.40 YOY M * day 0.00 0.91 M. myotis Intercept (Ad F) 2.00 <0.01 Intercept (Ad F * day) -0.02 <0.01 Ad M -1.14 <0.01 Ad M * day 0.02 0.05 YOY F -0.20 <0.01 YOY F * day -0.01 0.12 YOY M -0.67 <0.01 YOY M * day 0.00 0.32 M. nattereri Intercept (Ad F) 0.26 0.12 Intercept (Ad F * day) -0.02 0.07 Ad M -0.39 0.32 Ad M * day 0.00 0.96 YOY F 0.40 0.08 YOY F * day -0.01 0.51 YOY M -0.12 0.60 YOY M * day 0.02 0.42

53 Table S2.3 Location and sampling year were included in all models as random effects. Although no consistent patterns was evident, both location and sampling year did contribute significantly to individual models as summarized in the table below. In M. myotis, mite intensity differed across sampling locations when the very small sample set from Brunnen Meyer (n = 4) was included, but did not differ when these were not considered.

Species Random effect Prevalence Intensity M. daubentonii location

year *

M. myotis location *

loc without BM

year *

M. nattereri location

year

overall per host class host per overall M. daubentonii location

year

M. myotis location

loc without BM

year *

M. nattereri location *

year

overall temporal overall M. daubentonii location

year

M. myotis location

loc without BM

year

M. nattereri location *

year

host class x temporal x class host

54

55 Chapter 3

The effect of host social system on parasite population genetic structure: comparative population genetics of two ectoparasitic mites and their bat hosts

J. van Schaik, G. Kerth, N. Bruyndonckx and P. Christe

BMC Evolutionary Biology, 14:18, 2014

♂ Spinturnix bechstenii

56

57 Abstract

Background The population genetic structure of a parasite, and consequently its ability to adapt to a given host, is strongly linked to its own life history as well as the life history of its host. While the effects of parasite life history on their population genetic structure have received some attention, the effect of host social system has remained largely unstudied. In this study, we investigated the population genetic structure of two closely related parasitic mite species (Spinturnix myoti and Spinturnix bechsteini) with very similar life histories. Their respective hosts, the greater mouse-eared bat (Myotis myotis) and the Bechstein’s bat (Myotis bechsteinii) have social systems that differ in several substantial features, such as group size, mating system and dispersal patterns.

Results We found that the two mite species have strongly differing population genetic structures. In S. myoti we found high levels of genetic diversity and very little pairwise differentiation, whereas in S. bechsteini we observed much less diversity, strongly differentiated populations and strong temporal turnover. These differences are likely to be the result of the differences in genetic drift and dispersal opportunities afforded to the two parasites by the different social systems of their hosts.

Conclusions Our results suggest that host social system can strongly influence parasite population structure. As a result, the evolutionary potential of these two parasites also differs strongly, thereby affecting the risk and evolutionary pressure exerted by each parasite on its host.

58 Introduction

In the evolutionary arms race between hosts and their parasites, the interacting species may use immunological, physiological and behavioural adaptations (Loehle 1995, Ezenwa 2004). Hosts commonly use behavioural adaptations to avoid exposure, or actively remove, parasites (Hart 1990). In addition behavioural adaptations may also affect parasite population structure, thereby potentially reducing parasite intensity (Loehle 1995), and ultimately their evolutionary potential, classically defined as the ability to incorporate genotypes able to outcompete those put forward by the opponent (Gandon and Michalakis 2002). On the population level, a parasite’s genetic structure is closely linked to the life histories of both interacting species (Nadler 1995), as well as to the social system of the host (Altizer et al. 2003). Specifically, the relative rate of dispersal, and thereby gene flow (Gandon and Michalakis 2002), as well as the relative strength of genetic drift (Gandon and Nuismer 2009b, Nuismer et al. 2010), are important in determining host-parasite coadaptation dynamics. Therefore, comparisons of population genetic structure across multiple host-parasite pairs where hosts differ in key life-history and/or social system traits, will help elucidate how these factors affect microevolutionary host-parasite dynamics. Relative dispersal rates of hosts and parasites have been studied in a number of systems. For instance, in the black-legged kittiwake and a parasitic tick, parasite populations were found to be much more spatially structured than those of their hosts (McCoy et al. 2005). This difference was attributed to the fact that parasite dispersal was limited to the breeding season of the hosts, and therefore dispersal of the host outside of this period did not result in concurrent parasite dispersal (McCoy et al. 2005). In contrast, in a comparison of dispersal rates between two shearwater species and three parasitic lice, parasite gene flow was found to be much higher than that of its host, which was attributed to the transmission of parasites at communal wintering grounds where no host gene flow took place (Gómez- Díaz et al. 2007). These examples highlight the fact that relative dispersal is dependent on the intricate interaction between the life histories of both

59 species. In cases where gene flow in host and parasite are comparable, genetic drift can also substantially affect host-parasite coevolutionary dynamics as it can impede adaptation; even in cases where standing genetic variation is abundant in both species (Nuismer et al. 2010). This is especially relevant for parasites of vertebrate hosts, where meta-population dynamics often lead to patchily distributed parasite populations. As a result parasite populations often experience extinction events and strong population bottlenecks (e.g. Hafner et al. 2003). Unfortunately, comparative studies investigating the role of host social system in shaping parasite population genetic structure are rare. In this study, we investigate the population genetic structure of two ectoparasitic mite species that parasitize two closely related bat hosts with differing social systems. The mite species (Spinturnix myoti and Spinturnix bechsteini) are closely related and have indistinguishable life histories (Rudnick 1960, Deunff et al. 2004). As a result, we expect any differences observed in their microgeographic population genetic structure to be primarily the result of differences in the social system of their hosts, the greater mouse-eared bat (Myotis myotis) and the Bechstein’s bat (Myotis bechsteinii). The two host species share similar life-history traits but show substantial differences in their social systems, which include their social organization, social structure and mating system (Table 3.1). Both are long- lived, monotocous, non-migratory European vespertilionid bat species that follow the temperate cycle. In summer, they form exclusively female maternity colonies, which however differ between the two species in size, location, stability and degree of philopatry (Table 3.1). Females from different maternity colonies of M. myotis sometimes visit other maternity colonies and occasionally co-localize with maternity colonies of closely related Myotis blythii, whereas females from M. bechsteinii maternity colonies do not interact with one another or with other species. Males of M. myotis and M. bechsteinii disperse from their natal colony and are solitary throughout the summer (Zahn and Dippel 1997, Kerth and Morf 2004). In the autumn mating

60 Table 3.1 Overview of the key differences in social system between the greater mouse-eared bat (Myotis myotis) and Bechstein’s bat (Myotis bechsteinii), and the expected effects thereof on the population genetic structure of their parasites.

Schaik 2012 Schaik

Reference 2004 Krapp 2001 al. et Castella van & Kerth 2007 Kerth & Reckardt 2004 Krapp 2004 Krapp 1997 Dippel & Zahn 2003 al. et Kerth

fusion dynamics - Predicted effect on on effect Predicted population parasite structure genetic to lead colonies Larger less genetic drift to leads philopatry Lower parasite more transmission Fission drift genetic increase may into split colonies because subgroups reduces roosting Solitary transmission parasite harems Temporary increase parasite transmission

no

fusion

- 50)

– Bechstein’s bat Bechstein’s bechsteinii Myotis (10 Small almost high; Very individuals of exchange colonies between roost frequent low; Very cavities) (tree switching fission and dynamics In crevices (mostly solitary) contact) (little Swarming

eared bat eared

-

2000) occasional occasional –

hanging; solitary or or solitary hanging; - Greater mouse Greater myotis Myotis (50 Large but High; individuals of exchange colonies between (building/ site one High; summer throughout cave) Free clustered harems Temporary (extensive contact) and/or contact) swarming(little

natal natal philopatry Colony size Colony Hibernation Female Female Roost fidelity Roost

Social organization system Mating

61 season, male M. myotis form temporary harems in August and September where several females roost in direct contact with a male for one or more days. In contrast, M. bechsteinii mate at swarming sites where the sexes meet very briefly during the night (Kerth et al. 2003b). In winter both species hibernate at underground sites, but again differ in degree of aggregation and body contact, where M. myotis may form large clusters whereas M. bechsteinii roosts solitarily (Krapp 2004). Finally, the species differ in the distance travelled between summer and winter roosts. M. myotis is considered a regional migrant, easily travelling over 50 km, whereas M. bechsteinii is considered sedentary, generally not travelling over 30 km (Hutterer et al. 2005). Both species have recolonized the current study area since the last glacial maximum. However, for M. myotis there is the possibility of admixture as multiple glacial refugia have been identified (Iberia and Italy; Ruedi et al. 2008), while all M. bechsteinii in Central Europe are believed to originate from the Balkan region (Kerth et al. 2008). Both species are parasitized by ectoparasitic mites of the genus Spinturnix, which typically show strong cospeciation with their bat hosts (Bruyndonckx et al. 2009a). Spinturnix wing mites live exclusively on membranes of bats, reproduce sexually, are haematophagous and cannot survive off of their host for more than a few hours (Giorgi et al. 2004). Therefore, while dispersal of Spinturnix mites is extensive within bat maternity colonies, where female bats live in close body contact, little (M. myotis) or no (M. bechsteinii) transmission can occur between different maternity colonies in summer (Bruyndonckx et al. 2009b). It is expected that horizontal transmission of mites between colonies occurs during bat mating and hibernation periods. Bat maternity colonies constitute optimal conditions for parasite reproduction, and parasites show a strong preference for female and juvenile hosts (Christe et al. 2007). Mite abundance subsequently strongly decreases in autumn and throughout hibernation, and it is supposed that they are not able to reproduce during this time (Lourenço and Palmeirim 2008). Mites are believed to impose a substantial cost on their hosts during the maternity period (Lourenço and Palmeirim 2007). For example, in M. myotis individuals

62 experienced increased oxygen consumption and weight loss when experimentally infected (Giorgi et al. 2001). Mite prevalence and intensity is much higher in M. myotis (intensity per female 12–20; Christe et al. 2000) compared to M. bechsteinii (intensity per female 1–10; Reckardt and Kerth 2009). S. bechsteini is strictly host specific. S. myoti is found on M. myotis as well as its sister species M. blythii (which has an identical social system; Krapp 2004). In choice experiments S. myoti shows a clear preference for M. myotis and it is presumed that M. myotis is the main host species (Christe et al. 2003). A previous study of mtDNA sequence data in S. bechsteini found strong spatial differentiation between bat colonies and a high temporal turnover in the haplotypes found per bat colony, suggesting frequent local extinction and recolonisation (Bruyndonckx et al. 2009b). By comparing the genetic diversity, gene flow and genetic drift of the selected parasite species, we aim to assess the consequences that the differing social systems of the hosts have on the evolutionary potential of the parasites. In accordance with Nadler (1995), we predict that the larger colony size and increased contact rates among colonies of M. myotis will result in a less genetically structured population in S. myoti, and allow for substantial gene flow between colonies. In contrast, we expect the mite population of M. bechsteinii to be highly sub-structured due to reduced dispersal opportunities and strong genetic drift as a result of the smaller and demographically more isolated host colonies.

63 Methods

Previously analysed samples To compare host and parasite population genetic structure, we have combined newly generated datasets for both parasites (S. myoti: mtDNA cytb sequence data and 8 nucDNA microsatellites; S. bechsteini: 5 nucDNA microsatellites), with previously generated datasets for one of the mite species (S. bechsteini: mtDNA cytb) and both hosts (mtDNA and nucDNA), supplemented for M. myotis with two additional colonies for this study. An overview of the markers and samples previously analysed is given below as well as in the supplemental materials (Table S3.1). For M. myotis, four summer maternity colonies had been previously genotyped for ten microsatellites and sequenced for the second hypervariable domain (HVII) of the mtDNA control region (Castella et al. 2001). For M. bechsteinii, individuals from ten maternity colonies had been genotyped for eight nucDNA microsatellites as well as two mitochondrial microsatellites (Kerth et al. 2002b, Kerth et al. 2008). For S. bechsteini, mites from thirteen bat maternity colonies had been previously sequenced for a 513 bp fragment of Cytochrome B (Bruyndonckx et al. 2009b).

Sample collection and DNA extraction We sampled S. myoti in six M. myotis maternity colonies in Switzerland and Northern Italy in August 2004 and 2005 (Figure 3.1, Table 3.2a). Colony size estimates were made inside the roost and bats were caught either directly inside the colonies’ roosts during the day, or upon emergence from the roost entrance at night. Geographic distances between colonies ranged from 16 to about 200 km, which is comparable to the range M. myotis is known to disperse between summer and winter roosts (Hutterer et al. 2005). Twenty mites per bat colony, each originating from a different bat, were used for the genetic analyses.

64 Figure 3.1 Map of Central Europe showing the sampling locations for Myotis myotis/Spinturnix myoti (circles), and sampling regions for Myotis bechsteinii/Spinturnix bechsteini (triangles). For the latter pairing, the number of sampled colonies within a region is indicated within the triangle because all colonies within a region are located in close proximity to one another. All colony and region names correspond to the abbreviations given in Table 3.2. For each species, a picture of the typical roosting association is shown with an inset of the studied mite species (picture credits M. bechsteinii: GK, M. myotis: PC, mites: GK & JvS).

5" 9" RP" LF"

StU" Cou" Per" Mei"

Sat"

Agl"

100 km

S. bechsteini samples were collected from 13 M. bechsteinii maternity colonies in 2002 and in 2007 in two spatially distant regions (±200 km) in Germany, Lower Franconia (LF) and Rhineland-Palatinate (RP; Figure 3.1). As M. bechsteinii has not been recorded to disperse over 73 km (Hutterer et al. 2005) direct dispersal of either host or parasite between regions is not expected. At the same time, within regions, inter-colony distances are again

65 comparable to the expected dispersal distance between summer and winter roosts. We divided the available 18 sampling events from 13 colonies into three main subgroups based on spatial and temporal characteristics (LF in 2002: 100 mites from 5 bat colonies; LF in 2007: 195 mites from 8 bat colonies; RP in 2007: 107 mites from 5 bat colonies). The number of sampling events in each subgroup is less than were analysed for mtDNA (Bruyndonckx et al. 2009b) as all events with less than 10 samples were discarded in order to ensure sufficient sample sizes for all nucDNA analyses. Samples from 2002 were only used for the temporal analysis, whereas all other comparisons were performed using only the samples from 2007. In all cases, all bats within a (bat-box) roost were caught and sampled for mites, and colony size estimates reflect the number of bats present in the colony. All mites collected from a colony were used for the genetic analysis. For both mite species, individuals were removed from the bat’s wing and tail membrane using soft forceps and stored in 90% ethanol prior to DNA extraction. Collected mite specimens were individually rehydrated for two hours in 200 μl of sterile water before being crushed in liquid nitrogen. Total DNA was isolated from each individual mite using a standard proteinase K- phenol chloroform method (Sambrook et al. 1989).

Table 3.2 (next page) Description of molecular variability in a) Spinturnix myoti, b) Myotis myotis c) Spinturnix bechsteini d) Myotis bechsteinii. The following parameters are recorded: latitude (Lat), longitude (Long), estimated number of bats in the colony (colony size), number of individuals sequenced/genotyped (n), total number of haplotypes (N), nucleotide diversity (π), the mean number of microsatellite alleles per locus (NA), allelic richness (K), observed (Ho) and expected (He) heterozygosities, the number of private alleles per colony (Pall), and the inbreeding coefficient (Fis). For S. myoti and S. bechsteini the number of individuals sequenced and genotyped was the same for each colony.

66 a) S. myoti mtDNA nucDNA microsatellites

Colony Name Year Lat Long n N π NA K Ho He Pall Fis Agliè (Agl) 2005 45.3671 7.767 20 14 0.708 17.875 15.955 0.61 0.868 22 0.264 Courtételle (Cou) 2004 47.341 7.3178 19 13 0.701 18.125 16.752 0.755 0.904 11 0.191 Meiringen (Mei) 2005 46.7296 8.1812 18 7 0.777 13.125 12.743 0.546 0.871 6 0.209 Perreux (Per) 2004 46.9479 6.8179 20 10 0.874 18 16.121 0.733 0.898 13 0.320 Satigny (Sat) 2005 46.2143 6.0357 20 8 0.536 15.5 14.122 0.663 0.872 16 0.398 St-Ursanne (StU) 2005 47.3647 7.1537 20 14 0.759 17.5 15.787 0.695 0.890 11 0.244

b) M. myotis mtDNA nucDNA microsatellites

Colony Name Colony size n N π n NA K Ho He Pall Fis Agliè (Agl) 400 20 4 1.817 20 8.2 8.71 0.735 0.723 5 -0.017 Courtételle (Cou) 800 20 2 0.033 20 9 8.39 0.785 0.761 2 -0.031 Meiringen (Mei) 80 20 2 0.062 20 9 7.43 0.795 0.772 4 -0.029 Perreux (Per) 200 20 3 0.161 20 9.9 8.16 0.79 0.789 9 -0.002 Satigny (Sat) 190 18 3 1.993 20 9.3 7 0.789 0.763 3 -0.034 St-Ursanne (StU) 200 20 1 0 20 9.7 9.03 0.733 0.763 6 0.039

c) S. bechsteini mtDNA nucDNA microsatellites

Colony Name Year Lat Long n N π NA K Ho He Pall Fis Blutsee (BS) 2007 49.4331 9.4958 41 3 0.18 5.2 3.981 0.736 0.645 1 -0.130 Einsiedeln (ES) 2002 49.5407 9.5641 16 2 0.32 6.8 5.806 0.727 0.703 2 0

2007 11 4 0.67 6.8 6.237 0.739 0.754 0 0.069

Guttenberg 2 (GB2) 2002 49.4443 9.5154 15 3 0.6 12 9.354 0.747 0.864 10 0.169

2007 20 2 0.27 6.6 5.24 0.747 0.706 2 -0.032

Gramschatz 1(GS1) 2002 49.5409 9.5842 25 3 0.46 8.2 6.133 0.677 0.750 2 0.118

2007 22 6 0.77 10.2 7.822 0.757 0.843 2 0.125 Höchberg (HB) 2002 49.4705 9.5201 21 5 0.49 7.4 5.9 0.632 0.743 3 0.175

2007 20 1 0 5.2 4.375 0.627 0.631 0 0.033 Lower Frankonia (LF) Frankonia Lower Irtenberg 3 (IB3) 2002 49.4308 9.5016 23 1 0 5 4.453 0.753 0.677 1 -0.089

2007 38 1 0 4.6 3.598 0.579 0.584 0 0.023

Reutholz (RT) 2007 49.737 9.861 22 3 0.66 9.8 7.601 0.696 0.809 2 0.164

Steinbach (SB) 2007 49.4215 9.4442 21 1 0 4.2 3.833 0.657 0.572 1 -0.126

Altrich 4 (AL4) 2007 49.9636 6.8726 14 2 0.14 5.4 4.728 0.643 0.662 2 0.065

Bitburg (BI) 2007 49.9726 6.4793 22 3 0.44 7.4 5.735 0.609 0.753 1 0.216

Palatine (RP) Palatine Duppach (DU) 2007 50.2685 6.5507 24 6 0.72 8.2 6.549 0.670 0.772 2 0.154 - Longuich (LO) 2007 49.7916 6.7514 25 3 0.67 6.6 5.01 0.701 0.710 1 0.033

Orenhofen (OH) 2007 49.9115 6.6781 22 1 0 2.6 2.255 0.345 0.352 0 0.043 Rhineland

67

d) M. bechsteinii mt msats nucDNA microsatellites

Colon Pal Colony Name n Na K n NA K Ho He Fis y size l Blutsee (BS) 15-19 30 3.5 2.22 30 11.1 5.07 0.783 0.802 1 0.057

Einsiedeln (ES) 20-24 10 1 1 10 7.1 4.63 0.85 0.769 0 -0.052

Guttenberg 2 (GB2) 35-39 70 2 1.55 70 12.6 4.95 0.801 0.825 2 0.041

Gramschatz 1 (GS1) 40-44 93 1.5 1.08 93 13 4.83 0.828 0.81 4 -0.014

Höchberg (HB) 20-24 57 4.5 2.45 57 11.6 4.86 0.806 0.799 1 0.008

Irtenberg 3 (IB3) 25-29 16 1.5 1.35 16 9.5 4.99 0.844 0.799 2 -0.024 Lower Frankonia (LF) Frankonia Lower Reutholz (RT) 40-44 17 1 1 17 9.3 4.95 0.79 0.794 2 0.029

Steinbach (SB) 20-24 34 1 1 34 9.3 4.57 0.825 0.792 1 -0.007

Rhineland Bitburg (BI) 40-44 9 1 1 9 6.8 4.85 0.819 0.795 3 0.028 -Palatine (RP) Duppach (DU) 45-49 20 1.5 1.3 20 9.1 4.86 0.856 0.804 1 -0.039

Additional host samples For the two newly analysed M. myotis maternity colonies (Satigny, St- Ursanne), wing tissue punches from 20 bats were obtained with a sterile biopsy punch of the wing membrane Ø 2 mm (Worthington-Wilmer and Barratt 1996). For these colonies samples were taken concurrently with mite samples, for the other bat maternity colonies samples were collected and analysed previously (Castella et al. 2001). Samples were preserved, extracted, and sequenced for the second hypervariable domain (HVII) of the mtDNA control region and 10 microsatellites (A13, B11, B22, C113, E24, F19, G9, H19, H29 and G30) as described in Castella et al. (2001).

Amplification Amplification of Cytochrome b (cytb) for S. myoti was performed according to the protocol described in Bruyndonckx et al. (2009a) using the primer pair C1-J-2183 and C1-J-2797mod (Simons et al. 1994). Microsatellite loci for both species were developed from an enriched genomic library of S. myoti. For S. myoti, eight microsatellite loci were established (SM7, SM11, SM13, SM17, SM18, SM19, SM51 and SM55), where for S. bechsteini only five microsatellites could be successfully amplified (SM11, SM16, SM17, SM18

68 and SM35) [GenBank: JF288840- JF288850] (van Schaik et al. 2011). Amplification protocol and multiplex configuration were as developed in van Schaik et al. (2011).

Mite mtDNA genetic analysis Haplotype diversity (H) and nucleotide diversity (π) were calculated using Arlequin 3.5 (Excoffier et al. 2005). A statistical parsimony network was computed using TCS 1.21 (Clement et al. 2000). An analysis of molecular variance, performed in Arlequin 3.5, was used to examine the genetic structure and estimate pairwise Φ-statistics among all populations. To test whether Φ-statistics were sensitive to distances between haplotypes, we performed the same analyses based only on haplotypic frequencies. Isolation by distance in mite populations was tested through the correlation between matrices of ΦST / (1- ΦST) values and log transformed geographic distance using Mantel tests (10,000 permutations) in FSTAT 2.9.3 (Goudet 2002). Geographic distances were calculated as the shortest linear distance connecting the populations.

Mite microsatellite genetic analysis For both mite species we checked for the presence of null alleles, allelic dropout, and stuttering using MicroChecker 2.2.5 (van Oosterhout et al. 2004). We also checked for deviations from Hardy-Weinberg equilibrium and linkage disequilibrium using Genepop on the web 4.0.10 (Rousset 2008). We calculated number of alleles per locus, allelic richness, observed and expected heterozygosity, FIS, and pairwise FST-values using Fstat 2.9.3 (Goudet 2002). Number of private alleles was calculated using Genalex 6 (Peakall and Smouse 2006). To assess the level of genetic differentiation of mites within and between bat colonies, single-level and hierarchical AMOVAs were performed in Arlequin 3.5 (Excoffier and Lischer 2010). Isolation by distance was measured by comparing matrices of FST / (1- FST) and log transformed geographic distance using Mantel tests (10,000 permutations) in FSTAT 2.9.3 (Goudet 2002). Sequential Bonferroni corrections were used to

69 compute the critical significance levels for simultaneous statistical tests.

Pairwise F’ST and G”ST-values were calculated using Genodive 2.0b23 (Meirmans and Van Tienderen 2004). To investigate temporal differentiation of mite populations within a colony, mites from five colonies of M. bechsteinii were sampled twice (2002 and 2007) and compared using pairwise FST-values and a Mantel test in FSTAT 2.9.3 (Goudet 2002).

Parasite and host comparison Summary statistics, diversity indices and population differentiation were calculated for both hosts from existing datasets and the two newly analysed M. myotis colonies as described above for mites. To compare parasite and host genetic distances we used a partial Mantel test (10000 permutations) correcting for geographic distance. For comparison of parasite and host mitochondrial genetic distance, we used ΦST / (1- ΦST), and nuclear genetic distance was compared using FST / (1 - FST) (Rousset 1997). A structure analysis was performed in STRUCTURE 2.3.3 (Pritchard et al. 2000) for all species using only the nucDNA microsatellites, applying an admixture model without location as a prior. For S. myoti and M. myotis, we selected a range of K from 1 to 10, and for S. bechsteini and M. bechsteinii from 1 to 15. Five iterations per K were run with a burn-in and run length of 200 000 and 1 000 000 repetitions respectively. The most probable K was inferred using the ΔK method of Evanno et al. (Evanno et al. 2005). Finally, one-tailed Spearman’s rank correlation tests were performed using R (R Development Core Team 2015) to test for a positive correlation between mite diversity indices (H, π, K,

HO, HE) and host colony size. Further supporting information can be found in the supplementary materials (Figure S3.2, Figure S3.3)

70 Results

M. myotis genetic data The additional host mitochondrial analysis revealed that all HV2 haplotypes corresponded to previously published haplotypes (Castella et al. 2000, Castella et al. 2001, Ruedi et al. 2008; Table 3.2b). As expected, M. myotis bat colonies showed high mtDNA differentiation (ΦST = 0.56, p < 0.001) and, despite being statistically significant, low nucDNA (FST = 0.015, p < 0.001) differentiation, indicating strong female philopatry and male-biased dispersal. Descriptive statistics for all colonies can be found in Table 3.2b; results are similar to those previously published by Castella et al. (2001).

S. myoti mtDNA Among the 117 S. myoti mites sequenced, 49 different cytb haplotypes were detected. The 697 aligned nucleotides consisted of 49 variables sites, of which 18 were parsimony-informative. All haplotypes were deposited in GenBank under accession numbers [KJ174107-KJ174155]. The haplotype network of S. myoti presents two star-like patterns with some haplotypes in between (Figure 3.2a). Two haplotypes were the most represented: h1 was present in 12% of individuals and h2 in 16.2%. Nine haplotypes were shared between bat colonies and 40 were private haplotypes. The number of haplotypes per population ranged from 7 to 14 (mean = 11, Table 3.2a), and nucleotide diversity from 0.536 to 0.874 (mean = 0.726; Table 3.2a). S. myoti populations showed low pairwise differentiation

(mean ΦST = 0.012; Table 3.3a), and only Satigny was significantly differentiated from two other populations (Meiringen, Agliè). A mantel test revealed no significant correlation between genetic and geographic distances (r2 = 0.02, p = 0.64). The 697 bp fragment analysed in S. myoti represents an overlap of 72% with the 513 bp fragment of cytb previously analysed for S. bechsteini (Figure 3.2b; Bruyndonckx et al. 2009b). A comparison of the most common haplotypes of each mite species showed 93% similarity between species.

71 The overall structure of the haplotype networks does differ in that S. bechsteini has far fewer haplotypes (23 vs. 49) despite a larger sample size, and does not exhibit two distinct haplotype clusters. This indicates that the pattern observed in S. myoti may be the result of admixture from the two glacial refugia of its host.

Figure 3.2 Haplotype network for a) the 49 haplotypes determined by sequencing the cytochrome b (cytb) of 119 Spinturnix myoti, and b) the 23 haplotypes for cytochrome b (cytb) for the 402 Spinturnix bechsteini included in this comparison, as previously analysed in Bruyndonkx et al. (2009b). The size of circles is proportional to the number of individuals sharing the same haplotype. For each species, the list of which haplotypes were found in each colony is given as an inset.

a) h31 h27 h14 h41 h69 h24

h43 h32 h25 h37 h2 h44 h68 h6

h39 h45 h70 h10 h13 h11 h29

h36 h7 h4 h42 Colony Name mtDNNA haplotypes h72 h1, h2, h4, h9, h10, h11, h27, h35, h36, Agliè h16 h28 h30 h43, h44, h45, h64, h65 h1, h2, h5, h6, h12, h24, h25, h29, h41, Courtételle h42, h66, h67, h70

h35 h38 Meiringen h5, h7, h8, h9, h26, h31, h42

h46 h2, h5, h12, h13, h16, h24, h34, h39, h40, Perreux h42 h5 h8 Satigny h1, h2, h32, h47, h55, h64, h68, h72

h64 h1, h2, h12, h13, h14, h17, h28, h30, h37, St-Ursanne h38, h46, h49, h50, h69 h67 h1 h55 h66 h47

h50 h9 h49 h12

r

e h34

p h26 s h40 s l 1 pe y h65 ua

<5 ot l id

<10 v ap di >10 h n i

h17

72 b) Colony Name mtDNNA haplotypes

24 48 41 BS 1, 2, 3 ES 1, 2, 4, 24, 66 12 23 GB2 1, 2, 3, 22 22 446 47 GS1 1, 2, 6, 21, 23, 42, 43, 61 21 HB 1, 2, 4, 5, 6, 44 42 IB3 1, 3 1 2 43 44 RT 3, 6, 25 28 SB 2 AL4 5 2, 41 29 26 BI 12, 28, 41 3 61 DU 2, 4, 28, 29, 46, 47, LO 1, 2, 48 6 66 OH

r 41 s <5 <10 <25 <50 individuals pe >50 haplotype

Table 3.3 Pairwise ΦST (below the diagonal) and FST-values (above the diagonal) for a) Spinturnix myoti, b) Myotis myotis c) Spinturnix bechsteini d) Myotis bechsteinii. For M. bechsteinii values below the diagonal are pairwise

FST-values of mitochondrial microsatellites. Asterisks indicate significant differentiation (p < 0.05). a) S. myoti

Mite ΦST \ Fst Agliè Courtételle Meiringen Perreux Satigny St-Ursanne Agliè - 0.014* 0.018* 0.014* 0.026* 0.016* Courtételle -0.02 - 0.004 0.013 0.004 0.002 Meiringen 0.05 0.02 - 0.01 0.015* 0.004 Perreux -0.01 -0.04 0.01 - 0.015 0.009 Satigny 0.11* 0.04 0.08* 0.05 - 0.012* St-Ursanne 0.03 -0.01 0.03 -0.01 0.02 - b) M. myotis

Host ΦST \ FST Agliè Courtételle Meiringen Perreux Satigny St-Ursanne

Agliè - 0.043* 0.057* 0.034* 0.035* 0.036* Courtételle 0.72* - 0.016 -0.001 0.009 -0.003 Meiringen 0.71* 0.04 - 0.0004 0.007 0.014 Perreux 0.70* 0.15* 0.12* - 0.006 0.003 Satigny 0.37* 0.21* 0.20* 0.18* - 0.002

St-Ursanne 0.73* 0 0.05 0.18* 0.22* -

73 c) S. bechsteini

LF RP

Mite ΦST \ Fst BS ES GB2 GS1 HB IB3 RT SB AL4 BI DU LO OH Blutsee - 0.217* 0.255* 0.202* 0.316* 0.126* 0.153* 0.351* 0.260* 0.243* 0.185* 0.275* 0.406* Einsiedeln 0.54* - 0.174* 0.084* 0.184* 0.275* 0.068* 0.221* 0.130* 0.123* 0.145* 0.177* 0.365* Guttenberg 2 0.73* 0.51* - 0.131* 0.283* 0.307* 0.116* 0.315* 0.180* 0.186* 0.186* 0.215* 0.421*

Gramschatz 1 0.22* 0.16* 0.36* - 0.159* 0.226* 0.052* 0.213* 0.133* 0.130* 0.079* 0.098* 0.312* LF Höchberg 0.88* 0.75* 0.87* 0.60* - 0.348* 0.171* 0.299* 0.228* 0.210* 0.204* 0.248* 0.422* Irtenberg 3 0.90* 0.83* 0.91* 0.69* 1.00* - 0.158* 0.372* 0.322* 0.284* 0.213* 0.301* 0.458* Reutholz 0.62* 0.33* 0.53* 0.27* 0.66* 0.53* - 0.233* 0.121* 0.149* 0.113* 0.135* 0.309* Steinbach 0.87* 0.72* 0.110 0.55* 1.00* 1.00* 0.66* - 0.250* 0.244* 0.267* 0.239* 0.475* Altrich 4 0.83* 0.61* 0.77* 0.50* 0.94* 0.96* 0.56* 0.94* - 0.214* 0.173* 0.163* 0.314* Bitburg 0.72* 0.47* 0.64* 0.40* 0.77* 0.83* 0.45* 0.78* 0.60* - 0.138* 0.181* 0.379*

Duppach 0.59* 0.29* 0.47* 0.25* 0.62* 0.70* 0.31* 0.61* 0.52* 0.41* - 0.158* 0.382* RP Longuich 0.50* 0.26* 0.25* 0.16* 0.64* 0.72* 0.34* 0.42* 0.54* 0.44* 0.29* - 0.243* Orenhofen 0.88* 0.76* 0.87* 0.62* 1.00* 1.00* 0.67* 1.00* 0.030 0.72* 0.63* 0.65* -

d) M. bechsteinii

LF RP

Host mtFST \ FST BS ES GB2 GS1 HB IB3 RT SB BI DU Blutsee - 0.023 0.004 0.005 0.008 0.008 0.011 0.006 0.072 0.016

Einsiedeln 0.333* - 0.036* 0.032* 0.044 0.032 0.03 0.036* 0.5 0.356*

Guttenberg 2 0.331* 0.245* - 0.007 0.010* 0.002 0.010* 0.006 0.448 0.445*

Gramschatz 1 0.364* -0.001 0.252* - 0.018* 0.005 0.004 0.004 0.488 0.351 LF Höchberg 0.242* 0.075 0.142* 0.087* - 0.009 0.028* 0.01 0.375 0.341*

Irtenberg 3 0.139* 0.260* 0.239* 0.259* 0.148* - 0.014 0.005 0.318 0.28

Reutholz 0.02 0.388* 0.373* 0.412* 0.304* 0.201* - 0.014 0.072 0.211

Steinbach 0.146* 0.333* 0.274* 0.320* 0.195* 0.004 0.205* - 0.333 0.312

Bitburg 0.011 0.028 0.004* 0.009* 0.017* 0.009* 0.015 0.012* - 0.013

RP Duppach 0.167* 0.042* 0.015* 0.013* 0.030* 0.022* 0.010* 0.019* 0.311* -

Mite nucDNA No linkage disequilibrium was found between loci in either mite species. All six S. myoti populations showed highly significant deviations from Hardy-

Weinberg equilibrium (p < 0.0001), as a result of heterozygote deficiency (FIS: 0.191-0.398). Similarly, S. bechsteini populations were not in Hardy- Weinberg equilibrium as a result of heterozygote deficiency (p < 0.0001), with five exceptions (ES-2007, GB2-2007, HB-2007, IB3-2002, OH). Microchecker indicated the possible presence of null alleles in all microsatellite loci for both

74 species, but found no evidence for allelic dropout or stuttering. As discussed in the original marker description (van Schaik et al. 2011), we believe these heterozygote deficiencies are not the result of null alleles for several reasons. First, all markers show similarly heterozygote deviations indicating that null alleles would have to be present in all markers across both species. Second, mite populations may exhibit substantial inbreeding, as often observed in obligate parasite species (e.g. Leo et al. 2005), as populations are often small and largely isolated. Therefore, although the possible presence of null alleles cannot be completely dismissed, we believe the markers to be biologically informative.

S. myoti nucDNA Overall genetic variation in S. myoti was very high with total number of alleles per locus ranging from 13.13 to 18.13, and allelic richness ranging from 12.74 to 16.75 (Table 3.2a). A large proportion of these alleles were specific to one bat colony, with the number of private alleles ranging from 6 in Meiringen, to 22 in Aglié (mean = 13.17, Table 3.2a). Between bat colonies, S. myoti pairwise FST-values (Table 3.3a) showed very little differentiation (0.002 – 0.026), and significant pairwise differentiation was only found between Aglié (separated from the other colonies by the alps) and all other colonies, and between Satigny and two other colonies (Meiringen and St. Ursanne).

Pairwise F’ST- and G”ST-values were slightly higher (−0.003-0.241 and 0.031-

0.264 respectively) but did not differ strongly from the pairwise FST-values (data not shown). An AMOVA analysis found the vast majority of variation within mite populations (98.9%; Table 3.4). Unlike in the mtDNA sequence, a significant, but very weak, correlation between genetic and geographic distances (β = 0.005, r2 = 0.362, p = 0.027; Table S3.4) was found, but S. myoti nuclear and mitochondrial genetic distance were nevertheless also significantly correlated (r2 = 0.26, p = 0.049).

75 Table 3.4 Analysis of molecular variance for a) Spinturnix myoti and b) Spinturnix bechsteini. For S. bechsteini a hierarchical AMOVA including region as an additional factor is shown, with the values of a non-hierarchical AMOVA given in parentheses. Asterisks indicate significant contributions.

Variance Percentage Source of variation d.f. Sum of squares components of variation Spinturnix myoti Among colonies 5 30.96 0.04 1.1* Among individuals, 111 512.39 0.96 26.0* within colonies Within individuals 117 315.5 2.69 72.9 Spinturnix bechsteini Among regions 1 40.39 0.05 2.4* Among colonies, 11 (12) 269.92 (309.64) 0.5 (0.52) 22.5* (23.3*) within regions Among individuals, 289 494.33 (518.55) 0.05 (0.08) 2.2* (3.4*) within colonies Within individuals 302 487 (496) 1.61 (1.64) 72.9 (73.3)

S. bechsteini nucDNA Overall genetic variation in S. bechsteini was lower than that of S. myoti with 2.6 to 12.0 alleles per locus (mean = 6.83), and a mean allelic richness of 5.52 (Table 3.2c). The number of private alleles was also lower (0–10, mean = 1.79). However, it is important to note that the number of S. bechsteini populations was also much higher than in S. myoti thereby increasing the chance that we had sampled rare but widespread alleles at multiple locations.

Pairwise FST-values among populations were much higher in S. bechsteini than in S. myoti (0.052-0.475, mean = 0.228; Table 3.3c) as well as those of its host (Table 3.3d), and all S. bechsteini populations were significantly differentiated from one another. Pairwise F’ST- and G”ST-values showed even more exacerbated differentiation between mite populations (0.333-0.929 and 0.334-0.93 respectively), but again closely followed the pattern seen in the pairwise FST-values (data not shown). An AMOVA revealed

76 very similar patterns as in S. myoti, with the majority of the sampled variation found within S. bechsteini populations (73.3%; Table 3.4). Nevertheless, there was also significant differentiation among mite populations (p < 0.001). Between the spatially distant regions of Lower Franconia (LF) and

Rhineland-Palatine (RP), 45% of the alleles were shared. Pairwise FST-values of S. bechsteini between bat colonies from differing regions were very similar to those between bat colonies from the same region (within LF = 0.215, within RP = 0.235, between regions = 0.236). Indeed, a hierarchical AMOVA including regions found only 2.4% of the variation between regions, with the vast majority of variation found within S. bechsteini populations (72.9%) and among bat colonies within regions (22.5%; Table 3.4). No correlation was found between geographic and genetic distance (r2 = 0.027, p = 0.39; Table S3.4).

A clear temporal genetic differentiation (FST = 0.085-0.254, mean = 0.147) in S. bechsteini was evident in all five bat colonies sampled for mites in 2002 and 2007. This level of differentiation is comparable to the average differentiation seen between all sampling events between different bat colonies within one year (0.146 and 0.238 for 2002 and 2007 respectively). Pairwise differentiation between the five colonies was not correlated between 2002 and 2007 (Spearman’s rank correlation: r = −0.360, p = 0.238), indicating no stable sub-structuring within the region. Within individual bat colonies, only 26.0-41.2% of alleles were conserved across sampling events, also indicating strong temporal turnover of the S. bechsteini populations. In all, our results for nucDNA closely mirror those of the previously analysed mtDNA (Bruyndonckx et al. 2009b). It is therefore unsurprising that a significant correlation between nuclear and mitochondrial FST-values can be seen (r2 = 0.34, p = 0.001).

Comparison with host We applied mantel test analysis to examine the correlation between the genetic distances of hosts and parasites (Table 3.5). In neither of the host- parasite pairs were any of the pairwise ΦST or FST-values significantly

77 correlated between species after correcting for geographic distance. A plot of the pairwise genetic distance (FST/1 – FST) between populations of hosts and parasites reveals that this lack of correlation is due to large variation in parasite pairwise differentiation at low levels of host genetic differentiation in both species pairs (Figure 3.3a,b). Additionally, in M. bechsteinii and S. bechsteini, no effect of geographic distance on host and parasite pairwise genetic differentiation can be observed (Figure 3.3b).

Table 3.5 Correlations (partial mantel) between host and parasite genetic differentiation corrected for geographic distance. For each pair the slope (β) and the variance explained by the model (R2) are given. No correlations were significant after correcting for distance.

S. myoti/M. myotis S. bechsteini/M. bechsteinii β R2 β R2 Mite mtDNA - Host mtDNA -2.59 0.139 -0.329 0.115 Mite mtDNA - Host nDNA -0.17 0.125 -3.33 0.025 Mite nDNA - Host mtDNA 0.003 0.022 -0.101 0.097 Mite nDNA - Host nDNA 0.343 0.013 -0.04 0.08

78 Figure 3.3 Pairwise genetic distance (FST/1 – FST) estimates between populations of hosts and parasites for a) Myotis myotis and Spinturnix myoti, and b) Myotis bechsteinii and Spinturnix bechsteini. For the latter pair, the symbols indicate whether colonies were within the same region (closed circles) or from different regions (open circles).

a) 0,030

0,025 ) t s 0,020 F (1-

/ t s

F 0,015

i

t o y

m . 0,010 S

0,005

0,000 -0,01 0,00 0,01 0,02 0,03 0,04 0,05 0,06 0,07 M. myotis F / (1-F ) st st

b) 0,7

0,6

) t s 0,5 F (1-

/ t s 0,4 F

i n i 0,3 hste c be 0,2 S. 0,1

0,0 0,00 0,01 0,02 0,03 0,04 0,05 M. bechsteinii F / (1-F ) st st

79 A STRUCTURE analysis revealed several interesting differences in both pairs of host and parasite (Figure 3.4). In S. myoti no clear sub-structuring was observed (Figure 3.4a), whereas in its host, M. myotis, the southernmost colony (Aglié) appears to cluster separately (Figure 3.4b). This is concordant with phylogeographic analyses, which have indicated that populations of M. myotis south of the Alps originate from a different glacial refugium (Ruedi et al. 2008), although this barrier is evidently not present for its mites. In M. bechsteinii and S. bechsteini clear sub-structuring according to host colony can be observed in the parasite (Figure 3.4c), while host colonies show no evidence for population sub-structuring (Figure 3.4d) as is expected with an outbreeding mating system such as swarming (Kerth et al. 2003b). Finally, since host colony size between species appears to have a large effect on the population genetic structure of its parasites, we used Spearman’s rank correlation tests to investigate whether variation in host colony size within each host was correlated with parasite diversity indices (Table 3.6). Host colony size was not significant correlated with any of the parasite genetic indices after Bonferroni correction, although there was a positive trend between parasite allelic richness and host colony size in both species pairs.

Table 3.6 Spearman rank correlations between host colony size and parasite genetic parameters. For each pair the correlation coefficient (ρ) and the P- value are given. No correlations were significant after Bonferroni correction (p < 0.01).

M. myotis M. bechsteini Parasite trait ρ p ρ p Number of haplotypes 0.75 0.09 0.28 0.26 Nucleotide diversity -0.26 0.61 0.29 0.24 Expected heterozygosity 0.64 0.17 0.49 0.12 Observed heterozygosity 0.41 0.43 0.16 0.64 Allelic richness 0.90 0.015 0.45 0.06

80 Figure 3.4 STRUCTURE results for a) Spinturnix myoti, b) Myotis myotis c) Spinturnix bechsteini d) Myotis bechsteinii. Colony names correspond to the abbreviations given in Tab. 2. Results are shown for the number of subpopulations with the best ΔK and highest log likelihood (S. bechsteini K = 7, M. myotis K =3). In S. myoti and M. bechsteinii no discernable population sub-structuring was found, with strongest support being found for K = 1. For these species K = 2 is shown to illustrate the lack of structuring when multiple subpopulations are assumed.

a) S. myoti (K=2)

Agl Cou Mei Per Sat StU b) M. myotis (K=3)

Agl Cou Mei Per Sat StU c) S. bechsteini (K=7)

BS ES GB2 GS1 HB IB3 RT SB BI DU d) M. bechsteinii (K=2)

BS ES GB2 GS1 HB IB3 RT SB BI DU

81 Discussion

The population genetic structure of parasite populations is strongly influenced by both its own life history as well as the life history and social system of its host. Here, we compared the population genetic structure of both host and parasite in two closely related systems where parasite life histories are nearly identical, but hosts differ substantially in social system. We find that the population genetic structure of the two mite species differs strongly as a result of the social system of their hosts, which is in agreement with our predictions based on the differences in social system of their hosts.

Parasite population genetic structure In S. myoti, overall mtDNA haplotype diversity (49 haplotypes in 120 individuals) and nuclear genetic diversity were high (mean 16.69 alleles per locus in only 20 individuals per colony). This diversity is higher than that seen in its host, M. myotis, and may be the result of admixture between parasites originating from several glacial refugia or species, coupled with sufficiently large host maternity colony size to prevent strong bottlenecks in the mites. Between M. myotis colonies, we found very low genetic differentiation and no evidence for population substructuring in the mites. Indeed the vast majority of genetic diversity of S. myoti occurred within bat maternity colonies suggesting a large amount of parasite exchange between hosts originating from different maternity colonies outside of the maternity period, resulting in a highly diverse and panmictic population. These results are concordant with the observation of other empirical studies on host-parasite co-variation (e.g. McCoy et al. 2005), that have found levels of parasite gene flow much higher than originally predicted (Price 1977). Notably, the extensive mixing of parasites outside of the breeding period has also been found in ectoparasitic lice of birds, where the genetic structure of parasites was largely shaped by the dispersal of lice at communal wintering sites (Gómez-Díaz et al. 2007). The population genetic structure of S. bechsteini contrasted sharply with that of S. myoti. Overall nuclear genetic diversity was lower, but still

82 higher than that of its host, M. bechsteinii. All S. bechsteini populations were significantly differentiated from one another, and it was possible to assign mites to subpopulations according to their host colony of origin. This is likely to be due to strong genetic drift within host colonies as a result of their small maternity colony size as well as their tendency to hibernate without body contact with conspecifics. Both factors combine to drastically limit the number mites present within a host colony when the colonies reform in spring. Nevertheless, S. bechsteini populations within colonies were temporally unstable (between sampling years mean FST = 0.147 for nucDNA) suggesting that gene flow between colonies is still substantial. In agreement with this finding, Bruyndonckx et al. (2009b) observed a large turnover in haplotypes between sampling years. Despite this strong differentiation among colonies and years at a local scale, differentiation of S. bechsteini between colonies from spatially distinct regions was not higher than within regions, suggesting that overall genetic diversity of the S. bechsteini population at a regional level is stable. A comparable pattern of strong population genetic substructure and high levels of genetic drift is also seen in the parasites of other host taxa with similarly closed societies as in Bechstein’s bats, e.g. in the ectoparasitic chewing lice of pocket gophers (rev. in Hafner et al. 2003).

Relationship between parasite and host population structure No correlation was found between host and parasite genetic differentiation in either of the species. Additionally, within each of the two host species, colony size did not significantly correlate with any of the parasite genetic indices, although a trend of increasing allelic richness with increased colony size was present in both species pairs.

Influence of host social system Our results indicate that differences between hosts in colony size, mating system, and in particular the degree of social interaction outside of the summer maternity roosts have a large effect on parasite genetic structure. M.

83 bechsteinii has a remarkably closed social system, with very strong natal philopatry and vastly limited social interaction outside of the summer maternity season (Kerth et al. 2000, Kerth and van Schaik 2012). Previously, it has also been shown that M. bechsteinii actively reduces the intensity of another ectoparasite species that deposits its larval stages in the roosts via roost-switching behaviour (bat flies; Reckardt and Kerth 2007). It thus seems possible that the much more closed social system of M. bechsteinii, as compared to M. myotis, has also evolved to restrict the infestation of other parasites, such as wing mites, that depend on body contact between hosts. In M. myotis, our data provide no evidence for such anti-parasite behaviour. While this may be because there is an insufficient number of alternative roosts to increase population subdivision into smaller colonies, social interaction during other periods such as mating and hibernation is also extensive, thereby further permitting parasite exchange. Several other factors probably have also influenced the genetic structure of both mite species, but these factors do not detract from the influence of host social structure. For example, the phylogeographic history of both mite species is quite different, and may explain the differences in the number of haplotypes and nucleotide diversity found in the mtDNA sequences (compare Figure 3.2a and Figure 3.2b), and likely also the diversity found in the nucDNA microsatellites. Nevertheless, these macrogeographic differences between the two mite species cannot explain the differences seen in population genetic structure on a microgeographic scale. For example, almost all M. bechsteinii colonies harboured S. bechsteini populations that were monotypic or had only two haplotypes as a result of the strong winter bottleneck. This contrasts sharply with the sampled populations of S. myoti, in which we found between seven and fourteen haplotypes in only twenty samples per populations. Thus, although the history of both species has certainly influenced the overall nucleotide and genetic diversity observed, the differences in genetic structure observed on a population level are still primarily the result of differences in host social system. Another major difference between the two mite species is the

84 potential use of secondary host, with identical social system, in S. myoti. Here too, the social systems of the hosts play a role, as the closed social system of M. bechsteinii minimizes contact between conspecifics and virtually eliminates contact with other species. Therefore, while the possible use of additional hosts in S. myoti may increase its effective population size and potentially also increase its dispersal opportunities, these factors can also be (indirectly) attributed to the differing social systems of the hosts.

Consequences for parasite evolutionary potential The observed differences in population genetic structure of the two mite species should strongly influence their evolutionary potential. In S. bechsteini, the influence of genetic drift strongly limits the likelihood that any local adaptation to its host maternity colony is able to persist and spread. S. myoti, in contrast, has a much more stable population genetic structure as well as a higher rate of gene flow relative to its host, and may therefore be able to locally adapt to its major host, M. myotis. The observed difference in population genetic structure between the mites analysed here also have broader consequences for general investigations of parasites in relation to host social system. For example, they suggest that parasite species with very similar life histories may have vastly different evolutionary potentials depending on not only the life history but also the social system of their hosts. As a result, we conclude that host social system can be effective beyond reducing the overall chance of parasite infection, by potentially also playing a role in limiting the evolutionary potential of, often unavoidable, parasites. Therefore, comparative and theoretical studies of host-parasite interactions that investigate the role of host population size and community modularity (e.g. Caillaud et al. 2013) will be critical not only in understanding parasite transmission, but also in investigating the evolutionary potential of established parasite species.

85 Conclusions In conclusion, our results suggest that host social system can strongly influence parasite population genetic structure. Most notably, host maternity colony size appears to strongly affect the genetic drift experienced by the different parasite species and the social organization of the host outside of the maternity period affects the opportunities for parasite exchange between individuals from remote maternity colonies. We conclude that such differences in host social system have consequences for both the direct costs of parasites as well as the general threat of disease transmission. Therefore, the concurrent genetic analysis of host and parasite allows for inferences about the movements and social contacts of host species, as well as broader conclusions regarding host-parasite dynamics.

Data availability The haplotype sequences for S. myoti have been deposited in GenBank under ascension numbers [KJ174107-KJ174155].

Acknowledgements We would like to thank Michel Blanc, Pascal Roduit, Julien Oppliger, Peter Zingg, Elena Patriarca, Paolo Debernardi, Karsten Reckardt, Isabelle Henry, Markus Melber, Daniela Fleischmann, Manfred Weishaar, and many others for their help during collection of mites. We are grateful to Thomas Broquet, who provided useful comments on the analyses and interpretations, and to Nathalie Tzaud, Sébastien Nusslé, Nelly DiMarco, Philippe Busso and Jari Garbely for laboratory facilities. Funding was provided by grant 31003A_138187 from the Swiss National Science Foundation and by la Fondation Herbette to PC, as well as the Julius Klaus Foundation and the German Science Foundation (DFG KE 746/3-1 and KE 746/4-1) to GK. JvS is funded by the Volkswagen Foundation, and the International Max Planck Research School for Organismal Biology.

86 Supplementary materials

Table S3.1 Overview of the markers were used in this study and where a complete description of their amplification conditions can be found.

Primers/markers Data originally Species Markers used described in published in S. myoti mtDNA cytB (697bp) Simons et al., 1994 this study nucDNA SM7, SM11, SM13, SM17, SM18, SM19, SM51, SM55 van Schaik et al., 2011 this study M. myotis mtDNA HV-2 (307bp) Castella et al., 2001 Castella et al., 2001* nucDNA A13, B11, B22, C113, E24, F19, G9, H19, H29, G30 Castella & Ruedi 2000 Castella et al., 2001* S. bechsteini mtDNA cytB (513bp) Bruyndonckx et al., 2009 Bruyndonckx et al., 2009 nucDNA SM11, SM16, SM17, SM18, SM35 van Schaik et al., 2011 this study M. bechsteinii mtDNA mtMicrosatellites (AT1, AT2) Kerth et al., 2000 Kerth et al., 2000 nucDNA B15, B22, B23, G30, P5, P8, P20, paur3 Kerth et al., 2002 Kerth et al., 2003 * = plus two new colonies in this study

Figure S3.2 (next page) The program Structure was used to evaluate population sub-structuring for each species. Below are the a) Log-likelihood values for all tested K’s for each species, as well as b) the concordant DeltaK values (as described in Evanno et al., 2005) used to determine the most likely number of sub-populations.

87 a) Likelihood of all K values run (calculated in Structure Harvester):

S. myoti M. myotis

S. bechsteini M. bechsteinii

b) DeltaK values for all species (calculated using Structure Harvester):

S. myoti M. myotis

S. bechsteini M. bechsteinii

88 Figure S3.3 As can be seen in the graphs for S. bechsteini both K=2 and K=7 resulted in high DeltaK values, and K=10 (the actual number of populations sampled) resulted in the highest overall Log-likelihood. Below, outputs for K=2 and K=10 are provided (K=7 can be found in Figure 3.4).

S. bechsteini (K=2)

BS ES GB2 GS1 HB IB3 RT SB BI DU

S. bechsteini (K=10)

BS ES GB2 GS1 HB IB3 RT SB BI DU

Figure S3.4 Statistical correlations and graphs correlating nuclear genetic distance and geographic distance (using FST / (1- FST) and Ln(distance)). For both S. myoti and M. myotis genetic distance is significantly (positively) correlated with geographic distance. No such relationship is found in S. bechsteini or M. bechsteinii, nor is it found when only samples within LF are analysed.

β R2 S. myoti 0.005 0.362* M. myotis 0.015 0.342* S. bechsteini -0.012 0.027 M. bechsteinii 0.001 0.026

89 S. myoti M. myotis

S. bechsteini M. bechsteinii

S. bechsteini (without RP) M. bechsteinii (without RP)

90 91 Chapter 4

Host and parasite life history interplay to yield divergent population genetic structures in two ectoparasites living on the same bat species

J. van Schaik, D. Dekeukeleire, G. Kerth

Molecular Ecology, 24:10, 2015

Myotis bechsteinii at a swarming site, © René Janssen

92

93 Abstract

Host-parasite interactions are ubiquitous in nature. However, how parasite population genetic structure is shaped by the interaction between host and parasite life history remains understudied. Studies comparing multiple parasites infecting a single host can be used to investigate how different parasite life history traits interplay with host behaviour and life history. In this study, we used 10 newly developed microsatellite loci to investigate the genetic structure of the parasitic bat fly (Basilia nana). Its host, the Bechstein’s bat (Myotis bechsteinii), has a social system and roosting behaviour that restrict opportunities for parasite transmission. We compared fly genetic structure to that of the host and another parasite, the wing-mite, Spinturnix bechsteini. We found little spatial or temporal genetic structure in B. nana, suggesting a large, stable population with frequent genetic exchange between fly populations from different bat colonies. This contrasts sharply with the genetic structure of the wing-mite, which is highly sub- structured between the same bat colonies as well as temporally unstable. Our results suggest that although host and parasite life history interact to yield similar transmission patterns in both parasite species, the level of gene flow and eventual spatio-temporal genetic stability is differentially affected. This can be explained by the differences in generation time and winter survival between the flies and wing-mites. Our study thus exemplifies that the population genetic structure of parasites on a single host can vary strongly as a result of how their individual life history characteristics interact with host behaviour and life history traits.

94 Introduction

In host-parasite interactions, initial infection risk, subsequent transmission, and ultimately parasite population genetic structure are determined by how host and parasite life histories interact (Nadler 1995, Barrett et al. 2008). As a result, different parasites can respond contrastingly to the same life history characteristics or behavioural adaptations of a host (Côté and Poulin 1995). For example, host behaviours such as allogrooming may reduce infection intensity of certain ectoparasites while increasing the transmission of other directly transmitted parasites, such as nematodes (MacIntosh et al. 2012). Elucidating how differing life history factors interact is important for understanding host-parasite dynamics at both the local (population genetic structure) and broad (coevolutionary patterns) scales (Criscione 2008), as well as their effect on disease risk and spread (Cross et al. 2005, Nunn 2012). In one of the most detailed investigations of parasite genetic structure at a local scale, McCoy and colleagues (2003) found genetic differentiation in a tick within host (bird) breeding cliffs, principally influenced by the spatial organization of hosts as well as cliff topography. In the same system, local adaptation of ticks was found between breeding cliffs located between 50 and 800 meters from one another (McCoy et al. 2002), demonstrating that genetic differentiation found on such small spatial scales can indeed influence host-parasite coadaptation. In another study of seabirds and their parasites, three specialized louse species of three shearwater (sub-)species showed no genetic differentiation across hosts, while a generalist flea species showed strong differentiation across the same host (sub-)species (Gómez-Díaz et al. 2007). These differences can be attributed to the fact that lice remain on the host year-round thereby facilitating horizontal transmission at communal wintering grounds of the host, whereas fleas only infect hosts during the nesting phase and therefore horizontal transmission is restricted to host nests in the immediate vicinity (Gómez-Díaz et al. 2007). Unfortunately, such investigations of parasite population genetic structure are rare, especially for parasites of hosts with social and/or behavioural anti-parasite

95 adaptations. Thus how differences in parasite life history interact with host life history and social system to shape parasite population genetic structure within host meta-populations remains understudied. The Bechstein’s bat (Myotis bechsteinii) provides an interesting model to investigate how host and parasite life history interact to shape parasite local genetic structure. During the summer, this forest-living bat forms all- female maternity colonies in tree cavities and bat boxes comprised of 10 to 50 adults and their dependent offspring (Kerth et al. 2002a). Female bats are highly philopatric, and immigration into these colonies is extremely rare (Kerth et al. 2002b). Male bats roost solitarily throughout the summer, also switching roosts less frequently, but may occasionally utilize roosts that have been previously occupied by female colonies (Kerth and Morf 2004). During late summer and autumn both sexes meet at underground sites, that are located within approximately 50 km of the summer habitat, in a lek-like mating system known as swarming (Kerth et al. 2003b). During winter, Bechstein’s bats hibernate, often singly, in deep crevices within these underground sites (Baagøe 2001). As expected in such highly philopatric female societies with outbreeding males, there is strong mitochondrial differentiation (Kerth et al. 2000), but very little nuclear genetic structure across colonies (Kerth et al. 2002a, Kerth et al. 2003b). In addition to their closed societies, Bechstein’s bats show behavioural adaptations aimed at reducing parasite pressure (Kerth and van Schaik 2012). Most notably, Bechstein’s bats use frequent roost switching behaviour and prefer novel roost sites (Reckardt and Kerth 2006, 2007) to avoid the offspring of parasites that must temporarily leave the host to reproduce. Female maternity colonies switch day-roost (bat boxes and tree cavities) every 2-3 days on average, using up to 50 different day-roosts throughout the summer (Reckardt and Kerth 2007). Additionally, maternity colonies do not overlap in roost home-range with one another (Kerth et al. 2000). Moreover, individual bats groom themselves extensively, and allogrooming within maternity colonies is common (Kerth et al. 2003a). Taken together, the small colony size, severely limited inter-colony bat contact, and

96 behavioural adaptations strongly reduce the opportunities for the horizontal transmission (defined here as the transmission of parasites from members of one maternity colony to members of another colony or to solitary males) of directly transmitted parasites (van Schaik et al. 2014). Despite these adaptations, the Bechstein’s bat is commonly parasitized by two ectoparasites: the bat fly (Basilia nana) and the wing-mite (Spinturnix bechsteini). Both are highly specialized obligate ectoparasites primarily infecting the Bechstein’s bat. Bat flies (Diptera: Nycteribiidae) are wingless, obligatory, hematophagous ectoparasites that inhabit the pelage of bats (Dick and Patterson 2006, 2007). The bat fly, B. nana, cannot disperse independently from its primary host, the Bechstein’s bat, and female flies only briefly leave their host approximately every 5-10 days to deposit a single terminal (3rd- instar) larva on the wall of the roost (Reckardt and Kerth 2006). These larvae immediately develop into a puparium, and can emerge as fully developed imagoes in ca. 3 weeks (Dick and Patterson 2007). Developed imagoes wait inside the puparia and only emerge in the presence of a potential host (Reckardt and Kerth 2006). Due to the frequent roost switching observed in the host, only 30% of bat fly B. nana puparia deposited in day-roosts eventually emerge in the presence of a host (Reckardt and Kerth 2006). Despite this temporary decoupling with the host, B. nana is remarkably specific to Bechstein’s bats and is only sporadically found on other bat species that roost in the same tree cavities, such as Natterer’s bat (Myotis nattereri) and brown long-eared bat (Plecotus auritus) in our study area. Critically, male Bechstein’s bats are also frequently infected by B. nana, and may act as vectors for horizontal transmission by consecutively occupying roosts also used by female Bechstein’s bat maternity colonies (Kerth and Morf 2004, Schöner et al. 2010). Previous studies have shown that there are at least two fly generations per year, the first coming directly after bats return from hibernation and a second in late summer (Reckardt and Kerth 2006). Bat fly puparia do not survive frost, and thus do not survive the winter in the

97 bat boxes (Reckardt and Kerth 2006); instead they survive the winter as imagoes on the host. Whether bat flies impose significant direct fitness costs on their hosts is largely unknown, but costs are generally considered minor (Zahn and Rupp 2004, Dick and Patterson 2006). However, bat flies can serve as vectors for more costly endoparasites, including Haemosporidia and Bartonella (Megali et al. 2011, Billeter et al. 2012). Regardless of the exact cost of infection, Bechstein’s bats employ several behaviours that limit B. nana transmission and infection intensity (Reckardt and Kerth 2007), suggesting that infection may be costly in some way. It is currently unknown to what extent these behaviours also affect fly population genetic structure, and thus fly evolutionary potential. In several previous analyses, the effects of host life history and social system on parasite local genetic structure of another common ectoparasite of the Bechstein’s bat, the wing-mite Spinturnix bechsteini, have been investigated (Bruyndonckx et al. 2009b, van Schaik et al. 2014). S. bechsteini is highly host-specific, lives exclusively on the wing membranes and cannot survive off of the host (Giorgi et al. 2004). Thus, unlike bat flies, wing-mites are not affected by the roost-switching behaviour of their host. Wing-mites reproduce sexually and are oviviparous, with female mites giving birth to single adult-like protonymphs which rapidly develop into adults (Rudnick 1960). While able to disperse freely within bat maternity colonies, transmission of wing-mites between colonies only occurs during bat mating and hibernation periods (Bruyndonckx et al. 2009b). Male Bechstein’s bats are only very rarely infected with wing-mites during summer (Reckardt and Kerth 2009), presumably as they are groomed away. Wing-mites reproduce faster than flies, and thus infection intensity within bat maternity colonies in early autumn is much higher than that of flies (mean intensity per bat 3.61 and 0.56 respectively; Reckardt and Kerth 2009). Wing-mite populations subsequently decrease sharply during late autumn and throughout hibernation (Lourenço and Palmeirim 2008). Using mtDNA sequence data (Bruyndonckx et al. 2009b) and nDNA microsatellites (van Schaik et al. 2014),

98 S. bechsteini was found to have high genetic differentiation between bat colonies and a high temporal turnover within bat colonies, suggesting frequent local extinction and re-colonisation. Here we use 10 newly developed microsatellite loci to investigate the population genetic structure of the ectoparasitic bat fly B. nana on a local scale. Subsequently, we compare the population genetic structure of B. nana with that of the previously investigated wing-mite S. bechsteini in the same area, to investigate how differences in parasite life history interplay with host social system and life history to shape population genetic structure. We predict that fly genetic structure will be weaker than that of the previously investigated wing-mite as a result of their longer generation time and higher winter survival (parasite life history traits), as well as their increased persistence and opportunity for horizontal transmission via male bats (host life history). For the same reasons, we hypothesize that although roost- switching, allogrooming and limited inter-colony contact reduce fly infection intensity, they do not cause strong temporal instability in population genetic structure, as seen in S. bechsteini.

99 Methods

Study area and sampling Flies were collected from 9 Bechstein’s bat maternity colonies living in forests in the vicinity of Würzburg, Germany (Figure 4.1). All bat colonies make regular use of bat boxes, and have been consistently monitored for up to 20 years (Kerth and van Schaik 2012). Imagoes of flies were collected from bats caught from their roosts in August and September. Additionally, fresh fly puparia were collected from bat boxes for which constant monitoring could show that Bechstein’s bats (and no other bat species) had recently occupied the box (colonies BS, GB2, HB). All colonies additionally make use of natural tree roosts to varying degrees, and overall roost switching is comparable across roost types (Kerth and Melber 2009). No puparia could be collected from these locations. Flies were removed from the bat’s fur using soft forceps and stored in 90% ethanol prior to DNA extraction. All imago flies were morphologically identified prior to genetic analysis (Theodor 1967, Hutson 1984). Genomic DNA was isolated from individual flies using a salting-out method (Miller et al. 1988). The abdomen of visibly gravid female flies was removed prior to extraction, in order to avoid co-amplification of the embryo’s DNA during the subsequent PCRs.

Microsatellite development Genomic DNA was sent to GenoScreen (Lille, France; www.genoscreen.fr) for the creation of a microsatellite library using high-throughput sequencing. This yielded 416 potential microsatellite sequences; of which unlabelled primer pairs were developed for 65 and initially tested for amplification and polymorphism using pooled DNA from 8 individuals. All primer pairs were tested with a range of 6 different annealing temperatures (54°C-64°C; Veriti Thermal Cycler, Applied Biosystems). Each 10 µl PCR reaction contained 1 µl of DNA template (10 ng), 5 µl of 2x QIAGEN Multiplex Master-Mix (Qiagen), 1 µl of 10 µM primer mix and 3 µl of distilled water. PCR products were assessed on a 2% agarose gel using GelRed (Biotium Inc.), and 40 primer pairs were subsequently ordered with an M13 - universal tail on the forward

100 Figure 4.1 Map showing the sampled bat colonies (circles), forest patches (light grey), the river Main (dark grey) and the city of Würzburg (Bavaria, Germany). All colony names correspond to the abbreviations given in Table 4.2.

primer (as in Schuelke 2000). PCR was preformed as before, but with a second round of 10 amplification cycles with an annealing temperature of 53°C in the presence of the universal M13-fluorescent (FAM) primer. This returned 16 primer pairs that yielded at least 3 alleles using the pooled DNA

101 sample, which were subsequently ordered with individual fluorescent labels. To assess these loci for Hardy-Weinberg equilibrium and linkage, 50 individuals from the bat colonies BW and ES were genotyped. Analysis performed in Genepop on the web 4.0.10 (Rousset 2008) found significant deviations from Hardy-Weinberg equilibrium in 3 loci, as well as evidence for linkage in 3 further loci, and thus these 6 loci were discarded. Therefore, we established 10 polymorphic microsatellite loci in 3 multiplexes (Table 4.1), which were used to genotype all individuals.

Microsatellite amplification PCR amplification was performed using 3,5 µl reactions containing 2 µl 2x QIAGEN Multiplex Master-Mix (Qiagen), 0.5 µl of 10 µM primer mix, 0.5 µl of distilled water, and an evaporated DNA template. Each PCR was composed of an initial denaturation at 95°C for 15 min; followed by 34 amplification cycles (95°C for 60 s, 60°C for 60 s, and 72°C for 60 s), followed by a final elongation of 72° C for 7 min. One µl of PCR product was added to 9 μL Hi- Di formamide and 0.07 μL GS-500 LIZ size-standard (Applied Biosystems) and resolved in POP4 polymer in an ABI 3130 Genetic Analyser (Applied Biosystems). Data was analysed using GENEMAPPER version 4.1.

Data analysis In total, 332 flies from 9 bat maternity colonies and 16 sampling events (spaced within and between years) were genotyped for all microsatellite loci (Table 4.2). All loci were checked for the presence of null alleles, allelic dropout, and stuttering using MicroChecker 2.2.5 (van Oosterhout et al. 2004). All sampling events were checked for deviations from Hardy-Weinberg equilibrium and linkage disequilibrium using Genepop on the web 4.0.10 (Rousset 2008).

102 Table 4.1 Characterization of the newly developed microsatellite loci for Basilia nana. The following abbreviations are used: annealing temperature

(Ta), the multiplex mix in which each marker was included (Primer Mix) and which fluorescent label was used (Label), the observed fragment length range (Size range), the number of alleles observed (No. alleles), observed and

expected heterozygosity (Ho and He) and both primer sequences (F = forward, R = reverse). All sequences have been deposited in the GenBank under the accession numbers provided.

Repeat Primer Mix; Size range No. of GenBank Locus T H H Primer Sequences (5'-3') motif a Label (bp) alleles o e Accession no.

BN1 (CT)8 60 B; FAM 80-102 8 0.518 0.521 KP974822 F: TGCCTAACACAAGGGGCTTA R: GCAATTACATTAATGGCCTGA

BN6 (TC)7 60 A; HEX 103-121 9 0.541 0.591 KP974823 F: TTTCATACATCACAAAGCATCAA R: ACTGATTGGAATGCTGGAGG

BN21 (AC)9 60 A; NED 120-136 9 0.618 0.614 KP974824 F: TCTGCCCTTTGCGTAGTTAG R: TCATTTGTCATTCATCGTTGTG

BN25 (AC)7 60 B; FAM 134-166 12 0.502 0.558 KP974825 F: AACTTAGCTGGCTGCTGCTC R: GCCGATGCTGGTATTTGTTT

BN32 (TTG)11 60 B; HEX 63-117 17 0.696 0.733 KP974826 F: GGCCGCTTGCTTATTTACTC R: ACGACACGAATAGCAACACG

BN42 (TGT)7 60 B; HEX 126-156 11 0.566 0.594 KP974827 F: TGGATGTGTTGTTGTGGTTG R: CACGAAAATCAGTTCCCGTT

BN55 (TTG)8 60 A; FAM 132-159 9 0.532 0.539 KP974828 F: TCAGCATCATGCAACTGTGA R: CAACAGCATTTCAGCGAGTC

BN56 (TGT)6 60 C; HEX 149-155 3 0.248 0.238 KP974829 F: TGCTATGGTTACCACAATTTCG R: ACTCGGCTTGCTTGTGATCT

BN64 (ACA)10 60 C; FAM 159-231 14 0.603 0.717 KP974830 F: CCAGCAACACGTTAAGCAGA R: GCTGTCGGCCATCATTTATT

BN65 (GTT)9 60 A; FAM 206-233 9 0.459 0.497 KP974831 F: CGGATTCCGTTGTATTGCTT R: CTAGCGTTCATCCGACACAA

Subsequently, in order to increase the number of colonies that could be compared, as well as the intra-colony sample size, for the analysis of spatial genetic structure, samples from 2002 and 2003 were pooled. A hierarchical AMOVA comparing genetic variation between colonies and between years for the two pooled years found only 0.006% of variance to be between 2002 and 2003 (supplementary materials, Table S4.1). All tests and comparisons were

103 also carried out using separate datasets for each year, but did not yield different results (data not shown). Number of alleles per locus, allelic richness, observed and expected heterozygosity, FIS, and single-level AMOVAs were calculated using Genodive

2.0b25 (Meirmans and Van Tienderen 2004). Pairwise FST-values, as well as the standardized measure G’ST (Hedrick 2005), were also calculated using Genodive 2.0b25 (Meirmans and Van Tienderen 2004). The number of private alleles per sampling event was calculated using Genalex 6 (Peakall and Smouse 2006). Isolation by distance (IbD) was measured by comparing matrices of FST / (1- FST) and log transformed geographic distance using Mantel tests (10,000 permutations) in Genodive 2.0b25 (Meirmans and Van Tienderen 2004). Additionally, fly genetic distance was compared to a matrix of forest fragment ID (using the same method) to investigate the influence of proximity within forest patches rather than geographic distance, to investigate the possible transmission of flies between female Bechstein’s bat maternity colonies via male Bechstein’s bats or other bat species throughout the summer. Sequential Bonferroni corrections were used to compute the critical significance levels for related statistical tests. Temporal differentiation within a single bat maternity colony was investigated in three colonies for which a sufficient sample was collected in

2002/3 and 2011 using pairwise FST-values and hierarchical AMOVAs calculated in Genodive 2.0b25 (Meirmans and Van Tienderen 2004). A similar analysis was carried out comparing the samples from 2002 and 2003 for the four bat colonies for which both years were sampled (BS, BW, ES, SD). In order to assess the influence of our destructive fly sampling on the temporal differentiation found within colonies, we performed a Kendall’s rank correlation between the number of flies sampled in the previous sample(s) and the temporal FST-values. We found no effect of destructive sampling in both 2003 (Kendall’s T < 0.001; p = 0.997) and 2011 (Kendall’s T = 0.280; p = 0.249).

104 Table 4.2 Overview of host colony information and basic genetic descriptors of all fly samples used in this study. The following abbreviations are used: bat colony latitude (Lat) and longitude (Long), estimated number of bats in the colony (colony size), number of flies genotyped (n), mean number of microsatellite alleles per locus (NA), allelic richness (K), observed (Ho) and expected (He) heterozygosities, number of private alleles per colony (Pall), and inbreeding coefficient (Fis).

Colony Name Year Lat Long Colony size n NA K Ho He Pall Fis Blutsee (BS) 2002 49.725 9.833 15-19 12 4.9 3.639 0.543 0.567 0 0.034 2003 13 2011 13 4 3.507 0.459 0.486 3 0.06 Brandtwiese (BW) 2002 49.898 9.995 20-24 17 5.5 3.617 0.517 0.558 0 0.062 2003 38 2011 16 4 3.497 0.524 0.547 2 0.024 Einsiedel (ES) 2002 49.902 9.945 20-24 24 5.8 3.564 0.529 0.551 1 0.021 2003 27 Guttenberg 2 (GB2) 2003 49.745 9.865 35-39 14 4.3 3.696 0.55 0.548 2 -0.005 2011 42 5.1 3.639 0.571 0.577 2 -0.003 Gramschatz 1(GS1) 2002 49.903 9.978 40-44 12 3.9 3.576 0.455 0.523 0 0.105 Gramschatz 2 (GS2) 2002 49.947 9.94 20-24 12 4.5 3.998 0.65 0.58 4 -0.122 Höchberg (HB) 2002 49.785 9.867 20-24 36 5.4 3.709 0.529 0.582 2 0.099 Steinbach (SB) 2002 49.704 9.745 20-24 9 3 2.931 0.461 0.434 0 -0.074 Stalldorf (SD) 2002 49.571 9.912 25-29 26 5.3 3.710 0.546 0.576 2 0.046

2003 21

Comparison with host and wing-mite population genetic structure Existing genetic datasets are available for both the host, Myotis bechsteinii (microsatellites, both nuclear and mitochondrial: Kerth et al. 2002b; Kerth and van Schaik 2012), and for the ectoparasitic wing-mite, Spinturnix bechsteini (nuclear microsatellites: van Schaik et al. 2014; and mtDNA cytb sequences: Bruyndonckx et al. 2009b). For both species (host and wing-mite), the datasets were adapted to match the colonies sampled for B. nana and summary statistics and pairwise population differentiation were calculated as described above.

105 To compare fly, host and wing-mite genetic distances we used a partial Mantel test (10000 permutations) correcting for geographic distance.

Matrices of FST / (1 - FST) were used to compare the nuclear genetic distance of all species, as well as the mitochondrial (microsatellite) genetic distance in the host. For comparison to wing-mite mitochondrial genetic distance, we used ΦST / (1- ΦST). A structure analysis comparing nuclear population genetic structure was performed in structure 2.3.3 (Pritchard et al. 2000) for all colonies for which data are available for all three species. For each species we used an admixture model without providing location as a prior for a range of potential subpopulations (K) from 1 to 10 (number of sampled colonies included: 6). Five iterations were run for each K with a burn-in and run length of 200000 and 1000000 repetitions respectively, and the most probable K was inferred using the ΔK “Evanno method” (Evanno et al. 2005) using Structure Harvester Web v0.6.93 (Earl and vonHoldt 2011). Additionally, data were analysed using geneland 3.2.4 (Guillot et al. 2005), which has been shown to be more robust with low sample sizes (Frantz et al. 2012). To determine the number of subpopulations, 10 independent runs (1000000 MCMC iterations, thinning of 1000, uncertainty of spatial coordinates of 100m) were preformed where K was allowed to vary between 1 and 10.

106 Results

A Microchecker analysis did not find evidence for the presence of null alleles, allelic dropout or stuttering when analysing over all populations within a year. No linkage disequilibrium was found between loci. We found between 3 and 17 alleles per locus (mean = 10.1; Table 4.1). Of the nine sampled B. nana populations, two showed highly significant deviations from Hardy-Weinberg equilibrium due to heterozygote deficiency (p < 0.0001; BW and SD), with highly significant deviations in two (BN25, BN64) and five (BN6, BN25, BN37, BN42, BN65) markers respectively. Additionally, two other populations were found to have marginally significant heterozygote deficiencies (p<0.05; ES and HB), stemming primarily from significant deviations in one (BN64) and two (BN6, BN64) markers respectively. In other B. nana populations, single markers showed deviations from Hardy-Weinberg in six cases. We believe that these deficiencies are primarily the result of sampling of related individuals (including puparia) within bat colonies (see also Dharmarajan et al. 2011). Overall genetic diversity was low with a mean of 4.64 alleles per locus per population and a mean allelic richness of 3.59 (Table 4.2). We found a total of 18 private alleles evenly distributed across colonies (range: 0-4, mean = 1.5; Table 4.2).

Spatial genetic structure

Pairwise FST-values of flies among bat colonies showed very little population differentiation (range: -0.005 - 0.063, mean = 0.010; Table 4.3), with only flies from BS being significantly differentiated from flies of two other bat colonies

(GS2 and SB). Pairwise G’ST-values gave a slightly larger range, but were not qualitatively different (range: 0 - 0.138, mean = 0.033; Table 4.3). An AMOVA found the vast majority of genetic variation within fly individuals (93%), with low but significant differentiation among flies within colonies (6.4%) as well as among colonies (0.6%; Table 4.4a). Similarly, a structure analysis was unable to find any sub-structuring (Figure 4.2a), with the highest log- likelihood supporting a single population (lnP: -3268.440 ± 0.114; See

107 supplemental materials Figure S4.2 for all ln-P and ΔK values). Additionally, a geneland analysis across all nine fly populations was also unable to detect population sub-structuring in the fly, finding highest likelihood support for a single population. No correlation was found between geographic and genetic distance (r2 = 0.0, p = 0.537; Table 4.5), nor were flies from bat colonies living within the same forest fragment more similar (p = 0.228).

Table 4.3 Pairwise FST-values (above the diagonal) and G”ST-values (below the diagonal) for B. nana. Asterisks indicate significant differentiation after correction.

G’ST \ FST BS BW ES GB2 GS1 GS2 HB SB SD BS -- 0.002 0.003 -0.003 0.005 0.025* 0.010 0.063* 0.005 BW 0.007 0.003 -0.001 0.009 0.007 0.006 0.024 0.003 ES 0.010 0.009 -- -0.005 0.011 0.009 0.004 0.026 0.000 GB2 0.000 0.000 0.000 -0.002 0.008 -0.003 0.029 0.000 GS1 0.020 0.026 0.030 0.005 -- 0.034 0.013 0.023 0.009 GS2 0.061 0.019 0.020 0.017 0.084 0.007 0.040 0.010 HB 0.027 0.015 0.012 0.000 0.041 0.021 -- 0.035 0.002 SB 0.138 0.063 0.063 0.066 0.060 0.083 0.091 -- 0.030 SD 0.015 0.008 0.001 0.003 0.028 0.026 0.008 0.078 --

Temporal genetic structure No temporal genetic differentiation (Mantel test, p = 0.330) of flies was found in the three bat colonies sampled in 2002 or 2003 and 2011. The level of differentiation within colonies across years (FST = 0.012) was slightly higher than the average differentiation seen between different colonies sampled within a single year (FST = 0.009). A similar analysis was carried out for the four colonies where sufficient fly samples were collected in both 2002 and

2003 (BS, BW, ES, SD) yielding very similar results (mean within colony FST =

108 0.013, mean within year FST = 0.006). A hierarchical AMOVA supported this result and found none of the genetic variance was partitioned across years (- 0.1%; Table 4.4b), while again finding the vast majority of variation within individuals (93.9%).

Figure 4.2 STRUCTURE results for a) Basilia nana, b) Myotis bechsteinii and c) Spinturnix bechsteini. Colony names correspond to the abbreviations in Table 4.2. In B. nana and M. bechsteinii no discernable population sub- structuring was found (K=1). For these species K=2 is shown to illustrate the lack of sub-structuring when multiple subpopulations are assumed. For S. bechsteini, the best ΔK and highest log likelihood values were attained for K=6 (the actual number of colonies sampled).

109 Table 4.4 a) Single-level analysis of molecular variance (AMOVA) in B. nana, b) hierarchical AMOVA investigating temporal variance across all colonies sampled in 2002/3 and 2011. Asterisks indicate significant contributions. a) Sum of Variance Percentage of Source of variation d.f. squares component F-statistic variation

Among colonies 8 32.277 0.018 FST = 0.006 0.6* Among individuals,

within colonies 252 763.085 0.184 FIS = 0.065 6.4*

Within individuals 261 694.500 2.661 FIT = 0.070 93.0 b)

Sum of Variance Percentage of Source of variation d.f. squares component F-statistic variation

Among years 1 3.534 -0.004 FCT = -0.002 -0.2 Among colonies,

within years 4 15.271 0.018 FSC = 0.006 0.6* Among individuals,

within colonies 159 476.347 0.16 FIS = 0.056 5.6*

Within individuals 165 441.500 2.676 FIT = 0.061 93.9

Comparison with host and wing-mite We applied mantel tests to examine the correlation between the genetic distances of host and parasites (Table 4.5). Fly and bat pairwise FST-values (nuclear and mitochondrial) were not significantly correlated after correcting for geographic distance. Fly nuclear genetic distance was however significantly correlated with wing-mite nuclear genetic distance (r2 = 0.363, p

= 0.044), but not to wing-mite mitochondrial genetic distance (pairwise ΦST-

2 values; r = 0.027, p = 0.300). Plots of pairwise genetic distance (FST/1 – FST) between fly nDNA and both bat and wing-mite nDNA are provided in Figure 4.3. A structure analysis for the six colonies sampled for all three species was only able to detect population sub-structuring in the wing-mite (Figure 4.2) as had previously been show by van Schaik et al. (2014). Wing-mite populations were highly differentiated and structure found evidence for 6 sub-populations, clustering wing-mites according to their native bat colony (Figure 4.2c; see also van Schaik et al. 2014). In both the fly and bat no

110 structuring was detected, with the highest log-likelihood given for only one population (Figure 4.2a-b; see supplemental materials Figure S4.2 for graphs of ln-P and ΔK of all species).

Table 4.5 Correlation of fly genetic distance to geographic distance (IbD), host nuclear and mitochondrial genetic distance and wing-mite nuclear and mitochondrial genetic distance. All correlations to host and wing-mite genetic distance were performed as partial mantel tests correcting for geographic distance. For each correlation the slope (β), the variance explained by the model (R2) and P-value (P) are given.

β R2 P Fly nDNA - Geographic distance -0.0001 0 0.537 Fly nDNA - Host nDNA -0.332 0.071 0.229 Fly nDNA - Host mtDNA 0 0.025 0.103 Fly nDNA - Mite nDNA 0.085 0.363 0.044 Fly nDNA - Mite mtDNA 0.001 0.027 0.300

111 Figure 4.3 Pairwise genetic distance (FST/1 – FST) estimates between populations of hosts and parasites for a) fly nDNA vs. bat nDNA, b) fly nDNA vs. wing-mite nDNA. There was no correlation between fly and host genetic distance (β = -0.332; p = 0.229). Fly and wing-mite genetic distance were significantly correlated (β = 0.085; p = 0.044). a) 0.07%

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/(1!F 0.03% ST

Fly%F 0.02%

0.01%

0% 0% 0.005% 0.01% 0.015% 0.02% 0.025% 0.03% 0.035% 0.04% 0.045% 0.05%

!0.01% Bat%FST/(1!FST)!! b) 0.07%

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0.05%

0.04% !! ) ST

/(1!F 0.03% ST Fly%F

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0% 0% 0.05% 0.1% 0.15% 0.2% 0.25% 0.3% 0.35% 0.4%

!0.01% Mite%FST/(1!FST)!!

112 Discussion

Spatio-temporal genetic structure Using 10 nuclear microsatellite loci to investigate the population genetic structure of the bat fly Basilia nana, we found almost no genetic differentiation between the sampled host colonies. Temporally, the sampled fly populations were similarly stable, as genetic differentiation over a 9 year timespan was insignificant and comparable to the low differentiation seen between different bat colonies within a single year. Genetic distance between fly populations was neither correlated to geographic distance, nor to the genetic distance of the host. The observed population genetic structure (or lack thereof) can be explained in light of both fly and bat life history. The lack of genetic differentiation across host colonies suggests extensive horizontal transmission of flies between host maternity colonies. Although horizontal transmission via male Bechstein’s bats or perhaps even other bats is possible, we did not observe increased genetic differentiation between forest patches or over geographic distance as would be expected if transmission occurred primarily via males or other species overlapping with multiple adjacent female maternity colonies during summer. Instead, we suspect that the focal point of transmission of flies from different host maternity colonies and male bats occurs at underground sites during autumn and winter. This is supported by the correlation seen between fly and mite genetic distance across colonies as further outlined in the next paragraph. Given the possible migration distances between summer and winter sites in M. bechsteini (Hutterer et al. 2005), we expect all of the bat colonies in the study area can potentially meet at communal mating/hibernation sites. As flies go through only two generations in the summer (Reckardt and Kerth 2006), horizontal transmission at communal sites in the other seasons thereby effectively allows for gene flow within the catchment area of these sites every second generation. This results in a large fly meta-population whose genetic pool encompasses multiple bat colonies within the area, thereby overcoming the limited population sizes within individual colonies.

113 Influence of host behavioural/social adaptations By comparing the genetic structure of the fly to the previously analysed wing- mite, the interaction between host and parasite life history can be more extensively contrasted. We found a weak, but significant, correlation between fly and wing-mite nuclear genetic differentiation across colonies (r2 = 0.363, p = 0.044; figure 4.3). This suggests that fly and wing-mite horizontal transmission between host colonies occurs in a similar fashion, i.e. primarily during host mating and hibernation periods (van Schaik et al. 2014). We argue that the large differences observed in the degree of genetic differentiation in the two parasites are subsequently caused by differences in the levels of gene flow and genetic drift in both species. During summer, frequent roost switching with a strong preference for previously unoccupied roosts (Reckardt and Kerth 2007) significantly reduces the number of fly puparia that are able to successfully infect host colonies. Additionally, as Bechstein’s bat maternity colonies do not overlap in roost use, this does not allow for direct transmission of flies between female maternity colonies. However, presumably as a result of roost transmission, flies are able to persist on male Bechstein’s bats throughout the summer, increasing the transmission between female maternity colonies via male bats. Coupled with their low number of generations per year, these life history characteristics yield low genetic drift and high gene flow, resulting in a temporally stable and undifferentiated meta-population. On the other hand, while wing-mites are not affected by roost switching behaviour of the host, their survival and gene flow are strongly affected by the small colony size and extremely limited inter-colony interaction of female bats, and their inability to persist on male bats. Moreover, the higher rate of reproduction in the mites results in substantial inbreeding within colonies and allele frequency differences between colonies. These characteristics interact to yield strong genetic differentiation of mites between individual host maternity colonies as well as high temporal instability including frequent local extinction events (Bruyndonckx et al. 2009b, Reckardt and Kerth 2009, van Schaik et al. 2014). As a consequence, the levels of gene flow and genetic drift, and thus

114 population genetic structures, of the two parasite species are highly divergent despite the fact that the interaction between host and parasite life histories broadly leads to similar patterns of transmission. Interestingly, a comparative study across two wing-mite species illustrates that small changes in host and parasite life history can also lead to a genetically stable population structure in wing-mites. In Spinturnix myoti, a closely related wing-mite species found on the greater mouse-eared bat (Myotis myotis), a genetically diverse and unstructured population was found (van Schaik et al. 2014), very similar to the one observed in B. nana in this study. Greater mouse-eared bat summer maternity colony sizes are much larger than those of Bechstein’s bats, and they frequently interact with another bat species (lesser mouse-eared bat; Myotis blythii) also infected by S. myoti, and often hibernate in large clusters (Güttinger et al. 2001). As a result, S. myoti does not suffer from the same winter bottleneck, and the initial spring population in each summer maternity colony is much larger than in S. bechsteini (van Schaik et al. 2014). Additionally, during the autumn mating period, greater mouse-eared bats may also form temporary harems where direct contact between females from different maternity colonies may take place. In combination, this yields a wing-mite population that is genetically highly diverse and panmictic.

Comparison with other host-parasite systems Several investigations of parasite genetic structure have found large differences due to differing parasite dispersal abilities. In a comparison of three parasites (two lice and one fly) of the Galapagos Hawk (Buteo galapagoensis), Whiteman and colleagues (2007) found differing levels of inter-island genetic differentiation in the parasites closely reflecting their ability to disperse. While the fly closely mirrored the lack of genetic structure observed in the host, the lice showed moderate and strong differentiation as a result of their differing dispersal methods (horizontal and vertical transmission respectively). This is very similar to the results found in the current study, although the strong difference between the genetic structures

115 of different parasites observed in our study is not the result of different degrees of vertical transmission but rather due to differences in the amount of genetic drift induced by the interaction between parasite life history and host social system. In another study, two feather lice species of the Australian Magpie, Toon & Hughes (2008) were found to have strongly contrasting phylogeographic patterns over the range of the host. While one feather louse species closely followed the phylogeographic structure observed in the host, the other feather louse showed a contrasting pattern. This contrast was attributed to differences in dispersal ability between the lice, with the latter species being able to potentially disperse via long-range male host dispersal, or via hitchhiking on hippoboscid flies (Toon and Hughes 2008). Here too, strong similarities can be found with the current study, as male vectors appear to strongly influence the phylogeographic signal of two otherwise similarly transmitted parasites.

Conclusion The two parasites of the Bechstein’s bat investigated here show highly divergent spatial genetic structures despite relying on comparatively similar transmission opportunities, presumably due to differences in the amount of gene flow and genetic drift. Concordantly, we find that the temporal genetic stability of the two parasite populations within our single host meta- population is similarly divergent. Taken together, the few studies investigating the population genetic structure of multiple parasites on a single host (Gómez-Díaz et al. 2007, Whiteman et al. 2007, Toon and Hughes 2008; this study) have illustrated that parasite population genetic structure can differ strongly as a result of both parasite life history characteristics (dispersal ability, reproductive rate), host life history (inter-population contact, male vectors, colony size), and even inter-parasite interactions (parasite acting as a vector for another parasite). Therefore, in order to make accurate predictions regarding the genetic structure, and ultimately evolutionary potential, of a parasite, the life histories of both interacting species must be well characterized and their potential interactions evaluated.

116 Data accessibility Nucleotide sequences of the 10 new microsatellites generated for this study were deposited in GenBank under Accession Numbers KP974822- KP974831. Microsatellite data for all flies analysed have been submitted to DataDryad: doi:10.5061/dryad.5dd67

Acknowledgements We would like to thank Daniela Fleischmann, Markus Melber, Karsten Reckardt and many others for their help collecting samples; Ina Römer, Alain Frantz and Sébastien Puechmaille for their help in the lab and with data analysis; and Pascal Hablützel, Serena Dool and five anonymous referees for their useful comments on the manuscript. This study was carried out under license from the nature conservancy department of Lower Franconia. Our research was funded by two grants from the Volkswagen Stiftung to JvS (Az 84 871) and GK (Az 84 959). JvS is a member of the Max Planck Research School for Organismal Biology.

117 Supplementary materials

Table S4.1 A hierarchical analysis of molecular variance (AMOVA) comparing all samples from 2002 and 2003. As only 0.006% of variance was found among years, we pooled samples from both years when analysing spatial patterns of genetic differentiation to increase sample size and overall number of compared colonies.

Source of Sum of Variance Percentage of variation d.f. squares component F-statistic variation Among years 1 7.761 0.02 0.006 0.6*

Among colonies, 6 25.055 0.02 0.006 0.6* within years

Among individuals, 170 564.130 0.173 0.055 5.4* within colonies

Within individuals 178 529.000 2.972 0.067 93.3

Figure S4.2 Below are the log-likelihood values and corresponding DeltaK values (as described in Evanno et al. 2005) for all K’s tested using structure (K= 1-10; 5 iterations per K). All graphs were produced using Structure Harvester (Earl and vonHoldt 2011). In B. nana and M. bechsteinii, no evidence for population sub-structuring was found (K=1 has the highest log- likelihood), whereas in S. bechsteini the number of recovered sub- populations (K=6) corresponds to the number of populations sampled.

Basilia nana (fly)

118 Myotis bechsteinii (bat)

Spinturnix bechsteini (wing-mite)

119

120

121 Chapter 5

Synthesis and general discussion

A friend of mine recently expressed her dismay at “lowly” parasites. I beg to differ – if anything, parasites, including bat flies, are incredible examples of evolution at its best, organisms capable of both adapting to life in the most hostile of environments (the very substrate you live on wants you dead!) and resisting diseases that live inside your body.

- Piotr Naskrecki

Social hosts face a wide diversity of parasites and pathogens at all times, requiring an equally wide arsenal of defense mechanisms. The aim of this dissertation is to contribute towards understanding how facets of host social system interact with host and parasite life history to shape host-parasite infection and evolutionary dynamics. Specifically, I focused on exploring this topic within a multi-host, multi-parasite comparative system of European bat species and their mite and fly ectoparasites. Using this framework, I addressed three main research questions regarding the influence of bat social system on mite infection dynamics and mite and fly population genetic structure (see research aims; chapter 1). In this chapter, I synthesize the effects observed in chapters 2-4 and discuss their relevance at the two investigated levels of host-parasite dynamics (local infection dynamics, population genetic structure and

122 evolutionary potential). Subsequently, I briefly explore the possible consequences of host sociality at the third level (the directionality of the evolutionary trajectory), and discuss the possible restrictions that parasites impose on host social system. Finally, I integrate these effects into a general summary of the overall impact of host sociality on host-parasite dynamics, and provide an outlook regarding future directions in host-parasite evolutionary research.

Host sociality and parasite infection dynamics

In chapter 2 I provide an unambiguous example of how host social organization and mating system influence parasite infection and transmission dynamics. Across three hosts with varying group size in summer and differing degrees of contact during mating in autumn, I observe marked differences in parasite infection intensity throughout the autumn mating period closely mirroring the predictions made based on the social systems of the hosts. At the onset of the autumn mating period, mite prevalence and infection intensity was highest in females and juveniles of M. myotis, with lower infection levels in M. daubentonii and M. nattereri, faithfully reflecting differences in host aggregation size in summer. Males of M. myotis and M. nattereri were rarely infected at the onset of the mating season, matching their generally solitary nature during summer. In M. daubentonii, the formation of male bachelor groups during summer had a clear effect on mite prevalence and infection intensity as M. daubentonii of all host age and sex classes were similarly infected. Additionally, the gradual disbandment of maternity colonies in autumn was clearly visible in all species, as overall mite prevalence and intensity decreased throughout autumn in each, further highlighting the role of host social organization in shaping parasite infection dynamics.

123 Regarding parasite transmission, a similarly clear effect of host mating system was found in males of M. myotis and M. nattereri. In M. myotis, where there is lengthy contact (1 or more days) between the sexes in temporary harems, mite infection of male bats rose to levels equivalent to those of the other host classes by the end of the season. Meanwhile, in M. nattereri, where contact between the sexes during mating is comparatively short, male bats still experienced lower levels of parasite prevalence and intensity at the end of the autumn mating season. As a final note, despite catching dozens of M. bechsteinii, our focal species in the other chapters, we did not find any mites on this species. Nor were mites found on approximately 200 Bechstein’s bats sampled at ten other sites and on single occasions during the first year of sampling (data not shown). This suggests that mite infection levels in this host are likely even lower, or that mites may even go locally extinct in certain host populations. In general, the effects of host social system on parasite infection dynamics are comparatively well characterized, as shown by the accuracy of the predictions in this study. Nevertheless, it remains important to examine these effects, as accurate interpretation of parasite population genetic structure can only be achieved when these patterns are known. For example, at the level of population genetic structure, the genetic differentiation of parasite populations may either be the result of 1) low parasite transmission between populations, 2) strong local adaptation of the local parasite populations or 3) may simply arise due to strong genetic drift within populations. Therefore, understanding infection and transmission dynamics at the ecological level remains paramount to accurately interpreting parasite population genetic structure and the resulting evolutionary dynamics of the host-parasite interaction. Naturally, other genetic indices will also help reveal which of these scenarios is most likely, but these estimates are often inexact at the low sample sizes and marker numbers achievable for most parasite species. This is especially relevant in host species where social system is complex and aggregation and contact rates vary throughout the year (e.g. seasonal fluctuation), particularly when these changes are coupled with

124 major changes in host physiology (e.g. hibernation). Although often overlooked (Altizer et al. 2006), in these cases, understanding the concurrent dynamics of parasite infection, and notably how parasites persist during “sub-optimal” periods, becomes even more critical.

Host sociality and parasite population genetic structure

In the other two chapters I explore how host social system and parasite life history interact to shape parasite population genetic structure. In chapter 3 I show that differences in host social system result in contrasting population genetic structures in two bat-mite pairs (M. myotis and S. myoti, M. bechsteinii and S. bechsteini). S. myoti populations showed high levels of genetic diversity and very little pairwise differentiation, whereas those of S. bechsteini were much less diverse, strongly differentiated and showed strong temporal turnover. As in chapter 2, the contrasting patterns observed in parasite structure can be interpreted based on the predicted effect of several aspects of host social system that differ between the two host species. Specifically, M. myotis, relative to M. bechsteinii, forms much larger summer maternity colonies and there is more inter-group contact during all seasons. In S. myoti, this yields a large and panmictic population structure, which is both spatially and temporally stable. In S. bechsteini, mite populations in individual host colonies undergo a yearly winter bottleneck that severely limits effective population size and leads to the temporal instability of mite populations (including frequent local extinction). As mite horizontal transmission occurs primary in autumn before this bottleneck, this additionally leads to strong genetic differentiation among colonies due to genetic drift. These results corroborate the results from chapter 2 and illustrate that the difference in overall mite infection and mite transmission, as shaped by the social system of their hosts, also result in marked differences in parasite population genetic structure. Significantly, as the relative rate of gene flow

125 and genetic drift between the host and parasite were also opposite in the two species pairs investigated, these differences are predicted to lead to a higher evolutionary potential of the mite in one instance (M. myotis / S. myoti) and of the bat in the other (M. bechsteinii / S. bechsteini). Naturally, parasite population genetic structure is also strongly influenced by the life history of the parasite (Barrett et al. 2008). Therefore, in chapter 4, I explore how different parasite life histories interact with the same host social system by comparing the population structure of the mite S. bechsteini characterized in chapter 3 to that of the bat fly, B. nana. In contrast to S. bechsteini (described above), B. nana showed little spatial or temporal genetic structure, suggesting a large, stable population with frequent genetic exchange between fly populations from different bat maternity colonies. These results suggest that although the transmission patterns were similar in both parasite species, the level of gene flow and eventual spatio-temporal genetic stability differs due to the reproductive mode and life-history strategy of the parasites. Specifically, female S. bechsteinii give birth to protonymphs directly on the host, while B. nana deposits puparia on the walls of the roost. Coupled with the frequent roost switching behavior of the host, which strongly affects the ability of B. nana to successfully infect the host (Reckardt and Kerth 2007), this yields much faster population growth in S. bechsteinii than in B. nana. However, as the flies that do successfully infect hosts live longer and flies only go through 2-3 generations isolated in host colonies before having the opportunity to horizontally transmit at autumn swarming sites, this ironically yields to a much higher effective population size and a more temporally stable genetic structure in B. nana as the entire region effectively becomes one population rather than a sub-structured metapopulation. Similar to the previous study, these differences in parasite population genetic structure again yield contrasting evolutionary potentials, and hence ability to locally adapt to the host, in the two parasite species. As a whole the results presented in these two chapters show that parasite population genetic structure can be interpreted based on 1) the

126 predicted effects of individual parameters of host social system and 2) their interaction with parasite life history. However, despite this apparent success, how these parameters interact and the relative importance of each remain difficult to predict. For example, although the highly differentiated and temporally unstable population genetic structure of S. bechsteini can be interpreted in light of its hosts small summer maternity colony size, it would not have been possible to estimate the severity of the annual bottleneck or the stark contrast between the population genetic structure of S. bechsteini and S. myoti without exploring it empirically. Analogously, as the second study shows, the interaction between host social system and parasite life history is sensitive to very small differences in either, and certain aspects of host behavior may be highly relevant for one parasite species, but not for another. Being able to accurately gauge the importance of these effects is critical for coevolutionary outcomes, as theoretical models predict that even slight differences in parasite gene flow or drift can strongly alter parasite evolutionary potential and local adaptation dynamics (Gandon and Nuismer 2009b). Moreover, this sensitivity may also explain why many meta-analyses that aim to uncover general trends between host and parasite characteristics (and genetic structure) find little to no effect (Poulin and Forbes 2012, Mazé- Guilmo et al. 2016). These differences are even more striking when considering the limited diversity of host social systems and range of parasite types investigated. The comparative framework used here was specifically intended to eliminate possible confounding effects of differences in host life history, environmental factors, and large differences in parasite life history (e.g. generalist vs. specialist, mobile vs. non-mobile). Given our poor predictive ability despite these simplifications, it is therefore evident that accurate estimations of parasite population genetic structure and its consequences for evolutionary potential based solely on the predicted effects of all host social and parasite life history characteristics currently remains effectively impossible. Nevertheless, comparative investigations exploring these interactions are by no means pointless, as it will only be possible to uncover generalities

127 regarding the relative importance, and interaction of individual effects, through such studies.

A brief aside on the evolution of virulence and parasite induced restrictions to host sociality

Although beyond the scope of the work presented in this dissertation, a discussion of the effect of host sociality on host-parasite dynamics would be incomplete without briefly considering its likely impact at the third level of interaction (i.e. what happens when parasites are able to locally adapt?), as well as the possible restrictions that parasite pressure impose on host social system. Theoretical observations suggest that the formation of tight-knit social units may play an instrumental role in shaping the evolutionary trajectory of parasite virulence. By subdividing the overall population into distinct social units (i.e. creation of metapopulation), the transmission between individuals within such units becomes analogous to vertical transmission, which is expected to lead to lower virulence (Boots and Sasaki 1999). This is supported by work in a moth-virus system, where virulence was indeed shown to be lower in spatially structured populations (Boots and Mealor 2007). Interestingly, within social units, the increased social contact within groups may similarly select for reduction of parasite virulence (Bonds et al. 2005). This is because virulence is predicted to be highest in cases where host defense is achieved through resistance, as opposed to tolerance or avoidance (Raberg et al. 2009). As resistance and avoidance mechanisms become ineffective above a certain parasite prevalence threshold (Bonds et al. 2005), tolerance mechanisms will often be favored in social hosts. In sum, it therefore appears that host sociality per se may often favor the evolution of reduced virulence in associated parasites, though the more subtle contribution of individual aspects of host social system remain unexplored.

128 The obvious question remains whether parasite pressure ultimately limits the breadth of social systems available to a host species, or whether a host’s social system is adaptively shaped to minimize parasite pressure. In 1976, Freeland boldly stated that parasites and disease have had, and have, an impact in determining many of the characteristics of primate sociality (Freeland 1976). He subsequently outlined 16 hypotheses regarding specific ways in which parasites and disease may influence host sociality in both primates and mammals in general, concluding that behaviors that aid in avoiding infection are numerous, but whether these mechanisms resulted from targeted selection for disease avoidance remains to be tested (Freeland 1976). Forty years later, documented examples of host social and behavioral avoidance mechanisms are abundant in all social taxa (e.g. Møller et al. 1993, Moore 2002). Likewise, the effects that individual facets of host social system have on parasite infection dynamics are broadly understood (Poulin and Forbes 2012). However, evidence that parasites actively influence host sociality remains rare. Nevertheless, recently there is an increased recognition that the interaction between host ‘behavioral immune system’ and parasites is strongly reciprocal, and that hosts may indeed actively adapt based on this feedback (Ezenwa et al. 2016). Perhaps the most convincing evidence for restriction of host social system by parasites comes from a recent work on Grant’s gazelle and its parasites (Ezenwa and Snider 2016). In this system, Ezenwa and Snider found a reciprocal feedback between the maintenance of male territories used to attract mates and parasite load. Specifically, parasites were found to be a cost of territoriality, while concurrently these parasites dampened the behaviors required for territory maintenance, suggesting that the inter- and intra-individual variability in territory defense (with its obvious direct implications on mating system) is strongly influenced by parasite pressure (Ezenwa and Snider 2016). Thus far, investigations on the interplay between host sociality and parasite pressure, and the possible resulting restrictions to host social system, have focused primarily on the direct effects of sociality on parasite infection levels at an ecological level. Significantly, the possible role of

129 adaptive alterations and restrictions of host social system may extend to the evolutionary timescale and its interaction with parasite virulence as outlined in the first paragraph of this section (Ezenwa et al. 2016). In this extension, the feedback between parasite pressure and host social system at an evolutionary scale may restrict host sociality to those systems in which the host’s primary parasite threats are either locally maladapted, or in which parasite adaptation leads to the evolution of lower virulence levels. This addition implies that the ‘behavioral immune system’ may act at both the ecological and evolutionary timescales, and could be critical in reducing the virulence of parasites and pathogens that would otherwise have the potential to cause significantly more damage to their hosts. It goes without saying that such adaptive constraints of host social system will only occur in situations where parasites impose significant selective pressure on hosts, which additionally cannot be compensated for by more flexible immediate adaptations such as increased investment in immune response, or grooming and avoidance behaviors (Friant et al. 2016, Villa et al. 2016). Providing evidence for this hypothesis and establishing a causal link between parasite infection and constraints to host social system on an evolutionary scale is obviously complicated by several factors. For one, the selective pressures that led to current social system will, in many cases, be absent (the ghosts of parasites past, cf. Mooring et al. 2006). Additionally, it is nearly impossible to disentangle the effects of parasites and disease from the other factors that influence or constrain host social system, such as predation pressure (Kappeler and van Schaik 2002) and the defensibility of resources and mates (Clutton-Brock 1989, Clutton-Brock 2009). Nevertheless, targeted comparative studies certainly have the potential to further our understanding of host-parasite eco-evolutionary dynamics (e.g. examples in Table 1 of Ezenwa et al. 2016). Ultimately, regardless of whether these consequences have been actively selected for based on parasite and pathogen pressure, or whether they are merely convenient byproducts, their influence on host-parasite evolutionary dynamics remains.

130 Overall impact of host sociality on host-parasite evolutionary dynamics

To summarize across the three levels of host-parasite interaction, several important effects of host social system on host-parasite dynamics can be recognized. At the individual level, sociality inherently increases the risk of parasite exposure (Kappeler et al. 2015), as avoidance mechanisms are only effective if the entire social unit is able to avoid infection. I illustrate this in chapter 2, where increased host social aggregation and increased contact during mating both lead to increased parasite infection intensity and transmission. Conversely, the benefits of sociality increase the opportunity for a wide range of behavioral and social adaptations, as well as compensatory trade-offs, which increase the viability of tolerance as an effective defense mechanism. In addition, as tolerance and behavioral / social adaptations can be comparatively fast, plastic and effective against a broader range of parasites as compared to immunological and physical defenses (Medzhitov et al. 2012, Sears et al. 2015), their increased use may reduce overall defense costs. At the level of local genetic population structure, the impact of host social system is again substantial. In chapters 3 and 4 almost completely opposite parasite population genetic structures are observed, despite the narrow range of parasite life histories and host social systems investigated here. As population genetic structure of both interacting species consequently determines local evolutionary dynamics, these striking differences in parasite genetic structure are likely to subsequently lead to similarly divergent evolutionary trajectories. These predicted consequences for parasite local adaptation can theoretically be tested using transplant experiments, although the feasibility of such experiments in the current system may be complicated by difficulties in parasite marking (unpublished data). Finally, although not investigated in this system, the potential influence and feedback between host social system and parasite infection and

131 virulence at the evolutionary level may be vastly underappreciated. Notably, how host social system affects dynamics at this third level has momentous consequences for our interpretation of the effects of host social system at the level of the local genetic structure. In the case that host substructuring into social units indeed leads to the evolutionary reduction of virulence, this may mean that the consequences of local adaptation at second level are exactly opposite to those currently accepted (i.e. local adaptation of the parasite will lead to increased costs for the host). In sum, the effects of host social system on parasite infection intensity, transmission dynamics and population genetic structure observed here clearly illustrate that host sociality strongly shapes host-parasite evolutionary dynamics. Therefore, host sociality should be considered an instrumental, albeit perhaps partially unintentional, component of host defense against parasite and pathogen pressure.

Future directions

As demonstrated by the many unknowns and suppositions in the sections above, our understanding of precisely how social hosts affect, and are affected by, parasites on an evolutionary scale is still in its infancy. The increased applicability of advanced genetic and genomic tools to non-model species (and smaller organisms) has already greatly increased our ability to investigate parasite population genetics, as exemplified by the exponential increase in studies over the past few years (Mazé-Guilmo et al. 2016). A continuation of this trend, with special emphasis on comparative studies characterizing parasite genetic structure across a diversity of host systems, will help separate the effects of specific facets of host social system and explore (the variation in) their interactions. Likewise, an increased integration of local dynamics (landscape genetics) and broad scale patterns and history (phylogeography) will help uncover to what extent local

132 adaptation generates and maintains differentiation at a broader scale (Rissler 2016). As noted above, perhaps the biggest gap in our knowledge pertains to our understanding of how host sociality affects local adaptation and the evolution of virulence in parasites. Here too, advances in comparative genomics, with a special emphasis on emerging parasite and pathogen dynamics across a range of host social systems, will give us some insight into how host sociality shapes the evolutionary outcome of these interactions. Such studies are naturally contingent upon prior characterization of infection dynamics and local population genetic structure, as performed in this dissertation. As such, the bat-ectoparasite model presented here provides an ideal foundation to be expanded and continued upon in this direction. Finally, the integration of these insights into applied disease ecology and conservation approaches will greatly improve the efficacy of these efforts (Vander Wal et al. 2014a, Vander Wal et al. 2014b, Forbes et al. 2015). This will be critical given the wide range of anthropogenic changes to ecosystems (e.g. population reduction, fragmentation, introduction of exotic species, climate change) that will affect species interactions (Lampert et al. 2016) and host-parasite dynamics in particular (Longdon et al. 2015). As a result, understanding how host sociality is regulated by, and itself affects, parasites and pathogens will be instrumental to applied conservation efforts and the control of disease across both animals and humans (Streicker et al. 2012).

133

134 List of publications and selected abstracts

In addition to the chapters presented in this dissertation, I have (co-)authored several other publications during my time as a PhD candidate concerning parasites, bat behaviour and conservation. These are listed below, including abstracts of the most pertinent publications.

2011 Isolation and characterisation of microsatellite loci for two species of Spinturnicid bat wing mites (Spinturnix myoti and Spinturnix bechsteini)

J. van Schaik, N. Bruyndonckx, G. Kerth, P. Christe Acarologia 51:127-131

Part of MSc research and preamble to the work presented in this dissertation

Abstract To investigate the potential for host-parasite coadaptation between bats and their wing mites, we developed microsatellite loci for two species of Spinturnix mites. For Spinturnix myoti, parasite of Myotis myotis, we were able to develop nine polymorphic loci and screened them in 100 mites from five bat colonies. For S. bechsteini, parasite of M. bechsteinii, we developed five polymorphic loci, which were also screened in 100 mites from five bat colonies. In both species, all markers were highly polymorphic (22-46 and 6-23 alleles per locus respectively). The majority of markers for both species exhibited departure from Hardy-Weinberg proportions (8 of 9 and 3 of 5, respectively). One marker pair in S. myoti showed evidence for linkage disequilibrium. As the observed departures from Hardy-Weinberg proportions are most likely a consequence of the biology of the mites, the described microsatellite loci should be useful in studying population genetics and host- parasite dynamics of Spinturnix myoti and Spinturnix bechsteini in relation to their bat hosts.

135 2012 Causes and consequences of living in closed societies: lessons from a long-term socio-genetic study on Bechstein's bats

G. Kerth, J. van Schaik Molecular Ecology 21:633-646

Invited Review

Abstract Understanding the ecological, behavioural and genetic factors influencing animal social systems is crucial to investigating the evolution of sociality. Despite the recent advances in population genetic methods and the analysis of social interactions, long-term studies exploring the causes and consequences of social systems in wild mammals are rare. Here, we provide a synthesis of 15 years of data on the Bechstein’s bat (Myotis bechsteinii), a species that raises its young in closed societies of 10–45 females living together for their entire lives and where immigration is virtually absent. We discuss the potential causes and consequences of living in closed societies, based on the available data on Bechstein’s bat and other species with similar social systems. Using a combination of observational and genetic data on the bats together with genetic data on an ecto-parasite, we suggest that closed societies in Bechstein’s bats are likely caused by a combination of benefits from cooperation with familiar colony members and parasite pressure. Consequences of this peculiar social system include increased sensitivity to demographic fluctuations and limits to dispersal during colony foundation, which have broad implications for conservation. We also hope to illustrate by synthesizing the results of this long-term study the diversity of tools that can be applied to hypothesize about the factors influencing a species’ social system. We are convinced that with the expansion of the number of social mammals for which comparably detailed socio-genetic long-term data are available, future comparative studies will provide deeper insights into the evolution of closed societies.

136 2015 Bats Swarm Where They Hibernate: Compositional Similarity between Autumn Swarming and Winter Hibernation Assemblages at Five Underground Sites

J. van Schaik, R. Janssen, T. Bosch, A.-J. Haarsma, J. J. A. Dekker, B. Kranstauber PLoS ONE 10:e0130850

Analysis based on previous bat conservation work in Netherlands

Abstract During autumn in the temperate zone of both the new and old world, bats of many species assemble at underground sites in a behaviour known as swarming. Autumn swarming behaviour is thought to primarily serve as a promiscuous mating system, but may also be related to the localization and assessment of hibernacula. Bats subsequently make use of the same underground sites during winter hibernation, however it is currently unknown if the assemblages that make use of a site are comparable across swarming and hibernation seasons. Our purpose was to characterize the bat assemblages found at five underground sites during both the swarming and the hibernation season and compare the assemblages found during the two seasons both across sites and within species. We found that the relative abundance of individual species per site, as well as the relative proportion of a species that makes use of each site, were both significantly correlated between the swarming and hibernation seasons. These results suggest that swarming may indeed play a role in the localization of suitable hibernation sites. Additionally, these findings have important conservation implications, as this correlation can be used to improve monitoring of underground sites and predict the importance of certain sites for rare and cryptic bat species.

137 accepted Swarming behaviour, catchment area and seasonal movement patterns of the Bechstein’s bats: implications for conservation

D. Dekeukeleire, R. Janssen, A.-J. Haarsma, T. Bosch, J. van Schaik Acta Chiropterologica

Analysis of Bechstein’s bat swarming behaviour

Abstract Bats display marked seasonality throughout the temperate zone and use different habitats during different parts of the year. Unfortunately, detailed information regarding seasonal distribution and movements is often lacking, thereby hampering the development of adequate conservation measures. In this study we used radio telemetry to track females of the endangered Bechstein’s bat from autumn swarming sites to their summer maternity colony ranges. We were able to tag 22 individuals, 18 of which were subsequently recovered at 9 roost sites up to 20.58 km away. Females from multiple colonies visited the same swarming site on a single night. Concurrently, we recovered females from a single maternity colony at different swarming sites on the same night. The catchment area of the investigated swarming sites measured 27.05 km2, and was notably skewed to the northwest. Tagged bats were recovered in forest fragments ranging in size from 5.42 to 128.98 ha. Notably, all but one of the recovered roosts were found in forests that have been continuously wooded since at least 1775. Surveys during the summer at these sites confirmed the presence of maternity colonies at six out of seven locations that could be investigated. Our study exemplifies that characterizing the seasonal movement patterns, and identifying the habitats critical to the conservation of an elusive species throughout its annual cycle, can facilitate concerted conservation efforts.

138 Other Contributions

Dekeukeleire, D., R. Janssen, and J. van Schaik. 2013. Frequent melanism in Geoffroy’s bat (Myotis emarginatus, Geoffroy 1806). Hystrix, 24:197- 198. Kerth, G., D. Fleischmann, J. van Schaik, and M. Melber. 2013. From behaviour and genetics to nature conservation: 20 years research on Bechstein’s bats. Pages 35-50 in M. Dietz, editor. Populationsökologie und Habitatansprüche der Bechsteinfledermaus Myotis bechsteinii. Zarbock GmbH & Co. KG, Frankfurt. Mohr J., C. Koch von Helversen, J. van Schaik, F. Mayer, S. P. Ripperger, D. Josic, C. Strätz. accepted. Eine neue Fledermausart für Bayern – die Nymphenfledermaus (Myotis alcathoe, Helversen & Heller 2001). Nyctalus, 18:3-4

139

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159 Author contributions

The ideas presented in this dissertation have been developed by me and extensively discussed and refined with Gerald Kerth. All chapters and ‘general parts’ of this dissertation were written by me and commented on by co-authors. An itemized list of contributions per chapter can be found below.

Chapter 2: JvS designed the study, performed the fieldwork, and analyzed the data. JvS wrote the paper with input and discussion from GK.

Chapter 3: All authors designed the research and participated in sample collection; JvS and NB performed the molecular genotyping, sequencing and data analysis; and JvS wrote the paper with input from all coauthors.

Chapter 4: The study was designed by JvS and GK; field sampling was managed by GK and JvS; DNA extraction and genotyping was conducted by DD; data analysis was performed by JvS and DD. The manuscript was written by JvS with input from all authors.

This work would not have been possible without the aid of many additional scientists who aided in collecting samples in the field or provided other assistance. Please refer to the acknowledgement statements of the individual chapters for details.

160 Acknowledgements

I am indebted to a great many people who helped make this dissertation possible.

Scientific research would not be possible without funding. Therefore, I would first sincerely like to thank the Volkswagen Foundation and the IMPRS for Organismal Biology for giving me the opportunity to carry out my work. Similarly, funding would not help much without a great support staff to make it through the bureaucracy and paperwork. A special thanks to Dr. Grewe, Daniel, Mäggi, Carmen, Ilse and the entire Seewiesen administration team for facilitating and allowing me to focus on the fun stuff instead.

Dear Gerald, I could not have wished for a better mentor, friend and supervisor. Thank you for your endless patience, despite my occasional stubbornness, side-project distractions and disregard for deadlines. Thanks also for your keen insight, helpful comments, fruitful discussions, many phone calls and overall support! Even from a distance, it’s been an absolute pleasure working with you.

This project would also not have been possible with Bart and his entire department who supported me in Seewiesen. I would also like to thank Bart, as well as Philippe and Karen for their wise words and guidance as advisory committee members, and Martin, for agreeing to be my supervisor in Konstanz.

Next, a big thanks to Daan, for your truly exemplary MSc project, your profound patience in dealing with fly morphology and tricky primers, and for all the other interesting discussions and collaborations.

161 Before going any further, I should thank the many people that helped lay the foundation for this work. Especially the Dutch bat crew: René, Bart, A-J, Thijs and Jan, for introducing me to the dark side and continuing to collaborate together on all sorts of adventures ever since. Thanks also to my thematic predecessors, Nadia and Karsten, who provided the foundation necessary for my work and left hundreds of assorted parasite samples in the freezers for me to work with.

I am eternally grateful to the countless people who assisted me in the field. The Würzburg crew: Markus, Dani and the army of students who have helped collect parasites over the years. Frauke, Lena and Johannes for their immense hospitality in Münster and Forchheim, and for sharing their incredible field sites and knowledge with me. Finally, to Matthias for help obtaining permits to make all my adventures legal.

After fieldwork comes lab work, and here too, I am indebted to many people. Particularly to Jari, Sylvia (and the whole Seewiesen lab team) and Ina for their instruction, advice and support in all things molecular.

A big thanks to all my friends, who helped in all sorts of various ways, from help with data analysis to proof-reading to brainstorming to simply being great friends: Leo, Stefan, Robin, Jacky, Uli, Lisa, Bryson, Ryan, the entire Seewiesen United and 3M/ESPE football teams, Caro, Michael, Veronika, Sébastien, and the many others, you know who you are!

And of course to Susi, for being a friend like no other.

Finally, to my family, for making it seem like the most natural thing in the world to follow your passion and become a biologist.

Thank you, Dankjewel, Danke

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Curriculum vitae

Antoon Jacobus (Jaap) van Schaik Date of birth: 21.11.1986 Current affiliation: Max Planck Institute for Ornithology, Germany University of Greifswald, Germany E-mail: [email protected]

Education 2010 - 2016 PhD Max Planck Institute for Ornithology, Seewiesen, Germany “The influence of host social system on parasite genetic population structure.”

2007 - 2009 MSc (cum laude) University of Groningen, The Netherlands Top Master program Evolutionary Ecology

2004-2007 Bsc (with honors) University College Utrecht, The Netherlands Specialization in Molecular and Developmental Biology

2004 High School (honors arts distinction) Durham School of the Arts, North Carolina, USA

Academic Awards and Scholarships 2014 Awarded 1 year PhD Scholarship; International Max Planck Research School for Organismal Biology

2010 Awarded 3,5 year PhD Scholarship; Volkswagen Stiftung.

2010 Best Student Talk; 14th International Bat Research Meeting, Prague, CZ

163 Scientific Activities Representation 2011 - 2012 Student representative on the Board of the International Max Planck Research School for Organismal Biology

Course participation and organization 2010 - 2016 Attended: Scientific Integrity and Ethics, Scientific Illustration, Scientific Presentation, Scientific Writing, Bird Ringing, Spatial statistics in R 2012 Organized: Joint symposium between the International Max Planck Research Schools for Organismal Biology and Evolutionary Biology

Teaching 2009 - 2012 Co-organizer and instructor at annual field course on bat capture and handling 2011 - 2015 Annual lecture on Conservation in the Benelux, University of Greifswald 2013 Supervision of MSc student 2016 Field course in Bat biology

Public outreach 2012 Volunteer at “Tag der offnen Tür” at MPIO Seewiesen 2014 Public lecture in series “Organismen als Lebensraum”, University of Greifswald

Peer review Publons ID: 752323 2010 - Referee for: Acta Chiropterologica, Animal Behaviour, Behavioral Ecology, Behavioral Ecology and Sociobiology, Conservation Genetics, Journal of Mammalogy, Molecular Ecology, Journal of Heredity

Scientific Skills Languages English (native), Dutch (native), German (B2), Spanish (A2)

Practical Field skills: Bat capture and handling, Bird ringing, General natural history

164 Laboratory skills: DNA extraction, Sequencing and alignment, Microsatellite development and scoring

Computer Basic skills: Microsoft Office, Adobe Photoshop and Illustrator Statistical analysis: R (basic statistics, general linear modeling, similarity indices), Population genetics software (Genemapper, Genodive, Structure, Genepop, fstat, arlequin, CodonCode Aligner)

Publications ORCID ID: 0000-0003-4825-7676

ResearchGate: https://www.researchgate.net/profile/Jaap_van_Schaik

Google Scholar: https://scholar.google.de/citations?user=acnwIxQAAAAJ

Publications submitted for peer review van Schaik J, Kerth G (submitted) Host social organization and mating system shape parasite transmission opportunities in three European bat species

Peer reviewed publications

Dekeukeleire D, Janssen R, Haarsma A-J, Bosch T, van Schaik J (2016) Detecting bat maternity colonies in a highly fragmented landscape via radio tracking from autumn swarming sites. Acta Chiropterologica, in press Mohr J, Koch von Helversen C, van Schaik J, Mayer F, Ripperger SP, Josic D, Strätz C (accepted) Eine neue Fledermausart für Bayern – die Nymphenfledermaus (Myotis alcathoe, Helversen & Heller 2001). Nyctalus, 18:3-4 van Schaik J, Janssen R, Bosch T, Haarsma A-J, Dekker JJA, Kranstauber B (2015) Bats swarm where they hibernate: compositional similarity between autumn swarming and winter hibernation assemblages at five underground sites. PloS one 10.7 van Schaik J, Dekeukeleire D, Kerth G (2015) Host and parasite life history interplay to yield divergent population genetic structures in two ectoparasites living on the same bat species. Molecular Ecology DOI: 10.1111/mec.13171

165 van Schaik J, Kerth G, Bruyndonckx N, Christe P (2014) The effect of host social system on parasite population genetic structure: comparative population genetics of two ectoparasitic mites and their bat hosts. BMC evolutionary biology 14, 18. Dekeukeleire D, Janssen R, van Schaik J (2013) Frequent melanism in Geoffroy’s bat (Myotis emarginatus, Geoffroy 1806). Hystrix, the Italian Journal of Mammalogy 24, 197-198. Kerth G, Fleischmann D, van Schaik J, Melber M (2013) From behaviour and genetics to nature conservation: 20 years research on Bechstein’s bats. In: Populationsökologie und Habitatansprüche der Bechsteinfledermaus Myotis bechsteinii (ed. Dietz M), pp. 35-50. Zarbock GmbH & Co. KG, Frankfurt. Kerth G, van Schaik J (2012) Causes and consequences of living in closed societies: lessons from a long-term socio-genetic study on Bechstein's bats. Molecular Ecology 21, 633-646. van Schaik J, Bruyndonckx N, Kerth G, Christe P (2011) Isolation and characterisation of microsatellite loci for two species of Spinturnicid bat wing mites (Spinturnix myoti and Spinturnix bechsteini). Acarologia 51, 127-131. Coyer JA, Hoarau G, van Schaik J, Luijckx P, Olsen JL (2011) Trans‐Pacific and trans‐Arctic pathways of the intertidal macroalga Fucus distichus L. reveal multiple glacial refugia and colonizations from the North Pacific to the North Atlantic. Journal of Biogeography 38, 756-771.

Non peer reviewed publications van der Plas ALD, van Schaik J (2010) Determinatie tabel tot de boom- en bodemwantsen van Nederland. Jeugdbondsuitgeverij. ISBN: 978-90- 5107-044-6 [translation: key to the stink bugs of Netherlands] Haarsma, A-J, van Schaik J, Bosch T, Janssen R (2015). The Bat Catcher's Manual: Manual for assessment of reproductive status, age and health in European bats. Electronic publication: www.vleermuizen vangen.nl

Conference contributions

2010 International Berlin Bat Meeting – Talk “A comparison of genetic population structure in host and parasite” 2010 IMPRS Grand Challenges Symposium – Talk “Might mites be a mighty source of information” 2011 Meeting of German Bat Researchers – Poster

166 “Bat-Mite genetic population structure” 2011 Fachtagung Bechsteinsfledermaus - Talk “Interaktion der Bechsteinfledermaus mit ihren Parasiten” 2011 European Society for Evolutionary Biology – Poster “A comparison of genetic population structure in two host- parasite systems (Myotis bechsteinii - Spinturnix bechsteini and Myotis myotis - Spinturnix myoti)” 2011 Volkswagen Symposium Evolutionary Biology – Poster “A comparison of genetic population structure in two host- parasite systems (Myotis bechsteinii - Spinturnix bechsteini and Myotis myotis - Spinturnix myoti)” 2013 International Bat Research Meeting – Talk “Comparative Population Genetics of Bechstein’s Bat and Two of its Ectoparasites” 2013 Volkswagen Symposium Evolutionary Biology – Talk “Comparative Population Genetics of Bechstein’s Bat and Two of its Ectoparasites” 2013 Göttinger Freilandtage – Talk “Can a closed host social system reduce the evolutionary potential of parasites? Insights from the Bechstein’s bat and two of its parasites” 2014 IMPRS Grand Challenges Symposium – Talk “Host-Parasite interactions in a social world” 2015 International Berlin Bat Meeting – Talk “Small differences in host and parasite life history can strongly affect parasite population genetic structure: lessons from two bat hosts and three ectoparasites” 2016 Summer school on dispersal (Univ of Greifswald) – Talk “Dispersal at the mercy of your host: dispersal and gene flow in non-mobile parasites”

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