Science, Faculty of
Zoology, Department of
DSpace
UBCV
Phelan, Orna
Master of Science - MSc
University of British Columbia
There are over 3,500 species of mosquito, occupying a huge range of environments including inland and coastal habitats. Salinity tolerance plays a crucial role in the ecology of mosquitoes as it can determine whether a particular habitat is suitable for larvae. Understanding how aquatic larvae physiologically cope with salt and how adult mosquitoes detect salt is of critical importance to understanding the biology of important vector species. In this study, the larval salinity tolerance, oviposition preference and breeding habitat ecology of a widespread (Ae. aegypti) and restricted (Ae. togoi) mosquito species was investigated to try to understand key physiological and behavioral differences. Ae. aegypti breed and develop in freshwater containers associated with urban environments while Ae. togoi develop in high fluctuating salt-water rockpools. By conducting larval survival studies, I found that, although Ae. togoi larvae are capable of surviving in extremely high concentrations of seawater, Ae. aegypti larvae can tolerate a wider range of ions at intermediate concentrations. This ability to survive in a wide variety of water types could partially explain how Ae. aegypti have been able to spread globally while Ae. togoi remains restricted to coastal areas. Oviposition bioassays found that salinity may not be a key driver of oviposition for Ae. togoi, as it is for Ae. aegypti. Finally, a field study of Ae. togoi in metro Vancouver uncovered that temperature, precipitation, salinity and the interaction of these factors are important predictors of larval abundance. This study has highlighted the importance of investigating field populations as well as conducting laboratory experiments when investigating the biology of a species. In reality, a suite of interacting factors modulates the ability of species to survive in their habitat and these factors can only be uncovered by examining field populations. In addition, a two-species comparison can aid into providing preliminary insight about how evolution has shaped osmoregulatory strategies as well as the chemosensory system in the face of exploiting new habitats. Investigating mosquito physiology and behavior can aid in predicting distribution of mosquito populations and eventually this can aid in developing targeted control strategies for vector species.
An investigation into the salinity tolerance, oviposition behavior and breeding habitat ecology of a widespread (Aedes aegypti) and restricted (Aedes togoi) mosquito species by Orna Phelan B.Sc., University College Dublin, 2019 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE in THE FACULTY OF GRADUATE AND POSDOCTORAL STUDIES (Zoology) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) July 2023 © Orna Phelan, 2023 ii The following individuals certify that they have read, and recommend to the Faculty of Graduate and Postdoctoral Studies for acceptance, the thesis entitled: An investigation into the salinity tolerance, oviposition behavior and breeding habitat ecology of a widespread (Aedes aegypti) and restricted (Aedes togoi) mosquito species submitted by Orna Phelan in partial fulfilment of the requirements for the degree of Master of Science in Zoology Examining Committee: Dr. Benjamin J. Matthews, Assistant Professor, Zoology, UBC Supervisor Dr. Christopher Harley, Professor, Zoology, UBC Supervisory Committee Member Dr. Colin Brauner, Professor, Zoology, UBC Additional Examiner Additional Supervisory Committee Members: Dr. Michelle Tseng, Assistant Professor, Zoology, UBC Supervisory Committee Member iii Abstract There are over 3,500 species of mosquito, occupying a huge range of environments including inland and coastal habitats. Salinity tolerance plays a crucial role in the ecology of mosquitoes as it can determine whether a particular habitat is suitable for larvae. Understanding how aquatic larvae physiologically cope with salt and how adult mosquitoes detect salt is of critical importance to understanding the biology of important vector species. In this study, the larval salinity tolerance, oviposition preference and breeding habitat ecology of a widespread (Ae. aegypti) and restricted (Ae. togoi) mosquito species was investigated to try to understand key physiological and behavioral differences. Ae. aegypti breed and develop in freshwater containers associated with urban environments while Ae. togoi develop in high fluctuating salt-water rockpools. By conducting larval survival studies, I found that, although Ae. togoi larvae are capable of surviving in extremely high concentrations of seawater, Ae. aegypti larvae can tolerate a wider range of ions at intermediate concentrations. This ability to survive in a wide variety of water types could partially explain how Ae. aegypti have been able to spread globally while Ae. togoi remains restricted to coastal areas. Oviposition bioassays found that salinity may not be a key driver of oviposition for Ae. togoi, as it is for Ae. aegypti. Finally, a field study of Ae. togoi in metro Vancouver uncovered that temperature, precipitation, salinity and the interaction of these factors are important predictors of larval abundance. This study has highlighted the importance of investigating field populations as well as conducting laboratory experiments when investigating the biology of a species. In reality, a suite of interacting factors modulates the ability of species to survive in their habitat and these factors can only be uncovered by examining field populations. In addition, a two-species comparison can aid into providing preliminary insight about how evolution has shaped osmoregulatory strategies as well as the iv chemosensory system in the face of exploiting new habitats. Investigating mosquito physiology and behavior can aid in predicting distribution of mosquito populations and eventually this can aid in developing targeted control strategies for vector species. v Lay summary Mosquitoes are the deadliest animals in the world and understanding aspects of mosquito biology can aid in predicting mosquito distribution and spread. Some species such as Ae. aegypti are distributed all over the globe while others, such as Ae. togoi are only found on the coast. The factors that have allowed some species to spread is not fully understood. In this study I have found that Ae. aegypi larvae can tolerate a wider range of salt types than Ae. togoi larvae. In addition, although Ae. aegypti avoid laying eggs in salt water, some other factor is probably more important for picking a suitable larval habitat for Ae. togoi. Overall, these results hint that the larval physiology and the adult chemosensory system of these two species are different and have evolved to help them overcome the challenges faced in each of their respective environments. vi Preface The research presented in this thesis is the result of my original work. All experiments were conducted at the University of British Columbia and field work was conducted at Lighthouse Park in West Vancouver under the supervision of Dr. Benjamin J. Matthews. The experimental design of chapters 2, 3 and 4 were developed by myself, my supervisor Dr. Benjamin J. Matthews, and Dr. Dan Peach. Dr. Katie Marshall, Jarrett Blair and Nick Tochor assisted with the ecological modeling analysis in chapter 4. vii Table of Contents Abstract.........................................................................................................................................iii Lay Summary.................................................................................................................................v Preface............................................................................................................................................vi Table of Contents.........................................................................................................................vii List of Tables................................................................................................................................ xi List of Figures.............................................................................................................................xiii List of Abbreviations..................................................................................................................xvi Acknowledgements ...................................................................................................................xvii Chapter 1: General Introduction.................................................................................................1 1.1. The importance of studying mosquitoes.............................................................................1 1.2. Distribution of Aedes aegypti and Aedes togoi...................................................................2 1.3. Life cycle of the mosquito..................................................................................................3 1.4. Effect of salt on mosquito life history……………………………………………………5 Chapter 2: Ae. aegypti and Ae. togoi larval salinity tolerance...................................................7 Chapter 2 objectives……………………………………………………………………………….7 2.1 Introduction……………………………………………………………………………………8 2.1.1 The importance of investigating salinity tolerance………………………………..…….8 2.1.2 Osmoregulation strategies…………………...…………………………………………10 2.1.3 Salinity tolerance of the larvae of Ae. aegypti…………………………………………11 2.1.4 Salinity tolerance of the larvae of Ae. togoi..……..…………………………………….13 2.2 Methods………………………………………………………………………………………15 2.2.1 Aedes aegypti stock colony…………………………………………………………….15 2.2.2 Aedes togoi stock colony………………………………………………………………15 2.2.3 Blood feeding set up…………………………………………………………………...16 viii 2.2.4 Larval survival assays………………………………………………………………….18 2.2.5 Statistical analysis……………………………………………………………………...22 2.3 Results………………………………………………………………………………………..23 2.3.1 Effects of different ionic salts on Aedes aegypti larval survival…………………23 2.3.2 Effects of different ionic salts on Aedes togoi larval survival…………………...25 2.3.3 Comparison of larval survival between Aedes togoi and Aedes aegypti………...27 2.4 Discussion………………………………………………………………………………........31 2.4.1 H1: Mosquito larval survival depends on the concentration and the identity of the ionic salt solution they are reared in………….…………………………………………….31 2.4.2 H2: As a salt-water species, Ae. togoi will show higher rates of survival in all solutions tested……………………………………………………………………………...32 2.4.3 Future directions……………………………………………………………………...35 Chapter 3: Oviposition preference of Ae. aegypti and Ae. togoi..............................................37 Chapter 3 objectives……………………………………………………………………………...37 3.1 Introduction ………………………………………………………………………………….38 3.1.1 The mosquito taste system and oviposition behavior………………………………...39 3.1.2 Oviposition behavior of Ae. aegypti and Ae. togoi……………………..…………….40 3.2 Methods………………………………………………………………………………………42 3.2.1 Two choice oviposition preference assays……………………………………………42 3.2.2 Image acquisition using Raspberry pi………………………………………………...45 3.2.3 Statistical analysis…………………………………………………………………….46 3.3 Results………………………………………………………………………………………..47 3.3.1 Number of eggs laid per individual…………………………………………………..47 3.3.2 Ae. aegypti oviposition preference assays …………………………………………...49 3.3.3 Ae. togoi oviposition preference assays………………………………………………53 3.3.4 Comparison of oviposition preference between Ae. aegypti and Ae. togoi...………...55 ix 3.4 Discussion……………………………………………………………………………………57 3.4.1 H1: Osmolarity is the primary factor that mosquitoes use to evaluate if a given body of water is suitable for egg-laying……………………………………………………………..57 3.4.2 H2: Ae. togoi will show a preference for ovipositing in the freshwater solution over the treatment solution at a higher concentration than Ae. aegypti………………………….58 3.4.3 Future directions……………………………………………………………………...60 Chapter 4: Breeding habitat ecology of Ae. togoi .....................................................................62 Chapter 4 objectives……………………………………………………………………………...62 4.1 Introduction ………………………………………………………………………………….62 4.1.1 Modeled distributions of Ae. togoi……………………………………………………62 4.1.2 Environmental variation affects mosquito abundance………………………………..63 4.2 Methods ……………………………………………………………………………………...66 4.2.1 Study site……………………………………………………………………………...66 4.2.2 Measuring environmental variables…………………………………………………..68 4.2.3 Statistical analysis…………………………………………………………………….69 4.3 Results ……………………………………………………………………………………….71 4.3.1 Principal component analysis………………………………………………………...72 4.3.2 Negative Binomial generalized linear mixed effects model…………………………75 4.3.3 Correlation between larval abundance and PC1, PC3 and PC4……………………...77 4.3.4 Variation of principal components through the year ….……………………………..79 4.3.5 Reservoir pools during extreme weather events……………………………………...81 4.3.6 Inter-rockpool variation………………………………………………………………83 4.4 Discussion………………………………………………………………………………........85 4.4.1 Variation in principal components through the year …………………………………85 4.4.2 Interactions between abiotic factors…………………………………………………..87 4.4.3 Other factors that could influence larval abundance …………………………………89 4.4.4 Effect of extreme weather event on larvae and inter-rockpool variation …………….91 x 4.4.5 Future directions……………………………………………………….……………..93 5: General conclusions and future directions ...........................................................................95 5.1 Larval survival studies …………………………………………………………………95 5.2 Oviposition preference assays ……………………………………………………….....96 5.3 Breeding habitat ecology of Ae. togoi…………………………………………………..98 Bibliography…………………………………………………………………………………...101 Appendix………………………………………………………………………………………124 xi List of Tables Table 1. Conversion table for common units to measure salinity………………………………...9 Table 2. The results of a series of one-way ANOVAs to test the effect of osmolarity (Osm) on Ae. aegypti larvae percentage survival…………………………………………………………...21 Table 3. The results of a series of one-way ANOVAs to test the effect of osmolarity (Osm) on Ae. togoi larvae percentage survival……………………………………………………………..25 Table 4. The results of a series of two-way ANOVAs to test the effect of species, osmolarity (Osm) and their interaction on Ae. aegypti and Ae. togoi percentage survival…………………..27 Table 5. Concentration that caused the first significant decrease in survival and concentration that is lethal to 100% of larvae for each species and each salt tested……………………………29 Table 6. Concentration that caused the first significant decrease in survival and concentration that is lethal to 100% of larvae for each species and each salt tested……………………………30 Table 7. A series of one-way ANOVAs to test if there was an effect of osmolarity on number of eggs laid for each salt and each species………………………………………………………….47 Table 8. The results of a two-way ANOVA to test the effect of osmolarity (Osm) and salt ID on female adult Ae. aegypti oviposition preference………………………………………………...52 Table 9. One sample t-tests to test if the oviposition preference of Ae. aegypti females is significantly different from 0……………………………………………………………………52 Table 10. The results of a two-way ANOVA to test the effect of osmolarity (Osm) and salt ID on female adult Ae. togoi oviposition preference…………………………………………………..54 Table 11. One sample t-tests to test if the oviposition preference of Ae. togoi females is significantly different from 0……………………………………………………………………54 Table 12. Two-way ANOVAs to test the effect of species, osmolarity (Osm) and the interaction between species and osmolarity on oviposition preference for KCl and NaCl……………….…56 Table 13. Heatmap indicating the relative loadings of each principal components…………..…74 xii Table 14. Results from the generalized linear mixed effects model (GLMM) associating Ae. togoi larval abundance with principal components and their interactions………………………76 xiii List of Figures Figure 1. Blood feeding protocol set up…………………...…...………………………………..17 Figure 2. Components of blood feeding apparatus…………………...…………………………17 Figure 3. Ae. aegypti feeding on artificial membrane…………………………………………...18 Figure 4. Percentage survival of Ae. aegypti larvae in sodium chloride (NaCl), Instant Ocean©, potassium chloride (KCl), magnesium chloride (MgCl2), sodium sulfate (Na2SO4) and calcium chloride (CaCl2) solutions across a concentration gradient……………………………………...24 Figure 5. Percentage survival of Ae. togoi larvae in sodium chloride (NaCl), Instant Ocean©, potassium chloride (KCl), magnesium chloride (MgCl2), sodium sulfate (Na2SO4) and calcium chloride (CaCl2) solutions across a concentration gradient……………………………………...26 Figure 6. Comparison of percentage survival of Ae. togoi and Ae. aegypti larvae in sodium chloride (NaCl), Instant Ocean©, potassium chloride (KCl), magnesium chloride (MgCl2), sodium sulfate (Na2SO4) and calcium chloride (CaCl2) solutions at shared concentrations…….28 Figure 7. Schematic of oviposition preference assay……………………………………………44 Figure 8. Raspberry pi imaging set up and images acquired………………...………………….45 Figure 9. Total amount of eggs laid per concentration. n-value represents each single female adult Ae. aegypti that laid over 10 eggs………………………………………………………….48 Figure 10. Total amount of eggs laid per concentration. n-value represents each single female adult Ae. togoi that laid over 10 eggs……………………………………………………………49 Figure 11. The effect of calcium chloride (CaCl2), Instant Ocean©, magnesium chloride (MgCl2), potassium chloride (KCl), sodium chloride (NaCl) and sodium sulfate (Na2SO4) on the oviposition preference of adult female Ae. aegypti mosquitoes…………………………………51 Figure 12. The effect of potassium chloride (KCl) and sodium chloride (NaCl) on the oviposition preference of adult female Ae. togoi mosquitoes……………………………………53 Figure 13. Comparison of oviposition preference for adult Ae. aegypti and Ae. togoi at each concentration tested for potassium chloride (KCl) and sodium chloride (NaCl)………………..55 xiv Figure 14. Map of Vancouver, British Columbia with study site (Lighthouse Park) indicated by red triangle……………………………………………………………………………………….66 Figure 15. Zoomed in map of study site with locations of individual rockpools marked. Gradient colours to indicate the number of larvae collected in each rockpool over the year study……….67 Figure 16. Monthly abundance and seasonality of Ae. togoi larvae recorded over 16 rockpools in Lighthouse Park from April 2021- April 2022……………………………………………..........71 Figure 17. Monthly abundance and seasonality of Ae. togoi larvae in each rockpool sampled from April 2021- April 2022……………………………………………………………………..72 Figure 18. Scree plot showing how much variation each principal component captures from the dataset……………………………………………………………………………………………73 Figure 19. Relationship between PC1 and PC2. PC scores are coloured by month to show how the PC values change over time………………………………………………………………….75 Figure 20. Regression plots showing correlation between larval abundance and principal components………………………………………………………………………………………78 Figure 21. Variability in larval abundance in the study area superimposed on changes in PC 1, 3 and 4. Connected scatterplots showing how the relationship between larval abundance and principal component changes through time …….……………………………………………….80 Figure 22. Big red rockpool through the seasons………………………………………………..82 Figure 23. Plots showing larval abundance (A), temperature of the pool (B), previous weeks precipitation values (C) and salinity of the pool (D) during the summer months……………….83 Figure 24. Figure 24. Average value of each environmental variable across all weeks for each rock pool ……………………………………………...…………………………………………84 Figure A.1. LC50 curves showing survival of Ae. aegypti larvae in a variety of ionic salts….124 Figure A.2. LC50 curves showing survival of Ae. togoi larvae in a variety of ionic salts…….124 Figure A.3 Dose response curves of Ae. aegypti oviposition preference in response to increasing osmolarity in a variety of ionic salts……………………………………………………………125 xv Figure A.4. Correlation matrix of environmental variables input into PCA…………………...126 xvi List of Abbreviations ANOVA Analysis of variance GLMM Generalized linear mixed effects model OPI Oviposition preference index PCA Principal component analysis xvii Acknowledgments First and foremost, I want to thank my supervisor Dr. Benjamin J Matthews for the unwavering support over the course of this project. You have been an incredible scientific mentor as well as a huge source of encouragement. Thank you for believing in me even when I didn’t. Thank you to my committee members Dr. Michelle Tseng and Dr. Chris Harley for their invaluable insight and direction throughout this project. I also want to thank Dr. Katie Marshall for all the advice, guidance and support. I am grateful for all the help with the science but also, I am incredibly grateful for the mentorship and encouragement you gave me along the way. Thank you to Nick Tochor for everything. From running the whole lab, to helping me build experimental set ups to assisting with analysis, I don’t know what I would have done without you. Thank you to Jarrett Blair for the invaluable help with the coding aspects of this project. Thank you to all the members of the Matthews lab (especially Leisl Brewster and honorary member Jess Li) for always being around to bounce ideas off and for all the coffee and lunch breaks. Finally, thank you to my parents and my sister back home who I miss every day. I would not have been able to finish this project without your support. The field work for the project was conducted on the ancestral and unceded land of the xʷməθkʷəy̓əm (Musqueam), Sḵwx̱wú7mesh (Squamish), and səlilwətaɬ (Tsleil-Waututh) peoples. I am incredibly grateful for the privilege of living and working on these lands. 1 Chapter 1: General Introduction 1.1 The importance of studying mosquitoes Mosquitoes represent an incredibly diverse group of insects with over 3,500 described species that occupy a huge range of habitats across the globe (Foster & Walker, 2019; López-Pujol, 2011). Disease transmission by mosquitoes is one of the most important health risks to the general public, however it has been estimated that only 2.5% of mosquito species are known vectors of pathogens that cause disease in humans (CDC, 2022; Webb, 2008; Yee et al., 2022). Aedes aegypti, also known as the yellow fever mosquito, is the main vector of the arthropod-borne viruses (arboviruses) that cause Yellow fever, Dengue fever, Chikungunya and Zika (Gloria-Soria et al., 2016). In particular, Dengue fever is one of the most significant viral diseases that is spread from human to human via mosquitoes Getachew et al., 2015). Ae. aegypti is endemic in Africa, the Americas, eastern Mediterranean, Southeast Asia, and the Western Pacific and it has been estimated that 50–100 million people suffer from dengue infections every year (Guillena et al., 2010; WHO, 2012). Understanding vector physiology, behavior and distribution is vital to develop effective control methods and slow the spread of these lethal human diseases. In addition to studying vector species, it is also important to investigate mosquitoes that are not the primary vector of disease (such as the coastal rock pool mosquito, Aedes togoi), in order to compare and contrast their life strategies. In recent years, more and more studies have indicated that, even within one genus such as Aedes, what we know about one species of mosquito cannot be generalized to all species (Cunze et al., 2016; Kain et al., 2022; Roiz et al., 2015). The broad focus of this work is to determine if the mechanisms that guide oviposition 2 behavior and larval survival are different between two Aedes mosquitoes with widespread (Ae. aegypti) and restricted (Ae. togoi) niches. More specifically, this work aims to investigate the tolerance of larvae and the egg laying preference of adult mosquitoes to various concentrations of salts in order to understand key physiological and behavioral differences between these species. This work may aid in uncovering why certain species are restricted to certain habitats. Global warming is causing species distributions to change and expand (Le Roux & McGeoch, 2008). This work may aid in better predicting how mosquito species will spread under climate change. 1.2 Distribution of Aedes aegypti and Aedes togoi Some species of mosquitoes are incredibly widespread and invasive while others remain restricted to specific niches. The ancestral home of Ae. aegypti is sub- Saharan Africa and the ancestral form (Ae. aegypti formosus) still inhabits this area and breeds in tree holes and other natural bodies of water (Powell & Tabachnick, 2013). Ae. aegypti aegypti, on the other hand, have adapted to a synanthropic way of life and have spread to tropical and subtropical regions around the world (Powell et al., 2018). This species has successfully colonized all continents except Antarctica (Ibañez-Justicia et al., 2017). For the purpose of this thesis, I have used the CDC’s definition of an invasive species as “one that has been accidentally or deliberately introduced to a region where it is not native and whose presence negatively impacts the environment, the economy, or the society including human and animal health” (Invasive Species, 2022). Under this definition, Ae. aegypti are a widespread, invasive species, spreading disease outside their native range. 3 Ae. togoi, on the other hand, are a species of mosquito with a much narrower distribution. They are found in coastal areas from subtropic to subarctic East Asia (Sota et al., 2015a), as well as the Pacific coast of Canada and the USA (Belton, 1983; Peach & Matthews, 2020). It is not known whether Ae. togoi is native to North America or if it is non-native (Belton, 1980, 1983; Peach & Matthews, 2020; Sota et al., 2015a). In Asia, Ae. togoi is a carrier of the filarial parasite Brugia malayi (Hayashi, 2011; Tanaka et al., 1979; Wada, 2011), Japanese encephalitis (Petrishcheva, 1948a; Rosen et al., 1978; Rosen, 1986) and potentially the parasites Wuchereria bancrofti and Dirofilaria immitis (Tanaka et al., 1979). Ae. togoi is also a potentially competent vector for West Nile Virus but it does not appear on the CDC’s list of North American mosquito species known to carry the virus, indicating that it is not (yet) an important or primary vector of the disease (Centers for Disease Control, 2005; Stephen et al., 2006). Although there is uncertainty about the invasive status of Ae. togoi, under the CDC’s definition, they are not considered an invasive species in North America because their presence does not have a negative impact on the environment, the economy or human and animal health (that we know of). 1.3 Life cycle of the mosquito Mosquitoes can be either anautogenous or autogenous. Anautogenous mosquitoes need to take a blood meal in order to develop eggs whereas autogenous species are able to produce a batch of mature eggs without blood meal nutrients (Uchida, 1994). Most populations of Ae. aegypti and Ae. togoi are anautogenous, meaning that they must take a blood meal from a host in order to reproduce (McGinnis, 1982; Shaw et al., 2015). The blood meal host preference is variable depending on the species (Munstermann, 1997). Aedes aegypti are synanthropic, meaning that they live close to, and benefit from human settlement and they are anthropophilic in 4 that they prefer feed on humans rather than animals (McBride et al., 2014; Ponlawat & Harrington, 2005). Ae. togoi have been reported to feed on humans, cattle and birds (McGinnis, 1982). In Japan this species prefers to feed on cattle rather than humans but they will feed from humans in the absence of cattle (Omori & Fujii, 1953). Livestock is almost certainly not the preferred host for rock pool populations. Humans may be the preferred host in highly trafficked areas but many rock pools that house Ae. togoi are found in remote locations so it is unclear whether blood meals from humans are the primary source of nutrition for all populations (Petrishcheva, 1948b). In laboratory conditions, Ae. togoi will also feed on mice and guinea pigs (Lien, 1960). However, at this time their preferred host is not known in North America. Once a blood meal has been taken, females must choose a suitable egg-laying (oviposition) site (Day, 2016). Mosquito larvae and pupae require an aquatic environment to develop (Anoopkumar et al., 2017). Larvae cannot move from the body of water in which they hatch so choosing a suitable oviposition site where larvae will survive is a critical decision for the female adult. Aedes eggs can survive harsh conditions and withstand drying out for up to six months. They will then hatch when eventually submerged in water (Luz et al., 2008). Their ability to survive by entering this diapause-like state makes some species extremely difficult to control. Ae. aegypti generally lay eggs in freshwater containers where environmental conditions remain relatively stable (Gopalakrishnan et al., 2013). Ae. togoi, in contrast, lay eggs in highly fluctuating rock pools where environmental conditions are constantly changing (Morritt & Williams, 2000). Once conditions become favorable and larvae hatch from the egg, they go through four successive molts to reach the pupal stage (Munstermann, 1997). Larvae of most Aedes species are filter feeders and feed on micro-organisms and detritus in the water column (Merritt et al., 5 2003). Pupae do not feed and after 1-3 days, adult mosquitoes emerge (Anoopkumar et al., 2017). Both Ae. aegypti and Ae. togoi follow this life cycle, although Ae. togoi often have longer and more variable development times than Ae. aegypti. The development of Ae. aegypti from egg to adult usually takes 7-10 days in the laboratory while the development of Ae. togoi can take 14-18 days with larvae often hatching in waves, weeks apart (personal observation from rearing Ae. togoi in the laboratory). 1.4 Effect of salt on mosquito life history Salinity tolerance plays a crucial role in the ecology of mosquitoes, particularly those in coastal environments, as it can determine whether a habitat is suitable for larvae (Kengne et al., 2019). The way in which aquatic larvae can regulate the ions present in their environment (eg. Na+, Cl-, So24-, Mg2+, K+) determine their survival. Most species of mosquito are osmoregulators, meaning that they strictly maintain internal osmotic pressure regardless of the external environment (Pallarés et al., 2015). However, it is not known whether the osmotic pressure overall or the concentrations of particular ions is what leads to larval death at high salinities. By answering this question, we can begin to speculate about transport mechanisms that may be present and involved in excreting various ions in mosquito larvae. By including a species comparison between a freshwater and saltwater species we can begin to investigate if they regulate ions the same way. This may begin to shed some light on how evolution can shape osmoregulatory mechanisms in the face of exploration of a new habitat (i.e., brackish environments). 6 In addition to larval survival, salinity can also influence oviposition behavior of adult mosquito females (Bentley & Day, 1989). Because the larvae of mosquitoes are aquatic and cannot move from where they hatch, the choice of oviposition site can determine mosquito fitness and survival and so selecting an appropriate egg-laying site is a critical decision for female mosquitoes (Baik & Carlson, 2020). There has been much research into how the taste system in mosquitoes can guide oviposition behavior (Afify & Galizia, 2015; Bentley & Day, 1989; Matthews et al., 2019). Ae. aegypti mosquitoes avoid laying eggs in saline waters that are lethal to larvae (~300mOsm) (Gunathilaka et al., 2018; Panigrahi et al., 2014; Xia, 2021). Ae. togoi mosquitoes also avoid laying eggs in extremely saline solutions but their threshold is much higher than that of freshwater mosquitoes and they will often oviposit in saline water up to 20g/L (~57% seawater) (Asakura, 1980a; Lien, 1960; Morritt & Williams, 2000). One caveat to these studies is that the only saline solution that was tested was NaCl or seawater. It is not known whether the adults are sensing osmolarity or if they are capable of detecting various ions in the water. By understanding how adult female mosquitoes interpret cues (such as salinity) from the environment we can gain valuable insight into their sophisticated chemosensory systems. The overall objective of this thesis is to determine whether larval salinity tolerance and oviposition preference differs between a widespread (Ae. aegypti) and a restricted (Ae. togoi) mosquito species. 7 Chapter 2: Ae. aegypti and Ae. togoi larval salinity tolerance Chapter 2 objectives The objective of my second chapter was to investigate the survival of Ae. aegypti and Ae. togoi larvae in salts composed of a variety of ions that are common in seawater (sodium (Na+), chloride (Cl¯), sulphate (SO24¯), magnesium (Mg2+), potassium (K+) and calcium (Ca2+)). There is evidence that mosquito larvae possess various ion transport mechanisms to excrete specific ions (Bradley, 1987; Dow, 2017). Therefore, it is plausible that the level of survival of larvae will be different depending on the solution they are reared in. I am interested in uncovering whether mosquito larvae have different tolerances for various ions as this may shed some light on their osmoregulatory system and the kind of transport mechanisms they possess. My first hypothesis (H1) is that both Ae. aegypti and Ae. togoi larval survival depends on the concentration of the solution they are reared in but also the identity of the ionic salt. I predict that both Ae. aegypti and Ae. togoi larval survival will be different depending on the identity of the ionic salt they are reared in. In addition, there is evidence that different mosquito species posses different osmoregulatory mechanisms depending on their habitat (Bradley, 1987). Freshwater larvae must generally retain ions while saline water larvae must excrete excess ions. My second hypothesis (H2) is that, because Ae. togoi develop in saline rock pools, they have evolved a higher salt tolerance than Ae. aegypti. I predict that Ae. togoi larvae will show higher survival than Ae. aegypti across all concentrations of all salt solutions tested. In order to test these hypotheses, I conducted larval survival studies on Ae. aegypti and Ae. togoi larvae in six different salt solutions; sodium chloride (NaCl), Instant Ocean©, 8 potassium chloride (KCl), magnesium chloride (MgCl2), sodium sulfate (Na2SO4) and calcium chloride (CaCl2). By controlling for osmolarity, we can uncover whether the identity of the ion is important to survival. In other words, we can see if percentage survival is the same between different solutions that have the same osmolarity. 2.1 Introduction 2.1.1 The importance of investigating salinity tolerance The extent to which mosquitoes can tolerate salinity is one important trait that can influence their ecology by dictating their larval habitats, which in turn affects their distribution (Ramasamy & Surendran, 2011). Mosquito larvae can be found in various aquatic habitats, ranging from fresh water to saline environments (Clark, 2004). High levels of salinity and specific ionic compositions can pose significant stressors in aquatic habitats. Therefore, this makes salinity one of the primary environmental factors that can affect the distribution of these organisms. (Ward, 1992). Different studies use various units to measure salinity such as parts per thousand (ppt), osmolarity (Osm), molarity (M) and grams per litre (g/l). Table 1 is a conversion table for common units used to measure salinity. Measurements of osmolarity depend on temperature and so Table 1 represents osmolarity under typical experimental conditions (25°C). However, the salinity of seawater varies across time and from place to place. For example, the marine waters of coastal British Columbia experience seasonal variations in salinity due to influxes of freshwater from melting snow at certain points of the year (Arriagada et al., 2016; Pickard & McLeod, 1953). Therefore, full strength seawater may not necessarily be 35ppt at all times of the year and in all places. 9 % Seawater g/L salt Osmolarity (Osm) (mOsm) ppt 100 35 1.2 1200 35 50 17.5 0.6 600 17.5 40 14 0.48 480 14 30 10.5 0.36 360 10.5 10 3.5 0.12 120 3.5 Table 1. Conversion table for common units to measure salinity at 25°C. The larvae of Ae. togoi are capable of developing in much higher concentrations of seawater than Ae. aegypti, yet they remain restricted in their distribution. Ae. aegypti larvae on the other hand, are relatively poor at surviving in saline environments and yet are widely distributed. Ae. aegypti larvae may possess some mechanism that allows them to survive in a broader range of habitats than Ae. togoi, despite their poor salinity tolerance. This chapter will aim to investigate whether the larvae of Ae. aegypti and Ae. togoi differ in their tolerance to various ionic compounds in order to answer this question. Almost all studies investigating osmoregulation in mosquito larvae focus on a handful of species. The mechanisms for Na+ and K+ regulation in Ae. aegypti larvae is fairly well understood but this is not the case for Ae. togoi (see 2.1.2) (Donini & O’Donnell, 2005; Hine et al., 2014). This study may be able to shed light on Ae. togoi larval survival in high salt concentrations and this in turn may give insight into how osmoregulation strategies differ between a salt-water and a freshwater species. By using a species comparison with two species that occupy very different habitats and have very different physiological problems to overcome, we may begin to understand the evolution of osmoregulatory mechanisms in insects with aquatic life stages such as mosquitoes. 10 2.1.2 Osmoregulation strategies Organisms face many physiological challenges in an aquatic environment, one of which being fluctuations in the salinity of the external environment. Maintaining the osmotic concentration of hemolymph is essential for aquatic organisms to support homeostasis (Pallarés et al., 2015). Larvae possess specific regulatory mechanisms depending on the type of aquatic habitat they are found in (Bradley, 1987). Osmoregulators maintain their internal body fluids at a constant osmotic pressure regardless of the osmotic pressure of the external environment (Pallarés et al., 2015). In contrast, osmoconformers keep their internal fluids at the same osmotic pressure as the external environment (Bradley, 1987). Freshwater larvae, such as Ae. aegypti face ion loss due to the fact that there are higher levels of ions in their body than the external environment. In addition, they often experience water uptake due to osmosis (Bradley, 1987). Ae. aegypti are strict osmoregulators, maintaining hemolymph osmolarity within a range of 250-375 mOsm and can survive in external salinities from 0 up to 300 mOsm (Bradley, 1987; Edwards, 1982b, 1982a). Ae. aegypti larvae possess some ability to overcome ion loss. Firstly, they produce a very dilute urine to conserve ions and secondly, they are able to actively transport ions into the hemolymph through the anal papillae (Ramsay, 1950; Stobbart, 1974). The main organs involved in osmoregulation in Ae. aegypti larvae are the midgut, Malpighian tubules, rectum and anal papillae (V. B. Wigglesworth, 1933). Malpighian tubules produce the primary urine by actively transporting K+ and Cl¯ ions (Bradley, 1987; Ramsay, 1950, 1951). Na+, K+ and Cl¯ ions are then reabsorbed in the rectum before the urine is eliminated (Ramsay, 1950). In addition, Na+ and Cl¯ ions are also taken up through the anal papillae through sodium and chloride “pumps” (Stobbart, 1974). In this way, Ae. aegypti are 11 able to maintain appropriate ion concentrations in the hemolymph during development in dilute solutions. Unlike Ae. aegypti, the larvae of Ae. togoi are able to tolerate a wide range of salinities and are part of the 5% of mosquito species that can survive and develop in saline water (O’Meara, 1976). Because of their habitat, Ae. togoi larvae face the opposite problem to Ae. aegypti in that they must often deal with excess salts. In dilute solutions, saline-water larvae osmoregulate in a similar way to freshwater larvae and depending on the species, either the rectum or the anal papillae are responsible for reabsorbing ions from the urine (Bradley & Phillips, 1977b; Ramsay, 1950). However, unlike freshwater larvae, the rectum of saline-water larvae has two distinct segments. (Bradley et al., 1984; Ramsay, 1950). The posterior rectal segment may have evolved as an ion-secreting organ, allowing certain species to survive in extremely saline environments (Bradley & Phillips, 1977b). In Ae. togoi larvae, the hind gut is divided into two structures, the rectum and the anal canal (Asakura, 1980b). For many other salt-water-mosquito larvae, the rectum is the main site of ion excretion, however, for Ae. togoi, the anal canal has been found to be the major site for ion excretion (Asakura, 1982). These ion anatomical specializations and secretion mechanisms allow them to maintain a constant osmotic concentration in their hemolymph under hypersaline conditions (Bradley, 1987; Bradley et al., 1984). 2.1.3 Salinity tolerance of the larvae of Ae. aegypti Ae. aegypti are generally considered a freshwater species, however, it should be noted that in some coastal populations of Ae. aegypti the larvae are capable of developing in brackish 12 water (de Brito Arduino et al., 2015; Ratnasari et al., 2021). The level of salinity tolerance varies between different strains of Ae. aegypti. For example, some studies have shown that 100% of Ae. aegypti larvae survive at a concentration of 3.5g/L seawater (~10%) (Clark, 2004). In this study, intermediate salinities (30, 40% seawater) caused a decline in survival and all larvae died at 50% seawater. In addition to decreased survival, Ae. aegypti larvae in this study also experienced sub-lethal fitness consequences when reared at high salinity. Intermediate salinities caused the most rapid development whereas high salinities (20% seawater) led to reduced growth rates and increased time to pupation (Clark, 2004). Therefore, even if larvae can survive to adulthood in saline conditions, they may experience a decrease in fitness. Similar results were seen in a study of Ae. aegypti from southeastern Brazil (de Brito Arduino et al., 2015). This study also reported that growth rate of larvae as well as adult wing length decreased with increasing salinity. Although there are some exceptions, wing length in dipterans is often used to assess body size and has been shown to be directly related to fecundity (Armbruster & Hutchinson, 2002; Briegel, 1990; Honěk, 1993; Yan et al., 2021). Therefore, mosquitoes with smaller wing length generally exhibit a decrease in fitness. Other studies have reported much higher and lower tolerances of Ae. aegypti to salt. A study by Ramasamy et al., compared salinity tolerance between fresh and brackish water populations of Ae. aegypti in Sri Lanka. They found that Ae. aegypti larvae from the brackish water population showed 100% survival to adulthood at a salinity of 10 ppt (equivalent to about 29% seawater) and 12 ppt (roughly 34% seawater). In comparison, larvae from the freshwater population could only survive in salinities up to 8 ppt. (~23% seawater) (Ramasamy et al., 2014). Another study has reported that any seawater concentration above 1.5g/L (~4.3%) causes 100% mortality of larvae (Ekechukwu & Ekeh, 2011). Because salinity tolerance is so variable between 13 different strains and populations, it was important that I repeated the seawater and NaCl experiments with the colony of Ae. aegypti that I was working with to account for this intra-species variation in order to properly compare with the additional ions I am testing. 2.1.4 Salinity tolerance of the larvae of Ae. togoi Ae. togoi are known as the coastal rock pool mosquito because they develop in fluctuating salt-water rock pools (Morritt & Williams, 2000; Peach & Matthews, 2020). Rock pools present a physiologically challenging habitat for the organisms occupying them due to high fluctuations in environmental conditions. Variables such as salinity, temperature and oxygen concentration vary on a daily as well as a seasonal basis (Taylor & Morris, 1983). In particular, these pools often experience extreme changes in salinity due to evaporation and warming during the summer which causes the salinity to increase. They may also experience extreme dilution during heavy rainfall in the autumn and winter (Cheung, 1991). In order for the larvae of Ae. togoi to get oxygen, they must swim to the surface of these rock pools to breath using distal abdominal spiracles. These migrations from the bottom or middle to the surface of the pool can expose larvae to a range of salinities (salt water is denser than freshwater and so the salinity is often higher at the bottom of pools) (Morritt & Williams, 2000). Ae. togoi must be capable not only of surviving in a wide range of salinities, but also of tolerating very quick changes in salinity. Previous studies have confirmed that Ae. togoi larvae show higher levels of survival in saline water than Ae. aegypti (Lien, 1960; McGinnis & Brust, 1983; Morritt & Williams, 2000). One study found that the larvae of a laboratory colony of Ae. togoi from Vancouver, B.C 14 completed development successfully at 0, 10, 20 and 35g/L (~0, 28, 57, 100% seawater, Table 1) with no significant difference in larval mortality (McGinnis & Brust, 1983). Another study found that Ae. togoi larvae in Hong Kong could survive and maintain haemolymph concentration when they external solution was between 300-1240mOsm/kg (i.e. up to about 100% seawater) but increased larval mortality was seen when larvae were reared in hypersaline conditions (>1800mOsm/kg ~ 150% seawater) (Morritt & Williams, 2000). Interestingly, although 1800mOsm/kg appears to be the cut off threshold for Ae. togoi larvae in the laboratory, they have been found in rock pools in the wild with osmotic concentrations much higher (up to 4000mOsm/kg ~325% seawater) without any apparent adverse effects (Morritt & Williams, 2000). However, as with Ae. aegypti, different strains of Ae. togoi from different places may have differing tolerances to salt water. In addition, the survival of these two species in a wide range of ionic salts has not been tested. Therefore, this study may lead to a better understanding of which ions are important in determining overall salt tolerance. 15 2.2 Methods 2.2.1 Aedes aegypti stock colony Ae. aegypti Orlando strain was used for all experiments involving Ae. aegypti. Eggs were obtained from a laboratory colony established by B. Matthews at the University of British Columbia, Vancouver. Ae. aegypti eggs were hatched using a vacuum pump to ensure all larvae hatched at the same time. Larvae were then placed in larval rearing pans containing dechlorinated water (12.75 x 10.4375cm). These pans were kept in an incubator at 25°C and larvae were fed ground fish food (Tetramin 77803-02). After 3-5 days, pupae were removed, placed in smaller containers, and put into mesh cages (30 x 30 x 30cm). Cages were kept in an insectary which was maintained at 80 % humidity and 27°C. All mosquitoes were reared with a photoperiod of 14L10D. A 20mL vial of 10% sucrose solution with a cotton wick was placed in each cage to provide non-blood nutrition for adult mosquitoes. Females were fed defibrinated sheep’s blood approximately 3 days before eggs were needed (see 2.2.3). Gravid females were given access to water in a circular plastic dish with filter papers to oviposit in. 2.2.2 Aedes togoi stock colony A laboratory colony of Aedes togoi was established from wild larvae and pupae collected from supra-littoral rock pools above the high tide mark at Lighthouse Park in West Vancouver (approx. 49.3316° N, 123.2636° W). Eggs were not hatched in a vacuum pump as it seemed to have no effect on hatching. As with Ae. aegypti, larvae were placed in larval rearing pans containing dechlorinated water and raised in a 25°C incubator. They were also fed ground fish food (Tetramin 77803-02). Larvae of Ae. togoi took longer to develop than Ae. aegypti and were also more variable in hatching and rearing time (personal observation from preliminary 16 laboratory experiments). Rearing time refers to the development time of mosquitoes in the laboratory from egg to adult. Once egg-containing papers were placed in water, eggs hatched in waves, with the second round of larvae hatching from the same paper, around a week or so after the first larvae emerged. Seven to ten days after hatching, pupae were removed, placed in small plastic containers, and put into a large colony cage. Cages were kept at room temperature as opposed to the humid insectary as Ae. togoi are found in more temperature climates than Ae. aegypti. As with Ae. aegypti, Ae. togoi were reared with a photoperiod of 14L10D. Adults were given constant access to a wick attached to a 20 mL vial of 10% sucrose solution. Females were sometimes fed defibrinated sheep’s blood using the membrane feeder, however they had to be supplemented with human blood from a volunteer when colony numbers became low. It was noted that when fed defibrinated sheep’s blood, Ae. togoi did not lay as many eggs as they did when fed human blood. Gravid females were given access to water in a circular plastic dish with a brown, textured paper lining to oviposit in as it was noted that, Ae. togoi were more likely to lay eggs on a textured surface than the smooth filter paper. 2.2.3 Blood feeding apparatus Mosquitoes require important cues such as heat and CO2 in order to take a blood meal. Our lab has developed a blood feeding procedure in which four glass blood feeders are attached by water lines to a pump (Figure 1). Parafilm is stretched and attached to the bottom of each glass feeder to mimic human skin and provide the mosquitoes with a membrane to insert their proboscis into (Figure 2,3). Five ml of defibrinated sheep’s blood is then transferred to each feeder being used. The pump propels water that has been heated to human body temperature 17 (37°C) through these glass feeders and this water heats the blood. Once the blood feeding assay is set up, human breath is blown over the cages to induce the mosquitoes to take a blood meal. Figure 1. Blood feeding set up. Photos taken by Nick Tochor Figure 2A. Parafilm stretched over the glass blood feeder to act as a membrane. B. Blood being transferred to the glass feeder on top of a cage of mosquitoes. Photos by Nick Tochor. A B 18 Figure 3. Ae. aegypti feeding on artificial membrane. 2.2.4 Larval survival assays Larvae were hatched in larval rearing pans containing dechlorinated water. After 24 hours, 1st instar larvae were picked out to be used for experiments. The salts tested were: sodium chloride (NaCl) (VWR catalog # CASX0420-3), Instant Ocean© (Instant Ocean Spectrum Brands catalog #SS15-10), potassium chloride (KCl) (Sigma Aldrich, catalog #P9541-500G), magnesium chloride (MgCl2) (VWR, catalog #97063-152), sodium sulfate (Na2SO4) (VWR, catalog # BDH9302-500G) and calcium chloride (CaCl2) (Sigma, Aldrich, catalog #C5670-500G). All solutions were made by molarity and then were converted to osmolarity for analysis. This was done by multiplying the molarity by the number of particles produced when the solution is dissolved in water. The reason for converting units from molarity to osmolarity is that compounds dissociate into ions in water and these ions are what the biological membrane of aquatic organisms must deal with. I was interested in investigating how mosquito survive in solutions containing different ions. The concentrations tested are listed in Table 2. Because 19 Instant Ocean is a mixture of many different ionic salts, a master batch of Instant Ocean (1.2 Osm or 100% seawater) solution was made up and checked using an osmometer. This solution was then diluted to get the desired concentrations. For this reason, only the osmolarity (and not the molarity) is reported. The concentrations tested differ between Ae. aegypti and Ae. togoi because the goal was to find the concentration that caused 100% mortality of larvae and this concentration was quite different depending on the species and the ionic salt solution. Dechlorinated water was used in the control group (0 Osm/L). Ten one day old larvae were placed in a plastic cup containing 150ml of salt solution. Three replicates of each concentration were tested. Larvae were fed fresh fish food (Tetramin 77803-02) every 48 hours or whenever needed, taking care not to over feed. Cups were checked every 48 hours and the number of larvae alive, dead, and pupated was measured. Pupae were removed and placed in a separate container where they could emerge as adults. Dead larvae were removed each time the assay was checked. Larval survival was measured as the proportion of larvae that survived to pupation. 20 Salt Species Concentration (M/L) Concentration (Osm/L) Instant Ocean Ae. aegypti Ae. togoi 0.025 0.05 0.075 0.1 0.125 0.15 0.175 0.2 0.25 0.3 0.35 0.4 0.45 0.5 0.55 0.6 0.25 0.5 0.75 1 1.5 2 2.5 3 NaCl Ae. aegypti Ae. togoi 0.025 0.05 0.075 0.1 0.125 0.15 0.175 0.2 0.125 0.25 0.375 0.5 0.625 0.75 0.875 1 1.5 2 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.25 0.5 0.75 1 1.25 1.5 1.75 2 3 4 MgCl2 Ae. aegypti 0.025 0.05 0.075 0.1 0.125 0.15 0.175 0.2 0.075 0.15 0.225 0.3 0.375 0.45 0.525 0.6 21 Table 2. All ionic salt concentrations tested in larval survival studies of Ae. aegypti and Ae. togoi Salt Species Concentration (M/L) Concentration (Osm/L) MgCl2 KCl Ae. togoi Ae. aegypti Ae. togoi 0.025 0.05 0.075 0.1 0.025 0.05 0.075 0.1 0.125 0.15 0.175 0.2 0.00625 0.0125 0.025 0.125 0.25 0.075 0.15 0.225 0.3 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.0125 0.025 0.05 0.25 0.5 CaCl2 Ae. aegypti Ae. togoi 0.025 0.05 0.075 0.1 0.125 0.15 0.175 0.2 0.025 0.05 0.075 0.1 0.125 0.15 0.175 0.2 0.075 0.15 0.225 0.3 0.375 0.45 0.525 0.6 0.075 0.15 0.225 0.3 0.375 0.45 0.525 0.6 Na2So4 Ae. aegypti Ae. togoi 0.025 0.05 0.075 0.1 0.125 0.15 0.175 0.2 0.025 0.05 0.075 0.1 0.075 0.15 0.225 0.3 0.375 0.45 0.525 0.6 0.075 0.15 0.225 0.3 22 2.2.5 Statistical analysis All statistical analyses were performed using R (Version 4.2.1) and alpha was set at 0.05 throughout. Classic LC50 ecotoxicology analysis could not be used to analyse this data due to high control mortality (too high to do mathematical correction), not enough partial kills, and variability in responses (see Appendix Figure A1, A2). In addition, because the osmolarity of concentrations tested for each salt differed, an ANOVA of survival as a factor of identity of the salt could not be performed to uncover whether survival was significantly different between the salts. A one-way ANOVA was performed to test if osmolarity explained significant variation in larval survival (Rao & Lin, 2020). The normality and homogeneity of variance were examined using Q-Q plots and Levene test, respectively. All data met the homogeneity assumption and because the analysis of variance is robust to non-normality and sample sizes were equal amongst groups, the failure to meet the normality test was ignored. If the effect of osmolarity was statistically significant, a post-hoc Tukey HSD was performed to find the concentration at which survival began to be significantly affected. This procedure was repeated independently for Ae. aegypti and then for Ae. togoi. In this way I could compare the dose that caused the first significant decrease in percentage survival between the salts. To compare larval survival between species, a two-way ANOVA, followed by a post-hoc Tukey HSD was performed with osmolarity, species, and the interaction between osmolarity and species as factors (Rabiul Alam et al., 2018; Woodley et al., 2023). These analyses were conducted for each salt tested. Only concentrations that had been tested on both Ae. aegypti and Ae. togoi were kept in this analysis. 23 2.3 Results 2.3.1 Effects of different ionic salts on Aedes aegypti As expected, Ae. aegypti larvae survival was high (mean = 93.43%, sd= ± 7.64%) in the dechlorinated freshwater controls and survival decreased as osmolarity increased for all solutions (Figure 4). As hypothesized, the identity of the salt that larvae were reared in was found to affect survival (Table 3). In other words, Ae. aegypti larvae were more tolerant to some solutions than others. The concentrations that killed 100% of larvae were: 0.45 Osm in Instant Ocean, 0.4 Osm in NaCl, 0.225 Osm in MgCl2, 0.3 Osm in KCl, 0.375 Osm in CaCl2 and 0.3 in Na2SO4 (Figure 4). The effect of increases in salt concentration on survival also differed between salts. For example, Ae. aegypti larvae showed high survival rates in concentrations of Instant Ocean up to 0.45 Osm whereas survival steadily decreased as salt concentration increased for NaCl. The percentage of larvae that survived at intermediate concentrations (0.15-0.3 Osm) was lower than in Instant Ocean. These results suggest that Ae. aegypti larvae are most tolerant to Instant Ocean and least tolerant to MgCl2. 24 Figure 4. Percentage survival of Ae. aegypti larvae in A. Instant Ocean©, B. sodium chloride (NaCl), C. magnesium chloride (MgCl2), D. potassium chloride (KCl), E. calcium chloride (CaCl2), F. sodium sulfate (Na2SO4) solutions across a concentration gradient. Black dots represent each replicate (% survival of 10 larvae), while the boxplot represents group data. The horizontal line in the boxplot is the median and the whiskers represent the minimum (Q1-1.5 xIQR) and maximum (Q3 + 1.5 xIQR). n = 3 groups/concentration. In a given panel, data labeled with different letters are significantly different from each other; p<0.05, ANOVA followed by Tukey’s HSD. 25 Salt Species df F p-value Instant Ocean Sodium Chloride Ae. aegypti Ae. aegypti 16 9 63.45 27.42 2e-16* 2.4e-09* Magnesium Chloride Ae. aegypti 8 185.7 1.08e-15* Potassium Chloride Calcium Chloride Ae. aegypti Ae. aegypti 8 8 52.2 121.9 6.9e-11* 4.41e-14* Sodium Sulfate Ae. aegypti 8 230.1 <2e-16* Table 3. The results of a series of one-way ANOVAs to test the effect of osmolarity (Osm) on Ae. aegypti larvae percentage survival for each salt tested. Asterisk (*) denotes significance at α= 0.05 2.3.2 Effects of different ionic salts on Aedes togoi larval survival Ae. togoi larval survival generally decreased as osmolarity increased (Figure 5, Table 4). However, unlike Ae. aegypti, the larvae of Ae. togoi did not show 100% survivability in the control solutions (0 Osm) (mean = 58.15%, sd = ± 20.41%) and in some trials (especially Instant Ocean and NaCl), percentage survival initially increased with an increase in osmolarity before decreasing. Individual larval survival was also much more variable than Ae. aegypti. Survival of Ae. togoi larvae was markedly affected by the identity of the salt they were reared in. The dose that killed 100% of larvae is as follows: 1.5 Osm in Instant Ocean. 1.5 Osm in NaCl, 0.225 Osm in MgCl2, 0.05 Osm in KCl, 0.15 Osm in CaCl2 and 0.15 Osm in Na2SO4 (Figure 5). Ae. togoi larvae were tolerant to very high concentrations of Instant Ocean and NaCl (10 times more than Ae. aegypti), but not other solutions. They were least tolerant to KCl, a very low dose (0.05 Osm) caused 100% mortality of larvae (Figure 5). 26 Figure 5. Percentage survival of Ae. togoi larvae in A. Instant Ocean©, B. sodium chloride (NaCl), C. magnesium chloride (MgCl2), D. potassium chloride (KCl), E. calcium chloride (CaCl2), F. sodium sulfate (Na2SO4) solutions across a concentration gradient. Black dots represent each replicate (% survival of 10 larvae), while the boxplot represents group data. The horizontal line in the boxplot is the median and the whiskers represent the minimum (Q1-1.5 xIQR) and maximum (Q3 + 1.5 xIQR). n = 3 groups/concentration. In a given panel, data labeled with different letters are significantly different from each other; p<0.05, ANOVA followed by Tukey’s HSD. 27 Salt Species d.f F p-value Calcium Chloride Ae. togoi 6 56.33 5.28e-09 * Instant Ocean Ae. togoi 8 76.62 2.55e-12 * Magnesium Chloride Ae. togoi 4 17.88 0.00015 * Potassium Chloride Ae. togoi 6 21.56 4.74e-06 * Sodium Chloride Ae. togoi 10 3.923 0.00745 * Sodium Sulfate Ae. togoi 4 83.5 1.22e-07 * Table 4. The results of a series of one-way ANOVAs to test the effect of osmolarity (Osm) on Ae. togoi larvae percentage survival for each salt tested. Asterisk (*) denotes significance at α = 0.05 2.3.3 Comparison of larval survival between Aedes togoi and Aedes aegypti A two-way ANOVA showed that Ae. aegypti and Ae. togoi differed in their mean survival rates and that each species responded to salt concentration uniquely (Table 5). Figure 6 shows the results of a post-hoc Tukey test following this ANOVA. Overall, at shared concentrations, Ae. togoi had higher survival rates in the highest concentrations of NaCl and Instant Ocean but Ae. aegypti had higher survival rates in the highest concentrations of MgCl2, Na2SO4, KCl and CaCl2 (Figure 6). Ae. aegypti appear to have an absolute Osm limit in all salts while Ae. togoi can survive in high concentrations of NaCl and Instant Ocean but not the other ionic salts tested. Table 6 reports the concentration of each salt solution that caused the first significant decrease in survival as well as the dose that caused 100% mortality of larvae for both species. 28 Figure 6. Comparison of percentage survival of Ae. togoi and Ae. aegypti larvae in A. Instant Ocean©, B. sodium chloride (NaCl), C. magnesium chloride (MgCl2), D. potassium chloride (KCl), E. calcium chloride (CaCl2), F. sodium sulfate (Na2SO4) solutions at shared concentrations. Dots represent each replicate (% survival of 10 larvae), while the boxplot represents group data. The horizontal line in the boxplot is the median and the whiskers represent the minimum (Q1-1.5 xIQR) and maximum (Q3 + 1.5 xIQR). n = 3 groups/concentration. In a given panel, data labeled with an asterisk show significant differences in percentage survival between species at that concentration, p<0.05, 2-way ANOVA followed by Tukey’s HSD 29 Salt Variable d.f F p-value Calcium Chloride Species Osmolarity Species:osmolarity 1 2 2 334.53 25.12 19.08 3.95e-10* 5.14e-05* 0.000188* Instant Ocean Species Osmolarity Species:osmolarity 1 2 2 9.6 30.47 80.6 0.00922* 1.98e-05* 1.11e-07* Magnesium Chloride Species Osmolarity Species:osmolarity 1 3 3 77.04 61.04 13.15 1.63e-07* 5.59e-09* 0.000138* Potassium Chloride Species Osmolarity Species:osmolarity 1 2 2 353.659 9.962 9.127 1.03e-09 * 0.00340* 0.00446* Sodium Chloride Species Osmolarity Species:osmolarity 1 2 2 1.710 7.639 10.279 0.21554 0.00727* 0.00251* Sodium Sulfate Species Osmolarity Species :osmolarity 1 2 2 342.35 43.49 14.01 3.45e-10* 3.18e-06* 0.000727* Table 5. The results of a series of two-way ANOVAs to test the effect of species, osmolarity (Osm) and their interaction on percentage survival for each salt tested. Asterisk (*) denotes significance at α = 0.05 30 Salt Species Concentration that caused first significant decrease in survival (Osm) Concentration that is lethal to 100% of larvae (Osm) Instant Ocean Ae. aegypti 0.45 0.45 Ae. togoi 1.5 1.5 Sodium Chloride Magnesium Chloride Ae. aegypti Ae. togoi Ae. aegypti 0.15 1.5 0.225 0.4 1.5 0.225 Ae. togoi 0.15 0.225 Potassium Chloride Ae. aegypti 0.25 0.3 Ae. togoi 0.05 0.05 Calcium Chloride Sodium Sulfate Ae. aegypti Ae. togoi Ae. aegypti 0.3 0.075 0.15 0.375 0.075 0.15 Ae. togoi 0.075 0.15 Table 6. Concentration that caused the first significant decrease in survival and concentration that is lethal to 100% of larvae for each species and each salt tested. 31 2.4 Discussion As predicted, Ae. aegypti and Ae. togoi larval survival was found to be different depending on the identity of the ionic salt they are reared in. However, contrary to predictions, Ae. togoi, a saltwater species, only had higher survival rates than Ae. aegypti, the freshwater species, in two of the six solutions tested, NaCl and Instant Ocean. 2.4.1 H1: Mosquito larval survival depends on the concentration and the identity of the ionic salt solution they are reared in The results of this study give support to the hypothesis that mosquito larval survival depends on both the concentration and identity of the ionic salt solution they are reared in. Both Ae. aegypti and Ae. togoi showed different survival rates depending on the identity of the salt they were reared in even when the osmolarity was the same (although survival differed far more between salts for Ae. togoi as compared to Ae. aegypti). For example, at 0.4 Osm of Instant Ocean, 100% of Ae. aegypti larvae survived but at 0.4 Osm of KCL, 100% of Ae. aegypti larvae died (Figure 4). Similarly, for Ae. togoi larval survival was dramatically affected by the identity of the salt they were reared in. They survived in concentrations of NaCl and Instant Ocean around 10 times higher than any of the other salt solutions. However, survival was lower than Ae. aegypti larvae in MgCl2, KCl, CaCl2 and Na2SO4. These results could hint that mosquito larvae cope with different ions using ion specific mechanisms. Instant Ocean is the best proxy for the effects of high salinity as it contains a reasonable ratio of ions. Although the concentration that killed 100% of larvae was similar for Instant Ocean and NaCl for each species (0.4-0.45 Osm for Ae. 32 aegypti, 1.5 Osm for Ae. togoi), the pattern of survival is different. Both species are better able to cope with relative intermediate concentrations of Instant Ocean than intermediate concentrations of NaCl. This could suggest that a particular balance of ions is important for mosquito larvae to maintain homeostasis and single salt ions, in the absence of balancing ions can lead to larval death. These results are similar to other studies that have investigated the larval salinity tolerance of Ae. aegypti and Ae. togoi. Clarke et al., found that 100% of Ae. aegypti larvae survived at 10% Instant Ocean (which is approximately 0.1 Osm) and that there was a sharp decline in survival at 30% Instant Ocean (approximately 0.4 Osm). In this study the first significant decline in survival occurred at 0.45 Osm of Instant Ocean. McGinnis & Brust found that Ae. togoi larvae could survive in concentrations up to 100% seawater (1.2 Osm). In this study the first significant decline in larval survival occurred at 1.5 Osm. 2.4.2 H2: As Ae. togoi develop in saline rock pools, they have evolved a higher salt tolerance than Ae. aegypti. The results of these studies go against the original prediction that as a salt-water species, Ae. togoi would show higher rates of survival in all solutions tested. Although this study and others have shown that Ae. togoi larvae can survive in higher concentrations of seawater than Ae. aegypti, this is not the case for other ionic salts such as Na2SO4, CaCl2 and KCl (Clark, 2004; McGinnis & Brust, 1983) Ae. togoi only showed higher survival rates than Ae. aegypti in Instant Ocean and NaCl. This was an interesting finding and may shed some light on how 33 osmoregulatory strategies differ between freshwater and saltwater larvae. These results suggest that Ae. togoi have developed specialised ways of dealing with NaCl and seawater. As discussed previously, both Ae. aegypti and Ae. togoi are osmoregulators, using species specific strategies to ensure the maintenance of a strict haemolymph osmolarity regardless of the external salinity. Studies have begun to describe the mechanism of Na+, Cl- and K+ regulation in Ae. aegypti. Na+ and Cl- are actively transported across the epithelium of the anal papillae through many different specialized ion transport proteins whereas potassium ions can move passively through the body via diffusion, driven by concentration gradients (Donini et al., 2007; Donini & O’Donnell, 2005). A full understanding of the molecular mechanisms of ion transport in mosquito larvae remains unresolved but Na+/K+-ATPase and V-type H+-ATPase are thought to be the primary enzymes responsible for providing the energy to transport ions in the anal papillae (Durant et al., 2021). Studies have suggested that Na+ is taken up through a Na+ channel while Cl- is taken up though a Cl-/HCO3– exchanger (Del Duca et al., 2011). All Na+, Cl- and K+ ion regulation is thought to occur at the anal papillae however, little is known about how mosquito larvae regulate other ions that could be found in aquatic habitats such as SO4, Mg2+ or Ca2+. It has been found that transport of Ca2+ does not occur at the anal papillae (Barkai & Williams, 1983). Perhaps the anal papillae is the site of exchange for monovalent ions such as Na+, Cl- and K+ while exchange of divalent ions occurs in the other osmoregulatory organs such as the Malpighian tubules and the midgut. The results of this study show that Ae. aegypti can survive at intermediate concentrations of MgCl2, CaCl2 and KCl. This indicates that they must have some ability to regulate these ions. In contrast, Ae. togoi clearly posses specific mechanisms to transport high concentrations of Na+ and Cl- but they do not posses the ability to regulate other ions. 34 Studies of another salt-water mosquito, Aedes campestris, have hypothesized that the transport rate for ions is altered when the larvae are placed in hyper-saline conditions either through changes in the number of protein carriers in the epithelium or through stimulating carriers that are already present through hormonal or neural control (Bradley & Phillips, 1977a). Perhaps, due to their habitat (ocean water is mostly dominated by chloride (~19g/L) and sodium (~10.5g/L) (Millero et al., 2008)), Ae. togoi can in a similar way increase the transport rate of Na+ and Cl-. Because they rarely come into contact with high concentrations of these other ions, they may not possess the ability to increase the transport rate of them. Ae. togoi may be a generalist for sodium and chloride concentration (i.e., they can survive in a wide range of concentrations of NaCl) but a specialist for ion specificity (i.e., they cannot survive in wide range of ions). In contrast, Ae. aegypti appear to be capable of surviving in a wider range of ions up to a certain concentration (with the exception of MgCl2). Studies have demonstrated that Ae. aegypti larvae exhibit remarkable adaptability to varying types of water (Kengne et al., 2019; Ramasamy et al., 2014; Surendran et al., 2018). For example, one study has shown that the anal papillae of Ae. aegypti larvae increase in size when adapted to brackish water and then decrease when reared in freshwater (Surendran et al., 2018). Ae. aegypti larvae are also capable of surviving in high levels of ammonia (NH4+ ) that other animals cannot survive in (Chitolina et al., 2016; Durant & Donini, 2019; Irving-Bell et al., 1987). One study found that Ae. aegypti larvae displayed significant plasticity in responding to high levels of external ammonia by modifying the excretion of ammonia via the anal papillae (Durant & Donini, 2019). Perhaps it is this ability to adapt to unusual water types that has allowed Ae. aegypti to spread around the globe. Ae. togoi, on the other hand, appear not to possess this capacity for adapting to various water types due to their restriction to coastal areas. 35 They rarely encounter ions apart from Na+ and Cl- in high concentrations and so are not equipped to excrete them. Another possible explanation for the apparent toxic effects of KCl, Na2SO4 and CaCl2 to Ae. togoi might be related to how this species ingests ions. Saline water larvae increase their drinking rate in hypersaline conditions to replace water that is lost by osmosis (Bradley et al., 1984). As a result of this increase in drinking, larvae must process a significant salt load. Presumably, the salt-secreting organs (the rectum and anal canal) of Ae. togoi are well adapted to excreting Na+ and Cl-, but they may not be capable of excreting large loads of these other ions. 2.4.3 Future directions Overall, it appears that, Ae. aegypti may posses the ability to survive in a wide range of ions (up to a threshold of approximately 300mOsm) while Ae. togoi are more specialised to survive in high concentrations of Na+ and Cl-. A full analysis of the ion transporters present in both Ae. aegypti and Ae. togoi larvae is needed to uncover the molecular mechanisms for how these species differ in their osmoregulation strategies. As described above, several potential ion transporters (such as Na+/K+-ATPase and V-type H+-ATPase) have already been identified and sequenced in Ae. aegypti larvae and many other exchangers (K+/H+ and Na+/H+ ) have been theorised (Donini & O’Donnell, 2005; Durant et al., 2021). Firstly, a more complete model of ion transporters in the anal papillae, the Malpighian tubules and the midgut of mosquito larvae is needed. Then, it would be interesting to uncover if these transporters are present in the larvae of Ae. togoi and also if they show differential gene expression to Ae. aegypti in response to hypersaline conditions. Modern genomic approaches will aid in these goals. 36 One study found, when raised in freshwater versus saline water, Anopheline larvae experience a significant change in the localization of rectal Na+/K+ P-ATPase, indicating a significant shift in their physiological response (Smith et al., 2008). This change in protein localisation was seen in both a freshwater Anopheline species (Anopheles gambiae) and a saline water Anopheline species (An. albimanus). The authors concluded that this regulation of protein expression was distinct from culicine larvae. The results of this study suggest that conclusions drawn from data related to one genus of mosquito cannot necessarily be generalized to all species. Although Ae. aegypti and Ae. togoi are both part of the Aedes genus, this sentiment still applies. It is important to understand how the physiological mechanisms of osmoregulation in a species such as Ae. aegypti differs from a species such as Ae. togoi. Future directions for this work include sequencing the transcriptome of both Ae. aegypti and Ae. togoi osmoregulatory organs in freshwater and then comparing the expression when larvae are reared in hypersaline media. This could shed some light on where different transporters are located (i.e., the anal papillae, Malpighian tubules, hindgut) and also, how transporters may be upregulated during times of osmotic stress. In addition, I have suggested that Ae. aegypti may be more plastic in their ability to adapt to unusual water types. The plastic ability of Ae. togoi could be investigated by acclimating larvae to various concentrations of these ionic salts to see if they show higher survivability than when they are exposed chronically to high concentrations as they were in this study. 37 Chapter 3: Oviposition preference of Ae. aegypti and Ae. togoi Chapter 3 objectives The objective of my third chapter was to investigate the oviposition preference of Ae. aegypti and Ae. togoi in response to the same salts that were tested in the larval survival assays. There is evidence that some dipteran species possess osmosensitive ion channels that are responsible for detecting water and regulating water intake (Cameron et al., 2010). Insects are capable of tasting salt and also sensing osmolarity. These experiments aim to determine which of these factors guides egg-laying. My first hypothesis (H1) is that osmolarity is the primary factor that mosquitoes use to evaluate if a given body of water is suitable for egg laying. Therefore, I predict that egg laying preferences will be similar at the same concentration (osmolarity) of different ionic salt solutions. From the findings of chapter 2 it is clear that Ae. togoi can survive in a much higher concentration of NaCl and Instant Ocean than Ae. aegypti. My second hypothesis (H2) is that because of this, Ae. aegypti and Ae. togoi would show different oviposition preferences to each other. I predicted that Ae. togoi would begin to show a preference for ovipositing in the freshwater solution over the treatment solution at a higher concentration than Ae. aegypti would begin to show a preference. The objective is to determine whether oviposition preference differs between a freshwater and a saltwater mosquito. This could aid in uncovering whether the chemosensory system differs between two species that face very different challenges in their respective habitats. 38 3.1 Introduction In order to develop eggs, anautogenous female mosquitoes require the proteins found in blood (Zhou et al., 2007). Once a female mosquito has taken a blood meal from its preferred host, she must locate a suitable site to lay these eggs (Day, 2016). Selecting an appropriate egg-laying (oviposition) site is critical to fitness in animals such as mosquitoes as they do not engage in parental care once the eggs have been laid. Because the larvae of mosquitoes are aquatic and cannot move from where they hatch, the choice of oviposition site can be a determinant of mosquito fitness and survival (Baik & Carlson, 2020). Mosquitoes exhibit a remarkable diversity of oviposition behaviors depending on the species and their range (Day, 2016). Despite these differences, oviposition behavior for all mosquito species requires that the mosquito identifies and responds to a complicated mix of physical and chemical cues. There are a variety of ways that female mosquitoes choose where to oviposit. First, they locate potential water sources using long range cues such as vision, bacterial volatiles and humidity (Bentley & Day, 1989; Costa et al., 2010; Navarro et al., 2003). Once the mosquito has found a source of water, she uses short range cues to decide where to lay her eggs (Bentley & Day, 1989). She probes the water using her tarsi and mouthparts to test for a variety of factors (such as salinity, presence of food and presence of chemical cues from con-specific larvae or predators) that will determine if this body of water is suitable for larvae (Afify & Galizia, 2015; Pamplona et al., 2009; Zahiri & Rau, 1998). If a body of water is deemed suitable, the female will then deposit her eggs. One solution to limit the spread of disease vectors such as Ae. aegypti is to prevent egg-laying in standing water. Understanding how adult females choose and evaluate breeding sites can aid in controlling mosquito species. If we can understand the cues that stimulate egg-laying, 39 there is the potential to interrupt the egg-laying process. This can be done chemically using oviposition traps and making standing water sites unsuitable for larvae or genetically, by modifying how adult females interpret these cues. Investigating the difference in oviposition preference between a wide-spread species (Ae. aegypti) and a restricted species (Ae. togoi) can help us to uncover if these species have similar or differing strategies for evaluating water sites and ultimately choosing an oviposition site. By testing different ionic salts (NaCl, Instant Ocean©, KCl, MgCl2, Na2SO4, CaCl2) we can begin to understand one of the cues that the adult mosquito is sensing when she decides to either lay her eggs or avoid a potential breeding site. She may be using osmotic pressure or presence of a particular ion to make this decision. 3.1.1 The mosquito taste system and oviposition behavior Salt taste is one of the most complex taste modalities in insects and several pathways work in combination to detect salt (Taruno & Gordon, 2023). It has been found that, of the five classes of sensory neurons expressed in the fly labellum (e.g. mouthparts), four are activated by salt (Jaeger et al., 2018). Many taste modalities are evolutionarily conserved between flies and mosquitoes and some may be modified in the mosquito for behaviors other than feeding, such as oviposition (Baik & Carlson, 2020). Each mosquito species is likely to have evolved a taste system tuned to its specific needs. Presumably, some taste responses will be evolutionarily conserved between species while others will have evolved in response to a new habitat or life history. Comparative studies can inform the mechanisms of how mosquito behavior has evolved. The complete understanding of how neural responses are signaled by salt-tasting organs at the molecular and cellular level remains elusive. Recently, it has been discovered that 40 freshwater egg-laying behavior in Ae. aegypti is mediated by the ion channel ppk301 (Matthews et al., 2019). Ppk301 is found in chemosensory structures such as the tarsi and proboscis that touch the water when a female is evaluating a potential egg laying site. Ppk301 neurons are triggered by both water and high salt but mutants that have the ppk301 gene knocked out no longer respond to water but still respond to salt. The authors suggested that some other pathway is responsible for aversion to high salt. It is possible that this other pathway is activated by ions that are a proxy for salinity. By investigating oviposition behavior in a range of ionic solutions, it may be possible to infer what, if any, ion activates the sensory receptors that cause a mosquito to avoid a salty breeding site. It is also possible that the cue that the adult mosquito senses when she evaluates a body if water is not ionic composition. In Drosophila melanogaster an osmosensitive protein called ppk28 is responsible for detecting water and regulating water intake (Cameron et al., 2010). Therefore, it is plausible that mosquitoes also use an osmosensitive channel to detect osmotic pressure and infer information about a given body of water. By controlling for osmolarity, we can test if the oviposition preference of the adult mosquito is the same between various ionic salts and this can tell us if osmotic pressure is the key driver of aversion to salty breeding sites. 3.1.2 Oviposition behavior of Ae. aegypti and Ae. togoi Because Ae. aegypti are synanthropic and generally live and breed close to humans, they tend to lay eggs in freshwater containers found in urban environments such as barrels, plastic drums, and jerrycans (Getachew et al., 2015). These containers, which are often found near human settlements, tend to be more long-lasting than natural ones and are also more likely to 41 hold standing water. Numerous studies have indicated a strong correlation between Ae. aegypti and urban environments. (Hiscox et al., 2013; Maciel-de-Freitas et al., 2006; Paupy et al., 2010). The larvae of Ae. aegypti are considered freshwater and, aside from some brackish water populations, usually cannot survive in solutions of high salinities (Bradley, 1987; Clark, 2004; V. Wigglesworth, 1938). Studies have shown that the number of eggs laid by Ae. aegypti decreases as salinity increases (Gunathilaka et al., 2018; Matthews et al., 2019; Panigrahi et al., 2014; Xia, 2021). Ae. aegypti overwhelmingly prefer to oviposit in freshwater or water of very low salinity. One study found, when given a choice of oviposition sites, the highest rate of oviposition occurs in a solution of 0.2% NaCl (~5.7% seawater), the amount of eggs laid is significantly reduced in a 1% NaCl (~29% seawater) and no eggs are laid in solutions more saline than 3% NaCl (~86% seawater) (Gunathilaka et al., 2018). However, as with larval salinity tolerance, the oviposition behaviors between different strains of Ae. aegypti can vary. In coastal regions in Jaffna, Sri Lanka some populations of Ae. aegypti have been found to oviposit in brackish water of up to 18 ppt (51% seawater) (Ramasamy et al., 2011). Other laboratory studies have shown that female adults do not show a preference between 0 and 10% seawater and only start showing an aversion to saltwater at 12% (Matthews et al., 2019; Navarro et al., 2003). Ae. aegypti are still generally considered to be a freshwater species although significant variation in tolerance to brackish water may be seen in different populations. In contrast to Ae. aegypti, the larvae of Ae. togoi develop in brackish water of fluctuating salinity and so the oviposition preference of adults is quite different to that of Ae. aegypti (Asakura, 1980a; Lien, 1960; Morritt & Williams, 2000). One study found that female mosquitoes did not display a preference between distilled water and salt solutions containing 5, 42 10, and 20g/L of salt (14, 29, 57% seawater). However, they actively avoided the 40g/L (114% seawater) NaCl solution (Trimble & Wellington, 1979). Methods 3.2 3.2.1 Two choice oviposition preference assays Two- choice oviposition assays were employed to determine the range at which Ae. aegypti and Ae. togoi show a preference for freshwater versus increasing concentrations of salt water. The colonies of Ae. aegypti and Ae. togoi described in methods section 2.2.1 and 2.2.2 were the same colonies used for these experiments. Ae. aegypti were blood fed 3 days before the experiment and Ae. togoi were blood fed 7 days before the experiment (see 2.2.3). Ae. aegypti were fed defibrinated sheep’s blood but because the colony of Ae. togoi were wild caught and not lab adapted they would not blood feed from the artificial feeder well enough to lay the quantity of eggs needed for this assay. For this reason, they were fed on a human volunteer. Females were visually inspected for full engorgement and those who took a blood meal were removed from the colony immediately after blood feeding and placed in a separate cage. Only these fully engorged individuals were used in the experiment. Three days after blood feeding, one gravid female was placed in a 50oz container with a mesh lid. The container contained two oviposition cups, one with 150ml dechlorinated tap water and the other with 150ml treatment salt (Figure 7). Ae. aegypti were given filter paper to oviposit on and Ae. togoi were given brown, textured paper. This is because during preliminary trials, it was found that Ae. togoi would not lay eggs on the same filter paper as Ae. aegypti and laid eggs more readily on coloured, textured paper. Ae. aegypti were given 72 hours to oviposit and Ae. togoi were given 43 one week. Mosquitoes were not given access to sugar water during the assays. Five concentrations of each salt were tested with six replicates per concentration. The salts tested were sodium chloride (NaCl), Instant Ocean©, potassium chloride (KCl), magnesium chloride (MgCl2), sodium sulfate (Na2SO4) and calcium chloride (CaCl2) for Ae. aegypti. However, due to the difficultly in obtaining sufficient replication for Ae. togoi, only sodium chloride (NaCl) and potassium chloride (KCl) oviposition assays were completed for this species. The difficulty in obtaining replicates was due to the fact that Ae. togoi did not feed as well as Ae. aegypti and a much smaller proportion of females laid eggs. In addition, the Ae. togoi colony was much smaller and development times were longer than Ae. aegypti. The concentrations tested were 0.01, 0.05, 0.1, 0.2 and 0.4 Osm for Ae. aegypti and 0.05, 0.1, 0.2 and 0.4 Osm for Ae. togoi. A random sample of treatment waters were tested using an osmometer to ensure the osmolarity was in an acceptable range. All buckets were kept in an insectary which was maintained at 80 % humidity and 27°C. At the end of the experimental period, all egg papers were photographed using a raspberry pi camera set up and all eggs were manually counted (see 3.2.2 for details on image acquisition). The oviposition preference index (OPI) was calculated for each replicate using the following formula: 𝑂𝑂𝑂𝑂𝑂𝑂 = 𝑁𝑁2− 𝑁𝑁1 𝑁𝑁2+ 𝑁𝑁1 Where N1 and N2 are the number of eggs deposited in the treatment cup and the control cup, respectively. OPI ranges from 1, -1 where -1 represents a complete preference for the control and 1 represents a complete preference for the treatment. 44 In preliminary studies it was found that individual Ae. aegypti females could lay up to 100 eggs when blood-fed. When testing a behavior such as oviposition it is important to recognize that in order to find evidence of a true preference there must be a minimum threshold met for how many eggs are laid by one individual. In order to preserve replicates while still being diligent about uncovering a true preference, any replicate where less than 10 eggs were laid was excluded from analysis. This led to numbers of replicates being slightly unequal between treatments. Figure 7. Oviposition preference assay set up. N1 represents the control (distilled water), N2 represents the treatment salt. OPI = 0.75. 45 3.2.2 Image acquisition using Raspberry pi Figure 8 shows the imaging set up that was used to photograph egg papers in this assay. A Raspberry Pi HQ camera was attached to a Raspberry Pi computer (model 3+) using a Raspberry Pi CSI ribbon cable for camera (30cm). The camera was fixed to a retort stand. An LED tracing panel was used to provide constant illumination. Egg papers were transferred from the oviposition assay to the LED tracing panel for imaging. These standardized images were used in order to facilitate efficient manual counting while providing a record of raw data. Full details of the set up as well as relevant python script can be found on the following Github repository that was created by Nicholas Tochor and Benjamin Matthews available here: https://github.com/bnmtthws/CSHL-Protocols-Mosquito-Egg-Counting Figure 8. A, Imaging set up using raspberry pi attached to a HQ camera. B, C, examples of images of egg papers acquired using raspberry pi camera set up. Photo A taken by Nicholas Tochor. 46 3.2.3 Statistical analysis All statistical analyses were performed using R (Version 4.2.1). Firstly, one-way ANOVAs were used to test if there was an effect of osmolarity on the total number of eggs laid. This was to ensure that higher concentrations of salt were not physically damaging the adult mosquitoes and preventing them from laying eggs at all. Dose-response curves were attempted to investigate the effect of increasing osmolarity of oviposition preference but because the results were extremely varied between trials there was no curve that fit all trials and so these curves could not be compared to one another. (See Appendix Figure A3). Instead, two-way ANOVA with osmolarity, salt ID, and the interaction between osmolarity and salt ID were run for each trial to test if oviposition preference, as measured by oviposition preference index (OPI), was affected by the identity of the salt for each species. A Levene test was used to test for the assumption of homogeneity of variances and normality was investigated using a Q-Q plot. All data met these assumptions. Then, one sample t-tests were performed for each concentration where the error bars did not intersect 0 to determine if the preference index was significantly different from 0. If the oviposition preference index is significantly different from 0, we can conclude that there is a preference. T-tests were corrected for multiple comparisons using Bonferroni correction. Thirteen t- tests were performed for Ae. aegypti trials and so the threshold for significance was divided by 13 (i.e., 0.05 ÷ 13 = 0.0038). Three t-tests were performed for Ae. togoi trials and so the threshold for significance was divided by 3 (i.ie., 0.05 ÷ 3 = 0.016). In order to compare oviposition preference in the various salts between species, a two-way ANOVA, followed by a post-hoc Tukey HSD was performed with osmolarity, species, and the interaction between osmolarity and species as factors. 47 3.3 Results 3.3.1 Total number of eggs laid per individual Figures 9 and 10 show the total amount of eggs laid per individual mosquito at every concentration of every salt tested. For all trials except sodium chloride on Ae. aegypti, there was no effect of osmolarity on the total number of eggs laid (Table 7). Salt Species d.f F p-value Calcium Chloride Ae. aegypti 4 1.48 0.239 Instant Ocean Ae. aegypti 4 0.75 0.566 Magnesium Chloride Ae. aegypti 4 1.852 0.155 Potassium Chloride Ae. aegypti Ae. togoi 4 3 1.01 1.527 0.426 0.238 Sodium Chloride Ae. aegypti Ae. togoi 4 3 7.42 1.121 0.00028* 0.356 Sodium Sulfate Ae. aegypti 4 0.845 0.511 Table 7. A series of one-way ANOVAs to test if test if there was an effect of osmolarity on number of eggs laid for each salt and each species. 48 Figure 9. Total amount of eggs laid per concentration. n-value represents each single female adult Ae. aegypti that laid over 10 eggs. Black dots represent each replicate, while the boxplot represents group data. The horizontal line in the boxplot is the median and the whiskers represent the minimum (Q1-1.5 xIQR) and maximum (Q3 + 1.5 xIQR). Asterix (*) indicates an effect of osmolarity on number of eggs laid. 49 Figure 10. Total amount of eggs laid per concentration. n-value represents each single female adult Ae. togoi that laid over 10 eggs. Black dots represent each replicate, while the boxplot represents group data. The horizontal line in the boxplot is the median and the whiskers represent the minimum (Q1-1.5 xIQR) and maximum (Q3 + 1.5 xIQR). Asterix (*) indicates an effect of osmolarity on number of eggs laid. 3.3.2 Ae. aegypti oviposition preference assays For all salts tested, the tendency for mosquitoes to oviposit in dechlorinated freshwater increased as the osmolarity of the salt-treatment oviposition container increased (Figure 11). In other words, the saltier the treatment solution, the more likely the mosquito was to choose to oviposit in the freshwater control. Although there was an effect of osmolarity, there was no effect of salt identity on oviposition preference for Ae. aegypti (Table 8). 50 In order to test if oviposition preference at a given concentration relative to the dechlorinated water control was significantly different from 0 (i.e., there was a preference) one-sample t-tests were employed (Table 9). Ae. aegypti adults showed no preference for ovipositing between the treatment and control at 0.01, 0.05, 0.1 and 0.2 Osm Instant Ocean (approximately 0.8, 4, 8 and 17% seawater) (Fig 11A). The only salt concentration where we observed a preference for ovipositing in freshwater was 0.4 Osm Instant Ocean. .Ae. aegypti showed stronger oviposition preferences in the NaCl trial (Figure 11B). There was a significant oviposition avoidance in the treatment at 0.05, 0.2 and 0.4 Osm but not 0.1 Osm. Ae. aegypti adults showed no preference between the control and treatment solutions 0.01, 0.05, 0.1 and 0.2 Osm of MgCl2 (Figure 11C) but, like the Instant Ocean trial, at 0.4 Osm they preferred to oviposit in the control. For KCl there was a significant preference to avoid the treatment over the control shown at 0.2 Osm but not at 0.4 Osm, although this may have been due to a single outlier skewing the data (Figure 11D). For all other concentrations tested there was no preference between the control and the treatment. For CaCl2 there was no statistically significant difference from 0 in oviposition preference for any of the concentrations tested (Figure 11E). Finally, for Na2SO4, there was a significant preference to avoid oviposition in the treatment at 0.2 and 0.4 Osm (Figure 11F). However, although not statistically significant, there appears to be more aversion to ovipositing in the lower treatment concentrations of sodium sulfate than in other salts tested. Overall, it appears that, Ae. aegypti are most averse to ovipositing in sodium chloride and sodium sulfate, the two sodium salts tested in these assays. 51 Figure 11. The effect of A Instant Ocean©, B sodium chloride (NaCl), C magnesium chloride (MgCl2), D potassium chloride (KCl), E calcium chloride (CaCl2), F sodium sulfate (Na2SO4) on the oviposition preference of adult female Ae. aegypti mosquitoes. A value of -1 indicates total preference for the control and a value of 1 indicates total preference for the treatment. Black dots represent each replicate, while the boxplot represents group data. The horizontal line in the boxplot is the median and the whiskers represent the minimum (Q1-1.5 xIQR) and maximum (Q3 + 1.5 xIQR). In a given panel, data labeled with an asterisk (*) indicates response is significantly different from 0 (t-test with Bonferroni correction, alpha = 0.0038) 52 Factor d.f F p-value Osmolarity 6 15.029 1.14e-13* Salt ID 5 1.659 0.147 Osmolarity x Salt ID 17 1.017 0.442 Table 8. The results of a two-way ANOVA to test the effect of osmolarity (Osm) and salt ID on female adult Ae. aegypti oviposition preference. Asterisk (*) denotes significance at alpha = 0.05 Salt Species Concentration (Osm) T p-value Instant Ocean Sodium Chloride Magnesium Chloride Potassium Chloride Ae. aegypti Ae. aegypti Ae. aegypti Ae. aegypti 0.4 0.05 0.2 0.4 0.4 0.1 0.2 0.4 -4.3152 -4.6623 5.1873 -11.055 -6.0383 0.69375 -6.8296 -1.5657 0.003501* 0.01862 0.0005737* 1.1e-05* 0.003793* 0.526 0.002404* 0.1925 Calcium Chloride Sodium Sulfate Ae. aegypti Ae. aegypti 0.4 0.01 0.05 0.2 0.4 -3.3451 -1.754 -0.23205 -1.0002 -4.3646 0.01551 0.1398 0.2066 0.0001888* 0.000151* Table 9. One- sample t-tests in order to test if the oviposition preference of Ae. aegypti females is significantly different from 0 (i.e., no preference). Alpha was set at 0.0038 to account for multiple comparisons 53 3.3.3 Ae. togoi oviposition preference assays Due to the difficulty in obtaining replicates, only NaCl and KCl assays could be completed for this species. The results of the two-way ANOVA indicate that there is no effect of salt ID on oviposition preference but there was an effect of salt concentration (osmolarity) (Table 10). However, one-sample t-tests showed that Ae. togoi preferred to lay eggs in the freshwater container when the treatment container was 0.4 Osm KCl (Figure 12A, Table 11). For NaCl adults showed no preference between the treatment and control solutions at any concentration tested (Figure 12B, Table 11). Figure 12. The effect of A potassium chloride (KCl) and B sodium chloride (NaCl) on the oviposition preference of adult female Ae. togoi mosquitoes. A value of -1 indicates total preference for the control and a value of 1 indicates total preference for the treatment. Black dots represent each replicate, while the boxplot represents group data. The horizontal line in the boxplot is the median and the whiskers represent the minimum (Q1-1.5 xIQR) and maximum (Q3 + 1.5 xIQR). In a given panel, data labeled with an asterisk (*) indicates response is significantly different from 0 (t-test with Bonferroni correction, alpha is set at 0.016) 54 Factor d.f F p-value Osmolarity 3 8.197 7.25e-05* Salt ID 1 0.775 0.381 Osmolarity x Salt ID 3 1.548 0.208 Table 10. The results of a two-way ANOVA to test the effect of osmolarity (Osm) and salt ID on female adult Ae. togoi oviposition preference. Asterisk (*) denotes significance at alpha = 0.05 Salt Species Concentration (Osm) t p-value Sodium Chloride Ae. togoi 0.1 0.2 -2.779 3.2703 0.01928 0.02219 Potassium Chloride Ae. togoi 0.4 -4.3646 0.007259* Table 11. One- sample t-tests in order to test if the oviposition preference of Ae. togoi females is significantly different from 0 (i.e., no preference). Alpha was set at 0.016 to account for multiple comparisons 55 3.3.4 Comparison of oviposition preference between Ae. togoi and Ae. aegypti A two- way ANOVA (Table 12) was employed to test if there was a difference in oviposition preference between Ae. aegypti and Ae. togoi in KCl and NaCl solutions. The oviposition preference differed between Ae. aegypti and Ae. togoi for NaCl and there was a significant effect of osmolarity on oviposition preference. However, the interaction term is not significant meaning that the effect of osmolarity on OPI did not differ between Ae. aegypti and Ae. togoi. The oviposition preference did not differ between Ae. aegypti and Ae. togoi for KCl but, again, there was a significant effect of osmolarity on oviposition preference. This means that averaged across the two species, oviposition preference is the same at each of the KCl concentrations tested. Figure 13. Comparison of oviposition preference for adult Ae. aegypti and Ae. togoi at each concentration tested for potassium chloride (KCl) and sodium chloride (NaCl). Dots represent each replicate, while the boxplot represents group data. The horizontal line in the boxplot is the median and the whiskers represent the minimum (Q1-1.5 xIQR) and maximum (Q3 + 1.5 xIQR). There was no significant difference in oviposition preference between species (two-way ANOVA followed by a post hoc Tukey test). 56 Salt Variable d.f F p-value Sodium Chloride Species Osmolarity Species:osmolarity 1 3 3 19.943 5.925 1.181 4.11e-05* 0.00143* 0.32543 Potassium Chloride Species Osmolarity Species:osmolarity 1 3 3 0.004 3.338 0.638 0.9532 0.0303* 0.5955 Table 12. Two-way ANOVA to test the effect of species, osmolarity (Osm) and the interaction between species and osmolarity on oviposition preference for KCl and NaCl. Asterisk (*) denotes significance at α = 0.05 57 3.4 Discussion Contrary to predictions, the results of this study indicate that both osmolarity and identity of the ionic salt influence oviposition behaviour of Ae. aegypti and Ae. togoi. Oviposition preference was statistically different between Ae. aegypti and Ae. togoi in the NaCl solutions but not the KCl solutions. 3.4.1 H1: Osmolarity is the primary factor that mosquitoes use to evaluate if a given body of water is suitable for egg laying The results of the two-way ANOVAS (Table 8, 10) indicate that salt ID did not explain overall variation in OPI for either Ae. aegypti or Ae. togoi. However, the goal of the ANOVA was to test whether mean oviposition response was different between salts. One-sample t-tests were able to test whether an oviposition response was different from 0 (i.e., no preference). From the results of these t-tests, it is clear that some salts elicit an aversive oviposition response at lower concentrations than others. In other words, mosquitoes avoid certain salts at lower concentrations than others. These results suggest that adults can distinguish between waters of different ionic compositions. Although osmolarity was found to have a significant effect on oviposition preference, this data goes against the hypothesis that osmolarity is the primary factor that mosquitoes use to evaluate if a given body of water is suitable for egg laying, the identity of the salt is important too. This matches a previous study that investigated oviposition preferences in the eastern tree hole mosquito, Aedes triseriatus (Zaim & Newson, 1979). This study suggested that some other influential factor aside from osmotic pressure was involved in 58 discriminating between various inorganic salt solutions. Similar results have been reported for The London Underground mosquito, Culex molestus (Hudson, 1956). For Ae. aegypti, the solutions that were avoided at the lowest concentrations were salts that contained sodium, NaCl and Na2SO4. This could indicate that sodium is the ion that activates the sensory pathway that is involved in signaling high concentrations of salt. However, Instant Ocean also contains sodium, and this salt did not elicit the same aversive response in Ae. aegypti at lower concentrations. Similarly, sodium did not elicit an aversive response to egg laying for Ae. togoi. However, some previous studies have shown that Ae. togoi only begin showing an aversion to ovipositing in salt water at concentrations above 20g/L (~57% seawater) (Trimble & Wellington, 1979). In this study the concentrations of NaCl tested may not have been high enough to elicit an aversion by Ae. togoi. Ae. togoi responded differently to NaCl and KCl as they avoided ovipositing in the highest concentration of KCl but not the highest concentration of NaCl. It would be interesting to uncover if Ae. togoi avoid MgCl2, Na2SO4 and CaCl2 more than NaCl as this would indicate that they can in fact distinguish between different ions and this would point to the hypothesis that they possess receptors that are specific to specific ions. 3.4.2 H2: Ae. togoi will show a preference for ovipositing in the freshwater solution over the treatment solution at a higher concentration than Ae. aegypti in all ionic salt solutions. The results of a two-way ANOVA (Table 12) indicate that Ae. aegypti and Ae. togoi show no significant difference in oviposition preference in KCl solutions but they do show a difference in oviposition in NaCl solutions. Osmolarity had an effect on oviposition preference in both trials. Because the interaction term (species: osmolarity) was not significant for either KCl 59 or NaCl, this indicated that the rate of oviposition preference does not differ between Ae. aegypti and Ae. togoi. In other words, the effect of osmolarity does not depend on species. However, it is clear that oviposition preference is far more variable in Ae. togoi and Ae. aegypti (Figure 13). This variability could suggest that there is no strong preference for Ae. togoi at these concentrations. This finding potentially indicates that at the concentrations tested, salt is not a huge driver of oviposition aversion for Ae. togoi, as it is for Ae. aegypti. As discussed in the introduction, many taste modalities have been co-opted by mosquitoes for non-feeding behaviors, such as oviposition. It is plausible that various mosquito species have evolved a taste system adjusted to its particular needs depending on its habitat. Because Ae. togoi breed in sites where the salinity is constantly fluctuating and can be extremely high, their chemosensory system may have evolved to not taste salt at lower levels because this level of salt is not lethal to their larvae. Because Ae. togoi do not show a strong aversion to NaCl, it is possible that some factor other than salt is the main driver of oviposition for this species. The type of rock-pools that this species inhabits as larvae presumably have a distinct chemical makeup, composed of various microbiota. Some microbiota may be food items for larvae and thus are attractive to adult mosquitoes, while others may be indigestible and/or toxic and thus should be avoided by the adult (Ranasinghe & Amarasinghe, 2020). In addition to microbiota, many other abiotic and biotic factors such as pH, temperature, presence of con-specifics or presence of predators may be more influential in the decision to lay eggs than salinity for Ae. togoi. 60 3.4.3 Future directions As discussed above, Ae. togoi will oviposit readily in 57% seawater (approximately 0.7 Osm) but oviposition rates decline at concentrations higher than this (Trimble & Wellington, 1979). This is a much higher concentration than what Ae. aegypti have been found to oviposit in. Although the results of this study did not find the concentration of NaCl that causes Ae. togoi to avoid laying eggs, I predict that if higher concentrations of NaCl had been tested, Ae. togoi oviposition in the treatment solution would decline at approximately 0.7 Osm. However, I do not know if Ae. aegypti and Ae. togoi would differ in their response to other salts. In order to answer this question, higher concentrations of all salts must be tested for Ae. togoi. Studies have shown that using individual mosquitoes (as was done in this study) is preferable to using groups when investigating oviposition preference (Okal et al., 2015). However, sample size estimations have illustrated that it may take between 100-200 individual mosquitoes to give bioassays sufficient power to detect a change in preference between two treatments (Okal et al., 2015). Performing more replicates would improve statistical power but performing this many replicates for each concentration of every treatment salt tested may not be possible due to time and space constraints. However, this experiment could be scaled back to test oviposition preference in just NaCl and KCl. This would still help to gain some insight to if and how Ae. aegypti and Ae. togoi can detect various ions and whether they use these ions at high concentrations as a cue to avoid egg laying. In order to uncover the function or phenotypic trait that a particular gene is responsible for, genetic editing involving CRISPR knock-in or knock-out studies are often used. When investigating mosquito genetics, researchers often use genes that have been annotated in the Drosophila genome as a starting off point. The results of this study suggest that when looking for 61 a gene that may encode behaviors related to oviposition, genes that encode taste receptors, rather than osmosensitive receptors may be a good starting point. In addition, the results of this study suggest that salinity is not an important driver of oviposition for Ae. togoi. Chapter 4 is an investigation into the breeding habitat ecology of this species and aims to try to understand what other factors may be important in the oviposition decision for this species. Once other factors that seem to be important to oviposition have been uncovered, laboratory experiments could test the interacting effects of these factors on oviposition. 62 Chapter 4: Breeding habitat ecology of Ae. togoi Chapter 4 objectives The goal of this thesis is to determine how oviposition behavior and larval survival differ between widespread (Aedes aegypti) and restricted (Aedes togoi) mosquito species. As has been discussed earlier in this thesis, there has been much research done on all aspects of the biology of the important vector species, Ae. aegypti but little on Ae. togoi. In order to gain a well-rounded view of Ae. togoi larval survival and oviposition behavior, it was important that I observed them in their natural environment. The goal of this chapter is to characterize the breeding habitat ecology of Ae. togoi in Lighthouse Park in West Vancouver where larvae can be found developing in supra-littoral rock pools. I was interested in uncovering whether, within a microhabitat, some rock pools are more favourable for Ae. togoi than others. I hypothesized that some rock pools would contain more larvae than others and environmental factors such as salinity, temperature, pH and precipitation would be important in predicting larval distributions. Because 100% mortality of larvae was observed at approximately 100-120% seawater in the laboratory, I predicted that salinity of the pool would be a limiting factor for larvae. 4.1 Introduction 4.1.1 Modeled distributions of Ae. togoi Ae. togoi is present in coastal regions of East Asia in environments ranging from subtropical to subarctic (Petrishcheva, 1948a; Sota et al., 2015b; Tanaka et al., 1979). There is also a population of Ae. togoi that inhabits coastal regions in the Pacific Northwest of North 63 America ranging from southern British Columbia, Canada to northern Washington, United Sates (Belton, 1983; Peach, 2018; Peach et al., 2019). Although the range of Ae. togoi is quite well-known in Asia, their range in North America is less understood. However, recent studies that have investigated the potential distribution of this species have hypothesized that Ae. togoi could have arrived in North America by anthropogenic or Beringian dispersal (Peach et al., 2019; Peach & Matthews, 2020; Sota et al., 2015b). Therefore, there is still uncertainty about whether they are a native or invasive species in North America. 4.1.2 Environmental variation affects mosquito abundance The effect of climatic variation on mosquito abundance is species, season and habitat specific (Roiz et al., 2014). Broad scale factors such as temperature, rainfall, tidal regime, humidity and photoperiod can be negatively or positively correlated with mosquito abundance depending on species. One study that investigated distribution patterns of Aedes japonicus japonicus and Aedes togoi used maximum entropy modelling to uncover the most important variables that would determine suitable habitats for these species (Peach et al., 2019). They found that mean diurnal temperature range, mean temperature of the wettest quarter, mean temperature of the coldest quarter, precipitation seasonality and annual precipitation were the most important variables in predicting Ae. togoi distribution. On a broad scale, seasonality and temperature are probably the most important factors that determine Ae. togoi survival and abundance. However, within a microhabitat, it is not known what comprises ideal habitat for Ae. togoi. I was interested in investigating the microhabitat 64 factors that determine larval abundance within a rocky-shore ecosystem. Within a given coastal area, are there certain rock pools that provide better habitat for Ae. togoi than others? Supra-littoral rockpools, where Ae. togoi larvae develop, present a physiologically challenging environment for the organisms that live in them (Satyam & Thiruchitrambalam, 2018). The supra-littoral zone is the area above the high tide line that is not connected to the ocean but may receive salt-water spray (Stephenson & Stephenson, 1949). Even within a microhabitat such as a rocky shoreline, pools will face different stresses depending on their location and size. Pools on the lower shore, close to the ocean, may be washed out periodically during storms whereas pools on the upper shore may be in danger of drying up during hot temperatures. In addition, organisms in smaller pools may face more severe environmental conditions due to the limited water volume, which is less effective in moderating environmental fluctuations. (Martins et al., 2007). The abiotic and biotic factors that affect the abundance of Ae. togoi in these rockpools have not been studied in great detail. Uncovering these factors can aid in predictive modelling of mosquito distributions as it can help us to better understand the relative importance of the parameters that encompass suitable habitat for mosquitoes. Almost everything we know about the biology of Ae. togoi is from laboratory experiments and chapter 2 and 3 have investigated important behaviors and physiology of Ae. togoi under controlled conditions. However, to fully understand the ecology of an organism, you must observe them in their natural environment. Although this species has been shown to survive in solutions of up to 100% seawater in the laboratory, they have been found in natural rock pools of salinities three times that of seawater without any apparent adverse effects (Asakura, 1980a; McGinnis & Brust, 1983; Morritt & Williams, 2000). It is clear that salinity is not the only factor that effects larval 65 survival. One of the goals of this chapter is to investigate 1) if there is a maximum salinity that this species can survive in in their natural habitat and 2) if other environmental factors such as pH, temperature and volume of the pool are important to determining suitable habitat for this species. For example, the distribution of organisms in aquatic habitats can be limited significantly by the pH of the environment. Preserving a stable internal pH is crucial for maintaining homeostasis in aquatic environments and typically, the richness and diversity of invertebrate species in aquatic habitats decrease when pH levels are extremely high or low. (Sutcliffe & Hildrew, 1989). However, larval mosquitoes are capable of tolerating far greater pH ranges than many other aquatic organisms (Clements, 1963). It has been found that both freshwater and brackish water larvae can survive and develop in waters ranging from pH 4 to pH 11 (Clark, 2004). The pH tolerance of Ae. togoi has not been explicitly studied but it is fair to assume that they probably possess the same ability to survive in a wide range of pH values. However, due to the fluctuating nature of their breeding habitat, they presumably must be able to tolerate relatively quick and large changes in pH. One goal of this chapter is to investigate if pH affects larval abundance. Precipitation is another abiotic factor that may be important to larval development. As has been discussed previously, smaller rock pools on the upper shore are at risk of drying out. A large downfall of rain can provide shelter to developing larvae in these rock pools. However, one study found that high rainfall was correlated with low numbers or complete absence of mosquito larvae (Gardner et al., 2012). They suggested that high precipitation flushed larvae out of breeding habitats. Their study supported the hypothesis that while moderate rainfall is important to mosquitoes as it provides oviposition and larval habitats, too much precipitation is detrimental to mosquito populations. 66 4.2 Methods 4.2.1 Study site All field work for this project took place in Lighthouse Park in the city of West Vancouver (49.3316° N, 123.2636° W) (Figure 14). To investigate the factors that affect larval survival a variety of abiotic and biotic factors were investigated over the course of a year (April 2021- April 2022). Sixteen rock pools in the southwest region of the park were chosen as sample sites (Figure 15). These rockpools represented various potential breeding habitats for Ae. togoi as they varied in size, volume, salinity, temperature, and distance from the sea. All rock pools were visited once a week for one year and the salinity, pH, temperature, approximate volume, and larval abundance was measured during each visit. Figure 14. Map of the Vancouver area, British Columbia with study site (Lighthouse Park) indicated by red triangle 67 Figure 15A. Zoomed in map of study site with locations of individual rockpools marked. B. The gradient colours indicate the number of larvae collected in each rockpool over the year study. B A 68 4.2.2 Measuring environmental variables The temperature and salinity of the individual rock pools were measured using a Fisherbrand™ salinity meter pen (catalog #15078202). pH was measured using a Fisherbrand™ pH pen (catalog # S35927). The technique for measuring volume was adapted from a protocol by Brenha-Nunes et. al (Brenha-Nunes et al., 2016). The total area of each rock pool was divided into smaller shapes (i.e., square, rectangle, triangle) and the area of these shapes was measured using a Mileseey brand laser measuring device. Two to three depth measurements were taken for each shape using a 2m fold up ruler and an average depth was calculated. The volume of each shape was calculated, and these volumes were summed to get an approximate volume for the rock pool. Because the volume of the rock pools was extremely variable, volume was re-calculated each week. Depths were taken from the same point each week to ensure that how the volume was changing week to week was being accurately measured. Historic weather data such as temperature and precipitation were obtained from Environment and Climate Change Canada - Meteorological Service of Canada (ECCC-MSC) at the Vancouver Harbour CS weather station (CWHC). The total precipitation in the last week, 2 weeks and 3 weeks was calculated and made into new variables. Similarly, the temperature from the previous week, 2 weeks and 3 weeks was summed to create historic temperature variables. Finally, a mosquito dipper (volume 300ml) was used to measure relative larval abundance. All immature forms of Ae. togoi including larvae and pupae were counted in this measurement but throughout this thesis this measurement is referred to as larval abundance. The pool was visually inspected to see where the largest density of larvae was, and this is where the measurement was taken. A total of 3 dips were taken, with larvae replaced each dip and the average larvae per dip was calculated. 69 4.2.3 Statistical analysis All statistical analyses were performed using R (Version 4.2.1). First, a standardised principal component analysis (PCA) was used to reduce the dimensionality of the dataset into a smaller number of variables that account for the highest variation across the dataset. The relationship between larval abundance and these principal components (which represent the environmental variables) was investigated using a generalized linear mixed effects model (GLMM). This statistical method has been used in other studies to investigate the relationship between mosquito abundance and climatic variables (Bisanzio et al., 2011; Evans et al., 2019; Roiz et al., 2015) The response variable (average larvae) was not normally distributed and was over dispersed (the variance is greater than the mean). Transforming the data did not overcome the overdispersion and so a negative binomial distribution was used (Stoklosa et al., 2022). GLMM models are capable of incorporating random effects and they handle non-normal data (Bolker et al., 2009). Random effects can be used to avoid pseudoreplication from repeated measures, for example sampling from the same location each week. I incorporated Rockpool ID as a random effect in this model to account for the fact that I took repeated measurements from the same pools. The fixed effects are the first five principal components and their interactions, and the response variable is dip average, which represents the average number of larvae caught in a given pool on a given day. The following code was used to perform the GLMM: 70 mod1 <- glmer.nb(dip_average ~ PC1+PC2+PC3+PC4+PC5+ PC1:PC2 + PC1:PC3 + PC1:PC4 + PC1:PC5 + PC2:PC3 + PC2:PC4 + PC2:PC5+ PC3:PC4 + PC3:PC5 + PC4:PC5 +(1|rockpool), data = mm_data, control = glmerControl(optimizer = "bobyqa")) Then, to understand how the predictor variables and larval abundance are associated over time, weekly values for dip average were superimposed on the weekly values of each principal component that the GLMM deemed significant. This was done to see how larval abundance was coupled and uncoupled with predictor variables throughout the year. In order to investigate inter-rockpool variation, the average value of each environmental variable as well as the mean number of larvae caught across all weeks was calculated by rock pool. As there was a top and bottom measurement for some of the environmental variables (salinity, temperature and pH), the mean of the top and bottom measurements was first calculated. 71 4.3 Results The highest abundance of Ae. togoi larvae were recorded in the summer months with the maximum number of larvae seen in August (Figure 16). Very few larvae were recorded in the winter months (November- February) but diapausing 4th instar larvae were collected on occasion. There were differences in the number of larvae caught between rock pools with “Big red”, “Seagull” and “Seaweed” pools consistently containing the most larvae (Figure 17). The pools that were vertically closest to the ocean, (i.e., lowest on the shore) “Barnacle” and “Little red”, never contained larvae. Figure 16. Monthly abundance and seasonality of Ae. togoi larvae recorded over 16 rockpools in Lighthouse Park from April 2021- April 2022. 72 Figure 17. Monthly abundance and seasonality of Ae. togoi larvae in each rockpool sampled from April 2021- April 2022. 4.3.1 Principal component analysis Some of the environmental variables such as temperature at the top of the pool, temperature at the bottom of the pool, air temperature and historical temperature were highly correlated (see Appendix Figure A.3). To reduce the dimensionality of the dataset and create new variables that maximize variance, a principal component analysis was employed. A scree plot showed that 87.8% of variation in the dataset was explained by the first five principal components and so these were retained for further analysis (Figure 18). The loadings for each principal component are shown in Table 12. PC1 was primarily loaded by the temperature variables (temperature of the pools, daily temperature and the previous week’s temperature). PC2 73 mostly reflects pH of the pools, PC3 mostly reflects salinity of the pools, PC4 is mostly driven by precipitation and PC5 is primarily loaded by volume of the pool. PC1 and PC2 cumulatively explained the most variation across the dataset (55.3%.). Figure 19 shows the relationship between PC1 and PC2 and how they change over time. PC1 was loaded negatively by the temperature variables and so positive values on the x-axis indicate lower temperatures and negative values represent higher temperatures. This is reflected by the clustering of the colours in Figure 19. Points coloured red represent warmer months and points coloured blue represent colder months. The clustering of colours on the x-axis indicates that the aggregate values for PC1 change over time. However, we do not see this clustering on the y-axis and so the aggregate values for PC2 are not necessarily associated with a particular month or season. Figure 18. Scree plot showing how much variation each principal component captures from the dataset 74 PC1 PC2 PC3 PC4 PC5 Air temperature -0.43177 0.09285 -0.02549 0.091158 -0.05432 Temperature top of pool -0.41844 0.032306 0.052681 0.16518 0.072591 Temperature bottom of pool -0.41929 0.033263 0.042058 0.159147 0.070606 pH top of pool -0.0361 -0.57576 -0.25683 0.32469 -0.0005 pH bottom of pool -0.0254 -0.60153 -0.21436 0.272927 0.095248 Salinity top of pool -0.04534 -0.29418 0.61291 -0.04931 -0.21397 Salinity bottom of pool 0.005482 -0.22534 0.651786 0.064977 -0.13423 Volume of pool 0.092427 0.109077 0.280077 0.273067 0.888516 Daily precipitation 0.158561 0.260917 0.013801 0.633506 -0.25384 Daily temperature sum -0.44157 0.105678 -0.00108 0.095226 -0.05536 Previous week precipitation 0.207851 0.245607 0.061043 0.517251 -0.2368 Previous week temperature -0.43217 0.084331 0.007102 -0.00027 -0.02977 Table 13. Heatmap indicating the relative loadings of each principal component. Positive loadings indicate that a variable and a principal component are positively correlated and are coloured red while negative loadings indicate that a variable and a principal component are negatively correlated and are coloured blue. 75 Figure 19. Relationship between PC1 and PC2. PC scores are coloured by month to show how the PC values change over time. 4.3.2 Negative Binomial generalized linear mixed effects model The results of the GLMM are reported in Table 14. The p-value of each variable indicates how well each predictor variable can predict the value of the response variable. PC1 (which is mainly loaded by temperature), PC3 (which is mainly loaded by salinity) and PC4 (which is mainly loaded by precipitation) are all good predictors of larval abundance. Interestingly, there are some important interactions too. A significant interaction term indicates that the effect of one principal component on the response variable changes according to the value of another principal component. Interactions between PC1:PC2, PC1:PC3, PC1:PC4 and PC2:PC3 are also predictors of larval abundance. 76 Table 14. Results from the generalized linear mixed effects model (GLMM) associating Ae. togoi larval abundance with principal components and their interactions. The p-values of PCs and PC interactions deemed significant are bolded (α<0.05). 77 4.3.3 Correlation between larval abundance and PC1, PC3 and PC4 Figure 20A-C shows regression plots of larval abundance (dip average) and the principal components that the GLMM model found to be significant. The GLMM was used to generate predicted values for larval abundance and these values were used to create the regression line. The points in the plot represent the real data. As expected, PC1 is negatively correlated with larval abundance, meaning that the highest numbers of larvae are predicted during high temperatures (Figure 20A). In general, PC3 is not highly correlated with larval abundance, this relationship may be over-estimated because of one extreme outlier (Figure 20B). Nevertheless, when this outlier was removed from the data and the GLMM was rerun, PC3 was still found to be a significant predictor of larval abundance. There is a very weak relationship between PC4 and larval abundance (Figure 20C). Because this dataset contained so many 0 values for larval abundance, it is difficult to visualize a clear correlative relationship between larval abundance and PC3 and PC4 when the entire yearly dataset is analyzed. 78 Figure 20. Correlation between dip average and A. PC1, B. PC3, C.PC4. The dots represent the real data and the line is a fitted generalised linear regression from the negative binomial model with standard error shown. 79 4.3.4 Variation of principal components through the year Figure 21A-C shows weekly values for dip average superimposed on the weekly values of each principal component that the GLMM deemed significant. Figure 21 D-F shows how the relationship between larval abundance and principal component changes through time. These plots show that each principal component is a good indicator of larval abundance during the summer months (defined here as April-September) but not during the winter months (October-March). In these plots, time does not flow from left to right, the arrows indicate the direction of time. In Figure 21D, high larval abundance is associated with low values for PC1, and low larval abundance is associated with high values of PC1. In Figure 21E and 21F, larval abundance is associated with PC3 and PC4 during the summer months but there is no obvious relationship between larval abundance and the PCs during the winter months. This indicates that the principal components 3 and 4 are good predictors of larval abundance only in the summer months. 80 Figure 21. Variability in larval abundance in the study area superimposed on changes in PC 1, 3 and 4 (A-C). Connected scatterplots showing how the relationship between larval abundance and principal component changes through time (D-F). Numbers represent months and color represents season. 81 4.3.5 Reservoir pools during extreme weather events During the summer of 2021, Vancouver experienced an extreme weather event now known as the Pacific Northwest heat dome (Emerton et al., 2022; White et al., 2023). During the heat dome which took place between June 25th-July 1st 2021, temperatures in Canada were up to 20°C higher than usual (Government of Canada, 2022). As this was such an unprecedented event, I wanted to investigate the effect of this extreme weather event on Ae. togoi larval abundance in Lighthouse Park. Figure 22 shows one rock pool, “Big red”, before, during and after the heat dome. These pictures demonstrate the variation in one breeding habitat for Ae. togoi over the course of one year. Figure 23 shows larval abundance (A), temperature of the pool (B), previous weeks precipitation values (C) and salinity of the pool (D) during the summer months when the heat dome took place. Before the heat dome, Big red had the highest number of larvae followed by Seaweed pool. However, during the heat dome, both pools dried up completely and so all larvae that were present died. In contrast to this, Log pool never had very high numbers of larvae pre-heat dome but after the first rain event following weeks of no precipitation, it had the highest level of larvae present. Only one pool, Seagull, never dried up completely and consistently contained larvae. Missing data on these plots indicates that a pool dried up completely. 82 Figure 22. “Big red” rock pool on; A. April 13th 2021, B. July 6th 2021, C. July 21st 2021, D. November 9th 2021, E. December 21st 2021. A B C D E 83 Figure 23. Plots showing A larval abundance, B temperature of the pool, C previous weeks precipitation values and D salinity of the pool from June 2021- September 2021. Extreme heat event (Vancouver heatwave) is indicated by the black dotted line. Missing data indicates that the rock pool dried up. 4.3.6 Inter-rockpool variation Figure 24 is a summary of the mean value for each environmental variable as well as the mean number of larvae caught across all weeks per rock pool. Qualitatively, the pools that contained the most larvae per week did not appear to differ in their environmental parameters (salinity, pH, temperature, volume) from the pools that contained the least number of larvae. 84 Rockpool Salinity (ppt) Temperature (°C) pH Volume (L) Mean larvae Barnacle 19.08 15.38 8.07 64.1 0 Little red 18.65 15.165 8.59 48.38 0 Foot 12.01 13.63 8.74 3.69 0.26 Milo 1.95 13.15 8.15 40.25 0.36 Big rock 11.36 12.94 8.03 142.66 1.18 Shrub 0.46 14.21 8.9 26.57 1.28 Highrise 1.79 13.24 9.1 6.37 1.5 Polychaete 7.38 13.65 8.7 2.22 1.5 Ledge 15.32 12.84 8.45 7.12 2.02 Sailboat 1.71 13.89 7.95 117 3.72 Grass 4.19 12.37 7.69 66.22 5.64 Spiderweb 5.66 13.98 8.51 48.94 5.75 Log 5.56 14.23 7.43 80.55 6.47 Seagull 20.05 15.64 8.45 131.92 6.54 Seaweed 18.60 14.46 8.73 133.78 9.1 Big red 13.91 13.94 8.53 315.49 11.71 Figure 24. Mean value of each environmental variable and mean larvae caught across all weeks for each rock pool 85 4.4 Discussion A key take away from this study is that Ae. togoi can thrive in highly variable environments. They were found in pools where the salinity ranged from 0-85ppt (~2.5x seawater), the temperature ranged from 0-34°C and the pH was extremely basic at times (10.8). These extremes in environmental variables seemed to have no obvious adverse effects on the larval population. The only factor that limited larval abundance was seasonality and loss of habitat (due to pools drying out in extreme heat). Fourth instar diapausing larvae were found alive during winter in rockpools where sheets of ice had formed over the top. In the summer, larvae could cope with water temperatures were as high as 34°C. In addition to the ability of larvae to survive in extreme conditions, it is important to consider the role of oviposition in larval distribution. In this study, fourteen of the sixteen pools contained larvae at some point. For the two pools that never contained larvae, it is not clear if adults did in fact lay eggs in these pools, but the conditions were not suitable for hatching and larval development or if adults used oviposition cues to avoid these pools. Speculations about why these pools never contained larvae are discussed later in the discussion. 4.4.1 Variation in principal components through the year The results of the GLMM show that PC1, PC3 and PC4 are predictors of larval abundance but how closely correlated these principal components are to larval abundance changes throughout the year and depends on the value of the other principal components. Figure 21A-C shows how dip average and the principal components become coupled and uncoupled at different points in the year. PC1 is correlated with larval abundance throughout the year. In the 86 summer months, low values of PC1 (high temperature) are associated with high larval abundance and high values of PC1 (low temperatures) are associated with low larval abundance. PC3 does not seem to be as tightly associated with larval abundance as PC1 (Figure 21B). High values of PC3 indicate high salinities and the highest values of PC3 are seen in the winter months. This is probably because, during winter there were more storms, and this could cause more salt-water spray to enter the rockpools. In addition, sea surface salinity is also highest in the winter months. Sea surface salinity drops in June during the Fraser River freshet when a huge influx of snow and ice melt flows into rivers in British Columbia (Yin et al., 1997). PC4 appears to be closely coupled with larval abundance in the summer months (Figure 21C). Even though the highest values of PC4 are seen during the winter months (as there is always more precipitation in the winter), during summer, spikes in PC4 are followed by spikes in larval abundance. The highest spike in larval abundance occurs at the end of July. After a period of low precipitation (low PC4 value), the first rainfall was followed by a huge increase in larvae. Then, a drop in PC4 in August is followed by a drop in larval abundance. This pattern continues until the beginning of October. After this, the value of PC4 doesn’t affect larval abundance anymore because temperatures have dropped, and eggs and 4th instar larvae are in diapause. When mosquito eggs are covered in water, many interacting factors can trigger hatching and studies have shown that a decline is oxygen level is one of these triggers (Becker et al., 2010). Dissolved oxygen begins to decline in water bodies when they become stagnant due to bacterial degradation. Therefore, it is possible that the spikes in precipitation during the study period induced hatching of eggs which lead to high levels of larval abundance. These results are partially consistent with another study that found, on a broad geographic scale, temperature and precipitation to be important in determining suitable habitat for Ae. togoi 87 (Peach et al., 2019). Other studies have found that while some saline water species such as Ae. albopictus, Cx. iridescens, and Cx. dolosus can tolerate high salinities, larval abundance is not necessarily correlated with high salinity (Multini et al., 2021). I suspect that the reason we see a correlation between high salinities and high numbers of larvae in the GLMM is simply that there was a spike in salinity of the rock pools during the heat dome at the peak of summer when larvae are generally most abundant. In addition, as pools dry up and get smaller, it is easier to collect more larvae in one dip. One limitation of this type of analysis is, because larvae were absent from rockpools for a large portion of this study and variables such as salinity continued to fluctuate greatly during these periods, it is difficult for a model to correlate larval abundance with such variables. However, I decided not to split the data into different seasons for analysis because the overall goal of this study was to investigate the factors that affect Ae. togoi larval abundance throughout the course of a whole year. In addition, it is important to recognise that because interactions between principal components were found to be significant, it is not possible to full examine the effect of a single principal component. A principal component such as salinity may only be important in predicting larval abundance when combined with a certain temperature or visa-versa. 4.4.2 Interactions between abiotic factors Another key finding from this study is that interacting ecological factors are important to predicting larval assemblages. Results from the GLMM show that interactions between PC1:PC2, PC1:PC3, PC1:PC4 and PC2:PC3 were significant predictors of larval abundance. 88 Other studies have investigated the interaction between temperature and precipitation (PC1:PC4) and how this interaction affects mosquito populations. A study by Alto and Juliano exposed Ae. albopictus mosquitos to different precipitation and temperature treatments and found that the highest number of adult mosquitoes emerged when temperatures were high, but breeding sites didn’t dry out completely (Alto and Juliano, 2001). However, combining higher temperatures with drying had a negative impact on adult emergence. This study suggested that more adults emerge in in warmer regions than cooler regions, as long as the breeding site does not dry up completely. This pattern was seen in this study too. The highest number of larvae were seen during warm temperatures, but when high temperatures were combined with 0 precipitation, this led to a huge decline in larval abundance. The instances of highest larval abundance occurred during warm temperatures, right after a large precipitation event (Figure 21C). Several studies have investigated the interacting effects of environmental stressors on mosquito larvae, however, many of these studies only investigated freshwater mosquitoes (Clark, Flis and Remold, 2004; Multini et al., 2021; Boerlijst et al., 2023). The way that mosquitoes respond to multiple environmental factors depends on life stage and sex of the mosquito (Silberbush et al., 2014; Alcalay et al., 2018). Often the effect of one environmental variable can be intensified when combined with another. For example, mosquito larvae may be more or less able to deal with osmotic stress at different temperatures. 89 4.4.3 Other factors that could influence larval abundance In addition to the abiotic factors that were recorded (pH, salinity, temperature, volume), biotic factors such as presence of conspecifics and predators may also determine suitable development habitat. It has been found that Ae. aegypti, Ae. albopictus, and Culex quinquefasciatus adults prefer to oviposit in bodies of water that contain conspecific larvae and pupae as this can be an indicator that a pool is suitable for larval development (Faierstein et al., 2019). Although large numbers of conspecifics can lead to competition for food, generally conspecific larvae are attractive in densities up to ~ 1 larva/mL (Benzon & Apperson, 1988; Zahiri & Rau, 1998). Even if pools contain a large number of potential predators, if there are conspecifics present, adults will still be attracted to the site (Wong et al., 2011). The effect of predators on ovipositional behavior of mosquitoes is highly variable depending on life history and risk of predation. Generally, mosquitoes avoid ovipositing in pools containing fish and insect predators. However, it has been found that oviposition avoidance in response to predators is weak for mosquitoes of the genus Aedes that oviposit in freshwater containers (Vonesh & Blaustein, 2010). Because Ae. togoi are an unusual Aedes species in that they are not container breeders and may encounter many different types of predators in their breeding habitat, they may be deterred from ovipositing in certain rock pools that hold an abundance of predators. However, the effect of predation on the oviposition behavior of Ae. togoi has not been investigated. For example, pools that were closest to the ocean (Barnacle and Little Red), that never contained Ae. togoi larvae, often contained a higher abundance of marine species such as sculpins (personal observation). Tide pool sculpins (Cottidae) are known to feed on small invertebrates, isopods, amphipods, shrimp and worms. One study of the diet of two species of Cottidae on the west coast of Vancouver Island found that chironomid larvae (non-90 biting midges) were a component of both sculpin species diets (Nakamura, 1971). Chironomids are closely related to mosquitoes and so it is plausible that Ae. togoi larvae may be predated upon by sculpins. Perhaps the presence of fish or other organisms is a deterrent for ovipositing adult females. However, another reason larvae were not observed in these two pools may also be due to the fact that they periodically get flushed out during the high tide. Future directions for this work could include conducting a survey of potential predators in the rock pools at Lighthouse Park. Oviposition preference assays could be performed in laboratory conditions to test if Ae. togoi avoid ovipositing in water that has held predators (such as sculpins) versus plain dechlorinated water. The microbial composition of the rock pools could also play a part in determining Ae. togoi abundance. Mosquito larvae generally feed on organic matter from the environment, such as plant and animal debris as well as microorganisms such as algae, protozoa, and bacteria (Merritt et al., 2003). In the laboratory, larvae were fed on ground fish food. Presumably, the composition of food available in rock pools in the field is different and more varied than what they were fed in the laboratory. Perhaps the nutritional content of their diet affected larval survival. The most prevalent microbiota in mosquito larval diets is bacteria, which frequently serves as the primary source of nutrition for larval growth and development (Ranasinghe & Amarasinghe, 2020). The microbial communities that mosquitoes feed on as larvae have been found to be important not only to larval growth, but also adult fitness (Strand, 2018). These microbiota have important roles in immunity, digestion of food and fecundity at the adult stage (Strand, 2018). One study has found that Ae. aegypti larvae are unable to complete development in water devoid of bacteria, suggesting that bacteria are extremely important for the growth and 91 development of mosquito larvae. (Rozeboom, 1935). Therefore, chemical composition of the rockpools could also have influenced Ae. togoi larval abundance. 4.4.4 Effect of extreme weather event on larvae and inter-rockpool variation The heat dome of 2021 presented an unprecedented challenge for marine organisms in Canada, especially those inhabiting rocky intertidal shores. It has been estimated that over one billion marine invertebrates died across the coastline of the Salish Sea (White et al., 2023). This presented an opportunity to study the impact of an extreme weather event on the larval population of Ae. togoi. In the first week of sampling during the heatwave (June 30th 2021), seven of the sixteen rockpools had dried out completely. Pools continued to dry out over the coming weeks and by July 29th 2021, only three pools remained, Seagull, Barnacle and Little red. Of these pools, Seagull was the furthest from the ocean and did not receive regular splash from the high tide. Amazingly, larvae were found alive in this pool on July 29th 2021, when nearly all other rock pools had dried up and become unavailable for larval development. This further demonstrates that, as long as, a pool is prevented from drying out completely, Ae. togoi larvae may survive. This study also demonstrated the remarkable ability of the Ae. togoi population to bounce back after an extreme event. Immediately after the first rainfall in August following the heatwave, almost all pools that has previously held larvae were recolonized in the succeeding weeks. However, there were differences in how well individual pools recovered. For example, before the heat wave, Big red and Seaweed pools consistently contained the most larvae but following the heatwave, Log and Seagull pool had the largest spike in larval abundance, with 92 Seaweed containing larvae constantly through the heat wave period. I hypothesized that, perhaps Seagull pool is a population reservoir for when conditions become unfavourable and then when conditions improve, adults can emerge from this reservoir pool and recolonize other pools. However, it is also possible that adult mosquitos persisted during this time and a larval reservoir was not necessary to sustain the population. For example, it has been found that Anopheles coluzzii, a vector of malaria in Africa, can persist during the dry season in the Sahel through a type of adult dormancy (Faiman et al., 2022). It is not known whether adult Ae. togoi can survive in such extreme temperatures as was recorded during the heat dome but it is a possibility. In addition it is not known whether the resulting hatching of larvae after this precipitation event was from existing eggs that were laid before the rainfall or whether new eggs had been laid by surviving adults after the rainfall. Due to the lack of data on the breeding habitat ecology of Ae. togoi in natural settings, the goal of this chapter was to begin to characterize the habitat of the Vancouver population and to provide some insight to pool-to-pool variation in larval abundance. Climate change can affect mosquito populations in many ways, particularly by altering and expanding their range (Liu-Helmersson et al., 2019). Although Ae. togoi are not an important vector of disease in North America, they do pose a threat in East Asia by transmission of filariasis (Dedkhad et al., 2018). Several studies have indicated that global climate change could increase the transmission of mosquito vector-borne diseases such as malaria, lymphatic filariasis, and dengue globally (Githeko et al., 2000; Rocklöv & Dubrow, 2020). One important consequence of global climate change is the salinization of freshwater and the expansion of brackish water bodies in coastal zones (Ramasamy & Surendran, 2012). This, in turn, can increase the density of saline-tolerant mosquitoes, such as Ae. togoi. By understanding the factors that create an ideal habitat for certain 93 species, we can predict potential range expansions. The results of this study could aid in producing fine grained species distribution models for Ae. togoi in coastal areas. 4.4.5 Future directions Although this study could not report exactly what makes some rock pools more suitable for larvae than others, it is an important step in characterising the breeding habitat ecology of this species. A full topographical and physiochemical analysis is needed to determine what, if anything, makes Seagull pool (the reservoir pool) special. Although there were differences in the measured environmental parameters of the pools (Table 13), there were not significant patterns of particular pools housing more larvae with respect to these parameters. For example, there was no significant difference in salinity, pH or temperature between a pool that never held larvae (Barnacle) and a pool that consistently contained large numbers of larvae (Seaweed) (Figure 24). Including parameters that were not investigated in this study (such as distance from the high tide line, elevation, chemical water analysis, shade from the sun and leaf litter) could aid in identifying these reservoir pools for Ae. togoi. A chemical and microbial analysis of the water from different rock pools at Lighthouse Park may shed some light on what and/or how much bacteria are important for Ae. togoi larval survival. It would be interesting to see if different rockpools contained different communities of bacteria and if one particular community was associated with high larval abundance. This could explain why certain rockpools seemed to be more favourable for larvae. In addition, performing experiments to test the effect of interacting ecological factors on Ae. togoi larval survival and oviposition will aid in identifying the ideal habitat for Ae. togoi 94 populations to thrive and potentially begin to answer the question of why Ae. togoi are restricted to coastal areas. The oviposition experiments described in chapter 3 could be expanded to include testing the effect of predators or conspecifics on Ae. togoi oviposition preference. Similarly the larval survival studies described in chapter 2 could be expanded to include parameters such as temperature and pH in addition to salinity. 95 Chapter 5: General conclusions and future directions The focus of this thesis was to investigate how larval salinity tolerance and oviposition behaviors differ between Ae. aegypti and Ae. togoi, with the overall goal of trying to gain some insight into why some species of mosquito become invasive and widespread while other remain restricted in their distribution. Through the results of chapter 2 and 3 we have gained some valuable insight into how physiology and behaviors differ between these two species and chapter 4 is an important step in characterizing the breeding habitat ecology of a previously understudied mosquito. 5.1 Larval survival studies The first major finding from chapter 2 is that mosquito larval survival depends on the salt concentration of the media they are raised in but also the identity of the ions present. Larval survival of both Ae. aegypti and Ae. togoi was higher in certain ionic salts than others, even when they were the same osmolarity. This suggests that general osmotic pressure is not the only factor that leads to larval death, the identity of the ions present also has an effect. These results may indicate that mosquito larvae cope with different ions using various ion-specific mechanisms. There has been much work done on the mechanisms of Na+ and Cl- regulation in Ae. aegypti and it has been hypothesized that uptake of these ions is independent (Donini et al., 2007; Patrick et al., 2002). However, very few studies have investigated how mosquito larvae uptake and excrete other types of ions that they may encounter in aquatic environments. This is where a species comparison becomes useful. By conducting these larval survival studies on Ae. aegypti and Ae. togoi we can see if they posses the same ability to survive in various water types or if their 96 osmoregulatory systems have been changed due to their expansion into different habitats. The results of this study suggest that these species do differ in how they uptake and excrete various ions. Ae. togoi may be generalists when it comes to NaCl concentration but specialists when it comes to what types of ions they can survive in. On the other hand, Ae. aegypti may be generalists for many different types of ions up to a certain threshold. Ae. togoi may posses excretory mechanisms that Ae. aegypti do not, or they may be able to upregulate certain genes that increase excretion of Na+ and Cl- during times of osmotic stress. Future physiological studies as outlined in chapter 2 will directly test this. Although the salinity of rock-pools that Ae. togoi larvae inhabit can fluctuate dramatically, the main salts present are always sodium and chloride, just in varying concentrations. In contrast, due to their strong association with human settlement, the breeding habitats for Ae. aegypti can vary from tires to plastic buckets to septic tanks (Durant & Donini, 2019; Getachew et al., 2015). Ae. aegypti have had to evolve to survive in a wide range of breeding habitats and thus deal with the chemical make up of these individual sites. In addition, the salinity of these sites will dilute during times of random rainfall. Therefore, it makes sense that Ae. aegypti must be able to survive in a wide range of water types but not necessarily a wide range of salt concentrations. This may be part of the reason why Ae. aegypti have been able to spread globally. 5.2 Oviposition preference assays The results of chapter 3 goes against the hypothesis that osmolarity is the primary factor that mosquitoes use to evaluate if a given body of water is suitable for egg laying. Instead, it is 97 possible that the sensory pathways that signal an aversive response for the mosquito may be triggered by specific ions. Because Ae. aegypti showed the most aversive oviposition response to ionic compounds that contained sodium, I hypothesized that perhaps sodium is what signals high salt and that a breeding site should be avoided. This information may be useful when it comes to trying to uncover the genes that encode aversion to high salt. By looking at sodium dependent taste receptors in Drosophila melanogaster, we may be able to compile candidate genes to investigate the genes that signal and aversive oviposition response in mosquitoes. When oviposition preference was compared between Ae. aegypti and Ae. togoi it is clear, at least for NaCl, that Ae. togoi will readily oviposit in concentrations much higher than that of Ae. aegypti. There are two potential mechanisms for why Ae. togoi do not avoid ovipositing in salty water. The first is a behavioral mechanism. It is possible that the chemosensory system can detect Na+ and Cl- ions in the water at breeding sites, but they choose to lay eggs anyway because the level of salt present is not lethal to larvae. On the other hand, it is possible that the sequence or expression of salt receptors in their chemosensory systems differs dramatically from Ae. aegypti. If Ae. togoi have different receptors to Ae. aegypti, they may not be able to taste salt at low levels. There is precedence for the idea that different mosquito species can express different types or levels of chemosensory receptors depending on their life history (Ignell et al., 2022). This is seen in mosquitoes with different host preferences. Volatile cues from potential hosts are detected by the mosquito’s olfactory system and neurons expressing receptors recognise these volatile organic compounds (VOCs) (Zhao et al., 2022). It has been shown that the evolution of host preference can cause structural changes in sensory tissues as well as changes in the expression level of genes involved in chemosensation (Ignell et al., 2022). It is plausible that 98 because Ae. togoi breed in salt-water rock pools, the receptors of their chemosensory system have evolved to not taste low levels of salt as avoiding these bodies of salt water won’t increase their fitness. Once a genome for Ae. togoi becomes available future experiments will be able to uncover differences in the chemosensory system on a genetic level. 5.3 Breeding habitat ecology of Ae. togoi Finally, the results of chapter 4 have provided some insight into the factors that determine larval abundance of Ae. togoi in their natural environment. Throughout the course of one year, the breeding habitat of this species experienced major extremes in environmental fluctuations including an unprecedented heat wave. However, the larvae were able to survive high water temperatures, extremes in salinity and a period of no precipitation in which most of their breeding habitat evaporated. The presence of one “reservoir” rock pool may have provided habitat to sustain the population until the next rainfall. This population also exhibited the ability to bounce back after such an extreme event and recolonize rock pools that had been previously dried up. In chapters 2 and 3, I investigated the role of salinity in larval survival and oviposition behavior of Ae. togoi under controlled laboratory conditions. However, the results of this field work have shown that a multitude of interacting factors are important predictors of larval abundance. Perhaps the reason we do not see survival rates in very high salinities in laboratory conditions is because larval survival is affected, not only by one factor such as salinity, but by many interacting factors. The ability of larvae in natural rockpools to withstand salinities in excess of seawater may be modulated by temperature, pH or precipitation. 99 In reality, there are countless factors that can affect larval survival and abundance. Firstly, populations of mosquitoes are often determined by the availability of potential hosts (Takken & Verhulst, 2013). At this time, the host preference of Ae. togoi in the American Pacific Northwest is not known. They have been reported to feed on humans, cattle and birds (McGinnis, 1982). However, in an area such as Lighthouse Park, humans are probably not the main source of a blood meal. It is possible that their main source of blood comes from seabirds such as loons, grebes, alcids and gulls. If this is the case, their restriction to coastal areas may be due to their host preference. Furthermore, by occupying such a highly fluctuating and harsh habitat, Ae. togoi larvae may potentially avoid competition for space and resources from other mosquitoes. In addition to host availability, breeding habitat availability can also determine mosquito distribution (Rose et al., 2020). For example, it has recently been hypothesised that the speciation of the “domestic” form of Ae. aegypti, Ae. aegypti aegypti, first arose in response to the hot dry seasons experienced by this species in the West African Sahel (Rose et al., 2023). At this time, water that was stored by humans became a breeding habitat for Ae. aegypti in the Sahel where their previous breeding habitat (tree holes) had become less abundant. This in turn drove the host preference of Ae. aegypti from non-human animals to humans (Powell & Tabachnick, 2013). In a similar way, it is possible that Ae. togoi are restricted to coastal areas because the rock pools that they develop in contain something intrinsic to larval survival and thus adult fitness. This study did not determine the factor that made some rock-pools more suitable for Ae. togoi larvae than others but there are many potential factors that could be important that were not tested. For example, the chemical composition of breeding site rock pools may contain microbiota that is necessary for larval growth and development (Ranasinghe and Amarasinghe, 2020). In addition, 100 the reason we do not see survivability in 300% seawater in the laboratory may also be due to chronic stress conditions. In larval survival experiments, 1st instar larvae are placed in the treatment solution and remain there for the duration of development. In the field, due to the highly fluctuating nature of coastal rock pools, larvae may be subject to acute stress, but the salinities can decrease and increase on daily scales. It is possible that larvae can only deal with these extremes in salinities on a short timescale and this is why we see them alive in the field in these conditions but not in the laboratory. Overall, this study has shed some light on how a widespread (Ae. aegypti) and a restricted (Ae. togoi) mosquito species cope with salt and how this may impact their distribution. This study has also begun to characterise the breeding habitat ecology of Ae. togoi, one of the 5% of mosquito species that can survive and develop in brackish water. Mosquitoes are extremely important organisms to study because mosquito-borne disease causes hundreds of thousands of human deaths each year (CDC, 2022; Webb, 2008). Although Ae. togoi are currently not known to carry disease in North America, they are carriers of diseases such as Japanese encephalitis in East Asia. Warmer temperatures due to climate change can increase the geographic spread of mosquitoes and increased precipitation can create more breeding habitats (Rocklöv & Dubrow, 2020). Investigating factors that can contribute to mosquito distribution (such as breeding habitat) can help us to track their spread and predict how populations will bounce back after extreme weather events. Understanding vector mosquito physiology, behavior and distribution is vital to develop effective control methods and slow the spread of these vectors. 101 Bibliography Afify, A., & Galizia, C. G. (2015). Chemosensory Cues for Mosquito Oviposition Site Selection. Journal of Medical Entomology, 52(2), 120–130. https://doi.org/10.1093/jme/tju024 Anoopkumar, A., Puthur, S., Varghese, P., Rebello, S., & Aneesh, E. (2017). Life cycle, bio-ecology and DNA barcoding of mosquitoes Aedes aegypti (Linnaeus) and Aedes albopictus (Skuse). The Journal of Communicable Diseases, 49(3), 31–41. Armbruster, P., & Hutchinson, R. A. (2002). Pupal mass and wing length as indicators of fecundity in Aedes albopictus and Aedes geniculatus (Diptera: Culicidae). Journal of Medical Entomology, 39(4), 699–704. https://doi.org/10.1603/0022-2585-39.4.699 Arriagada, G., Vanderstichel, R., Stryhn, H., Milligan, B., & Revie, C. W. (2016). Evaluation of water salinity effects on the sea lice Lepeophtheirus salmonis found on farmed Atlantic salmon in Muchalat Inlet, British Columbia, Canada. Aquaculture, 464, 554–563. https://doi.org/10.1016/j.aquaculture.2016.08.002 Asakura, K. (1980a). The anal portion as a salt-excreting organ in a seawater mosquito larva, Aëdes togoi Theobald. Journal of Comp Physiol B, 138, 59–65. Asakura, K. (1980b). The anal portion as a salt-excreting organ in a seawater mosquito larva, Aedes togoi Theobald. Journal of Comparative Physiology ? B, 138(1), 59–65. https://doi.org/10.1007/BF00688736 Asakura, K. (1982). Ultrastructure and chloride cytochemistry of the hindgut epithelium in the larvae of the seawater mosquito, Aëdes togoi Theobald. Archivum Histologicum Japonicum, 45(2), 167–180. https://doi.org/10.1679/aohc.45.167 102 Baik, L. S., & Carlson, J. R. (2020). The mosquito taste system and disease control. Proceedings of the National Academy of Sciences, 117(52), 32848–32856. https://doi.org/10.1073/pnas.2013076117 Barkai, A. I., & Williams, R. W. (1983). The exchange of calcium in larvae of the mosquito Aedes aegypti. The Journal of Experimental Biology, 104, 139–148. https://doi.org/10.1242/jeb.104.1.139 Becker, N., Petric, D., Zgomba, M., Boase, C., Madon, M., Dahl, C., & Kaiser, A. (2010). Mosquitoes and their control. Springer Science & Business Media. Belton, P. (1980). The first record of Aedes togoi (Theo.) in the United States-aboriginal or ferry passenger? Mosquito News, 40(4), 624–626. Belton, P. (1983). The Mosquitoes of British Columbia. In Natural History. British Columbia Provincial Museum. Bentley, M. D., & Day, J. F. (1989). Chemical ecology and behavioral aspects of mosquito oviposition. Annual Review of Entomology, 34(1), 401–421. https://doi.org/10.1146/annurev.en.34.010189.002153 Benzon, G. L., & Apperson, C. S. (1988). Reexamination of chemically mediated oviposition behavior in Aedes aegypti (L.) (Diptera: Culicidae). Journal of Medical Entomology, 25(3), 158–164. https://doi.org/10.1093/jmedent/25.3.158 Bisanzio, D., Giacobini, M., Bertolotti, L., Mosca, A., Balbo, L., Kitron, U., & Vazquez-Prokopec, G. M. (2011). Spatio-temporal patterns of distribution of West Nile virus vectors in eastern Piedmont Region, Italy. Parasites & Vectors, 4(1), Article 1. https://doi.org/10.1186/1756-3305-4-230 103 Bolker, B., Brooks, M., Clark, C., Geange, S., Poulsen, J., Stevens, H., & White, J.-S. (2009). Generalized linear mixed models: A practical guide for ecology and evolution. Trends in Ecology & Evolution (Personal Edition), 24, 127–135. https://doi.org/10.1016/j.tree.2008.10.008 Bradley, T. J. (1987). Physiology of osmoregulation in mosquitoes. Annual Review of Entomology, 32(1), 439–462. https://doi.org/10.1146/annurev.en.32.010187.002255 Bradley, T. J., & Phillips, J. E. (1977a). Regulation of rectal secretion in saline-water mosquito larvae living in waters of diverse ionic composition*. Journal of Experimental Biology, 66(1), 83–96. https://doi.org/10.1242/jeb.66.1.83 Bradley, T. J., & Phillips, J. E. (1977b). The effect of external salinity on drinking rate and rectal secretion in the larvae of the saline-water mosquito Aedes taeniorhynchus. The Journal of Experimental Biology, 66(1). https://doi.org/10.1242/jeb.66.1.97 Bradley, T. J., Strange, K., & Phillips, J. E. (1984). Osmotic and ionic regulation in saline-water mosquito larvae. In A. Pequeux, R. Gilles, & L. Bolis (Eds.), Osmoregulation in Estuarine and Marine Animals: Proceedings of the Invited Lectures to a Symposium Organized within the 5th Conference of the European Society for Comparative Physiology and Biochemistry—Taormina, Sicily, Italy, September 5–8, 1983 (pp. 35–50). Springer. https://doi.org/10.1007/978-3-642-45574-2_3 Brenha-Nunes, M. R., Contente, R. F., & Rossi-Wongtschowski, (2016). A protocol for measuring spatial variables in soft-sediment tide pools. Zoologia (Curitiba), 33(2). https://doi.org/10.1590/S1984-4689zool-20150165 104 Briegel, H. (1990). Metabolic relationship between female body size, reserves, and fecundity of Aedes aegypti. Journal of Insect Physiology, 36(3), 165–172. https://doi.org/10.1016/0022-1910(90)90118-Y Cameron, P., Hiroi, M., Ngai, J., & Scott, K. (2010). The molecular basis for water taste in Drosophila. Nature, 465(7294), 91–95. https://doi.org/10.1038/nature09011 Centers for Disease Control. (2005). West Nile Virus activity—United States,. Morbidity and Mortality Weekly Report, 54(49), 1253–1256. Cheung, P. S. C. (1991). An intertidal survey of Cape d’Aguilar, Hong Kong with special reference to the ecology of high-zoned rock pools. The University of Hong Kong. https://doi.org/10.5353/th_b3120962 Chitolina, R. F., Anjos, F. A., Lima, T. S., Castro, E. A., & Costa-Ribeiro, M. C. V. (2016). Raw sewage as breeding site to Aedes (Stegomyia) aegypti (Diptera, culicidae). Acta Tropica, 164, 290–296. https://doi.org/10.1016/j.actatropica.2016.07.013 Clark, T. M. (2004). Differences in the effects of salinity on larval growth and developmental programs of a freshwater and a euryhaline mosquito species (Insecta: Diptera, Culicidae). Journal of Experimental Biology, 207(13), 2289–2295. https://doi.org/10.1242/jeb.01018 Clements, A. N. (1963). Chapter 3- Osmotic and ionic regulation of body fluids In A. N. Clements (Ed.), The Physiology of Mosquitoes (Vol. 17, pp. 57–71). Pergamon. https://doi.org/10.1016/B978-1-4831-9773-9.50007-0 Costa, E. A. P. de A., Santos, E. M. de M., Correia, J. C., & Albuquerque, C. M. R. de. (2010). Impact of small variations in temperature and humidity on the reproductive activity and survival of Aedes aegypti (Diptera, Culicidae). Revista Brasileira de Entomologia, 54(3), 488–493. https://doi.org/10.1590/S0085-56262010000300021 105 Cunze, S., Koch, L. K., Kochmann, J., & Klimpel, S. (2016). Aedes albopictus and Aedes japonicus—Two invasive mosquito species with different temperature niches in Europe. Parasites & Vectors, 9(1), Article 1. https://doi.org/10.1186/s13071-016-1853-2 Day, J. F. (2016). Mosquito oviposition behavior and vector control. Insects, 7(4), Article 4. https://doi.org/10.3390/insects7040065 de Brito Arduino, M., Mucci, L. F., Serpa, L. L. N., & Rodrigues, M. de M. (2015). Effect of salinity on the behavior of Aedes aegypti populations from the coast and plateau of southeastern Brazil. Journal of Vector Borne Diseases, 52(1), 79–87. Dedkhad, W., Christensen, B. M., Bartholomay, L. C., Joshi, D., Hempolchom, C., & Saeung, A. (2018). Immune responses of Aedes togoi, Anopheles paraliae and Anopheles lesteri against nocturnally subperiodic Brugia malayi microfilariae during migration from the midgut to the site of development. Parasites & Vectors, 11(1), 528. https://doi.org/10.1186/s13071-018-3120-1 Del Duca, O., Nasirian, A., Galperin, V., Donini, A. (2011). Pharmacological characterisation of apical Na+ and Cl- transport mechanisms of the anal papillae in the larval mosquito Aedes aegypti. The Journal of Experimental Biology, 214(Pt 23). https://doi.org/10.1242/jeb.063719 Donini, A., Gaidhu, M., Strasberg, D., & O’Donnell, M. (2007). Changing salinity induces alterations in hemolymph ion concentrations and Na+ and Cl- transport kinetics of the anal papillae in the larval mosquito, Aedes aegypti. The Journal of Experimental Biology, 210, 983–992. https://doi.org/10.1242/jeb.02732 Donini, A., & O’Donnell, M. J. (2005). Analysis of Na+, Cl-, K+, H+and NH4+ concentration gradients adjacent to the surface of anal papillae of the mosquito Aedes aegypti: 106 Application of self-referencing ion-selective microelectrodes. Journal of Experimental Biology, 208(4), 603–610. https://doi.org/10.1242/jeb.01422 Dow, J. A. (2017). The essential roles of metal ions in insect homeostasis and physiology. Current Opinion in Insect Science, 23, 43–50. https://doi.org/10.1016/j.cois.2017.07.001 Durant, A. C., & Donini, A. (2019). Development of Aedes aegypti (Diptera: Culicidae) mosquito larvae in high ammonia sewage in septic tanks causes alterations in ammonia excretion, ammonia transporter expression, and osmoregulation. Scientific Reports, 9(1), Article 1. https://doi.org/10.1038/s41598-019-54413-6 Durant, A. C., Grieco Guardian, E., Kolosov, D., & Donini, A. (2021). The transcriptome of anal papillae of Aedes aegypti reveals their importance in xenobiotic detoxification and adds significant knowledge on ion, water and ammonia transport mechanisms. Journal of Insect Physiology, 132, 104269. https://doi.org/10.1016/j.jinsphys.2021.104269 Edwards, H. A. (1982a). Aedes aegypti: Energetics of osmoregulation. Journal of Experimental Biology, 101(1), 135–141. https://doi.org/10.1242/jeb.101.1.135 Edwards, H. A. (1982b). Ion concentration and activity in the haemolymph of Aedes aegypti larvae. Journal of Experimental Biology, 101(1), 143–151. https://doi.org/10.1242/jeb.101.1.143 Ekechukwu, N. E., & Ekeh, F. N. (2011). Effects of sodium chloride concentrations on larvae and pupae of Aedes aegypti. Animal Research International, 8(3), Article 3. https://doi.org/10.4314/ari.v8i3 Emerton, R., Brimicombe, C., Magnusson, L., Roberts, C., Di Napoli, C., Cloke, H. L., & Pappenberger, F. (2022). Predicting the unprecedented: Forecasting the June 2021 Pacific Northwest heatwave. Weather, 77(8), 272–279. https://doi.org/10.1002/wea.4257 107 Evans, M. V., Hintz, C. W., Jones, L., Shiau, J., Solano, N., Drake, J. M., & Murdock, C. C. (2019). Microclimate and larval habitat density predict adult Aedes albopictus abundance in urban areas. The American Journal of Tropical Medicine and Hygiene, 101(2), 362–370. https://doi.org/10.4269/ajtmh.19-0220 Faierstein, G., Lu, W., Sena, A., Barbosa, R., & Leal, W. (2019). Conspecific and allospecific larval extracts entice mosquitoes to lay eggs and may be used in attract-and-kill control strategy. Scientific Reports, 9(1), Article 1. https://doi.org/10.1038/s41598-019-50274-1 Faiman, R., Yaro, A. S., Dao, A., Sanogo, Z. L., Diallo, M., Samake, D., Yossi, O., Veru, L. M., Graber, L. C., Conte, A. R., Kouam, C., Krajacich, B. J., & Lehmann, T. (2022). Isotopic evidence that aestivation allows malaria mosquitoes to persist through the dry season in the Sahel. Nature Ecology & Evolution, 6(11), Article 11. https://doi.org/10.1038/s41559-022-01886-w Fighting the World’s Deadliest Animal, CDC. (2022, April 6). https://www.cdc.gov/globalhealth/stories/2019/world-deadliest-animal.html Foster, W. A., & Walker, E. D. (2019). Mosquitoes (Culicidae). In G. R. Mullen & L. A. Durden (Eds.), Medical and Veterinary Entomology (Third Edition) (pp. 261–325). Academic Press. https://doi.org/10.1016/B978-0-12-814043-7.00015-7 Gardner, A. M., Hamer, G. L., Hines, A. M., Newman, C. M., Walker, E. D., & Ruiz, M. O. (2012). Weather variability affects abundance of larval Culex (Diptera: Culicidae) in storm water catch basins in suburban Chicago. Journal of Medical Entomology, 49(2), 270–276. https://doi.org/10.1603/ME11073 Getachew, D., Tekie, H., Gebre-Michael, T., Balkew, M., & Mesfin, A. (2015). Breeding Sites of Aedes aegypti: Potential Dengue Vectors in Dire Dawa, East Ethiopia. 108 Interdisciplinary Perspectives on Infectious Diseases, 2015. https://doi.org/10.1155/2015/706276 Githeko, A., Lindsay, S., Confalonieri, U., & Ja, J. (2000). Climate change and vector-borne diseases: A regional analysis. Bulletin of the World Health Organization, 78(9). https://pubmed.ncbi.nlm.nih.gov/11019462/ Gloria-Soria, A., Ayala, D., Bheecarry, A., Calderon-Arguedas, O., Chadee, D. D., Chiappero, M., Coetzee, M., Elahee, K. B., Fernandez-Salas, I., Kamal, H. A., Kamgang, B., Khater, E. I. M., Kramer, L. D., Kramer, V., Lopez-Solis, A., Lutomiah, J., Martins Jr, A., Micieli, M. V., Paupy, C., … Powell, J. R. (2016). Global genetic diversity of Aedes aegypti. Molecular Ecology, 25(21), 5377–5395. https://doi.org/10.1111/mec.13866 Gopalakrishnan, R., Das, M., Baruah, I., Veer, V., & Dutta, P. (2013). Physicochemical characteristics of habitats in relation to the density of container-breeding mosquitoes in Asom, India. Journal of Vector Borne Diseases, 50(3), 215–219. Government of Canada, I. (2022, June 27). Surviving the heat: The impacts of the 2021 western heat dome in Canada. Innovation, Science and Economic Development Canada. https://science.gc.ca/site/science/en/blogs/science-health/surviving-heat-impacts-2021-western-heat-dome-canada Guillena, J. B., Opena, E. L., & Baguio, M. (2010). Prevalence of the dengue fever (DF) and dengue hamorrhagic fever (DHF). Proceedings of the 11th National Convention on Statistics (NCS ’10),p.16,2010., 17. Gunathilaka, N., Ranathunge, T., Udayanga, L., Wijegunawardena, A., & Abeyewickreme, W. (2018). Oviposition preferences of dengue vectors; Aedes aegypti and Aedes albopictus in 109 Sri Lanka under laboratory settings. Bulletin of Entomological Research, 108(4), 442–450. https://doi.org/10.1017/S0007485317000955 Hayashi, S. (2011). Brugian filariasis in Japan. Tropical Medicine and Health, 39(1, Supplement 02), 25–28. https://doi.org/10.2149/tmh.39-1-suppl_2-25 Hine, R. M., Rouhier, M. F., Park, S. T., Qi, Z., Piermarini, P. M., & Beyenbach, K. W. (2014). The excretion of NaCl and KCl loads in mosquitoes. 1. Control data. American Journal of Physiology-Regulatory, Integrative and Comparative Physiology, 307(7), R837–R849. https://doi.org/10.1152/ajpregu.00105.2014 Hiscox, A., Kaye, A., Vongphayloth, K. V., Banks, I., Piffer, M., P, K., P, S., S, K., N, H., Sw, L., & Pt, B. (2013). Risk factors for the presence of Aedes aegypti and Aedes albopictus in domestic water-holding containers in areas impacted by the Nam Theun 2 hydroelectric project, Laos. The American Journal of Tropical Medicine and Hygiene, 88(6). https://doi.org/10.4269/ajtmh.12-0623 Honěk, A. (1993). Intraspecific variation in body size and fecundity in insects: A general relationship. Oikos, 66(3), 483–492. https://doi.org/10.2307/3544943 Hudson, B. N. A. (1956). The behaviour of the female mosquito in selecting water for oviposition. Journal of Experimental Biology, 33(3), 478–492. https://doi.org/10.1242/jeb.33.3.478 Ibañez-Justicia, A., Gloria-Soria, A., den Hartog, W., Dik, M., Jacobs, F., & Stroo, A. (2017). The first detected airline introductions of yellow fever mosquitoes (Aedes aegypti) to Europe, at Schiphol International airport, the Netherlands. Parasites & Vectors, 10(1), 603. https://doi.org/10.1186/s13071-017-2555-0 110 Ignell, R., Lazzari, C. R., & Lorenzo, M. G. (2022). Sensory Ecology of Disease Vectors. Wageningen Academic Publishers. http://ebookcentral.proquest.com/lib/ubc/detail.action?docID=30349695 Invasive Species. (2022). Canadian Council on Invasive Species. Canadian Council on Invasive Species. https://canadainvasives.ca/ Irving-Bell, R. J., Okoli, E. I., Diyelong, D. Y., Lyimo, E. O., & Onyia, O. C. (1987). Septic tank mosquitoes: Competition between species in central Nigeria. Medical and Veterinary Entomology, 1(3), 243–250. https://doi.org/10.1111/j.1365-2915.1987.tb00350.x Jaeger, A. H., Stanley, M., Weiss, Z. F., Musso, P.-Y., Chan, R. C., Zhang, H., Feldman-Kiss, D., & Gordon, M. D. (2018). A complex peripheral code for salt taste in Drosophila. ELife, 7, e37167. https://doi.org/10.7554/eLife.37167 Kain, M. P., Skinner, E. B., Athni, T. S., Ramirez, A. L., Mordecai, E. A., & Hurk, A. F. van den. (2022). Not all mosquitoes are created equal: A synthesis of vector competence experiments reinforces virus associations of Australian mosquitoes. PLOS Neglected Tropical Diseases, 16(10), e0010768. https://doi.org/10.1371/journal.pntd.0010768 Kengne, P., Charmantier, G., Blondeau-Bidet, E., Costantini, C., & Ayala, D. (2019). Tolerance of disease-vector mosquitoes to brackish water and their osmoregulatory ability. Ecosphere, 10(10), e02783. https://doi.org/10.1002/ecs2.2783 Le Roux, P. C., & McGeoch, M. A. (2008). Rapid range expansion and community reorganization in response to warming. Global Change Biology, 14(12), 2950–2962. https://doi.org/10.1111/j.1365-2486.2008.01687.x 111 Lien, J. C. (1960). Laboratory culture of Aedes (Finlaya) togoi (Theobald), 1907 and measurements of its susceptibility to insecticides. Entomologia Experimentalis et Applicata, 3(4), 267–282. https://doi.org/10.1111/j.1570-7458.1960.tb00457.x Liu-Helmersson, J., Brännström, Å., Sewe, M. O., Semenza, J. C., & Rocklöv, J. (2019). Estimating past, present, and future trends in the global distribution and abundance of the arbovirus vector Aedes aegypti under climate change scenarios. Frontiers in Public Health, 7. https://doi.org/10.3389/fpubh.2019.00148 López-Pujol, J. (2011). The importance of biological interactions in the global impact of mosquito biodiversity. In Human vector-borne diseases and environmental changetudy of Biodiversity. inTech. Maciel-de-Freitas, R., Neto, R. B., Gonçalves, J. M., Codeço, C. T., & Lourenço-de-Oliveira, R. (2006). Movement of dengue vectors between the human modified environment and an urban forest in Rio de Janeiro. Journal of Medical Entomology, 43(6). https://doi.org/10.1603/0022-2585(2006)43[1112:modvbt]2.0.co;2 Martins, G., Hawkins, S., Thompson, R., & Jenkins, S. (2007). Community structure and functioning in intertidal rock pools: Effects of pool size and shore height at different successional stages. Marine Ecology Progress Series, 329, 43–55. https://doi.org/10.3354/meps329043 Matthews, B. J., Younger, M. A., & Vosshall, L. B. (2019). The ion channel ppk301 controls freshwater egg-laying in the mosquito Aedes aegypti. ELife, 8, 143. https://doi.org/10.7554/eLife.43963 112 McBride, C. S., Baier, F., Omondi, A. B., Spitzer, S. A., Lutomiah, J., Sang, R., Ignell, R., & Vosshall, L. B. (2014). Evolution of mosquito preference for humans linked to an odorant receptor. Nature, 515(7526), Article 7526. https://doi.org/10.1038/nature13964 McGinnis, K. M. (1982). Reproductive Biology and Ecology of Aedes togoi (Theobald). M.S.c Thesis, University of Manitoba. McGinnis, K. M., & Brust, R. A. (1983). Effect of different sea salt concentrations and temperatures on larval development of Aedes togoi (Diptera: Culicidae) from British Columbia. Environmental Entomology, 12(5), 1406–1411. https://doi.org/10.1093/ee/12.5.1406 Merritt, R. W., Dadd, R. H., & Walker, E. D. (2003). Feeding behavior, natural food, and nutritional relationships of larval mosquitoes. Annual Review of Entomology, 37(1), 349–376. https://doi.org/10.1146/annurev.en.37.010192.002025 Millero, F. J., Feistel, R., Wright, D. G., & McDougall, T. J. (2008). The composition of standard seawater and the definition of the reference-composition salinity scale. Deep Sea Research Part I: Oceanographic Research Papers, 55(1), 50–72. https://doi.org/10.1016/j.dsr.2007.10.001 Morritt, D., & Williams, G. A. (2000). Osmoregulation in larvae of the mosquito Aedes togoi from supralittoral rock pools at Cape d’Aguilar, Hong Kong. Proceedings of the Tenth International Marine Biological Workshop. The Marine Flora and Fauna of Hong Kong and Southern China, 6-26 April 1998, Hong Kong. Multini, L. C., Oliveira-Christe, R., Medeiros-Sousa, A. R., Evangelista, E., Barrio-Nuevo, K. M., Mucci, L. F., Ceretti-Junior, W., Camargo, A. A., Wilke, A. B. B., & Marrelli, M. T. (2021). The influence of the pH and salinity of water in breeding sites on the occurrence 113 and community composition of immature mosquitoes in the green belt of the city of São Paulo, Brazil. Insects, 12(9). https://doi.org/10.3390/insects12090797 Munstermann, L. E. (1997). Care and maintenance of Aedes mosquito colonies. The Molecular Biology of Insect Disease Vectors, 13–20. https://doi.org/10.1007/978-94-009-1535-0_2 Nakamura, R. (1971). Food of two cohabiting tide-pool Cottidae. Journal of the Fisheries Board of Canada, 28(6), 928–932. Navarro, D. M. F., Oliveira, P. E. S. D., Potting, R. P. J., Brito, A. C., Fital, S. J. F., & Sant’Ana, A. E. G. (2003). The potential attractant or repellent effects of different water types on oviposition in Aedes aegypti L. (Dipt., Culicidae). Journal of Applied Entomology, 127(1), 46–50. https://doi.org/10.1046/j.1439-0418.2003.00690.x Okal, M. N., Lindh, J. M., Torr, S. J., Masinde, E., Orindi, B., Lindsay, S. W., & Fillinger, U. (2015). Analysing the oviposition behaviour of malaria mosquitoes: Design considerations for improving two-choice egg count experiments. Malaria Journal, 14(1), 250. https://doi.org/10.1186/s12936-015-0768-2 O’Meara, G. F. (1976). Saltmarsh mosquitoes (Diptera: Culicidae). In Marine Insects (pp. 303–333). https://www.researchgate.net/publication/226056790_Marine_Insects Omori, N., & Fujii, S. (1953). On the feeding habits of Aedes togoi and some other species of mosquitoes. Yokohama Medical Bulletin, 4(1). https://pubmed.ncbi.nlm.nih.gov/13090790/ Pallarés, S., Arribas, P., Bilton, D. T., Millán, A., & Velasco, J. (2015). The comparative osmoregulatory ability of two water beetle genera whose species span the fresh-hypersaline gradient in inland waters (Coleoptera: Dytiscidae, Hydrophilidae). PLOS ONE, 10(4), e0124299. https://doi.org/10.1371/journal.pone.0124299 114 Pamplona, L. de G. C., Alencar, C. H., Lima, J. W. O., & Heukelbach, J. (2009). Reduced oviposition of Aedes aegypti gravid females in domestic containers with predatory fish. Tropical Medicine & International Health, 14(11), 1347–1350. https://doi.org/10.1111/j.1365-3156.2009.02377.x Panigrahi, S. K., Barik, T. K., Mohanty, S., & Tripathy, N. K. (2014). Laboratory evaluation of oviposition behavior of field collected Aedes mosquitoes. Journal of Insects, 2014, 1–8. https://doi.org/10.1155/2014/207489 Patrick, M. L., Gonzalez, R. J., Wood, C. M., Wilson, R. W., Bradley, T. J., & Val, A. L. (2002). The characterization of ion regulation in amazonian mosquito larvae: evidence of phenotypic plasticity, population‐based disparity, and novel mechanisms of ion uptake. Physiological and Biochemical Zoology, 75(3), 223–236. https://doi.org/10.1086/342002 Paupy, C., Ollomo, B., Kamgang, B., Moutailler, S., Rousset, D. (2010). Comparative role of Aedes albopictus and Aedes aegypti in the emergence of Dengue and Chikungunya in central Africa. Vector Borne and Zoonotic Diseases (Larchmont, N.Y.), 10(3). https://doi.org/10.1089/vbz.2009.0005 Peach, D. A. (2018). First Record of Culex tarsalis Coquillett (Diptera: Culicidae) in the Yukon. Journal of the Entomological Society of British Columbia, 115. Peach, D. A., Almond, M., & Pol, J. C. (2019). Modeled distributions of Aedes japonicus japonicus and Aedes togoi (Diptera: Culicidae) in the United States, Canada, and northern Latin America. Journal of Vector Ecology: Journal of the Society for Vector Ecology, 44(1), 119–129. https://doi.org/10.1111/jvec.12336 115 Peach, D. A., & Matthews, B. J. (2020). Modeling the putative ancient distribution of Aedes togoi (Diptera: Culicidae). Journal of Insect Science (Online), 20(3). https://doi.org/10.1093/jisesa/ieaa035 Petrishcheva, P. A. (1948a). On the transition of Aedes togoi Theob. and Aedes japonicus Theob. (Diptera, Culicidae) to a synanthropic form of life. Entomolosicheskoye Obozreniye, 103–108. https://doi.org/10.21236/AD0648125 Pickard, G., & McLeod, D. (1953). Seasonal variation of temperature and salinity of surface waters of the British Columbia coast. Journal of the Fisheries Research Board of Canada, 10(3), 125–145. https://doi.org/10.1139/f53-009 Ponlawat, A., & Harrington, L. C. (2005). Blood feeding patterns of Aedes aegypti and Aedes albopictus in Thailand. Journal of Medical Entomology, 42(5), 844–849. https://doi.org/10.1093/jmedent/42.5.844 Powell, J. R., Gloria-Soria, A., & Kotsakiozi, P. (2018). Recent history of Aedes aegypti: vector genomics and epidemiology records. Bioscience, 68(11), 854–860. https://doi.org/10.1093/biosci/biy119 Powell, J. R., & Tabachnick, W. J. (2013). History of domestication and spread of Aedes aegypti—A Review. Memórias Do Instituto Oswaldo Cruz, 108(Suppl 1), 11. https://doi.org/10.1590/0074-0276130395 Rabiul Alam, M., Hossain, M., & Rahman, M. (2018). Maternal origins induced plasticity in salt adaptability of Avicennia officinalis L. seedlings in the Sundarbans of Bangladesh. Hydrobiologia, 820, 227–244. https://doi.org/10.1007/s10750-018-3659-z Ramasamy, R., Jude, P. J., Veluppillai, T., Eswaramohan, T., & Surendran, S. N. (2014). Biological differences between brackish and fresh water-derived Aedes aegypti from two 116 locations in the Jaffna peninsula of Sri Lanka and the implications for arboviral disease transmission. PLOS ONE, 9(8), e104977. https://doi.org/10.1371/journal.pone.0104977 Ramasamy, R., & Surendran, S. (2012). Global climate change and its potential impact on disease transmission by salinity-tolerant mosquito vectors in coastal zones. Frontiers in Physiology, 3. https://www.frontiersin.org/articles/10.3389/fphys.2012.00198 Ramasamy, R., & Surendran, S. N. (2011). Possible impact of rising sea levels on vector-borne infectious diseases. BMC Infectious Diseases, 11(1), Article 1. https://doi.org/10.1186/1471-2334-11-18 Ramasamy, R., Surendran, S. N., Jude, P. J., Dharshini, S., & Vinobaba, M. (2011). Larval development of Aedes aegypti and Aedes albopictus in peri-urban brackish water and its implications for transmission of arboviral diseases. PLOS Neglected Tropical Diseases, 5(11), e1369. https://doi.org/10.1371/journal.pntd.0001369 Ramsay, J. A. (1950). Osmotic regulation in mosquito larvae. Journal of Experimental Biology, 27, 145–157. Ramsay, J. A. (1951). Osmotic regulation in mosquito larvae: The role of the malpighian tubules. Journal of Experimental Biology, 28(1), 62–73. https://doi.org/10.1242/jeb.28.1.62 Ranasinghe, H. a. K., & Amarasinghe, L. D. (2020). Naturally occurring microbiota associated with mosquito breeding habitats and their effects on mosquito larvae. BioMed Research International, 2020, e4065315. https://doi.org/10.1155/2020/4065315 Rao, X., & Lin, G. (2020). Effects of age, salinity and temperature on the metamorphosis and survival of Capitulum mitella cyprids (Cirripedia: Thoracica: Scalpellomorpha). Journal of the Marine Biological Association of the United Kingdom, 100(1), 55–62. https://doi.org/10.1017/S0025315419001152 117 Ratnasari, A., Jabal, A. R., Syahribulan, S., Idris, I., Rahma, N., Rustam, S. N. R. N., Karmila, M., Hasan, H., & Wahid, I. (2021). Salinity tolerance of larvae Aedes aegypti inland and coastal habitats in Pasangkayu, West Sulawesi, Indonesia. Biodiversitas Journal of Biological Diversity, 22(3), Article 3. https://doi.org/10.13057/biodiv/d220316 Rocklöv, J., & Dubrow, R. (2020). Climate change: An enduring challenge for vector-borne disease prevention and control. Nature Immunology, 21(5), Article 5. https://doi.org/10.1038/s41590-020-0648-y Roiz, D., Ruiz, S., Soriguer, R., & Figuerola, J. (2014). Climatic effects on mosquito abundance in Mediterranean wetlands. Parasites & Vectors, 7(1), 333. https://doi.org/10.1186/1756-3305-7-333 Roiz, D., Ruiz, S., Soriguer, R., & Figuerola, J. (2015). Landscape effects on the presence, abundance and diversity of mosquitoes in Mediterranean wetlands. PLOS ONE, 10(6), e0128112. https://doi.org/10.1371/journal.pone.0128112 Rose, N. H., Badolo, A., Sylla, M., Akorli, J., Otoo, S., Gloria-Soria, A., Powell, J. R., White, B. J., Crawford, J. E., & McBride, C. S. (2023). Dating the origin and spread of specialization on human hosts in Aedes aegypti mosquitoes. ELife, 12, e83524. https://doi.org/10.7554/eLife.83524 Rose, N. H., Sylla, M., Badolo, A., Lutomiah, J., Ayala, D., Aribodor, O. B., Ibe, N., Akorli, J., Otoo, S., Mutebi, J.-P., Kriete, A. L., Ewing, E. G., Sang, R., Gloria-Soria, A., Powell, J. R., Baker, R. E., White, B. J., Crawford, J. E., & McBride, C. S. (2020). Climate and urbanization drive mosquito preference for humans. Current Biology, 30, 3570–3579. https://doi.org/10.1101/2020.02.12.939041 118 Rosen, L. (1986). The natural history of Japanese encephalitis virus. Annual Reviews in Microbiology, 40, 395–414. Rosen, L., Tesh, R., Lien, J., & Cross, J. (1978). Transovarial transmission of Japanese encephalitis virus by mosquitoes. Science, 199(4331), 909–911. https://doi.org/10.1126/science.203035 Rozeboom, L. (1935). The relation of bacteria and bacterial filtrates to the development of mosquito larvae. American Journal of Epidemiology, 21(1), 167–179. https://doi.org/10.1093/oxfordjournals.aje.a118108 Satyam, K., & Thiruchitrambalam, G. (2018). Chapter 7—Habitat ecology and diversity of rocky shore fauna. In C. Sivaperuman, A. Velmurugan, A. K. Singh, & I. Jaisankar (Eds.), Biodiversity and Climate Change Adaptation in Tropical Islands (pp. 187–215). Academic Press. https://doi.org/10.1016/B978-0-12-813064-3.00007-7 Shaw, W. R., Attardo, G. M., Aksoy, S., & Catteruccia, F. (2015). A comparative analysis of reproductive biology of insect vectors of human disease. Current Opinion in Insect Science, 10, 142–148. https://doi.org/10.1016/j.cois.2015.05.001 Smith, K. E., VanEkeris, L. A., Okech, B. A., Harvey, W. R., & Linser, P. J. (2008). Larval anopheline mosquito recta exhibit a dramatic change in localization patterns of ion transport proteins in response to shifting salinity: A comparison between anopheline and culicine larvae. The Journal of Experimental Biology, 211(Pt 19), 3067. https://doi.org/10.1242/jeb.019299 Sota, T., Belton, P., Tseng, M., Yong, H. S., & Mogi, M. (2015a). Phylogeography of the coastal mosquito Aedes togoi across climatic zones: testing an anthropogenic dispersal hypothesis. PLOS ONE, 10(6), e0131230. https://doi.org/10.1371/journal.pone.0131230 119 Stephen, C., Plamondon, N., & Belton, P. (2006). Notes on the distribution of mosquito species that could potentially transmit West Nile Virus on Vancouver Island, British Columbia. Journal of the American Mosquito Control Association, 22(3), 553–556. Stobbart, R. H. (1974). Electrical potential differences and ionic transport in the larva of the mosquito Aedes aegypti (L.). Journal of Experimental Biology, 60(2), 493–533. https://doi.org/10.1242/jeb.60.2.493 Stoklosa, J., Blakey, R. V., & Hui, F. K. C. (2022). An overview of modern applications of negative binomial modelling in ecology and biodiversity. Diversity, 14(5), Article 5. https://doi.org/10.3390/d14050320 Strand, M. R. (2018). Composition and functional roles of the gut microbiota in mosquitoes. Current Opinion in Insect Science, 28, 59–65. https://doi.org/10.1016/j.cois.2018.05.008 Surendran, S. N., Sivabalakrishnan, K., Jayadas, T. T. P., Santhirasegaram, S., Laheetharan, A., Senthilnanthanan, M., & Ramasamy, R. (2018). Adaptation of Aedes aegypti to salinity: characterized by larger anal papillae in larvae. Journal of Vector Borne Diseases, 55(3), 235. https://doi.org/10.4103/0972-9062.249482 Sutcliffe, D. W., & Hildrew, A. G. (1989). Invertebrate communities in acid streams. Seminar Series - Society for Experimental Biology. https://agris.fao.org/agris-search/search.dorecordID=US201302683041 Takken, W., & Verhulst, N. O. (2013). Host preferences of blood-feeding mosquitoes. Annual Review of Entomology, 58(1), 433–453. https://doi.org/10.1146/annurev-ento-120811-153618 Tanaka, K., Mizusawa, K., & Saugstad, E. S. (1979). A revision of the adult and larval mosquitoes of Japan (Including the Ryukyu Archipelago and the Ogasawara Islands) and 120 Korea (Diptera: Culicidae). Contributions of the American Entomological Institute, 16, 989. Taruno, A., & Gordon, M. D. (2023). Molecular and cellular mechanisms of salt taste. Annual Review of Physiology, 85, 25–45. https://doi.org/10.1146/annurev-physiol-031522-075853 Taylor, A. C., & Morris, S. (1983). Diurnal and seasonal variation in physico-chemical conditions within intertidal rock pools. Estuarine, Coastal and Shelf Science, 17(3), 339–355. https://doi.org/10.1016/0272-7714(83)90026-4 Trimble, R. M., & Wellington, W. G. (1979). Effects of salinity on site selection by ovipositing Aedes togoi (Diptera: Culicidae). Canadian Journal of Zoology, 57(3), 593–596. https://doi.org/10.1139/z79-069 Uchida, K. (1994). Autogenous egg development in anautogenous Culex pipiens pallens mosquitoes. Journal of Insect Physiology, 40(10), 835–839. https://doi.org/10.1016/0022-1910(94)90016-7 Vonesh, J. R., & Blaustein, L. (2010). Predator-induced shifts in mosquito oviposition site selection: A meta-analysis and implications for vector control. Israel Journal of Ecology and Evolution, 56(3–4), 263–279. https://doi.org/10.1560/IJEE.56.3-4.263 Wada, Y. (2011). Vector mosquitoes of filariasis in Japan. Tropical Medicine and Health, 39(1, Supplement 02), 39–42. https://doi.org/10.2149/tmh.39-1-suppl_2-39 Ward, J. V. (1992). Aquatic insect ecology. 1. Ecology and habitat. John Wiley & Sons, Inc. https://www.cabdirect.org/cabdirect/abstract/19920511104 Webb, C. E. (2008). Mosquito ecology: field sampling methods. Australian Journal of Entomology, 47(4), 382–383. https://doi.org/10.1111/j.1440-6055.2008.00673.x 121 White, R. H., Anderson, S., Booth, J. F., Braich, G., Draeger, C., Fei, C., Harley, C. D. G., Henderson, S. B., Jakob, M., Lau, C.-A., Mareshet Admasu, L., Narinesingh, V., Rodell, C., Roocroft, E., Weinberger, K. R., & West, G. (2023). The unprecedented Pacific Northwest heatwave of June 2021. Nature Communications, 14(1), Article 1. https://doi.org/10.1038/s41467-023-36289-3 WHO. (2012). Global Strategy for Dengue Prevention and Control 2012-2020. WHO, Geneva, Switzerland, 2012. Wigglesworth, V. (1938). The regulation of osmotic pressure and chloride concentration in the haemolymph of mosquito larvae. The Journal of Experimental Biology, 15, 235–247. Wigglesworth, V. B. (1933). The function of the anal gills of the mosquito larva. Journal of Experimental Biology, 10(1), 16–26. https://doi.org/10.1242/jeb.10.1.16 Wong, J., Stoddard, S. T., Astete, H., Morrison, A. C., & Scott, T. W. (2011). Oviposition site selection by the dengue vector Aedes aegypti and its implications for dengue control. PLOS Neglected Tropical Diseases, 5(4), e1015. https://doi.org/10.1371/journal.pntd.0001015 Woodley, A., Hintz, L. L., Wilmoth, B., & Hintz, W. D. (2023). Impacts of water hardness and road deicing salt on zooplankton survival and reproduction. Scientific Reports, 13(1), Article 1. https://doi.org/10.1038/s41598-023-30116-x Xia, S. (2021). Laboratory oviposition choice of Aedes aegypti (Diptera: Culicidae) from Kenya and Gabon: Effects of conspecific larvae, salinity, shading, and microbiome. Journal of Medical Entomology, 58(3), 1021–1029. https://doi.org/10.1093/jme/tjaa285 122 Yan, J., Kibech, R., & Stone, C. (2021). Differential effects of larval and adult nutrition on female survival, fecundity, and size of the yellow fever mosquito, Aedes aegypti. Frontiers in Zoology, 18. https://doi.org/10.1186/s12983-021-00395-z Yee, D. A., Dean Bermond, C., Reyes-Torres, L. J., Fijman, N. S., Scavo, N. A., Nelsen, J., & Yee, S. H. (2022). Robust network stability of mosquitoes and human pathogens of medical importance. Parasites & Vectors, 15(1), 216. https://doi.org/10.1186/s13071-022-05333-4 Yin, K., Harrison, P. J., & Beamish, R. J. (1997). Effects of a fluctuation in Fraser River discharge of primary production in the central Strait of Georgia, British Columbia, Canada. Canadian Journal of Fisheries and Aquatic Sciences, 54(5), 1015–1024. https://doi.org/10.1139/f97-010 Zahiri, N., & Rau, M. E. (1998). Oviposition attraction and eepellency of Aedes aegypti (Diptera: Culicidae) to waters from conspecific larvae subjected to crowding, confinement, starvation, or infection. Journal of Medical Entomology, 35(5), 782–787. https://doi.org/10.1093/jmedent/35.5.782 Zaim, M., & Newson, H. D. (1979). Larval development and oviposition behavior of Aedes triseriatus (Diptera: Culicidae) as affected by varying concentrations of sodium chloride and calcium nitrate in the water. Environmental Entomology, 8(2), 326–329. https://doi.org/10.1093/ee/8.2.326 Zhao, Z., Zung, J. L., Hinze, A., Kriete, A. L., Iqbal, A., Younger, M. A., Matthews, B. J., Merhof, D., Thiberge, S., Ignell, R., Strauch, M., & McBride, C. S. (2022). Mosquito brains encode unique features of human odour to drive host seeking. Nature, 605(7911), 706–712. https://doi.org/10.1038/s41586-022-04675-4 123 Zhou, G., Kohlhepp, P., Geiser, D., Frasquillo, M. del C., Vazquez-Moreno, L., & Winzerling, J. J. (2007). Fate of blood meal iron in mosquitos. Journal of Insect Physiology, 53(11), 1169. https://doi.org/10.1016/j.jinsphys.2007.06.009 124 Appendix Figure A.1 LC50 curves showing survival of Ae. aegypti larvae in a variety of ionic salts Figure A.2 LC50 curves showing survival of Ae. togoi larvae in a variety of ionic salts 125 Figure A3. Dose response curves of Ae. aegypti oviposition preference in response to increasing osmolarity in a variety of ionic salts Osmolarity (Osm) Oviposition Preference Index 126 Figure A.4 Correlation matrix of environmental variables input into PCA
Thesis/Dissertation
eng
Zoology
Vancouver : University of British Columbia Library
Attribution-NonCommercial-NoDerivatives 4.0 International
Graduate
Matthews, Benjamin J., 1983-
An investigation into the salinity tolerance, oviposition behavior and breeding habitat ecology of a widespread (Aedes aegypti) and restricted (Aedes togoi) mosquito species
Text