Demographic Structure and Aging in Bactrocera Tryoni (Diptera: Tephritidae) in Subtropical Australia

Demographic Structure and Aging in Bactrocera tryoni (Diptera: Tephritidae) in Subtropical Australia

Mst Shahrima Tasnin

M. Sc. (Zoology)

Submitted in fulfilment of the requirements for the degree of Doctor of Philosophy

2020

School of Biology and Environmental Science Faculty of Science and Engineering Queensland University of Technology

Keywords

Age distribution, age-structure, aging, Bactrocera tryoni, captive cohort, captive-cohort method, cue-lure, Dacinae, Dacini, demography, demographic structure, dry season, fecundity, fertility, fruit-based trap, guava-juice odour, host-fruit, longevity, long-lived insect, olfactory response, overwintering, phenological adaptation, population ecology, population phenology,

Queensland fruit fly, quiescence mechanism, rainfall, reference cohort, reproductive aging, reproductive potential, Tephritidae, tropical fruit fly, tomato-based trap, tropical insect, wet season.

iii iv Abstract

Bactrocera tryoni (Froggatt) (Diptera: Tephritidae) is Australia’s primary horticultural insect pest. Original endemic to tropical and subtropical eastern Australia, it is now established in nearly all Queensland, New South Wales, and Victorian horticultural production areas. Despite its economic importance, knowledge of the species’ field demographics is almost entirely lacking, with the exception of basic seasonal abundance data and work undertaken on the overwintering biology of the fly in cool, temperate Australia. Modelers have assumed continuous breeding by the species except where limited or slowed by temperature and such models have been used to inform risk analysis, but many of the underlying demographic assumptions of the models have never been tested. To help fill this gap, my thesis focuses predominantly on developing a deeper understanding of the demography of field populations of B. tryoni in subtropical eastern Australia; with a focus on methodology development and validation, the collection and analysis of population age-structure data using the demographic method, and then an assessment of the impact of age on B. tryoni reproductive capacity.

The demographic method of age-structure estimation requires the capturing of wild insects from the field, with the accuracy of the method requiring the capture of those insects to be without age-bias. I used lure trapping to collect wild flies, but with no existing information on how B. tryoni’s olfactory responses change with age I needed to test for the potential for differential response with aging. To do this I researched the effect of age on olfactory response of B. tryoni males to cue-lure and females to guava-juice odour from sexual maturation (3 weeks) to 15 weeks. I also tested male response to tomato odours over their life from week one to 15 weeks. Additionally, I compared catches of wild males to tomato-based traps and cue- lure traps in the field during different seasons of the year. The olfactory experiments showed

that sexually mature males were strongly attracted to both cue-lure and host-fruit odour until an advanced age (12 weeks age), although the male response to cue-lure declined at 15 weeks of age. Additionally, in the field males responded to both cue-lure and tomato-baited traps throughout the year and the capture rate did not significantly differ between trap types. Sexually mature females showed their highest attraction to guava-juice odour until six weeks of age and then their attraction gradually declined with aging. This olfactory work is published or in press as two refereed journal articles.

Having tested my sampling methodology, I moved to assessing B. tryoni population age- structure. At a coastal site in sub-tropical eastern Australia, I studied the age of a wild population, with a focus on times of the year when marked population abundance changes occur i.e. early autumn; late autumn; late winter, early spring and early summer. I followed the demographic approach developed by J. R. Carey and colleagues which involves collection of mortality data from two cohorts of insects maintained in the laboratory: one being the ‘captive cohort’ of wild flies captured from the field at an unknown age, the other the ‘reference cohort’ consisting of known age individuals that emerge in the laboratory from wild infested fruit. Each season I collected the captive cohort using cue-lure and tomato-based traps, and I obtained the reference cohort from flies that emerged from infested host fruit collected from the same site.

From the mortality data of both cohorts, I estimated the age-structure using a likelihood function (which is mathematically different from the demographic method of Carey and colleagues).

The study showed that the age-structure of a wild B. tryoni population varied greatly with season. The summer and autumn populations were composed of mixed-age flies with young, middle-age and old flies all present in the population. In contrast, late winter and early spring

populations were composed almost exclusively of old to very old individuals. Surprisingly, the longevity of reference cohort flies, despite being held for their entire lives under the same, constant laboratory conditions, showed strong seasonality with spring and autumn populations short-lived, while late autumn and late winter populations were long-lived. The age-structure data directly contrasts with the work of population modellers who, for my study region, had predicted six to eight generations per year based on assumptions of constant breeding. Rather, and despite temperature and hosts not being limiting, my data showed breeding was halted by mid-autumn and did not recommence until the beginning of spring. A maximum of three, but more commonly only two B. tryoni generations per season were predicted by the likelihood function modelling which indicate that the population may have a maximum four to at most five generations per year.

The age-structure study showed that the late winter and early spring population contained a very large proportion of very old individuals. This led me to carry out a whole-of-life fertility experiment to evaluate the effect of age on fertility of males and females in a non-competitive environment, when paired with a continuously young or same-age mating partner. The study showed that the fecundity and fertility of females paired with the either same-age or young partner declined with age, although the females paired with young males were capable of laying fertile eggs at a very old age. The eggs of young partners paired with aging males had increasing hatch rate as males aged, indirect evidence for increasing male fertility with age.

When combined, the data showing seasonal variation in age-structure and longevity strongly suggests that B. tryoni has an endogenous mechanism which allows it to increase reproductive capacity during what would be the spring/summer wet-season fruiting period of its indigenous rainforest habitat, followed by an adult quiescence mechanism during what would be the non-

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fruiting dry season. This basic mechanism remains, even in human-modified landscapes where fruit are not seasonally limiting. This pattern explains not just our data, but also matches the well documented population phenology of the species which consistently in subtropical

Australia shows rapid spring increases with populations peaking in summer and early autumn, before declining again until the following spring. Rather than having the continuous breeding and overlapping generations as predicted by day-degree based models, the population effectively “resets” itself every spring to a single starting generation as the very old flies present at the end of winter start the new season’s activity. Very old females appear unlikely to further contribute to the new season’s population beyond getting it begun as their fecundity, fertility and ability to locate host fruits is low. In contrast, very old males can contribute further to the rapid spring population growth if they have access to young F1 female partners as males retain fertility into old age and they showed a constant attraction to cue-lure, which provides males with mating advantages, until an advance age.

In conclusion, the study showed that the demography, and not just the abundance of the subtropical population of B. tryoni varies with season, and as such they are not unlike temperate insects. The variation in age-structure at different seasons arises from similar cycles of reproductive activity, which for the temperate insects is dictated by limiting low winter temperatures but for B. tryoni is likely driven by an endogenous quiescence mechanism for surviving the monsoonal dry season when hosts are lacking. The demographic approach I developed here can be applied more broadly to tropical and subtropical insects for which demographic data of wild populations is largely lacking and is likely to provide novel insights to their ecology. For B. tryoni, if extended and confirmed at other sites, the new knowledge will help inform the best timing for applying pest management tools such as mass-trapping and the release of sterile males.

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Table of Contents

Section Contents Pg. No. a Keywords iii b Abstract v c Table of contents ix d List of figures xiii e List of tables xv f Statement of original authorship xvi g Acknowledgements xvii 1.0 Chapter 1: General introduction and literature review 1 1.1 General introduction 2 1.2 Demography of tropical insects 5 1.3 Dacini fruit flies 7 1.3.1 Seasonality in the population abundance of fruit flies 8 1.3.2 Importance of demographic and aging research of tropical 10 fruit flies 1.4 Demographic study in wild insects 13 1.4.1 Aging in wild insects 13 1.4.2 Constraints of aging research in wild insects 14 1.4.3 Demographic approach of age estimation of wild insects 15 1.4.4 Application of demographic approach for age estimation 16 1.5 Aging effects on olfactory response of insects 17 1.6 Reproductive aging in insects 19 1.6.1 Reproductive aging in female insects 19 1.6.2 Reproductive aging in male insects 20 1.6.3 Effect of mating partner age on reproductive potential 21 1.7 Introduction to study insect 23 1.7.1 Role of abiotic and biotic factors on B. tryoni population 24 growth 1.7.2 Seasonal phenology of B. tryoni 26

Section Contents Pg. No. 1.7.3 Olfactory response of male and female B. tryoni 29 1.7.4 Reproductive potential of male and female B. tryoni 31 1.8 Thesis outline 32 2.0 Chapter 2: Effect of advanced age on olfactory response of male 36 and female Bactrocera tryoni 2.1 Introduction 37 2.2 Materials and methods 40 2.2.1 Study insect 40 2.2.2 Olfactometer bioassay 41 2.2.3 Experimental design 42 2.2.4 Data analysis 44 2.3 Results 44 2.3.1 Effect of age on the male response to cue-lure 44 2.3.2 Effect of age on the female response to guava-juice odour 49 2.4 Discussion 54 2.4.1 Reduction in olfactory response with ageing 54 2.4.2 Reduction in exploratory activity with ageing 55 2.4.3 Patterns in reduced olfactory response in males and females 56 2.4.4 Implications for management 58 3.0 Chapter 3: Response of male Bactrocera tryoni to host-fruit odours 59 3.1 Introduction 60 3.2 Materials and methods 62 3.2.1 Study site and material 62 3.2.2 Field observations. Male responsiveness to tomato-based 62 traps versus cue-lure traps 3.2.3 Olfactory response of males across their life to tomato odour 63 3.2.4 Data analysis 65 3.3 Results 66 3.3.1 Field observation. Responsiveness of males to tomato-based 66 3.3.2 Olfactory response of males across their life to tomato odour 67 3.4 Discussion 68

Section Contents Pg. No. 3.4.1 Males olfactory response to host-fruit odour with maturation 69 and aging 3.4.2 Why males are attracted to host-fruits odour? 70 3.4.3 Implications of study 71 4.0 Chapter 4: Seasonality in age-structure and longevity of 74 Bactrocera tryoni in subtropical Australia 4.1 Introduction 75 4.2 Materials and methods 78 4.2.1 Study insect 78 4.2.2 Demographic approach of age estimation 79 4.2.3 Study site 80 4.2.4 Sampling dates 80 4.2.5 Sampling and rearing of wild caught captive flies 81 4.2.6 Collection of infested fruits and rearing of reference flies 83 4.2.7 Data collection 84 4.2.8 Data analysis 84 4.3 Results 88 4.3.1 Comparison of captive and reference cohort survival 88 4.3.2 Seasonal influence on the longevity of reference flies 88 4.3.3 Survival of captive males 92 4.3.4 Age-structure of wild population of B. tryoni 93 4.4 Discussion 97 4.4.1 Seasonality of B. tryoni 98 4.4.2 Demographic structure and population abundance in tropical 100 insects 4.4.3 Using the demographic approach for tropical insect age 102 estimation 5.0 Chapter 5: Age-related reproductive potential of Bactrocera tryoni 104 5.1 Introduction 105 5.2 Materials and methods 108 5.2.1 General structure of experiment 108

Section Contents Pg. No. 5.2.2 Insects 109 5.2.3 Experimental setup 110 5.2.4 Collection and assessment of eggs 112 5.2.5 Data analysis 113 5.3 Results 115 5.3.1 Effect of age and mating partner’s age on female fecundity 117 and fertility 5.3.2 Effect of male age and female mating partner age on egg 117 hatch rate of the female partner 5.3.3 Longevity of males and females 118 5.4 Discussion 119 5.4.1 Effect of female age and mating partner age on fecundity and 120 fertility 5.4.2 Effect of male age and mating partner age on hatch rate of 121 partner’s eggs 5.4.3 Implications for B. tryoni population demography 121 6.0 Chapter 6: General discussion 124 6.1 General discussion 124 6.2 Summary of the thesis results 124 6.3 The demography and underlying mechanisms of population phenology 127 of Bactrocera tryoni 6.4 Implications of the study 129 6.4.1 Basic implications 129 6.4.2 Applied implications 131 6.5 Future research direction 133 7.0 Key research findings 136 8.0 Bibliography 139

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List of Figures

Fig. No. Figure Title Pg. No. Figure 2.1 Diagrammatic representation of response variables measured 43 concerning Bactrocera tryoni foraging in a Y-tube olfactometer Figure 2.2 The mean (± 1SE) probability of male Bactrocera tryoni selective 46 orientation to cue-lure at five ages for (A) all tested flies (explorer + non-explorer) and (B) explorer flies only Figure 2.3 The mean (± 1SE) probability of five age-groups of male 47 Bactrocera tryoni exploring either arm of a Y-tube olfactometer in the presence of a cue-lure source in one arm and a blank control Figure 2.4 The mean (± 1SE) time taken (seconds) by five age-groups of 48 male Bactrocera tryoni to locate a cue-lure source Figure 2.5 Age-related olfactory response of male Bactrocera tryoni to cue- 49 lure (results of chi-square analyses) Figure 2.6 The mean (± 1SE) probability of female Bactrocera tryoni 51 selectively orientating to guava-odour at five age-groups for (A) all tested flies (explorer + non-explorer) and (B) explorer flies Figure 2.7 The mean (± 1SE) probability of five age-groups of female 52 Bactrocera tryoni exploring either arm of a Y-tube olfactometer in the presence of a guava-juice source and a blank control Figure 2.8 The mean (± 1SE) time taken (seconds) by five age-groups of 53 female Bactrocera tryoni to locate a guava-juice source Figure 2.9 Age-related olfactory responses of female Bactrocera tryoni to 54 guava-juice odour versus a blank control (results of the chi-square test) Figure 3.1 Olfactory response of males of Bactrocera tryoni of different ages 67 to tomato odour Figure 3.2 Olfactory response of maturing males of Bactrocera tryoni to 68 tomato odour. Figure 4.1 An example of age-distribution produced by maximum likelihood 86 method using hypothetical data.

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Fig. No. Figure Title Pg. No. Figure 4.2 Cumulative survival curves of five cohorts of adult male 91 Bactrocera tryoni that emerged in the laboratory from field infested fruit Figure 4.3 Cumulative survival curves of three cohorts of adult female 92 Bactrocera tryoni that emerged in the laboratory from field infested fruit Figure 4.4 Probability density of age (in days) of wild Bactrocera tryoni 95 captured during different seasons in 2017-18 from a site in subtropical Australia Figure 5.1 Individual fly chamber supplied with water, sugar cube and yeast 111 hydrolysate ad libitum Figure 5.2 The mean (± 1SE) number of eggs laid by Bactrocera tryoni 116 females every second day from day 11 to death when paired with a young or same-age mating partner Figure 5.3 The mean (± 1SE) hatch rate (%) of eggs laid by Bactrocera tryoni 117 females every second day from day 11 after emergence to death when paired with a young or same-age male partner Figure 5.4 The mean (± 1SE) hatch rate (%) of eggs laid by young or same- 118 age Bactrocera tryoni females when paired weekly with aging males from day 11 after emergence until male death Figure 5.5 Cumulative survival curve of male and female Bactrocera tryoni 119 paired with a same-age or young mating partner Figure 5.S The mean (± 1SE) number of eggs laid by young or same-age 123 Bactrocera tryoni female partners paired with the aging males weekly from day 11 to death

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List of Tables

Table No. Table Title Pg. No. Table 3.1 The number and proportion of Bactrocera tryoni males captured 66 by cue-lure and tomato-based traps Table 3.S The number of wild Bactrocera tryoni males collected from two 73 cue-lure or two fruit-based traps containing one of six different fruit-based traps Table 4.1 A pairwise comparison of survival function of five reference 89 cohorts of adult male Bactrocera tryoni that emerged in the laboratory from field infested fruit Table 4.2 Survival of wild Bactrocera tryoni males (= captive cohorts) in the 93 laboratory. Flies were collected as adults during different seasons in 2017-18 from a site in subtropical Australia Table 4. S Akaike Information Criteria Weight (AICw) calculated from 103 maximum likelihood for eight potential reference cohorts against each season’s captive cohort

Statement of Original Authorship

The work contained in this thesis has not been previously submitted to meet requirements for an award at this or any other higher education institution. To the best of my knowledge and belief, the thesis contains no material previously published or written by another person except where due reference is made.

The research chapters of this thesis are presented as multi-authored papers. The contributions of my co-authors to those chapters are provided at the start of each chapter.

The photograph used in the title page was taken by Jaye Newman. All other photographs were taken by the author.

Signature: QUT Verified Signature

Date: ______

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Acknowledgements

I wish to express my sincere gratitude to my principal supervisor Prof. Anthony Clarke who had given me the opportunity to work under his supervision. I am extremely grateful to him for his immense support, valuable advice, encouragement, and appreciation during my whole PhD journey. His constructive and knowledgeable discussions always help me to think critically during experimental designing and writing. During hard time, his simplest solutions for the toughest problems work as a pain killer. His work and family life balance theory given me the flexibility to work in my own way. In a word, without his kind encouragement, guidance and support the project would not be completed.

I would like to express my gratefulness to my associate supervisor Dr. Katharina Merkel for her friendly support and advice all the way. Her constructive discussion and advice were invaluable for experimental designing and writing. I am thankful to her for the extraordinary support during my data analysis and critical comments on my manuscripts. Thanks to her for teaching us statistics and be always there in need.

My sincere thanks to QUT technical staff members Anne-Marie McKinnon, Karina Pyle, Mark

Crase and Sharyn Berg for their kind support to help me in operating equipment and assisting me in ordering material for the experiments. I am extremely grateful to QUT colleague Dr.

Michael Bode for his incredible assistance in mathematical modelling of age-structure estimation. Without his assistance, it would not be possible to finish perfectly.

I am extremely grateful to my QUT colleagues and lab mates Francesca Strutt, Jacinta

McMahon, Kiran Mahat, Shirin Roohigohar, Melissa Starkie, Jaye Newman, Bianca Jayde

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Kay, Aead M Abdelnabi, Mark Schutze, Matt Krosch and Muhammad Farooq for their kind assistance and joyful time during my PhD journey. Dr. Rehan Silva and Bianca Jayde Kay deserve special thanks for their invaluable support during my experiments and valuable suggestions. I highly appreciate their hard work and very grateful to them.

I want to express my gratitude to Ms. Thelma Peek and Ms. Linda Clarke for providing me pupae for my experiments and for providing me valuable information for collecting infested host-fruits. I am also grateful to Mr Brendan Missenden for informing and helping me to collect the infested mangoes from his property. My sincere gratitude to the owner and staff, especially

Bob Brinsmead and Mick O’Reilly, of Tropical Fruit World, Tweed Valley, NSW for allowing us onto their property for collecting wild flies and infested fruits throughout the year.

I would like to thank my family, friends, and many people in home and abroad who helped me during my PhD journey mentally and physically. I appreciate my husband’s immense support and thankful to him for being with me during my study period. Thanks to my little daughter for her patience and sweet company during hard time. I am grateful to my brother’s family for their support and encouragement. I must thank my mother-in-law for supporting my family during my critical time and my parents for their inspiration.

Finally, I would like to express my gratefulness to QUT for providing me the opportunity to undertake PhD and providing all the financial support to conduct my research. This research project would not have been completed without QUT Post graduate research award and QUT

HDR tuition fee sponsorship award.

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Chapter 1: General introduction and literature review

1.1 GENERAL INTRODUCTION

Demography is defined by Carey (1993) as “the study of populations and the processes that shape them”. Demography is based on four aspects of a population: size, distribution, structure and change. Structure means the distribution of a population by age and sex, while change implies total growth or decline of the population (Carey 1993, Carey and Roach 2020). The mechanisms and consequences that cause changes in a population are referred to as population dynamics. Age-structure and reproductive potential are two basic components which causes changes in a population (Carey and Roach 2020).

A population’s growth and decline are largely determined by the age of individuals of the population (Cole 1957). Knowing the age-structure of a wild population can inform demographic inference and interpretation (Poston 2019) as age-structure, and the birth and death processes that shape them, are interrelated and mutually affecting (Preston et al. 2001,

Carey et al. 2012). Thus, the population’s age-structure and reproductive potential are closely linked, and the temporal fluctuation of age-composition may result in fluctuations in population growth (Poston 2019, Hoy et al. 2020). For instance, a population containing predominantly young individuals is likely to have high reproductive potential and a low mortality rate. In contrast, an old population is more likely to have low reproductive potential and a high mortality rate (Poston 2019). Hence, age and age-dependent trends of reproductive potential are important life-history phenomena which influence the fertility of individuals at a given age

(Charlesworth 1994). Fisher et al. (1985) introduced the parameter “reproductive value” as a measure of the relative extent of the reproductive contribution of different age-groups of individuals to the future population and it is considered an important demographic parameter because it recognizes the role of an individual’s age to population change (Carey 1982). Thus, knowledge of the age-structure and age-dependent reproductive potential of wild animals is

Chapter 1: General introduction and literature review vital for understanding the demographic trends of wild populations from both theoretical and applied perspectives (Kouloussis et al. 2011, Poston 2019, Hoy et al. 2020).

Along with reproductive potential, other important behaviours and physiologies of insects are also affected by age, such as olfaction (Iliadi and Boulianne 2010, Gadenne et al. 2016). For example, as newly emerged adults, insects may be more attracted to food odours, while after sexual maturation they may be more attracted to olfactory cues from mating partners (Klowden

1990). Additionally, an insect’s response to the same odour may also change with age (Crnjar et al. 1990, Gadenne et al. 2016). Thus, understanding the olfactory response of insects throughout their life is also crucial to understanding their behavioural changes with aging, as well as for designing effective trapping tools (Kouloussis et al. 2009).

Given this brief background, the aim of my PhD is to develop a deeper understanding of the demography of field populations of Bactrocera tryoni (Froggatt) (Diptera: Tephritidae) (a.k.a

Queensland fruit fly or Q-fly) in subtropical eastern Australia. Bactrocera tryoni is Australia’s primary insect pest of horticulture (Clarke et al. 2011), but despite this economic importance knowledge of the species’ population demographics is almost entirely lacking, with the exception being work undertaken on the overwintering biology of the fly in cool, temperate

Australia (Clarke et al. 2019) and some basic seasonal abundance data (Fletcher 1974, Lloyd et al. 2010, Muthuthantri et al. 2010). Modelers have assumed continuous breeding by the species except where limited by temperature (Meats 1981, Sutherst and Yonow 1998, Yonow et al. 2004), and such models have been used to inform risk analysis (Sutherst et al. 2000a), but many of the underlying demographic assumptions of the models have never been tested and the modelers themselves recognize key gaps in knowledge (Yonow et al. 2004).

Chapter 1: General introduction and literature review

My PhD research has three major objectives. The first objective is to evaluate the impacts of aging on the olfactory response of B. tryoni, critical operationally for improving field management of the species and also theoretically when undertaking age-structure estimation.

The second objective is to estimate the age-structure of a wild population of Queensland fruit fly during different seasons. The final objective is to quantify the effect of ageing on the reproductive potential of male and female B. tryoni. Such a demographic and ageing study is of importance for several reasons. From an ecological perspective, it will directly help to understand what internal changes happen in a field population of B. tryoni during the year, while indirectly helping to understand the underlying mechanisms influencing those changes.

From an applied perspective, it will provide information about the age-group of flies which has highest reproductive value, helping inform growers of seasonal risk and for estimating the best time for applying pest management tools such as the inundative release of biological control agents, mass-trapping and the release of sterile males. Additionally, the methodology I use and refine will allow the demographic approach to be applied more broadly to pest and non-pest tropical and subtropical insects for which demographic data of wild populations is largely lacking.

Following this brief introduction of the thesis, in the following sections I set the background for the research chapters by reviewing relevant literature. In section 1.2, I focus on the diversity and abundance of tropical insects to give a broader ecological context of the demographic properties of insects which live in temperature-stable environments, as does B. tryoni in its endemic rainforest habitat. Following that, in section 1.3 I give an overview of tephritid fruit flies, their population phenology and why deeper demographic knowledge is required for this insect family. While there is importance in understanding the demography and aging of wild insects, why ageing studies are limited and how the demographic method offers a solution to

Chapter 1: General introduction and literature review the problem of aging wild insects is reviewed in section 1.4. In sections 1.5 and 1.6 I review the literature on how age impacts an insects’ olfactory response and reproductive behaviour, respectively. In section 1.7 I introduce my study insect, B. tryoni, with emphasis on its reproduction, population growth and phenology, olfaction and reproductive potential.

Following this background literature review, in section 1.8 I outline the structure of my thesis.

1.2 DEMOGRAPHY OF TROPICAL INSECTS

Insects comprise approximately 66% of all known animal species in the planet (Zhang 2011), with the vast majority of them concentrated in the tropics (Lewinsohn and Roslin 2008, Leal et al. 2016, Andresen et al. 2018). In natural systems, as elsewhere, tropical insects play key roles in ecosystem functioning (Sutton and Collins 1991, Noriega et al. 2018) and the supply of ecosystem services (Greenwood 1987, Jankielsohn 2018). In modified systems insect herbivores cause approximately 15 % crop lost worldwide, with the largest proportion of losses occurring in the tropics where insect pests can remain active year-round (Maxmen 2013). By recording seasonal population fluctuations, and utilising captive insects for reproductive and survival data, the study of demography of tropical insects has been paid considerable attention by both basic and applied ecologists (Cornell et al. 1998, Molleman 2018). Although the research purposes may vary, for example conservation versus pest management, most studies ask the same basic ecological question: how and why insect populations change over time and space (Peterson et al. 2009, Silva et al. 2011, Becerra 2015).

Temporal variation in insect population abundance may occur due to seasonal changes in biotic and abiotic factors. Major factors that directly affect the development of insects, and hence cause population fluctuation are temperature, rainfall, humidity, day length, availability of food and resources, and natural enemies (Wolda 1988, Didham and Springate 2003, Lourenço et al.

Chapter 1: General introduction and literature review

2019). Among these factors’ temperature is considered the most important for affecting insect population growth, especially in temperate regions where winters are cold. Thus, temperate insects show distinct seasonal phenology driven by temperature, with increases in population during spring and summer, declining during autumn and winter (Wolda 1988). However, tropical insects are considered not to be restricted by temperature (Kishimoto-Yamada and

Itioka 2015), as mean ambient temperature never falls below 18 ○C in the tropics (Peel et al.

2007). The stability of tropical temperatures can lead to a common misconception about the annual variability of insect populations in tropics, i.e. that their populations should fluctuate less than temperate insects as they live in a temperature stable environment (Wolda 1978a, b).

However, this assumption is not valid as approximately 75% of tropical forests demonstrate strong seasonality due to wet-season/dry-season rainfall patterns (Murphy and Lugo 1986).

Within such forests some tropical insects show predictable phenology patterns (Kishimoto-

Yamada and Itioka 2015, Santos et al. 2017).

Tropical insects can face extreme environmental conditions created by the monsoon cycles of wet and dry seasons (Bonebrake et al. 2010, Molleman 2018). Seasonal fluctuation of abundance of many tropical insects, most especially herbivores, has been related to the changed availability of resources for breeding and survival (Braby 1995). More specifically, in the monsoonal tropics an onset of the rainy season commonly leads to an increased abundance of insects through a functional correlation with a rain-driven change in leaf productivity, flowering and fruiting (Wolda 1978b, Frith and Frith 1985, Muniz et al. 2012). For example, the abundance of Ithomiine butterflies increases with the onset of the wet season and declines dramatically during the dry season due to the initial availability, and then lack of, host plants for breeding (Bonebrake et al. 2010). Thus, seasonality is a common phenomenon in tropical dry forests and monsoonal rainforests, although it may be absent or uncommon in perpetually

Chapter 1: General introduction and literature review wet tropical forests (Kishimoto-Yamada and Itioka 2015). However, not all tropical insects follow this pattern, with the abundance of some West African tropical rainforest butterflies increasing towards the high-dry season (Maicher et al. 2018).

1.3 DACINI FRUIT FLIES

The Tephritidae (Diptera) is one of the most speciose families of true flies, containing more than 5000 species worldwide (Norrbom et al. 1999). Within the tephritids, the dacini fruit flies

(Tephritidae: Dacinae) are nearly all fruit breeders (Robinson and Hooper 1989). The Dacini contains four genera, Bactrocera Macquart (461 spp), Zeugodacus Hendel (196 spp), Dacus

Fabricius (273 spp) and the rare Monacrostichus Bezzi (2 spp) (Doorenweerd et al. 2018).

Bactrocera and Zeugodacus species are widely distributed in the monsoonal tropical regions of Asia, Australia and the South-west Pacific (Drew 1989), while Dacus species are most common in the tropical dry forests and savannahs of Africa (Meyer et al. 2013). Female Dacini oviposit into fruit where the resultant larvae grow and feed. Larval infestation can cause fruit to prematurely fall to the ground, where the larvae then leave the fruit and pupate in the soil, subsequently emerging as teneral flies and sexually maturing over two to three weeks (May

1958, Fletcher 1989). All Dacini have a similar life cycle pattern but vary in life history traits such as the number of generations per year, fecundity rate of females, and the host plants that eggs are laid into and upon which the larvae feed (Clarke 2019). Depending on species, Dacini may utilize one or more host plant species for oviposition and larval development (Clarke

2017). Due to their nature of laying into fruit, Dacini can cause damage to commercial horticultural crops and there are approximately 50 Dacini pest species (Vargas et al. 2015).

While recognizing that the family Tephritidae contains many other frugivorous and non- frugivorous species, where the term “fruit fly” is used hereon in this thesis it is referring to

Bactrocera or the other closely related genera within the Dacini.

Chapter 1: General introduction and literature review

1.3.1 Seasonality in the population abundance of fruit flies

Like many other insects, the lifecycle of frugivorous tephritid fruit flies are also affected by seasonal changes in environmental factors (Ye and Liu 2007, Ghanim 2017, Li et al. 2020).

Fruit fly populations are dynamic across and within species, and the dynamics may be seasonal or unseasonal (Muthuthantri et al., 2010; Wolda, 1988). Where fruit fly populations show periodic fluctuation throughout the year, it is considered to be mostly driven by climatic factors and the availability of larval host fruit (Comins and Fletcher 1988, Duyck et al. 2004,

Vayssières et al. 2015). In temperate regions, invasive fruit fly populations are considered to driven by low winter temperatures rather than a lack of availability of host fruits (Bateman

1968a, Zervas 1987, Israely et al. 1997). For instance, in Hubei Province China the winter is very cold with freezing temperature which limit the growth of Bactrocera dorsalis (Hendel) and no adult fruit flies were captured during that period. However, the population abundance of the fly increased from July to the end of December which coincided with high temperatures and the ripening period of sweet oranges (Han et al. 2011). However, in tropical regions winter temperatures never fall below the temperatures required for growth and development of fruit fly populations and thus, in the tropics, fruit fly breeding is predicted to be continuous if hosts are not limiting (Yonow, et al. 2004, Choudhary, et al. 2017, Baker, et al. 2019).

An assumption that host fruits are always available for breeding is a major simplification of the system. In the tropics the availability of resources for breeding may be heavily influenced by the monsoonal dry-wet cycle, hence fruit fly populations can seasonally fluctuate (Tan and

Serit 1994, Yonow et al. 2004, Muthuthantri et al. 2010, Vayssières et al. 2015). In spite of temperature not being limiting and being highly polyphagous, the population of B. dorsalis in

Penang Island of Malaysia, showed a bimodal pattern of population fluctuation. The first peak occurred between February and April, while the second peak occurred between August and

Chapter 1: General introduction and literature review

November. Both peaks were correlated with the wet season when suitable host fruits were abundant, while low fly abundance was linked to a scarcity of host fruits during the dry season

(Tan and Serit 1994). A similar bimodal pattern of population fluctuation was also observed for B. dorsalis in Uganda, where the peak abundance was correlated with major mango fruiting seasons (Mayamba et al. 2014). In Benin, the population of B. dorsalis showed a unimodal pattern of population fluctuation where the maximum population abundance was correlated with wet season (Vayssières et al. 2015). In tropical India, 69% of the variation in B. dorsalis trap catches could be explained by only two variables: rainfall and the abundance of immature guava fruit (Jayanthi and Verghese 2011).

Frugivorous tephritids in other sub-families and tribes also show fruit-driven seasonality in their population cycles. The Mediterranean fruit fly, Ceratitis capitata (Wiedemann) showed fluctuation in population abundance throughout the year where peak abundance was correlated with availability of major hosts in tropical and subtropical regions (Harris and Lee 1987,

Appiah et al. 2009, Martínez-Ferrer et al. 2010). Even in the same climatic region, C. capitata populations may differentially fluctuate. For example, in two neighbouring orchards (approx.

0.5 km apart) on the Greek island of Chios the populations differed in annual peak timing due to different host plant composition, abundance and availability of preferred hosts in and surrounding those orchards (Katsoyannos et al. 1998). Other tropical polyphagous species of the South and Central American genus Anastrepha Schiner show distinct population fluctuations throughout the year with sharp rises in population abundances associated with fruiting peaks of their major hosts, but not correlated with rainfall (Hedström 1993, Celedonio-

Hurtado et al. 1995).

Chapter 1: General introduction and literature review

While an extensive range of studies have focused on the changing seasonal abundances of fruit flies and their correlation with biotic and abiotic factors, how demographic structure is impacted by, or impacts upon, the changing populations of fruit flies in the tropics remains nearly entirely unknown.

1.3.2 Importance of demographic and aging research of tropical fruit flies

1.3.2.1 Theoretical importance

Age-structure is one of the basic components of population dynamics and can help predict the future growth or decline of a population (Cole 1957). Additionally, current age-structure reflects the demographic past of the population (Poston 2019). For example, when a population contains many young individuals it indicates a recent previous period of birth; while populations composed of largely older individuals indicates a higher number of births in an earlier period followed by a period of lower births, or disproportionate mortality of young individuals. Likewise, a population of mixed age structure of young, middle, and old age classes reflects both the population’s past and future (Land et al. 2005, Carey et al. 2012). Thus, studying age-structure of a wild insect population during different seasons directly helps to understand the changes happening in that population during the year (Schaeffer Pedrotti et al.

2019).

Demographic studies can also indirectly help to understand the underlying mechanisms influencing population phenology (Kishimoto-Yamada and Itioka 2015), as seasonal variation in population abundance can arise from phenotype and genotype adaptation in response to selection on the timing of life cycle events with the optimal season (Wolda 1989, Molleman

2018). For instance, in a demographic study with wild-caught individuals of Drosophila melanogaster (Meigen) and Drosophila simulans Sturtevant, pronounced changes in

Chapter 1: General introduction and literature review population age distributions across seasonal time was exhibited. The temperate D. melanogaster contained uniformly young individuals early in the active (=spring) season, with age-structured heterogeneity increasing in later seasons leading to winter. In contrast, D. simulans, which is a more tropical species than temperate, showed a mixed age structure in the spring population and was consistently age-structured during all seasons (Behrman et al. 2015).

The difference in age composition in the early spring populations reflects different adaptive mechanisms in these species (Behrman et al. 2015, Machado et al. 2016). Drosophila melanogaster undergoes an overwintering diapause; thus, the presence of uniformly young age individuals is an indication of synchronized emergence of the F1 generation after the dormancy period (Tauber et al. 1986). In contrast, D. simulans does not undergo an overwintering diapause but migrates to warmer (southern) refugia during environmentally unfavourable seasons (Schmidt 2011) where they continue breeding which results in mixed-age flies in late spring populations. Thus, understanding how changes in environmental factors impact on changes of a species’ demographic structure can provide understanding on how a species is adapted to coping with a seasonally changing environment (Kishimoto-Yamada and Itioka

2015, Schaeffer Pedrotti et al. 2019).

For tropical fruit flies in the tropics, explicit assumptions have been made that breeding is continuous with no seasonal breaks (Yonow et al. 2004, Choudhary et al. 2017, Baker et al.

2019), despite the known importance of seasonally limited host fruit for breeding (Tan and

Serit 1994, Celedonio-Hurtado et al. 1995, Martínez-Ferrer et al. 2010, Mayamba et al. 2014).

Demographic research offers an approach to determine if continuous breeding does occur, or if there are other, currently unrecognised, components of fruit fly population biology.

Chapter 1: General introduction and literature review

1.3.2.2 Applied importance

Studies on demographic structure and ageing in fruit flies is important from a pest management perspective as it can help to increase the effectiveness of management tools that target the adult insects, for instance, the Sterile Insect Technique (SIT) (Dyck et al. 2006). In SIT programs, very large numbers of mass-reared sterile males are released into the field to mate with wild females (Suckling et al. 2016). Females mated with sterilised males lay unfertilized eggs and thus the population declines (Pérez‐Staples et al. 2013, Shelly and McInnis 2016). Thus, the success of SIT program is largely depending on mating of released males with the wild females

(Matsumoto et al. 2008). There are many attributes which can influence the mating success of males and females (Lance and McInnis 2005), of which age of insects is one of the important factors (Carey 1982). For example, the age of the wild adult population at the time of releasing sterile males may have a profound effect on the success of a SIT program (Carey 1982).

Populations which contain a high proportion of young female flies of pre-ovipositional stage, which are usually the first to mate, should be a major target for sterile-male release programs

(Carey 1982). Additionally, if the age-structure of the wild population is assessed correctly, the over-flooding ratio (the ratio of sterile to wild males) can be adjusted to match the population of wild males that are in a reproductively active age (Kouloussis et al. 2009).

Similar to SIT, the lure-and-kill technique targets adult insects. The mechanism of any lure- and-kill technique is to attract insects using a lure and so bring them to a killing agent, such as an insecticide, liquid or sticky substance (El-Sayed et al. 2009, Clarke et al. 2011). A lure can be chemical attractants such as sex pheromone, food-based attractant, host fruit odour, and phytochemical compounds, or visual attractants such as colour attractant or fruit mimic (Clarke et al. 2011, Shelly et al. 2014). The efficacy of lure-and-kill techniques can be heavily affected by the age of insects, as various behavioural and physiological activities change with age

Chapter 1: General introduction and literature review resulting in changes to the attractiveness of the lure cue (Jang 1995, Kendra et al. 2005,

Gadenne et al. 2016). For instance, immature female fruit flies need protein for sexual maturation, thus they forage for proteinaceous food and are attracted by the odour of protein

(Prokopy et al. 1991). However, once mature their need for protein lessens and so they will be only weakly protein responsive (Balagawi et al. 2014). Thus, trapping of females using protein- based odour may be heavily biased toward capturing immature flies and leave the damaging gravid females largely unaffected (Prokopy et al. 1991, Aluja et al. 1993, Jin et al. 2017, Sollai et al. 2018). Additionally, males of many species of Dacini fruit flies are attracted to the so- called male-lures (e.g. cue-lure and methyl eugenol), generally when they are sexually mature

(Wong et al. 1991, Metcalf and Metcalf 1992, Weldon et al. 2008, Kamiji et al. 2018). The use of such chemicals in monitoring and lure-and-kill can rarely capture immature males.

Differential response to protein and male lures is two examples of how the knowledge of the age composition of wild populations could be used to help improve timing for better application of lure-and-kill techniques.

In spite of having theoretical and applied importance, demographic and aging research is still an under studied field in ecology dealing with only a few economically important insects

(Carey 2011, Kouloussis et al. 2011, Papadopoulos et al. 2016). The reason for this lack of information is discussed in detail in the following section.

1.4 DEMOGRAPHIC STUDY IN WILD INSECTS

1.4.1 Aging in wild insects

Insects have been used as model organisms to understand the genetics, physiology, and evolutionary ecology of ageing, where the vast majority of data comes from laboratory reared individuals. However, the study of aging in wild insects is important, because the life of

Chapter 1: General introduction and literature review laboratory reared animal differs to a very great extent from their lives in the wild (Zajitschek et al. 2020). In a captive-environment organism are maintained under optimal conditions, without natural enemies and adversities. In contrast, wild animals in a natural environment incur intrinsic physiological stress as they encounter and deal with extrinsic stresses (Kawasaki et al. 2008, Carey 2011, Zajitschek et al. 2020). Because of the highly unnatural conditions in most laboratory studies, ageing and longevity in the wild can markedly differ from laboratory reared animals. This imposes limitations to understanding the actuarial properties of a species’ aging (Kawasaki et al. 2008, Zajitschek et al. 2020). Unfortunately, accurately measuring the age-structure of a wild population, or the age of wild individuals, is very difficult (Muller et al.

2007, Rao and Carey 2015).

1.4.2 Constraints of aging research in wild insects

Studying age distribution and survival of wild animals, especially insects, with conventional age-grading methods, can be expensive, complex, and have low accuracy (Carey et al. 2008,

Carey et al. 2012, Rao and Carey 2015, Johnson et al. 2019). Cole (1957) noted numerous limiting issues associated with understanding population age distributions in the field over 60 years ago: unfortunately, little has changed in the intervening time (Carey et al. 2008). There remain inadequate technologies to quantify wild insects’ age structure with accuracy. Although an extensive range of methods are available to estimate the age of insects, such as pteridine fluorescence (Lehane et al. 1986, Thomas and Chen 1989, Bernhardt et al. 2017), transcriptional profiles (Hugo et al. 2010a, Hugo et al. 2014b), and circular hydrocarbons analysis (Gerade et al. 2004, Moore et al. 2017), the majority of such approaches are limited to measuring the age of young and middle-aged insects. Age-grading based on morphological changes using ovariolar dilatation and growth line methods has low accuracy (Hugo et al.

2014a). Additionally, the application of such methods because of their complexity has been

Chapter 1: General introduction and literature review largely limited to a small number of insects of medical, veterinary, and forensic importance

(Zhu et al. 2013, Edalat et al. 2017, Shang et al. 2020). For many agriculturally important pests, including tephritid fruit flies, only young, immature flies can be identified with certainty as they do not possess mature oocytes and sperm (Fletcher et al. 1978, Kendra et al. 2006). Due to the small size of insects, traditional mark-recapture techniques to age wild individuals in the field through temporal tracking also has extreme limitations (Southwood 1966).

1.4.3 Demographic approach of age estimation of wild insects

The life-table is an important tool of research in the field of demography as it deals with the mortality and survival properties of a cohort to estimate the actual rate of aging (Müller et al.

2004). In zoology, its application has traditionally been restricted to experimental animals reared in a captive environment (most insect studies), or based on mark-recapture methods of wild populations where the target taxa are large enough to be easily tracked and recaptured

(e.g. vertebrates) (Udevitz and Ballachey 1998). However, with modification, the life-table can be used for age estimation of unknown age, wild individuals of any size using the captive cohort method (Müller et al. 2004, Muller et al. 2007). This method is based on combining information from a captive and reference cohort: where the captive cohort consists of adult individuals captured from the wild at unknown age, returned and held under constant laboratory conditions, and whose time of post-capture death is then recorded; and the reference cohort consists of known age adult individuals held under the same laboratory conditions as the captive cohort to record whole lifespan (Muller et al. 2007, Carey et al. 2008, Carey et al. 2012,). It has been demonstrated that the age distribution of the wild population can be estimated from the death distribution of those individuals in the captive environment (Müller et al. 2004, Muller et al.

2007, Carey et al. 2008). According to Vaupel (2009), if an individual can be captured from a stationary population according to their abundance, and their mortality only depends on age,

Chapter 1: General introduction and literature review then age distribution is equal to the death distribution and the former can be predicted by the latter.

1.4.4 Application of demographic approach for age estimation of wild insects

The demographic method has been applied to study seasonal changes in age-structure in wild populations in a limited number of temperate and Mediterranean insects (Carey et al. 2008,

Carey et al. 2012, Behrman et al. 2015, Papadopoulos et al. 2016). For example, the age- structure of wild C. capitata in Greece was estimated using post-capture mortality data from approximately 4000 wild individuals over three field seasons and showed that major changes in population age-structure occurred in the wild population, with middle-age and older flies predominant during all seasons (Carey et al., 2008). The spring population was relatively older than the summer and autumn populations, which coincided with the availability of host fruits, the main driver of C. capitata populations on Chios Island, the study site (Papadopoulos et al.,

2001; Carey et al., 2008). Post-capture longevity of wild C. capitata was also used to infer changes in age-structure during a three-month field season in Volos, Greece. The study demonstrated that the early population of C. capitata was extremely long-lived (>200 days in longest lived), but the late season population was short-lived with a reduction of mean longevity to around 50–75 days. The shorter-lived flies in late autumn indicated seasonally driven mortality and the absence of long-lived individuals indicated cessation of fly emergence in the late season (Carey et al., 2012). This type of demographic study has not been applied to tropical insect species.

The accuracy of age estimation of wild insects using the demographic approach largely depends on capturing individuals from the field without age-bias with respect to their proportional representation within the age-structured population (Muller et al. 2007, Carey et al. 2008).

However, the trapping methods used to capture wild insects may be affected by changes in the

Chapter 1: General introduction and literature review physiology and behaviour of an insect with age. Thus, for an accurate age estimation, understanding the potential or real trapping bias is important (Kouloussis et al. 2009). The following section covers the literature on how insect olfaction is affected by age, as olfactory based trapping is the methodology used in my thesis to collect wild individuals.

1.5 AGING EFFECTS ON OLFACTORY RESPONSE OF INSECTS

Olfaction is central to many of the important behavioural activities of insects, such as finding hosts for shelter and food, locating mating and oviposition sites, and avoiding natural enemies

(Wyatt 2014, Lebreton et al. 2017). An insect’s olfactory response to odours is affected by intrinsic physiological factors such as nutritional status, mating status, state of sexual maturity, and age (Gadenne et al. 2016, Jin et al. 2017, Reyes et al. 2017, Lemmen-Lechelt et al. 2018).

For example, insects that are deprived of food generally have a higher attraction to food odours

(Wäckers 1994, Díaz-Fleischer et al. 2014). Mating status also affects an insect’s attraction to volatiles (Jang 1995, Gadenne et al. 2016, Jin et al. 2017, Crava et al. 2019). For instance, virgin insects are more responsive to odour from mating sites and partners (Aluja et al. 1993,

Jin et al. 2017, Sollai et al. 2018), however, after mating, females’ attraction switches to host- odours or oviposition substrate cues (Gadenne et al. 2016, Jin et al. 2017).

Age is one of the important intrinsic factors which strongly affects the olfactory responses of insects (Gadenne et al. 2016). In insects, age-related changes in olfactory responses are linked to the level of sexual maturation, as well as senescence or aging (Martel et al. 2009, Gadenne et al. 2016). Insects sensitivity to certain odours may increase with age, for example, females of the blowfly, Phormia regina Meigen, show increasing olfactory sensitivity to swormlure-4 and 1-hexanol during the first week of adult life (Crnjar et al. 1990). In contrast to increasing olfactory sensitivity, an insect’s response to odours can be negatively affected by aging (Iliadi

Chapter 1: General introduction and literature review and Boulianne 2010, Gadenne et al. 2016). For example, Anastrepha obliqua (Macquart) antennal responses to male lure and host fruit volatiles were observed until 20 days of age and it was found that older flies exhibited lower antennal response compared to younger flies

(Reyes et al. 2017). Additionally, some experiments demonstrate that the olfactory responses diminish with aging in flies regardless of the source of odours (Cook-Wiens and Grotewiel

2002, Tamura et al. 2003). Such a reduction of olfactory response might be caused by the developing defects in the olfactory system and associated parts of the brain, as well as defects in locomotor activity (which allow the fly to physically orientate to an odour source) with aging

(Cook-Wiens and Grotewiel 2002).

Surveillance and management of many of the world’s pest insects, including tephritids, relies on the use of olfactory attractants (Aluja 1996, Koyama et al. 2004, Shelly et al. 2014). While it is known that an insect’s response to odours can change with age, and in many cases may be negatively affected by increasing age (Martel et al. 2009, Gadenne et al. 2016), there is very limited research evaluating bias in trapping using olfactory attractants (Kouloussis et al. 2009).

While for the Dacini age-related response of males to male-lure (e.g. cue-lure, methyl eugenol, zingerone) have been researched for some species, most such studies stopped when the flies became sexually mature (Wong et al. 1991, Metcalf and Metcalf 1992, Weldon et al. 2008,

Kamiji et al. 2018). Only Fitt (1981) continued well into the life of a fly, detecting no change in the response of Bactrocera opiliae (Drew & Hardy) to methyl eugenol after 12 weeks of age.

Along with olfaction, aging also can strongly influence many other behaviours and physiological activities in insects; for instance, reproductive activities, motor activities, learning and memory (Grotewiel et al. 2005, Iliadi and Boulianne 2010, Gadenne et al. 2016).

Chapter 1: General introduction and literature review

Understanding how age affects the reproductive potential of insects is crucial to predict demographic changes of a wild population (Cole 1957, Charlesworth 1994). In the following section reviews how age of male and females, and their mating partners’ ages, affects reproductive success.

1.6 REPRODUCTIVE AGING IN INSECTS

1.6.1 Reproductive aging in female insects

Fecundity and fertility are considered quantitative parameters of female reproductive success which continuously change with age (Novoseltsev et al. 2003, Novoseltsev et al. 2005, Iqbal et al. 2016). In general, both fecundity and fertility peak in young females, and then decline thereafter (Túler et al. 2018). For example, egg production of Drosophila reaches a maximum at only four days after emergence, after which it steadily declines reaching its lowest level at

50 days (David et al. 1975). Decrease in daily fecundity may be caused by both a reduction in cellular division and an increase in the egg resorption frequency (David et al. 1971). Besides fecundity, fertility of Drosophila females also shows a consistent decline as flies age (David et al. 1975, Novoseltsev et al. 2004).

The physiology and behaviour of female flies also change significantly as a result of mating, leading to reduced female longevity and future fertility. Reproductive decline in older females may also happen due to males ceasing to court and mate older females due to a decreased attractiveness of the female due to aging (Kuo et al. 2012). Females may also stop mating and egg laying prior to death because of deteriorated physiological state (Klepsatel et al. 2013).

Chapter 1: General introduction and literature review

1.6.2 Reproductive aging in male insects

In males, the quantity and quality of sperm and mating activities are considered measures of reproductive success, and both have been observed to be affected by age (Johnson and

Gemmell 2012, Sasson et al. 2012, Herrera‐Cruz et al. 2018). With ageing, the quantitative reduction of sperm is observed in many insects, such as in virgin males of Aedes aegypti

(Linnaeus) where the number of sperm was highest at 10 to 20 days of age and then declined thereafter. In some cases, the number of sperm does not change with age, but their fertility declines (Harwood et al. 2015). For example, females of Anastrepha ludens (Loew) mated with

60-day old males had low egg hatch rate due to a reduction in the sperm quality of old males

(Harwood et al. 2015).

The negative effects of age on male fertility may be due to behavioural, as well as physiological changes. Additional to declines in sperm quantity and quality, male reproductive activities such as number of matings, mating latency and copula duration are also affected by age (Johnson and Gemmell 2012, Ruhmann et al. 2018, Rodríguez-Muñoz et al. 2019). The mating frequency and ability to inseminate females starts to decline in A. ludens at 30 days (Abraham et al. 2016). Additionally, females may choose young males not just because of their greater fertility, but also lower germline mutation rate (Beck and Promislow 2007).

In contrast to reduced fertility and reproductive fitness with aging, some insects show an opposite pattern (Prathibha et al. 2011, Verspoor et al. 2015). For example, in Drosophila ananassae Doleschall females mated with older males had greater fertility compared to females mated with young and middle-aged males (Prathibha et al. 2011). Additionally, in some species, older males demonstrate greater mating frequency, higher insemination rate and fertility than younger counterparts (Prathibha et al. 2011, Somashekar and Krishna 2011,

Chapter 1: General introduction and literature review

Verspoor et al. 2015). For example, age-related change in mating behaviours in a short-lived damsel fly, Coenagrion puella Linnaeus, showed that male and female mating rate did not decline with age (Hassall et al. 2015).

1.6.3 Effect of mating partner age on reproductive potential of insects

The age of a mating partner is known to affect the reproductive success of their partner and many insects prefer to mate with a partner of specific age (Avent et al. 2008, Verspoor et al.

2015, Liang et al. 2019). Age-related variation in quantity and quality of sperm has a profound impact on female fertility (Jones and Elgar 2004, Avent et al. 2008, Liu et al. 2011). For example, females of the hide beetle, Dermestes maculatus De Geer, mated with very young (1 week) and very old (13 week) old age partners suffered from decreases in fecundity and fertility

(Hale et al. 2008). Thus, females prefer to mate with specific age males which can enhance their fertilization and offspring production, or fitness of their progeny (Avent et al. 2008,

Verspoor et al. 2015); although there are a few exceptions when females do not receive fitness benefits from mating with preferred-age partner (Lai et al. 2020). What age groups of males or females are more preferred is not fixed, rather it varies with species (Liu et al. 2014, Verspoor et al. 2015, Ekanayake et al. 2017a). Some females prefer to mate with young males, such as in the case of A. ludens (Herrera‐Cruz et al. 2018), while others prefer to mate with middle-age males such as Colaphellus bowringi Baly (Liu et al. 2011).

The hypothesis of why females generally prefer younger over older males is that young males are more fertile and have less deleterious mutations in the germline, while older males may also suffer from reduced reproductive fitness because of energetic investment trade-offs to survival and early-life reproduction (Beck and Promislow 2007). However, there is an opposite hypothesis which proposes that older males might be superior to younger males as they have

Chapter 1: General introduction and literature review proven survival ability which is an indicator of high genetic quality. Additionally, older males may have a higher number of sperm stored and may invest more in reproduction due to reduced remaining lifespan (Avent et al. 2008). There is some evidence in the literature where females show preference for older males and when mated those females benefited from receipt of a large amount of sperm, greater fertilization rate and increased offspring production. As examples, Drosophila pseudoobscura Frolova, Drosophila bipectinata Duda and Drosophila subobscura Collin were all observed to preferentially mate with older males and acquired direct benefits through higher fertilization rates (Avent et al. 2008, Somashekar and Krishna 2011,

Verspoor et al. 2015).

Male age not only affect the fertility of the female partner, but also her longevity. Females of

Ophraella communa LeSage mated with older mating partners lived longer than females paired with younger males (Zhao et al. 2017); while females of D. bipectinata mated with old males had shorter life spans compared to females that mated with young and middle-age partners

(Somashekar and Krishna 2011).

Similar to males, the quality of females may also change with age and males may prefer to mate with females of a certain age to maximize their reproductive output (Pandey 2013, Liu et al. 2014, Shi et al. 2018). For example, C. bowringi and Zygogramma bicolorata Pallister males preferred middle-age partners (Pandey 2013, Liu et al. 2014), while Acanthoplus discoidalis (Walker) males preferred young females (Bateman and Ferguson 2004).

While mating-partner age is known to affect the reproductive success of the opposite partner, most studies focus on testing the effects in a competitive environment with particular age- groups of insects (Tamura et al. 2003, Jones and Elgar 2004, Avent et al. 2008, Liu et al. 2011),

Chapter 1: General introduction and literature review with only a few considering lifelong studies (Hale et al. 2008, Ruhmann et al. 2018). However, age-based competitive experiments may be problematic to interpret as contrary results can be obtained in non-competitive environments. For example, in a competitive environment C. capitata males show a dramatic decline in mating probability with increasing age, while in a non-competitive environment older males still demonstrated the potential to produce offspring and mating probability declined much more gradually with increasing age (Papanastasiou et al.

2011).

1.7 INTRODUCTION TO STUDY INSECT

Bactrocera tryoni (Froggatt) (Diptera: Tephritidae), is a polyphagous insect pest, laying eggs into fruit of more than 40 plant families (Hancock et al. 2000). The species historical endemic range is considered to be the tropical and subtropical coastal regions of eastern Australia (May

1953, Drew et al. 1984). However, in the last 100 years it has extended its geographic range southward and is currently established in temperate New South Wales and most of Victoria

(Fletcher 1979, O'loughlin et al. 1984, Dominiak and Mapson 2017). Bactrocera tryoni is multivoltine (= multiple generations per year), with the annual generation number for a given location thought to be determined by climatic factors, especially temperature (Meats 1981).

Moisture availability is thought to limit the expansion of the fly into inland Australia (Sultana et al. 2017). Based on bio-climatic data, in tropical and subtropical Australia B. tryoni is modelled as being able to have up to eight generations per year (Meats 1981, Yonow & Sutherst

1998), but in areas with a cold winter such as Victoria, only three to four generations are thought possible in a year (Fletcher 1979, O'loughlin et al. 1984). In temperate Australia sexual activities of adult flies cease during late autumn and they remain inactive until spring, the breeding cessation traditionally correlated with cold winter temperatures (Bateman 1968,

Fletcher 1975, Fletcher 1979). In subtropical and tropical regions, B. tryoni populations show

Chapter 1: General introduction and literature review population fluctuation throughout the year with low abundance during late autumn and winter, but then with rapid population growth during early to late spring, reaching a maximum population level in summer (Muthuthantri et al. 2010).

My thesis focuses predominantly on the demography of B. tryoni, and the following sections cover the literature pertaining to its population growth, seasonal phenology and reproduction, as well as what is known about its olfactory response in relation to trapping and fly age.

1.7.1 Role of abiotic and biotic factors on B. tryoni population growth

The rate of B. tryoni population growth is directly influenced by the level of reproduction within a population (May 1961, Sutherst and Yonow 1998). As for nearly all other Diptera, B. tryoni is a bisexual species which requires male/female mating for reproduction. After emergence from the pupal stage the adults are sexually immature and so minimum nutritional, physiological and environmental conditions are required to allow sexual maturation and mating which occurs within two to three weeks in wild (Dalby‐Ball and Meats 2000) and 10-12 days in the laboratory (Meats and Khoo 1976, Taylor et al. 2013).

Based on work done in temperate Australia, temperature is considered the most important abiotic factor affecting time to sexual maturation and mating of B. tryoni (Pritchard 1970,

Fletcher 1975). Maturation of B. tryoni ovaries is influenced by the ambient temperature and the required degree day accumulation above a minimum threshold temperature of 13.5 °C

(Fletcher 1975, Meats and Fay 1976). Additionally, in already mature females, egg production may be stopped, slowed, or even reversed (through resorbing eggs into the body) at lower or

(more rarely) extreme higher temperatures: when temperature again becomes favorable, egg maturation restarts (Fletcher 1975, Meats and Khoo 1976). Winter temperatures in temperate

Chapter 1: General introduction and literature review

Australia not only reduce egg production by females, but also reduce sperm utilization and during mid-winter fertilization may be completely stopped. Given these physiological impacts, in temperate Australia B. tryoni breeding is dramatically reduced during the winter months due to lack of required temperature thresholds for the ovarian maturation and mating (Pritchard

1970, Fletcher 1975, Meats and Fay 1976). Additionally, during winter when temperature is below the mating threshold (~16 °C), male flies remain inactive and so females don’t have the opportunity to remate and refill spermatheca (Fletcher 1975). Females who retain mature eggs during winter can only remate in late winter or early spring when ambient temperatures are again above 16 °C at the time of dusk mating (Fletcher 1975, Meats and Fay 1976).

Host fruit is another critical element for completion of the fruit fly life cycle. Females oviposit into the host fruit where the resultant larvae feed and grow. Thus, continuation of the life cycle exclusively depends on availability of suitable host-fruits (May 1958, May 1961). Queensland fruit fly is highly polyphagous and lays into fruit of more than 20 plant families (Hancock et al. 2000). However, females prefer to oviposit on certain host fruits over others, which can enhance the larval performance (Balagawi 2006). Additionally, females prefer to lay eggs in mature and ripe fruits over the unripe fruit (Eisemann 1980) and show strong attraction to fully ripe host fruit odours (Cunningham et al. 2016). Because of direct need for fruit for larval development, there is an intimate association between the availability of suitable host fruits for larvae and the abundance of adult fruit flies (Leblanc and Allwood 1997). While in tropical and subtropical regions B. tryoni population abundance is known to fluctuate with the availability of host fruits (Drew et al. 1984, Muthuthantri et al. 2010), even in temperate regions where temperature is a major limiting factor for population growth, the abundance of flies during favourable seasons is influenced by host abundance and quality (Fletcher 1974, Clarke et al. 2019, van Klinken et al. 2019).

Chapter 1: General introduction and literature review

Rainfall is another factor that affects the population growth of B. tryoni (Sultana et al. 2017) as well as several other tephritid pest species (Tan and Serit 1994, Amice and Sales 1997,

Muthuthantri et al. 2010). Along with temperature, moisture is important for growth and survival of B. tryoni because extremely dry conditions can reduce female fecundity up to 17% and matured larvae and newly emerged teneral flies may die (O’Loughlin 1964, Bateman

1968b, Hulthen and Clarke 2006). Additionally, dry weather can limit plant growth, reducing tree fruiting and promoting the drop of immature fruits, hence reducing the opportunity for egg laying, hatching and larval growth (Bateman 1968, Dominiak et al. 2006). Thus, the abundance of fruit fly is known to be influenced by moisture; during wet years it has higher abundance and lower abundance in low rainfall years (Bateman 1968).

1.7.2 Seasonal phenology of B. tryoni

1.7.2.1 Seasonal phenology in temperate region

In temperate Australia B. tryoni populations show a distinct seasonal peak in late summer/early autumn and the population abundance remains very low during winter (Bateman 1968, Fletcher

1975, Clarke et al. 2019). The low population abundance during winter is linked to reduce breeding activities as described above. Although, rainfall and environmental moisture are known to affect population growth, temperature is considered the major driver of the seasonal phenology of B. tryoni in temperate Australia (Bateman 1968, Pritchard 1970, Fletcher 1975,

Yonow et al. 2004).

Several years of trap catch data of B. tryoni from an orchard near Wilton (Sydney Basin) showed distinct peaks of adult flies’ number in September, December, and late February

(Bateman 1968, Fletcher 1974). Fletcher (1974) showed that the population had a small peak in population abundance in September and October, which was thought to be the F1 generation

Chapter 1: General introduction and literature review of the overwintered population. Following this, the population abundance reached a second peak during early summer when the F1 progeny of the overwintering population matured.

During summer, availability of good quality hosts again dramatically increased fruit flies number lead to the highest level of trap catches at the end of the season. After that the number of trapped males declined steadily and reached a minimum during the winter months (Fletcher

1974). The male flies that emerged during autumn failed to attain sexual maturity due to cold weather, and already matured flies remained sexually inactive (Fletcher 1973, Fletcher 1974).

1.7.2.2 Seasonal phenology of B. tryoni in tropical and subtropical region

Unlike temperate regions, in the tropics temperature fluctuates less during the year and modelling predicts that B. tryoni breeding should be continuous throughout the year if breeding hosts are available (Meats 1981, Sutherst and Yonow 1998, Yonow et al. 2004). Depending on temperature, a predominantly temperature driven CLIMEX model predicted more than six and more potential generations of B. tryoni in tropical and subtropical eastern Australia (Sutherst and Yonow 1998), an almost identical result to the predictions of an earlier B. tryoni phenology model developed by Meats (1981). However, although temperatures are not limiting, B. tryoni population still shows a typical temperate phenology in tropical Australia, with winter month depression and populations rebuilding in the spring (Lloyd et al. 2010, Muthuthantri et al.

2010). As breeders in the fruits of tropical forests (Drew 1989), B. tryoni’s native hosts are seasonally restricted because of monsoon driven flowering and fruiting (Sakai et al. 1999).

Muthuthantri et al. (2010) analyzed a large historical (1940s and 1950s) B. tryoni trapping dataset from nine sites across Queensland. This data shows a clear pattern of fluctuation of B. tryoni population abundance, the population of Q-fly reducing significantly during autumn and winter, then increasing dramatically in early spring, before reaches a peak level in late spring and summer. A similar pattern of autumn and winter decline, with a rapid August increase, was

Chapter 1: General introduction and literature review also reported for B. tryoni from the Central Burnett district of south-east Queensland (Lloyd et al. 2010). Muthuthantri et al. (2010) further report that B. tryoni had a unimodal pattern of abundance in Cairns, Atherton, Rockhampton and Toowoomba, with an exponential increase in population abundance in mid- to late-spring then reducing over summer and reached at bottom level in autumn and winter. Similar increases in the spring population were also reported from Ayr, Maryborough and Sunnybank, but these sites had two or more population peaks in the annual spring to autumn cycle. In contrast, B. tryoni populations in Gatton and

Stanthorpe exhibited slower population increase after overwintering which gradually increased during spring and summer and reached the highest level during late summer/early autumn, and again decrease through winter: this is a typically temperate population pattern (Yonow et al.

2004), and reflects the fact that Stanthorpe (which is at high altitude) has a temperate climate

(Clarke et al. 2019). Importantly, for most tropical and subtropical sites, Muthuthantri et.

(2010) detected no correlation between B. tryoni abundance and temperature or rainfall.

1.7.2.3 Drivers of seasonal phenology of B. tryoni in tropical region

While, in temperate regions, fruit fly phenology is clearly shown to be driven by temperature, what drives the phenology pattern of B. tryoni in tropical and subtropical regions is less clear.

Temperature and rainfall were reported to have less impact on the tropical phenology of B. tryoni than the availability of host fruits and fly dispersion (Drew et al. 1984). Muthuthantri et al. (2010) concluded that B. tryoni phenology in its endemic range is primarily driven by host fruit availability. However, a recent study showed only partial correlation between host fruit availability, temperature and B. tryoni’s overwintering phenology in sub-tropical Australia.

The study concluded that there might be other, unrecognized physiological and behavioural mechanisms influencing B. tryoni phenology in regions where temperature is not limiting

(Merkel et al. 2019).

Chapter 1: General introduction and literature review

Although much research has been conducted on B. tryoni phenology and its drivers, there is no study which investigates the changes in the demographic structure of a B. tryoni population over seasonal time. Changes in demographic structure of an insect population is a consequence of the dynamics of the birth and death rate over seasonal time and this can help to understand the population dynamics of wild populations (Schaeffer Pedrotti et al. 2019).

1.7.3 Olfactory response of male and female B. tryoni

The males of many Dacini species show strong, positive attraction to a small group of plant- derived phenylbutanoids and phenylpropanoids, or their synthetic analogues. These “male lures”, the best known of which are methyl eugenol and cue-lure, have been the mainstay of dacine monitoring and control for many decades (Metcalf and Metcalf 1992, Shelly 2010,

Kumaran et al. 2013). Cue-lure [4-(p-acetoxyphenyl)-2-butanone] is the most widely employed male lure for B. tryoni field monitoring, quarantine surveillance, and lure-and-kill control (= the male annihilation technique) (Lloyd et al. 2010, Stringer et al. 2017). Bactrocera tryoni male attraction to cue-lure increases with age and reaches a maximum when males become sexually mature (Weldon et al. 2008). Consumption of protein increased lure attraction in young males, related to the earlier sexual maturation of those flies after protein exposure

(Weldon et al. 2008). In contrast, very early exposure of immature males to raspberry ketone

(a cue-lure analogue) subsequently supressed the male lure response (Akter et al. 2017b).

Biologically, male attraction to cue-lure is related to sexual maturation and mating activities

(Weldon et al. 2008, Kumaran et al. 2013, Kumaran et al. 2014a). Consumption of cue-lure increases male mating success and mating frequencies by enhancing the pheromone calling of males and making the males more active (Kumaran et al. 2013, Kumaran et al. 2014a, Kumaran et al. 2014b). Females mated with lure-fed males had higher fecundity and increased remating inhibition (Kumaran et al. 2013).

Chapter 1: General introduction and literature review

Female B. tryoni are only rarely attracted to cue-lure (Weldon et al. 2008) but are strongly attracted to host-fruit odours (Eisemann and Rice 1992, Ero et al. 2011). Female attraction to host-fruit odour is closely linked to their oviposition activities (Prokopy et al. 1991, Eisemann and Rice 1992). Due to the close association of female fruit flies with fruit, there is a growing international effort to develop female traps based on host-fruit odours (Cunningham et al. 2016,

Mas et al. 2020). Several studies have demonstrated that female Dacini are more attracted to ripe than unripe fruit (Alagarmalai et al. 2009, Rattanapun et al. 2009, Cugala et al. 2014), and while this is also assumed for B. tryoni there is little published evidence. However, a series of behavioural experiments to fruit ripening volatiles by B. tryoni exhibited that sexually mature male and female flies both had strong attraction to the volatiles of fully-ripe guava over other three less-ripe stages. The results also showed that the volatiles of fully ripened guava fruits contained large amounts of the esters ethyl acetate, ethyl propionate, and ethyl butyrate and that female flies were attracted to a blend of these three volatiles (Cunningham et al. 2016).

Multiple studies have investigated the effect of ageing on male and female response to male- specific lures and host-fruits odour respectively till the sexual maturation (Metcalf and Metcalf

1992, Weldon et al. 2008, Cunningham et al. 2016). While it is known that the olfactory response of many insects negatively affects by aging (Iliadi and Boulianne 2010, Gadenne et al. 2016) and trap catches using olfactory attractants may lead to bias in capture certain aged insects (Kouloussis et al. 2009), but how advanced age affect the olfactory response of both sexes of B. tryoni is completely unknown. Additionally, investigation about male’s response to host-fruits odour in relation to age also worth to know which has been largely ignored in both basic and applied field of studies.

Chapter 1: General introduction and literature review

1.7.4 Reproductive potential of male and female B. tryoni

Bactrocera tryoni become sexually mature within 10-12 days after emergence from the pupa.

Females mate only once or a few times in their lifetime depending on the quality of males (Fay and Meats 1983). Like other insects, B. tryoni females have the capacity for the long-term storage of sperm in the spermatheca. Once females are mated, they can fertilize their eggs for seven weeks (Perez‐Staples et al. 2007). In contrast to females, males can mate multiple times in their lifetime and, if mating occurs over consecutive days, they have the ability to transfer a constant amount of sperm at each mating event (Radhakrishnan et al. 2009).

The reproductive potential of B. tryoni is affected by several factors, including nutritional status, age, size, and mating experience. Among these factors, the effect of diet on male sexual development and reproductive potential has been paid much attention because of the need to produce competitive flies for SIT (Perez-Staples et al. 2007). Most of the studies on B. tryoni reproductive potential have involved testing the effects of different diet supplements for enhancing sexual performance and competitiveness of mass-reared flies. From such studies it is known that feeding on protein increases the mating probability of sterile males (Perez‐Staples et al. 2008, Pérez-Staples et al. 2009), as does feeding males with raspberry ketone, sugar and yeast (Akter et al. 2017a).

Age-related studies on the reproductive potential of B. tryoni has been given less attention.

Female fecundity increases with age to a peak daily production at four to five weeks of age, thereafter declining and reached at lowest level at eight (Kumaran et al. 2013) and 10 weeks of age (Fitt 1990). Males provided with a young mating partner every week did not show any decline in mating frequency until seven weeks post-maturation and mated males secured equal mating number of mating as virgin males in a non-competitive environment (Fay and Meats

Chapter 1: General introduction and literature review

1983). However, in a competitive environment, young (14 days) and experienced males achieved more mating success than old (28 days) and virgin males (Ekanayake et al. 2017a).

1.8 THESIS OUTLINE

Although the previous literature review has identified that much research has been conducted to document the phenology of B. tryoni in its endemic range, deeper assessment of any demographic changes associated with changing phenology remain absent except for studies on overwintering B. tryoni populations in their invasive range in temperate Australia (Fletcher

1975). To fill this gap, my thesis focuses on the demography of wild Queensland fruit fly populations in subtropical Australia, with a focus on methodology development and validation, the collection and analysis of population data using the demographic method and focusing on age-structure estimation (Muller et al. 2007, Carey et al. 2008), and then an assessment of the impact of age on B. tryoni reproductive capacity. My thesis is presented in six chapters. This first chapter provides the background literature review for the thesis, the 2nd to 5th chapters are experimental chapters, while the general discussion chapter integrates the experimental findings and discusses their implications both for B. tryoni and more broadly for our understanding of the demography of tropical insects.

The accuracy of age-structure estimation depends on capturing wild flies without age-bias

(Carey et al. 2008, Kouloussis et al. 2009). Because I collected wild flies using volatile-based traps, this may have biased results if the response to those attractants changed over the life of a fly. This was of particular concern as some previous literature with other insects has found that the olfactory response to odours can diminish with age (Iliadi and Boulianne 2010,

Gadenne et al. 2016). This led to the design of the first (Chapter 2) and second (Chapter 3) experimental chapters of my thesis.

Chapter 1: General introduction and literature review

Cue-lure is the most commonly used lure for trapping B. tryoni males (Lloyd et al. 2010,

Stringer et al. 2017). However, females are rarely attracted to cue-lure (Weldon et al. 2008) but are attracted to host fruit odours (Eisemann 1980, Cunningham et al. 2016). While there is research on B. tryoni male response to cue-lure, and female response to host fruit odours, none of these studies examine attraction after flies become sexually mature, i.e. the studies focus on attractant response from adult emergence to maturation, but then stop. This was considered a particular issue for my thesis, as B. tryoni has the capacity to be a very long-lived insect

(Chapter 4 results), but its olfactory capacity for most of its life is entirely unknown. Thus,

Chapter 2 of my thesis examines how age, post sexual maturation, affects the olfactory response of male and female B. tryoni to cue-lure and host-fruit odour, respectively. At time of thesis submission this chapter is published online (but not yet in paper format) in the Journal of Insect Physiology.

In developing trapping techniques to capture wild flies for Chapter 4, I trialled fruit-based traps which used the volatiles emitted from freshly crushed fruit as the attractant. This was planned as a method to trap females, but to my surprise these traps attracted almost exclusively male flies. Subsequent reading of the literature shows that while there is evidence that males of several species of Dacini fruit fly are attracted to host-fruits odour, including B. tryoni (Clarke and Dominiak 2010, Cunningham et al. 2016), this finding has been largely ignored in the field of behavioural and applied tephritid research. In Chapter 3 I report the comparative results of trapping males at fruit-based traps versus male at cue-lure traps, and in line with the age-bias issue addressed in Chapter 2 I record male response to fruit-derived odours over their life (from pupal emergence to 15 weeks). The results of Chapter 3 are presented succinctly, with the emphasis of the chapter placed not so much on the specific results, but rather on making the broader point that male Dacini response to fruit odours occurs at a level too great to be

Chapter 1: General introduction and literature review continuously ignored in the literature. At time of thesis submission this chapter is in press with the Journal of Economic Entomology, but not yet publicly available.

My third, and major experiment (Chapter 4), was designed to determine the age-structure of B. tryoni populations during the year, concentrating particularly where literature reports that there are marked changes in population abundance, i.e. early autumn (when the population is large and I predict will have a mix of young, middle age and old age flies); late autumn (as population size declines and I predict will have middle to old age flies); late winter to early spring (when overwintering flies start to become active and I predict they will be mostly very old); and finally early summer (when the population grows rapidly and I predict will have mostly young and middle-age individuals). To estimate the age of wild populations I followed, with modification, the demographic approach of Carey and colleagues (Carey et al., 2008; Muller et al., 2007) which involves collection of mortality data from two cohorts of live flies maintained in the laboratory: one the ‘captive cohort’ of wild flies captured from the field at an unknown age, the other the ‘reference cohort’ consisting of known-age individuals that emerge in the laboratory from wild infested fruits. The captive flies were caught in the field using cue-lure and tomato-based traps. Due to methodological constraints, it was hard to capture females and all studied flies were males. At time of thesis submission, this chapter is under review with the journal Scientific Reports.

The results of Chapter 4 showed that the age-structure of Queensland fruit fly populations changes predictably with season, with a maximum of three generations per year, not six to eight are previously modelled. Notably, and as hypothesised, the late winter and early spring population contained a very large proportion of very old individuals. As these flies become the parental (F0) generation for the new season’s population, I was particularly interested in

Chapter 1: General introduction and literature review understanding their reproductive capacity. In Chapter 5, I carry out a whole-of-life fertility experiment, evaluating the effect of age on reproductive potential of males and females in a non-competitive environment when paired with a continuously young or same-age mating partner. Biologically, this was to provide insights into what would be the reproductive outcome if an old F0 male, or old F0 female, had the opportunity to mate with a young (F1) or old (F0) partner at the beginning of spring. Female reproductive potential was directly measured by egg and hatch-rate counts, while male fertility was indirectly measured by an assessment of the egg hatch-rate of the female paired with the male every week. At time of thesis submission, this chapter is under review with the Journal of Insect Physiology.

The last chapter (Chapter 6) brings all the chapters’ findings together to conclude how seasonal changes in environment and aging affect the demography, life history and biology of

Queensland fruit fly. The discussion is extended beyond B. tryoni to look at the broader theoretical and applied implications of this kind of research for other tropical insects.

Chapter 2: Effect of advanced age on olfactory response of male and female B. tryoni

Chapter 2: Effect of advanced age on olfactory response of male and female Bactrocera tryoni

This chapter has been published as:

Tasnin, M. S., K. Merkel, and A. R. Clarke. 2020. Effects of advanced age on olfactory response of male and female Queensland fruit fly, Bactrocera tryoni (Froggatt) (Diptera:

Tephritidae). Journal of Insect Physiology 122: 104024.

All authors discussed the design and logic of the experiment, TMS carried out the experimental work, TMS and KM carried out data analysis and all authors helped interpret the data, TMS wrote the first draft, all authors worked on subsequent drafts, all authors approved the manuscript.

Chapter 2: Effect of advanced age on olfactory response of male and female B. tryoni

2.1 INTRODUCTION

For insects, olfaction is an essential sensory modality for the perception of stimuli from the environment (Krieger and Breer 1999, Touhara and Vosshall 2009). Olfaction plays a key role in behaviours such as the location of food, mates and oviposition substrates, as well as enemy avoidance (Wyatt 2014, Lebreton et al. 2017). An insect’s response to odours may vary depending on physiological factors such as feeding and nutritional status, mating status and sexual maturation (Gadenne et al. 2016, Jin et al. 2017, Lemmen-Lechelt et al. 2018). For example, insects that are deprived of food generally have a higher attraction to food odours

(Wäckers 1994); while virgin insects are more responsive to odours from mating sites and partners than are mated insects (Jin et al. 2017, Sollai et al. 2018). An individual’s age is another factor that strongly affects the odour response of an insect (Gadenne et al. 2016, Reyes et al. 2017).

In insects, age-related changes in olfactory responses are linked to sexual maturation, as well as ageing (Martel et al. 2009, Gadenne et al. 2016). For example, in early life, insects are more attracted to food odours while, after sexual maturation, they may be more attracted to cues from mating partners (Klowden 1990). Additionally, an insect’s response to the same odour may change with age, for example, females of the blowfly, Phormia regina Meigen, show increasing olfactory sensitivity to swormlure-4 and 1-hexanol during the first week of adult life

(Crnjar et al. 1990). In contrast to increasing olfactory sensitivity, an insect’s response to odours can be negatively affected by ageing once past some optimal age (Iliadi and Boulianne

2010, Gadenne et al. 2016). For instance, the antennal olfactory sensitivity of tsetse flies,

Glossina morsitans morsitans Westwood, to various tested volatiles started declining after only five days of age (Otter et al. 1991), while the perception of aversive odours diminished in eight week old Drosophila melanogaster Meigen (Cook-Wiens and Grotewiel 2002). For D.

Chapter 2: Effect of advanced age on olfactory response of male and female B. tryoni melanogaster, Cook-Wiens and Grotewiel (2002) attributed the reduction of olfactory response with increasing age to both the development of age-related defects in the olfactory system and associated parts of the brain, as well as a decline in locomotor activity.

Tephritid fruit flies (Diptera: Tephritidae) are globally significant insect pests of agriculture, affecting most horticultural crops (Norrbom et al. 1999). Female fruit flies oviposit into host fruits, where resultant larval feeding causes fruit damage (May 1958, Fletcher 1989, Sutherst et al. 2000b). The behaviour and ecology of tephritid fruit flies are strongly tied to olfaction, including the pheromonal attraction of conspecifics during mating (Landolt et al. 1985, López-

Guillén et al. 2011), location of host fruit by females for oviposition (Eisemann 1980, Jang et al. 1999, Liu and Zhou 2016), and for male tephritids of the tribe Dacini for the location of plant secondary chemicals which are linked to male sexual selection (Raghu 2007, Shelly 2010,

Kumaran et al. 2013). The management of pest tephritids relies heavily on the manipulation of this chemical ecology, using olfactory attractants for surveillance and lure-and-kill controls

(Aluja 1996, Koyama et al. 2004).

Despite the implications for management, and simply for better understanding tephritid biology, studies of ageing and changing olfactory responses in tephritids are limited. Multiple studies have investigated the effect of ageing from adult emergence to sexual maturity [which occurs on average from 10 to 20 days after emergence, (Clarke 2019)] on the response of male

Dacini to male-specific lures, such as methyl eugenol (ME) and cue-lure (Wong et al. 1991,

Metcalf and Metcalf 1992, Weldon et al. 2008, Kamiji et al. 2018). Most of these studies have found that lure attraction is dependent on the male becoming sexually mature, although in some species males may begin to respond prior to maturation (Wee et al. 2018). Fitt (1981), in the only study of its type, recorded the response of Bactrocera opiliae (Drew and Hardy) to ME

Chapter 2: Effect of advanced age on olfactory response of male and female B. tryoni past sexual maturation and found no change in responsiveness of males up to 12 weeks of age.

Outside of the Dacini male lures, age-related olfaction studies in the Tephritidae are rare. The response of Ceratitis capitata (Wiedemann) to synthetic food attractants was investigated until

40 days of age, where it was shown that sugar-fed flies showed higher response at middle age

(10-25 days age) while protein-fed flies showed higher response at a young age (1-5 days age) with a declining trend afterwards (Kouloussis et al. 2009). For Anastrepha obliqua (Macquart), antennal responses to male lure and host-fruit volatiles were observed until 20 days of age and it was found that older flies exhibited lower antennal response compared to younger flies

(Reyes et al. 2017). While such studies are valuable, and with the exception of the study by Fitt

(1981) for males, there are no studies of which we are aware that evaluate olfactory responses of both male and female tephritid fruit flies to olfactory cues until an advanced age, as has been done for Drosophila (Cook-Wiens and Grotewiel 2002) and other insects (Gadenne et al.

2016). This is despite the fact that some tephritids can be very long-lived (Carey et al. 2008), with Dacini tephritids, the focus of this paper, surviving 11 weeks on average in the laboratory

(Clarke 2019) and over 28 weeks as over-wintering adults (Clarke et al. 2019).

Bactrocera tryoni (Froggatt) (Diptera: Tephritidae) is an Australian endemic insect which is a key pest of the Australian horticultural industry (Sutherst et al. 2000b, Clarke et al. 2011).

Sexually mature Bactrocera tryoni males are attracted to cue-lure [4-(p-acetoxyphenyl)-2- butanone] (Meats and Hartland 1999), while mature females are attracted to volatiles released from ripening host fruits (Eisemann 1980, Cunningham et al. 2016). Cue-lure is widely used for quarantine surveillance, monitoring and field control of B. tryoni (Dominiak et al. 2003,

Lloyd et al. 2010, Reynolds et al. 2016, Stringer et al. 2017), while fruit-based odours are being used as the basis for female traps (Cunningham et al. 2016). Bactrocera tryoni can be long- lived, with some individuals surviving in excess of 20 weeks in controlled laboratory studies

Chapter 2: Effect of advanced age on olfactory response of male and female B. tryoni

(Balagawi 2006), but there is no knowledge of how olfactory responses in the fly change once they become sexually mature, which occurs at approximately 21 days for wild flies (Dalby‐

Ball and Meats 2000).

Given the importance of olfaction in the management of B. tryoni, this study evaluates age- dependant olfactory responses and exploratory activities of the fly from sexual maturity to advanced age (15 weeks). Specifically, we observed the effect of age on olfactory response and exploratory activity of male and female flies in the presence of cue-lure and guava-juice odour, respectively. We hypothesized that: (i) exploratory activities will be higher in younger flies compared to older flies; (ii) the flies’ response to odours will be higher at a younger age compared to old age; and (iii) younger flies will take less time to choose the odour source compared to old flies.

2.2 MATERIALS AND METHODS

2.2.1 Study insect

Bactrocera tryoni used for the experiment were collected from the field, bred from naturally infested fruits. Two cohorts of wild flies were obtained from South-east Queensland (approx.

27○S, 152○E): the first from a collection of 200 mango fruits made on the 5th Feb 2018; the second from a collection of 180 carambola fruits made on the 18th Mar 2018. Infested fruits were placed in plastic containers on a layer of vermiculite and kept in an incubator at 25 ○C and 65 % relative humidity. After two weeks the vermiculite was sieved for pupae. Pupae were placed in 32 x 32 x 32 cm white mesh cages supplied with water. Each evening, flies emerging during the preceding 24hr period were transferred to new holding cages to keep flies separate according to emergence date. The holding cages were supplied with standard diets (water, sugar cubes and yeast hydrolysate ad libitum) throughout the rearing period. Each cage contained

Chapter 2: Effect of advanced age on olfactory response of male and female B. tryoni

200 flies, 100 of each sex to allow for mating. Flies originating from mango and carambola were treated as two separate cohorts for experimental purposes.

2.2.2 Olfactometer bioassay

To observe age-related changes in exploratory activities and olfactory responses, five age- groups (3, 6, 9, 12 and 15 week-old) of male and female B. tryoni were tested. Based on the authors’ unpublished data, and in agreement with Dalby-Ball and Meats (2000), the three weeks old flies can be regarded as newly sexually mature and mated. Male age-related olfaction was tested against 0.1ml undiluted cue-lure, while females were tested against the odour of 1ml of a commercial guava-juice (water + 30% guava [Psidium guava] puree, Golden Circle Ltd,

QLD 4013, Australia) exposed on a petri dish. Guava is a major host of B. tryoni (Hancock et al. 2000) and mature females are highly attracted to ripe guava odours (Cunningham et al.

2016). Dosages of both attractants were based upon preliminary concentration trials which sought to maximise positive fly orientation.

Experiments were conducted using a glass Y-tube olfactometer (Model: CADS-2P, Sigma

Scientific Ltd) with a single odour source (cue-lure for males, and guava juice for females) and a no-odour (blank) control. The olfactometer consisted of a 15 cm long stem and two 10 cm long side-arms (75° angle and 5 cm internal diameter). Side-arms were attached to two sealed glass jars, each 20 cm in depth and 14 cm diameter. An adjustable air compressor pumped airstream at a rate of 2.5 L/minute through a clean air delivery system which was connected separately to both glass jars. A table lamp with white light was placed just above the junction of Y-tube arms to minimise differences in light intensity in the experimental arena. The odour sources were placed in an open petri dish, which was sat within the glass jar of the treatment arm: odour sources were replaced every two hours. The arm of the odour-containing glass jar

Chapter 2: Effect of advanced age on olfactory response of male and female B. tryoni was changed after testing 17 flies (i.e. half of a cohort treatment), at which time the olfactometer was also cleaned with water and 70 % ethanol. A total of 35 flies was tested from each cohort (i.e. mango and carambola) for each age-group, resulting in 70 flies tested for each age-group. In the case of three and six week age-groups, 70 males originating from the carambola cohort only were tested against cue-lure due to a logistic difficulty during the experiment with the mango cohort flies. All tests were conducted in the same, small laboratory room with controlled temperature (26 ± 1 ○C) and constant lighting.

2.2.3 Experimental design

All experiments were carried out using individual flies and, for all experiments, the same procedure was followed. One hour before the experiment started, 35 flies were transferred from their maintenance cage in the insectary and brought to the experimental lab for acclimation.

Flies were individually released at the entrance of the olfactometer stem. The fly’s behaviour in the olfactometer was observed for up to 10 minutes with the variables below recorded. If a fly showed no positive olfactory decision within 10 minutes the trial was terminated. i. Exploratory activity: If a fly moved upwind and crossed the marked halfway point of either side-arm of the olfactometer it was defined as an ‘explorer’ (coded as ‘1’); a fly which did not upwind forage in this way for the 10 minutes of observation was referred as a “non-explorer”

(coded as ‘0’). ii. Olfactory response (explorer): When a fly responded positively to the odour containing arm

(crossed the midpoint of the treatment side-arm) this was recorded as selective orientation

(coded as ‘1’); when a fly went past the midpoint of the control arm this was defined as non- selective orientation (coded as ‘0’).

Chapter 2: Effect of advanced age on olfactory response of male and female B. tryoni iii. Time-to-response: The time taken after release for flies showing selective orientation to reach Y-tube arm with odour source (measured in seconds). These measured variables are illustrated in Figure 2.1.

Figure 2.1. Diagrammatic representation of response variables measured concerning

Bactrocera tryoni foraging in a Y-tube olfactometer. Non-explorer, fly did not cross the midpoint of either olfactometer arm in 10 minutes (dark grey area); Explorer, fly did cross the midpoint of either olfactometer arm within 10 minutes (light grey area); Time-to-response, the time taken by an explorer fly to cross the arm mid-point; Selective and non-selective orientation, the response of an explorer fly to the odour arm or blank control arm, respectively.

Male experiments were conducted between 08:00 to 13:00 hours, because male B. tryoni are most attracted to cue-lure during morning hours (Weldon et al. 2008), while female experiments were conducted from 10:00 to 15:00 hours which is considered the peak window for female oviposition in this species (Ero et al. 2011).

Chapter 2: Effect of advanced age on olfactory response of male and female B. tryoni

2.2.4 Data analysis

All data analysis and visualizations were performed with the R statistical program (Team 2018) and SigmaPlot (Systat Software, San Jose, CA). Male and female data were analysed separately as the sexes were examined against different odours as well as having differences in longevity.

In the experiment, age-group and cohort were explanatory variables, while exploratory activity, olfactory response and time-to-response were response variables. As exploratory activity and olfactory response were recorded as “1” or “0” for an individual fly, the resulting data were binary, while the time-to-response (measured in seconds) was continuous and followed a gamma distribution. Within each gender, generalized linear models (GLMs) were fitted to examine if the olfactory response, exploratory activity and time-to-response of individual flies were affected by the factors age-group and cohort. Age-groups and cohorts were initially fitted to test their interactive and additive effect on the response variables. A stepwise backward elimination approach was applied to determine the minimum adequate model. When a significant effect was detected by the model, a post hoc test was conducted for pairwise comparison of means using the package emmeans (Russell 2018). The comparison tests were performed on the log odds ratio scale for binary data. Additionally, chi-square tests were conducted with the raw data which was the frequency of flies choosing the odour or control.

This test examined if the number of flies choosing the odour source or the control differed from a 1:1 ratio depending on the age of flies. A deviation from a 1:1 ratio within an age-group indicates directed movement, as opposed to a random walk into either arm.

2.3 RESULTS

2.3.1 Effect of age on the male response to cue-lure

GLMs were run with age-groups (excluding weeks 3 and 6) and cohorts to determine their interactive and additive effect on the response variables. In both models, there was no

Chapter 2: Effect of advanced age on olfactory response of male and female B. tryoni significant difference between the cohorts in how the olfactory response in males changed with age. Following this, both models were run with all the age-groups and cohorts which also produced non-significant effects of the cohort for all the response variables. Thus, the cohort was subsequently removed from the models and the following results only focus on the significant explanatory variable; age-group.

The GLMs run with the response variable “olfactory response” showed that age had a significant effect on male response to cue-lure. Subsequently, GLMs were run with

“exploratory activity” and “time-to-response” to determine whether the reduction in olfactory response was related to changes in these parameters. Additionally, chi-square tests were conducted to examine whether reduced olfactory response of males was due to a decline in choosiness for the odour or not. The results of GLMs and chi-square tests are presented below.

2.3.1.1 Olfactory response of male to cue-lure

GLM revealed that, for all flies tested (i.e. explorers + non-explorers), there was a significant difference in the probability of flies positively orientating to cue-lure among the five age- groups [GLM (selective-orientation ~ age-groups, family = binomial), Chi2 = 19.431, Df = 4,

P < 0.001]. The subsequent pairwise comparisons revealed that there was no significant difference in selective orientation rate from 3 to 12 week old flies (Wk. 3 vs. 6, Z = 0.511, P =

0.986; Wk. 3 vs. 9, Z = 0.680, P = 0.961; Wk. 3 vs. 12, Z = 0.171, P = 0.910; Wk. 6 vs. 9, Z =

0.169, P = 0.910; Wk. 9 vs. 12, Z = -0.509, P = 0.987), but 15 week old flies had a significantly lower positive orientation rate compared to all other younger age-groups (Z = 3.683, P = 0.002;

Z = 3.218, P = 0.011; Z = 3.061, P = 0.019; and Z = 3.529, P = 0.004 in 15 vs. 3, 6, 9 and 12 week pairwise comparisons respectively) (Fig. 2.2 A). For explorer flies only, the probability of flies selectively orientating to cue-lure did not significantly differ depending on age-group

Chapter 2: Effect of advanced age on olfactory response of male and female B. tryoni

[GLM (selective orientation ~ age-groups, family = binomial) (Chi2 = 9.188, Df = 4, P = 0.057, mean probability = 0.79 ± .06)] (Fig.2.2 B).

1.0 A

0.8 a a a 0.6 a

0.4 b

0.2

Probablity of selective orientation 0.0 3 6 9 12 15 Age (weeks)

1.0 B

0.8

0.6

0.4

0.2

Probablity of orientationselective 0.0 3 6 9 12 15 Age (weeks)

Figure 2.2. The mean (± 1SE) probability of male Bactrocera tryoni selective orientation to cue-lure at five ages for (A) all tested flies (explorer + non-explorer) and (B) explorer flies

Chapter 2: Effect of advanced age on olfactory response of male and female B. tryoni only. Different letters above bars represent significant differences at P <0.05. There is no significant age effect in Fig. B.

2.3.1.2 Exploratory activity

The probability of males exploring either arm of the olfactometer was significantly affected by the age of the flies [GLM: (explorer ~ age-groups, family = binomial), Chi2 = 15.393, Df = 4,

P = 0.004], with the subsequent post hoc test revealing that there was a significant drop in the exploration probability of flies at 15 weeks of age compared to 3 weeks (Z = 3.711, P = 0.002,

3 vs. 15 week pairwise comparison), while the 6 to 12 week responses were intermediate to, and not significantly different from, the two extremes (Fig. 2.3).

1.0

a 0.8 ab ab ab 0.6 b

0.4

Probablity of exploring 0.2

0.0 3 6 9 12 15 Age (weeks)

Figure 2.3. The mean (± 1SE) probability of five age-groups of male Bactrocera tryoni exploring either arm of a Y-tube olfactometer in the presence of a cue-lure source in one arm and a blank control in the other. Different letters on the bars represent significant difference at

P <0.05.

Chapter 2: Effect of advanced age on olfactory response of male and female B. tryoni

2.3.1.3 Time-to-response

There was a significant effect of age on the time-to-response to cue-lure for male flies [GLM

(time duration ~ age groups, family = gamma), F = 2.650, Df = 4, P = 0.035]. The subsequent post hoc test demonstrated a significant difference in time-to-response with 3 week old males taking significantly less time than 15 week old males (Z= 3.581, P = 0.003), but both age- groups were not significantly different from the response times of 6, 9, and 12 week old males

(Fig. 2.4).

400 b

300 ab ab ab 200 a

100

Time-to-response (seconds)

0 3 6 9 12 15 Age (weeks)

Figure 2.4. The mean (± 1SE) time taken (seconds) by five age-groups of male Bactrocera tryoni to locate a cue-lure source. Different letters on the bars represent significant differences at P <0.05.

2.3.1.4 Choice of male to cue-lure vs. control

Explorer male flies showed a significant preference to cue-lure over the control until an age of

12 weeks (Week [Wk.] 3, Chi2 = 15.868, P < 0.001; Wk. 6, Chi2 = 23.273, P < 0.001; Wk. 9,

Chi2 = 20.455, P < 0.001; Wk. 12, Chi2 = 25.130, P < 0.001), however the response of males

Chapter 2: Effect of advanced age on olfactory response of male and female B. tryoni to cue-lure or control did not significantly differ from a 1:1 ratio at week 15 (Chi2 = 1.581, P =

0.209) (Fig. 2.5).

Control Cue-lure 15 12 19

20 12 6 40 ***

9 7 37 ***

6 6 38 Age (weeks) Age ***

3 12 41 ***

0 20 10 0 10 20 30 40 50 Number of explorer males

Figure 2.5. Age-related olfactory response of male Bactrocera tryoni to cue-lure. Results of chi-square analyses demonstrate significant deviation from 1:1 response ratio to cue-lure and blank-odour control in all age-groups except 15 weeks (P < 0.001 = ***). Seventy flies were tested per age-group, not all responded. The number of males that went to cue-lure and blank control arm are presented in black and grey bars respectively.

2.3.2 Effect of age on the female response to guava-juice odour

GLMs were run with age-groups and cohorts to determine their interactive and additive effect on female olfactory responses. The cohorts did not have significant effects on any of the response variables in both models. Subsequently, cohort was removed from the models and the following results only focus on the significant explanatory variable: age-group.

Chapter 2: Effect of advanced age on olfactory response of male and female B. tryoni

The GLMs run with the response variable “olfactory response” showed that age had a significant effect on female response to guava-juice odour. Subsequently, GLMs were run with exploratory activity and time-to-response to explore whether the reduction in olfactory response was related to changes in these parameters. Additionally, chi-square tests were conducted to examine whether reduced olfactory response of females was due to a decline in choosiness for the odour or not. The results of GLMs and chi-square tests are presented below.

2.3.2.1 Olfactory response of female to guava-juice

GLM revealed that, for all flies tested (i.e. explorers + non-explorers), there was a significant difference in the probability of flies selectively orientating to guava-juice among the five age- groups [GLM (selective orientation ~ age-groups, family = binomial), Chi2 = 15.121, Df = 4,

P = 0.004]. The subsequent post hoc tests demonstrated that attraction to guava-juice odour was significantly higher for 3 week-old versus 15 week-old females (Z = 3.337, P = 0.008), with 6, 9 and 12 week old flies intermediate between these extremes (Fig. 2.6 A). However, the probability of selective orientation for explorer flies did not differ with age [GLM (selective orientation ~ age-group, family = binomial), Chi2 = 0.198, Df = 4, P = 0.995, mean probability

= 0.69 ± 0.07] (Fig. 2.6 B).

Chapter 2: Effect of advanced age on olfactory response of male and female B. tryoni

1.0 A

0.8 a ab 0.6 ab ab 0.4 b

0.2

Probablity of orientationselective 0.0 3 6 9 12 15 Age (weeks)

1.0 B

0.8

0.6

0.4

0.2

Probablity of selective-orientation 0.0 3 6 9 12 15 Age (weeks)

Figure 2.6. The mean (± 1SE) probability of female Bactrocera tryoni selectively orientating to guava-odour at five age-groups for (A) all tested flies (explorer + non-explorer) and (B) explorer flies only. Different letters above bars represent significant differences at P <0.05.

There is no significant age effect in Fig B.

Chapter 2: Effect of advanced age on olfactory response of male and female B. tryoni

2.3.2.2 Exploratory activity

The probability of females exploring either arm of the olfactometer was significantly affected by the age of the flies [GLM: (explorer ~ age-groups, family = binomial), Chi2 = 38.257, Df =

4, P < 0.001], with the subsequent post hoc tests revealing that there was a significant drop in the exploration probability of flies at 9, 12 and 15 weeks of age compared to 3 weeks (Z =

3.383, P = 0.006; Z = 3.526, P = 0.004 and Z = 4.979, P < 0.001 in 3 vs. 9, 12 and 15 week pairwise comparisons respectively). There was also a significant difference between the exploration probability of 6 week and 15-week-old flies (Z = 4.066, P < 0.001). However, there were no significant differences in the exploration probability between 3- and 6-week-old females, as well as among 9 to 15 weeks old flies (Fig. 2.7).

1.0 a ab 0.8 bc bc 0.6 c

0.4

Probablity of exploring 0.2

0.0 3 6 9 12 15 Age (weeks)

Figure 2.7. The mean (± 1SE) probability of five age-groups of female Bactrocera tryoni exploring either arm of a Y-tube olfactometer in the presence of a guava-juice source and a blank control. Different letters on the bars represent significant differences at P <0.05.

Chapter 2: Effect of advanced age on olfactory response of male and female B. tryoni

2.3.2.3 Time-to-response

There was no significant effect of age on the time-to-response to guava-juice odour for female flies [GLM (time duration ~age-groups, family = gamma), F = 2.321, Df = 4, P = 0.059, mean time = 219.15 ± 28.60 sec.] (Fig. 2.8).

400

300

200

100

Time-to-response (seconds)

0 3 6 9 12 15 Age (weeks)

Figure 2.8. The mean (± 1SE) time taken (seconds) by five age-groups of female Bactrocera tryoni to locate a guava-juice source did not show significant difference, Df = 4, P = 0.059.

2.3.2.4 Choice of female to guava-juice vs. control

Explorer female flies showed a significant preference to guava-juice over the control for all age-groups tested (Wk. 3, Chi2 = 9.290, P = 0.002; Wk. 6, Chi2 = 8.643, P = 0.003; Wk. 9, Chi2

= 5.818, P = 0.016; Wk. 12, Chi2 = 5.232, P = 0.022; Wk. 15, Chi2 = 5.121, P = 0.023) (Fig.

2.9).

Chapter 2: Effect of advanced age on olfactory response of male and female B. tryoni

Control Guava-juice

15 10 23 *

12 14 29 *

9 14 30 *

Age (weeks) Age 6 17 39 **

3 19 43 **

30 20 10 0 10 20 30 40 50 Number of explorer females

Figure 2.9. Age-related olfactory responses of female Bactrocera tryoni to guava-juice odour versus a blank control. Results of the chi-square test demonstrates significant deviation from

1:1 response ratio to guava-odour and blank-odour control in all age-groups (P < 0.05 = *; P <

0.01 = **). Seventy flies were tested per age-group, not all responded.

2.4 DISCUSSION

2.4.1 Reduction in olfactory response with ageing

Similar to other insects (Cook-Wiens and Grotewiel 2002, Iliadi and Boulianne 2010, Gadenne et al. 2016), advancing age was found to negatively affect the olfactory response of B. tryoni with respect to the tested odours. We found decreased orientation to odour sources in both male and female B. tryoni, with the probability of selective orientation of males and females dropping significantly at 15 weeks compared to three weeks. In D. melanogaster, a similar reduction of olfactory response was attributed to developing defects in the olfactory system as well as decreasing locomotor activity with ageing (Cook-Wiens and Grotewiel 2002). The reduction in the selective orientation of female B. tryoni to odour sources can be more directly attributed to reduced exploratory activity (i.e. locomotion) with age because the selective

Chapter 2: Effect of advanced age on olfactory response of male and female B. tryoni orientation probability of females was constant at all ages among explorer flies. However, for males, the situation is more complex with, at 15 weeks, both a significant drop in the number of explorer flies and the failure of explorers to discriminate between lure and blank arms of the olfactometer.

2.4.2 Reduction in exploratory activity with ageing

The current study revealed a decline in the exploratory activity of flies with ageing in the presence of the tested odours. As the flies aged, fewer crossed the mid-line of the olfactometer arms, with many simply sitting in the mouth of the Y-tube for the 10 minute observation period.

Additionally, at advanced age, male flies took a significantly longer time to choose the odour source compared to the youngest flies. However, female flies did not have a significant difference in time-to-response at all tested ages. Reduction in exploratory activity and locomotion with increasing age has been recorded in other insects. In studies with D. melanogaster, 6 week old flies were 30-fold more likely to stay at the release point than 3 week old flies (Grotewiel et al. 2005), while 40-41 day old flies were less likely to cross a 27-cm- diameter arena from the release point than 6-7 day old flies (Iliadi and Boulianne 2010). A similar trend was reported for C. capitata, where walking frequency declined after three weeks and was extremely low before death (Carey et al. 2006). Male and female B. tryoni, reared on a standard laboratory diet, showed different patterns in flight and walking frequency with age.

Females increased mean locomotor activities from 4 to 10 to 30 days, while males showed increased locomotor activity from days 4 to 10 but had reduced activity at 30 days (Prenter et al. 2013). However, in contrast to a decline in locomotor activity at an early age (i.e. between

10 and 30 days), in the current study males and females were observed to retain their maximal exploratory activities for longer periods (6 weeks in females, 12 weeks in males). This may be because of the different experimental setup. All of the previous ageing research on locomotor

Chapter 2: Effect of advanced age on olfactory response of male and female B. tryoni and exploratory activities were conducted without an odour sources, while the current experiments were conducted in the presence of cue-lure and guava juice which have been reported to increase activity and flight of mature males and females in wind tunnel experiments

(Meats and Hartland 1999, Dalby Ball and Meats 2000). Additionally, the current research was conducted with wild flies, while the work of Prenter et al. (2013) used laboratory-reared flies, which may also influence results.

2.4.3 Patterns in reduced olfactory response in males and females

The olfactory responses and exploratory activities of both males and females declined at advanced age. The male olfactory response to cue-lure was constant until 12 weeks of age, after which their olfactory response dropped dramatically at 15 weeks when there were few explorers, and those that did move orientated indiscriminately to control and treatment arms.

However, female exploratory response decreased gradually over time and reached the lowest level at the oldest age-group, although the oldest age-group still showed a significant orientation preference to guava-juice odour. Male and female olfactory responses are discussed separately in the following sections

2.4.3.1 The constant attraction of males to cue-lure until an advanced age

Males of B. tryoni retained positive olfactory responses to cue-lure for most of their life. A similar result was observed in B. opiliae, where male’s response to methyl eugenol remained unchanged until 12 weeks of age (Fitt 1981). The Bactrocera male response to a small group of plant-derived secondary chemicals is considered a critical element of their biology and ecology (Clarke 2019), as exposure to these chemicals enhances individual male fitness through increased sexual competitiveness (Metcalf and Metcalf 1992, Weldon et al. 2008,

Kumaran et al. 2013, Kumaran et al. 2014a). Bactrocera tryoni males’ mate throughout their

Chapter 2: Effect of advanced age on olfactory response of male and female B. tryoni lives, even though older males have reduced mating success when in competition with young males (Ekanayake et al. 2017a). There is thus an evolutionary driver for male flies to retain a strong lure response for as long in life as possible, and this is reflected in our results (to week

12) and those of Fitt (1981). In this light, we interpret the dramatic decrease of male olfactory response at 15 weeks, caused by simultaneous drops in locomotor activity and selective olfactory orientation, as likely symptomatic of wider failures of several biological systems associated with advanced age, rather than a loss of “interest” in cue-lure per se.

2.4.3.2 Higher attraction to host fruit odour in younger females

The females’ exploratory activities to guava-juice odour showed a gradual reduction with ageing, but with no corresponding decline for positive selection to the odour in explorer flies.

A similar response was found in A. obliqua, where a decline in the olfactory response to volatiles of host fruits was found in 20 day old females compared to 1, 5 or 10 day old females

(Reyes et al. 2017). In B. tryoni, at a given point in time, the olfactory response of gravid females to host fruit odour is linked with oviposition (Eisemann and Rice 1992). We believe our results support this observation in a longitudinal temporal context, and this explains the female decline in response with ageing. In our experiment, we found young females (3-6 weeks) demonstrated the highest response to guava juice odour, with a continuous decline thereafter. This correlates closely with the lifetime fecundity patterns of female B. tryoni, which sees a peak in egg production at four weeks, with a continuous decline thereafter (Fitt 1990,

Kumaran et al. 2013).

While the current study identified aging effects on olfaction of B. tryoni, a limitation of this study is that the male and female olfactory responses were each tested against a single odour type, i.e. cue-lure for males and guava juice for females. Thus, the study cannot determine

Chapter 2: Effect of advanced age on olfactory response of male and female B. tryoni whether the changes reported here are general patterns of age-related olfactory change for males and females of this species, or if the patterns observed relate to the specific odours tested.

Further studies are therefore required to confirm or deny the generality of our results.

2.4.4 Implications for management

As the olfactory response of an insect may vary with age, the trapping effectiveness of pest insects for surveillance and management may also vary (Kouloussis et al. 2009). Cue-lure is an effective monitoring tool for male B. tryoni and is used to control field populations of this insect by mass-trapping and male-annihilation (Dominiak et al. 2003, Lloyd et al. 2010,

Reynolds et al. 2016, Stringer et al. 2017). That male flies retain their attraction to cue-lure consistently until an advanced age is a positive finding for pest management. However, loss of attraction to cue-lure may be a problem for sampling B. tryoni males at the very end of winter, when there is a majority of very old males in the population (authors’ unpublished data), following the overwintering quiescent period (Fletcher 1979, O'loughlin et al. 1984,

Muthuthantri et al. 2010, Clarke et al. 2019). It is possible that such populations may be undetected, or at least underestimated, if relying solely on cue-lure trapping. Also positively for pest management, the results suggest that new generation female traps based on host fruit odours (Gregg et al. 2018), can be expected to be most effective against female B. tryoni when they are at their reproductive peak, but also less effective against the very old spring populations.

Chapter 3:Response of male Bactrocera tryoni to host-fruit odour

Chapter 3: Response of male Bactrocera tryoni to host-fruit odours

This chapter is published as:

Tasnin, M. S., R. Silva, K. Merkel, and A. R. Clarke. 2020. Response of male Queensland fruit fly (Diptera: Tephritidae) to host-fruit odours. Journal of Economic Entomology 113: 1888-

1893.

TMS, KM and ARC discussed the design and logic of the experiment, TMS and RS carried out the experimental work, TMS and KM carried out data analysis and TMS, KM and ARC helped interpret the data, TMS wrote the first draft, all authors worked on subsequent drafts, all authors approved the manuscript.

Chapter 3:Response of male Bactrocera tryoni to host-fruit odour

3.1 INTRODUCTION

The tribe Dacini (Diptera: Tephritidae) is a major clade within the true fruit flies, containing

932 species in four genera (Vargas et al. 2015, Doorenweerd et al. 2018, Clarke 2019). Dacini are fruit breeders, with the larvae feeding within host fruits (May 1958, Fletcher 1989).

Approximately 10% of dacines are pests of commercial fruits and vegetables and include some of the world’s most destructive horticultural pests, such as Bactrocera dorsalis (Hendel) and

Zeugodacus cucurbitae (Coquillett) (Vargas et al. 2015).

The surveillance and management of most Dacini fruit flies rely on lure-and-kill trapping

(Aluja 1996, Koyama et al. 2004). Males are strongly attracted to a small group of closely related plant-derived phenylbutanoids and phenylpropanoids, or their synthetic analogues.

These “male lures”, the best known of which are methyl eugenol and cue-lure, have been the mainstay of dacine monitoring and control for many decades (Metcalf and Metcalf 1992, Shelly

2010, Kumaran et al. 2013). Females are only rarely attracted to male-lures (Weldon et al.

2008), but as the females oviposit into host fruits, they are attracted to host-fruit volatiles

(Eisemann 1980, Prokopy et al. 1991, Jang Eric B 1996). Due to the female’s close association with host fruits, there is a growing international effort to develop female traps based on host- fruit odours (Siderhurst and Jang 2006, Vargas et al. 2018, Jaleel et al. 2019). The third category of lure commonly used for Dacini management is food attractants, commonly protein- based, which can attract both males and females (Epsky et al. 2014). Food-based attractants can have significant operational problems and attract non-target insects (Dominiak 2006) and so, in the last decade, most research on new dacine lures has focused on the male and female specific lures.

Chapter 3:Response of male Bactrocera tryoni to host-fruit odour

As described above, Dacini lure research has fallen into a sex-based dichotomy, with only the food-based attractants of the three lure types specifically trying to target both males and females

[see for example Shelly et al. (2014)]. In this paper, we raise the issue that perhaps this should not be the case and that males should also be considered as targets for the fruit-based lures.

While scattered in the literature, there is ample evidence that male Dacini also respond positively to fruit-based odours. Generally presented as a secondary data set from experiments focusing on female-lure development, numerous authors have identified male Dacini responding to fruit odours (Siderhurst and Jang 2006, Clarke and Dominiak 2010, Biasazin et al. 2014, Cunningham et al. 2016). For example, male Z. cucurbitae and B. dorsalis are attracted to volatile compounds of cucumber (Siderhurst and Jang 2010, Jang et al. 2017), while male Dacus ciliatus Loew are attracted to volatiles of melon fruits (Alagarmalai et al. 2009).

However, despite such records, the male response is rarely if ever discussed in these papers and it remains a “non-issue” in the literature.

Our interest in this topic arose from a preliminary trial using freshly crushed fruit to try and catch wild female Queensland fruit fly, Bactrocera tryoni, but instead we caught large numbers of males. Following from this initial observation we carried out further work to determine: (i) does the male response to fruit occur throughout the life of a male or only at certain times; (ii) do wild males respond to fruit odours at all times of the year; and (iii) how strong is the fruit response in comparison to the male lure response? We addressed these questions continuing to use B. tryoni as our study organism. The males of this species are strongly attracted to cue-lure

(Dominiak et al. 2003, Stringer et al. 2017), and in addition to our preliminary observations males are known to be attracted to orange-juice/ammonia traps in the field (Clarke and

Dominiak 2010), are known to respond to fruit-based odour blends in field cages (Cunningham et al. 2016), and are present in fruiting orchards (Ero et al. 2011). We used field trapping and

Chapter 3:Response of male Bactrocera tryoni to host-fruit odour laboratory olfactometer studies to investigate the male fruit-odour response addressing the questions raised above.

3.2 MATERIALS AND METHODS

3.2.1 Study site and material

All field observations were conducted on a subtropical agro-tourism property, Tropical Fruit

World (TWF), situated in far-northern New South Wales, Australia (28°17′S, 153°31′E). More than 500 varieties of fruits are grown on the farm, many of them B. tryoni host fruits. The background fly population is high during all times of the year.

A preliminary field trial was conducted in the field with six host-fruits of B. tryoni where male showed strong response to tomato-based traps, thus we selected tomato as a host-fruit for further study (see supplementary Table 3.S).

3.2.2 Field observations. Male responsiveness to tomato-based traps versus cue-lure

traps

This experiment was designed to observe the male responsiveness to tomato-based traps during the year relative to the numbers of males being caught in cue-lure traps. We selected five time points during 2017– occurring in early autumn, late autumn, late winter, early spring, and early summer – chosen as they coincide with marked changes in the abundance of field populations of B. tryoni (Muthuthantri et al. 2010). In 2018, the early autumn and early spring samplings were repeated. The study was conducted at TFW. On each sampling occasion, four cue-lure and four tomato-based traps were placed on eight separate trees in a garden patch with fruiting host trees available during the seasons (i.e. persimmon, guava, custard apple, mulberry, white

Chapter 3:Response of male Bactrocera tryoni to host-fruit odour sapote, carambola and avocado) from 8.00 am to 1.00 pm and continuously observed by two persons. Males attracted by the traps were live-captured upon arrival.

3.2.3 Olfactory response of males across their life to tomato odour

While our preliminary data showed males responded to fruit-odours, we wanted to determine at an individual fly level if fruit response was a life-long effect, a “one-off” behaviour, or was possibly influenced by sexual maturation. Using adult flies reared from wild collected maggots we tested the response of flies of different age (from 1 week to 15 weeks old) to tomato-odour in an olfactometer. The experiment was done in two parts, the first covering weeks 3 to 15 (Part

1), and then a second covering weeks 1 to 3 (Part 2). Wild B. tryoni become sexually mature between two and three weeks of age (Dalby‐Ball and Meats 2000). Experimental details are as follow.

3.2.3.1 Source of flies

For Part 1 of the study, we used adult flies emerging from naturally infested mango (collected

5th Feb 2018) and carambola (collected 18th Mar 2018) from sites in South-east Queensland

(approx. 27○S, 152○E). Infested fruits were placed over vermiculite in plastic containers and held at 25○C and 65% RH. After 14 days, pupae were sieved from the vermiculite and held until adult emergence. Once each day during the emergence period the newly emerged flies were counted and placed in a new holding cage and provided with water, sugar cubes and yeast hydrolysate ad libitum. This process created fly cohorts of known age. To allow for mating, each holding cage contained both sexes (100 males and 100 females) that emerged on the same date, although only the male flies were used for the olfactory experiment. The same rearing protocol was followed for Part 2 of the study, except that the flies came from infested mulberry

Chapter 3:Response of male Bactrocera tryoni to host-fruit odour fruit obtained from Tropical Fruit World (28.17'S, 153.31’E), located in the Tweed Valley,

New South Wales, Australia (collected 20th Oct 2019).

3.2.3.2 Olfactometer experiments

The olfactory response of males against fully ripe tomato-odour was tested in seven age groups

(Part 1: 3, 6, 9, 12 and 15 weeks; Part 2: 1, 2 and 3 weeks) using a glass Y-tube olfactometer

(Model: CADS-2P, Sigma Scientific Ltd). The olfactometer comprised of a 15 cm long stem and two 10 cm long side-arms (75° angle and 5 cm internal diameter) attached to two sealed glass jars. One jar provided the tomato-odour (a whole tomato sliced in half) and another jar without any odour source (blank control). A clean air delivery system was attached with an adjustable air compressor which pumps airstream through the jar at a rate of 2.5 L/minute.

The experiments were conducted in a laboratory from 10 am to 2 pm under constant conditions with controlled temperature (26 ± 1 ○C) and constant artificial light. Flies were carried to the laboratory from an insectary one hour before the start of the experiment to allow for acclimation to the new environment. The olfactory tests were conducted on individual males and a single male was used just once. Each male was observed until it chose either arm of the olfactometer, or was discarded if non-responsive after 10 minutes. When a male responded positively to the tomato-odour containing arm (crossed the midpoint of the treatment side-arm) this was recorded as attracted to tomato odour; when a male went past the midpoint of the control arm this was defined as attracted to control [see detail in Tasnin et al. (2020a)].

For each age-group, 70 individual flies were tested in two replications (2 x 35). For Part 1 of the experiment the 35 flies of each replication originated from the two different fruit cohorts

(i.e. mango and carambola), while the flies of Part 2 came from the single mulberry cohort.

Thirty-five flies were tested in a day, with the glass jar and Y-tube of the olfactometer cleaned

Chapter 3:Response of male Bactrocera tryoni to host-fruit odour with 70% ethanol, washed with water and dried with paper towel after testing 17 individuals.

The tomato-odour containing arm was then changed and the second half of the males tested.

3.2.4 Data analysis

3.2.4.1 Field observations

Differences in the mean number of male flies caught at tomato traps versus cue-lure traps (n =

7 sampling occasions, catches within a sampling occasion summed) were tested through a paired t-test following a positive test for assumption of homogeneity of variance. Results are presented as the mean ± 1 standard error of the mean.

3.2.4.2 Olfactometer trials

There were two independent trials: Part 1 being to test the effect of aging on already sexually mature flies, and Part 2 being to test the effect of sexual maturation. Because they were designed as separate experiments, and conducted with different fly cohorts, it is not appropriate to combine the data sets and so the results of the two components were analysed independently.

In a preliminary analysis, the effect of fruit cohort was tested for Part 1, found not to be significant, and so was discounted as a factor for subsequent analyses.

For Part 1 and Part 2 experiments, Chi-square tests were conducted to examine whether the male fly response to tomato-odour and control arm differed from a 1:1 ratio (the departure from a 1:1 ratio would be expected if flies choose selectively and not randomly). The statistical program R (R Core Team 2018) and SigmaPlot (Systat Software, San Jose, CA) was used for analysing and visualizing the data.

Chapter 3:Response of male Bactrocera tryoni to host-fruit odour

3.3 RESULTS

3.3.1 Field observation. Responsiveness of males to tomato-based traps versus cue-lure

traps

For the seven sampling occasions, 94.4 ± 22.8 males was caught at the highly male-attractive cue-lure, while 68.3 ± 20.6 males were caught at the tomato traps: the mean catch rates was not significantly different (t = 1.27, Df = 6 P = 0.251). The ratio of males’ responsiveness to tomato-based traps versus cue-lure traps varied with sampling occasion. The highest proportion of males (58-60%) responded to tomato traps during late winter and early spring samplings of

2017, the lowest proportion captured at tomato traps (20-35%) were in early summer 2018 and early autumn 2017-18, while during the late autumn 2017 and early spring 2018 samplings, almost equal proportion of males were caught at cue-lure and tomato traps (Table 3.1).

Table 3.1. The number and proportion of Bactrocera tryoni males captured by cue-lure and tomato-based traps

Sampling Sampling Number of Cue-lure traps Tomato-based traps season date males captured (proportion) (proportion) Early autumn 13/03/2017 61 0.65 0.35

Late autumn 24/05/2017 350 0.53 0.47

Late winter 17/08/2017 210 0.42 0.58

Early spring 7/09/2017 114 0.40 0.60

Early summer 17/11/2017 160 0.77 0.23

Early autumn 16/03/2018 187 0.80 0.20

Early spring 19/09/18 57 0.51 0.49

Chapter 3:Response of male Bactrocera tryoni to host-fruit odour

3.3.2 Olfactory response of males across their life to tomato odour

3.3.2.1 Part 1: Three weeks of age to 15 weeks

Male B. tryoni demonstrated a significant preference to tomato-odour over the blank control at all tested ages (Week [Wk.] 3, Chi2= 4.587, P = 0.032; Wk. 6, Chi2 =30.224, P < 0.001; Wk.

9, Chi2 =23.290, P < 0.001; Wk. 12, Chi2= 35.267, P < 0.001; Wk. 15, Chi2 = 24.083, P <

0.001) (Fig. 3.1).

Control Tomato

15 7 41 ***

12 7 53 ***

9 12 50 ***

Age (weeks) Age 6 11 56 ***

3 23 40 *

30 20 10 0 10 20 30 40 50 60 Number of males

Figure 3.1. Olfactory response of males of Bactrocera tryoni of different ages to tomato-odour.

For each age-group a total 70 flies tested in two replications but not all responded. Bars followed by “*” or “***” indicate ratios that significantly deviate from a 1:1 response ratio for tomato-odour and blank-odour control at a significance level of P < 0.05 and P < 0.001, respectively.

3.3.2.2 Part 2: One week of age to three weeks

Male B. tryoni did not show a significant preference to tomato-odour over the blank control at

1 week of age (Wk. 1, Chi2 = 1.230, P = 0.267). However, both 2- and 3-week-old males

Chapter 3:Response of male Bactrocera tryoni to host-fruit odour showed a significant preference to tomato-odour over the control (Wk. 2, Chi2 = 15.000, P <

0.001 and Wk. 3, Chi2 = 28.446, P < 0.001) (Fig. 3.2).

Control Tomato 4

3 11 54 ***

2 15 45 ***

Age (weeks) Age 1 22 30

0 30 20 10 0 10 20 30 40 50 60 Number of males

Figure 3.2. Olfactory response of maturing males of Bactrocera tryoni to tomato-odour. For each age-group a total 70 flies tested in two replications but not all responded. Bars followed by “***” indicate ratios that significantly deviate from a 1:1 response ratio for tomato-odour and blank-odour control at a significance level of P < 0.001.

3.4 DISCUSSION

The field observations revealed that males could be trapped by tomato all through the year, at times in greater numbers than males responding to cue-lure. Males were observed to respond to both types of attractant from morning through to the afternoon, except for summer when males responsiveness was greatly reduced after 11.30 am. In the laboratory, male responsiveness to tomato-odour increased with sexual maturation, but then remained constant through the life of the fly.

Chapter 3:Response of male Bactrocera tryoni to host-fruit odour

3.4.1 Males olfactory response to host-fruit odour with maturation and aging

Cue-lure is considered a highly attractive, male-specific lure for B. tryoni and other dacines

(Vargas et al. 2010, Royer 2015, Reynolds et al. 2016). In contrast, male dacines are generally disregarded in discussions around fruit-odour based attractants (Quilici et al. 2014).

Nevertheless, when comparing the attraction of crushed tomato and cue-lure in the field, while more flies in total were caught at cue-lure the differences in the mean of catches were not significantly different. Further, males of B. tryoni showed an attraction to tomato-based traps year-round. The rate of male responsiveness to tomato-based traps compared to cue-lure traps varied depending on sampling occasions, but the sampling design was not sufficient to say if these differences had biological meaning (e.g. such as through seasonal changes in the structure of B. tryoni populations), or were simply experimental variation. Further research is needed to test this issue.

Maturing males (1- 3 weeks age) demonstrated a different pattern of attraction to tomato-odour with age, where the youngest age group (1 week) did not differentiate tomato-odour and control arms, while 2 and 3 week-old males did (Fig. 3.2). Similar to B. tryoni males, immature B. tryoni females (5 days old) were non-responsive to the odour of yeast (Pichia kluyveri Bedford)

(Piper et al. 2017). Once mature, males showed attraction to tomato-odour throughout their lives (Fig. 3.1). Thus, the results suggest that the attraction of males to host-fruits odour may be related to their sexual maturation, which is reported in many Dacini species with respect to their attraction to the male-lures (Wong et al. 1991, Metcalf and Metcalf 1992, Kamiji et al.

2018). Unlike other insects (Iliadi and Boulianne 2010, Gadenne et al. 2016) age did not negatively affect the olfactory response of B. tryoni males. A similar pattern was recorded in the congeneric Bactrocera opiliae (Drew and Hardy), where males showed a consistent attraction to the male attractant methyl eugenol until the end of the experiment at 12 weeks

Chapter 3:Response of male Bactrocera tryoni to host-fruit odour

(Fitt 1981). While male B. tryoni consistently chose tomato-odour over the blank control until

15 weeks of age, they did not discriminate between cue-lure and a blank control at 15 weeks in the same olfactometer setting (Tasnin et al. 2020a). While this difference may be attractant dependent (i.e. cue-lure vs fruit odour), other variables may also have influenced these results.

For example, age-related responsiveness of insects to odour may be influenced by the diet type on which they were reared. For example, Ceratitis capitata (Wiedemann) reared on a sugar diet had low attraction to food-odour when young (1-5 days old) which increased at middle- age (10-25 days) and again declined when old (35-45 days). In contrast, flies reared on a protein diet exhibited a consistently declining responsiveness to food-based traps with increasing age

(Kouloussis et al. 2009). However, for this study (Part 1) and Tasnin et al. (2020a) the adult flies were kept under the same holding condition and originated from the same larval hosts.

3.4.2 Why males are attracted to host-fruit odours?

It is not clear why B. tryoni males should have a strong attraction to host-fruit volatiles, but we can postulate three potential reasons: (i) to utilise the fruit as a direct resource; (ii) as a mechanism of mate location (as females are likely to be on fruit); and (iii) because commonalities between the male and female sensory systems are such that males respond to the fruit even though the male response has no direct functional role. With respect to utilising the fruit as a direct resource, males of C. capitata are responsive to host-fruit odours which enhance their signalling activity towards females (Shelly and Villalobos 2004, Segura et al.

2018), and an exposure to host-fruit increased mating success in males of that species

(Katsoyannos et al. 1997, Shelly and Villalobos 2004). Additionally, some tephritid males are known to utilise host-fruit juice as a food resource, for example males of Rhagoletis indifferens

Curran (Yee 2003). However, neither of these options seems plausible in our system, as within a fruiting orchard B. tryoni males rest on foliage near fruit, but do not feed on the fruit (Ero et

Chapter 3:Response of male Bactrocera tryoni to host-fruit odour al. 2011), and only infrequently even walk upon the fruit (A.R.C. pers obs). With respect to utilising fruit as mate location mechanism this is possible, as male B. tryoni do locate themselves in fruiting orchards near ovipositing females (Ero et al. 2011). However, B. tryoni has been shown to have an aggregated, non-resource based mating system where mating happens over a narrow temporal window, which happens independently of fruit (Ekanayake et al. 2017b). Thus, the need for males to locate fruit as a mate rendezvous mechanism also does not appear a valid hypothesis. This leave, as the remaining hypothesis, that male host-fruit attraction is due to similarities between the male and female olfactory systems. An anatomical study of the antennal lobe (the key neural processing element of an insect’s olfactory system) of B. dorsalis showed that males and females exhibited minimal differences in the size and structural organization of the components of the lobe, with only eight of 65 glomeruli sexually dimorphic (Lin et al. 2018). Very similar results have been reported for C. capitata (Solari et al. 2016). Thus, it may be that male B. tryoni (and related species) respond to fruit-odours simply because they have the same olfactory “wiring” as females, rather than because it serves a functional role for the males. Further behavioural, anatomical, and neurological research would be needed to confirm this hypothesis.

3.4.3 Implications of study

Males of B. tryoni display a strong attraction to cue-lure (Meats and Hartland 1999) which has been used as a field monitoring and control agent since the 1960s (Dominiak et al. 2003, Lloyd et al. 2010, Stringer et al. 2017). However, this study shows that fruit-based traps should also be considered for trapping males. Indeed, substantial B. tryoni male catches have been made in field trials testing fruit odour-based traps for female B. tryoni following on from the initial research of Cunningham et al. (2016) (J.P. Cunningham pers. comm. to authors). We thus conclude that while, to date, the focus of developing fruit-based traps for Dacini has been for

Chapter 3:Response of male Bactrocera tryoni to host-fruit odour female control (Quilici et al. 2014, Cunningham et al. 2016, Jang et al. 2017), the additional capacity for male control should also be incorporated into trials.

Chapter 3:Response of male Bactrocera tryoni to host-fruit odour

Supplementary Table 3.S. The number of wild Bactrocera tryoni males and females collected from two cue-lure or two fruit-based traps containing one of six different fruit-based traps over three hours in an open field environment.

Collection No of males captured No of females captured methods 1st 15 minutes After 3 hours 1st 15 minutes After 3 hours

Cue-lure 4 38 0 0

Tomato 5 23 0 0

Orange 0 11 0 1

Nectarine 0 13 0 1

Plum 0 9 0 0

Peach 1 12 0 0

Grape 0 7 0 0

Chapter 4: Seasonality in age-structure and longevity of Bactrocera tryoni in subtropical Australia

This chapter is currently under review as:

Tasnin, M. S., K. Merkel, M. Bode and A. R. Clarke. 2020. Seasonality in age-structure and longevity of Bactrocera tryoni in subtropical Australia. Scientific Reports: in review.

TMS, KM and ARC discussed the design and logic of the experiment, TMS carried out the experimental work, TMS, KM and MB carried out data analysis and all authors helped interpret the data, TMS wrote the first draft, all authors worked on subsequent drafts, all authors approved the manuscript.

Chapter 4: Seasonality in age-structure and longevity of Bactrocera tryoni in subtropical Australia

4.1 INTRODUCTION

Demography deals with four major aspects of a population: size, distribution, structure and change, where structure means the distribution of a population by age and sex and change implies total growth or decline of the population (Carey 1993, Carey and Roach 2020). The conventional methods of demographic study involve lifetable techniques, mortality models, and population comparison (Carey 2001). For insects, whose small size makes it highly difficult to track individuals in the field, demographic data is generally obtained using lifetable techniques which are dependent on the use of mortality data from known-age individuals maintained in the laboratory (Southwood 1966), or through capture-recapture methods to assess aging in the wild (Udevitz and Ballachey 1998).

While it is recognized that there is growing importance in understanding aging in the wild

(Müller et al. 2004, Zajitschek et al. 2020), it can be very difficult to accurately estimate the age of wild insect populations using conventional age-grading methods (Carey et al. 2008, Rao and Carey 2015). Developed as an extension of the life-table approach to age wild insect populations (Müller et al. 2004, Carey 2011), the demographic method uses combined information from a ‘captive cohort’ (individuals captured from the wild at an unknown age whose post-capture longevity is then recorded under standard conditions) and a ‘reference cohort’ (adult individuals emerging from wild collected juveniles [e.g. larvae or caterpillars], then held under the same standard conditions to provide whole-of-life longevity) to back calculate the age distribution of the unknown age wild adults through the deconvolution method

(Muller et al. 2007, Carey et al. 2008, Carey et al. 2012). The approach is based on the concept that if individuals can be captured from a wild population without bias to their proportional age distribution in the wild, and the force of mortality is only dependent on age and independent of rearing environment, then the age distribution in the wild is equal to the death distribution in

Chapter 4: Seasonality in age-structure and longevity of Bactrocera tryoni in subtropical Australia captivity and so the former can be predicted by the later (Muller et al. 2007, Vaupel 2009). The demographic approach has been implemented to explore population demography over seasons in a limited number of temperate and Mediterranean insects (Carey et al. 2008, Carey et al.

2012, Behrman et al. 2015, Papadopoulos et al. 2016), but has not been applied to tropical insects.

Approximately 75% of tropical forests demonstrate strong seasonality (Murphy and Lugo

1986), and within those forests some tropical insects also show predictable phenology patterns

(Kishimoto-Yamada and Itioka 2015, Santos et al. 2017). Seasonal fluctuation of abundance of tropical herbivorous insects has been linked to monsoonal cycles of wet and dry seasons

(Bonebrake et al. 2010, Molleman 2018), with an increased number of insects in the wet season considered to be related to the increased availability of new leaf and vegetative material for feeding and breeding (Frith and Frith 1985, Braby 1995, Muniz et al. 2012). For example, the abundance of Ithomiine butterflies increases with the onset of the wet season and declines dramatically during the dry season, due to the availability, or lack thereof, of host plants for oviposition and caterpillar feeding (Bonebrake et al. 2010). An exception to this pattern is thought to exist for polyphagous herbivore species where hosts are considered to be available throughout the year: in this case continuous breeding is predicted as both temperature and hosts are not limiting (Wolda 1988, Yonow et al. 2004, Baker et al. 2019).

While numerous studies on the phenology of tropical insects have investigated the drivers of changing population abundance, e.g. rainfall, host availability, etc. (Valtonen et al. 2013,

Hernández and Caballero 2016, Marchioro and Foerster 2016), we are not aware of any study which has gone further and investigated if changes in population abundance are also associated with changes in population demography, for example birth rates and death rates. Thus, the

Chapter 4: Seasonality in age-structure and longevity of Bactrocera tryoni in subtropical Australia demographic processes behind seasonal population change remains unknown in tropical insects

(Kishimoto-Yamada and Itioka 2015).

The polyphagous tropical fruit flies (Bactrocera spp., Diptera: Tephritidae) include invasive pest species for which modelers and biosecurity risk analysts have made explicit assumptions that breeding is, or can be, continuous in the tropics because hosts and temperature are not limiting (Meats 1981, Sutherst and Yonow 1998, Choudhary et al. 2017, Baker et al. 2019).

However, as breeders in the fruits of tropical forests (Clarke 2019), their potential hosts may be seasonally restricted because of monsoon driven flowering and fruiting (Sakai et al. 1999).

Thus, they may also have seasonally changing demographics associated with these events, but if so, this is unknown as it is for other seasonally impacted tropical insects.

In this chapter we explore this issue, using as our test animal Bactrocera tryoni (Froggatt)

(Diptera: Tephritidae), a native Australian insect originally endemic to the Australian east coast tropical and subtropical rainforests (Drew 1989, Sutherst and Yonow 1998), but which since the late 1800s has also become a pest of horticulture (Dominiak 2019). The Australian east coast rainforests have a restricted reproduction (=flowering + fruiting) season which occurs during spring and early summer, initiated by the start of the wet-season monsoon (Boulter et al. 2006). In temperate parts of Australia, where B. tryoni is invasive (Dominiak and Mapson

2017), its breeding is considered temperature limited, with a winter decline in population numbers (Bateman 1967, 1968). However, paradoxically, this species also shows

“overwintering” population declines in subtropical and tropical Australia (Lloyd et al. 2010,

Muthuthantri et al. 2010), where lower threshold temperatures are not limiting (Pritchard 1970,

Clarke et al. 2019). A simple absence of suitable hosts during this population depression period in the tropics also does not explain the phenology of the fly, as a recent phenological study

Chapter 4: Seasonality in age-structure and longevity of Bactrocera tryoni in subtropical Australia demonstrated little correlation of either temperature or host fruit availability on the population phenology of B. tryoni at a subtropical site (Merkel et al. 2019).

Using the demographic approach (Muller et al. 2007, Carey et al. 2008), we initiated a study of age-structure changes of wild B. tryoni populations in relation to phenological changes of those populations to better understand the species’ demographic ecology in its tropical range.

As the core element of the demographic approach, we collected captive and reference cohorts of B. tryoni during different seasons. Surprisingly, the longevity of reference flies collected in different seasons showed strong seasonality, leading us to refine our study objectives.

Specifically, the study addressed three major questions: i. In the wild, in a subtropical site where host fruits are always available, does the tropical insect B. tryoni breed continuously through the year, or is there demographic evidence for gaps in breeding? ii. Does the demographic structure of field populations change over season? iii. Can the demographic approach help explain the “winter” decline in a region where lower temperatures are not limiting? Additional to its value for understanding this particular species, we believe the demographic methodology we modify and refine here can be applied to other tropical insects for which demographic studies are absent.

4.2 MATERIALS AND METHODS

4.2.1 Study insect

Bactrocera tryoni is a polyphagous, multivoltine species with a long-lived adult stage and overlapping generation (Clarke et al. 2011). In tropical and subtropical eastern Australia lower temperatures are not limiting to B. tryoni development (Sutherst and Yonow 1998), yet B. tryoni populations show a typical temperate pattern in their phenology with a significant decline in numbers during the southern hemisphere late autumn and winter months (i.e. May

Chapter 4: Seasonality in age-structure and longevity of Bactrocera tryoni in subtropical Australia to August) (Muthuthantri et al. 2010). Larval rearing from infested fruit, and adult fly maintenance under laboratory conditions, are long established and optimised techniques for B. tryoni (Heather and Corcoran 1985) making this species well suited for a combined field and laboratory study.

4.2.2 Demographic approach of age estimation

We used a demographic approach similar to that developed by Muller et al. (2007) and Carey et al. (2008). The method involved two cohort types: (i) the captive cohort- consisting of unknown age adult individuals captured in the field; and (ii) the reference cohort- consisting of adult individuals of known age as they emerged in the laboratory from wild, egg and larval infested fruit sources collected from the same site as the captive cohort. This approach to wild population aging is based on the principle that the distribution of the timing of death of wild insects in a controlled, captive environment reflects the population age distribution in a wild environment (Vaupel 2009), if the force of mortality in the wild and laboratory conditions are the same and that individuals can be captured from the field in an unbiased fashion with respect to the age distribution of the field population (Muller et al. 2007, Carey et al. 2008). In its simplest form, if wild caught insects are returned from the field and all die within a short time, then it may be postulated that the sampled field population consisted predominantly of old individuals. Conversely, if wild caught insects are returned from the field and all die only after a long holding period, then it may be postulated that the sampled field population consisted predominantly of young individuals (Carey et al. 2012). In practice, the quality of the interpretation is refined by utilising both the post-capture longevity data from the captive cohort and the longevity data from the reference cohorts, to estimate the age distribution of the wild individuals at the time when they were captured (Muller et al. 2007, Carey et al. 2008).

Chapter 4: Seasonality in age-structure and longevity of Bactrocera tryoni in subtropical Australia

4.2.3 Study site

Field work was undertaken at Tropical Fruit World (28.17'S, 153.31’E), a commercial agro- tourism farm located in the Tweed Valley, New South Wales, Australia. The site is subtropical, located within 4 km of the coast, with mean summer and winter temperatures, respectively, of

28 ○C and 21 ○C, and a yearly mean rainfall of 1622 mm, falling predominantly in the spring and summer months. The farm grows more than 500 varieties of exotic and native fruits, many of them larval hosts of B. tryoni. In addition to availability of fruit throughout the year, the minimal use of pesticides makes the site suitable for collecting B. tryoni throughout the year

(Merkel et al. 2019).

4.2.4 Sampling dates

The captive cohorts were collected at five time points in the year of 2017: 13th Mar (early autumn), 25th May (late autumn), 17th Aug (late winter), 7th Sep (early spring), and 17th Nov

(early summer). In 2018, the early autumn (16th Mar) and early spring (19th Sep) seasons were repeated. For an unknown reason very few flies were captured in an attempted late autumn

2018 collection, and so this replication is unavailable. The timing of samples was chosen based on the known phenology of B. tryoni in subtropical Australia (Lloyd et al. 2010, Muthuthantri et al. 2010, Merkel et al. 2019). In early autumn flies are still active with high population abundance, but by late autumn the population has declined, and it remains at low levels during winter. In late winter flies starts to come in traps but the population levels are still low. In the early spring B. tryoni population abundance starts to increase rapidly, presumably with the onset breeding. The population abundance peaks in early summer and remains high through to the start of autumn. Our sampling occasions covered the end of winter period just before the start of the spring population increase, the start of the spring increase, periods of high population abundance during summer and early autumn, and then during the late autumn

Chapter 4: Seasonality in age-structure and longevity of Bactrocera tryoni in subtropical Australia decline. Note, we use the term “overwintering” in this paper for convenience to describe the period of low fly abundance which occurs from mid-autumn through to late winter. However, by doing so, we do not wish to infer that the fly is cold-temperature limited. The site’s mean winter average of 21 ○C is well above lower temperature thresholds for B. tryoni and two independent climatic models have each predicted six to eight generations of the fly per year at our site based on day degree accumulation above a 12 ○C lower threshold (Meats 1981, Sutherst and Yonow 1998).

4.2.5 Sampling and rearing of wild caught captive flies (W)

Flies from the field were live captured following their attraction to traps baited with cue-lure

(4-(4-acetoxyphenyl)-2-butanone) or freshly cut slices of ripe tomato, Lycopersicon esculentum Mill. Cue-lure was selected as males are strongly attracted to this chemical and it is used routinely in the field for surveillance and monitoring of B. tryoni (Meats and Hartland

1999, Reynolds et al. 2016). As females are not attracted to cue-lure (Weldon et al. 2008), we tried different methods to capture females, such as fruit-based traps, protein bait and direct hand aspiration, but all of these methods failed to capture sufficient females for experimental use. However, fruit-based traps using tomato did capture large number of males (Tasnin et al.

2020b) and so we continued to use them alongside the cue-lure for the purpose of capturing flies in the field. On every sampling occasion, four cue-lure and four tomato-based traps were hung in fruiting orchards at 8.00 am in the morning and collected at 1.00 pm in the afternoon.

Thereafter, flies were immediately transferred to a white mesh cage (32 x 32 x 32 cm) containing water and sugar and kept in a cool place until returned to the laboratory in an air- conditioned vehicle.

Chapter 4: Seasonality in age-structure and longevity of Bactrocera tryoni in subtropical Australia

On return to the laboratory, on the same day of collection, flies were transferred to a constant temperature cabinet. The initial temperature cabinet temperature was set to mirror corresponding mean field temperatures, and then adjusted (up or down as required) at a rate of

1 ○C every 8 hrs until it reached the standard insectary temperature of 27 ± 1○C. This temperature ramping was done as initial trials showed that this gradual temperature adjustment minimised sudden post-capture mortality. After three days, by which time temperature adjustment was completed, flies were transferred to the insectary and separated in new holding cages as groups of 35 to 40 flies. At this point flies were visually reassessed (first assessment was done at time of capture) to confirm that only B. tryoni were held. The only other local fruit fly species easily confused with B. tryoni is B. neohumeralis (Hardy), and this species is rare at the study site (Merkel et al. 2019). In the insectary flies were maintained at 27 ± 1○C, 65 ±

1 % RH and 12D: 12L, and supplied with water, sugar, and yeast hydrolysate ad libitum. Any flies that died within three days of collection (i.e. before transfer to the insectary) were excluded from post-capture longevity analysis as their death, while possibly natural, could not be separated from mortality due to handling shock.

Because of methodological constraints, it was impossible to collect female flies and all the captive cohorts consist of male flies only. Once sexually mature, male B. tryoni response to cue-lure is constant and independent of age until 15 weeks, when response declines (Tasnin et al. 2020a); sexually mature male response to tomato-odours is independent of age up to and including 15 weeks (Tasnin et al. 2020b). For both cue-lure and tomato-odour, sexually immature flies are non-responsive. Therefore, with respect to the experimental need to sample from the field to an unbiased age estimate (Kouloussis et al. 2009), our sampling will not recover sexually immature males (sexual maturation occurs at approximately 10 days of age in

B. tryoni (Perez-Staples et al. 2007)), and so the presence of very young flies will be under-

Chapter 4: Seasonality in age-structure and longevity of Bactrocera tryoni in subtropical Australia estimated in our study. However, between 10 and (at least) 105 days of age, we believe the males were sampled without age bias.

4.2.6 Collection of infested fruits and rearing of reference flies

Concurrent with the collection of wild adults, except for the early autumn 2017 sample, ripe host fruits available in the field were collected and returned to the laboratory. The fruits collected varied with season, but included carambola, custard apple, guava, mulberry and white sapote. In the laboratory, fruits were placed in ventilated plastic containers on a layer of vermiculite and held in an incubator at 27 ○C and 65 % RH. After 14 days the vermiculite was sieved and obtained pupae were placed in a mesh cage in the same insectary which held the captive flies. During early spring and early summer 2017 very few flies emerged from the fruits and so these dates were excluded from subsequent calculations. Thus, we obtained five reference cohorts that were collected on the 24th May 2017 (late autumn), 17th Aug 2017 (late winter), 16th Mar 2018 (early autumn), 23rd May 2018 (late autumn) and 19th Sep 2018 (early spring). Newly enclosed adults were sexed and placed as a group of 30 to 40 flies in separate mesh cages and held under identical conditions as were flies of the captive cohort. These flies became the reference cohorts (R). Our methodology here differs from earlier studies using the demographic method through the use of multiple reference cohorts (previous studies use only one combined reference cohort created from flies collected at different time points), and through the grouping of individuals (previous studies held insects individually) (Carey et al.

2008). We ran preliminary trials to test the effect of group (40 flies) and individual holding on fly survival and detected negligible differences, but grouping flies dramatically decreased the time spent in the insectary each day.

Chapter 4: Seasonality in age-structure and longevity of Bactrocera tryoni in subtropical Australia

While female flies were hard to collect from the field for the age-structure study due to methodological constraints, female flies that were emerged from infested fruits with the reference males during late autumn 2017 (32 females) and late winter 2017 (75 females) and early autumn 2018 (78 females) were kept in separate cages for whole-of-life longevity study.

However, during late autumn 2018 and early spring 2018, control females longevity study was not possible due to logistic issues.

4.2.7 Data collection

For captive cohorts, the day when wild flies were transferred to the insectary was considered as day zero. The fly cages were checked daily for any dead flies and their post-capture longevity recorded. For reference cohorts, the day when flies emerged was considered as day zero and longevity of the dead flies recorded by daily checking. The dead flies were removed from the cages regularly. If there were days when data was not recorded (an infrequent event), the number of dead flies was averaged over the missed day(s) to obtain daily mortality.

4.2.8 Data analysis

4.2.8.1 Survival function of reference and captive flies

For an overall comparison of survival of captive and reference flies, the Kaplan-Meier survival function was run using combined data from all captive and reference cohorts (IBM SPSS

Statistics 25). To compare the longevity of reference males from the five collections and females from the three collections following creation of the Kaplan-Meier survival functions, pairwise log-rank tests were conducted. For captive cohorts, pairwise log rank tests were conducted to compare the survival of the two captive cohorts collected during the same seasons in early autumn and early spring in 2017 and 2018.

Chapter 4: Seasonality in age-structure and longevity of Bactrocera tryoni in subtropical Australia

4.2.8.2 Estimation of age-structure of wild flies

Our data is sourced from observations of a captive cohort and a reference cohort. The captive cohort data is collected from a population of 푊 wild caught individuals – of unknown age – who were kept in captivity until they died. The length of time that elapses before each individual dies is recorded in an 푊 element vector 퐕.

The reference cohort data was collected from a population of 푅 individuals that were emerged, reared, and died in captivity but originated from wild sources (infested fruits). The proportion of the cohort that are alive on day 푡 − 1, who die during day 푡 is recorded as element 푡 in vector

퐌, whose length is therefore as long as the oldest age (in days) observed in the reference individuals. We applied a 30-day moving-window average to the vector. Since the reference cohort was followed until the last individual dies at age 휔, the last element in 퐌 is equal to 1.

Our goal is to estimate a discrete probability density vector 퐀 that describes the age distribution of the captive cohort at the time of capture, and which provides a best-fit to the observed survival of that cohort. Given that the captive cohort could be composed of multiple sub- cohorts (i.e., multiple reproductive events), we do not assume a parametric form for this probability density function, which may be complicated and multimodal.

Likelihood function

The log likelihood of observing the longevity vector 퐕, given a particular initial age distribution

퐀, is:

푊 휔 푡+퐕푖−ퟏ 퐿퐿(퐕|퐀) = ∑푖=1 ln[∑푡=1 퐀푡 퐌(푡 + 퐕푖) ∏휏=푡 (1 − 퐌(휏))] ………………………Equation 1

Chapter 4: Seasonality in age-structure and longevity of Bactrocera tryoni in subtropical Australia

The initial summation aggregates the independent contribution of each individual in the captive cohort to the likelihood. The second summation considers all possible ages of that individual at the time of capture, weighted by the probability that the individual survives for 퐕푖 days and then subsequently dies (according to the mortality rates observed in the reference cohort).

Fitting the initial age distribution for the captive cohort

Thus, given an age distribution, we can calculate the likelihood of observing a given longevity vector in a captive cohort. The goal is therefore to efficiently search for the age distribution that maximizes the likelihood. We search for the best-fit distribution using nonparametric candidate functions for 퐀. Specifically, we fit a piecewise cubic spline to a set of 15 equidistant points between 1 and 365 days, whose values are initially chosen at random (Fig. 4.1). We calculate the likelihood of this proposed age distribution, and vary the values of the 15 points using a constrained interior-point algorithm to minimize this measure. This algorithm is implemented in Matlab R2019a as the function fmincon. We repeat the search from several randomly selected initial guesses to ensure that our best-fit function is not a local maxima.

Figure 4.1. An example of age distribution produced by maximum likelihood method using hypothetical data.

Chapter 4: Seasonality in age-structure and longevity of Bactrocera tryoni in subtropical Australia

Choosing the reference cohort

As longevity of reference flies showed strong seasonality (a highly unexpected result, see later), instead of combining the data from reference cohorts collected during various seasons (Carey et al. 2008, Carey et al. 2012), a single season’s reference cohort was paired with a captive cohort selected based on maximum likelihood ratio and AIC weight that gave the best fitted age-distribution for the captive cohort.

We calculated the best-fit age distribution for each observed captive cohort, using each available reference cohort in turn. Because there are eight potential reference cohorts (i.e. reference cohorts collected during five seasons, a combined reference cohort from the same season replications collected in late autumn 2017 and 2018, a combined reference cohort from two close seasons [late winter and early spring], and the combination of all five seasons) this results in eight best-fit distributions, and eight maximum likelihood values. We used Akaike

Information Criteria weights (AICw) to determine which of these reference cohorts best explained the observed mortality dynamics. The AICw is effectively proportional to the probability that each model (reference cohort) minimizes the information lost by using that model to represent the truth:

AIC − AIC AICw = exp [ min 푖] 푖 2 where AIC푖 is calculated from the maximum 퐿퐿 (see Eq. 1) for reference cohort 푖.

Defining age-groups

Due to variation in the longevity of reference cohorts, attempts to age captive populations quantitatively gave variable results depending on the reference cohort used in model fitting. In contrast, when the modelled age structure of a captive cohort is plotted against the survival

Chapter 4: Seasonality in age-structure and longevity of Bactrocera tryoni in subtropical Australia curve of the utilised reference cohort, highly consistent qualitative ages could be estimated.

Thus, we report the modelled age groups of captive cohorts as young, middle-age and old as relative measures depending on where the modelled age-distribution curve sits in relation to the survival curve of utilised reference cohort. “Young” populations are those for which the modelled population aligns with the survival curve where it is showing little or no population mortality, “middle-age” populations are those align with the survival curve where it is showing approximately 50% population mortality, and “old” populations are those align with the survival curve where it is showing approximately near 100% population mortality.

4.3 RESULTS

4.3.1 Comparison of captive and reference cohort survival

A total of 901 captive males and 242 reference males were studied across all sampling occasions. The survival function of reference males was significantly different from the captive males (Chi2 = 179.52, Df = 1, P <0.001). The mean (and median) longevity of reference males was 74.8 days (and 57 days), while for captive males the mean (and median) post-capture longevity was 28.8 days (and 19 days). Eleven reference males (4.5%) lived >200 days, with a maximum longevity of 253 days; while for captive males just a single male lived > 200 days, dying at 229 days.

4.3.2 Seasonal influence on the longevity of reference flies

The reference males emerging in the laboratory from field infested fruits collected at five time points during 2017 and 2018 exhibited significant differences in survival probability in pairwise log-rank tests (Table 4.1), despite being held under the same constant conditions from emergence. The late-winter 2017 males were long-lived, with more than 45% living longer than 120 days and the longest living 253 days.

Chapter 4: Seasonality in age-structure and longevity of Bactrocera tryoni in subtropical Australia

Table 4.1. A pairwise comparison of survival function of five cohorts of adult male Bactrocera tryoni that emerged in the laboratory from field infested fruit (= reference cohorts) collected during different seasons in 2017-18 from a site in subtropical Australia. In the laboratory flies were held at 27 ˚C constant temperature and had ad libitum access to water and food.

Seasons No. of Late winter 17/08/17 Early autumn 16/03/18 Late autumn 23/05/18 Early spring 19/09/18 and Dates males Chi2 P Chi2 P Chi2 P Chi2 P Late autumn 31 8.070 0.005 6.822 0.009 0.939 0.333 0.642 0.423 24/05/17 Late winter 77 44.366 <0.001 1.519 0.218 14.504 <0.001 17/08/17 Early autumn 76 14.955 <0.001 4.991 0.025 16/03/18 Late autumn 21 3.353 0.067 23/05/18 Early spring 37 19/09/18

Chapter 4: Seasonality in age-structure and longevity of Bactrocera tryoni in subtropical Australia

The survival probability of late winter 2017 males was significantly greater than for other seasons except late autumn 2018 (Df =1 and P = 0.005; < 0.001; 0.218 and <0.001 in pairwise comparisons between late winter 2017 vs. late autumn 2017; early autumn 2018; late autumn

2018; and early spring 2018, respectively). In contrast, early-autumn 2018 males were short- lived, with only 6% living beyond 120 days and the longest-lived dying at 161 days. The survival probability of early-autumn 2018 males was significantly lower from all other seasons

(Df = 1 and P = 0.009; <0.001; <0.001; and 0.025 in pairwise comparisons between early autumn 2018 vs. late autumn 2017; late winter 2017; late autumn 2018 and early spring 2018, respectively). The survival probability of late-autumn 2017, late-autumn 2018, and early- spring 2018 males were intermediate between these two extremes. While male survival of late- autumn 2017, late-autumn 2018 and early spring 2018 cohorts did not significantly differ from each other, the early spring male cohort had a steeper death curve at the end of the population and no males lived longer than 120 days. In contrast, 22-25% of the late-autumn population lived longer than 120 days (Fig. 4.2).

Chapter 4: Seasonality in age-structure and longevity of Bactrocera tryoni in subtropical Australia

1.0 Late autumn (25/05/17) Late winter (17/08/17) 0.8 Early autumn (16/03/18) Late autumn (23/05/18) Early spring (19/09/18) 0.6

0.4

Cumulative survival function survival Cumulative 0.2

0.0 0 40 80 120 160 200 240 280 Longevity (days)

Figure 4.2. Cumulative survival curves of five cohorts of adult male Bactrocera tryoni that emerged in the laboratory from field infested fruit (= reference cohorts) collected during different seasons in 2017-18 from a site in subtropical Australia. In the laboratory flies were held at 27 ˚C constant temperature and had ad libitum access to water and food.

The control females emerged from infested host fruits collected during three different seasons also showed significant difference in survival probability. Similar to males, the late autumn

2017 and late winter 2017 females were long-lived while early autumn 2018 females were short-lived (Chi2= 12.306, Df = 1, P <0.001 and Chi2= 56.012, Df = 1, P <0.001 in a pairwise comparisons between early autumn 2018 vs. late autumn 2017 and early autumn 2018 vs. late winter 2017 respectively). However, late autumn 2017 and late winter 2017 seasons survival probablity did not significantly differ (Chi2= 3.164, Df =1, P = 0.08) (Fig 4.3).

Chapter 4: Seasonality in age-structure and longevity of Bactrocera tryoni in subtropical Australia

1.0 Late autumn (25/05/17) Late winter (17/08/17) 0.8 Early autumn (16/03/18)

0.6

0.4

Cumulative survival function survival Cumulative 0.2

0.0 0 40 80 120 160 200 240 280 Longevity (days)

Figure 4.3. Cumulative survival curves of three cohorts of adult female Bactrocera tryoni that emerged in the laboratory from field infested fruit collected during different seasons in 2017-

18 from a site in subtropical Australia. In the laboratory flies were held at 27 ˚C constant temperature and had ad libitum access to water and food.

4.3.3 Survival of captive males

Mean and median longevity of captive males showed seasonal variation. Mean and median post-capture longevity was highest during early autumn 2017 at 41.6 and 34 days, respectively, with longevity then declining through late autumn and reaching a minimum in late winter and early spring. The mean and median longevity started to increase again in early summer until peaking again at around 39 days in early autumn 2018 (Table 4.2).

Chapter 4: Seasonality in age-structure and longevity of Bactrocera tryoni in subtropical Australia

Table 4.2. Survival of wild Bactrocera tryoni males (= captive cohorts) in the laboratory. Flies were collected as adults during different seasons in 2017-18 from a site in subtropical Australia.

In the laboratory flies were held at 27 ˚C constant temperature and had ad libitum access to water and food.

Sampling No of males Mean post- Median post- Maximum season studied capture capture longevity longevity (days) longevity (days) (days) Early autumn 50 41.6 34 163 13/03/2017 Late autumn 334 29.9 19 141 24/05/2017 Late winter 126 11.4 6 229 17/08/2017 Early spring 41 16.2 5 120 7/09/2017 Early summer 126 30.4 18 169 17/11/2017 Early autumn 178 39.8 38 152 16/03/2018 Early spring 50 18.7 11.5 135 19/09/2018

4.3.4 Age-structure of wild population of B. tryoni

4.3.4.1 Age-structure estimation and consistency

While the best fit model for each captive cohort was calculated (Suppl. Table 4 S.), we found that applying different reference cohorts to the same captive cohort produced estimated age- structure predictions that were qualitatively consistent, although the ranges of predicted age within structured age-groups varied, i.e. they were qualitatively consistent, but not quantitatively consistent (Fig. 4.4). The reason for this quantitative inconsistency was because

Chapter 4: Seasonality in age-structure and longevity of Bactrocera tryoni in subtropical Australia of the survival variation in the control cohorts. Thus, we focus on presenting the results in qualitative terms (i.e. young, middle-aged, and old) which are generally highly consistent regardless of reference cohort used, and as such gives us confidence in the robustness of the results. We note that in some seasons, notably the autumn samples, the application of different control cohorts to the same captive cohort provided qualitatively different outcomes as well as quantitatively different outcomes: we discuss such cases individually.

4.3.4.2 General pattern of age-distribution

The age-structure of wild B. tryoni populations generated by the likelihood method showed that the demographic structure of the population varied with season. For all seasons the population never consisted of more than three age-groups of individuals. The early-autumn sampling, which had the maximum number of age groups, consisted of a mixed-age population with young, middle-aged and old individuals. The late-autumn population consisted of two age groups of middle-aged and old flies, while the late winter and early spring populations were dominated by very old individuals. However, by early summer, a mix of ages was again apparent with young, middle-aged and old flies. More detail on each season follows.

Chapter 4: Seasonality in age-structure and longevity of Bactrocera tryoni in subtropical Australia

Figure 4.4. Probability density of age (in days) of wild Bactrocera tryoni captured during different seasons in 2017-18 from a site in subtropical Australia. Each graph is the fitted age distribution for the season as estimated using the likelihood function with all possible combinations of reference cohorts. The red line is the survival function of the reference cohort used in the estimation of the likelihood function and the blue curves are age-distribution (L = late, E = early, aut = autumn, win = winter, spr = spring, sum = summer, 17 = 2017 and 18 =

2018).

Early autumn 2017 and 2018: The early autumn 2017 population consisted of a mix of two to three age groups of flies. The most common pattern showed only two age groups, one young and the other either middle-aged or old (Fig. 4.4). The model estimation for the same season in

2018 showed a different age distribution pattern, with the population containing a single age cohort of middle-aged to old-age flies and only a few very young flies. Despite the apparent differences between the years, a pairwise long-rank test of the survival functions of early autumn 2017 and 2018 populations found no significant difference between these two collections (Chi2 = 0.4, Df = 1, P = 0.54).

Late autumn 2017: The age distribution pattern was highly consistent across the models and showed two dominant age-groups of individuals consisting of middle-aged to old males. Two of the eight models also estimated the presence of some young flies (Fig. 4.4).

Late winter 2017: The age-structure predictions across models were again highly consistent, showing that the population contained a single age-group of predominantly old flies. Some models predicted a small number of very young individuals, but middle-aged flies were entirely absent from all models (Fig. 4.4).

Chapter 4: Seasonality in age-structure and longevity of Bactrocera tryoni in subtropical Australia

Early spring 2017 and 2018: The early spring populations from 2017 and 2018 again showed consistency in age-structure, with the common pattern being that the populations contained one dominant age-group of predominantly very old flies, and a second small group of young individuals (Fig. 4.4). The log-rank test comparing the survival functions of the 2017 and 2018 early spring captive cohorts did not detect a significant difference (Chi2 = 0.959, Df = 1, P =

0.33).

Early summer 2017: As for the early autumn populations, the early summer population consisting of a mixed age-group with young, middle-age and moderately old-age flies. As for the early autumn cohorts, the models run with different control cohorts on the early summer captive cohort gave a greater range of both qualitative and quantitative predictions, possibly due to the greater range of fly ages in the field (Fig. 4.4).

4.4 DISCUSSION

Contrary to expectations based on population modelling (Sutherst and Yonow 1998, Yonow et al. 2004), the population of wild B. tryoni at our site during the year was composed of only one or two, very occasionally three, generational age-groups. The presence of old age individuals in late winter and early spring very clearly indicates a gap in population growth from mid- autumn to late winter. The presence of some young individuals in the early spring indicates that the population begins breeding again in the spring and the mixed-age population during summer and early autumn is an indication of continuous breeding from spring to autumn.

Notably, the “autumn to winter” breeding cessation is not temperature driven, as the lower temperatures are not cold enough to stop breeding (Pritchard 1970, Fletcher 1975, Meats and

Fay 1976). Breeding at the site was also not halted due to lack of host fruit for larvae, as fruit are continuously available at that site (Merkel et al. 2019). The following discussion develops

Chapter 4: Seasonality in age-structure and longevity of Bactrocera tryoni in subtropical Australia these points with respect to B. tryoni, but then broadens to examine the implications of the findings, and the methodology used, to understanding the demography of other tropical monsoonal insects.

4.4.1 Seasonality of B. tryoni

4.4.1.1 Seasonal longevity differences in captive control cohorts

The longevity of flies that emerged in the laboratory from field collected infested fruits showed strong seasonality, despite being held under the same constant conditions. Early spring and early autumn flies were relatively short-lived, while late autumn and late winter populations were very long-lived. This is unlikely to be linked to the original host fruit of the flies, as larval rearing host has little impact on the longevity of adult B. tryoni (Balagawi 2006). Similarly, while variation in insect adult lifespan can be induced by dietary variation (Carey et al. 1998,

Lee et al. 2008), and this has been demonstrated in B. tryoni (Fanson and Taylor 2012), it is not relevant in our study as flies were maintained in the laboratory, from emergence, on a standard and unchanging diet. Rather, decreasing longevity in insects is a common life-history trade-off against increasing fecundity (McElderry 2016, Werfel et al. 2017), and while not measured here we strongly suspect the short-lived spring population would have been significantly more fecund than the long-lived winter population. Variation in adult longevity

(and possibly fecundity) in B. tryoni might be an epigenetic modification induced by environmental stimuli experienced during an earlier developmental stage (Kozeretska et al.

2017). Bactrocera tryoni pupae and adults have rapidly enhanced capacity to survive freezing temperatures (-4 ○C) after experiencing a period of cold acclimation in critical periods of earlier developmental stages (Meats 1983), indirect evidence for epigenetic modification of physiology in this species. Further, Kumaran et al. (2018) have demonstrated covalent histone modifications in the genome of B. tryoni, i.e. evidence for the presence of an epigenome. While

Chapter 4: Seasonality in age-structure and longevity of Bactrocera tryoni in subtropical Australia requiring further research to confirm, we believe the evidence points to the different longevities of the control cohorts being attributable to seasonally linked cues, acting on larvae in fruit, leading to histone modification of the genome and subsequent changes in adult longevity.

4.4.1.2 Mechanism of seasonal phenology of B. tryoni

When combined, the data sets strongly suggest that B. tryoni has an endogenous mechanism which allows it to rapidly increase reproductive capacity during the spring/summer wet-season fruiting period of its indigenous rainforest habitat (Drew 1989, Boulter et al. 2006), followed by an adult quiescence mechanism during the non-fruiting dry season. This pattern explains not just our data, but also matches the well documented population phenology of the species, which consistently shows rapid spring increases with populations peaking in late summer and early autumn, before declining again until the following spring (Lloyd et al. 2010, Muthuthantri et al. 2010). The population thus effectively “resets” itself every spring to a single starting generation, rather than having the continuous breeding and overlapping generations predicted by models which assume that temperature and hosts are not limiting for this polyphagous, tropical species (Sutherst and Yonow 1998, Yonow et al. 2004). Further indirect evidence of the endogenous nature of this pattern comes from factory-scale mass rearing data of B. tryoni for the Sterile Insect Technique. Dominiak et al. (2008) showed that flies in a enviroment controlled mass-rearing factory, over several years, had reduced breeding during the winter months, had increasing longevity leading into winter, and decreasing longevity leading into summer. The authors expressed surprise at, but could not explain, a mechanism for their results.

Chapter 4: Seasonality in age-structure and longevity of Bactrocera tryoni in subtropical Australia

4.4.2 Demographic structure and population abundance in tropical insects

The study showed that the demography, and not just the abundance of the tropical B. tryoni varied with season, and such they are not unlike temperate and Mediterranean insects (Carey et al. 2008, Carey et al. 2012, Behrman et al. 2015). The Mediterranean species Ceratitis capitata (Wiedemann) also has an early spring population that consists of mainly old individuals due to a lack of quality breeding hosts in the winter months. However, with the onset of summer and autumn the availability of suitable hosts increases, which results in increased population size and age-structure heterogeneity as the season progresses through to winter (Papadopoulos et al. 2001, Carey et al. 2008). In the temperate region, Drosophila melanogaster Meigen similarly showed a uniformly young early spring population, which rapidly grew such that late season populations contained mixed age individuals (Behrman et al. 2015). For each of the three species, the variation in age-structure at different seasons arise from similar cycles of reproductive activity, although those activities are influenced by different seasonal effects. For the temperate D. melanogaster cold winter temperatures limit breeding; for C. capitata a lack of quality hosts during the mild, wet winter months limits breeding; and for B. tryoni an endogenous quiescence mechanism, that we believe to be an adaptation to surviving a monsoonal dry season lack of hosts (but still operating in a human modified landscape), resets breeding to the start of the wet season.

While restricted to a single species our data has clear implications for, and link to, other tropical insects. While it is well recognised that the availability of resources for breeding can vary greatly in the tropics due to seasonal rainfall cycles (Bonebrake et al. 2010, Santos et al. 2017,

Molleman 2018), we present data here that suggests both a mechanism for maximising the usage of breeding hosts when they are available, and also for aiding population survival in their

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Chapter 4: Seasonality in age-structure and longevity of Bactrocera tryoni in subtropical Australia absence. Longevity is closely linked to reproduction, which may vary with changes in ecological environment (Carey 2001). Thus, short lifespan in tropical insects during favourable seasons is likely to be linked to a greater reproductive output in a breeding-resource rich environment to allow enhanced opportunity to take utilise those resources. On the other hand, a long lifespan is likely to be related to lower reproductive output during a period of scarcity of resources and uncertain environmental conditions (McElderry 2016, Werfel et al. 2017) for example the central African nymphalid Euphaedra medon (Linnaeus) can live for more than nine months in a mode of reproductive diapause to cope with very harsh dry seasons

(Brakefield and Reitsma 1991, Molleman et al. 2007). Seasonality in reproductive strategy has also been reported in several species of tropical satyrine butterflies, where reproductive activity markedly declines during the dry seasons and increses in the wet season (Braby 1995). To these butterfly studies, we now add a dipteran example, which strongly suggests that life-history trade-offs between longevity and reproducton can occur at the seasonal level and likely involve complex physiological and behavioural adaptive mechanisms in tropical insects.

4.4.3 Using the demographic approach for tropical insect age estimation

Our study demonstrated that the likelihood function method we used here, an experimentally similar but mathematically different approach to deconvolution modelling (Müller et al. 2004,

Muller et al. 2007, Carey et al. 2008) can be applied to estimate the age of wild tropical insects qualitatively. However, the method cannot be applied for a quantitative measure unless a biologically appropriate reference cohort can be found. We found it to be biologically quite complex to determine the appropriate reference cohort for a given captive cohort, given the potential extreme longevity of flies in the field, and the endogenous variability across the reference cohorts. We thus paired each captive cohort with all the possible combination of reference cohorts to broaden our opportunity to find a general pattern. While it may be

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Chapter 4: Seasonality in age-structure and longevity of Bactrocera tryoni in subtropical Australia appropriate to use a combined reference cohort for temperate insects (Carey et al. 2008, Carey et al. 2012), we do not recommend it as an approach for tropical species which may show seasonal variation in longevity as relying on a single control cohort, or combining control cohorts, may lead to bias in the predicted ages of captive cohorts. Developing better methodology for appropriatly linking captive and control cohorts is needed to improve the quantitative predictions of the demographic approach when applied to tropical insects.

While there is a conflict about the reliability of using data from the laboratory reared animals to reveal life history traits (Zajitschek et al. 2020), the demographic method we followed here shows that flies that were collected from the wild as an adult and then held for the rest of their life in captivity, or collected as an immature and then held in the captivity for their whole adult life, can still provide novel insights into the aging in wild insects during different seasons.

Thus, we consider the demographic approach of age-estimation to be not only useful to understand ageing in wild, but agree with other authors that it can also be a useful tool for determining information about the reproduction, longevity, and other life history traits of wild insects (Müller et al. 2004, Kouloussis et al. 2009, Kouloussis et al. 2011). Further, with refinement to better align captive and reference cohorts, we believe it has the potential to greatly advance insect demography in the tropics.

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Supplementary Table 4.S. Akaike Information Criteria Weight (AICw) calculated from maximum likelihood for eight potential reference cohorts against each season’s captive cohort. The best-fitted age-distribution for a season were chosen from maximum AICw value which are indicated by bold numbers. Captive Cohorts Reference cohorts Seasons Late autumn Late winter Early autumn Late autumn Early spring Late Late winter 2017 + All and dates 24/05/17 17/08/17 16/03/18 23/05/18 19/09/18 autumn Early spring 2018 seasons 2017-18 Early autumn 0.006 0.029 0.002 0.803 3.13E-123 0.130 0.017 0.013 13/03/17

Early autumn 0.005 0.009 0.493 0.446 8.75E-85 0.034 0.009 0.003 13/03/17

Late winter 8.9E-41 0.560 1.19E-38 7.44E-42 9.75E-79 1.77E-40 0.281 0.158 17/08/17

Early spring 0.089 0.178 0.133 0.025 0.013 0.261 0.183 0.117 7/09/17

Early summer 0.044 0.119 0.082 0.467 1.04E-161 0.135 0.092 0.062 17/11/17

Early autumn 2.81E-19 1.55E-17 4.35E-17 1 1.73E-50 3.87E-08 7.12E-18 3.21E-22 16/03/18

Early spring 19/09/18 0.062 0.208 0.205 0.074 3.53E-41 0.084 0.217 0.150

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Chapter 5: Age-related reproductive potential of Bactrocera tryoni

This chapter is currently under review as:

Tasnin, M. S., K. Merkel, Kay, B. J., Peek, T. and A. R. Clarke. 2020. Age-related reproductive potential of Bactrocera tryoni. Journal of Insect Physiology: in review.

TMS, KM and ARC discussed the design and logic of the experiment, PT provided pupae,

TMS and KBJ carried out the experimental work, TMS and KM carried out data analysis and all authors helped interpret the data, TMS wrote the first draft, all authors worked on subsequent drafts, all authors approved the manuscript.

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5.1 INTRODUCTION

Reproductive potential is one of the basic components of population dynamics (Carey and

Roach 2020). For insects, underpinning reproductive potential are the elements of fecundity and fertility, where fecundity is number of eggs laid by a female and fertility is the proportion of eggs hatched which may be linked to either, or both, male and female parent (Leather 1995,

Shelly 2000). Age is an important factor which affects reproductive potential, with young organisms generally having a higher reproductive potential than older organisms, hence the growth and then decline of a population as it ages (Cole 1957, Charlesworth 1994).

Age influences reproductive potential in a variety of insects (Iliadi and Boulianne 2010,

Johnson and Gemmell 2012, Leather 2018, Túler et al. 2018). A female’s fecundity and fertility are maximal when reproductively young, and then gradually decreases into old age

(Novoseltsev et al. 2004, Túler et al. 2018). For example, female Drosophila melanogaster

Meigen laid its daily maximum number of fertile eggs at four days after adult emergence, steadily declining thereafter before reaching a minimum daily number of fertile eggs at 50 days of age (David et al. 1975). Similar to females, age-related reduction in sperm quantity, quality and fertilization success is also observed in males (Ponlawat and Harrington 2007, Hale et al.

2008, Johnson and Gemmell 2012). For example, in D. melanogaster, sperm production declines after 40 days of age, fertilization success starts declining at 28 of age, and viable offspring production becomes minimal by 12-15 weeks of age [reviewed in Grotewiel et al.

(2005)].

Frugivorous tephritid fruit flies (Diptera: Tephritidae) include many species of highly destructive horticultural pests (Norrbom et al. 1999). Generally, fruit flies become sexually mature within one to three weeks of emergence (Blay and Yuval 1999, Jácome et al. 1999,

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Chapter 5: Age-related reproductive potential of Bactrocera tryoni

Taylor et al. 2013). After reaching sexual maturity, female fecundity and fertility reach a peak level within only a few days, stay at that level for a variable time of days to weeks depending on species, and then start to decline (Blay and Yuval 1999). For example, Anastrepha serpentina (Wiedemann) becomes sexually mature at 15-18 days post-emergence, net fecundity reaches a peak level within 20 days and hatch rate peaks at 21 days. These high rates of fecundity and fertility are retained for 50 to 60 days, depending on diet, but after that both dramatically decline (Jácome et al. 1999). In frugivorous tephritids, the quantity and quality of male sperm is also affected by age. For example, in the fruit fly Ceratitis cosyra (Walker), the quantity of sperm was very low at five days of age, increased with sexual maturation until reaching a maximum at 10 days of age and, plateauing there before declining at 25 days of age

(Roets et al. 2018). In wild Anastrepha ludens (Loew) both the quantity and quality of sperm declined at 64 days of age (Herrera‐Cruz et al. 2018), but fertilization success, which peaked at 25 days of age, started to decline by 30 days of age (Harwood et al. 2015). Additionally, the male probability of mating is known to decline in C. capitata with increasing age in both competitive and non-competitive conditions (Papanastasiou et al. 2011).

Bactrocera tryoni (Froggatt), the Queensland fruit fly, is the most damaging tephritid fruit fly pest in Australia (Clarke et al. 2011). The fruit fly becomes sexually mature and mate within

10-12 days after emerged from the pupal stage which requires a minimum nutritional, physiological and environmental conditions (Meats and Khoo 1976, Taylor et al. 2013).

Depending on the quality of the male partner, B. tryoni females mate only once or a few times in their life, with diminished sexual receptivity after mating (Fay and Meats 1983,

Radhakrishnan and Taylor 2007, Clarke 2019). Females have the capacity to retain and utilize sperm stored in the spermatheca for up to seven weeks after mating (Barton-Browne 1957,

Perez‐Staples et al. 2007). Males, in contrast, can mate on consecutive days and can replenish

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Chapter 5: Age-related reproductive potential of Bactrocera tryoni their sperm daily to supply an equal amount of sperm at consecutive mating (Radhakrishnan et al. 2009).

Significant research has been conducted on the reproductive potential of mass-reared B. tryoni with respect to varying the diet of young (sexually immature and just mature) adults (Perez-

Staples et al. 2007, Perez‐Staples et al. 2008, Pérez-Staples et al. 2009, Akter et al. 2017a), but only a few studies have focused on the species’ reproductive potential with increasing age after reaching sexual maturity. In a competitive environment, young (14 days old), large and experienced males achieved more mating than old (28 days), small and naïve males, respectively (Ekanayake et al. 2017a), but in a non-competitive condition mated and virgin males obtained almost equal numbers of mating, at a level which remained constant, until seven weeks after maturation (Fay and Meats 1983). Female fecundity gradually increases after sexual maturation reaching a peak at 4-5 weeks of age and then declines thereafter to eight

(Kumaran et al. 2013) and 10 weeks of age (Fitt 1990). While limited aspects of how male and female reproductive potential are influenced by age for this species are known, there is no study which investigates lifelong fertility of either sexes.

Bactrocera tryoni overwinter as adults (Clarke et al. 2019) and the late winter and early spring population consists of predominantly old to very old individuals, replaced over time with a new generation of young individuals (Chapter 4 data). However, despite the predominance of old individuals and the presumed negative consequences that would have for population increase,

B. tryoni populations show rapid increase from early to late spring (Lloyd et al. 2010,

Muthuthantri et al. 2010). This leads to questions about the reproductive potential of the overwintered males and females, and their interaction with the new season individuals. When overwintering flies become active in the late winter and early spring is the population’s

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Chapter 5: Age-related reproductive potential of Bactrocera tryoni reproductive potential limited just to old males mating with old females? If so, is viable egg production very low, as might be predicted from research on other tephritids; or if old males and females have the opportunity to mate with a young partner does their advanced age become less important as in many insects the age of a mating partner is known to affect the reproductive success of their partner (Avent et al. 2008, Verspoor et al. 2015, Liang et al. 2019).

With this background, the aim of this study is to understand the role of an individual’s age, and their mating partner’s age, on the reproductive potential of male and female B. tryoni from sexual maturation (11 days old) to death. In laboratory-based experiments we answer the following questions: (i) do a female’s age-related fecundity and fertility patterns vary depending on the age of male mating partner; (ii) does male age impact the fertility of eggs laid by the female mating partner; and (iii) is the longevity of male and females affect by the presence of a young or same-age mating partner?

5.2 MATERIALS AND METHODS

5.2.1 General structure of experiment

The study was conducted to determine the effect of age on the reproductive potential of male and females from day 11 after emergence until their death, in presence of a same-age or young mating partner. The fecundity and fertility of an individual female was measured by the number of eggs laid and hatched; while male fertility was assessed indirectly by measuring the hatch rate of eggs laid by the female partner. A total of 70 males and 70 females were studied, where half of the males and females had access to a same-age virgin mating partner (replaced weekly), while the other half received a young virgin partner (replaced weekly). Each fly was housed in an individual chamber along with a single partner. Egg collections were made every second day and hatch rate was assessed four days after egging. Individual chambers were checked

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Chapter 5: Age-related reproductive potential of Bactrocera tryoni daily to record death. We note the indirect measure of recording male fertility and limitations that imposes on interpretation. When paired weekly with a young virgin partner, then a change with male age in the partner’s egg hatch rate may not unreasonably be interpreted as a change in male fertility, but when paired with same-age virgin females then a change in egg hatch rate may be due to changes in either or both sexes. Our experimental design allows us to tease these two influences apart.

5.2.2 Insects

Bactrocera tryoni pupae were obtained from a culture (F14 from the wild) maintained by the

Queensland Government Department of Agriculture and Fisheries, Brisbane, Australia. The use of a laboratory line was not ideal as selection in the laboratory can lead to increased reproduction at the expense of longevity (Gilchrist et al. 2012), but it was logistically unfeasible to collect enough wild flies for experimental need. Additionally, experience with culturing wild flies also shows that they would not have used the artificial egging devices which were operationally required. Because of possible laboratory selection effects, the use of cultured flies for these experiments should be kept in mind when extrapolating our results to wild flies.

5.2.2.1 Experimental flies

Five-hundred pupae were placed into a white mesh cage (32 x 32 x 32 cm), supplied with water, sugar and yeast hydrolysate ad libitum and held in an insectary at 27 ○C, 65% RH and 14L:10D.

One-hundred males and 100 females emerging within a 24-hour period were separated by sex and housed in two different cages under the same rearing conditions until set up into individual holding cages.

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5.2.2.2 Same-age mating partners

At the same time as experimental flies were established, 500 pupae were placed into each of four white mesh cages and held in the same conditions as described above. Flies emerging over a three-day period were separated by sex within three days of emergence and a total of 800 males and 800 females were placed, 100 each, into 16 cages. From these cultures the virgin,

“same-age” mating partners were drawn weekly.

5.2.2.3 Young mating partners

Each week the experiment ran, beginning 19 days before the first experimental mating, 100 newly emerged male and female flies were placed into separate cages and held in the same conditions as above. From these weekly-renewed cultures, the “young-age” mating partners were drawn. Young-age partners were from 17-19 days old (i.e. sexually mature) and virgin when introduced to the experimental flies.

5.2.3 Experimental setup

5.2.3.1 Individual chambers

Individual fly chambers were prepared using a 1000 ml plastic container. The lid of each container had a circular opening cut into it, sealed with an empty 10ml cup that could be easily removed and replaced. Inside each chamber a sugar cube, water and yeast hydrolysate were provided ad libitum (Fig. 5.1). Ten days after emergence, 70 males and 70 females were taken from the “experimental fly” cultures and placed individually into 140 chambers. These flies were then randomly assigned to four groups: 35 males with same-age partner; 35 males with young- age partner; 35 females with same-age partner; 35 females with young-age partner. All chambers were individually numbered.

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Figure 5.1. Individual fly chamber supplied with water, sugar cube and yeast hydrolysate ad libitum. A single male and female Bactrocera tryoni pair were housed in the chamber and egging cups were provided every second day through the circular opening by withdrawing and replacing the empty cup.

5.2.3.2 Mating partners

For each of the experimental flies, there was a corresponding mating partner. Mating partners were kept in each chamber with the experimental fly (i.e. there were two flies, a male and female, in each chamber at any given time), but were changed weekly. Same-age female and male treatments were provided with a virgin same-age male or female partner, respectively.

Thus, in the first week of the experiment (at age 10 days) both groups received a 10 day-old mating partner, the following week they received a 17 day-old partner, and so on: thus at any given time the mating partner was the same age as the experimental fly. On the other hand,

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Chapter 5: Age-related reproductive potential of Bactrocera tryoni young-age female and male treatments were, each week, always provided with a young male or female partner of 17 to 19 days age. Mating partners were replaced with new virgin mating partners rotationally at either five or seven days after introduction, allowing them to be done at the same time as an egg collection. The time duration can be considered enough to measure fertility, as females are known to be more fecund during the first five days after mating (Perez‐

Staples et al. 2007). During changing of the mating partners, each fly chamber was checked carefully for the availability and quality of food which was replaced as required.

5.2.3.3 Longevity

All fly chambers were checked daily for dead flies. When an experimental fly died the age at death was recorded and the experiment terminated for that individual. However, if a mating partner died, a new partner of the same age was added.

5.2.4 Collection and assessment of eggs

Every 2nd day, from day 11 after emergence, egging cups were provided to each container to assess female fecundity. Egging cups were prepared in the morning by lining the inside of a 10 ml, lidded cup with black filter paper soaked with apple juice. Both the cup and its filter paper lining were then punctured multiple times with a pin. Following that the empty cup blocking the hole in the lid of each fly chamber was removed and immediately replaced with an egging cup, labelled to match the container’s number. Egging cups were placed before 9.00 am and were removed the following day before 8.00 am.

Following collection, each egging cup was visually inspected for the presence of eggs. Eggs were generally found in clusters on the black filter paper liner, which was extracted (along with any eggs not on the filter paper) from its egging cup and transferred to a petri dish lined on the

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Chapter 5: Age-related reproductive potential of Bactrocera tryoni bottom with a wet, white filter paper. After transfer, the egg clusters on the black filter paper were gently spread with a fine paintbrush and the petri dish covered. All the petri dishes were placed into a sealed 20 L plastic container, which was then covered in cloth and held in a temperature cabinet at 26○C temp, 65% RH, 12L: 12D. This handling and storage protocol for the eggs was developed following preliminary experiments and resulted in minimal or no egg mortality. The petri dishes were left for four days in the cabinet, as eggs hatch within 2 to 4 days at 25○C (Bateman 1967). Under a stereomicroscope the total number of eggs laid, and the number of eggs hatched and unhatched were counted.

5.2.5 Data analysis

5.2.5.1 General

All the data analysis and visualisation were performed using R (Version 3.6.3), IBM SPSS

Statistics (Version 25) and Sigma Plot (Version 13, Systat Software, San Jose, CA). In this study, fly age and mating partner group (i.e. young or same-age) were the explanatory variables, while the number of eggs laid and hatched were response variables. The number of eggs laid by females was treated as count data with a poisson distribution, while the egg hatch rate was treated as proportional data with a binomial distribution. To calculate the fecundity of females any zero counts before the first egg was laid were removed from the data set as it was assumed that the females were still immature. However, once females started laying eggs, any zeroes in any egg-laying event was counted as a true zero. Male and female data were analysed separately, with only longevity compared between the sexes. The age of individual flies was log-transformed to normalize variances and achieve model convergence. In addition, we introduced an observation-level random effect to avoid Type I errors due to overdispersion

(Harrison 2014). Optimal models were determined using likelihood ratio tests.

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5.2.5.2 Effect of female age and presence of young vs. same-age mating partner’s on female

fecundity and fertility

The effect of female age and the presence of young vs. same-age male on fecundity was tested using Generalized Linear Mixed Model (GLMM) for count data with a square root link- function. To account for repeated observations of females a Female_ID was added as a random term. The model was fitted using the function ‘glmer’ from the R package ‘lme4’ with the following arguments: formula = No_Eggs ~ log(Female_Age) * Male_Age_Group +

(1|Female_ID) +(1|obs), family = poisson(link = sqrt), control = glmerControl (optimizer =

“bobyqa”), data = data, verbose = TRUE.

To determine the effect of female age and the presence of a young vs. same-age male on egg hatch we used a GLMM for binomial data with the following arguments: formula = Hatch_rate

~ Female_Age * Male_Age_Group + (1|Female_ID) + (1|obs), data = data, family = binomial, control = glmerControl(optimizer = "bobyqa"), verbose = TRUE.

5.2.5.3 Effect of male and mating partner’s age on partner’s egg hatch rate

To determine the effect of male age and mating, with same age or young mating partner, on egg hatch of the partner we used a GLMM for binomial data with the following arguments: formula = Hatch_rate ~ Male_Age * Female_Age_Group + (1|Male_ID/Female_ID) + (1|obs), data = data, family = binomial, control = glmerControl (optimizer = "bobyqa"), verbose =

TRUE. The random term was nested to allow for the variance of females mated with a single male.

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5.2.5.4 Longevity of males and females

The survival function of two groups of males and females were compared between groups within each sex and between sexes by Kaplan-Meier survival function followed a pairwise log- rank test.

5.3 RESULTS

5.3.1 Effect of age and mating partner’s age on female fecundity and fertility

The fecundity of female flies was significantly affected by female age (Chi2 = 947.64, Df = 1,

P < 0.001), with fecundity declining with age (Fig.5.2). There was no difference in fecundity of females exposed to young and same-age males (log (Female_Age)*Male_Age_Group: Chi2

= 0.05, Df = 1, P = 0.82; Male_Age_Group: Chi2 = 0.33, Df = 1, P = 0.57). The total number of eggs laid by 70 individual females during the life-time greatly varied from a minimum 49 eggs to a maximum 1211 eggs. The mean life-time fecundity of a B. tryoni female in this experiment was 624.6 ± 29.9 eggs laid over a mean life span of 61.3 ± 2.4 days.

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100 Female with same-age partner Female with young partner

Number of eggs (mean + 1SE)Number of eggs 0 0 20 40 60 80 100 Age (days)

Figure 5.2. The mean (± 1SE) number of eggs laid by Bactrocera tryoni females every second day from day 11 to death when paired with a young or same-age virgin mating partner which was replaced weekly (n = 35 individuals for each group).

The hatch rate was significantly affected by the female’s age and the strength of the effect depended on the mating partner age group (log (Female_Age)*Male_Age_Group: Chi2 = 4.33,

Df = 1, P = 0.04). Initially, the hatch rate in eggs from females with a young mating partner was higher than in the eggs from females with a same age partner. The hatch rate declined in both groups for eggs from females older than 20 days but did so more strongly in the group with the young mating partner [estimated slope parameter (m): m = -1.15, female with same- age male; m = -1.77, female with young male)]. However, the rate again diverged in females with young mating partner after 60 days of age but the female with same-age males consistently showed the declining trend. (Fig. 5.3).

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100 Female with same-age partner Female with young partner

Hatch rate (mean + 1SE) 20

0 0 20 40 60 80 100

Age (days)

Figure 5.3. The mean (± 1SE) hatch rate (%) of eggs laid by Bactrocera tryoni females every second day from day 11 after emergence to death when paired with a young or same-age virgin male partner which were replaced weekly (n = 35 individuals for each group).

5.3.2 Effect of male age and female mating partner age on egg hatch rate of the female

partner

The hatch rate of eggs of the female partner was significantly affected by the male’s age and the age of the female (log (Male_Age) *Female_Age_Group: Chi2 = 37.99, Df = 1, P < 0.001).

The hatch rate declined with the age of males that mated with females of the same-age (m = -

1.46). In contrast, the hatch rate of eggs from young females did not show a decline over time but instead increased with the age of the males (m = 0.91) (Fig. 5.4).

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100 Male with same-age partner Male with young partner

Hatch rate (mean + 1SE) 20

0 0 20 40 60 80 100 120 140 160

Age (days)

Figure 5.4. The mean (± 1SE) hatch rate (%) of eggs laid by young or same-age Bactrocera tryoni females when paired weekly with aging males from day 11 after emergence until male death (n = 35 for each group).

The fecundity of females’ partner was not statistically analysed as males were paired with a new virgin female weekly and the experiment was not designed to assess the effect of male age on female’s fecundity. However, the eggs laid by the young and same-age female partners is graphically presented to show the egg laying trend only (Suppl. Fig. 5 S).

5.3.3 Longevity of males and females

The log-rank test showed no significant differences in the longevity of males mated with young or same-age mating partner (Chi2 = 2.472, Df = 1, P = 0.116). Similarly, female longevity was also not affected by the age of the mating partner (Chi2 = 0.074, Df = 1, P = 0.786). The log- rank test detected that males and females had a significant difference in their survival (Chi2 =

45.067, Df = 1, P < 0.001). Males lived significantly longer than females with a mean and

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Chapter 5: Age-related reproductive potential of Bactrocera tryoni median longevity 92.7 ± 3.9 and 98.0 ± 4.1 days, respectively, while female mean and median longevity was 61.3 ± 2.4 and 56.0 ± 2.5 days, respectively (Fig. 5.5).

1.0 Female with same-age male Female with young male 0.8 Male with same-age female Male with young female

0.6

0.4

Cumulative survival function survival Cumulative 0.2

0.0 0 40 80 120 160 200 Longevity (days)

Figure 5.5. Cumulative survival curve of male and female Bactrocera tryoni paired with a same-age or young mating partner (n =35 for each group).

5.4 DISCUSSION

Independent of the age of male mating partner, increasing age negatively affected the fecundity and fertility of female B. tryoni, after both attributes peaked at approximately 20 days. When

B. tryoni males were mated consistently with a young virgin partner, the indirect evidence of the partner’s egg hatch rate suggested that male fertility increases with increasing age. No such affect was seen when males were mated with a same-age virgin female, probably because of the age-related change in female fecundity and fertility. Typical of many insects, female B. tryoni have a shorter life span than males, with the longevity of both sexes unaffected by the age of mating partner.

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5.4.1 Effect of female age and mating partner age on fecundity and fertility

The fecundity of females peaked at three weeks of age and then steadily declined with age. A similar decline in fecundity with age has been previously reported in B. tryoni, although the peak of fecundity was reported at four to five weeks of age (Fitt 1990, Kumaran et al. 2013).

Age-related declines in female fecundity have also been reported other tephritid species (Blay and Yuval 1999, Jácome et al. 1999).

While the age of the male partner did not influence the female fecundity pattern, female fertility was affected by both female age and mating partner age. The pattern of fertility and the peak timing was different in the two treatment groups. While both groups of females had an initial increase in hatch rate in the first week of the experiment, females mated with same-age males still had a 15-20% lower hatch rate than females mated with young males. This initial difference in fertility might be due to differences in degree of sexual maturation and the amount of stored sperm of the still very young male partners, which at this stage were still younger than the males of the “young male” treatment. In our experiment, the “same-age” virgin males were very newly sexually mature (10 days of age) when used in the first week of the experiment and may have had less stored sperm compared to the 17-19 day-old “young-age” virgin males. This is seen in A. ludens, where males reach maturity at 20 days of age, but their insemination success peaks at between 25 and 30 days of age (Harwood et al. 2015). As female B. tryoni are known to have reduced sexual receptivity up to 30 days after their first mating (Radhakrishnan et al. 2009), driven by quality of seminal fluid not sperm number (Radhakrishnan and Taylor

2007, Radhakrishnan et al. 2009) a difference in received sperm quantity at the time of first mating may account for the differences in egg hatch between the two treatment groups of females not just for the first week, but for nearly a month after (Fig. 5.3). Re-mating later in life by both groups of females would have negated this initial effect. While the mean data

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Chapter 5: Age-related reproductive potential of Bactrocera tryoni presented in the Fig. 5.3 appears to show a reversal of female fertility between the two treatment groups beyond approximately 60 days of age, this was driven by the results of only a very few individuals (hence the large errors) and the model did not predict a treatment difference.

5.4.2 Effect of male age and mating partner age on hatch rate of partner’s eggs

The hatch rate of a male partner’s eggs varied with the age of the male and the male’s partner.

When males were weekly provided with a young virgin female partner there was a significant increase in the partner’s egg hatch rate of eggs with increased male age, which we interpret as increasing male fertility with age. While the males of many insects show reduced fertility with increasing age (Harwood et al. 2015, Herrera‐Cruz et al. 2018, Roets et al. 2018) this is not inevitable, as it has been shown in several species of Drosophila that older males demonstrate greater mating frequency, higher insemination rate and fertility than younger counterparts

(Prathibha et al. 2011, Somashekar and Krishna 2011, Verspoor et al. 2015). However, to our knowledge, this study is the first record in a tephritid fruit fly which shows increasing fertility trend in females mated with aging males. In contrast to increasing egg hatch when aging males were mated with young females, the egg hatch of aging females declines. We believe this pattern is likely driven by the identified decline in female fertility with aging as it runs counter to the male change in fertility with age.

5.4.3 Implications for Bactrocera tryoni population demography

Bactrocera tryoni egg production and hatch rate declined with age when same-age partners were involved. The evidence suggests that this was due to the decline of female fertility with age, rather than due to changes in male fertility, as female fertility declined with age even when having access to young males. Despite the decline in production, a small number of viable eggs were still being laid nearly to the end of a female’s life. In the field, during winter, B. tryoni

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Chapter 5: Age-related reproductive potential of Bactrocera tryoni longevity is longer than recorded here (O'loughlin et al. 1984), due presumably to slowed day- degree accumulation and the fact that, as a laboratory adapted population, our flies may have been indirectly selected for reduced longevity. Nevertheless, the data suggests that the very old flies present in the field at the end of winter are physiologically capable of starting the next generation. Old males, if they then have access to young F1 female partners, have the capacity to help further contribute to the rapid spring population growth observed in the field. However, old females appear unlikely to further contribute to new season’s population beyond getting it begun as their fecundity will not again increase even if mated with a young F1 male.

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100 Male with same-age female partner Male with young female partner

Number of eggs (mean + of 1SE) eggs Number (mean

0 0 20 40 60 80 100 120 140 160 Age (days)

Supplementary Figure 5 S. The mean (± 1SE) number of eggs laid by young or same-age

Bactrocera tryoni female partners paired with the aging males weekly from day 11 to death (n

= 35 individuals for each group).

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Chapter 6 : General discussion

Chapter 6: General discussion

6.1 GENERAL DISCUSSION

In this thesis I focused on the demography and aging of Bactrocera tryoni to better understand its field ecology in subtropical Australia. For studying demographic structure, I used a demographic approach of age estimation, the accuracy of which depends on sampling wild individuals without age-bias. To assess any age-biases when trapping using volatile-based traps, I started my thesis by testing the effect of age on the olfactory response of male B. tryoni to cue-lure and female B. tryoni to guava-juice odour (Chapter 2) and male response to tomato- odour (Chapter 3). In Chapter 4 I captured wild males using cue-lure and tomato-odour and used those flies, plus reference flies, to estimate the age-structure of the wild population at different times of the year. This age study showed that the late winter and early spring population were composed of predominantly old individuals which led me to assess the reproductive potential of old B. tryoni in Chapter 5.

Here I summarise and collate the results of these chapters and discuss the implication of my study for understanding the demography of the field populations of B. tryoni. I then discuss the implications of my research for pest management and, finally, address future research directions.

6.2 SUMMARY OF THE THESIS RESULTS

The result of the olfactory experiments showed impacts of age on the olfactory response of both sexes of B. tryoni to the tested odours. Males showed a constant attraction to cue-lure from sexual maturation (3 weeks) until 12 weeks of age, but that response significantly declined

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Chapter 6 : General discussion at 15 weeks of age. The decline at 15 weeks appeared to be related to a loss of both olfactory and locomotory capacity, suggesting that for that particular cohort of flies they were approaching the ends of their lives. In contrast to males, females showed their highest attraction to guava-odour at three and six weeks of age which then gradually and continuously declined with age. Similar to their cue-lure response, males also responded to tomato-odour once they matured but they retained their attractiveness until the end of the trial at 15 weeks of age. In the field male B. tryoni responded to tomato-based traps throughout the year and although the number of males attracted to tomato-based traps varied with respect to numbers caught at cue- lure traps, the mean number of flies captured by the two odour types did not significantly differ.

The potential to use fruit-based odour traps for the sampling and management of male

Bactrocera fruit flies has been largely ignored by both researchers and field practitioners, and my Chapter 3 (male fruit odour response) is largely written to raise the profile of this opportunity.

As males did not respond to cue-lure and tomato-based odours until sexual maturity, the age study of wild flies trapped by these volatiles will have underestimated the presence of very young flies (i.e. < ~ 10-18 days of age), but the methods can capture flies from approximately two to 12 (cue-lure) or 15 weeks (fruit odour) of age without age-bias. For very old flies (>15 weeks of age) their odour response remains unknown, but when such flies occur in the field

(i.e. at the end of winter) they dominate the population and so a decline in odour response at advanced age, if it occurs, becomes of little importance for age-structure estimation. It could, however, be an issue if field sampling was being undertaken to specifically detect such very old flies, e.g. to determine if an invasive population of flies had survived winter.

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Chapter 6 : General discussion

My study showed that the age-structure of the B. tryoni population at my field site varied greatly with season. At any given time of the year, modelling predicted the population was composed of no more than three overlapping generations, with one or only two generations the most common pattern. During early summer and early autumn, the population was composed of two to three age-groups with young, middle-age and old-age flies. However, the age- structure heterogeneity decreased through the season, so that the late autumn population was composed of two prominent cohorts of middle-aged to old-aged flies and the late winter population was composed of only a single cohort of old flies. The early spring population was composed of predominantly very old flies and a small cohort of young flies which indicated the initiation of breeding activity after winter. Because of sampling bias (i.e. the inability to trap flies until sexually mature), this new season’s cohort may have been slightly larger, or have appeared slightly earlier, than the modelling predicted.

Very unexpectedly, reference flies that emerged in the laboratory from field-collected infested fruits showed strong seasonality in their adult longevity, despite being held under constant conditions. The early spring and early autumn populations were short-lived while the late autumn and late winter populations were relatively long-lived. This observation goes against standard assumptions of insect development and aging (Gullan and Cranston 2014) and may explain why attempts to model B. tryoni seasonal population dynamics have only been partially successful (Yonow et al. 2004).

In the last experimental chapter, the age-related reproductive potential study showed that age has an impact on the fertility of both male and female B. tryoni. The fecundity of females declined with increasing age, a pattern which was not influenced by the age of their mating partners. However, a female’s fecundity and fertility (as assessed by egg hatch rate) was

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Chapter 6 : General discussion influenced by her age and the age of her mating partner. Females mated with young males had higher egg hatch rates as they aged than did females mated with a same age male. Although the fecundity and hatch rate of both groups of females declined with age, females still had the capacity to produce some viable eggs in extreme old age. A male’s ability to fertilize a female was affected by both the age of the male and the female partner’s age. When a male mated with a same-age female, the egg hatch rate of their female partner declined with increasing age of both sexes. In contrast, when a male was mated with a young female partner throughout their life, the egg hatch rate of their female partner increased with male age which is indirect evidence of increased male fertility with age and, to my knowledge, this is the first time this has been recorded in any tephritid.

6.3 THE DEMOGRAPHY AND UNDERLYING MECHANISMS OF POPULATION

PHENOLOGY OF QUEENSLAND FRUIT FLY

Temperature-driven day-degree accumulation models predict continuous breeding of B. tryoni in tropical and subtropical Australia with 6-8 overlapping generations if host-fruits are available (Meats 1981, Sutherst and Yonow 1998, Yonow et al. 2004). However, my study showing that the field population is generally composed of only one to two generations (very rarely three) at any given time, with a distinct break in breeding during the middle months of the year, indicates that the population will complete a maximum of only four, or at most five generations in a year.

Queensland fruit fly shows a distinct pattern of population phenology in subtropical Australia, with a decline in abundance during winter and a rapid increase in spring (Lloyd et al. 2010,

Muthuthantri et al. 2010; Lloyd et al. 2013). My study shows that not only the abundance but also the demographic structure of the field population changes at these times, a finding which

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Chapter 6 : General discussion has distinct commonalities with other insects that live in temperate and Mediterranean regions

(Carey et al. 2008, Carey et al. 2012, Behrman et al. 2015). Seasonally induced changes in the availability of breeding resources leads to changes in the level of breeding activity by a local population during the year, resulting in age-structure variation (Carey et al. 2008, Carey et al.

2012, Behrman et al. 2015). For example, the early spring population of Drosophila melanogaster was composed of uniformly young individuals due to the synchronized emergence of overwintering adult flies after winter dormancy and reproductive diapause: age- structure heterogeneity increased with seasonal progression through the summer due to continuous breeding activities (Behrman et al. 2015). Similarly, the presence of old Ceratitis capitata individuals in the Mediterranean during early spring resulted from a breeding gap over the winter which was due not to low temperatures (the Mediterranean winter is mild) but rather due to a lack of suitable hosts for breeding. The subsequent availability of host fruits after the winter gap saw breeding resume resulting in young individuals in the late summer and autumn population (Papadopoulos et al. 2001, Carey et al. 2008). While in D. melanogaster and C. capitata winter temperatures and the availability of suitable hosts, respectively, limit reproduction, neither of these factors was limiting for Queensland fruit fly at the site where I worked, or generally in other human-modified landscapes of coastal and sub-coastal

Queensland and northern New South Wales. Nevertheless, the population still shows a winter decline, and my demography chapter indicates a clear breeding gap from mid/late autumn to late winter.

As breeders in the fruits of tropical forests (Clarke 2019), the potential hosts of B. tryoni may be seasonally restricted because of monsoon driven flowering and fruiting in their endemic rainforest habitat (Boulter et al. 2006). I strongly suspect that the temporally restricted breeding of flies that I detected is driven by an endogenous mechanism in response to restricted breeding

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Chapter 6 : General discussion resources in their endemic habitat during the dry season. The combined data of seasonality in age-structure and longevity strongly suggest that B. tryoni has an endogenous mechanism which allows them to restrict their breeding during resource-poor dry seasons (late autumn and winter) when suitable hosts are lacking in their endemic rainforest habitat. This results in a decline in population abundance, but corresponding increases in longevity allow individuals to survive the unfavourable season until fruits are again available the following wet season. Then during a resource enriched wet season (spring and summer) Queensland fruit fly can shorten their lifespan as a likely trade-off for increased reproductive capacity, thus making best use of the seasonally available fruits. This hypothesis would not only explain my own data but also matches with the distinct phenology of B. tryoni in the subtropical region (Lloyd et al. 2010,

Muthuthantri et al. 2010). However, a major assumption of this analysis is that longevity is traded-off against fecundity, i.e. increased longevity lower fecundity, decreased longevity higher fecundity. While this is a very common life-history trade-off in animals (McElderry

2016, Werfel et al. 2017), it is not something I have tested in my thesis as the need to do so was not recognised until too late in the process. While some indirect data from B. tryoni culturing suggests this fecundity is depressed during winter (Dominiak et al. 2008), direct experiments are needed to determine if the short-lived spring populations have higher fecundity than the long-lived autumn and winter populations.

6.4 IMPLICATIONS OF THE STUDY

6.4.1 Basic implications Studying the demographic structure and aging of a wild population of B. tryoni has helped to understand, or at least propose hypotheses for the underlying mechanisms influencing the seasonal phenology of Queensland fruit fly. As the longevity of the fruit fly changes with season, and there are likely complex physiological mechanisms modifying physiology with

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Chapter 6 : General discussion seasons, then it becomes easier to see that prediction of generation number merely based on the local temperature data (Meats 1981, Sutherst and Yonow 1998, Yonow et al. 2004) may lead to over or underestimation. Similarly, recognising that B. tryoni is a tropical insect with adaptations for surviving in a monsoon tropical environment, makes it easier to understand why previous attempts at predictive modelling have largely failed (Muthuthantri et al. 2010).

For example, Yonow et al. (2004), attempting to model B. tryoni populations relying on temperature and changing day-length (classical drivers of temperate insect population phenology (Bateman 1968, Pritchard 1970, Fletcher 1975), by their own admission failed to capture the end of winter/early spring population dynamics(see the discussion in that paper).

They could not explain why they were failing and while my study does not provide information on the mechanism which triggers B. tryoni from survival to reproduction, it does point future researchers towards looking at quiescence mechanisms utilised by tropical insects (Jones 1987,

Jones and Rienks 1987, Braby 1995), rather than continuing to focus on the temperate mechanism of temperature and daylength (e.g. Merkel et al. 2019).

In addition to helping understand the demography of B. tryoni, this demographic approach can also be applied to help understand the ecology of other tropical insects. Unlike temperate insects, diapause is uncommon in tropical insects as winter temperature is not limiting for them, but the availability of resources for breeding can vary greatly due to monsoonal rainfall cycles

(Bonebrake et al. 2010, Santos et al. 2017, Molleman 2018). Thus, tropical insects may also have complex physiological mechanisms to cope with seasonally changing resources

(Denlinger 1986, Jones 1987, Braby 1995). For example, several species of tropical satyrine butterflies show seasonality in reproductive strategies with reproductive activity markedly declining during the dry season and increasing in the wet season (Braby 1995). Additionally, the central African nymphalid Euphaedra medon (Linnaeus) can live for more than nine

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Chapter 6 : General discussion months in a reproductive diapause to cope with very harsh dry seasons (Brakefield and Reitsma

1991, Molleman et al. 2007). A commonality of these examples of tropical insect diapause are that they exist for large, charismatic insects (i.e. butterflies) which are relatively easy to directly observe and track. Getting similar data for smaller, more cryptic insects is much more difficult and so is largely absent. The demographic approach used here offers one solution to this but does need large numbers individuals which can collected in both the adult and juvenile stages.

While this would exclude many insect taxa, other herbivores or carrion feeders are examples of guilds that may be amenable to study using the demographic approach.

6.4.2 Applied implications

Queensland fruit fly is the primary insect pest of the Australian horticulture industry (Clarke et al. 2011). Due to regulatory withdrawal for most usages of two previously used pesticides, dimethoate and fenthion, management of the pest is becoming more reliant on resource-based control strategies, for instance lure-and-kill techniques using protein bait spray and cue-lure, and the Sterile Insect Techniques (Dominiak and Ekman 2013, Dominiak et al. 2015, Dominiak

2019). Although the methods are strategically different, they all target the adult life stage (Dyck et al. 2006).

In the Sterile Insect Technique, very large numbers of mass-reared sterile males are released in the field to mate with wild females (Suckling et al. 2016), resulting in the production of unfertilized eggs by the mated females leading to a decline in abundance of the pest population

(Pérez‐Staples et al. 2013, Shelly and McInnis 2016). Thus, the major target of the SIT is those females who have not yet mated, i.e. those females in a predominantly young population (Carey

1982). Knowledge about the demography and age of field populations can thus be very beneficial not only for enhancing the success of SIT technique but also optimising the timing

131

Chapter 6 : General discussion of fly release (Kouloussis et al. 2009). My demographic study shows that the early spring population was composed largely of old individuals, but there were a small number of young individuals and the population of young flies was just starting to develop. The release of sterile males during the early spring season would thus be highly efficient, as the new generation females would be seeking mates, while the majority males would be very old and while still fertile (my study) would be at a mating disadvantage against younger (sterile) males in a competitive environment (Ekanayake et al. 2017a). Additionally, the number of young flies seeking mates is low and so the number of flies needing to be released might be similarly lower.

In contrast, releasing sterile males late in the season is unlikely to cost effective as most females in the population are older and so will already be mated and their fecundity and fertility naturally declining without other intervention.

In the lure-and-kill technique, adult insects are controlled by attracting them using an olfactory or visual attractant and leading them to a killing agent, commonly a pesticide (El-Sayed et al.

2009, Shelly et al. 2014). An insect’s attraction to different cues changes with age and physiological status (Jang 1995, Kendra et al. 2005, Gadenne et al. 2016) and so information on the age of the wild population, and the effect of aging on olfactory response, can be very informative when designing recommendations for the efficient lure-an-kill programs

(Kouloussis et al. 2009). For instance, my field study showed that the late winter and early spring population was largely composed of very old individuals, while my olfactometer work showed that very old males had a significantly reduced olfactory response to cue-lure. Thus, the use of cue-lure for monitoring during late winter and early spring seasons may lead to underestimating the population abundance as many males may not respond. Additionally, the use of the male annihilation technique (lure and kill using cue-lure) (Lloyd et al. 2010) could also be expected to be less effective very early in the spring or during the second half of winter.

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Chapter 6 : General discussion

These examples clearly illustrate the importance of knowing the age of a B. tryoni in the field when trying to optimise the pest management tool-box for this species.

A final area of great importance of this research for pest management and biosecurity are reinstatement dates. After a declared outbreak in an area-free zone is brought under control, a predetermined period of time must past from the last fly collection before the area is declared free again (FAO-IPPC 2018). The actual durations of such periods are commonly restricted information because of trade sensitivities, but as an example Tasmania has previously required a reinstatement date of “one generation and 28 days or 12 weeks” before again accepting fresh produce from a fruit fly free zone on mainland Australia (Biosecurity Technical Group 2011).

Meats and Clift (2005) note that reinstatement periods are often calculated based on day degree accumulation, and this is seen in practice. For example, New Zealand took six months to declare an eradication of B. tryoni in Auckland when that period included the cool to cold autumn and winter months. In contrast, only six weeks was needed for Australia to declare freedom when a fly was detected in the town of Devonport during the summer months

(Biosecurity New Zealand 2020). Every extra day that a production area remains closed because the reinstatement date is longer than necessary costs grower’s money because of the lost opportunity of selling their crop. Conversely if a reinstatement date is too short, then biosecurity is compromised. Now that we are aware that B. tryoni (and perhaps other fruit flies?) development and aging is not entirely temperature dependent, new work on reinstatement dates should be done to determine the most appropriate reinstatement periods.

6.5 FUTURE RESEARCH DIRECTION

Should I, or others, have the opportunity to continue this work there are several areas requirement further investigation.

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Chapter 6 : General discussion

i. Conclusions from this thesis are limited by the scale of work I could personally

undertake. This is particularly pertinent to the demographic study, which was restricted

to a single site and only 1.5 years. The study of demographic structure over multiple

sites and multiple years, including in B. tryoni’s endemic habitat if that were possible,

would be invaluable to confirm that the population has an endogenous mechanism

related to seasonal phenology.

ii. The longevity of flies originated from infested host fruits showed strong seasonality,

even though flies were held in constant laboratory condition. This raises questions about

the reproductive potential of females during different seasons. Thus, the study of

females’ seasonal longevity coupled with the assessment of their reproductive potential

will be extremely valuable to be confirmed (or deny) that they have the seasonal

reproductive strategy I have proposed.

iii. The underlying mechanism(s) of what drives the differences in seasonal phenology

demonstrated by B. tryoni (i.e. longevity differences, the very late winter emergence

and then sudden spring population build-up) has not been determined. Environmentally

triggered epigenetic changes might occur, or there might be a long-cycle clock

mechanism starting from a constant environmental cue, such as the winter solstice.

Detailed molecular and physiological research is warranted to unravel these

mechanisms.

iv. Although the methodology of age-estimation has revealed valuable insights about

internal changes in field population structure, the accuracy of the method output can be

heavily influenced by choosing the appropriate reference cohort. In my study, reference

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Chapter 6 : General discussion

flies showed strong seasonality in longevity and, thus, it was hard to find a true

reference cohort for estimating the age of a captive cohort. So, a better method should

be developed to avoid age-bias in the estimation of the field population age.

v. In my study, a large number of males were attracted to host-fruit odour both in the field

and laboratory: which leads to the question of why males are attracted to the host-fruit

odour. As mating in B. tryoni does not happen on host-fruits, and male do not use the

fruit as a feeding resource, the only assumption for males’ strong attraction to host-fruit

odour might be the similarity in olfactory system internal wearing in males and females:

this could tested using neurological tools.

vi. In my study the attraction of males B. tryoni to cue-lure odours showed significant

reduction at advanced age in an olfactory experiment, a further confirmatory field study

will be valuable for practical implication.

135

Key research findings

7. KEY RESEARCH FINDINGS

i. The age-structure of wild-captured male Bactrocera tryoni varied greatly with

season and in a year the population had a maximum of three generations.

ii. The late winter and early spring populations were composed of predominantly old

flies with a few young individuals; the early summer and early autumn populations

were composed of mixed age flies with young, middle-age and old flies; the autumn

population was compose of middle-age and old flies.

iii. The presence of old flies during late winter and early spring indicates breeding gap

from late autumn to winter; the mixed-age individuals from early summer and early

autumn indicate continuous breeding throughout the period.

iv. Longevity of control flies that emerged from infested host fruits showed a strong

seasonality in spite of being held under constant laboratory condition: early spring

and early autumn males were short-lived, while late autumn and late winter flies

were long-lived.

v. A mathematical modification of the demographic approach was developed here to

estimate the age-structure of wild Bactrocera tryoni.

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Key research findings

vi. Sexually mature males retained a constant attraction to cue-lure and tomato odour

until 12 weeks of age; but at 15 weeks there was a simultaneous drop in both

locomotor activity and selective olfactory orientation to cue-lure.

vii. In the field males responded to both cue-lure and tomato-baited traps throughout

the year and the capture rate did not significantly differ between trap types.

viii. Females showed the highest attraction to guava-juice odour until six weeks of age

and declined gradually thereafter.

ix. The change on odour response over time can be associated with an age-related

change in initial locomotor activity for females as there was no change, over the life

of the experiment, in selective female orientation to the odour source once flies

started exploring within the olfactometer.

x. Increasing age negatively affected the fecundity and fertility of female B. tryoni

after both attributes peaked at approximately 20 days, but despite the decline in

production a small number of viable eggs were still being laid nearly to the end of

a female’s life.

xi. When B. tryoni males were mated consistently with a young partner, the indirect

evidence of the partner’s egg hatch rate suggested that male fertility increases with

increasing age.

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Key research findings

xii. The consistent attraction of male to cue-lure might be related to life-long

reproductive activities of males, as males are thought to mate continuously during

life.

xiii. Females’ highest attraction to guava-juice odour in early life followed by a gradual

decline might be linked with their oviposition rate which peaks in early life.

Takeaway messages

i. Assuming their endemic habitat is seasonally structured by the monsoon, B. tryoni

have an endogenous mechanism which allows them to cope with a seasonally

unfavourable environment by restricting breeding and increasing longevity during

the resource poor dry-season but increasing population abundance during the

resource rich wet-season.

ii. Rather than having the continuous breeding and overlapping generations as

predicted by day-degree based models, the population effectively “resets” itself

every spring to a new starting generation as the very old female flies lay their last

eggs and that cohort of offspring start the new season’s activity.

iii. Pest control and market access actions which utilise knowledge of B. tryoni

phenology need to take into account that day-degree accumulation alone cannot

adequately capture the phenology of this fly.

138

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