Ecological factors influencing community structure of parasites and their hosts

Understanding patterns and processes underlying the structure and assembly of ecological communities is a major goal of ecology. Community assembly involves a balance between dispersal events and interactions with biotic and abiotic elements that make up the local environment. Determining which processes dominate and under what circumstances remains unclear for parasite communities. Parasite communities of deer mice are examined to determine whether host traits, parasite interactions, and/or parasite dispersal is important in structuring within host parasite community structure. The results suggest that within host parasite communities accumulate in heavier, older hosts. Parasite dispersal plays a role in structuring parasite communities in deer mice. Helminths and ticks accumulated in older hosts, while fleas and lice did not. Helminths and lice were predicted to accumulate in older hosts because they are associated with their hosts for longer periods of time than ticks and fleas. In studies of parasite communities, it is important to document most, if not all, parasites of interest on or in a host. Using histopathology, I show that deer mice are not infected by parasites in other tissues that are not typically examined during standard parasitological surveys. I also survey rodents in the Great Basin for diseases that are caused by both infectious and non-infectious sources. Two pathogens were found in deer mice: the fungus Emmonsia crescens and the nematode Capillaria hepatica. The most common disease was extramedullary hematopoiesis (11%). I also investigated how habitat change influences species turnover. A major change in the environments of the Intermountain West is the expansion of pinyon-juniper woodlands (P-J). Rodent communities in the Great Basin are assessed to document species turnover following P-J conversion. I found that there was a diversity deficit (immigration credit) following P-J conversion because immigration of new species into P-J converted areas is slower than local species extinction. Diversity may increase if the immigrating species become more abundant. Parasites are also subject to environmental change, but little empirical data exist about how parasites will respond. Resampling historical sites following environmental change suggests that helminth diversity increased throughout the Great Basin region. This change was driven by a decrease in the prevalence and abundance of the pinworm Syphacia peromysci, making the relative abundances of helminth species more even. Complex life cycle parasites appear to be more stable to environmental change than those with direct life cycles because, in this system, complex life cycle parasites have lower host specificity.

ECOLOGICAL FACTORS INFLUENCING COMMUNITY STRUCTURE OF PARASITES AND THEIR HOSTS by Andrew William Bartlow A dissertation submitted to the faculty of The University of Utah in partial fulfillment of the requirements for the degree of Doctor of Philosophy Department of Biology The University of Utah December 2017 Copyright © Andrew William Bartlow 2017 All Rights Reserved The University of Utah Graduate School STATEMENT OF DISSERTATION APPROVAL The dissertation of Andrew William Bartlow has been approved by the following supervisory committee members: Sarah E. Bush and by , Chair 08/22/2017 Dale H. Clayton , Member 08/22/2017 Frederick R. Adler , Member 08/22/2017 M. Denise Dearing , Member 08/22/2017 Eric A. Rickart , Member 08/22/2017 M. Denise Dearing the Department/College/School of and by David B. Kieda, Dean of The Graduate School. Date Approved Date Approved Date Approved Date Approved Date Approved , Chair/Dean of Biology ABSTRACT Understanding patterns and processes underlying the structure and assembly of ecological communities is a major goal of ecology. Community assembly involves a balance between dispersal events and interactions with biotic and abiotic elements that make up the local environment. Determining which processes dominate and under what circumstances remains unclear for parasite communities. Parasite communities of deer mice are examined to determine whether host traits, parasite interactions, and/or parasite dispersal is important in structuring within host parasite community structure. The results suggest that within host parasite communities accumulate in heavier, older hosts. Parasite dispersal plays a role in structuring parasite communities in deer mice. Helminths and ticks accumulated in older hosts, while fleas and lice did not. Helminths and lice were predicted to accumulate in older hosts because they are associated with their hosts for longer periods of time than ticks and fleas. In studies of parasite communities, it is important to document most, if not all, parasites of interest on or in a host. Using histopathology, I show that deer mice are not infected by parasites in other tissues that are not typically examined during standard parasitological surveys. I also survey rodents in the Great Basin for diseases that are caused by both infectious and non-infectious sources. Two pathogens were found in deer mice: the fungus Emmonsia crescens and the nematode Capillaria hepatica. The most common disease was extramedullary hematopoiesis (11%). I also investigated how habitat change influences species turnover. A major change in the environments of the Intermountain West is the expansion of pinyon-juniper woodlands (P-J). Rodent communities in the Great Basin are assessed to document species turnover following P-J conversion. I found that there was a diversity deficit (immigration credit) following P-J conversion because immigration of new species into P-J converted areas is slower than local species extinction. Diversity may increase if the immigrating species become more abundant. Parasites are also subject to environmental change, but little empirical data exist about how parasites will respond. Resampling historical sites following environmental change suggests that helminth diversity increased throughout the Great Basin region. This change was driven by a decrease in the prevalence and abundance of the pinworm Syphacia peromysci, making the relative abundances of helminth species more even. Complex life cycle parasites appear to be more stable to environmental change than those with direct life cycles because, in this system, complex life cycle parasites have lower host specificity. iv TABLE OF CONTENTS ABSTRACT...................................................................................................................... iii LIST OF TABLES............................................................................................................ vii LIST OF FIGURES............................................................................................................ x ACKNOWLEDGEMENTS............................................................................................. xiv Chapters 1. INTRODUCTION ...........................................................................................................1 Background ................................................................................................................ 1 Chapter Summaries .................................................................................................... 4 References .................................................................................................................. 7 2. THE IMPORTANCE OF HOST TRAITS AND PARASITE DISPERSAL ON THE STRUCTURE OF PARASITE COMMUNITITES IN DEER MICE................................ 9 Abstract ...................................................................................................................... 9 Introduction...............................................................................................................10 Methods ................................................................................................................... 14 Results...................................................................................................................... 19 Discussion .................................................................................................................22 Acknowledgements.................................................................................................. 26 References................................................................................................................ 27 3. HISTOLOGICAL SURVEY OF DISEASES AND PARASITES OF WILD RODENTS IN THE GREAT BASIN ............................................................................... 47 Abstract .................................................................................................................... 47 Introduction.............................................................................................................. 48 Methods ................................................................................................................... 50 Results...................................................................................................................... 53 Discussion ................................................................................................................ 55 Acknowledgements.................................................................................................. 59 References................................................................................................................ 59 4. SPECIES TURNOVER OF RODENTS FOLLOWING HABITAT CHANGE.......... 69 Abstract .................................................................................................................... 69 Introduction.............................................................................................................. 70 Methods ................................................................................................................... 74 Results...................................................................................................................... 79 Discussion ................................................................................................................ 82 Acknowledgements.................................................................................................. 87 References................................................................................................................ 87 5. IMPACT OF ENVIRONMENTAL CHANGE ON PARASITE COMMUNITIES ...106 Abstract .................................................................................................................. 106 Introduction............................................................................................................ 107 Methods ................................................................................................................. 112 Results.................................................................................................................... 119 Discussion .............................................................................................................. 122 Acknowledgements................................................................................................ 128 References.............................................................................................................. 128 Appendices A. STABLE ISOTOPE ANALYSIS OF DEER MICE IN THE GREAT BASIN ........ 147 B. SPECIES OF LICE COLLECTED FROM RODENTS IN THE GREAT BASIN ... 148 C. ANIMALS INFESTED WITH BOTFLIES AT TIME OF CAPTURE .................... 149 D. HOST-PARASITE DATA FROM RODENTS IN THE GREAT BASIN ............... 150 E. HISTOPATHOLOGY RESULTS OF RODENTS .................................................... 167 F. SEQUENCES OF PARASITE SPECIES OF DEER MICE ...................................... 170 vi LIST OF TABLES 2.1. Life history traits of the seven taxonomic groups of parasites. In the column of time spent with host, short (S) refers to parasites that are associated with their hosts for up to several days or feed intermittently. Long (L) refers to parasites being associated with their hosts for long period of time (several weeks to months) .......................................... 33 2.2. The prevalence and mean intensity (± se) of ectoparasites and endoparasites found in 525 deer mice. The prevalence of coinfections is also shown .......................................... 34 2.3. Summary of GLMs for parasite group richness with a Poisson distribution (A) and total parasite rank sum (B) for the different habitat types ................................................ 35 2.4. Summary of GLMMs for parasite group richness with poisson distribution for 494 mice over seven sampling locations. Separate models were run for body mass (A) and body condition (B) ............................................................................................................ 36 2.5. Summary for GLMMs for total parasite rank sum with Poisson distribution for 494 mice over seven sampling locations for body mass (A), body condition (B) ................... 37 2.S1. Summary of GLMs for parasite group richness with a Poisson distribution (A) and total parasite rank sum with a Poisson distribution (B) for the seven sampling locations............................................................................................................................ 38 2.S2. Summary for generalized linear models for fleas (A), ticks (B), lice (C), nematodes (D), and cestodes (E) separately with binomial distributions for 494 mice over seven sampling locations ............................................................................................................ 39 2.S3. Summary for generalized linear models for parasite associations with Poisson distribution for 494 observations over seven sampling locations ..................................... 40 3.1 Diseases of rodents trapped in the Great Basin that were found using histology. The species affected for each disease is listed along with the prevalence (in parentheses)..... 64 4.1. Abundance of each species at each site that was resampled after P-J conversion. In total, historical sites had eight species, and recently sampled sites had ten ..................... 94 4.2. Abundance of each species captured at each site that was resampled for control sites ....................................................................................................................................95 4.S1. Summary of mixed model results for estimated species richness for the three habitat types with 20 observations from seven locations ............................................................. 96 4.S2. Summary of linear mixed effects model for species diversity for the three habitat types with 20 observations from seven locations ............................................................. 97 5.1. Forward (F) and reverse (R) primers and sequences for mitochondrial cytochrome c oxidase I (COI) genes that were used to split parasites into species groups................... 134 5.2. Parasite species composition in the Great Basin from historical sampling and resampling. Historical sampling included 400 deer mice. Recent sampling included 382 deer mice......................................................................................................................... 135 5.3. Parasite species at two sites sampling historically and resampled recently after an increase in P-J woodlands. Listed are the prevalences and abundances for both sites sampled. One hundred two mice were sampled for parasites at Stansbury A in 1968, and 49 deer mice were sampled more recently. Twenty-four mice were sampled historically at Stansbury B in 1957, and 26 were sampled recently ...................................................... 136 5.4. The prevalence and total abundance of Syphacia peromysci from deer mice in four replicate locations at which low P-J and high P-J habitat types were sampled. Locations are shown in Fig. 5.1. Sample size is the number of deer mice sampled at each site within each location ................................................................................................................... 137 5.5. Host specificity of nematode parasites found in deer mice (Peromyscus maniculatus) in the southwestern U.S. Host specificity refers to the number of mammal (definitive) hosts. These data include deer mice as a host ................................................................. 138 B.1. Species identifications of lice collected from rodents in the Great Basin from 2014 to 2016. Rodents were trapped, euthanized, and combed for ectoparasites. Each louse was mounted on a glass slide after first clearing the abdomen using a lysis buffer and proteinase k. All identifications were made by D. Gustafsson ....................................... 148 C.1. Botflies from rodents captured between 2014 and 2016 in the Great Basin. The number of botflies in each host and the habitat in which the rodent was captured is listed .................................................................................................................................149 D.1. Host-parasite data of rodents collected in the Great Basin. Listed are all the individual rodents captured, the species, sex, and the numbers of ectoparasites (split into fleas, ticks, and lice) and helminth species. Measurements (body length, tail length, leg length, and ear length) of each animal, and site locations can be obtained from the Natural History Museum of Utah (Collection numbers AWB1-AWB683) ................... 150 E.1. Results of histopathology for rodents captured in the Great Basin. Heart, lung, kidney, and liver tissue was examined for diseases and parasites using histology. Listed are the collection numbers, species of rodent, and any parasites and pathologies found. viii Rodent tissues were examined and diagnosed by Dr. David Gardiner, Animal Reference Pathology ........................................................................................................................ 167 F.1. Cytochrome oxidase I (COI) gene sequences of parasite species of deer mice collected in the Great Basin. Sequences are the sequences from one representative individual of each species ............................................................................................... 170 ix LIST OF FIGURES 2.1. Map of sampling sites in Utah and Nevada. Diamonds represent mountain ranges (locations) that were sampled. Inset: The Cedar Mountains were sampled at two sites (ecotone and P-J habitat types). The Stansbury Mountains and Oquirrh Mountains each consisted of two locations, and each location was sampled at three habitat types (sagebrush, ecotone, and P-J)............................................................................................ 42 2.2. Number of parasite groups and parasite rank sum for the different habitat types. A) Mean number of parasite groups per mouse in the three habitat types. The three habitats did not significantly differ. B) Mean total parasite rank sum per mouse for each habitat type. Different letters indicate significant differences between habitat types. Mice in pinyon-juniper had significantly more parasites than mice from sagebrush and ecotone habitats .............................................................................................................................. 43 2.3. Mass and body condition of deer mice and their relationship to the number of parasite groups and total parasite rank sum. A) Three age classes (juvenile, subadult, and adult) of deer mice (Peromyscus maniculatus) and the associated masses of individuals within those classes. N=40 for each class. Age classes of mice were based on pelage color after capture in the field. Different letters indicate significant differences. B) The number of parasite groups within each individual mouse and the associated mass of that mouse. Age class delineations were based on masses in A. There was a significant positive correlation between number of parasite groups and mouse mass (GLMM: z = 3.113, p = 0.001). C) Number of parasite groups and associated body condition of each mouse. There was no significant correlation between number of groups and body condition (GLMM: z = 1.087, p = 0.28). D) Total parasite rank sum index (abundance) and the relationship to body mass. Total parasite abundance was significantly correlated with body mass (GLM: z = 7.932, p < 0.001). The data are jittered in B and C along the y-axis to see more of the data ........................................................................................... 44 2.4. The relationships between mouse mass and the infection status (infected/not infected) for fleas (A), ticks (B), lice (C), nematodes (D), and cestodes (E). Tick, nematode, and cestode infection were significantly correlated with mouse mass. The data are jittered to see more of the data .................................................................................... 45 2.S1. Mean mass of mice in the three habitat types. Different letters indicate significant differences. Mice in pinyon-juniper had significantly higher masses than in sagebrush and ecotone habitat types ......................................................................................................... 46 3.1. Map of trapping locations in the Great Basin of Utah and Nevada. At each site, all rodents captured were euthanized and histology was performed. Trapping stopped once 25 deer mice (Peromyscus maniculatus) were trapped. .................................................... 66 3.2. Parasites found during histology in Peromyscus maniculatus. A) Eggs of Capillaria hepatica in the liver. B) Emmonsia crescens spore (fungus) in the lungs ........................ 67 3.3. Images of pathology found in deer mice using histology (H&E stain). A) Severe interstitial nephritis of kidney tissue. B) Mild pyelitis in kidney tissue. C) Hyperplastic BALT in lung tissue. D) Extramedullary hematopoiesis in liver tissue ........................... 68 4.1. Diagram of sagebrush to P-J woodland habitat gradient sampled in the Great Basin with the transition zone (ecotone) between the two primary habitat types. Sagebrush is characterized by having sagebrush and associated grasses and no juniper trees or pinyonpine. P-J woodlands are dense woodlands of juniper and pinyon-pine with very little understory. Ecotones have both P-J associated trees and an understory of sagebrush and grasses. Most of the trees in ecotones are small compared to those in P-J woodlands .... 98 4.2. Map of recent and historical sampling sites in the Great Basin. Rodents were sampled over sagebrush to PJ woodlands at eight locations. In each location, three habitats were sampled (yellow, brown, and green). Circles represent recent sampling, and squares refer to historical sampling. Squares with circles inside denote sites that were resampled and the colors refer to the habitat types of the sites historically (outer square color) and recently (inner circle color) ............................................................................. 99 4.3. The habitat preferences for each species based on where they were captured. All seven sites (six for sagebrush) were pooled together. Species that were less than 1% of total captures for each habitat type were considered present but rare. Rodent species are arranged according to habitat preference. Left to right: generalists, found in sagebrush and ecotones, sagebrush specialists, found in ecotones and P-J, P-J specialists ............ 100 4.4. Species richness and species diversity for deer mice sampled in 2014 to 2016. A) Estimated species richness using the Chao richness estimator for the three habitat types. Different letters indicate significant differences between habitat types (P < 0.05). Sagebrush and P-J sites significantly differed for the Chao estimator. B) Species diversity significantly differs between ecotone and P-J habitat types. Sagebrush did not significantly differ between ecotone or P-J habitats ....................................................... 101 4.5. Percent pinyon-juniper (P-J) cover in six historically sampled sites when mammals were sampled in the late 1950s, and the percent P-J cover of the same sites sampled in 2014-2016. Sites that cross from one habitat zone to the next are considered sites that changed habitats. Those in the same habitat type did not change over time ...................102 4.6. Species diversity (Simpson's D) of rodents in historically sampled sites in the 1950s and in 2014-2016. Four of the six sites had no change in diversity. The P-J control site and one P-J conversion site increased in diversity.......................................................... 103 xi 4.7. The number of sagebrush specialists (A) and P-J specialists (B) plotted against the percent P-J cover for 16 sites. There was a significant negative correlation between P-J cover and sagebrush specialists (Spearman rank, rs = -0.64, p = 0.008). There is no significant correlation between P-J cover and P-J specialists (Spearman rank, rs = 0.35, p = 0.19) ............................................................................................................................. 104 4.S1. Species accumulation curves for all sites sampled in the Great Basin using cumulative trap nights for each site separated by habitat type ....................................... 105 5.1. Map of current and historical parasite sampling sites in the Great Basin. Deep mice were trapped and sampled over sagebrush to PJ woodlands at four locations; two in Stansbury Mountains and two in the Oquirrh Mountains. In each location, three habitats were sampled (yellow, brown, and green). Circles represent current sampling, and squares refer to historical sampling. Squares with circles inside denote sites that were resampled and the colors refer to the habitat types of the sites historically (outer square color) and currently (inner circle color). Red triangles are the locations of weather stations at which temperature data was collected ........................................................... 139 5.2. Parasite species diversity (Simpson's D) (A) and rank abundance plots for parasites in the Great Basin historically (B) and during current sampling (C). Note the break in the axis in B .......................................................................................................................... 140 5.3. Change in P-J cover over time at the two resampled sites. Stansbury A was sampled historically in 1968 and Stansbury B was sampled in 1957 ........................................... 141 5.4. Parasite species diversity (Simpson's D) (A) and rank abundance plots for the two resampled sites: Stansbury A (B and C) and Stansbury B (D and E). Shown are the rank abundances of each site at each time point. Sample sizes are listed. Note the break in the axis in B .......................................................................................................................... 142 5.5. Parasite species diversity (Simpson's D) for low P-J cover and high P-J cover sites at four replicate locations: two locations in the Stansbury Mountains and two locations in the Oquirrh Mountains .................................................................................................... 143 5.S1. Parasite species accumulation based on sampling individual deer mice region-wide in the Great Basin (A) in two sites (B and C) that were resampled that were converted to P-J woodlands ................................................................................................................. 144 5.S2. Species accumulation curves for the Great Basin region (A) and the two sites that were converted to P-J woodlands (B and C). Solid lines represent species accumulation based on number of individual parasites found. Dashed lines represent extrapolated species richness based on the Chao species richness estimator. Shaded regions around each line represent 95% confidence intervals based on bootstrapped data. Sample sizes are listed in Fig. 5.4......................................................................................................... 145 5.S3. Temperature data from Tooele, UT (A) and Callao, UT (B). Both sites showed xii significant increases in mean temperature and mean max temperature from 1960-1970 to 2005-2015 ....................................................................................................................... 146 A.1. Isotope values of whiskers from deer mice. A) 15N and 13C values of mice caught in sagebrush habitats and pinyon-juniper (P-J) habitats. There is a significant difference between 15N in sagebrush and pinyon-juniper (t-test, t = 2.97, df = 21.06, p-value = 0.007), which suggests a difference in trophic level for mice in these two habitats. Mice in sagebrush are in a higher trophic level than those in P-J, which may be due to a higher insect diet (see B). There is no significant difference between 13C in mice from sagebrush and P-J habitats. B) 15N values of captive deer mice and field caught mice for comparison (from A). Captive mice were fed one of two diets for two months: seed rich or insect rich. Blood was taken and 15N and was measured. Mice fed insect rich diets had significantly higher 15N values than mice fed seed rich diets (t-test, t = -5.27, df = 15.09, P < 0.0001). These results suggest that mice in sagebrush habitats are consuming more insects than mice in P-J habitats ......................................................................................................... 147 xiii ACKNOWLEDGEMENTS I would like to thank several people for their support and guidance throughout graduate school and throughout the development of this dissertation. I would first like to thank my co-advisors Dale Clayton and Sarah Bush. They let me join their lab and pursue topics that I am passionate about and work on something different than what they generally study. I am thankful for their patience and guidance and making me a better scientist. Our long lab meetings discussing my data were challenging. But looking back, all the feedback I got from Dale, Sarah, and the rest of the lab has definitely improved my science and my ability to present data. Sarah's constant reminders to think about my data in the context of big concepts in ecology is an important skill that I will use throughout my career. I would like to thank my committee, Denise Dearing, Eric Rickart, and Fred Adler, for their helpful feedback during committee meetings. Their doors were always open. Whether it was talking statistics with Fred or getting field advice from Denise, they were always there when I needed help. I want to especially thank Eric Rickart for his constant encouragement and for being willing to meet with me on such short notice. He taught me how to identify mammals of the Great Basin, and his help processing animals for the museum collection was greatly appreciated. I also want to thank Denise and Eric for letting me borrow Sherman traps. It would have been hard to trap rodents without them. I am grateful to people outside the University of Utah who helped me the last couple years of graduate school. Vasyl Tkach and Michael Kinsella identified cestode and nematode specimens for me, which was a big help for the last chapter of this dissertation. Without their help, comparing my parasite data with historical data would not have been possible. I would not have made it to this stage without the constructive criticism, encouragement, and friendship from everyone in the Clayton-Bush Lab. Emily DiBlasi, Scott Villa, Sabrina McNew, and Graham Goodman provided a healthy environment for discussions about experimental design, concepts, and data interpretation. Graduate school is challenging with a lot of ups and downs, and the members of the Clayton-Bush lab were always there to laugh or offer support. Other members of the Clayton-Bush lab assisted me with field and lab work. Specifically, I would like to thank several undergraduates including Matthew Talmage, Hector Zumaeta, Brandy Mills, Angela Hansen, Erik Poole, Michael Thompson, Scott Ripple, and William Reynolds. Erik Poole was a big help when I first started field work. He went on several long trips to Nevada and helped in the initial troubleshooting. Even when we had to process animals all day, he never complained and did everything he could to make the process more enjoyable. Chapter 2 of this dissertation would not have been possible without the help of James Ruff. Jimmy took the time to teach me how to perform mixed models. Even when I would walked into his cubicle multiple times a day, he was always willing to talk and offer advice. Our long sessions talking about statistics and theory (and college football) in the Potts Lab or during coffee is something that I always looked forward to and will never forget. Jimmy's advice and constant positive attitude was always welcomed. xv Jimmy has made my science better and I thank him for that. I would like to send a special thanks to Dr. Michael Steele, my undergraduate advisor and mentor. Mike was a major factor in my decision to attend graduate school. Mike introduced me to the world of academia and taught me that science can be fun while addressing big questions in ecology. I will be ever grateful for his mentorship and friendship. Lastly, I need to thank my parents. Moving across the country to Utah to pursue graduate school was not easy at first. They always believed in me, never doubted my abilities, and always reminded me why I went to graduate school in the first place. I will always be thankful for their guidance and support in everything I do. xvi CHAPTER 1 INTRODUCTION Background Understanding patterns and processes underlying the structure of ecological communities is a major goal of ecology (Ricklefs and Schluter 1994). Ecological communities consist of all the populations in a given area that are interacting or have the potential to interact. Community assembly concerns the processes that give rise to the structure of local ecological communities. The structure of a community, such as species composition, species richness, and relative species abundance, results from processes operating at several scales. The species that make up local communities are generally a subset of the species found at larger, regional scales (Zobel 1997). It is these regional species pools from which individuals disperse to colonize a given area and possibly become a member of the local community (Kraft and Ackerly 2014). Following dispersal, deterministic and stochastic processes act to structure local communities. Community assembly involves a balance between dispersal events and interactions with biotic and abiotic elements that make up the local environment (Fukami et al. 2005). However, the abiotic and biotic portions of the environment are not static; environments change and species respond. This dissertation will examine the assembly and structure of rodents and their parasite communities. First, parasite communities of rodents will be studied within the context of within host (intrahost) community assembly. 2 Rodent and parasite communities will then be investigated in terms of environmental change and species turnover. Two general models have received attention for their role in assembling and structuring communities: deterministic assembly models (ecological selection) and neutral, dispersal-based assembly models (ecological drift). Deterministic assembly is the result of community structure being influenced by available niches and is defined by resource use and competition (MacArthur 1972; Diamond 1975). Deterministic processes are the result of biotic and abiotic characteristics of the environment that act as filters to determine which species from the regional pool are able to establish viable populations in the local community. Biotic factors such as interspecific competition and predation influence whether a species is able to compete and successfully establish (Kraft and Ackerly 2014). Environmental factors, such as habitat structure (e.g. habitat heterogeneity), and abiotic factors (e.g. temperature and precipitation) further restrict the species able to colonize a given location. If biotic and abiotic filters significantly influence the structure of a community, the community is structured based on deterministic processes that are predictable and repeatable (Shipley et al. 2012). Alternatively, dispersal-based models suggest that assembly is generated by haphazard dispersal and establishment of species from the regional species pool (Bell 2000; Hubbell 2001). Dispersal of individuals away from the natal area is an important life history characteristic that plays a significant role in the population dynamics of a species (Bowler and Benton 2005). Dispersal maintains gene flow in a population and decreases the negative consequences of inbreeding, competition, and density-dependent predation (Janzen 1970; Connell 1971). Dispersal to new areas also allows species ranges 3 to expand or contract following environmental change (Travis et al. 2013). During the assembly of a local community, individuals from the species pool must first disperse to the given area. Once individuals disperse, those individuals are subject to abiotic and biotic filters that may determine whether the species will establish to become a member of the local community (Kraft and Ackerly 2014). If random dispersal and colonization of individuals determine the structure of a community, then there will not be patterns related to environmental factors and biotic interactions (i.e. no ecological selection) (Cottenie 2005). Both dispersal and deterministic processes can be important in structuring the same ecological community. A major goal of ecology is finding which processes dominate assembly and under what circumstances. Parasites represent a large portion of the world's biodiversity (Price 1980), yet little is currently known about which processes dominate the structure of parasite communities (Johnson et al. 2015). Dispersal and deterministic processes may both influence the assembly of parasite communities (Rynkiewicz et al. 2015; Budischak et al. 2016). Which processes dominate parasite community assembly and under what circumstances remains unclear (Johnson et al. 2015). Understanding the assembly of parasite communities in the context of parasite dispersal, host environment (host traits), and parasite interactions (i.e. within host parasite competition) is receiving attention recently (Johnson et al. 2015; Rynkiewicz et al. 2015; Budischak et al. 2016). However, few empirical studies have investigated parasite community assembly under this framework (but see Budischak et al. 2016). This dissertation examines the ecological factors influencing community structure in parasites and their hosts. I address this concept using a rodent-parasite system in the 4 Great Basin. I test whether parasite dispersal, host traits, and/or parasite interactions are most important in shaping the community structure of deer mouse parasites (Chapter 2). I then investigate whether parasites, pathogens, or non-infectious diseases are found in tissues not typically examined by parasitologists or ecologists in wild rodents using histology (Chapter 3). Environments are not static, and environmental change can impact species composition and diversity of both parasites and their hosts. First, I explore how environmental change impacts species turnover of rodents in the Great Basin. Specifically, I test for a biodiversity deficit or surplus following pinyon-juniper (P-J) conversion (Chapter 4). I then examine how P-J conversion may impact species diversity, community structure, and species turnover of deer mouse parasites (Chapter 5). Chapter summaries Chapter 2: The importance of host traits and parasite dispersal on the structure of parasite communities of deer mice Chapter 2 investigates whether parasite communities in individual hosts are structured through host traits, parasite dispersal, and/or parasites interactions. Hosts, including humans, are often infected with more than parasite species, some with widely different life history characteristics and transmission dynamics. Parasites within a single host individual represent an ecological community in which several parasite species may interact. In this chapter, deer mice were sampled from the Great Basin in Utah and Nevada to test the null hypothesis that parasite community structure is independent of host traits and parasite interactions. I found that body condition, sex, and within host parasite interactions were not significant in predicting parasite community structure. Data show that host body mass was a significant predictor of parasite group richness and total 5 parasite abundance, indicating that heavier, older mice have more parasites. When taxonomic groups were analyzed separately, helminths (nematodes and cestodes) and ticks accumulated in older hosts. Helminths are often associated with their hosts for longer periods of time than fleas and ticks, so fleas and ticks were not predicted to be correlated with host mass. Lice are permanent parasites and were predicted to accumulate on hosts similar to helminths. Lice are associated with their hosts for long periods of time and can maintain infections indefinitely. However, infection with lice was not correlated with mass. The results suggest that dispersal differences among taxonomic groups should be taken into account rather than grouping parasites by whether they are found on the outside or the inside of a host. Chapter 3: Histological survey of diseases and parasites of wild rodents in the Great Basin Wild animals often have disease, whether caused by infectious pathogens or noninfectious sources. Standard collection techniques for parasites may miss parasites or diseases associated with infectious pathogens. Background levels of disease in animals, whether caused by infectious or non-infectious agents, may be important to consider in wildlife disease studies and disease ecology. We used histology to survey diseases in wild rodent populations. We examined liver, lung, heart, and kidney tissue in ten species of rodents from five locations (143 rodents total). We found diseases caused by both infectious pathogens and non-infectious sources. One parasite was found in liver tissue from one deer mouse. One other pathogen, a fungus, was found in four rodents. The most common pathologies found in rodents were either non-infectious in origin or unknown. This information can be used to create baseline data for disease in wild populations to 6 assess population health. Baseline data can aid in identifying emerging diseases, finding causes of disease, and assessing the success of control efforts. Pathology from noninfectious sources, such as environmental contaminants, genetics, or general health conditions is important to consider in the context of disease ecology. Chapter 4: Species turnover of rodents following habitat change Chapter 4 examines how environmental change influences species turnover of rodents in the Great Basin. Estimating changes in biodiversity and species composition following environmental change is essential for predicting species responses to future change. Species respond to environmental change by expanding or contracting their ranges, resulting in the establishment or disappearance of species from a given area. These changes in biodiversity are referred to as species turnover. Following environmental change, there may be delays in species immigrating to the new habitat or becoming locally extinct, which can lead to diversity surpluses or deficits. One type of environmental change occurring around the world is the conversion of savannahs and shrublands to dense woodlands. In the Great Basin, pinyon-juniper woodlands are expanding and replacing sagebrush steppe habitat. In this chapter, I test whether there is a diversity surplus or deficit in rodent communities following pinyon-juniper conversion and whether the species composition changes. P-J conversion resulted in turnover of rodent species. Results suggest that species immigration is slower and more variable after P-J conversions than local extinction. Estimates of rodent diversity soon after woody plant conversions may underestimate the ultimate diversity that will be supported because of the slow rate of immigration. 7 Chapter 5: Impact of environmental change on parasite communities Chapter 5 explores the impacts of environmental change on parasite communities. Several contradictory hypotheses have been proposed in the literature regarding parasite responses to environmental change. In this chapter, I test whether parasite community structure is affected by environmental change using both historical and recent hostparasite data in the Great Basin. I also test the hypothesis that parasites with complex life cycles will be less affected by environmental change than those with direct life cycles. Diversity increased in two sites that converted from low P-J cover to high P-J cover. There was a big decrease in prevalence and abundance of the direct life cycle parasite Syphacia peromysci, which caused the relative abundances of helminth communities to be more even. I found that P-J conversion was not the main cause of the decrease in S. peromysci prevalence and abundance based on recent sampling in low P-J and high P-J sites. This chapter suggests that parasites with direct life cycles may be more affected by environmental change than those with complex life cycles. In this system, direct life cycle parasites are generally more host specific than complex life cycle parasites, which may make them more vulnerable to environmental change. References Bell, G. 2000. The distribution of abundance in neutral communities. The American Naturalist 155:606-617. Bowler, D. E., and T. G. Benton. 2005. Causes and consequences of animal dispersal strategies: relating individual behaviour to spatial dynamics. Biological Reviews 80:205-225. Budischak, S. A., E. P. Hoberg, A. Abrams, A. E. Jolles, and V. O. Ezenwa. 2016. Experimental insight into the process of parasite community assembly. Journal of Animal Ecology 85:1222-1233. 8 Chave, J. 2004. Neutral theory and community ecology. Ecology Letters 7:241-253. Cottenie, K. 2005. Integrating environmental and spatial processes in ecological community dynamics. Ecology Letters 8:1175-1182. Diamond, J. M. 1975. Assembly of species communities. Pp. 342-444 in Ecology and Evolution of Communities (M. L. Cody, and J. M. Diamond, eds). Harvard University Press. Boston, Massachusetts. Fukami, T., T. Martijn Bezemer, S. R. Mortimer, and W. H. Putten. 2005. Species divergence and trait convergence in experimental plant community assembly. Ecology Letters 8:1283-1290. Hubbell S. P. 2001. The Unified Neutral Theory of Biodiversity and Biogeography. Princeton University Press. Princeton, New Jersey. Johnson, P. T., J. C. De Roode, and A. Fenton. 2015. Why infectious disease research needs community ecology. Science 349:1259504. Kraft, N. J., and D. D. Ackerly. 2014. Assembly of plant communities. Pp. 67-88 in Ecology and the Environment (R. K. Monson, ed.). Springer. New York City, New York. MacArthur, R. H. 1972. Geographical Ecology: Patterns in the Distribution of Species. Harper and Row, New York City, New York. Ricklefs, R. E., and D. Schluter. (eds.). 1993. Species Diversity in Ecological Communities: Historical and Geographical Perspectives. University of Chicago Press. Chicago, Illinois. Rynkiewicz, E. C., A. B. Pedersen, and A. Fenton. 2015. An ecosystem approach to understanding and managing within-host parasite community dynamics. Trends in Parasitology 31:212-221. Travis, J. M., M. Delgado, G. Bocedi, M. Baguette, K. Bartoń, D. Bonte, I. Boulangeat, J.A. Hodgson, A. Kubisch, V. Penteriani, and M. Saastamoinen. 2013. Dispersal and species' responses to climate change. Oikos 122:1532-1540. Zobel, M. 1997. The relative of species pools in determining plant species richness: an alternative explanation of species coexistence? Trends in Ecology and Evolution 12:266-269. CHAPTER 2 IMPORTANCE OF HOST TRAITS AND PARASITE DISPERSAL ON THE STRUCTURE OF PARASITE COMMUNITIES IN DEER MICE Abstract Hosts are often infected by more than one species of parasite. Parasites on or within hosts represent an ecological community in which parasite species have the potential to interact, but how or why hosts are infected with many parasites remains unclear. Deterministic processes related to host traits and parasite interactions, and parasite dispersal, may influence how parasite communities are structured. I test the null hypothesis that parasite community structure is independent of host traits and parasite interactions. To test this hypothesis, ectoparasitic arthropods and endoparasitic helminths were collected from deer mice (Peromyscus maniculatus) over three years in the Great Basin. I found that habitat, host body condition, and parasite interactions were not significant in predicting parasite community structure. Data show that parasite richness and total parasite load is best explained by body mass, which, in deer mice, is highly correlated with age. When parasite taxonomic groups were analyzed separately, host body mass was a significant predictor of tick prevalence, opposite of predictions. Ticks were predicted to follow the same pattern as fleas because they both are associated with their hosts for short periods of time (i.e. up to a few days). Like helminths, lice are associated with their hosts longer than ticks and fleas, and were predicted to accumulate 10 on their hosts. Nematodes and cestodes accumulated in heavier, older hosts, while lice did not. These results suggest that host age is an important trait in structuring parasite communities in deer mice. Dispersal differences among taxonomic groups should be taken into account rather than grouping parasites by whether they are found on the outside or inside of a host. Introduction Hosts often have more than one parasite species infecting them. Parasites within hosts represent ecological communities in which many parasite species may interact (Cox 2001; Poulin 2007; Griffiths et al. 2014). Interactions among parasites and with their hosts affect parasite transmission, disease severity, disease recovery, and susceptibility to other parasites and pathogens (Hartgers and Yazdanbakhsh 2006; Telfer et al. 2010; Blackwell et al. 2013). For example, Anaplasma phagocytophilum increases the susceptibility of field voles (Microtus agrestis) to cowpox virus by a factor of five, while also decreasing the susceptibility to Bartonella spp. (Telfer et al. 2010). Given the frequency and importance of coinfections, how or why individuals acquire many parasites remains unclear. Finding which factors lead to individuals becoming infected with many parasites is a critical step in understanding how parasite communities are structured. Dispersal, deterministic processes, and stochastic forces all act to structure free-living communities (MacArthur 1972; Diamond 1975; Bell 2000). These processes also apply to parasite communities (Pedersen and Fenton 2007; Johnson et al. 2015). Most studies on coinfection focus on hosts infected with two or three parasite species (e.g. trematodes) or taxonomic groups (e.g. nematodes and Mycobacterium spp.) within a host population 11 (Graham 2008; Telfer et al. 2010; Ezenwa and Jolles 2011; Johnson and Hoverman 2012; Lass et al. 2012). However, the distribution of all parasites on a given host species can shape community-level processes (Balestrieri et al. 2006; Holmstad et al 2008; Ferrari et al. 2009; Krichbaum et al. 2009; Kamath et al 2014). Applying a community ecology framework to parasite communities allows several hypotheses to be tested in the same host-parasite system. Parasites must disperse (transmit) to new hosts, and different parasites have different modes of transmission to encounter hosts. Parasites are encountered throughout the entire life of a host and from different sources. Hosts encounter most intestinal helminths by consuming infective stages, often from arthropod intermediate hosts, while ticks and fleas are encountered when foraging or searching for mates. Whether an individual is infected with a certain parasite at a given time point (i.e. time sampled for parasites) may be determined by parasite life history traits and transmission dynamics (Johnson et al. 2015; Rynkiewicz et al. 2015). These characteristics may be used to determine whether certain guilds (ectoparasites vs. endoparasites) or taxonomic groups are more likely to infect a subset of the population. These data will help predict whether parasites with similar properties will infect hosts following similar patterns. Following dispersal, parasites are subject to filtering by the environment and stochastic processes. Deterministic processes (ecological selection) result from interactions with the environment, host traits, and from interactions among parasite species forming predictable and repeatable infection patterns (Johnson et al. 2015; Rynkiewicz et al. 2015). If stochastic processes dominate infection, parasite structure will be unpredictable through differential exposure and susceptibility related to temporal, 12 spatial, or demographic heterogeneity (Johnson et al. 2015; Rynkiewicz et al. 2015; Budischak et al. 2016). This is called ecological drift. For example, certain areas may be "hotspots" for parasites in some years or seasons (Ezenwa 2003; Wolinska and King 2009; Paull et al. 2012). Stochasticity will produce no visible patterns of infection. Deterministic processes result in infection patterns that are repeatable such that a subset of the host population is most likely to be infected by many parasites. For hostparasite interactions, this involves host traits such as host species, dispersal ability, body size, and dietary breadth (Dallas and Presley 2014). Within a species, examples of host traits influencing infection include males often having more parasites than females due to hormone differences (Zuk and McKean 1996). Hosts in poor body condition may also be more susceptible to infection because of low immunocompetence (Tella et al. 2001; Beldomenico and Begon 2010; Johnson et al. 2015; Warburton et al. 2016). Host defense can also structure communities by influencing colonization-extinction events. Hosts have behaviors to decrease exposure to parasites, such as avoiding areas rich in parasites or infected mates (Folstad et al. 1991; Houde and Torio 1992; Gilbert 1997; Penn and Potts 1998; Karvonen et al. 2004). Hosts also preen or groom themselves to remove ectoparasites once infested (Murray 1987; Clayton 1991; Mooring et al 1996). After infection, hosts may become tolerant to infections or resistant to future infections through the immune system (Schmid-Hempel 2011; Barbour 2017). For example, juvenile birds and mammals often have a higher intensity of parasites than adults (Gregory et al 1992; Allander and Bennett 1994; Dawson and Bortolotti 1999; Sol et al. 2003), presumably because of adaptive immunity in adults (Sol et al. 2003). Both dispersal and deterministic processes can be important in structuring the same community. A major goal of ecology 13 is finding which processes dominate and under what circumstances. Positive or negative interactions between species or groups can act to structure parasite communities by influencing susceptibility to other parasite species (Lello et al. 2004; Cattadori et al. 2008; Graham 2008; Telfer et al. 2010). Parasites can interact with each other directly through competition or indirectly through changes in host immunity (Cox 2001). If infection is determined by competition among parasites, or through facilitation (i.e. positive interactions, such as through suppression of host defense), then the abundance of one parasite species will negatively or positively influence the abundance of another parasite species. Here, I test the null hypothesis that parasite community structure is independent of host traits and parasite interactions. This hypothesis is tested using deer mice (Peromyscus maniculatus) and their ecto- and endoparasites. I also examine whether there are patterns of infection based on life history similarities among different taxonomic groups of parasites. Taxonomic groups can be organized according to life history traits and transmission dynamics (Table 2.1). Fleas and ticks differ from lice because they have greater dispersal ability and feed for a short amount of time. Ticks feed up to five days (Piesman et al. 1987; Jones et al. 2015), and fleas feed intermittently up to several days if they are not groomed off (Krasnov et al. 2003; Krasnov 2008). Lice, on the other hand, are permanent parasites. Once lice infect a host, they can complete their entire life cycle on that host. Helminths are often transmitted through ingestion and are associated with their hosts for longer periods of time that ticks and fleas. Lice and helminths are similar in the time they are associated with their host. However, unlike lice, most helminths 14 cannot maintain an infection indefinitely. I predict that flea and tick infestations will be based on random colonization-extinction events because being infected at a given time will be independent of host age/mass. In contrast, I predict lice and helminths will accumulate in older, heavier hosts because they are found on or in their hosts longer than ticks and fleas. Methods Study system The focal species for this study is the North American deer mouse (Peromyscus maniculatus), which occupies nearly every habitat in North America. Deer mice are nocturnal and active year-round. Deer mouse home ranges vary from 0.032 to 1.2 hectares (Stickel 1968) with an average home range of between 590m2 and 1 hectare (Blair 1942; Wolff 1985). Males and females disperse from the natal area but often do not travel more than 1 km to establish their own home ranges and territories (Howard 1960). Several taxonomic groups of parasites parasitize deer mice. Ectoparasites include ticks, lice, and fleas. Endoparasitic helminths include nematodes (roundworms), cestodes (tapeworms), trematodes (flukes), and acanthocephalans (thorny-headed worms). This study was conducted in the Great Basin of Utah and Nevada from 2014 to 2016. Within the Great Basin, there are north to south spanning mountain ranges, resulting in a topography characterized as basin and range. Sagebrush (Artemesia spp.) and associated grasses dominate sagebrush steppe habitat in the valley floors and occur as elevation increases until pinyon-juniper (P-J) woodlands are reached. In each mountain range, Utah juniper (Juniperus osteosperma) and singleleaf pinyon pine (Pinus monophylla) are the predominate species present in P-J woodlands (Banner 1992). 15 Between sagebrush and P-J woodlands are transition zones (ecotones), which have both sagebrush and grasses as well as juniper trees and pinyon pine (Appendix A). These different mountain ranges are used as replicates; sagebrush, P-J woodlands, and ecotones are sampled. Animal trapping and processing Deer mice were trapped in seven mountain ranges (locations) in the Great Basin (Fig. 2.1). Four were in Utah and three were in Nevada. Throughout these seven locations, deer mice were trapped at 19 individual sites. Seven sites were located in the Stansbury Mountains, six were in the Oquirrh Mountains, and two were in the Cedar Mountains. The other locations were each sampled once. Each site was either sagebrush, P-J woodland, or the transition zone between the two habitat types (ecotone). The site in the San Francisco Mountains was a mix of P-J woodland and mountain mahogany (Cercocarpus spp.). Two of the sites in the Stansbury Mountains were sampled in 2015 and then resampled in 2016. Sherman live traps (H.B. Sherman Traps, Inc.) were used to catch deer mice. Traps were placed in transects five to ten meters apart. Traps were baited with whole oats and birdseed. When 25 deer mice were trapped and euthanized at a given site, trapping stopped. Because deer mice populations were low in abundance, two sites had less than 25 animals trapped (San Francisco Mountains, n = 16 and Cedar Mountains ecotone, n = 12). Captured mice and contents of the trap were emptied into Ziploc bags. Emptying the contents of the bag ensured that ectoparasites that came off the animal could be recovered. Each deer mouse was euthanized with the anesthetic isoflurane and placed on ice until it was taken to the lab for further processing. In the lab, mass, body length, tail 16 length, ear length, and leg length were measured for each mouse. Age classes were determined based on coat color for a subset of mice (mice were not aged in 2014). Juveniles were gray in color, subadults were gray-brown, and adults were brown. Masses of the subset of mice that were aged by coat color were used to divide all mice into the three age classes. Similar age classes have been used in deer mice (Douglass et al. 2001; Calisher et al. 2007). Parasite collection After measurements were taken, the digestive tracts, including the stomach, small intestine, caecum, and large intestine of each mouse, were removed and either dissected immediately or frozen at -80°C for later dissection. Mice were then placed in a freezer (20°C) until they could be combed for ectoparasites. All animal handling and processing was approved by the Institutional Animal Care and Use Committee of the University of Utah. Each mouse was thawed and then combed for ectoparasites (fleas, ticks, lice) using a LiceMeister comb over a white surface to help see any parasites removed by combing. After combing, forceps were used to examine the mouth, nose, and ears to find ticks. The fur was also examined for any parasites not dislodged during the combing process. Once fully processed, mouse carcasses were deposited at the Natural History Museum of Utah. All ectoparasites were stored in 95% ethanol. Ectoparasites were identified to the following taxonomic groups: lice, fleas, and ticks. These ectoparasites are the most common ectoparasites of deer mice. Mites were extremely rare (< 1% of mice), and we were not certain of how many microscopic mites were missed since these were not the focus. Digestive tracts were thawed and dissected for helminths. The small intestine, 17 stomach, caecum, and large intestine were dissected separately. Each part of the digestive tract was cut open using ball tipped scissors. The inside wall of each part of the digestive tract was scraped with a glass slide to remove any parasites attached with their mouthparts (i.e. cestodes and acanthocephalans). Intestinal contents were examined under a stereoscope to help find all helminths. Helminths were placed in 70% ethanol and stored in a freezer until they were needed for further identification. Helminths were identified to the following taxonomic groups: nematodes, cestodes, trematodes, and acanthocephalans. Statistical analyses All statistical analyses were completed in the software program R (R Core Team 2016). Body condition was calculated using a scaled body mass index (Peig and Green 2009). Total body length, not including the tail, was used as the scaling factor. This index has been shown to be an accurate predictor of deer mouse condition (Peig and Green 2009). In order to account for total parasite load in an individual, a rank sum method was used, which allows hosts to be compared relative to each other (Holmstad et al. 2005, 2008). This relative measure of parasite load allows for comparisons of total parasite abundance per host when many types of parasites are being considered (Holmstad et al. 2005). For each parasite group, individual mice were ranked 1 to n according to how many parasites of that group that individual was infected with. Individuals not infected with a given parasite group received a zero for that group. Individuals with the same number of a given parasite group (ties) all received the same ranking. Parasite ranks were summed up for each individual to get a total rank sum. 18 Generalized linear models (GLM) and generalized linear mixed models (GLMM) were used to find what best predicts group richness and total abundance of parasites. Sitespecific differences (i.e. habitat type and mountain range of sampling locations) in parasite richness or total rank sum of parasites were determined to inform the models involving host traits. To test for infection differences in the three habitat types, the initial GLM included habitat as a predictor variable. The number of parasite groups per individual (Poisson distribution) was the measure of parasite group richness and total parasite rank sum (Poisson distribution) was the measure of parasite abundance. Mountain range was also run in a separate GLM to determine if there were differences in group structure infecting mice across all seven mountain ranges. To test for effects of host mass, body condition, and sex, GLMMs were used. Group richness and total parasite rank were the response variables for each model. In the mixed effects models, mountain range was treated as a random effect to control for differences among sampling locations (see supplemental Table 2.S.1). Body mass and body condition (scaled mass index) were treated as fixed effects to determine the best predictor of group richness within individual hosts. Separate models were run for body condition and body mass because body mass was used in the calculation of body condition. Pregnant females (n=19) were not included in analyses related to body mass and body condition. Parasites were split to determine whether there were similar patterns of infection among groups with similar traits. Ectoparasites consisted of three groups: fleas, ticks, and lice. Endoparasites consisted of four groups: nematodes, cestodes, acanthocephalans, and trematodes. Nematodes consisted of species that have intermediate hosts (complex life 19 cycles) and species that are directly transmitted between hosts (e.g. pinworms). To test for whether life history traits of each parasite group are better predictors of infection, parasite taxonomic groups were analyzed separately using generalized linear models with binomial distributions. Because we are interested in infection throughout a host's life, body mass is used as a proxy for host age (Douglass et al. 2001). Status of infection (binomial distribution) was the response variable and body mass (proxy for age) was the predictor variable in each model. Whether an individual was infected or not was used because I was interested in probability of infection with respect to age. Intensity of each taxonomic group was not used because it was not possible to determine whether each parasite in or on a host was the result of one or multiple infection events. To test for interactions among parasite groups, generalized linear models with quasi-poisson error distributions were used in order to account for the overdispersed distributions of parasites. Parasite abundance of each parasite group was used for these models because interactions among parasite groups may be dependent on the number of parasites within a host, rather than being infected or not. Five models were created. The five most abundant parasite groups were the response variables (one for each model), with the predictor variables being the other four groups. Because of the low prevalence of both trematode and acanthocephalan infections, they were not included in these analyses. Mixed models were run using the lme4 (Bates et al. 2015) and lmerTest (Kuznetsova et al. 2016) packages in R (R Core Team 2016). Results Deer mice (n = 519) were trapped at 19 sites throughout the Great Basin in Utah and Nevada from 2014-2016. Over half (51%) of captured deer mice were co-infected 20 with at least one individual from two or more parasite groups (Table 2.2). Thirty-three percent of mice were coinfected with two or more ectoparasite groups, while 4% of mice were coinfected with two or more endoparasite groups (Table 2.2). There was a significant difference in parasite group richness and total parasite rank in individual mice across the seven sampling locations (Table 2.S1). Therefore, in the analyses of parasite group richness in individual hosts, mountain range was used as a random effect in the generalized linear mixed models. The number of parasite groups per individual did not significantly differ across habitat types (Fig. 2.2A, Table 2.3). The total parasite rank of host individuals was significantly higher in pinyon-juniper habitat types than in sagebrush (GLM: z = 1.798, p < 0.001, Fig. 2.2B, Table 2.3) and ecotone habitat types (GLM: z = -7.686, p < 0.001, Fig. 2.2B, Table 2.3). To investigate this pattern further, I found that masses were significantly different in the three habitat types (ANOVA, F = 11.08, p < 0.001; Fig. 2.S1). Masses were significantly higher in mice from pinyon-juniper than in both sagebrush (Tukey post-hoc, p < 0.001) and ecotone (Tukey post-hoc, p < 0.001) habitat types when all mice were pooled according to habitat type (Fig. 2.S1). Based on the pelage color of mice, three age classes were used: juvenile, subadult, and adult. The masses of individuals in the three age classes differed significantly (ANOVA, F = 189.8, p < 0.001; Fig. 2.3A). Therefore, mass was used as a proxy for age. In addition, 19 pregnant mice were excluded from analyses with body mass and body condition. Six other mice were excluded because their masses were not recorded. Therefore, 494 deer mice were used in the analyses for body mass and body condition. Number of parasite groups infesting individuals increased with body mass 21 (GLMM: z = 2.963, p = 0.003; Fig. 2.3B; Table 2.4). Body condition was not correlated with number of parasite groups found in individual mice (GLMM: z = 0.917, p = 0.36; Fig. 2.3C; Table 2.4). Rank sum of total parasites increased with increasing mass (GLM: z = 7.932, p < 0.001, Fig. 2.3D, Table 2.5), meaning heavier (and older) individuals had higher parasite loads (total rank sum). In contrast, body condition was not significant in explaining the total rank sum of parasites per individual mouse (GLMM: z = 0.467, p = 0.64, Table 2.5). Males did not differ from females in group richness (GLMM: z = 1.623, p = 0.11) or in total rank sum of parasites (GLMM: z = 1.586, p = 0.11). Each parasite group was analyzed separately to determine if similar life history traits among parasite groups predict whether heavier, older individuals have a higher probability of being infected with certain groups. Mass was not a significant predictor of either flea (GLM: z = 0.999, p = 0.32; Fig. 2.4A; Table 2.S2) or louse infection (GLM: z = -1.633, p = 0.10; Fig. 2.4C; Table 2.S2). However, mass was a significant predictor of tick infection (GLM: z = 1.956, p = 0.051; Fig. 2.4B; Table 2.S2). In contrast to fleas and lice, infection by the two endoparasite groups was predicted by mass. Mass was a significant predictor of nematode (GLM: z = 3.939, p < 0.001; Fig. 2.4D; Table 2.S2) and cestode infection (GLM: z =2.764 , p = 0.006; Fig. 2.4E; Table 2.S2). There were no significantly positive or negative associations between any two parasite groups (GLM: all p-values > 0.05; Table 2.S3), suggesting that there are no positive or negative interactions among parasite groups based on parasite groups abundances. 22 Discussion I tested the hypothesis that infection is independent of host traits and parasite interactions. A community framework allows for testing multiple predictions related to community structure across several scales using the same host-parasite system. Host body mass was positively correlated with parasite group richness and total parasite rank sum in individual deer mice. In both measures of community structure, males did not differ from females. In deer mice, mass is a strong predictor of age (Douglass et al. 2001; Calisher et al. 2007). These results are in contrast to previous studies showing juveniles have higher parasite loads than adults in birds (Allander and Bennett 1994; Dawson and Bortolotti 1999; Sol et al. 2003) and mammals (Michel 1952; Gregory et al. 1992). Results suggest that parasite communities are structured independently of host traits since parasites accumulate in hosts throughout their life. Assembly in which parasites accumulate in larger, older hosts is seen in other systems, including helminths of fish (Poulin and Valtonen 2001). These results also indicate an additive assembly process, which implies unsaturated parasite assemblages (Poulin 2007; Johnson and Hoverman 2012). Not all parasite groups accumulated in heavier, older hosts. In this system, dispersal is an important process in structuring parasite communities. The four endoparasitic helminth groups include species that are trophically transmitted (Goater et al. 2013). All cestode, acanthocephalan, and trematode species require arthropod intermediate hosts that need to be consumed by definitive hosts to be transmitted (Goater et al. 2013). In this study, deer mice are the definitive hosts (i.e. host in which parasite sexual reproduction occurs). A few nematode species in this system also require arthropod intermediate hosts, although there are some species can be transmitted directly 23 from host to host, the most prevalent of which are pinworms (Syphacia peromysci) (Frandsen 1960; Derrick 1971). Development times of these endoparasitic helminths vary, but can often be greater than two weeks; some species shed eggs for up to a year in rodent hosts depending on conditions and host physiology (Anya 1966; Munger et al. 1989; Lass et al. 2012). As a result, endoparasites are typically associated with their hosts for longer periods of time than ticks and fleas. Because infective stages of helminths need to be ingested, older hosts have had more time to consume arthropods and contaminated material in the environment. However, some helminths can die and not be able to reinfect the same host without the host consuming more infective stages within the environment. Pinworms, on the other hand, are different from other helminths because they can re-establish infections through coprophagy or grooming around the anus. Therefore, lice are most similar to pinworms than to other helminths that can only infect a host through consuming arthropod intermediate hosts or infective stages that are in the environment. In this study, pinworms (S. peromysci) had a 7% prevalence, while total nematode prevalence was 28%. Even though the majority of helminths in this system are trophically transmitted, the pattern of helminths accumulating in older hosts was still observed. Mass may be more important than strictly the age of the host. For example, two mice that are the same age may differ in mass. One host may have eaten more and consumed more infective stages. Disentangling the effects of mass and age would require very precise measurements of host age, such as measuring protein in eye lenses (Dapson and Irland 1972). Regardless of whether these results are caused by mass or age, it suggests that the probability of being infected with helminths increases from juveniles to 24 subadults to adults (see Fig. 2.4B). Deer mice often live less than one year in the wild (O'Farrell 1978; Baker 1983), and hosts have a higher probability of having more helminth parasites later in life. Deer mice may not invest heavily in immune responses to helminth infections. If the immune system was important in regulating helminth infection, then adult mice would have fewer helminths than younger hosts, a pattern observed in other systems (Gregory et al. 1992; Allander and Bennett 1994; Dawson and Bortolotti 1999; Sol et al. 2003). Raush and Tiner (1949) suggest that low numbers of helminth parasites do not cause significant harm to their rodent hosts. Investing more in reproduction, foraging, and thermoregulation may outweigh the benefits of reducing parasite infections for this shortlived species (Pedersen and Greives 2008). The pattern of accumulating parasites as hosts get older was not observed for two ectoparasite groups. It was predicted that lice would show similar patterns to nematodes and cestodes and show a positive correlation with host body mass. Lice are permanent parasites and once they infest a mouse, they can complete their entire life cycle on one host individual. Therefore, lice can maintain infestations indefinitely. Our data were not consistent with this prediction. It appears that lice infect hosts independently of host age, which may be mediated by parasite defense. Mice are known to significantly reduce ectoparasite numbers, including lice, through grooming (Murray 1961; Glicken and Schwab 1980; Murray 1987; Hart 1994) and the immune system (Wikel 1982; Volf 1994). Even though ticks, like fleas, feed for relatively short amounts of time and can be groomed off hosts (Shaw et al. 2003; Hawlena et al. 2007), heavier, older individuals had 25 a significantly higher probability of tick infection. In contrast, there was no relationship between flea infection and mass. Both ticks and fleas are similar in their life history characteristics. One explanation for the observed difference is that, while both fleas and ticks can be encountered in the environment while foraging or searching for mates, fleas can also be encountered in nests (Bitam et al. 2010) and may infect mice at younger ages than ticks. Habitat type was not an important factor influencing parasite group richness, suggesting that, in terms of the habitat types examined, there were no hotspots resulting in higher parasite group richness per individual. Total parasite rank was higher in P-J habitats than in sagebrush and ecotone habitats. This was further investigated, and in P-J habitat types, deer mice weighed significantly more than those in the other two habitat types (see Fig. 2.S1). It is unclear if mice in P-J habitats are eating more and have a higher probability of consuming more infective stages of parasites, or if they live longer than in the other two habitat types (see Appendix C). Parasite interactions were also not important in structuring parasite communities within individual deer mice. These data suggest parasite infection is independent of parasite interactions (i.e. no competition or facilitation), which is consistent with other systems, such as ectoparasite assembly in fish (Gotelli and Rohde 2002). It also confirms an additive assembly pattern. Whether a deer mouse becomes infested with a particular parasite is more dependent on the age of the mouse rather than being outcompeted or facilitated by the presence or absence of other parasites. The lack of significant within host associations in deer mice makes sense considering the low prevalence of every parasite group (< 30%), except fleas (63%), and the high level of aggregation, which is a 26 general and consistent observation of parasite populations (Poulin 2007; Goater et al. 2013). Infection by the seven groups may be independent of each other because of the low prevalence of coinfections between most groups. In order to observe significant nonrandom associations between parasites, a greater sample size may be needed. However, even with 494 deer mice, significant associations were not found. In conclusion, sex, body condition, and habitat type were not correlated with group richness and total parasite abundance, suggesting that these factors do not influence parasite infection in this system. Older deer mice have higher parasite group richness and higher total parasite abundance than younger mice. This appears to be driven by differences in dispersal among different parasite groups. Infection by parasite taxonomic groups was not consistent with predictions, specifically with ectoparasite groups. Tick infection was significantly correlated with body mass, while lice were not correlated with mass, contrary to predictions. Flea infection was not correlated with age, which was consistent with predictions. Finally, the abundances of parasite taxonomic groups are independent of each other, further suggesting that parasite infection within hosts is cumulative. These results suggest that host age and dispersal differences among taxonomic groups are important in determining parasite community structure in deer mice. Acknowledgements This manuscript will be submitted for publication with Sarah Bush. I would like to thank Hector Zumaeta, Matthew Talmage, William Reynolds, Scott Ripple, and Brandy Mills for their assistance dissecting rodents for helminths and collecting ectoparasites. 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Long (L) refers to parasites being associated with their hosts for long period of time (several weeks to months). Group Free-living stage off the host Transmitted through ingestion Fleas X S Ticks X S Lice Time spent with host L Nematodes X L Cestodes X L Acanthocephalans X L Trematodes X L Permanent parasite X 34 Table 2.2. The prevalence and mean intensity (± se) of ectoparasites and endoparasites found in 525 deer mice. The prevalence of coinfections is also shown. Prevalence Mean intensity ± se Fleas 0.63 2.99 ± 0.15 Ticks 0.29 4.94 ± 0.20 Lice 0.28 6.08 ± 0.99 Ectoparasite group coinfections 0.33 NA Nematodes 0.28 16.39 ± 3.45 Cestodes 0.09 2.16 ± 0.49 Trematodes 0.008 2.75 ± 1.18 Acanthocephalans 0.025 4.15 + 1.72 Endoparasite group coinfections 0.04 NA 0.51 NA Ectoparasites Endoparasites All coinfections* * Animals coinfected with individuals from at least two different parasite groups 35 Table 2.3. Summary of GLMs for parasite group richness with a Poisson distribution (A) and total parasite rank sum (B) for the different habitat types. (A) Generalized linear model with a Poisson distribution for parasite group richness and the different habitat types. Intercept is set at ecotone. estimate standard error z-value p-value Intercept -0.102 0.171 -0.598 0.55 Sagebrush 0.021 0.265 0.078 0.94 Pinyon-juniper 0.311 0.215 1.447 0.15 (B) Generalized linear model with a Poisson distribution for total parasite rank sum and the different habitat types. Intercept is set at ecotone. estimate standard error z-value p-value Intercept 1.72 0.036 47.974 < 0.001* Sagebrush 0.097 0.054 1.798 < 0.001* Pinyon-juniper 0.32 0.043 7.686 0.07 * p-value significant at 0.05 36 Table 2.4. Summary of GLMMs for parasite group richness with poisson distribution for 494 mice over seven sampling locations. Separate models were run for body mass (A) and body condition (B). (A) Generalized linear mixed model for parasite group richness and body mass with intercept is set at mean mouse mass. standard Random effect variance deviation Mountain range 0.014 0.118 estimate standard error z-value p-value Intercept 0.432 0.067 6.482 <0.001* Mass (g) 0.030 0.010 3.113 0.001* Fixed effect (B) Generalized linear mixed model for parasite group richness and body condition with intercept is set at mean mouse body condition. standard Random effect variance deviation Mountain range 0.018 0.133 estimate standard error z-value p-value Intercept 0.455 0.070 6.500 < 0.001* Body condition 0.016 0.015 1.087 0.28 Fixed effect * p-value significant at 0.05 37 Table 2.5. Summary for GLMMs for total parasite rank sum with Poisson distribution for 494 mice over seven sampling locations for body mass (A), body condition (B) (A) Generalized linear mixed model for total parasite rank sum with poisson distribution and intercept set at mean body mass. Random effect variance standard deviation 0.221 0.470 estimate standard error z-value p-value Intercept 2.031 0.179 11.32 < 0.001* Mass (g) 0.017 0.005 3.46 < 0.001* Mountain range Fixed effect (B) Generalized linear mixed model for total parasite rank sum with poisson distribution and intercept set at mean body condition. Random effect variance standard deviation 0.231 0.480 estimate standard error z-value p-value Intercept 2.039 0.183 11.132 < 0.001* Body condition -0.001 0.007 -0.078 0.94 Mountain range Fixed effect * p-value significant at 0.05 38 Table 2.S1. Summary of GLMs for parasite group richness with a Poisson distribution (A) and total parasite rank sum with a Poisson distribution (B) for the seven sampling locations. (A) Generalized linear model with a Poisson distribution for parasite group richness and the seven sampling locations. Intercept is set at the Cedar Mountains. estimate standard error z-value p-value Intercept -0.916 0.374 -2.449 0.014* Stansbury Mountains 1.318 0.398 3.308 <0.001* Oquirrh Mountains 0.660 0.409 1.613 0.11 San Francisco Mountains 2.303 0.746 3.086 0.002* Dolly Varden Mountains 1.253 0.558 2.245 0.025* Toano Range 0.654 0.563 1.162 0.25 Pilot Range 1.179 0.563 2.094 0.036* (B) Generalized linear model with a Poisson distribution for total parasite rank sum and the seven sampling locations. Intercept is set at the Cedar Mountains. estimate standard error z-value p-value Intercept 0.082 0.162 0.507 0.612 Stansbury Mountains 0.496 0.170 2.924 0.003* Oquirrh Mountains 0.251 0.176 1.425 0.15 San Francisco Mountains 0.675 0.240 2.815 0.005* Dolly Varden Mountains 0.477 0.224 2.132 0.033* Toano Range 0.337 0.234 1.441 0.15 Pilot Range 0.366 0.233 1.573 0.12 * p-value significant at 0.05 39 Table 2.S2. Summary for generalized linear models for fleas (A), ticks (B), lice (C), nematodes (D), and cestodes (E) separately with binomial distributions for 494 mice over seven sampling locations. (A) Generalized linear model for tick infection with binomial distribution and intercept set at mean mouse mass. estimate standard error t-value p-value Intercept -0.879 0.100 -8.823 < 0.001* Mass (g) 0.053 0.027 1.956 0.051* (B) Generalized linear model for flea infection with binomial distribution and intercept set at mean mouse mass. estimate standard error t-value p-value Intercept 0.535 0.094 5.703 < 0.001* Mass (g) 0.025 0.025 0.999 0.32 (C) Generalized linear model for louse infection with binomial distribution and intercept set at mean mouse mass. estimate standard error t-value p-value Intercept -0.922 0.101 -9.161 < 0.001* Mass (g) -0.044 0.0268 -1.633 0.10 (D) Generalized linear model for nematode infection with binomial distribution and intercept set at mean mouse mass. estimate standard error t-value p-value Intercept -0.916 0.102 -8.978 < 0.001* Mass (g) 0.111 0.0281 3.939 <0.001* (E) Generalized linear model for cestode infection with binomial distribution and intercept set at mean mouse mass. estimate standard error t-value p-value Intercept -2.621 0.186 -14.099 < 0.001* Mass (g) 0.133 0.048 2.764 0.006* * p-value significant at 0.05 40 Table 2.S3. Summary for generalized linear models for parasite associations with quasiPoisson distribution for 494 observations over seven sampling locations. Generalized linear model for flea abundance with quasi-Poisson distribution. estimate standard error t-value p-value Intercept 0.651 0.070 9.342 < 0.001* Tick 0.004 0.0142 0.285 0.78 Lice -0.006 0.011 -0.589 0.56 Nematodes -0.004 0.004 -1.109 0.27 Cestodes 0.044 0.101 0.438 0.66 Generalized linear model for tick abundance with quasi-Poisson distribution. estimate standard error t-value p-value Intercept 0.333 0.166 2.001 0.046* Fleas 0.013 0.147 0.273 0.76 Lice 0.005 0.015 0.343 0.73 Nematodes 0.002 0.004 0.476 0.63 Cestodes 0.124 0.175 0.705 0.48 Generalized linear model for louse abundance with quasi-Poisson distribution. estimate standard error t-value p-value Intercept 0.661 0.228 2.899 0.0039* Fleas -0.048 0.078 -0.622 0.53 Ticks 0.016 0.037 0.436 0.66 Nematodes 0.004 0.005 0.811 0.42 Cestodes -1.106 1.082 -1.022 0.31 41 Table 2.S3 continued. Generalized linear model for nematode abundance with quasi-Poisson distribution. estimate standard error t-value p-value Intercept 1.767 0.272 6.505 < 0.001* Fleas -0.142 0.117 -1.219 0.22 Ticks 0.024 0.040 0.598 0.55 Lice 0.014 0.017 0.821 0.41 Cestodes -0.845 1.072 -0.788 0.43 Generalized linear model for cestode abundance with quasi-Poisson distribution. estimate standard error t-value p-value Intercept -2.031 0.276 -7.365 < 0.001* Fleas 0.035 0.069 0.510 0.61 Ticks 0.033 0.037 0.878 0.38 Lice -0.269 0.200 -1.342 0.18 Nematodes -0.031 0.042 -0.721 0.47 * p-value significant at 0.05 42 Figure 2.1. Map of sampling sites in Utah and Nevada. Diamonds represent mountain ranges (locations) that were sampled. Inset: The Cedar Mountains were sampled at two sites (ecotone and P-J habitat types). The Stansbury Mountains and Oquirrh Mountains each consisted of two locations, and each location was sampled at three habitat types (sagebrush, ecotone, and P-J). 43 Figure 2.2. Number of parasite groups and parasite rank sum for the different habitat types. A) Mean number of parasite groups per mouse in the three habitat types. The three habitats did not significantly differ. B) Mean total parasite rank sum per mouse for each habitat type. Different letters indicate significant differences between habitat types. Mice in pinyon-juniper had significantly more parasites than mice from sagebrush and ecotone habitats. 44 Figure 2.3. Mass and body condition of deer mice and their relationship to the number of parasite groups and total parasite rank sum. A) Three age classes (juvenile, subadult, and adult) of deer mice (Peromyscus maniculatus) and the associated masses of individuals within those classes. N=40 for each class. Age classes of mice were based on pelage color after capture in the field. Different letters indicate significant differences. B) The number of parasite groups within each individual mouse and the associated mass of that mouse. Age class delineations were based on masses in A. There was a significant positive correlation between number of parasite groups and mouse mass (GLMM: z = 3.113, p = 0.001). C) Number of parasite groups and associated body condition of each mouse. There was no significant correlation between number of groups and body condition (GLMM: z = 1.087, p = 0.28). D) Total parasite rank sum index (abundance) and the relationship to body mass. Total parasite abundance was significantly correlated with body mass (GLM: z = 7.932, p < 0.001). The data are jittered in B and C along the y-axis to see more of the data. 45 Figure 2.4. The relationships between mouse mass and the infection status (infected/not infected) for fleas (A), ticks (B), lice (C), nematodes (D), and cestodes (E). Tick, nematode, and cestode infection were significantly correlated with mouse mass. The data are jittered along the y-axis to see more of the data. 46 Figure 2.S1. Mean mass of mice in the three habitat types. Different letters indicate significant differences. Mice in pinyon-juniper had significantly higher masses than in sagebrush and ecotone habitat types. CHAPTER 3 HISTOLOGICAL SURVEY OF DISEASES AND PARASITES OF WILD RODENTS IN THE GREAT BASIN Abstract Wild animals have diseases caused by both infectious and non-infectious agents. In wild populations, non-infectious diseases are typically less understood than transmission dynamics of parasites and pathogens (e.g. helminthes, bacteria, viruses). However, non-infectious diseases can reduce host fitness and can also affect a host's ability to deal with infectious disease. Consequences of multiple infections within a host are beginning to receive attention because of the combined effects on host recovery, susceptibility, and fitness. Here, histology is used to survey tissues of rodents in the Great Basin to document baseline levels of pathology caused by both infectious and noninfectious agents. This method was also used to determine if parasites are being overlooked during routine parasitological surveys of rodents. Ten species of rodents were trapped and euthanized at five sites in Utah and Nevada. Liver, lung, heart, and kidney tissues were examined using histology. Results show that only two pathogenic diseases were found: hepatic capillariasis caused by the nematode Capillaria hepatica and adiaspiromycosis caused by the fungus Emmonsia crescens. These diseases were rare. Thirty-one percent of rodents were found to have diseases that were either non-infectious in origin or had unknown causes (e.g. inflammation). The most common disease was 48 extramedullary hematopoiesis (11%). Introduction Wild animals often have disease, whether caused by infectious agents (e.g. parasites and pathogens), non-infectious agents (e.g. environmental contaminants and toxins), or factors related to animal physiology (e.g. genetic defects and nutrition) (Daszak et al. 2000; Wobeser 2006). The most widely studied diseases in wild populations, infectious diseases, reduce the fitness of their hosts (Moller et al. 1990; Hudson et al. 2002; Knowles et al. 2013) and are involved in structuring ecological communities (Dobson and Hudson 1986; Hudson et al. 2002). Diseases have implications for conservation as well as for humans, such as the increased emergence of zoonotic diseases (McNamara 2015) and diseases threatening livestock (Bennett 2003). Recent work has focused on the importance of studying entire parasite and pathogen communities, instead of focusing on one or two species in isolation (Pedersen and Fenton 2006; Ferrari et al. 2009; Telfer et al. 2011). Interactions among parasites and pathogens affect transmission, disease severity, disease recovery, and susceptibility to other parasites and pathogens (Ferrari et al. 2009; Telfer et al. 2011). However, noninfectious diseases can influence the ability of an animal to deal with infectious disease and can alone act to reduce host fitness (Dmowski et al. 1998; Wobeser 2006; AcevedoWhitehouse and Duffus 2009; Tete et al. 2014). Non-infectious diseases are important to consider under the framework of parasite community ecology. Several factors are known to cause non-infectious disease in animals, including poor nutrition, environmental change, and environmental contaminants (Wobeser 2006; Acevedo-Whitehouse and Duffus 2009). For example, contaminants from zinc smelters 49 cause significant disease in wild bank voles and wood mice that live near them (Dmowski et al. 1998; Tete et al. 2014). Moreover, mercury (Dietz et al. 1996; Renzoni et al. 1998; Wadaan 2006) and lead (Fair and Myers 2002; Beier et al. 2013; Tete et al. 2014) are known to cause various states of disease in marine and terrestrial animals. Various states of disease can occur from tissue pathology to declines in general body condition (Van Saun 2005; Beldomenico and Begon 2009). For example, lead poisoning in birds causes anemia, paralysis, and histopathological lesions, including tissue necrosis, kidney degeneration, and encephalopathy (Golden et al. 2016). Mercury is known to cause severe liver and kidney damage in mammals, birds, and fish (Mela et al. 2007; Dardouri et al. 2016; López-Islas et al. 2017). To understand these interactions, and to understand how they may change over time, a baseline knowledge of infectious and non-infectious disease is needed in a study system that allows for large sample sizes from a variety of habitat types. Baseline data on disease can be used to assess changes to environmental conditions (Dietz et al. 1996; Plowright et al. 2008). Without sufficient baseline data for comparison, finding causes of disease and assessing the success of control efforts may not be achievable (Plowright et al. 2008; Artois et al. 2009). In addition, emerging diseases in wild populations cannot be properly identified without information on whether certain diseases have, in fact, increased in prevalence (Artois et al. 2009). In this study, rodents are sampled in the Great Basin. Histology is the technique of examining tissues microscopically to identify disease at the cellular and tissue level. Thin slices of tissues are stained to visualize cellular components and then examined under a microscope. Histology is often used to 50 document diseases of both infectious and non-infectious origin in humans or domestic animals (e.g. inflammation, tissue damage, chronic disease, cancer) (Kierszenbaum and Tres 2012). This technique can also detect parasites and pathogens in tissues that are not easily dissected, such as lung, liver, and kidney tissue. Histology has long been used to find parasite stages too small to see during dissection like helminth eggs and larvae, especially in veterinary medicine (Gardiner and Poynton 1999). Helminths can be identified to species based on morphology of the parasite within tissues (Gardiner and Poynton 1999). Histology is a useful tool, both to diagnose pathology and to find parasites in animal tissues. The goal of the present study is to survey wild rodents for diseases caused by both infectious and non-infectious agents in the Great Basin using histology. Another goal of this study is to determine if there are parasites and pathogens that are being missed by standard parasitological dissections of rodents in the Great Basin. Here, the terms disease and pathology are used interchangeably to refer to a disease state in an animal whether or not that disease is caused by a parasite, pathogen, or by non-infectious sources. The focus of this study is to examine and survey heart, liver, lung, and kidney tissues. Materials and methods Rodents trapping Rodents were trapped in the Great Basin of Utah and Nevada from May 2014 through September 2014. Rodents were captured at five sites (Fig. 3.1). Three sites were located in Nevada and two were located in Utah. Each site was dominated by pinyonjuniper woodland. The San Francisco Mountain site in southern Utah was half pinyonjuniper, half mountain mahogany (Cercocarpus spp.). Rodents were live-trapped using 51 Sherman traps (H.B. Sherman Traps, Inc.). Traps were placed in straight line transects five to ten meters apart. Twenty-five traps were placed in each transect. Some sites required two or three transects to capture the target number of deer mice. Traps were baited with whole oats and bird seed. Traps were placed under logs, by sagebrush plants, and under juniper trees. Traps were set in the evening and checked the following morning. Traps were also checked one to two times during the day for diurnal species (Tamias spp. and Microtus spp.). Once captured, each animal was euthanized using isoflurane and identified to species. Rodent identifications were confirmed by E.A. Rickart (Natural History Museum of Utah). All individuals regardless of age class were kept. Trapping stopped once 25 deer mice (Peromyscus maniculatus) were captured and euthanized. Rodent species other than P. maniculatus were also kept and processed. All animal handling and processing was approved by the Institutional Animal Care and Use Committee of the University of Utah. Rodent processing Most animals were processed in the field. Animals were sexed, weighed, and standard museum measurements were taken (body length, tail length, ear length, and leg length). The abdominal cavity of each animal was cut open using scissors. The organs, including the heart, lungs, kidneys, and liver, were removed and placed in either 10% neutral-buffered formalin or 95% ethanol before being processed for histology. Formalin is the standard method for preserving (fixing) organs for histology. Placing organs in 95% ethanol also preserves them for histology. Ethanol has the added advantage of preserving samples so that they can be used for the identification of parasites using molecular methods. This is important if parasites are not able to be identified by 52 morphology (D. Gardiner, personal communication). Animals not dissected in the field were placed on ice and brought back to the lab. Their organs were processed the same day they were captured. After processing, animals were deposited at the Natural History Museum of Utah in Salt Lake City, UT. Histology and diagnosis In the lab, the fixed organs (liver, lungs, heart, and kidneys) were removed from either the formalin or ethanol solution. In some cases, the adrenal glands were still attached to the kidneys and also examined, as described below. Each organ was cut into thin slices (about the width of a nickel) using a scalpel and placed in plastic cassettes. The following procedures were performed at a veterinary pathology clinic (Animal Reference Pathology, Salt Lake City, UT). All the organs for a single individual rodent were in one cassette. Tissues were processed as follows. Tissues were dehydrated to remove most of the water. Tissues were added to a series of ethanol solutions as follows: 70% ethanol for 15 minutes, 90% ethanol for 15 minutes, 100% ethanol for 15 minutes, 100% ethanol for 15 minutes, 100 % ethanol for 30 minutes, and a final 45 minutes in 100% ethanol. After the water was removed, the ethanol was "cleared" by placing tissues in a series of xylene solutions. They were placed in xylene for 20 minutes, removed, and placed in xylene for another 20 minutes. Tissues were removed and placed in xylene for another 45 minutes. Tissues were then removed from the final xylene solution and infiltrated with paraffin wax to completely replace the xylene. The tissues were placed in wax for 30 minutes, followed by another 30 minutes, followed by 45 minutes, changing the wax in between baths. 53 Once tissues were infiltrated with wax, the entire cassette was then embedded (blocked out) in paraffin wax by placing the cassette in a mold. The block was left to harden. The embedded organs were then cut with a microtome and placed on glass slides. All the organs for a single individual were in one block of wax and were on one slide. Slides were stained with hematoxylin and eosin to visualize cellular components during histological evaluation. The standard protocol for this staining method was followed (Fischer et al. 2008). Tissues were examined for evidence of pathology caused either by parasites, pathogens, or non-infectious agents. Each pathology found was identified and described. Parasites and pathogens found were identified to species. Tissue examination and identification of any pathology was performed by a veterinary pathologist (Dr. David Gardiner, Animal Reference Pathology, Salt Lake City, UT). Results Rodent sampling We trapped 143 rodents belonging to ten species in five locations in Utah and Nevada (Table 3.1; Fig. 3.1) from a combined total of 889 trap nights. The most abundant rodent species caught was the deer mouse Peromyscus maniculatus (n=116), and was the only species trapped at all five locations. Twenty-five deer mice were captured in four out of the five locations. Only 16 deer mice were captured in the San Francisco Mountains in southern Utah (Fig. 3.1). Other species trapped included P. truei (n=10), Perognathus parvus (n=2), Tamias dorsalis (n=8), T. minimus (n=1), Neotoma lepida (n=1), N. cinerea (n=1), Lemmiscus curtatus (n=2), Microtus montanus (n=1), and M. longicaudus (n=1). 54 Histology results Thirty-one percent (44/143) of all the rodents surveyed had at least one disease found using histology. Twenty-eight percent (33/116) of deer mice (P. maniculatus) had at least one disease, and only four animals had more than one type of disease. The diseases found using histology varied among rodent species (Table 3.1). Only two diseases were found that were caused directly by parasites and pathogens using histology and these pathogens were identified to species. The eggs of the nematode species Capillaria hepatica were found in one deer mouse causing hepatic capillariasis (Table 3.1, Fig. 3.2B). Four individuals were infected with the pathogenic fungus Emmonsia crescens, resulting in adiaspiromycosis (Table 3.1, Fig. 3.2A). The fungus was found in two Peromyscus maniculatus hosts, one Microtus montana, and one M. longicaudus. Three of these rodents were from the Stansbury Mountains. Other diseases found in rodents were all diseases for which either the causative agent was unknown or was a non-infective pathology (Table 3.1). Pathology was found in the lungs, liver, and kidneys. The only organ to show no pathology was the heart. Forty-eight individuals had their adrenal glands examined as well, with only one deer mouse (2%) showing an abnormality. Pathologies ranged from mild mineralization in the liver to mild chronic inflammation in the kidneys. The most prevalent pathology was extramedullary hematopoiesis (EMH) (12%) followed by hyperplastic bronchial associated lymphoid tissue (BALT) (6%, Table 3.1; Fig. 3.3). All the diseases listed in Table 3.1 as unknown could be caused by pathogens or caused by something noninfectious. These pathologies could be caused by bacterial infections or by some other underlying cause, such as injury to the tissue or environmental contaminants. 55 Discussion Wild rodents were surveyed for disease in the Great Basin using histology. The survey yielded several pathologies in rodents, some caused by pathogens, while others were non-infectious. The causes of several diseases were not able to be determined based on histology. Only one individual out of 143 rodents captured had a disease known to be caused by a parasite. The eggs of the helminth Capillaria hepatica were found in the liver of one deer mouse (P. maniculatus). This species of nematode is typically found in the liver of their hosts but is generally not found in deer mice in the Great Basin (Frandsen and Grundmann 1961; Grundmann et al. 1976). Peromyscus maniculatus is a host of C. hepatica, but seems to be much more prevalent in other parts of it range (Freeman and Wright 1960; Solomon and Handley 1971; Meagher 1999). The larvae are ingested and immediately migrate to the liver where they become adults and lay eggs throughout the liver (Wright 1961; Ceruti et al. 2001). Without histology of the liver, C. hepatica eggs would have been missed. Whether C. hepatica eggs are typically found throughout the entire liver or just a small section should be further investigated. It is unclear if these eggs would have been seen if the right tissue section was not examined. Results suggest that during routine parasitological surveys of rodents in the Great Basin, helminths are not being missed in heart, lung, or kidney tissue at least in deer mice, the most sampled species. Histology of P. maniculatus tissue in other parts of its range may yield different results regarding both pathologies present and parasites and pathogens infecting other tissues, such as liver flukes in northern parts of their range (Malek 1977). Four rodents were infected by the fungus Emmonsia crescens. It was found in 56 three rodent species, P. maniculatus, Microtus longicaudus, and M. montana. This species of fungus, along with two congeneric species, E. parva and E. pasteuriana, can infect humans causing the disease adiaspiromycosis. This disease is generally not harmful to humans; most infected individuals show no signs or symptoms. However, under certain conditions, such as in immunocompromised patients, it can cause respiratory failure, lung granulomas, and skin disease (Kamalam and Thambiah 1979; Bambirra and Nogueira 1983; Anstead et al. 2012). These fungal pathogens are known to infect P. maniculatus in Canada (Dowding 1947; Bakerspigel 1968), but it is unclear whether Emmonsia spp. are prevalent in Great Basin rodents. Grundmann and Tsai (1967) state that these species appear to be widespread in Great Basin rodents, but do not show any data. Emmonsia crescens was found in one muskrat (Ondatra zibethicus osoyoosensis) captured in the Salt Lake Valley, Utah (Grundmann and Tsai 1967). Dissecting and examining the lungs of infected individuals to find small Emmonsia spp. spores may yield false negatives. Histology may more accurately diagnose fungal pathogens. Histological surveys will help determine which rodent species are reservoir hosts for the pathogen and release infectious spores in the environment. It is not clear how much lung tissue should be examined to minimize false negatives. Lungs are small organs, and one section of each lung is a high percentage of total tissue, unlike the liver. The false negative rate is generally low for lung tissue (personal communication, D. Gardiner). This survey may be the first to provide data on E. crescens in rodents in the Great Basin. Pathologies were documented in the lung, liver, and kidney tissue of rodents. We found no parasites or disease in the hearts of any rodent. Most pathologies found in 57 rodents were liver and kidney tissue diseases. A few diseases may have been caused by either infectious or non-infectious sources. Extramedullary hematopoiesis (EMH), hyperplastic BALT, pyelitis, interstitial nephritis, inflammation, and granulomas may be caused by infectious agents or arise from environmental causes or underlying health issues. In addition to pathogens, inflammatory diseases, such as pyelitis and interstitial nephritis, can be caused by other foreign substances or autoimmune diseases (Wobeser 2006). Extramedullary hematopoiesis can be caused pathogens or be the result of other underlying pathologies such as myelofibrosis, which is a bone disorder that affects the production of red blood cells (Kim 2010) One pathogen that may cause interstitial nephritis in kidney tissue of rodents is Leptospira spp., which causes leptospirosis. These pathogenic bacteria reside in kidneys and are transmitted in the urine (Shearer et al. 2014). Further research should test whether deer mice in the Great Basin are reservoirs of Leptospira spp. The most common reservoirs of these bacteria are currently believed to be deer, skunks, and raccoons (Shearer et al. 2014). Leptospira spp. can infect humans, resulting in potentially serious disease (Terpstra 2003). Few studies have documented the natural occurrence of Leptospira spp. in wild rodents (Yager et al. 1953; Cirone et al. 1978). Microparasites (bacteria, viruses, protozoa) are often found by analyzing blood. Pathogens in other areas of the body such as Leptospira spp. in the kidney may be missed using these methods (Bharti et al. 2003). We suggest targeted sampling and histology of kidney tissue followed by PCR-based screening methods to identify additional reservoir hosts in the Great Basin. Recording pathologies in wild populations from non-contaminated environments 58 can be used as a baseline for future studies. Assessing changes in populations as land-use changes or as contaminants are introduced can allow wildlife biologists to determine how wildlife is affected and will be affected in the future. Environmental change is known to cause various diseases in animals, often resulting in a decrease in fitness (AcevedoWhitehouse and Duffus 2009). A sudden increase in diseases in certain tissues or finding pathologies that were previously absent in certain populations can help assess the general health of these populations and aid in conservation. Disease information can inform management decisions as well as disease control and prevention, including diseases of human importance (McNamara 2015). For example, rodents are often key players for pathogens of human importance (e.g. Lyme disease, Hantavirus, Bartonella spp., Leptospirosis). Without knowledge of baseline levels of disease, identifying emerging diseases, whether caused by infectious or non-infectious agents, is challenging. Being able to rapidly and accurately assess populations for an increase in disease prevalence allows affective control measures to be put into place (Dietz et al. 1996; Plowright et al. 2008; Artois et al. 2009). For example, rodents suddenly showing high amounts of kidney disease caused by Leptospirosis spp. can be targeted for control, and these areas can be managed to reduce human exposure. We document several diseases in wild populations of rodents in the Great Basin. Whether the non-infectious diseases found were caused by contaminants, a decrease in animal health due to poor nutrition, or some other factor is unclear. Diseases caused by non-infectious agents can act to reduce host fitness and should be monitored in the future. 59 Acknowledgements This manuscript will be submitted for publication with Sarah Bush. I would like to thank Erik Poole for assistance in the field and Eric Rickart for help with rodent identifications. 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Small Ruminant Research 61:153-164. Wadaan, M. A. 2009. Effects of mercury exposure on blood chemistry and liver histopathology of male rats. Journal of Pharmacology and Toxicology 4:126-131. 63 Wobeser, G. A. 2006. Essentials of Disease in Wild Animals. John Wiley & Sons, Inc. New York City, New York. Wright, K. A. 1961. Observations on the life cycle of Capillaria hepatica (Bancroft, 1893) with a description of the adult. Canadian Journal of Zoology 39:167-182. Yager, R. H., W. S. Gochenour Jr, A. D. Alexander, and P. W. Wetmore. 1953. Natural occurrence of Leptospira ballum in rural house mice and in an opossum. Proceedings of the Society for Experimental Biology and Medicine 84:589-590. 64 Table 3.1. Diseases of rodents trapped in the Great Basin that were found using histology. The species affected for each disease is listed along with the prevalence (in parentheses). Disease/pathology Causative agent Organ Species affected (prevalence) Location(s) where pathology was found Hepatic capillariasis Parasitic nematode (Capillaria hepatica) liver Peromyscus maniculatus (1/116) Dolly Varden Adiaspiromycosis Fungal pathogen (Emmonsia crescens) lungs Peromyscus maniculatus (2/116) Microtus montanus (1/1) Microtus longicaudus (1/1) Dolly Varden Stansbury Mountains Lymphocytic infiltrates Noninfectious origin liver Peromyscus maniculatus (1/116) Dolly Varden Mineralization Noninfectious origin liver, kidneys Peromyscus maniculatus (4/116) Dolly Varden Toano Range San Francisco Mountains Abnormal adrenal gland morphology Noninfectious origin adrenal gland Peromyscus maniculatus (1/116) Dolly Varden Dolly Varden Toano Range San Francisco Mountains Stansbury Mountains Extramedullary hematopoiesis (EMH) Unknown liver, kidney, lung Peromyscus maniculatus (14/116) Tamias dorsalis (1/8) Neotoma lepida (1/1) Peromyscus truei (1/10) Pneumonia Unknown lungs Peromyscus maniculatus (1/116) Pilot Range lungs Peromyscus maniculatus (6/116) Peromysycus truei (1/10) Tamias dorsalis (2/8) Dolly Varden Toano Range San Francisco Mountains Stansbury Mountains Hyperplastic bronchial associated lymphoid tissue (BALT) Unknown 65 Table 3.1. continued Interstitial nephritis Unknown kidneys Peromyscus maniculatus (4/116) Pilot Range San Francisco Mountains Stansbury Mountains Dolly Varden San Francisco Mountains Stansbury Mountains Mild chronic pyelitis Unknown liver Tamias dorsalis (3/8) Peromyscus maniculatus (2/116) Tamias minimus (1/1) Peromyscus truei (1/10) Granulomas Unknown lung Peromyscus truei (1/10) Stansbury Mountains Unknown bile duct, liver Peromyscus maniculatus (1/116) Tamias dorsalis (1/8) Microtus longicaudus (1/1) Dolly Varden San Francisco Mountains Stansbury Mountains Inflammation Figure 1 66 Pilot Range Toano Range Dolly Varden Mountains Nevada Stansbury Mountains Utah San Francisco Mountains Fig. 3.1. Map of trapping locations in the Great Basin of Utah and Nevada. At each site, all rodents captured were euthanized and histology was performed. Trapping stopped once 25 deer mice (Peromyscus maniculatus) were trapped. 67 Fig. 3.2. Parasites found during histology in Peromyscus maniculatus. A) Eggs of Capillaria hepatica in the liver. B) Emmonsia crescens spore (fungus) in the lungs. 68 Fig. 3.3. Images of pathologies found in deer mice using histology (H&E stain). A) Severe interstitial nephritis of kidney tissue. B) Mild pyelitis in kidney tissue. C) Hyperplastic BALT in lung tissue. D) Extramedullary hematopoiesis in liver tissue. CHAPTER 4 SPECIES TURNOVER OF RODENTS FOLLOWING HABITAT CHANGE Abstract Estimating biodiversity and community composition is a fundamental goal of community ecology and is becoming an increasing priority as humans modify landscapes. Changes in species composition following environmental change over time and across environmental gradients is called species turnover. A delay in species responding to environmental change means that current diversity may not reflect the diversity that will ultimately be supported by the new environment. Here, changes in rodent community structure following environmental change are investigated. By comparing current diversity to diversity 60 years ago, we determine whether there is a diversity surplus or deficit in habitats that have recently converted to pinyon-juniper woodland (P-J). Rodents were trapped at seven replicate locations in the Great Basin. At each location, sagebrush, P-J woodland, and the ecotone between these two habitats were sampled. Historical data were compared to recent data at three sites that were converted from ecotones to P-J woodlands. Rodent diversity over space and over time showed different patterns. Simpson's diversity decreased from ecotones to P-J habitats, but remained the same or increased following P-J conversion over time. This suggests a diversity surplus; however, the P-J sites sampled spatially were recently converted to P-J woodlands as well, possibly underestimating the diversity that these sites can ultimately support. Moreover, more 70 species immigrated than underwent apparent extinction, but immigrating species were rare, suggesting an immigration credit, specifically a lag in abundance. Measures of rodent diversity following woodland conversion may underestimate the diversity that will ultimately be supported by the new habitat. We highlight the importance of documenting historical habitat type to make inferences about time lags in diversity. Introduction A fundamental goal of community ecology is estimating biodiversity and species composition. Predicting changes in biodiversity after environmental change is increasing in priority due to an increase in land use change by humans (Folley et al. 2005; Sillmann et al. 2013; Ehrlen and Morris 2015). As environments are altered, species respond by expanding or contracting their ranges, which results in species turnover. When distributions of species shift, new assemblages of species are formed (Fagan et al. 1999), which can have drastic effects on ecosystem function (LoGiudice et al 2003; Larsen et al. 2005). Local species extinction and species immigration are two primary forces driving species turnover and shape the composition of the new community (Jackson and Sax 2010). The number of species affected and the time it takes for them to respond can have management and conservation implications (Kuussaari et al. 2009). In addition to change over time, species turnover also refers to changing community composition as a function of distance between sampling sites or across habitat gradients (Condit et al. 2002; Qian and Ricklefs 2012; LaManna et al. 2015). Species turnover temporally and spatially is mostly driven by habitat preferences, food availability, and interspecific interactions such as competition and predation (Douglas 1989; Peterson et al. 2002; Qian and Ricklefs 2012; LaManna et al. 2015). Here, using 71 historical data, species diversity and species composition is investigated over time and across a habitat gradient to determine species turnover following environmental change. Species vary in their responses to environmental change. Some species respond rapidly, while others are delayed, causing transient patterns of diversity. A delay in local species extinction is the "extinction debt", which refers to the species doomed to become extinct (Jackson and Sax 2010; Halley et al. 2016). Conversely, the species that will eventually immigrate to the area is the "immigration (or colonization) credit" (Jackson and Sax 2010). Immigration credit is different than the similar concept of species credit, which is used to refer to the number of species that will benefit from restoring habitat that was altered (Lira et al. 2012). Different rates at which species become locally extinct and immigrate can cause either a diversity surplus or a diversity deficit until the "biodiversity ledger" can be balanced (Jackson and Sax 2010; Essl et al. 2015). Understanding these time lags (or relaxation times) can help determine whether biodiversity is being underestimated or overestimated following a change in the environment (Jackson and Sax 2010; Hylander and Weibull 2012; Essl et al. 2015). Most studies examining changes in biodiversity suggest that extinction debt is much more common than immigration credit (Ford et al. 2009; Cousins and Vanhoenacker 2011; Dullinger et al. 2012; Bommarco et al. 2014). A common type of environmental change is habitat change. Modifications to the size, productivity, structure, and connectivity of habitats cause species to immigrate or disappear (Fritts and Rodda 1998; Kaspari 2000; Fahrig 2003; Jackson and Sax 2010; Haddad et al. 2015; Hanski 2015; Almeida-Gomes et al. 2016). One example of habitat change is the gradual conversion of savannah and shrublands to dense woodlands 72 (Margolis 2014). Woody plant conversions began approximately 150 years ago and are happening around the world. For example, tree cover increased significantly over nearly 70 years in South Africa (Wigley et al. 2010), and there has been a 42% increase in closed forests in savannas from 1947 to 1997 in northern Australia (Brook and Bowman 2006). These conversions are also documented in Europe (Barbaro et al. 2001) and South America (Cabral et al. 2003). A combination of climate change, overgrazing, changing fire regimes, and increased CO2 are hypothesized to be drivers of woodland conversions (McPherson et al. 1988; Archer et al. 1995; Van Auken 2000; Weisberg et al. 2007; Clifford et al. 2011; Margolis 2014). Recruitment of woody species in shrublands changes ecosystem processes and occurs across entire landscapes (Allen and Breshears 1998; Beckage et al. 2008). In the Intermountain West, sagebrush steppe is being converted to dense pinyonjuniper woodlands (P-J), causing drastic changes to western ecosystems (West 1999). P-J woodlands are expanding their distribution and are increasing both upslope and downslope along mountain ranges (Blackburn and Tueller 1970; Weisberg et al. 2007; Bradley and Fleishman 2008). The majority of the expansion is downslope into sagebrush habitats, replacing shrubs and associated grasses (Blackburn and Tueller 1970; Van Auken 2000; Weisberg et al. 2007). Initially, habitat heterogeneity increases when these conversions begin, creating transition zones (ecotones). An increase in heterogeneity increases species diversity because more niches support more species (MacArthur and Wilson 1967; Freemark and Merriam 1986; Germano and Lawhead 1986; Kerr and Packer 1997; Tews et al. 2004). The gradual expansion of P-J woodlands is well documented in Utah and 73 surrounding states. One consequence of this expansion is the loss of sagebrush and associated plants and animals that rely on these habitats (Rowe et al. 2010; Santos et al. 2014), such as the greater sage-grouse (Centrocercus urophasianus) and the sage thrasher (Oreoscoptes montanus) (Crawford et al. 2004; Rottler et al. 2014). Most studies focus on charismatic species that are threatened or have rapidly declining population sizes due to P-J expansion. Studies also monitor wildlife responses after removing P-J associated trees (Bombaci and Pejchar 2016; Gallo et al. 2016). Few studies have addressed species turnover of rodent communities following P-J conversion. Here, changes in rodent species diversity and species composition following P-J conversion are investigated in the Great Basin. The following questions are addressed: 1) How does species diversity and community composition of rodents change over time and space over a sagebrush to P-J habitat gradient? 2) Is there a diversity surplus or deficit in recently converted P-J habitats? Two types of data are used. First, rodents are sampled in sagebrush, ecotone, and P-J habitats from 2014 to 2016 at seven replicate locations. Second, sites that underwent P-J conversion from the late 1950s and ‘60s are resampled and compared to historical rodent data. By sampling different habitat types, species composition within each habitat will identify habitat specialists and generalists. These data can be used to make predictions as to which species will become locally extinct or immigrate following P-J conversion. Comparing different habitats at the exact same location controls for sitespecific differences that cannot be controlled for when sampling different habitats over space. These two kinds of data can be used to document species turnover and to determine if there are lags in diversity following woody plant expansion. 74 Materials and methods Study locations Both historical and present sampling was conducted in the Great Basin of Utah. The Great Basin is a desert ecosystem with intermittent mountain ranges extending north to south. These montane-desert systems generally have the same vegetation across the region: valley desert, dominated by sagebrush (Artemesia spp.) transitioning into P-J woodland at higher elevations. Salt bush (Atriplex canescen) and several species of grasses are also present in sagebrush communities. An ecotone occurs between the sagebrush and dense P-J woodland at mid-elevations. At the highest elevations, other conifers including firs, spruces, and pines are dominant tree species. In dense P-J woodlands, Utah juniper (Juniperus osteosperma) and singleleaf pinyon pine (Pinus monophylla) are the predominate species (Banner 1992). These mountain ranges can be used as replicates for sampling because they have the same habitat gradients moving from low to high elevation: sagebrush, ecotones, and P-J woodlands. P-J woodlands and sagebrush have relatively homogenous vegetation, while the ecotone is made up of vegetation from both habitats and is more heterogeneous. P-J woodlands have very little understory vegetation (Fig. 4.1). Rodent sampling over the environmental gradient Rodents were trapped from 2014 to 2016 at eight locations in five mountain ranges in the eastern part of the Great Basin (Fig. 4.2). Trapping occurred from May to the beginning of October. At most sampling locations, three habitat types were sampled: sagebrush, P-J woodland, and the ecotone. All animals were trapped using Sherman live traps (H.B. Sherman Traps, Inc.). Traps were placed in transects with five to ten meters 75 between traps. One transect was placed in each habitat type at each location. Rodents are generally territorial and have relatively small home ranges. Traps were placed far enough into each habitat type (approx. 1 km) to ensure that the rodents trapped were not individuals from another habitat type that were foraging or searching for mates. Traps were baited with a mixture of whole oats and birdseed. The total number of traps placed each night was recorded to get total trap nights at each site. Trapped animals were processed in the field and in the lab. Once an animal was trapped, the contents of the trap were emptied into a plastic bag. The animal was then euthanized with isoflurane and put on ice until it was taken to the lab for further processing. Animals not euthanized were marked using an ear punch tool to identify recaptures and to avoid counting animals more than once. They were then released where captured. Fully processed animal carcasses were placed in formalin, followed by 95% ethanol, and deposited at the Natural History Museum of Utah. All animal handling and processing was approved by the Institutional Animal Care and Use Committee of the University of Utah. Historical sampling and site selection Small mammals were trapped and recorded throughout Utah from 1957 to 1968 by A. Grundmann and his students from the University of Utah (Frandsen 1960; Frandsen and Grundmann 1961; Derrick 1968). On average, each location was trapped for three days (Frandsen 1960; Frandsen and Grundmann 1961). All trapping occurred from May to September. Records were kept for all individuals trapped. A field notebook documenting sampling locations includes directions, site-specific details, and approximate elevations. A subset includes descriptions of habitat type. Six historical locations were found with habitat descriptions that included references to either 76 sagebrush, P-J woodlands, or a sagebrush-P-J mix. Aerial photographs were gathered from the USGS (earthexplorer.usgs.gov) from around the same time as sampling occurred to document historical vegetation. Specifically, we were interested in the percent cover of pinyon pine and juniper trees between 1957 and 1970. We used Google Earth to document current vegetation patterns. Both historical and recent images were used to compare P-J cover over time. Three of the six sites showed noticeable habitat differences over time. Two of these sites are located in the Stansbury Mountains (one sampled in 1957 and the other in 1968) and one site is located in the Deep Creek Mountains (sampled in 1960) (Fig. 4.2). Each site had sagebrush and associated vegetation and a low percentage of P-J cover (ecotones) in the late 1950s and 1960s, but converted to P-J woodlands over the last 50 years. The other three sites were used as control sites because they did not change habitat types over time. Two control sites were sampled in 1957 (Deep Creek Mountains and Stansbury Island) and one was sampled in 1964 (House Mountains). Two of the sites were and are still dominated by sagebrush (Deep Creek Mountains and Stansbury Island) and one was and is still a dense P-J woodland (House Mountains). P-J cover analysis ImageJ (Rasband 2016) was used to estimate the percentage of P-J cover at all sites sampled (Abramoff et al. 2004; Pérez and Pascau 2013). Each study site was located in Google Earth. Percent cover was estimated per hectare. Hectare square images were imported into ImageJ. Percent tree cover was estimated by measuring the area of all the trees in the image. The color threshold of each image was adjusted so that only trees were selected. We used a threshold cutoff determined by the smallest tree in the image. 77 Smaller areas selected were excluded because they were not trees and should not be included in the estimation of tree cover. The areas of all the trees were added up and divided by the total area of the one-hectare image to get percent P-J per hectare. Sagebrush sites had zero percent P-J cover (n = 6 sites). Ecotone sites had a mean ± SE of 11.8 ± 2.9% (n = 7 sites) P-J cover, while pinyon-juniper sites had 51.9 ± 4.5% (n = 7 sites) P-J cover. Historical aerial photographs obtained from USGS were used to calculate percent cover for the six sites with historical mammal data. One image from Derrick (1971) was used that was the exact sampling location of a P-J converted site in the Stansbury Mountains. The same methods were used as above to estimate percent P-J cover. Species composition and diversity analyses To determine whether the rodent community at each site was thoroughly sampled, species accumulation curves were produced. The number of species were plotted against the cumulative trap nights throughout the trapping period at each site. Species community composition and habitat preferences were determined by grouping all sampled sites by habitat type. Each species captured was considered occupying a habitat if it was captured in a habitat type in one of the seven replicate locations. If a species that was captured represented less than 1% of the individuals captured in each habitat type among all study locations, this species was considered "rare". Species were considered absent if they were not captured in a habitat type among all sampled locations. Species richness was compared among habitat types. The Chao richness estimator was used to estimate species richness for each site. The means ± SEs of the Chao 78 estimated richness were calculated for each habitat type (n = 7 for ecotone, n = 7 for P-J sites; n = 6 for sagebrush sites). A linear mixed model (LMM) was used to analyze differences in richness among habitat types. Because each location was sampled three times (sagebrush, ecotone, and P-J), location was included as a random effect in the mixed model, while habitat type was modeled as the fixed effect. The model was based on 20 observations from seven locations. Species abundance was used to measure the evenness of the species present. At each site, Simpson's D was calculated. We used a linear mixed model to determine if species diversity significantly differed among the three habitat types. Again, location was used as a random effect and habitat was the fixed effect, and this model was based on 20 observations from seven locations. Species diversity (Simpson's D) was also calculated for the three resampled sites separately. Statistical analyses for diversity and species richness were performed using the Vegan package (Oksanen et al. 2016) in R. Mixed models were run using the lme4 (Bates et al. 2015) and lmerTest (Kuznetsova et al. 2016) packages in R (R Core Team 2016). Historical community composition was compared to the data obtained from resampling. Species absent in both the historical and present sampling data were not included in the comparison between historical and present species composition. Only species that were present in at least one of the sampling time points (historical or present) were used to examine species turnover in response to habitat change over time. Historical data were used to document the number of sagebrush and P-J specialists in varying amounts of P-J cover. Results of the spatial sampling informed which species were specialists. Sixteen sites (both historical and current) were used to 79 determine the number of sagebrush and P-J specialists in varying amounts of P-J cover. Data from the six historical sites (three control, three P-J converted) and the data from resampling those sites were included in the analysis. Four more sites from the historical data were added to this analysis. These sites varied in P-J cover, but were not resampled in 2014-2016. Results Spatial distribution of rodents over an environmental gradient We sampled rodent communities at 21 different sites from seven locations. We captured 650 (n = 163 for sagebrush, n = 234 for ecotone, and n = 253 for P-J) individual rodents comprising 17 species over a combined 5,848 trap nights. The sagebrush site in the House Mountains was only trapped for one night (25 trap nights) and no individuals were trapped. This site was not included in any of the analyses. All other sites were sampled for a minimum of 60 trap nights. Most sites (17/20) had at least 150 trap nights. Species accumulation curves indicate that some sites were not thoroughly sampled (Fig. 4.S1). The Chao species richness estimator was used to estimate species richness at each site to control for differences in how thoroughly each site was sampled. The Chao estimated species richness significantly differed between sites. Specifically, P-J habitats and sagebrush significantly differed (LMM; t = -3.002, p = 0.015; Fig. 4.3A, Table 4.S1), but there was no significant difference between sagebrush and ecotones (LMM; t = 0.884, p = 0.40, Fig. 4.3A, Table 4.S1) or between ecotones and P-J (LMM; t = -2.223, p = 0.055; Fig. 4.3A). Species diversity (Simpson's D) differed significantly among habitat types. Species diversity of sagebrush sites did not significantly differ between ecotone (LMM; t 80 = -1.162, p = 0.27) and P-J sites (LMM; t = -1.162, p = 0.27; Fig. 4.3B; Table 4.S2). However, species diversity of ecotone sites was significantly higher than in P-J sites (LMM; t = -2.413, p = 0.03; Fig. 4.3B, Table 4.S2). The species present in each habitat type were compiled to determine habitat preferences (Fig. 4.4). Peromyscus maniculatus and Perognathus parvus were abundant in all three habitat types and are considered habitat generalists. Three species were present in all three habitat types, but were rare in one or more habitat types: these species were Dipodomys ordii, Lemmiscus curtatus, and Reithrodontomys megalotis. There were no species that are strictly found in ecotones, and a few species are sagebrush specialists. Most species are P-J specialists or found in both ecotones and P-J habitats (Fig. 4.4). Sagebrush and ecotone habitats are very similar (see Fig. 4.1); therefore, if a species was found in both sagebrush and ecotones, but not in P-J, they were considered sagebrush specialists. Several species are sagebrush specialists in these study areas, including Reithrodontomys megalotis, Tamias minimus, Ammospermophilus leucurus, Dipodomys microps, and Chaetodipus formosus. Peromyscus truei, Tamias dorsalis, Microtus montanus, Neotoma cinerea, and T. umbrinus, are P-J specialists. Temporal biodiversity Historical P-J cover was estimated and compared to the current P-J cover (Fig. 4.5). Sites that cross from the ecotone habitat to the P-J habitat over time are considered sites that underwent P-J conversion; those in the same habitat zone did not change over time. P-J cover of the three ecotone sites increased dramatically. In the late 1950s, these sites had a mean ± SE P-J cover of 7.6 ± 3.7%. Following P-J conversion, P-J cover increased to 53.9 ± 8.7%. In addition, two sites have zero percent P-J cover. These two 81 sites were used as control sites along with a P-J site because P-J cover did not change (Fig. 4.5). We compared historical species diversity (Simpson's D) to diversity in 2014-2016 at six sites, three that underwent P-J conversion and three that did not. In two of the three P-J conversion sites, Simpson's D values were similar (Fig. 4.6). The third site showed an increase in diversity. Species diversity of the two sagebrush control sites remained the same, while species diversity of the P-J control site increased (Fig. 4.6). We compared historical and recent species composition of rodents in the P-J converted sites. Two species, Peromyscus maniculatus and Perognathus parvus, are habitat generalists and are still present in P-J converted sites (Table 4.1). P-J specialists immigrated following P-J expansion, including Neotoma cinerea, Tamias umbrinus, Peromyscus crinitus, and Lemmiscus curtatus, but were low in abundance. Some of these species were absent in some recently converted sites. The P-J specialists Peromyscus truei and T. dosalis both increased in abundance (Table 4.1). Sagebrush specialists, Reithrodontomys megalotis and Tamias minimus, underwent apparent local extinction, while Microtus longicaudus decreased in abundance. In total, two of the eight species present in the 1950s were lost and four species immigrated following P-J conversion for a net increase of two species (Table 4.1). Most species in the two sagebrush control sites generally the same over time (Table 4.2). The species present historically and currently are all sagebrush specialists based on the spatial data and from published mammalian species accounts. In the P-J control site, P-J specialists T. dorsalis and P. truei were absent in the past, but are now present (Table 4.2). The sagebrush specialist A. leucurus and the generalist P. parvus 82 were present historically, but were absent when the P-J site was resampled. There is a significant negative correlation between P-J cover and sagebrush specialists (Spearman rank, rs = -0.64, p = 0.008; Fig. 4.7A). There is no significant correlation between P-J cover and P-J specialists (Spearman rank, rs = 0.35, p = 0.19; Fig. 4.7B). Discussion Rodents were trapped in 2014-2016 and compared to historical data to investigate changes in species composition and diversity after P-J conversion. Data gathered from sampling from sagebrush to P-J woodlands can be used to make predictions about which species should immigrate or disappear from the three P-J converted areas. Habitat specialists in sagebrush and in P-J can be identified based on habitat sampling. Species found ecotones and not P-J habitats were Reithrodontomys megalotis, Tamias minimus, and Ammospermophilus leucurus. We would predict that these species would decrease in abundance or go locally extinct following P-J conversion. In addition, T. dorsalis, P. truei, Neotoma cinerea, T. umbrinus, M. montanus, and P. crinitus are predicted to immigrate following P-J conversion since these species are either P-J or higher elevation specialists in our study sites. Two species appeared to go locally extinct in these areas (R. megalotis and T. minimus). Four species immigrated, most notably P. truei and T. dorsalis. Trapping results for one species were not consistent with its documented habitat preferences. Two R. megalotis were trapped at one P-J site. This species is generally found in grassy habitats and is very abundant in sagebrush and ecotones (Webster and Jones 1982). This site was a lower elevation site with less P-J cover (40%) than the other 83 P-J sites (51.9 ± 4.5%). Several species were trapped over the environmental gradient that were not trapped at the three P-J converted sites during either time point. Even though local species extinction or species immigration were not documented over time for these species, these data can be used to predict changes in their distributions following conversion. We predict that three species will be forced out of areas as juniper encroaches and begins to replace sagebrush and associated plants: Dipodomys microps, Chaetodipus formosus, and D. ordii. These species are often associated with desert grasses and shrubs (Carroll and Genoways 1980; Garrison and Best 1990; Hayssen 1991). We also predict the decline of Ammospermophilus leucurus because it is mostly found in shrubby areas and associated grasses (Belk and Smith 1991). This species can be found where juniper is present, but is much less abundant (Belk and Smith 1991). Based on our results, P-J woodlands may not support these four species. Data over both space and time can be used to determine whether there are any lags in diversity following habitat change in the Great Basin. Following P-J conversion, there were no sagebrush specialists observed being delayed in their apparent extinction. Within the span of 60 years, two species appear to be locally extinct in P-J converted sites, T. minimus and R. megalotis. In contrast, four species immigrated following P-J conversion and were rare (< 1% of captures in P-J converted areas). These data suggest an immigration credit and abundance lag (Essl et al. 2015) following P-J conversion. An abundance lag suggests that a species may have immigrated but is low in abundance, resulting in lower diversity values until abundance increases (Essl et al. 2015). Based on the results of the spatial sampling, P-J expansion was expected to cause 84 an increase in species richness. This was observed after resampling P-J converted if all three sites are combined (eight species in historical ecotones and ten species in current PJ). When these three sites are split up, two of the sites had the same species richness, while the third increased by two (Table 4.1). The diversity, measured by Simpson's D, showed different patterns over space vs. over time. Spatially, diversity was significantly less in P-J woodlands than in ecotone habitats, whereas over time, diversity either remained the same or increased. These data imply a diversity surplus, but based on the habitat preferences, we do not predict any more species will become locally extinct or decrease in abundance in P-J habitats. We do, however, predict that more species will immigrate and/or increase in abundance (depending on the species). Moreover, the other P-J sites sampled in this study might not have been P-J for very long since conversion is occurring throughout the Great Basin. This would underestimate diversity and make inferences about time lags difficult since the true diversity would be unknown. To find historical cover for these sites, aerial photographs were obtained of the three P-J sites not compared with historical data (Cedar Mountains and both locations in the Oquirrh Mountains) to estimate P-J cover at approximately the same time as the historical data were collected. In 1954, the Cedar Mountain site had 17% P-J cover. The P-J sites in the Oquirrh Mountains had 11% and 28% P-J cover. These sites underwent PJ conversion recently and may be still being paid the immigration credit. Studies investigating species turnover over space and time should consider the habitat of the same site historically. Sites may still lag behind the diversity values that can ultimately be supported, and make inferences about diversity difficult. Deficits in diversity have been documented following environmental change 85 (Walther et al. 2005; Piqueray et al. 2011; Hylander and Weibull 2012), and have mainly been recorded for plants. Lags in plant colonization are often attributed to slow dispersal, resulting in few opportunities to establish a viable population (Verheyen and Hermy 2004; Piqueray et al. 2011). Here, we show that relatively high dispersing animals also undergo lags in immigration and colonization. Our results suggest that reduced fitness and survival following P-J conversion may occur faster than dispersing from suitable habitat and establishing a viable population in the new habitat. One P-J converted site increased in diversity. This site was located in the Deep Creek Mountains and had the highest percent P-J cover historically out of the three P-J converted sites (14.5%). This site also has the highest P-J cover currently (65%). The conversion of this site started prior to the other two sites. The increase in diversity at this site was caused by a decrease in P. maniculatus and the immigration of P. truei (Table 4.1). Moreover, if there is an immigration credit, we would predict that the P-J control site would increase in diversity after being P-J woodland for the last 60 years. Our data are consistent with this prediction because diversity did, in fact, increase. Peromyscus truei and T. dorsalis were recent immigrants to this site. However, this is only one site, and this may be well within the normal fluctuation of this site. P-J expansion is gradual and species may respond only after a threshold of P-J cover is reached. Our results show that P-J specialists may be less responsive to P-J cover than sagebrush specialists. When P-J cover was 40 % or greater, no sagebrush specialists were found (Fig. 4.7). This was not as clear-cut for P-J specialists. Even at 60% P-J cover, there are one site with zero P-J specialists, despite P-J specialists being documented in this mountain range (Brown 1971; Rickart 2001). For instance, P. truei 86 was not trapped in the Stansbury B site even though P-J cover was high (Table 4.1). During P-J conversion, ecotones are created when juniper trees begin to colonize a new area, producing an initial increase in habitat heterogeneity (Blackburn and Tueller 1970). An increase in species diversity following an increase in habitat heterogeneity is expected and is documented for several free-living groups (MacArthur and Wilson 1967; Kerr and Packer 1997; Tews et al. 2004). In the present study, sagebrush and ecotone habitats did not significantly differ in terms of rodent species richness or diversity. Based on these results, going from sagebrush to ecotones is not predicted to result in an increase in species richness or diversity. The difference in vegetation between sagebrush and ecotone sites is small compared to the difference between ecotone and P-J sites. As juniper and pinyon pine dominate the landscape, the understory disappears. The loss of understory vegetation may play a major role in determining rodent composition. Shrubs and grasses provide cover and food for many rodent species occupying the Great Basin Desert (West 1983). We found significant differences in species diversity from ecotones to P-J woodlands. P-J woodlands are expanding (Bradley and Fleishman 2008), and these expansions are likely to continue in the future (Neupane and Powell 2015). Species turnover due to P-J conversion was documented over a time period of 50 years. We show that species immigration may take longer than apparent species extinction, leading to a diversity deficit. Species that immigrated following P-J conversion were rare or absent, suggesting that they are in the initial stages of immigration. The diversity over space vs. over time suggests a diversity surplus; however, the P-J sites sampled spatially were recently converted to P-J woodlands as well. Measures of rodent diversity following 87 woodland conversion may underestimate the diversity that will ultimately be supported by the new habitat. Rodent diversity is predicted to increase if the rare and/or absent rodent species increase in abundance or immigrate. Understanding species responses to environmental change is important for predicting future distributions and responses to unforeseen change at a time when land use is being altered at an alarming rate. Acknowledgements This manuscript will be submitted for publication with Sarah Bush. I would like to thank Eric Rickart for identifying and helping to process mammal specimens. I would also like to thank Dale Clayton, Scott Villa, Sabrina McNew, Emily DiBlasi, and Graham Goodman for helpful feedback during lab meetings. James Ruff provided valuable guidance on statistical analyses. This study was supported by the USA National Science Foundation Graduate Research Fellowship Program (GRFP-1256065) and a grant from the Global Change and Sustainability Center at the University of Utah. References Abràmoff, M. D., P. J. Magalhães, and S. J. Ram. 2004. Image processing with ImageJ. Biophotonics International 11:36-42. Allen, C. D., and D. D. Breshears. 1998. Drought-induced shift of a forest-woodland ecotone: rapid landscape to climate variation. Proceedings of the National Academy of Sciences 25:14839-14842. Archer, S., D. S. Schimel, and E. A. Holland. 1995. Mechanisms of shrubland expansion: land use, climate or CO2? Climatic Change 29:91-99. Barbaro, L., T. Dutoit, andP. Cozic, P. 2001. A six-year experimental restoration of biodiversity by shrub-clearing and grazing in calcareous grasslands of the French Prealps. Biodiversity and Conservation 10:119-135. Bates, D., M. Maechler, B. Bolker, S. Walker. 2015. Fitting linear mixed effects models using lme4. 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Thicket expansion in a South African savanna under divergent land use: local vs. global drivers? Global Change Biology 16:964-976. 94 Table 4.1. Abundance of each species at each site that was resampled after P-J conversion. In total, historical sites had eight species, and recently sampled sites had ten. Species Peromyscus maniculatus Perognathus parvus Microtus montanus Reithrodontomys megalotis Tamias minimus Microtus longicaudus Tamias dorsalis Peromyscus truei Tamias umbrinus Neotoma cinerea Peromyscus crinitus Lemmiscus curtatus Species Peromyscus maniculatus Perognathus parvus Microtus montanus Reithrodontomys megalotis Tamias minimus Microtus longicaudus Tamias dorsalis Peromyscus truei Tamias umbrinus Neotoma cinerea Peromyscus crinitus Lemmiscus curtatus Species Peromyscus maniculatus Perognathus parvus Microtus montanus Reithrodontomys megalotis Tamias minimus Microtus longicaudus Tamias dorsalis Peromyscus truei Tamias umbrinus Neotoma cinerea Peromyscus crinitus Lemmiscus curtatus Stansbury Mountains A (Historical ecotone) 103 0 0 7 8 17 2 0 0 0 0 0 Stansbury Mountains B (Historical ecotone) 24 3 0 1 0 0 0 2 0 0 0 0 Deep Creek Mountains (Historical ecotone) 84 2 1 0 3 0 0 0 0 0 0 0 Stansbury Mountains A (P-J) 31 0 1 0 0 1 2 4 0 0 0 0 Stansbury Mountains B (P-J) 28 5 0 0 0 0 1 0 0 0 0 1 Deep Creek Mountains (P-J) 40 0 0 0 0 0 1 12 1 1 1 0 95 Table 4.2. Abundance of each species captured at each site that was resampled for control sites. Species Peromyscus maniculatus Perognathus parvus Reithrodontomys megalotis Dipodomys microps Dipodomys ordii Ammospermophilus leucurus Neotoma leopida Chaetidopus formosus Species Peromyscus maniculatus Perognathus parvus Reithrodontomys megalotis Dipodomys microps Dipodomys ordii Ammospermophilus leucurus Neotoma leopida Chaetidopus formosus Species Peromyscus maniculatus Perognathus parvus Peromyscus truei Tamias dorsalis Ammospermophilus leucurus Stansbury Island (Historical sagebrush) 18 4 0 6 16 0 0 0 Deep Creek Mountains (Historical sagebrush) 11 2 0 1 0 0 4 4 House Mountains (Historical P-J) 24 1 0 0 1 Stansbury Island (Sagebrush) 8 14 0 0 6 0 0 0 Deep Creek Mountains (Sagebrush) 0 0 0 0 5 2 0 2 House Mountains (P-J) 2 0 14 1 0 96 Table 4.S1. Summary of mixed model results for estimated species richness for the three habitat types with 20 observations from seven locations. Linear mixed model for the Chao richness estimator with intercept set at sagebrush Random effect variance standard deviation Location 0.413 0.643 Variable estimate standard error t-value p-value Intercept 6.57 0.688 9.561 <0.001* Habitat - P-J 2.886 0.961 3.002 0.015* Habitat - ecotone 0.843 0.953 0.884 0.40 * indicates a p-value < 0.05 97 Table 4.S2. Summary of linear mixed effects model for species diversity for the three habitat types with 20 observations from seven locations. Linear mixed model for species diversity with intercept set at ecotone Random effect variance standard deviation 0.001 0.029 estimate standard error t-value p-value Intercept 0.543 0.055 9.836 < 0.001* Habitat - P-J -0.184 0.076 -2.413 0.03* Habitat - sagebrush -0.092 0.079 -1.162 0.27 Location Fixed effect * indicates a p-value < 0.05 DIAGRAM OF HABITAT GRADIENT SAMPLED AND HABITAT STRUCTURE 98 P-J Ecotone Sagebrush Fig. B.1.4.1. Diagram of sagebrush to P-J woodland habitat gradient sampled in the Great Figure Diagram of sagebrush to P-J woodland habitat gradient sampled in the Great Basin Basinwith withthe thetransition transitionzone zone(ecotone) (ecotone)between betweenthe thetwo twoprimary primaryhabitat habitattypes. types. Sagebrush Sagebrushisischaracterized characterizedby byhaving havingsagebrush sagebrushand andassociated associatedgrasses grassesand andno nojuniper juniper trees treesororpinyon-pine. pinyon-pine.P-J P-Jwoodlands woodlandsare aredense densewoodlands woodlandsofofjuniper juniperand andpinyon-pine pinyon-pinewith with very little understory. Ecotones have both P-J associated trees and an understory of very little understory. Ecotones have both P-J associated trees and an understory of sagebrush sagebrushand andgrasses. grasses.Most Mostofofthe thetrees treesininecotones ecotonesare aresmall smallcompared comparedtotothose thoseininP-J P-J woodlands. woodlands. 99 Figure 4.2. Map of recent and historical sampling sites in the Great Basin. Rodents were sampled over sagebrush to PJ woodlands at eight locations. In each location, three habitats were sampled (yellow, brown, and green). Circles represent recent sampling, and squares refer to historical sampling. Squares with circles inside denote sites that were resampled and the colors refer to the habitat types of the sites historically (outer square color) and recently (inner circle color). Figure 4 100 Present Absent Present but rare P-J Ecotone Neotoma cinerea Tamias umbrinus Peromyscus crinitus Microtus montanus Peromyscus truei Tamias dorsalis Neotoma lepida Chaetodipus formosus Microtus longicaudus Dipodomys microps Tamias minimus Ammospermophilus leucurus Dipodomys ordii Reithrodontomys megalotis Lemmiscus curtatus Perognathus parvus Peromyscus maniuculatus Sagebrush Figure 4.3. The habitat preferences for each species based on where they were captured. All seven sites (six for sagebrush) were pooled together. Species that were less than 1% of total captures for each habitat type were considered present but rare. Rodent species are arranged according to habitat preference. Left to right: generalists, found in sagebrush and ecotones, sagebrush specialists, found in ecotones and P-J, P-J specialists. Figure 5 Mean number of species ± SE 8 A 101 b 7 6 5 a ab 4 3 2 1 0 0.6 Sagebrush B Ecotone Pinyon-juniper a ab Simpson's D ± SE 0.5 b 0.4 0.3 0.2 0.1 0.0 Sagebrush n = 6 sites Ecotone Pinyon-juniper n = 7 sites n = 7 sites Figure 4.4. Species richness and species diversity for deer mice sampled in 2014 to 2016. A) Estimated species richness using the Chao richness estimator for the three habitat types. Different letters indicate significant differences between habitat types (P < 0.05). Sagebrush and P-J sites significantly differed for the Chao estimator. B) Species diversity significantly differs between ecotone and P-J habitat types. Sagebrush did not significantly differ between ecotone or P-J habitats. 102 80 Percent PJ cover 70 Habitat change No habitat change 60 50 40 30 Pinyon-juniper 20 10 Ecotone 0 Sagebrush Historical Present Figure 4.5. Percent pinyon-juniper (P-J) cover in six historically sampled sites when mammals were sampled in the late 1950s, and the percent P-J cover of the same sites sampled in 2014-2016. Sites that cross from one habitat zone to the next are considered sites that changed habitats. Those in the same habitat type did not change over time. Figure 6 103 1.0 Habitat change No habitat change = Sagebrush = Ecotone = Pinyon-juniper Simpson's D 0.8 0.6 0.4 0.2 0.0 Historical Present Figure 4.6. Species diversity (Simpson's D) of rodents in historically sampled sites in the 1950s and in 2014-2016. Four of the six sites had no change in diversity. The P-J control site and one P-J conversion site increased in diversity. Figure 8 # Sagebrush specialists A 104 4 3 2 1 0 B6 0 10 20 30 40 50 60 70 50 60 70 % P-J cover # P-J specialists 5 4 3 2 1 0 0 10 20 30 40 % P-J cover Figure 4.7. The number of sagebrush specialists (A) and P-J specialists (B) plotted against the percent P-J cover for 16 historical sites. There was a significant negative correlation between P-J cover and sagebrush specialists (Spearman rank, rs = -0.64, p = 0.008). There is no significant correlation between P-J cover and P-J specialists (Spearman rank, rs = 0.35, p = 0.19). Figure 2 Number of species 6 105 Sagebrush 5 4 3 2 1 0 0 100 200 300 400 500 600 Cumulative trap nights Number of species 7 Ecotone 6 5 4 3 2 1 0 0 200 400 600 800 Cumulative trap nights Pinyon-juniper Number of species 6 5 4 3 2 1 0 0 100 200 300 400 500 600 Cumulative trap nights Figure 4.S1. Species accumulation curves for all sites sampled in the Great Basin using cumulative trap nights for each site separated by habitat type. CHAPTER 5 IMPACT OF ENVIRONMENTAL CHANGE ON PARASITE COMMUNITIES Abstract Environmental change is occurring at unprecedented rates and is a threat to biodiversity worldwide. Negative consequences of environmental change are documented for free-living species, but little is known about how parasites will respond to environmental change. Here, we address the question, does parasitic helminth diversity change over time in the Great Basin? Deer mice (Peromyscus maniculatus) are sampled for helminth parasites in the Great Basin and compared to historical data from the late 1950s and ‘60s. Species diversity increased throughout the Great Basin over more than 50 years. This increase in diversity was mainly caused by a decrease in the prevalence and abundance of Syphacia peromysci, a direct life cycle nematode, and to a lesser extent, an increase in the number of helminth species. To investigate this pattern, we test whether pinyon-juniper (P-J) expansion or life cycle differences are responsible for these changes to helminth communities. Over the last 50 years, two sites changed from low to high P-J cover over the last 50 years and were resampled in the exact same spots. Both sites showed an increase in parasite diversity and a decrease in S. peromysci. However, recent sampling in low and high P-J cover sites did not result in the same patterns, suggesting that habitat change is not the main driver of these differences. Parasite species showing the most changes were ones with direct life cycles. In this system, direct life 107 cycle parasites are generally more host specific than complex life cycle parasites. Environmental change may impact direct life cycle parasites more than parasites with complex life cycles because of differences in host specificity. Introduction Climate change and associated environmental changes are a threat to biodiversity around the world (Travis 2003; Hansen et al. 2010; Sillmann et al. 2013). Climate change has profound effects on wildlife distributions, abiotic components of environments, and species interactions (Parmesan and Yohe 2003; Koh et al. 2004; Tylianakis et al. 2008 Van der Putten et al. 2010). Despite the considerable amount of data on how plants and vertebrates are and will be affected by environmental change (Walther et al 2002; Parmesan and Yohe 2003; Koh et al. 2004; Hamann and Wang 2006; Moritz et al. 2008), there is little empirical data on how parasites are or will be affected. Parasites are traditionally among the last groups to be investigated in ecological systems (Poulin 2007). However, parasites represent a large portion of the world's biodiversity (Price 1980; de Meeûs and Renaud 2002). Understanding how parasite species distributions and interactions will be affected can help predict changes to ecosystem processes and inform conservation decisions in a time of global change (Gomez and Nichols 2013). It is difficult to predict how parasites will respond to changing environmental conditions due to differences in life history characteristics and transmission dynamics (Rohr et al. 2011; Altizer et al. 2013). Most of the projected responses are the result of predictive models or experiments under laboratory conditions (Patz et al. 2002; Mouritsen et al. 2005; Studer et al. 2010; Altizer et al. 2013; Molnar et al. 2013a, 2013b; Bonnell et al. 2016; Hall et al. 2016). Rising temperatures will cause parasite populations 108 and distributions to increase because of increased production of infective stages and transmission rates (Harvell et al. 2002; Poulin 2006; Marcogliese 2008). In contrast, Lafferty (2009) suggests that parasites will likely shift their distributions, but there may be little net increase in area (i.e. no expansion or reduction in ranges). Moreover, hosts may undergo range shifts while their parasites lag behind (Phillips et al. 2010; Cizauskas et al. 2017). Developing predictions may depend on characteristics of the parasites themselves, such as life cycle and host specificity (Cizauskas et al. 2017). Studies examining parasites facing environmental change often focus on endoparasitic helminths, which are typically divided into two categories based on life cycle. Parasites with direct life cycles have one host species required to complete their life cycle. Complex life cycle parasites have two or more required hosts. Several studies suggest that complex life cycle parasites will be affected more than those with direct life cycles because there is a greater chance that one of their obligate host species goes extinct (Rohr et al. 2011; Cizauskas et al. 2017). An alternative hypothesis predicts that parasites with direct life cycles will be more vulnerable to environmental change, specifically, those which have free-living larvae that must seek new vertebrate hosts (Altizer et al. 2013; Molnar et al. 2013). But not all direct life cycle parasites produce free-living infective larvae. Some species infect new hosts by consumption of the egg stage in the environment (Morand et al. 2007). Eggs of complex life cycle parasites are also consumed in the environment, but they are consumed by intermediate hosts (i.e. snails, arthropods), and infective larvae hatch within these hosts. These larvae are "sheltered" from the environment until the intermediate host is consumed by a vertebrate. Behavioral thermoregulation of intermediate hosts by 109 seeking more favorable conditions is particularly important for sheltering larvae, especially in higher temperatures (Molnar et al. 2013). If eggs of both direct and complex life cycle parasites are in the environment, one would predict that both would be equally vulnerable to environmental change. However, these life cycles may differ in where most infections take place and how long eggs are subject to environmental conditions. Different patterns of infection between these two life cycles may help predict which life cycle is most vulnerable to environmental change. Intermediate hosts may aggregate in areas where definitive host spends most of their time (e.g. animal nests, perches) (Smith 2001), especially coprophagous insects. Thus, infective eggs may spend minimal time in the environment before being consumed by an intermediate host through more targeted infection (i.e. consuming infected feces) (Boze et al. 2012). Similarly, direct life cycle parasites may infect new hosts through coprophagy or grooming. However, parasites with direct life cycles may infect new vertebrate hosts more in the environment than through these methods (Stahl 1963; Morand et al. 2007; Spickett et al. 2017). For example, Spickett et al. (2017) found that direct life cycle nematodes transmitted through ingestion of infectious stages in the environment were more prevalent than those that can also be transmitted through coprophagy or grooming. Environmental conditions may have a greater influence on direct life cycle parasites because of where most individuals are infected. We predict that direct life cycle parasites will be more vulnerable to environmental change than those with complex life cycles. Host specificity is also an important property of parasites and refers to the number of host species that a parasite population can use (Poulin et al. 2007). Parasites with low host specificity should be less affected by environmental change than parasites that can 110 infect only one host (Bush and Kennedy 1994; Koh et al. 2004; Cizauskas et al. 2017). Parasites that infect many host species can infect other hosts that may still be present following environmental change and extinction of a host species. Low host specificity also allows parasites to spread to new habitats and tolerate environmental change (Poulin et al. 2007). In contrast, parasites with high host specificity may have a higher probability of going extinct with their hosts (co-extinction) (Koh et al. 2004; Lafferty and Kuris 2009). If differences in life cycle and host specificity matter, habitat change may drive these changes through altering host communities and infection patterns. Throughout the Intermountain West, pinyon-juniper woodlands (P-J) are expanding into and replacing sagebrush steppe habitats (Blackburn and Tueller 1970; Weisberg et al. 2007; Bradley and Fleishman 2008). As P-J replaces sagebrush and canopy cover increases, the understory vegetation becomes less dense (Blackburn and Tueller 1970; Breshears et al. 1998; West 1999). Climate change is a major contributor to these conversions and woody plant expansion worldwide (Idso 1992; Miller and Wigand 1994; Archer et al. 1995; Kelly and Goulden 2008; Clifford et al. 2011). Over the past 50 years, temperatures have increased throughout the Great Basin (Logan et al. 2007) and P-J woodlands have expanded (Bradley and Fleishman 2008). This change in habitat may play a role in altering parasite communities. Addressing questions related to parasite community structure, life cycles, and host specificity over time are hard to document because there are few historical datasets that document parasites. A historical parasite dataset collected more than 50 years ago is used to address several questions. This dataset includes host-helminth records at sites surveyed 111 between 1957 and 1968 in the Great Basin in western Utah. From these records, helminth prevalence, abundance, intensity, species composition, and species diversity can be calculated and compared to new data collected more than 50 years later. The most sampled rodent species was deer mice (Peromyscus maniculatus). Deer mice are host to a diverse assemblage of helminths, some of which have direct life cycles and some that have complex life cycles. Here, we address the main question, does parasite diversity change over time in the Great Basin, and if so, which parasite species change? This question will be addressed by comparing current species richness, species diversity, and individual parasite abundance to historical parasite data from the 1950s-1960s in the Great Basin. We then address whether P-J expansion is responsible for any changes in parasite diversity, abundance, or species composition by sampling two sites that have gone from low P-J cover to high P-J cover (P-J conversion). Helminth community structure will be compared to historical data at those sites by sampling in the exact spots where parasites were sampled 50 years ago. Parasites are also sampled in low P-J cover sites and high P-J sites recently to further determine the influence of habitat on parasite community structure. We also determine whether life cycle type contributes to patterns of change over 50 years in the Great Basin by comparing historical nematode prevalence and abundance to recent nematode sampling since some nematodes have direct life cycles and some have complex life cycles. Lastly, we investigate patterns of host specificity between nematodes with direct and complex life cycles. 112 Methods Study system The focal species for this study is the North American deer mouse (P. maniculatus), which occupies nearly every habitat in North America. Deer mice are nocturnal and active year-round; they feed primarily on arthropods and seeds. The home range of deer mice varies, but can vary from 0.032 to 1.2 hectares (Stickel 1968). Because deer mice have limited home ranges, we can be confident that the mice are not moving long distances from where they are trapped. Deer mice are host to several groups of endoparasites, including cestodes, nematodes, trematodes, and acanthocephalans. These helminths have either direct life cycles or indirect life cycles (i.e. those with arthropod intermediate hosts). This study was conducted in the Great Basin from 2014 to 2016. The Great Basin is characterized by a desert ecosystem with north to south running mountain ranges creating a basin and range topography. The valley desert is dominated by sagebrush (Artemesia spp.) and associated grasses. In each mountain range, pinyon-juniper woodlands occur at higher elevations. Utah juniper (Juniperus osteosperma) and singleleaf pinyon pine (Pinus monophylla) are the predominate species (Banner 1992). The mountain ranges are essentially natural replicates because the same habitats occur in each range. Deer mice were trapped in the Stansbury Mountains, Oquirrh Mountains, Cedar Mountains, House Mountains, and Deep Creek Mountains in the Great Basin (Fig. 5.1). Three habitat types were sampled in the Stansbury and Oquirrh Mountains: sagebrush, pinyon-juniper (high P-J cover), and the transition zone between them (ecotone, low P-J cover) (Fig. 5.1). 113 Historical data Small mammals were trapped and sampled for parasites throughout Utah and parts of Nevada from 1957 to 1969; each location was trapped for three days on average (Frandsen 1960; Frandsen and Grundmann 1961, Derrick 1971). The animals were dissected to collect all intestinal helminths from the stomach, small intestines, caecum, and large intestines (Frandsen 1960; Derrick 1971). All parasites were identified based on morphology. A record was kept for each individual host trapped and sampled including those that did not have parasites. Field notes from collection trips indicate that all endoparasites from the gastrointestinal tract were collected and counted. Therefore, the prevalence, intensity, abundance, and species diversity of helminth communities can be calculated from these host-parasite records. A field notebook documenting sampling locations includes directions, site-specific details, approximate elevations, and general descriptions of habitat and vegetation. These notes were used to find historically sampled sites, and aerial photographs were obtained from the USDA and USGS to document and verify the historical vegetation. To compare historical and current parasite species composition, only historical sites that were either sagebrush, pinyon-juniper, or a mix of the two habitat types were used (Fig. 5.1). In total, I found 12 sites with those habitat types. From those sites, 400 deer mice were sampled for endoparasitic helminths. Most sites were sampled between 1957 and 1961. One site (Stansbury A) was sampled in 1968. Animal trapping and processing Deer mice were trapped using Sherman traps (H.B. Sherman Traps, Inc.). Traps were placed five to ten meters apart in transects. Whole oats and birdseed were used as bait. All animal handling and processing was approved by the Institutional Animal Care 114 and Use Committee of the University of Utah. Trapping was terminated at each site when 25 deer mice were trapped and euthanized. Because deer mice populations were low in numbers, four sites had less than 25 animals trapped (The Cedar Mountains, Deep Creek Mountains, and House Mountains; Fig. 5.1), despite 150 trap nights or more. Animals that were captured were placed into a Ziploc bag along with the contents of the trap to recover any ectoparasites that came off the animal while it was in the trap. The animal was euthanized with isoflurane. It was placed on ice and taken to the lab for further processing. In the lab, the mass, body length, tail length, ear length, and leg length of each animal was measured. Animals were then dissected. Their digestive tracts (i.e. stomach, small intestine, caecum, and large intestine) were removed and placed into a vial and frozen at -80 degrees C for later dissection. After processing, animal carcasses were deposited at the Natural History Museum of Utah, in Salt Lake City, UT. Parasite collection Digestive tracts were thawed and separated into the small intestine, stomach, caecum, and large intestine and dissected separately. In separate glass petri dishes, each part was cut open and the inside of the intestinal wall was scrapped with a glass slide to remove all attached parasites. The petri dishes were examined under a dissecting microscope to find any helminths. Water was added to the contents of the gastrointestinal tracts in order to make finding worms easier under the dissecting scope by breaking up and diluting food particles and feces. To ensure that worms were not missed, the contents of the gastrointestinal tracts were separated into several smaller petri dishes and examined separately. This ensure that all the liquid could be examined for parasites. This was especially important for finding pinworms in the caecum. All helminths were placed 115 in 70% ethanol and stored in a freezer until they were used for identification. Helminths were categorized as being either nematodes, cestodes, trematodes, or acanthocephalans based on morphology. Molecular methods were then used to split each taxonomic group into species groups because of potential cryptic species and the number of parasites that were recovered. Gastrointestinal tracts are the areas where most rodent helminths are found (Georgiev et al. 2007; Morand et al. 2007). Parasite identification DNA from each helminth specimen (nematode, cestode, trematode, acanthocephalan) was extracted using a Qiagen Blood and Tissue Kit. Fragments of the mitochondrial COI gene was amplified using a different set of primers for each helminth group (Table 5.1). The PCR reaction mixture was a 27µL reaction containing 2 µL of DNA, 0.5 µL of 10 mM dNTP, 0.5 µL of each 10 µM primers, 2.5 µL of NEB 10x buffer, 20.8 µL water, and 0.2 µL Taq DNA polymerase. The reactions ran for an initial denaturing at 95°C for 1 minute, followed by 40 cycles of denaturing at 95°C for 1 minute, annealing at 53°C for 90 s, extension at 72°C for 2 minutes, and a final extension at 72°C for 2 minutes was completed. Successful amplifications were visualized on a 1% agarose gel following electrophoresis by adding 4µL of unpurified PCR product in 2µL of loading dye. Successful amplifications were sequenced using Sanger sequencing (MCLAB, San Francisco, CA). Sequences were aligned and split into species groups using the software program Geneious (Kearse et al. 2012). Species groups were formed by performing a MAFFT alignment on all sequences for each helminth group (nematodes, cestodes, trematodes, and acanthocephalans) to determine pairwise percent identity. We 116 used a species group cutoff of 95% pairwise similarity (Derycke et al. 2010; Armenteros et al. 2014). However, each species group we identified had greater than 97% similarity within the group, and differences between species groups was less than 90%. We identified seven species of nematodes in deer mice, four species of cestodes, one species of trematode, and two species of acanthocephalans. Species names were matched with each species group. For nematodes, DNA was extracted from individual worms that were identified to species based on morphology by Michael Kinsella (HelmWest Laboratory; Gritzen 2012). These identified individuals were then analyzed together with the unknown species groups and matched according to sequence similarity. There were two nematode species groups that we were not able to assign to a particular species. Specimens from these groups were morphology distinct and were identified based on morphology by Michael Kinsella. Cestodes were identified using the same molecular methods. Species names were added to cestode sequences by Vasyl Tkach based on the morphology of the sequenced specimens (University of North Dakota). Change in P-J cover over time In addition to the records of parasites throughout the Great Basin, there were two sites that underwent habitat change. These sites were a mix of sagebrush and pinyonjuniper woodlands historically based on habitat descriptions in field notes and aerial photographs. These sites had low P-J cover (ecotones) in the past and are both located in the Stansbury Mountains (Stansbury A and Stansbury B; Fig. 5.1). After 50 years, pinyon-juniper expanded, and these sites are now dense pinyon-juniper woodlands with very little understory plants, such as sagebrush and associated grasses. 117 ImageJ (Rasband 2016) was used to estimate the percent of P-J cover at two sites both historically and currently using thresholding and particle analysis (Abramoff et al. 2004; Pérez and Pascau 2013). Historical aerial photographs were gathered from the USGS (https://earthexplorer.usgs.gov) and from Derrick (1971). Derrick (1971) describes sampling the rodent community for parasites and includes an aerial photograph of the exact location where traps were placed. Google Earth was used for current P-J cover. Each study site was located in Google Earth or in an aerial photograph. Percent cover was estimated per hectare. Hectare square images produced in Google Earth or from the historical aerial image were imported into ImageJ. Percent tree cover was estimated by measuring the area of all the trees in the image. The color threshold of each image was adjusted so that only trees were selected. A threshold cutoff was used that was determined by the smallest tree in the image. Smaller areas selected were excluded because they were not trees and should not be included in the estimation of tree cover. The areas of all the trees were added up and divided by the total area of the one-hectare image. Sampling low and high P-J cover sites To further investigate if habitat is responsible for any changes to parasite community structure, parasites were sampled in low P-J cover sites and high P-J cover sites at four replicate locations (Fig. 5.1). These data were compared to the data over time from historic sampling (low P-J cover) and more recent sampling (high P-J cover). If habitat is responsible for differences in parasite community structure between the two time points, then similar patterns would be observed when sampling from low P-J cover to high P-J cover sites. 118 Life cycle differences and host specificity Life cycles were determined for each parasite species. All cestodes, acanthocephalans, and trematodes have complex life cycles. Nematodes have both complex and direct life cycles. The life cycle of each nematode species was determined according to the literature. The host specificity was determined for each nematode species in the southwestern U.S. by searching the literature and dissertations that were written as part of the historical parasite data in the 1950s and 60s. Analyses Two types of species accumulation curves were created to determine if each deer mice was thoroughly sampled for parasites. We used number of deer mice sampled (sample-based accumulation) to determine parasite species accumulation (see Fig. 5.S1). The number of parasite individuals (individual-based accumulation) was also used to determine thorough sample coverage by using accumulation and extrapolation using the Chao richness estimator to find whether further parasite sampling would lead to more species. Individual-based accumulation and extrapolation was done using the iNEXT package (Hsieh et al. 2016) in R (R Core Team 2016; see Fig. 5.S2). Prevalence was calculated by taking the number of hosts infected with a given parasite divided by the total number of hosts sampled throughout the Great Basin or at the site level. Mean intensity (± SE) was calculated by taking the average number of parasite individuals per infected host (Bush et al. 1997). The evenness of the parasite species in the community was determined by using Simpson's diversity index (Simpson's D), which takes into account the relative abundance of each species. To compare relative parasite abundances, rank abundance plots were produced for the Great Basin and at the 119 site level for the two P-J converted sites. Statistical analyses for diversity and species richness were performed using the Vegan package (Oksanen et al. 2016) in R (R Core Team 2016). Results Parasite sampling I trapped 382 deer mice from 16 sites. Out of these 382 mice, 116 (30.4%) were infected with at least one helminth species. Historically, 224 out of 400 mice (56%) were infected with at least one helminth species. Historically and more recently (2014-2016), sample-based species accumulation suggests that helminth parasites were not added after sampling approximately 300 deer mice (Fig. 5.S1A). Using individual parasites (individual-based), rather than hosts as the sampling unit, an asymptote was not reached (Fig. 5.S2A). After using the Chao richness estimator to extrapolate species richness given greater sampling, it is predicted that current sampling will have higher species richness than historical sampling (Fig. 5.S2A). Comparison throughout the Great Basin Overall, species richness of parasites in deer mice increased in the Great Basin over 50 years (Table 5.2). There were 13 species historically and 14 species found during current sampling. Parasite species found in deer mice in the Great Basin and the prevalence and mean intensity of each are listed as well as the historical prevalence and mean intensity of the same parasite species (Table 5.2). There is a decrease in the prevalence of S. peromysci (Table 5.2). Comparing the current species composition to historical species composition, a few species were either lost or gained following 120 environmental change. The nematode species Heligmosomoides vandegrifti, Mastophorus muris, Syphacia montana, and a second acanthocephalan species were new species that were not found historically. Additionally, H. polygyrus, Trichuris stansburyi, and Brevistriata skrjabini were found in the past and were not found in deer mice during current sampling (Table 5.2). Species diversity increased throughout the Great Basin (Fig. 5.2A). Rank abundance plots of parasite species show a dramatic decrease in the abundance of S. peromysci (Fig. 5.2B and C). Comparison following P-J conversion Pinyon-juniper cover increased in two sites sampled for parasites historically (Fig. 5.3). Both sites were a mix of sagebrush and P-J in the past with a percent P-J cover between two and eight percent. Current estimates of P-J cover show that they are now greater than 30% P-J. The Stansbury B site is approximately 60% P-J. Sample-based species accumulation curves indicate that enough deer mice were sampled for parasites at the two P-J conversion sites (Fig. 5.S1B and C). Thorough sampling of parasites was also indicated by the asymptotes of individual-based accumulation curves using Chao estimation (Fig. 5.S2B and C). Parasite prevalence and mean intensity for the two sites resampled after being converted to P-J are also listed (Table 5.3). Species richness increased in P-J converted sites (five historically, eight after current sampling) (Table 5.3). This was mainly driven by one site, Stansbury B. A trematode species, Brachylaima microti, and an acanthocephalan species, Moniliformis clarki, are now present in this P-J converted site. Only four Bra. microti and three Mo. clarki were found out of 400 mice sampled historically. Brachylaima microti and Mo. clarki were found in sagebrush habitats 121 historically and are now found in P-J woodlands. Additionally, one acanthocephalan species was found historically, while two acanthocephalan species were found following resampling. Species diversity also increased at the two sites that were converted to P-J woodlands (Fig. 5.4A). The reasons for the increase in diversity are slightly different for each site. The Stansbury A site showed a decrease in the abundance of S. peromysci, which caused the abundance of each species to be more even (Fig. 5.4B and C). At the Stansbury B site, S. peromysci decreased, but the number of species also increased (Fig. 5.4D and Fig. 5.4E). Comparison of low P-J to high P-J sites Parasites were also sampled in low P-J cover sites and high P-J cover habitat sites at four replicate locations in the Stansbury and Oquirrh Mountains. To determine if changes to parasite communities were mainly driven by habitat, we compared parasite diversity in these two habitat types. We also compared the abundances of S. peromysci, the species that showed the most drastic change in abundance. Three of the sites showed slight increases in diversity, while the fourth one decreased (Fig. 5.5). None of the diversity values for these sites were as low as the diversity values historically (Fig. 5.2A, Fig. 5.4A, and Fig. 5.5). There is no pattern in the prevalence or total abundance of S. peromysci between low P-J cover sites and high P-J cover sites (Table 5.4). Prevalence decreased from low to high P-J habitats in two locations and increased slightly at the other two locations. Total abundance increased at three locations from low to high P-J cover, while decreasing at the fourth location (Table 5.4). 122 Life cycle differences and host specificity Of the seven direct life cycle nematodes, five (71%) were absent either historically or after resampling. Three nematodes were absent after resampling. Syphacia peromysci, a direct life cycle nematode species and the most prevalent and abundant parasite species historically, dramatically decreased in both prevalence (Table 5.2, Table 5.3) and abundance (Fig. 5.2, Fig. 5.4) throughout the Great Basin and at the two P-J converted sites. Of the three complex life cycle nematodes, only one was absent in the past (Ma. muris). Taking all complex life cycle parasites into account, no complex life cycle species were absent after resampling. Two species were recorded that were not present in the Great Basin historically (Table 5.2). The host specificity was determined for each nematode species (Table 5.5). The six nematodes with direct life cycles infect either one or two rodent species in the Great Basin. The three nematodes with complex life cycles have three or more rodent hosts (Table 5.5). Discussion We addressed the question, does parasite diversity change over time in the Great Basin, and if so, which parasite species change? There was an increase in parasite diversity in the Great Basin. This was mainly due to the decrease in the direct life cycle nematode Syphacia peromysci, which led to greater evenness among the remaining species. The two sites that were converted to P-J also showed a decrease in the abundance S. peromysci over time. In the Great Basin, this species mainly parasitizes deer mice. Grundmann and Frandsen (1960) state that this species is almost exclusively found in Peromyscus species and was universally distributed throughout the Great Basin. Syphacia 123 peromysci is a pinworm with a direct life cycle. Hosts are infected by Syphacia spp. by ingesting infective eggs from the perianal region of other hosts, when licking themselves, or from contaminated materials in the environment (Stahl 1963). The comparison of low and high P-J habitat types (Table 5.4) suggests that the changes in parasite species diversity and the abundance of S. peromysci is not caused solely by habitat change. There was no pattern in S. peromysci abundance over the four sampled locations. Further evidence to this is that there was a big decrease in the abundance of S. peromysci throughout the entire Great Basin (including sagebrush sites) and not just at sites that were converted to P-J woodlands. Grice and Prociv (1993) found that eggs of a similar species, Syphacia obvelata, are not very resistant to desiccation and suggest that this limits the transmission potential of S. obvelata compared to other direct life cycle nematodes. Furthermore, Froeschke et al. (2010) found a positive correlation between S. obvelata prevalence and rainfall and humidity and a negative correlation between S. obvelata prevalence and temperature. Warmer temperatures may cause eggs to desiccate and become less infective, even those eggs on the perianal region of hosts that are subject to outside temperatures. Even though infection and reinfection can occur through coprophagy and grooming behavior (Morand et al 2007), this may not be sufficient to sustain large populations of S. peromysci in host populations. Environmental infections may be more important, which would require resistance of infective eggs to environmental conditions. Over the last 50 years, temperatures have increased throughout the Great Basin (see Fig. 5.S3). Another pinworm found in deer mice is Aspiculuris americana. This species has similar prevalence and mean intensity in both time points sampled (Table 5.2). In the two 124 P-J converted sites, A. americana was not present historically when habitats had low P-J cover. Current parasite sampling suggests that this may not be based on habitat. Deer mice collected from both low and high P-J cover sampled recently were infected with A. americana. Little is known about the life cycle of A. americana, but the life cycle of a similar species, A. tetraptera, has been described (Anya 1966). Eggs hatch in the host and are shed in the feces as infective larvae. The larvae, compared to the eggs of S. peromysci, may be more tolerant to environmental conditions. The low prevalence in P. maniculatus (5/382) and historical sampling suggests A. americana mainly infects Microtus longicaudus (Frandsen 1960; Derrick 1971). These pinworms may be more dependent on M. longicaudus than deer mice. Future work should examine how warmer temperatures or drier conditions may impact the infectiveness of both pinworms, S. peromysci and A. americana. Three nematode species were found in 2014-2016 that were not found historically: Mastophorus muris, S. montana, and Heligmosomoides vandegrifti. In a catalogue of parasites from North American rodents, Doran (1955) did not list Ma. muris as occurring in P. maniculatus. This species was listed as a parasite of P. leucopus, which does not occur in the Great Basin. However, this species was found in deer mice in northeastern Quebec (Shad 1956). Mastophorus muris is also found in white-footed mice in eastern deciduous forests in Pennsylvania (Vandegrift and Hudson 2009). This species is similar in morphology to Protospirura numidica (M. Kinsella, personal communication) but was split from the Protospirura genus (Chitwood 1938). This species may have been misidentified in the historical dataset. These species are greater than 5% similar based on COI sequence similarity. This may be the first record Ma. 125 muris in P. maniculatus in the Great Basin, especially if this species was misidentified in the past. The other two species not found historically were S. montana and H. vandegrifti. Syphacia montana in P. maniculatus may be an accidental infection; only one mouse was infected. This species is not normally a parasite of P. maniculatus (Dyer 1969). Heligmosomoides vandegrifti is a new species described from white-footed mice (P. leucopus) in Pennsylvania (Durette-Desset and Kinsella 2007). There were no undescribed species in the historical data. There were also three nematode species that were found historically, but were not found during resampling: Brevistriata skrjabini, H. polygyrus (= Nematospiroides dubius, Baylis 1926; Behnke et al. 1991), and Trichuris stansburyi. Brevistriata skrjabini was found in one deer mouse historically. This parasite is extremely rare and is mainly found in Siberian chipmunks in Asia (Tamias sibiricus). Likewise, T. stansburyi is also rare and the only documented cases of this species is from a deer mouse in the Great Basin (Frandsen and Grundmann 1961a). Heligmosomoides polygyrus in P. maniculatus has been suggested to be the result of accidental infections (Forrester 1971), which may explain the low historical prevalence (5/400) and not finding this species during resampling. In a recent review, Cizauskas et al. (2017) suggest that parasites are as prone to adverse effects as free-living species and suggest that parasites with direct life cycles will be less affected by climate change than parasites with complex life cycles. An alternative hypothesis predicts that complex life cycle parasites are sheltered from environmental conditions because they are almost always in a host (Molnar et al. 2013; Kutz et al. 2014). Our results are consistent with this hypothesis. Of the three nematode species that 126 were absent following resampling, they all have direct life cycles (Table 5.2). The nematode species showing the biggest change in prevalence and abundance was S. peromysci, a direct life cycle parasite. Host specificity may explain the differences between complex and direct life cycle parasites in this system. Parasites that can infect several host species should be relatively stable to environmental fluctuations. In this system, the complex life cycle parasites, Protospirura numidica and Pterygodermatites peromysci (= Rictularia coloradensis, Lichtenfels 1970), infect insect intermediate hosts. For example, the beetle Eleodes tuberculata is the main intermediate host for P. numidica (Cook and Grundmann 1964; Anderson 2000), but three other insect intermediate hosts have been found (Healey and Grundmann 1974). These species are also coprophagic on mouse feces and are often found in close proximity to deer mice (Healey and Grundmann 1974). Protospirura numidica also infects up to seven other rodent species in the Great Basin besides P. maniculatus (Cook and Grundmann 1964). Ceuthophilus spp. (camel crickets) are the main intermediate hosts of Pt. peromysci (Luong and Hudson 2012). This parasite may also use other arthropod species as intermediate hosts similar to other parasite species in the same genus (Anderson 2000). Pterygodermatites peromysci infects up to five other rodent species in the Great Basin (Grundmann and Frandsen 1960; Frandsen and Grundmann 1961b). Mastophorus muris parasitizes two more species other than P. maniculatus. These records are from eastern New Mexico, and both species are found in the Great Basin (Pfaffenberger et al. 1985). More information is needed for Ma. muris regarding host specificity since this may be a new record for this species in the Great Basin. Furthermore, deer mice and the intermediate hosts for these three parasite species 127 are widely distributed throughout the region. All three parasite species are also found in low and high P-J habitat types. These generalist parasite species would not be as vulnerable to changes in the environment as parasites with hosts that are habitat specialists. Future studies on parasites and environmental change should consider the distributions of all the hosts required for the parasites to complete their life cycle as well as host specificity. In terms of direct life cycle nematodes, Syphacia peromysci is primarily a parasite of P. maniculatus, but it also infects one other rodent species in the Great Basin, Reithrodontomys megalotis (Grundmann and Frandsen 1960). This rodent is a generally restricted to grassy weedy habitats, such as sagebrush (Webster 1982). The combination of high host specificity and the transmission dynamics within the environment vs. infection due to grooming or coprophagy may account for the dramatic decrease in S. peromysci prevalence and abundance. Brevistriata skrjabini and Trichuris stansburyi may only infect deer mice, but more information is needed on these parasites in the Great Basin in terms of host specificity. In conclusion, parasite species diversity increased over 50 years in the Great Basin. This was mainly caused by a decrease in the prevalence and abundance of S. peromysci. The abundance of S. peromysci did not decrease from low to high P-J cover habitat types sampled in 2014-2016, suggesting that this decrease is not caused by strictly habitat change. Increasing temperatures or other changes related to climate change throughout the Great Basin may explain these results; however, further research is necessary. Our results also suggest that parasites with direct life cycles may be affected more by environmental change than those with complex life cycles due to differences in 128 host specificity. Acknowledgements This manuscript will be submitted for publication with Sarah Bush. I would like to thank Hector Zumaeta, Matthew Talmage, William Reynolds, Scott Ripple, and Brandy Mills for their assistance dissecting rodents for helminths. Matthew Talmage was essential for splitting helminths into species groups using barcoding. I also want to thank Michael Kinsella and Vasyl Tkach for identifying nematode specimens. Dale Clayton, Scott Villa, Sabrina McNew, Emily DiBlasi, and Graham Goodman provided helpful feedback. This study was supported by the USA National Science Foundation Graduate Research Fellowship Program (GRFP-1256065) and a grant from the Global Change and Sustainability Center at the University of Utah. References Abràmoff, M. D., P. J. Magalhães, and S. J. Ram, 2004. Image processing with ImageJ. Biophotonics International 11:36-42. Anderson, R. C., 2000. Nematode Parasites of Vertebrates: Their Development and Transmission. CABI Publishing, New York City, New York. Anya, A. O. 1966. Studies on the biology of some oxyurid nematodes. II. The hatching of eggs and development of Aspiculuris tetraptera Schulz, within the host. Journal of Helminthology 40:261-268. Armenteros, M., A. Rojas-Corzo, A. Ruiz-Abierno, S. Derycke, T. Backeljau, and W. Decraemer. 2014. 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Forward (F) and reverse (R) primers and sequences for mitochondrial cytochrome c oxidase I (COI) genes that were used to split parasites into species groups. Primer name Parasite(s) identified Sequence (5'- 3') JB3F Nematodes Cestodes Trematodes TTTTTTGGGCATCCTGAGGTTTAT JB5R Nematodes AGCACCTAAACTTAAAACATAATGAAAATG JB4.5R Cestodes TAAAGAAAGAACATAATGAAAATG TremR Trematodes CAACAAATCATGATGCAAAAGG AcanthF Acanthocephalans AGTTCTAATCATAA(R)GATAT(Y)GG AcanthR Acanthocephalans TAAACTTCAGGGTGACCAAAAAATCA 135 Table 5.2. Parasite species composition in the Great Basin from historical sampling and resampling. Historical sampling included 400 deer mice. Recent sampling included 382 deer mice. Prevalence Taxonomic group Parasite species Mean intensity ± SE Life cycle Historical Recent Historical Recent Nematode Syphacia peromysci Direct 0.3 0.07 31.9 ± 8.5 24.5 ± 8.2 Nematode Syphacia montana Direct 0 0.003 0 91 ± 0.0 Nematode Aspiculuris americana Direct 0.008 0.013 4.67 ± 1.8 3.4 ± 1.0 Nematode Heligmosomoides polygyrus Direct 0.015 0 1.17 ± 0.0 0 Nematode Heligmosomoides vandegrifti Direct 0 0.03 0 7.6 ± 2.1 Nematode Trichuris stansburyi Direct 0.003 0 1 ± 0.0 0 Nematode Brevistriata skrjabini Direct 0.003 0 1 ± 0.0 0 Nematode Protospirura numidica Complex 0.11 0.09 5.02 ± 0.6 5.03 ± 1.3 Nematode Pterygodermatites peromysci Complex 0.10 0.06 2.44 ± 0.3 2.04 ± 0.6 Nematode Mastophorus muris Complex 0 0.02 0 4.71 ± 1.6 Cestode Hymenolepis sp. Complex 0.033 0.039 3.08 ± 1.0 1.73 ± 0.5 Cestode Catenotaenia sp. 1 Complex 0.025 0.060 2.6 ± 1.0 1.30 ± 0.2 Cestode Catenotaenia sp. 2 Complex 0.015 0.003 1.0 ± 0.0 1.0 ± 0.0 Cestode Choanotaenia sp. Complex 0.003 0.003 1.0 ± 0.0 1.0 ± 0.0 Acanth. Moniliformis sp. Complex 0.008 0.02 2 ± 0.6 4.33 ± 2.5 Acanth. Acanth. sp. 2 Complex 0 0.005 0 5.0 ± 3.0 Trematode Brachylaima microti Complex 0.01 0.01 2.5 ± 1.0 2.0 ± 0.6 136 Table 5.3. Parasite species at two sites sampling historically and resampled recently after an increase in P-J woodlands. Listed are the prevalences and abundances for both sites sampled. One hundred two mice were sampled for parasites at Stansbury A in 1968, and 49 deer mice were sampled more recently. Twenty-four mice were sampled historically at Stansbury B in 1957, and 26 were sampled recently. Stansbury A Parasite species Prevalence Mean intensity ± SE Historical Recent Historical Recent 0.55 0.14 26.54 ± 4.12 27.9 ± 9.13 Aspiculuris americana 0 0.02 0 7.0 ± 0.0 Heligmosomoides vandegrifti 0 0.16 0 8.88 ± 2.37 Heligmosomoides polygyrus 0.059 0 1.17 ± 0.17 0 Protospirura numidica 0.03 0.06 1.67 ± 0.67 7.67 ± 6.17 Pterygodermatites peromysci 0.010 0 3.0 ± 0.0 0 Hymenolepis sp. 0.04 0 1.25 ± 0.25 0 Acanth. sp. 2 0 0 0 0 Brachylaima microti 0 0 0 0 Syphacia peromysci Stansbury B Parasite species Prevalence Mean intensity ± SE Historical Recent Historical Recent 0.25 0.04 23.5 ± 6.9 104.0 ± 0.0 Aspiculuris americana 0 0.04 0 3.0 ± 0.0 Heligmosomoides vandegrifti 0 0 0 0 Heligmosomoides polygyrus 0 0 0 0 Protospirura numidica 0 0.04 0 4.0 ± 0.0 0.13 0.04 1.33 ± 0.33 2.0 ± 0.0 Hymenolepis sp. 0 0.08 0 2.0 ± 0.0 Acanth sp. 2 0 0.04 0 2.0 ± 0.0 Brachylaima microti 0 0.08 0 1.0 ± 0.0 Syphacia peromysci Pterygodermatites peromysci 137 Table 5.4. The prevalence and total abundance of Syphacia peromysci from deer mice in four replicate locations at which low P-J and high P-J habitat types were sampled. Locations are shown in Fig. 5.1. Sample size is the number of deer mice sampled at each site within each location. Prevalence Total abundance Location Sample sizes Low P-J High P-J Low P-J High P-J Stansbury A Eco = 24, P-J = 49 0.21 0.14 218 195 Stansbury B Eco = 28, P-J = 26 0.14 0.04 57 104 Oquirrh A Eco = 25, P-J = 26 0.04 0.08 4 7 Oquirrh B Eco = 27, P-J = 26 0 0.04 0 1 138 Table 5.5. Host specificity of nematode parasites found in deer mice (Peromyscus maniculatus) in the southwestern U.S. Host specificity refers to the number of mammal (definitive) hosts. These data include deer mice as a host. Parasite species Life cycle Host specificity References Syphacia peromysci Direct 2 Grundmann and Frandsen 1960; Frandsen and Grundmann 1961b Aspiculuris americana Direct 2 Frandsen 1960; Derrick 1971 Heligmosomoides polygyrus Direct 2 Forrester 1971; Pfaffenberger et al. 1985 Heligmosomoides vandegrifti* Direct 1 Durette-Desset et al. 2007; Gritzen 2012 Trichuris stansburyi Direct 1 Frandsen and Grundmann 1961a Brevistriata skrjabini Direct 1 Frandsen and Grundmann 1961b Protospirura numidica Complex 8 Pterygodermatites peromysci Complex 6 Mastophorus muris Complex 3 Grundmann and Frandsen 1960; Cook and Grundmann 1964; Healey and Grundmann 1974 Grundmann and Frandsen 1960; Frandsen and Grundmann 1961b Pfaffenberger et al. 1985 * H. vandegrifti was described from P. maniculatus in Pennsylvania (Durette-Desset et al. 2007). 139 Figure 5.1. Map of current and historical parasite sampling sites in the Great Basin. Three habitats were sampled (yellow, orange, and green). Circles represent current sampling, and squares refer to historical sampling. Squares with circles inside denote sites that were resampled and the colors refer to the habitat types of the sites historically (outer square color) and currently (inner circle color). Red triangles are the locations of weather stations at which temperature data were collected. 0 0 A. americana Fig. 5.2. Parasite species diversity (Simpson's D) (A) and rank abundance plots for parasites in the Great Basin historically (B) and during current sampling (C). Note the break in the axis in B. Catenotaenia sp. 2 Choanotaenia sp. Bra. microti 100 Acantho. sp. 1 100 Hymenolepis sp. 200 Catenotaenia sp. 1 200 Mo. clarki 600 Ma. muris 300 700 Pt. peromysci 400 S. montana Historical Great Basin n = 400 He. vandegrifti C Pr. numidica B S. peromysci 3700 Abundance Historical Bre. skrjabini T. stansburyi Choanotaenia sp. Catenotaenia sp. 2 Mo. clarki He. polygyrus Bra. microti 3800 A. americana 3900 Catenotaenia sp. 1 Hymenolepis sp. Pt. peromysci Pr. numidica S. peromysci Abundance Simpson's D Figure 2 140 A 1.0 0.8 0.6 0.4 0.2 0.0 Current Current Great Basin n = 382 500 400 300 141 Figure 3 70 Stansbury B Percent P-J cover 60 50 40 Stansbury A 30 20 10 0 Historical Current Figure 5.3. Change in P-J cover over time at the two resampled sites. Stansbury A was sampled historically in 1968 and Stansbury B was sampled in 1957. Figure 4 142 A 1.0 Simpson's D 0.8 0.6 Stansbury A 0.4 Stansbury B 0.2 0.0 Historical Current B C 1550 Historical Stansbury A n = 102 1490 100 50 140 He. polygyrus Pr. numidica Hymenolepis sp. Pt. peromysci Historical Stansbury B n = 24 E S. peromysci He. vandegrifti Pr. numidica A. americana 160 140 Current Stansbury B n = 26 120 Abundance Abundance 100 0 S. peromysci 120 100 80 60 40 100 80 60 40 20 0 150 50 0 D 160 Current Stansbury A n = 49 200 Abundance Abundance 1500 250 20 0 S. peromysci Pt. peromysci S. peromysci Pr. numidica Hymenolepis A. americana Pt. peromysci Mo. clarki sp. Bra. microti Fig. 5.4. Parasite species diversity (Simpson's D) (A) and rank abundance plots for the two resampled sites: Stansbury A (B and C) and Stansbury B (D and E). Shown are the rank abundances of each site at each time point. Sample sizes are listed. Note the break in the axis in B. Figure 5 1.0 Oquirrh B Oquirrh A Simpson's D 0.8 Stansbury A 0.6 0.4 Stansbury B 0.2 0.0 Low P-J cover High P-J cover Fig. 5.5. Parasite species diversity (Simpson's D) for low P-J cover and high P-J cover sites at four replicate locations: two locations in the Stansbury Mountains and two locations in the Oquirrh Mountains. 143 Figure 2 144 A Great Basin Species richness 15 Current Historical 10 5 0 0 Species richness B 100 200 300 400 Deer mice sampled Stansbury A 8 Current Historical 6 4 2 0 0 20 60 80 100 Deer mice sampled C Stansbury B 8 Species richness 40 Current Historical 6 4 2 0 0 5 10 15 20 25 Deer mice sampled Figure 5.S1. Parasite species accumulation based on sampling individual deer mice (sample-based accumulation throughout the Great Basin (A) in two sites (B and C) that were resampled that were converted to P-J woodlands. 145 Figure 5.S2. Species accumulation curves using individual parasites (individual-based) for the Great Basin (A) and the two sites that were converted to P-J woodlands (B and C). Solid lines represent species accumulation based on number of individual parasites found. Dashed lines represent extrapolated species richness based on the Chao species richness estimator. Shaded regions around each line represent 95% confidence intervals based on bootstrapped data. Sample sizes are listed in Fig. 5.4. 146 35 1960 - 1970 2005 - 2015 30 30 * 25 * 25 20 20 15 Temperature (°C) Temperature (°C) 35 B Tooele Callao Figure. 5.S3. Mean temperature in July at two sites with temperature stations (Fig. 5.1) between two time periods, 1960-1970 and 2005 to 2010. (A) The mean temperature of Tooele, UT significantly increased between the two time periods (t-test: t = -3.53, d.f. = 19.96, P = 0.002). (B) The mean temperature of Callao, UT also significantly increased (t-test: t = -2.82, d.f. = 17.96, P = 0.017). 15 Mea APPENDIX A STABLE ISOTOPE ANALYSIS OF DEER MICE IN THE GREAT BASIN 20 A 10 15 δ N (‰) 15 5 Sagebrush Pinyon−juniper 0 −25 −20 13 −15 −10 δ C (‰) 16 15 δ N(‰) 14 B 12 10 8 6 4 2 Lab insect Lab seed Field P-J Field sagebrush Fig. A.1. Isotope values of whiskers from deer mice. A) 15N and 13C values of mice caught in sagebrush habitats and pinyon-juniper (P-J) habitats. There is a significant difference between 15N in sagebrush and pinyon-juniper (t-test, t = 2.97, df = 21.06, p-value = 0.007), which suggests a difference in trophic level for mice in these two habitats. Mice in sagebrush are in a higher trophic level than those in P-J, which may be due to a higher insect diet (see B). There is no significant difference between 13C in mice from sagebrush and P-J habitats. B) 15N values of captive deer mice and field caught mice for comparison (from A). Captive mice were fed one of two diets for two months: seed rich or insect rich. Blood was taken and 15N and was measured. Mice fed insect rich diets had significantly higher 15N values than mice fed seed rich diets (t-test, t = -5.27, df = 15.09, P < 0.0001). These results suggest that mice in sagebrush habitats are consuming more insects than mice in P-J habitats. APPENDIX B SPECIES OF LICE COLLECTED FROM RODENTS IN THE GREAT BASIN Table B.1. Species identifications of lice collected from rodents in the Great Basin from 2014 to 2016. Rodents were trapped, euthanized, and combed for ectoparasites. Each louse was mounted on a glass slide after first clearing the abdomen using a lysis buffer and proteinase k. All identifications were made by D. Gustafsson. Louse species Host species Prevalence Hoplopleura hesperomydis Peromyscus maniculatus 144/525 Polyplax auricularis Peromyscus maniculatus 1/525 Hoplopleura arboricola Tamias minimus Tamias dorsalis 3/10 1/12 Neohaematopinus neotomae Neotoma lepida 3/20 Neohaematopinus citellinus Ammospermophilus leucurus 1/8 Neohaematopinus pacificus Tamias dorsalis 1/12 Fahrenholzia reducta Perognathus parvus 2/22 Fahrenholzia pinnata Dipodomys ordii 2/10 Hoplopleura acanthopus Microtus longicaudus 1/8 Hoplopleura hesperomydis Reithrodontomys megalotis 1/26 Hoplopleura difficillus Tamias dorsalis 1/12 Hoplopleura sciuricola Lemmiscus curtatus 1/5 APPENDIX C ANIMALS INFESTED WITH BOTFLIES AT TIME OF CAPTURE Table C.1. Botflies from rodents captured between 2014 and 2016 in the Great Basin. The number of botflies in each host and the habitat in which the rodent was captured is listed. Collection Number * Host Species Botfly species Intensity per host Habitat AWB110 Peromyscus maniculatus Cuterebra 1 P-J AWB111 Peromyscus maniculatus Cuterebra 1 P-J AWB129 Peromyscus maniculatus Cuterebra 1 P-J AWB141 Peromyscus maniculatus Cuterebra 1 P-J AWB170 Peromyscus maniculatus Cuterebra 2 P-J AWB228 Peromyscus maniculatus Cuterebra 2 P-J AWB358 Neotoma lepida Cuterebra sp. 1 P-J AWB499 Peromyscus maniculatus Cuterebra 1 P-J AWB502 Peromyscus maniculatus Cuterebra 1 P-J AWB518 Peromyscus maniculatus Cuterebra 1 P-J AWB541 Peromyscus maniculatus Cuterebra 1 Sagebrush AWB568 Peromyscus maniculatus Cuterebra 1 P-J AWB571 Peromyscus maniculatus Cuterebra 1 P-J AWB575 Peromyscus maniculatus Cuterebra 1 P-J AWB604 Peromyscus maniculatus Cuterebra 1 P-J * Animals are located at the Natural History Museum of Utah in Salt Lake City, UT APPENDIX D HOST-PARASITE DATA FROM RODENTS IN THE GREAT BASIN Table D.1. Host-parasite data of rodents collected in the Great Basin. Listed are all the individual rodents captured, the species, sex, and the numbers of ectoparasites (split into fleas, ticks, and lice) and helminth species. Measurements (body length, tail length, leg length, and ear length) of each animal, and site locations can be obtained from the Natural History Museum of Utah (Collection numbers AWB1-AWB683). 151 M M F M NA M F F F M M M M F M M M M F F M F F 45 Peromyscus maniculatus 46 Tamias minimus 47 Peromyscus maniculatus 48 Peromyscus maniculatus 49 Peromyscus maniculatus 50 Peromyscus maniculatus 51 Peromyscus maniculatus 52 Peromyscus maniculatus 53 Peromyscus maniculatus 54 Lemmiscus curtatus 55 Perognathus parvus 56 Peromyscus maniculatus 57 Peromyscus maniculatus 58 Peromyscus maniculatus 59 Peromyscus maniculatus 60 Peromyscus maniculatus 61 Peromyscus maniculatus 62 Peromyscus maniculatus 63 Peromyscus maniculatus 64 Peromyscus maniculatus 65 Peromyscus maniculatus 66 Perognathus parvus 67 Peromyscus maniculatus 68 Lemmiscus curtatus 69 Peromyscus maniculatus 70 Peromyscus maniculatus 71 Peromyscus maniculatus 72 Peromyscus maniculatus 73 Peromyscus maniculatus 74 Peromyscus maniculatus 75 Peromyscus maniculatus 76 Peromyscus maniculatus 76 Neotoma cinerea 78 Peromyscus maniculatus 79 Peromyscus maniculatus 80 Peromyscus maniculatus 81 Peromyscus maniculatus 82 Peromyscus maniculatus 83 Peromyscus maniculatus 84 Peromyscus maniculatus 85 Peromyscus maniculatus AWB45 AWB46 AWB47 AWB48 AWB49 AWB50 AWB51 AWB52 AWB53 AWB54 AWB55 AWB56 AWB57 AWB58 AWB59 AWB60 AWB61 AWB62 AWB63 AWB64 AWB65 AWB66 AWB67 AWB68 AWB69 AWB70 AWB71 AWB72 AWB73 AWB74 AWB75 AWB77 AWB76 AWB78 AWB79 AWB80 AWB81 AWB82 AWB83 AWB84 AWB85 F F M F M F F M F NA M F F F F F M M F 44 Peromyscus maniculatus M sex AWB44 Species 43 Peromyscus maniculatus num AWB43 Host Number 8.8 26 26.5 17 20 19.5 20 19 9.5 19 16.0 23.5 19.5 20.5 23 19.5 21.5 19.5 20.5 18.5 24.5 23.5 22.0 22.5 23.5 26 19 15.5 21.5 20 25.5 20 19.5 110.0 NA 18.5 22 21 19 33.5 22 24.5 21.5 mass 0 0 0 0 0 0 0 0 1 0 1 7 1 0 0 0 0 18 25 0 0 1 0 0 0 0 15 12 13 17 1 1 10 11 4 4 16 14 15 4 3 5 21 ticks 0 1 0 1 1 0 0 0 1 1 0 0 0 2 0 0 0 1 1 0 0 0 0 0 0 3 0 0 0 0 0 0 0 2 0 1 1 7 0 1 3 2 1 2 0 0 0 0 0 2 1 0 0 0 0 0 1 0 3 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 3 1 fleas lice 0 2 3 1 0 0 0 0 212 0 0 15 0 0 0 15 44 6 26 0 0 0 0 0 0 0 1 NA NA 0 0 1 15 2 0 0 NA 1 0 5 Number of nematodes 0 2 2 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 NA 0 NA 0 2 0 0 0 0 0 0 0 0 NA NA 0 0 0 15 0 0 0 NA 1 0 5 Protospirura numidica 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 NA 0 NA 0 0 0 0 0 0 0 0 0 0 NA NA 0 0 0 0 0 0 0 NA 0 0 0 Mastophorus muris 0 0 1 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 NA 0 NA 6 0 0 0 0 0 0 0 0 0 NA NA 0 0 0 0 0 0 0 NA 0 0 0 Pterygodermatites peromysci 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 15 NA 44 NA 0 24 0 0 0 0 0 0 0 0 NA NA 0 0 0 0 0 0 0 NA 0 0 0 Syphacia peromysci 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 NA 0 NA 0 0 0 0 0 0 0 0 0 0 NA NA 0 0 0 0 0 0 0 NA 0 0 0 2 Aspiculuris americana 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 NA 0 NA 0 0 0 0 0 0 0 0 0 0 NA NA 0 0 0 0 0 0 0 NA 0 0 0 Heligmosomoides vandegrifti 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 NA 0 NA 0 0 0 0 0 0 0 0 0 0 NA NA 0 0 0 0 0 0 0 NA 0 0 0 Syphacia montana 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 NA 0 0 0 Number of cestodes 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 NA 0 NA 0 0 0 0 0 0 0 0 0 0 NA NA 0 0 0 0 0 0 0 NA 0 0 0 cest.sp.1 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 NA 0 NA 0 0 0 0 0 0 0 0 0 0 NA NA 0 0 0 0 0 0 0 NA 0 0 0 Hymenolepis sp. 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 NA 0 NA 0 0 0 0 0 0 0 0 0 0 NA NA 0 0 0 0 0 0 0 NA 0 0 0 cest.sp.3 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 NA 0 NA 0 0 0 0 0 0 0 0 0 0 NA NA 0 0 0 0 0 0 0 NA 0 0 0 cest.sp.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Number of acanthocephalans 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 NA 0 NA 0 0 0 0 0 0 0 0 0 0 NA NA 0 0 0 0 0 0 0 NA 0 0 0 acan.sp.1 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 NA 0 NA 0 0 0 0 0 0 0 0 0 0 NA NA 0 0 0 0 0 0 0 NA 0 0 0 acan.sp.2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Number of trematodes 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 NA 0 NA 0 0 0 0 0 0 0 0 0 0 NA NA 0 0 0 0 0 0 0 NA 0 0 0 Brachylaima microti) 152 114 Peromyscus truei 115 Peromyscus maniculatus 116 Peromyscus maniculatus 117 Peromyscus maniculatus 118 Peromyscus truei AWB114 AWB115 AWB116 AWB117 AWB118 131 Peromyscus maniculatus 113 Peromyscus truei AWB113 AWB131 112 Tamias dorsalis AWB112 130 Micotus montanus 111 Peromyscus maniculatus AWB111 AWB130 F 110 Peromyscus maniculatus AWB110 129 Peromyscus maniculatus F 109 Peromyscus maniculatus AWB109 AWB129 F 108 Peromyscus truei AWB108 128 Peromyscus maniculatus M 107 Peromyscus maniculatus AWB107 AWB128 F 106 Peromyscus maniculatus AWB106 127 Peromyscus maniculatus M 105 Peromyscus truei AWB105 AWB127 F 104 Peromyscus maniculatus AWB104 126 Peromyscus maniculatus F 103 Peromyscus truei AWB103 AWB126 F 102 Peromyscus truei AWB102 125 Peromyscus maniculatus F 101 Peromyscus truei AWB101 AWB125 F 100 Peromyscus maniculatus AWB100 124 Peromyscus maniculatus F 99 Peromyscus maniculatus AWB99 AWB124 M 98 Peromyscus truei AWB98 123 Peromyscus maniculatus F 97 Neotoma lepida AWB97 AWB123 M 96 Tamias dorsalis AWB96 122 Peromyscus maniculatus F 95 Peromyscus maniculatus AWB95 AWB122 F 94 Peromyscus maniculatus AWB94 121 Peromyscus maniculatus F 93 Peromyscus maniculatus AWB93 AWB121 F 92 Peromyscus maniculatus AWB92 119 Peromyscus maniculatus M 91 Peromyscus maniculatus AWB91 120 Peromyscus maniculatus F 90 Tamias dorsalis AWB90 AWB120 M 89 Peromyscus maniculatus AWB89 AWB119 M 88 Peromyscus maniculatus AWB88 F F M F M F M F F F M M M F M M F M F M M F 87 Peromyscus maniculatus M sex AWB87 Species 86 Peromyscus maniculatus num AWB86 Host Number NA 12.5 33.0 21.5 12.5 22 11.5 20 15 17 17.5 20.5 17.5 19 20.5 17 15 16.5 20.0 28.0 50.0 16.5 18 12.0 22.5 14 23.5 14 19.5 15.5 18.5 15.5 24 19.0 70.0 60.0 16 15.5 18.5 21.5 17.5 46.5 21 20.5 16.5 18 mass 0 0 0 0 0 6 0 0 0 9 0 1 0 7 3 1 0 13 0 2 4 10 2 33 7 0 8 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 1 0 0 0 ticks 1 1 2 0 8 2 3 1 1 3 10 0 6 0 0 1 2 0 0 1 2 3 6 2 2 0 1 0 0 3 0 6 1 1 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 2 0 0 0 0 0 4 0 0 2 0 0 0 0 0 0 4 0 0 0 0 0 0 4 0 9 0 2 0 15 1 1 2 1 21 1 0 4 0 4 6 fleas lice 0 0 0 69 7 0 10 0 22 52 18 5 31 0 2 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 1 0 1 2 0 1 Number of nematodes 0 NA 0 0 0 0 0 0 0 0 0 1 0 NA 2 0 0 NA NA NA 0 0 0 NA 0 0 NA 0 NA NA NA 0 0 NA NA NA 0 0 0 0 0 NA 0 0 0 1 Protospirura numidica 0 NA 0 0 0 0 0 0 0 0 0 0 0 NA 0 0 0 NA NA NA 0 0 0 NA 0 0 NA 0 NA NA NA 0 0 NA NA NA 0 0 0 0 0 NA 0 0 0 0 Mastophorus muris 0 NA 0 0 0 0 0 0 0 0 0 0 0 NA 0 0 0 NA NA NA 0 0 0 NA 0 0 NA 0 NA NA NA 0 1 NA NA NA 0 0 0 0 0 NA 0 2 0 0 Pterygodermatites peromysci 0 NA 0 69 0 0 10 0 0 52 15 0 31 NA 0 0 0 NA NA NA 0 0 0 NA 0 0 NA 0 NA NA NA 0 0 NA NA NA 0 0 0 0 0 NA 0 0 0 0 Syphacia peromysci 0 NA 0 0 7 0 0 0 0 0 0 0 0 NA 0 0 0 NA NA NA 0 0 0 NA 0 0 NA 0 NA NA NA 0 0 NA NA NA 0 0 0 0 0 NA 0 0 0 0 3 Aspiculuris americana 0 NA 0 0 0 0 0 0 22 0 3 4 0 NA 0 0 0 NA NA NA 0 0 0 NA 0 0 NA 0 NA NA NA 0 0 NA NA NA 0 0 0 0 0 NA 0 0 0 0 Heligmosomoides vandegrifti 0 NA 0 0 0 0 0 0 0 0 0 0 0 NA 0 0 0 NA NA NA 0 0 0 NA 0 0 NA 0 NA NA NA 0 0 NA NA NA 0 0 0 0 0 NA 1 0 0 0 Syphacia montana 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Number of cestodes 0 NA 0 0 0 0 0 0 0 0 0 0 0 NA 0 0 0 NA NA NA 0 0 0 NA 0 0 NA 0 NA NA NA 0 0 NA NA NA 0 0 0 0 0 NA 0 0 0 0 cest.sp.1 0 NA 0 0 0 0 0 0 0 0 0 0 0 NA 0 0 0 NA NA NA 0 0 0 NA 0 0 NA 0 NA NA NA 0 0 NA NA NA 0 0 0 0 0 NA 0 0 0 0 Hymenolepis sp. 0 NA 0 0 0 0 0 0 0 0 0 0 0 NA 0 0 0 NA NA NA 0 0 0 NA 0 0 NA 0 NA NA NA 0 0 NA NA NA 0 0 0 0 0 NA 0 0 0 0 cest.sp.3 0 NA 0 0 0 0 0 0 0 0 0 0 0 NA 0 0 0 NA NA NA 0 0 0 NA 0 0 NA 0 NA NA NA 0 0 NA NA NA 0 0 0 0 0 NA 0 0 0 0 cest.sp.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Number of acanthocephalans 0 NA 0 0 0 0 0 0 0 0 0 0 0 NA 0 0 0 NA NA NA 0 0 0 NA 0 0 NA 0 NA NA NA 0 0 NA NA NA 0 0 0 0 0 NA 0 0 0 0 acan.sp.1 0 NA 0 0 0 0 0 0 0 0 0 0 0 NA 0 0 0 NA NA NA 0 0 0 NA 0 0 NA 0 NA NA NA 0 0 NA NA NA 0 0 0 0 0 NA 0 0 0 0 acan.sp.2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Number of trematodes 0 NA 0 0 0 0 0 0 0 0 0 0 0 NA 0 0 0 NA NA NA 0 0 0 NA 0 0 NA 0 NA NA NA 0 0 NA NA NA 0 0 0 0 0 NA 0 0 0 0 Brachylaima microti) 153 M NA F F M F M M F M M M F F M M M M F M F M M 134 Peromyscus maniculatus 135 Peromyscus maniculatus 136 Peromyscus truei 137 Peromyscus maniculatus 138 Peromyscus maniculatus 139 Peromyscus maniculatus 140 Peromyscus maniculatus 141 Peromyscus maniculatus 142 Peromyscus maniculatus 143 Microtus longicaudus 144 Peromyscus maniculatus 145 Peromyscus maniculatus 146 Peromyscus maniculatus 147 Peromyscus maniculatus 148 Peromyscus maniculatus 149 Peromyscus maniculatus 150 Peromyscus maniculatus 151 Peromyscus maniculatus 152 Peromyscus maniculatus 153 Peromyscus maniculatus 154 Peromyscus maniculatus 155 Peromyscus maniculatus 156 Peromyscus maniculatus 157 Peromyscus maniculatus 158 Peromyscus maniculatus 159 Peromyscus maniculatus 160 Peromyscus maniculatus 161 Peromyscus maniculatus 162 Peromyscus maniculatus 163 Peromyscus maniculatus 164 Peromyscus maniculatus 165 Peromyscus maniculatus 166 Peromyscus maniculatus 167 Peromyscus maniculatus 168 Peromyscus maniculatus 169 Peromyscus maniculatus 170 Peromyscus maniculatus 171 Peromyscus maniculatus 172 Peromyscus maniculatus AWB134 AWB135 AWB136 AWB137 AWB138 AWB139 AWB140 AWB141 AWB142 AWB143 AWB144 AWB145 AWB146 AWB147 AWB148 AWB149 AWB150 AWB151 AWB152 AWB153 AWB154 AWB155 AWB156 AWB157 AWB158 AWB159 AWB160 AWB161 AWB162 AWB163 AWB164 AWB165 AWB166 AWB167 AWB168 AWB169 AWB170 AWB171 AWB172 F F M M F M M F M M F M F F M F M 133 Peromyscus maniculatus F sex AWB133 Species 132 Peromyscus maniculatus num AWB132 Host Number NA NA 17 18.5 18.5 18 15 18 17.5 17.5 18 20 20.5 17.5 21 16.5 15 18 16.5 16.5 16.5 19 17.5 15.5 15 16 14.5 17.5 16 17.5 41.5 20 19.5 15.5 11.5 15.5 20.5 16 17 17.5 11 mass 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 2 0 0 0 0 0 1 0 0 0 0 0 1 2 0 0 0 1 0 ticks 4 2 0 0 2 0 3 0 2 1 3 3 4 2 1 1 1 10 1 3 1 1 2 5 2 3 1 0 0 6 0 1 1 0 2 0 2 1 0 0 0 0 0 0 0 10 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 2 10 5 4 4 0 0 0 0 0 0 0 0 6 0 0 0 0 11 fleas lice 1 12 0 0 0 5 2 0 0 0 1 0 0 0 0 0 0 0 27 0 0 0 0 0 0 0 0 6 0 2 0 16 0 7 0 0 0 0 0 0 0 Number of nematodes 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 0 NA 0 0 0 0 Protospirura numidica 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 0 NA 0 0 0 0 Mastophorus muris 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 0 NA 0 0 0 0 Pterygodermatites peromysci 0 12 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 27 0 0 0 0 0 0 0 0 6 0 NA 0 0 0 0 0 0 NA 0 0 0 0 Syphacia peromysci 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 0 NA 0 0 0 0 4 Aspiculuris americana 1 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 NA 0 16 0 7 0 0 NA 0 0 0 0 Heligmosomoides vandegrifti 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 0 NA 0 0 0 0 Syphacia montana 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Number of cestodes 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 0 NA 0 0 0 0 cest.sp.1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 0 NA 0 0 0 0 Hymenolepis sp. 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 0 NA 0 0 0 0 cest.sp.3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 0 NA 0 0 0 0 cest.sp.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Number of acanthocephalans 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 0 NA 0 0 0 0 acan.sp.1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 0 NA 0 0 0 0 acan.sp.2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Number of trematodes 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 0 NA 0 0 0 0 Brachylaima microti) 154 M M F F M M M M F M F F M M M M F F M F M F F 175 Peromyscus maniculatus 176 Reithrodontomys megalotis 177 Peromyscus maniculatus 178 Peromyscus maniculatus 179 Peromyscus maniculatus 180 Peromyscus maniculatus 181 Peromyscus maniculatus 182 Peromyscus maniculatus 183 Peromyscus maniculatus 184 Peromyscus maniculatus 185 Peromyscus maniculatus 186 Microtus longicaudus 187 Peromyscus maniculatus 188 Peromyscus maniculatus 189 Peromyscus maniculatus 190 Peromyscus maniculatus 191 Peromyscus maniculatus 192 Peromyscus maniculatus 193 Peromyscus maniculatus 194 Peromyscus maniculatus 195 Peromyscus maniculatus 196 Peromyscus maniculatus 197 Reithrodontomys megalotis 198 Peromyscus maniculatus 199 Peromyscus truei 200 Peromyscus maniculatus 201 Peromyscus maniculatus 202 Microtus longicaudus 203 Peromyscus truei 204 Peromyscus truei 205 Peromyscus maniculatus 206 Peromyscus maniculatus 207 Peromyscus maniculatus 208 Reithrodontomys megalotis 209 Peromyscus truei 210 Peromyscus maniculatus 211 Peromyscus maniculatus 212 Microtus longicaudus 213 Peromyscus maniculatus 214 Peromyscus maniculatus 215 Tamias minimus 216 Tamias minimus AWB175 AWB176 AWB177 AWB178 AWB179 AWB180 AWB181 AWB182 AWB183 AWB184 AWB185 AWB186 AWB187 AWB188 AWB189 AWB190 AWB191 AWB192 AWB193 AWB194 AWB195 AWB196 AWB197 AWB198 AWB199 AWB200 AWB201 AWB202 AWB203 AWB204 AWB205 AWB206 AWB207 AWB208 AWB209 AWB210 AWB211 AWB212 AWB213 AWB214 AWB215 AWB216 M F F F F M F F F M M M M F F F M F F M 174 Reithrodontomys megalotis M sex AWB174 Species 173 Peromyscus maniculatus num AWB173 Host Number 29.5 35.5 16 20.5 23.5 12 11 15.5 8.0 13 16.5 15.5 17.5 14.0 25.5 10.5 8 17.5 17 8.5 14.5 19.5 19.5 13 17 17 15.5 18 17 19 26.5 15.5 17 20 14 13 19.5 17 13 18.5 14.5 19 10.0 18.5 mass 0 0 0 0 0 0 0 11 NA 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 ticks 0 0 4 1 1 0 0 2 NA 1 1 0 0 1 0 2 8 0 0 0 1 0 1 2 2 1 0 1 2 1 1 0 3 4 5 1 1 2 1 8 0 6 0 2 0 0 0 0 1 0 0 0 NA 0 8 6 0 0 0 4 2 0 0 0 0 0 1 10 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 2 3 fleas lice 0 0 0 0 0 0 0 0 0 0 6 0 0 12 50 0 5 24 20 0 201 0 5 26 2 0 1 0 95 0 49 0 8 0 0 0 0 0 0 1 2 0 0 0 Number of nematodes NA NA 0 0 NA 0 0 NA NA 0 0 0 NA NA NA 0 0 NA 20 NA 3 0 0 26 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 1 NA 0 NA 0 Protospirura numidica NA NA 0 0 NA 0 0 NA NA 0 0 0 NA NA NA 0 0 NA 0 NA 0 0 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 0 NA 0 NA 0 Mastophorus muris NA NA 0 0 NA 0 0 NA NA 0 0 0 NA NA NA 0 0 NA 0 NA 0 0 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 0 NA 0 NA 0 Pterygodermatites peromysci NA NA 0 0 NA 0 0 NA NA 0 6 0 NA NA NA 0 0 NA 0 NA 198 0 5 0 0 0 1 0 0 0 NA 0 8 0 0 0 0 0 0 0 NA 0 NA 0 Syphacia peromysci NA NA 0 0 NA 0 0 NA NA 0 0 0 NA NA NA 0 0 NA 0 NA 0 0 0 0 2 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 0 NA 0 NA 0 5 Aspiculuris americana NA NA 0 0 NA 0 0 NA NA 0 0 0 NA NA NA 0 5 NA 0 NA 0 0 0 0 0 0 0 0 4 0 NA 0 0 0 0 0 0 0 0 0 NA 0 NA 0 Heligmosomoides vandegrifti NA NA 0 0 NA 0 0 NA NA 0 0 0 NA NA NA 0 0 NA 0 NA 0 0 0 0 0 0 0 0 91 0 NA 0 0 0 0 0 0 0 0 0 NA 0 NA 0 Syphacia montana 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Number of cestodes NA NA 0 0 NA 0 0 NA NA 0 0 0 NA NA NA 0 0 NA 0 NA 0 0 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 0 NA 0 NA 0 cest.sp.1 NA NA 0 0 NA 0 0 NA NA 0 0 0 NA NA NA 0 0 NA 0 NA 0 0 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 0 NA 0 NA 0 Hymenolepis sp. NA NA 0 0 NA 0 0 NA NA 0 0 0 NA NA NA 0 0 NA 0 NA 0 0 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 0 NA 0 NA 0 cest.sp.3 NA NA 0 0 NA 0 0 NA NA 0 0 0 NA NA NA 0 0 NA 0 NA 0 0 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 0 NA 0 NA 0 cest.sp.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Number of acanthocephalans NA NA 0 0 NA 0 0 NA NA 0 0 0 NA NA NA 0 0 NA 0 NA 0 0 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 0 NA 0 NA 0 acan.sp.1 NA NA 0 0 NA 0 0 NA NA 0 0 0 NA NA NA 0 0 NA 0 NA 0 0 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 0 NA 0 NA 0 acan.sp.2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Number of trematodes NA NA 0 0 NA 0 0 NA NA 0 0 0 NA NA NA 0 0 NA 0 NA 0 0 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 0 NA 0 NA 0 Brachylaima microti) 155 M F M M F M F M F M M F M F F M F F M M M F F F M F M 219 Peromyscus maniculatus 220 Peromyscus maniculatus 221 Peromyscus truei 222 Tamias dorsalis 223 Peromyscus maniculatus 224 Peromyscus maniculatus 225 Peromyscus maniculatus 226 Peromyscus maniculatus 227 Peromyscus maniculatus 228 Peromyscus maniculatus 229 Peromyscus maniculatus 230 Peromyscus maniculatus 231 Peromyscus maniculatus 232 Reithrodontomys megalotis 233 Microtus longicaudus 234 Microtus longicaudus 235 Sorex monticolus 236 Peromyscus maniculatus 237 Peromyscus maniculatus 238 Peromyscus maniculatus 239 Peromyscus maniculatus 240 Peromyscus maniculatus 241 Peromyscus maniculatus 242 Peromyscus maniculatus 243 Peromyscus maniculatus 244 Peromyscus maniculatus 245 Peromyscus maniculatus 246 Peromyscus maniculatus 247 Peromyscus maniculatus 248 Pocket mouse 249 Peromyscus maniculatus 250 Peromyscus maniculatus 251 Peromyscus maniculatus 252 Peromyscus maniculatus 253 Peromyscus maniculatus 254 Peromyscus maniculatus 255 Peromyscus maniculatus 256 Peromyscus maniculatus 257 Peromyscus maniculatus 258 Peromyscus maniculatus 259 Perognathus parvus AWB219 AWB220 AWB221 AWB222 AWB223 AWB224 AWB225 AWB226 AWB227 AWB228 AWB229 AWB230 AWB231 AWB232 AWB233 AWB234 AWB235 AWB236 AWB 237 AWB 238 AWB 239 AWB 240 AWB 241 AWB 242 AWB 243 AWB 244 AWB 245 AWB 246 AWB 247 AWB 248 AWB 249 AWB 250 AWB 251 AWB 252 AWB 253 AWB 254 AWB 255 AWB 256 AWB 257 AWB 258 AWB 259 F F F M F F M M M M M F M M F 218 Peromyscus maniculatus F sex AWB218 Species 217 Peromyscus maniculatus num AWB217 Host Number 18.0 26.5 9 20 24 11 13 12.5 24 15 16.5 21.0 25 21 17.5 16 21 19 21 19 21 21 24 23.5 3.3 19.5 38.5 9.5 14 17.5 16 13 19.5 15 17.5 20 12.5 50.0 15.5 18.5 17.5 21.5 15.5 mass 1 4 1 10 0 1 0 0 1 0 13 0 0 2 0 0 0 1 0 0 7 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 ticks 2 12 4 8 2 2 5 2 18 2 8 0 11 3 0 4 1 0 3 5 3 1 1 6 0 0 2 0 2 2 0 0 6 0 0 0 5 1 0 1 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 13 6 0 0 0 2 0 0 4 0 0 0 0 0 0 0 35 0 2 0 4 0 0 0 1 5 1 0 fleas lice 0 0 0 0 1 0 0 0 1 0 2 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 9 0 0 0 0 0 3 0 0 0 0 Number of nematodes NA 0 0 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 0 0 0 0 NA NA NA NA 0 0 0 0 0 0 0 0 0 NA NA 0 0 0 0 Protospirura numidica NA 0 0 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 0 0 0 0 NA NA NA NA 0 0 0 0 0 0 0 0 0 NA NA 0 0 0 0 Mastophorus muris NA 0 0 0 1 0 0 0 1 0 2 NA 0 0 0 0 0 0 0 0 0 0 0 0 NA NA NA NA 0 0 0 0 0 0 0 0 0 NA NA 0 0 0 0 Pterygodermatites peromysci NA 0 0 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 0 0 0 0 NA NA NA NA 0 0 0 0 0 0 0 0 0 NA NA 0 0 0 0 Syphacia peromysci NA 0 0 0 0 0 0 0 0 0 0 NA 0 0 0 0 3 0 0 0 0 0 0 0 NA NA NA NA 0 0 0 0 0 0 0 0 0 NA NA 0 0 0 0 6 Aspiculuris americana NA 0 0 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 0 0 0 0 NA NA NA NA 0 0 0 0 9 0 0 0 0 NA NA 0 0 0 0 Heligmosomoides vandegrifti NA 0 0 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 0 0 0 0 NA NA NA NA 0 0 0 0 0 0 0 0 0 NA NA 0 0 0 0 Syphacia montana 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Number of cestodes NA 0 0 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 0 0 0 0 NA NA NA NA 0 0 0 0 0 0 0 0 0 NA NA 0 0 0 0 cest.sp.1 NA 0 0 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 0 0 0 0 NA NA NA NA 0 0 0 0 0 0 0 0 0 NA NA 0 0 0 0 Hymenolepis sp. NA 0 0 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 0 0 0 0 NA NA NA NA 0 0 0 0 0 0 0 0 0 NA NA 0 0 0 0 cest.sp.3 NA 0 0 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 0 0 0 0 NA NA NA NA 0 0 0 0 0 0 0 0 0 NA NA 0 0 0 0 cest.sp.4 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Number of acanthocephalans NA 0 0 0 0 0 0 0 0 0 0 NA 0 2 0 0 0 0 0 0 0 0 0 0 NA NA NA NA 0 0 0 0 0 0 0 0 0 NA NA 0 0 0 0 acan.sp.1 NA 0 0 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 0 0 0 0 NA NA NA NA 0 0 0 0 0 0 0 0 0 NA NA 0 0 0 0 acan.sp.2 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Number of trematodes NA 0 0 0 0 0 0 0 0 0 0 NA 0 1 0 0 0 1 0 0 0 0 0 0 NA NA NA NA 0 0 0 0 0 0 0 0 0 NA NA 0 0 0 0 Brachylaima microti) 156 M F M M F F M M F F F M F M F M M F F M F F M 262 Peromyscus maniculatus 263 Peromyscus maniculatus 264 Peromyscus maniculatus 265 Perognathus parvus 266 Peromyscus maniculatus 267 Peromyscus maniculatus 268 Peromyscus maniculatus 269 Pocket mouse 270 Peromyscus maniculatus 271 Peromyscus maniculatus 272 Lemmiscus curtatus 273 Peromyscus maniculatus 274 Peromyscus maniculatus 275 Peromyscus maniculatus 276 Peromyscus maniculatus 277 Peromyscus maniculatus 279 Tamias minimus 280 Tamias minimus 281 Lemmiscus curtatus 282 Pocket mouse 283 Pocket mouse 284 Peromyscus maniculatus 285 Peromyscus maniculatus 286 Peromyscus maniculatus 287 Peromyscus maniculatus 287 Tamias minimus 288 Peromyscus maniculatus 289 Peromyscus maniculatus 290 Peromyscus maniculatus 291 Pocket mouse 292 Peromyscus maniculatus 293 Pocket mouse 294 Peromyscus maniculatus 295 Peromyscus maniculatus 296 Peromyscus maniculatus 297 Peromyscus maniculatus 298 Peromyscus maniculatus 299 Peromyscus maniculatus 300 Peromyscus maniculatus 301 Pocket mouse 302 Tamias minimus 303 Pocket mouse 304 Peromyscus maniculatus 305 Peromyscus maniculatus 306 Peromyscus maniculatus AWB 263 AWB 264 AWB 265 AWB 266 AWB 267 AWB 268 AWB 269 AWB 270 AWB 271 AWB 272 AWB 273 AWB 274 AWB 275 AWB 276 AWB 277 AWB 279 AWB 280 AWB 281 AWB 282 AWB 283 AWB 284 AWB 285 AWB 286 AWB 287 AWB 278 AWB 288 AWB 289 AWB 290 AWB 291 AWB 292 AWB 293 AWB 294 AWB 295 AWB 296 AWB 297 AWB 298 AWB 299 AWB 300 AWB 301 AWB 302 AWB 303 AWB 304 AWB 305 AWB 306 M F M M F F F M M M M M F F M M M F M F M F 261 Tamias minimus AWB 262 F sex AWB 261 Species 260 Tamias minimus num AWB 260 Host Number 22.5 10.5 19.5 23.5 34.0 17.5 25.5 19.5 21.5 17 23 20 22.5 20.5 27.5 23.5 17.5 17.5 34 32.0 20 9 19.5 12 22.5 19.0 18.0 35.0 36.0 19.5 10.5 11.5 9 16 13.5 23.5 15.5 21.0 9.5 12.5 11.5 14.5 12.5 10.5 12 36.0 33.5 mass 0 1 0 0 NA 0 1 2 5 0 0 0 5 0 0 1 0 3 0 0 0 1 3 2 0 2 3 1 0 0 1 0 0 0 5 0 0 12 0 2 0 1 0 1 0 0 NA ticks 2 4 9 0 NA 1 3 0 3 5 4 1 3 0 3 0 1 4 2 0 6 7 4 1 0 0 0 1 0 5 2 1 11 13 8 1 1 0 5 6 10 0 13 3 5 0 NA 0 8 0 0 NA 1 0 0 0 2 0 0 1 3 0 0 0 0 0 4 0 6 0 1 0 0 0 7 0 0 0 0 1 0 1 0 3 0 0 0 0 0 1 0 0 0 NA fleas lice 2 0 0 0 0 0 0 0 0 0 108 0 6 0 0 0 0 0 0 0 0 1 0 42 0 0 0 0 0 1 0 9 0 0 0 0 0 36 0 0 0 0 0 0 0 0 0 Number of nematodes 0 0 0 NA NA NA 0 0 0 0 4 0 0 NA 0 NA 0 0 0 NA 0 0 0 0 NA NA NA NA NA 0 0 0 0 0 NA 0 0 NA 0 0 0 NA 0 0 0 NA NA Protospirura numidica 0 0 0 NA NA NA 0 0 0 0 0 0 0 NA 0 NA 0 0 0 NA 0 0 0 0 NA NA NA NA NA 0 0 0 0 0 NA 0 0 NA 0 0 0 NA 0 0 0 NA NA Mastophorus muris 2 0 0 NA NA NA 0 0 0 0 0 0 0 NA 0 NA 0 0 0 NA 0 0 0 0 NA NA NA NA NA 1 0 0 0 0 NA 0 0 NA 0 0 0 NA 0 0 0 NA NA Pterygodermatites peromysci 0 0 0 NA NA NA 0 0 0 0 104 0 6 NA 0 NA 0 0 0 NA 0 1 0 41 NA NA NA NA NA 0 0 9 0 0 NA 0 0 NA 0 0 0 NA 0 0 0 NA NA Syphacia peromysci 0 0 0 NA NA NA 0 0 0 0 0 0 0 NA 0 NA 0 0 0 NA 0 0 0 1 NA NA NA NA NA 0 0 0 0 0 NA 0 0 NA 0 0 0 NA 0 0 0 NA NA 7 Aspiculuris americana 0 0 0 NA NA NA 0 0 0 0 0 0 0 NA 0 NA 0 0 0 NA 0 0 0 0 NA NA NA NA NA 0 0 0 0 0 NA 0 0 NA 0 0 0 NA 0 0 0 NA NA Heligmosomoides vandegrifti 0 0 0 NA NA NA 0 0 0 0 0 0 0 NA 0 NA 0 0 0 NA 0 0 0 0 NA NA NA NA NA 0 0 0 0 0 NA 0 0 NA 0 0 0 NA 0 0 0 NA NA Syphacia montana 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 Number of cestodes 0 0 0 NA NA NA 0 0 0 0 0 0 1 NA 0 NA 0 0 0 NA 0 0 0 0 NA NA NA NA NA 1 0 0 0 0 NA 0 0 NA 0 0 0 NA 0 0 0 NA NA cest.sp.1 0 0 0 NA NA NA 0 0 0 0 0 0 0 NA 0 NA 0 0 0 NA 0 0 0 0 NA NA NA NA NA 0 0 0 0 0 NA 0 0 NA 0 0 0 NA 0 0 0 NA NA Hymenolepis sp. 0 0 0 NA NA NA 0 0 0 0 0 0 0 NA 0 NA 0 0 0 NA 0 0 0 0 NA NA NA NA NA 0 0 0 0 0 NA 0 0 NA 0 0 0 NA 0 0 0 NA NA cest.sp.3 0 0 0 NA NA NA 0 0 0 0 0 0 0 NA 0 NA 0 0 0 NA 0 0 0 0 NA NA NA NA NA 0 0 0 0 0 NA 0 0 NA 0 0 0 NA 0 0 0 NA NA cest.sp.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Number of acanthocephalans 0 0 0 NA NA NA 0 0 0 0 0 0 0 NA 0 NA 0 0 0 NA 0 0 0 0 NA NA NA NA NA 0 0 0 0 0 NA 0 0 NA 0 0 0 NA 0 0 0 NA NA acan.sp.1 0 0 0 NA NA NA 0 0 0 0 0 0 0 NA 0 NA 0 0 0 NA 0 0 0 0 NA NA NA NA NA 0 0 0 0 0 NA 0 0 NA 0 0 0 NA 0 0 0 NA NA acan.sp.2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Number of trematodes 0 0 0 NA NA NA 0 0 0 0 0 0 0 NA 0 NA 0 0 0 NA 0 0 0 0 NA NA NA NA NA 0 0 0 0 0 NA 0 0 NA 0 0 0 NA 0 0 0 NA NA Brachylaima microti) 157 F M F M M M M M M M M M F M M F M M F M F M 313 Reithrodontomys megalotis 314 Peromyscus maniculatus 315 Peromyscus maniculatus 316 Peromyscus maniculatus 317 Peromyscus maniculatus 318 Peromyscus maniculatus 319 Peromyscus maniculatus 320 Peromyscus maniculatus 321 Peromyscus maniculatus 322 Peromyscus maniculatus 323 Peromyscus maniculatus 324 Peromyscus maniculatus 325 Pocket mouse 326 Reithrodontomys megalotis 327 Peromyscus maniculatus 328 Peromyscus maniculatus 329 Peromyscus maniculatus 330 Peromyscus maniculatus 331 Peromyscus maniculatus 332 Peromyscus maniculatus 333 Peromyscus maniculatus 334 Peromyscus maniculatus 335 Peromyscus maniculatus 336 Peromyscus maniculatus 337 Peromyscus maniculatus 338 Peromyscus maniculatus 339 Peromyscus maniculatus 340 Peromyscus maniculatus 341 Peromyscus maniculatus 342 Reithrodontomys megalotis 343 Peromyscus maniculatus 344 Peromyscus maniculatus 345 Peromyscus maniculatus 346 Peromyscus maniculatus 347 Peromyscus maniculatus 348 Peromyscus maniculatus AWB 313 AWB 314 AWB 315 AWB 316 AWB 317 AWB 318 AWB 319 AWB 320 AWB 321 AWB 322 AWB 323 AWB 324 AWB 325 AWB 326 AWB 327 AWB 328 AWB 329 AWB 330 AWB 331 AWB 332 AWB 333 AWB 334 AWB 335 AWB 336 AWB 337 AWB 338 AWB 339 AWB 340 AWB 341 AWB 342 AWB 343 AWB 344 AWB 345 AWB 346 AWB 347 AWB 348 F M F M M M M M F F M F M M M 311 Reithrodontomys megalotis M 312 Tamias minimus 310 Pocket mouse AWB 310 M AWB 312 309 Peromyscus maniculatus AWB 309 M F sex AWB 311 308 Peromyscus maniculatus AWB 308 Species 307 Peromyscus maniculatus num AWB 307 Host Number NA 14.5 19.5 16.5 20.5 21 19 12.5 24 28 8 15 11.5 20 15 18.5 15 13.5 22 14.5 14.5 18 12.0 27.5 21 20.5 14 17.5 18 23 21 20.5 13 11 21.5 10.5 40.0 13.0 21.0 16 23 22 mass 0 0 0 0 2 3 0 0 0 2 0 0 0 3 0 13 2 8 1 0 0 1 0 0 0 0 0 0 0 0 0 1 0 1 3 NA 0 0 NA 8 0 0 ticks 0 1 0 0 2 1 2 2 4 4 0 3 0 4 1 3 3 5 3 4 4 5 2 1 2 3 1 4 1 3 0 7 2 2 0 NA 5 0 NA 5 0 0 0 0 0 0 0 0 0 0 0 0 9 26 0 0 1 8 0 0 0 0 3 3 0 0 0 0 0 0 0 0 0 1 0 0 0 NA 0 0 NA 0 0 1 fleas lice 0 0 0 0 14 0 NA 0 0 0 40 0 0 3 0 0 0 0 0 0 0 0 39 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 Number of nematodes 0 0 0 0 13 0 NA 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 NA NA 0 0 0 0 0 0 0 1 0 0 0 NA NA NA NA 0 0 0 Protospirura numidica 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 NA NA 0 0 0 0 0 0 0 0 0 0 0 NA NA NA NA 0 0 0 Mastophorus muris 0 0 0 0 1 0 NA 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 NA NA 0 0 0 0 0 0 1 0 0 0 0 NA NA NA NA 0 0 0 Pterygodermatites peromysci 0 0 0 0 0 0 NA 0 0 0 40 0 0 0 0 0 0 0 0 0 0 0 NA NA 0 0 0 0 0 0 0 0 0 0 0 NA NA NA NA 0 0 0 Syphacia peromysci 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 NA NA 0 0 0 0 0 0 0 0 0 0 0 NA NA NA NA 0 0 0 8 Aspiculuris americana 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 NA NA 0 0 0 0 0 0 0 0 0 0 0 NA NA NA NA 0 0 0 Heligmosomoides vandegrifti 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 NA NA 0 0 0 0 0 0 0 0 0 0 0 NA NA NA NA 0 0 0 Syphacia montana 0 0 0 0 0 2 NA 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 Number of cestodes 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 NA NA 0 0 0 0 0 0 0 0 0 0 0 NA NA NA NA 0 0 0 cest.sp.1 0 0 0 0 0 2 NA 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 NA NA 0 5 0 0 0 0 0 0 0 0 0 NA NA NA NA 0 2 0 Hymenolepis sp. 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 NA NA 0 0 0 0 0 0 0 0 0 0 0 NA NA NA NA 0 0 0 cest.sp.3 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 NA NA 0 0 0 0 0 0 0 0 0 0 0 NA NA NA NA 0 0 0 cest.sp.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Number of acanthocephalans 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 NA NA 0 0 0 0 0 0 0 0 0 0 0 NA NA NA NA 0 0 0 acan.sp.1 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 NA NA 0 0 0 0 0 0 0 0 0 0 0 NA NA NA NA 0 0 0 acan.sp.2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Number of trematodes 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 NA NA 0 0 0 0 0 0 0 0 0 0 0 NA NA NA NA 0 0 0 Brachylaima microti) 158 F M F M M M M M M F M F M F M M M M F M F F M 351 Peromyscus maniculatus 352 Peromyscus maniculatus 353 Neotoma lepida 354 Peromyscus maniculatus 355 Ammospermophilus leucurus 356 Peromyscus maniculatus 357 Peromyscus maniculatus 358 Neotoma lepida 359 Neotoma lepida 360 Peromyscus maniculatus 361 Neotoma lepida 362 Neotoma lepida 363 Neotoma lepida 364 Neotoma lepida 365 Pocket mouse 366 Dipodomys ordii 367 Reithrodontomys megalotis 368 Peromyscus maniculatus 369 Peromyscus maniculatus 370 Peromyscus maniculatus 371 Peromyscus maniculatus 372 Peromyscus maniculatus 373 Peromyscus maniculatus 374 Peromyscus maniculatus 375 Peromyscus maniculatus 376 Peromyscus maniculatus 377 Peromyscus maniculatus 378 Reithrodontomys megalotis 379 Neotoma lepida 380 Neotoma lepida 381 Ammospermophilus leucurus 382 Peromyscus maniculatus 383 Peromyscus maniculatus 384 Peromyscus maniculatus 385 Peromyscus maniculatus 386 Peromyscus maniculatus 387 Peromyscus maniculatus 388 Pocket mouse 389 Neotoma lepida 390 Neotoma lepida 391 Neotoma lepida 392 Neotoma lepida 393 Ammospermophilus leucurus 394 Peromyscus maniculatus 395 Peromyscus maniculatus AWB 351 AWB 352 AWB 353 AWB 354 AWB 355 AWB 356 AWB 357 AWB 358 AWB 359 AWB 360 AWB 361 AWB 362 AWB 363 AWB 364 AWB 365 AWB 366 AWB 367 AWB 368 AWB 369 AWB 370 AWB 371 AWB 372 AWB 373 AWB 374 AWB 375 AWB 376 AWB 377 AWB 378 AWB 379 AWB 380 AWB 381 AWB 382 AWB 383 AWB 384 AWB 385 AWB 386 AWB 387 AWB 388 AWB 389 AWB 390 AWB 391 AWB 392 AWB 393 AWB 394 AWB 395 F M M M M M M M F M M M F M F M M F M F M M M 350 Peromyscus maniculatus F sex AWB 350 Species 349 Neotoma lepida num AWB 349 Host Number 21.5 18.5 125.0 103.0 93.0 74.0 94.0 22.0 14.5 13 17.5 12 23.5 20.5 118.0 105.0 85.0 13.0 13.5 14.5 16.5 17.5 10.5 19 15 19.5 11.5 15 10.5 48.0 22.5 170.0 89.0 80.0 40.5 13.5 105.0 135.0 15.5 17.5 110.0 14.5 115.0 19 21 20 85.0 mass 0 0 NA 0 0 0 1 0 0 6 0 0 0 0 NA 2 0 NA 0 0 0 0 1 0 0 0 0 0 0 0 1 0 NA NA 1 0 1 0 0 0 0 0 2 0 3 1 ticks 0 1 NA 1 0 1 1 0 1 0 0 0 2 2 NA 2 6 NA 0 0 2 0 0 1 0 0 2 1 0 0 0 0 NA NA 2 0 1 1 1 7 3 2 3 2 0 3 4 0 NA 1 1 1 0 33 0 0 0 0 0 0 NA 1 3 NA 0 0 7 0 0 0 0 0 1 0 0 1 20 0 NA NA 2 0 0 0 0 0 0 0 24 0 0 1 fleas lice 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 Number of nematodes 0 2 NA NA NA NA NA NA 0 0 0 0 0 0 NA NA NA NA 0 0 0 8 0 0 0 0 0 0 NA NA NA NA NA NA NA 0 NA NA 0 0 NA 0 NA 0 0 0 NA Protospirura numidica 0 0 NA NA NA NA NA NA 0 0 0 0 0 0 NA NA NA NA 0 0 0 0 0 0 0 0 0 0 NA NA NA NA NA NA NA 0 NA NA 0 0 NA 0 NA 0 0 0 NA Mastophorus muris 0 0 NA NA NA NA NA NA 0 0 0 0 0 0 NA NA NA NA 0 0 0 0 0 0 0 0 0 0 NA NA NA NA NA NA NA 0 NA NA 0 0 NA 0 NA 0 0 0 NA Pterygodermatites peromysci 0 0 NA NA NA NA NA NA 0 0 0 0 0 0 NA NA NA NA 0 0 0 0 0 0 0 0 0 0 NA NA NA NA NA NA NA 0 NA NA 0 0 NA 0 NA 0 0 0 NA Syphacia peromysci 0 0 NA NA NA NA NA NA 0 0 0 0 0 0 NA NA NA NA 0 0 0 0 0 0 0 0 0 0 NA NA NA NA NA NA NA 0 NA NA 0 0 NA 0 NA 0 0 0 NA 9 Aspiculuris americana 0 0 NA NA NA NA NA NA 0 0 0 0 0 0 NA NA NA NA 0 0 0 0 0 0 0 0 0 0 NA NA NA NA NA NA NA 0 NA NA 0 0 NA 0 NA 0 0 0 NA Heligmosomoides vandegrifti 0 0 NA NA NA NA NA NA 0 0 0 0 0 0 NA NA NA NA 0 0 0 0 0 0 0 0 0 0 NA NA NA NA NA NA NA 0 NA NA 0 0 NA 0 NA 0 0 0 NA Syphacia montana 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Number of cestodes 1 0 NA NA NA NA NA NA 0 0 0 0 1 0 NA NA NA NA 0 0 0 0 0 0 0 0 0 0 NA NA NA NA NA NA NA 0 NA NA 0 0 NA 0 NA 0 0 0 NA cest.sp.1 0 0 NA NA NA NA NA NA 0 0 0 0 0 0 NA NA NA NA 0 0 0 0 0 0 0 0 0 0 NA NA NA NA NA NA NA 0 NA NA 0 0 NA 0 NA 0 0 0 NA Hymenolepis sp. 0 0 NA NA NA NA NA NA 0 0 0 0 0 0 NA NA NA NA 0 0 0 0 0 0 0 0 0 0 NA NA NA NA NA NA NA 0 NA NA 0 0 NA 0 NA 0 0 0 NA cest.sp.3 0 0 NA NA NA NA NA NA 0 0 0 0 0 0 NA NA NA NA 0 0 0 0 0 0 0 0 0 0 NA NA NA NA NA NA NA 0 NA NA 0 0 NA 0 NA 0 0 0 NA cest.sp.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Number of acanthocephalans 0 0 NA NA NA NA NA NA 0 0 0 0 0 0 NA NA NA NA 0 0 0 0 0 0 0 0 0 0 NA NA NA NA NA NA NA 0 NA NA 0 0 NA 0 NA 0 0 0 NA acan.sp.1 0 0 NA NA NA NA NA NA 0 0 0 0 0 0 NA NA NA NA 0 0 0 0 0 0 0 0 0 0 NA NA NA NA NA NA NA 0 NA NA 0 0 NA 0 NA 0 0 0 NA acan.sp.2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Number of trematodes 0 0 NA NA NA NA NA NA 0 0 0 0 0 0 NA NA NA NA 0 0 0 0 0 0 0 0 0 0 NA NA NA NA NA NA NA 0 NA NA 0 0 NA 0 NA 0 0 0 NA Brachylaima microti) 159 M M F F F F M M M M F M F F F F F F M F ? M M 398 Peromyscus truei 399 Reithrodontomys megalotis 400 Peromyscus maniculatus 401 Peromyscus maniculatus 402 Peromyscus maniculatus 403 Peromyscus maniculatus 404 Peromyscus truei 405 Neotoma lepida 406 Neotoma lepida 407 Peromyscus maniculatus 408 Neotoma lepida 409 Neotoma lepida 410 Dipodomys ordii 412 Dipodomys ordii 413 Dipodomys ordii 414 Dipodomys ordii 415 Ammospermophilus leucurus 416 Dipodomys ordii 418 Dipodomys ordii 419 Dipodomys ordii 422 Peromyscus truei 423 Peromyscus truei 424 Pocket mouse 429 Peromyscus maniculatus 430 Peromyscus maniculatus 431 Peromyscus maniculatus 432 Peromyscus maniculatus 433 Peromyscus maniculatus 434 Peromyscus maniculatus 435 Peromyscus maniculatus 436 Peromyscus maniculatus 437 Peromyscus maniculatus 438 Peromyscus maniculatus 439 Peromyscus maniculatus 440 Peromyscus maniculatus 441 Peromyscus maniculatus 442 Pocket mouse 443 Peromyscus maniculatus 444 Peromyscus maniculatus 445 Reithrodontomys megalotis 446 Peromyscus maniculatus 447 Reithrodontomys megalotis 448 Reithrodontomys megalotis 449 Peromyscus maniculatus 450 Peromyscus maniculatus 451 Dipodomys ordii AWB 398 AWB 399 AWB 400 AWB 401 AWB 402 AWB 403 AWB 404 AWB 405 AWB 406 AWB 407 AWB 408 AWB 409 AWB 410 AWB 412 AWB 413 AWB 414 AWB 415 AWB 416 AWB 418 AWB 419 AWB 422 AWB 423 AWB 424 AWB 429 AWB 430 AWB 431 AWB 432 AWB 433 AWB 434 AWB 435 AWB 436 AWB 437 AWB 438 AWB 439 AWB 440 AWB 441 AWB 442 AWB 443 AWB 444 AWB 445 AWB 446 AWB 447 AWB 448 AWB 449 AWB 450 AWB 451 M M F M F M F M F F M F F F M M F M M F 397 Neotoma lepida M sex AWB 397 Species 396 Peromyscus maniculatus num AWB 396 Host Number 14 15 18 16.5 18.5 23.5 13 17 26.5 13 22 16 21.5 17.5 17 15 12 16 17 18.5 25.0 22.5 49.0 51.0 54.0 71.0 35.0 47.0 53.0 50.0 165.0 72.0 12.5 110.0 14.5 25.5 12.5 23 17 13.5 11.5 22.5 100.0 22.5 mass 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 NA NA NA NA NA 1 NA 1 1 0 0 3 0 5 NA NA 0 0 0 0 0 NA 2 NA 1 ticks 0 0 0 0 0 0 0 0 0 1 0 0 12 0 1 1 1 0 4 0 0 1 1 NA NA NA NA NA 0 NA 0 0 0 3 0 0 NA NA 0 0 0 1 0 NA 0 NA 1 0 2 1 0 0 0 0 0 0 0 0 0 19 0 0 0 1 0 0 0 0 0 3 NA NA NA NA NA 1 NA 1 0 0 0 0 17 NA NA 0 100 3 0 1 NA 0 NA 0 fleas lice 0 0 0 4 2 0 0 0 2 0 0 0 1 0 4 0 0 0 0 0 0 0 0 yes 0 yes 0 0 0 0 0 0 10 0 3 0 0 0 0 Number of nematodes NA 0 0 NA NA 0 NA 0 0 NA 0 0 2 0 0 0 1 0 4 0 0 0 0 NA NA NA NA NA NA NA NA NA NA NA NA NA 0 NA NA NA 0 10 0 0 NA NA NA 0 Protospirura numidica NA 0 0 NA NA 0 NA 0 0 NA 0 0 0 0 0 0 0 0 0 0 0 0 0 NA NA NA NA NA NA NA NA NA NA NA NA NA 0 NA NA NA 0 0 0 0 NA NA NA 0 Mastophorus muris NA 0 0 NA NA 0 NA 4 0 NA 0 0 0 0 0 0 0 0 0 0 0 0 0 NA NA NA NA NA NA NA NA NA NA NA NA NA 0 NA NA NA 0 0 0 0 NA NA NA 0 Pterygodermatites peromysci NA 0 0 NA NA 0 NA 0 2 NA 0 0 0 0 0 0 0 0 0 0 0 0 0 NA NA NA NA NA NA NA NA NA NA NA NA NA 0 NA NA NA 0 0 0 3 NA NA NA 0 Syphacia peromysci NA 0 0 NA NA 0 NA 0 0 NA 0 0 0 0 0 0 0 0 0 0 0 0 0 NA NA NA NA NA NA NA NA NA NA NA NA NA 0 NA NA NA 0 0 0 0 NA NA NA 0 10 Aspiculuris americana NA 0 0 NA NA 0 NA 0 0 NA 0 0 0 0 0 0 0 0 0 0 0 0 0 NA NA NA NA NA NA NA NA NA NA NA NA NA 0 NA NA NA 0 0 0 0 NA NA NA 0 Heligmosomoides vandegrifti NA 0 0 NA NA 0 NA 0 0 NA 0 0 0 0 0 0 0 0 0 0 0 0 0 NA NA NA NA NA NA NA NA NA NA NA NA NA 0 NA NA NA 0 0 0 0 NA NA NA 0 Syphacia montana 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 Number of cestodes NA 0 0 NA NA 0 NA 0 0 NA 0 0 0 0 0 0 0 0 0 0 0 0 0 NA NA NA NA NA NA NA NA NA NA NA NA NA 0 NA NA NA 0 0 0 0 NA NA NA 0 cest.sp.1 NA 0 0 NA NA 0 NA 0 0 NA 0 0 0 0 0 0 0 0 0 0 0 0 0 NA NA NA NA NA NA NA NA NA NA NA NA NA 0 NA NA NA 0 0 0 0 NA NA NA 0 Hymenolepis sp. NA 0 0 NA NA 0 NA 0 0 NA 0 0 0 0 0 0 0 0 0 0 0 0 0 NA NA NA NA NA NA NA NA NA NA NA NA NA 0 NA NA NA 0 0 0 0 NA NA NA 0 cest.sp.3 NA 0 0 NA NA 0 NA 0 0 NA 0 0 0 0 0 0 0 0 0 0 0 0 0 NA NA NA NA NA NA NA NA NA NA NA NA NA 0 NA NA NA 0 1 0 0 NA NA NA 0 cest.sp.4 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Number of acanthocephalans NA 0 0 NA NA 0 NA 0 0 NA 0 0 0 0 0 0 0 0 0 0 0 0 0 NA NA NA NA NA NA NA NA NA NA NA NA NA 0 NA NA NA 0 0 0 0 NA NA NA 0 acan.sp.1 NA 0 0 NA NA 0 NA 0 0 NA 0 0 2 0 0 0 0 0 0 0 0 0 0 NA NA NA NA NA NA NA NA NA NA NA NA NA 0 NA NA NA 0 0 0 0 NA NA NA 0 acan.sp.2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Number of trematodes NA 0 0 NA NA 0 NA 0 0 NA 0 0 0 0 0 0 0 0 0 0 0 0 0 NA NA NA NA NA NA NA NA NA NA NA NA NA 0 NA NA NA 0 0 0 0 NA NA NA 0 Brachylaima microti) 160 F M M M M F F F NA F F M F M F F M M F M F M F 454 Peromyscus maniculatus 455 Dipodomys ordii 456 Peromyscus maniculatus 457 Reithrodontomys megalotis 458 Reithrodontomys megalotis 459 Peromyscus maniculatus 460 Peromyscus maniculatus 461 Peromyscus maniculatus 462 Peromyscus maniculatus 463 Peromyscus maniculatus 464 Peromyscus maniculatus 465 Peromyscus maniculatus 466 Peromyscus maniculatus 467 Peromyscus maniculatus 468 Peromyscus maniculatus 469 Reithrodontomys megalotis 470 Peromyscus maniculatus 471 Peromyscus maniculatus 472 Peromyscus maniculatus 473 Peromyscus maniculatus 474 Peromyscus maniculatus 475 Reithrodontomys megalotis 476 Reithrodontomys megalotis 477 Peromyscus maniculatus 478 Peromyscus maniculatus 479 Pocket mouse 480 Peromyscus maniculatus 481 Peromyscus maniculatus 482 Peromyscus maniculatus 483 Peromyscus maniculatus 484 Peromyscus maniculatus 485 Peromyscus maniculatus 486 Pocket mouse 487 Reithrodontomys megalotis 488 Peromyscus maniculatus 489 Peromyscus maniculatus 490 Peromyscus maniculatus 491 Peromyscus maniculatus 492 Peromyscus maniculatus 493 Pocket mouse AWB 454 AWB 455 AWB 456 AWB 457 AWB 458 AWB 459 AWB 460 AWB 461 AWB 462 AWB 463 AWB 464 AWB 465 AWB 466 AWB 467 AWB 468 AWB 469 AWB 470 AWB 471 AWB 472 AWB 473 AWB 474 AWB 475 AWB 476 AWB 477 AWB 478 AWB 479 AWB 480 AWB 481 AWB 482 AWB 483 AWB 484 AWB 485 AWB 486 AWB 487 AWB 488 AWB 489 AWB 490 AWB 491 AWB 492 AWB 493 M M M M M M F M M M M F F F F M M 453 Peromyscus maniculatus F sex AWB 453 Species 452 Peromyscus maniculatus num AWB 452 Host Number NA 18.5 15 20 20 18 19.5 12.0 13.5 19 19 7 16 12 18 20.0 9 15.5 5.0 10.0 14 20.5 18.5 11 9 9.0 11 18 17 9 19 19 15 16 18 11.0 12.5 17 16 16 22 mass NA 0 0 0 0 0 0 NA 0 0 0 0 0 0 1 0 1 0 0 0 0 0 NA 0 0 1 1 0 0 0 0 1 0 0 0 0 0 0 0 NA 0 0 ticks NA 0 1 0 0 0 0 NA 0 2 1 0 1 4 1 0 0 0 0 0 0 1 NA 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 1 NA 0 7 NA 0 0 0 0 0 0 NA 0 0 3 0 1 2 0 0 2 0 0 0 0 0 NA 0 0 0 0 1 7 0 0 5 3 0 0 0 0 0 1 NA 0 0 fleas lice 0 0 0 0 0 4 0 0 1 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 0 0 0 0 0 0 0 1 Number of nematodes NA 0 0 0 0 0 NA NA 0 0 0 0 0 0 NA 0 0 NA NA 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 0 0 NA NA 0 NA 0 0 0 Protospirura numidica NA 0 0 0 0 0 NA NA 0 0 0 0 0 0 NA 0 0 NA NA 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 0 0 NA NA 0 NA 0 0 0 Mastophorus muris NA 0 0 0 0 0 NA NA 1 0 0 0 0 0 NA 0 0 NA NA 0 0 0 0 0 NA 0 0 0 0 0 0 1 0 0 0 NA NA 0 NA 0 0 1 Pterygodermatites peromysci NA 0 0 0 0 4 NA NA 0 0 0 0 0 0 NA 0 0 NA NA 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 0 0 NA NA 0 NA 0 0 0 Syphacia peromysci NA 0 0 0 0 0 NA NA 0 0 0 0 0 0 NA 0 0 NA NA 0 0 0 0 0 NA 0 0 0 0 0 0 4 0 0 0 NA NA 0 NA 0 0 0 11 Aspiculuris americana NA 0 0 0 0 0 NA NA 0 0 0 0 0 0 NA 0 0 NA NA 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 0 0 NA NA 0 NA 0 0 0 Heligmosomoides vandegrifti NA 0 0 0 0 0 NA NA 0 0 0 0 0 0 NA 0 0 NA NA 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 0 0 NA NA 0 NA 0 0 0 Syphacia montana 0 1 0 0 0 0 0 0 0 2 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Number of cestodes NA 1 0 0 0 0 NA NA 0 2 0 1 0 0 NA 0 0 NA NA 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 0 0 NA NA 0 NA 0 0 0 cest.sp.1 NA 0 0 0 0 0 NA NA 0 0 0 0 0 0 NA 0 0 NA NA 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 0 0 NA NA 0 NA 0 0 0 Hymenolepis sp. NA 0 0 0 0 0 NA NA 0 0 0 0 0 0 NA 0 0 NA NA 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 0 0 NA NA 0 NA 0 0 0 cest.sp.3 NA 0 0 0 0 0 NA NA 0 0 0 0 0 0 NA 0 0 NA NA 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 0 0 NA NA 0 NA 0 0 0 cest.sp.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 Number of acanthocephalans NA 0 0 0 0 0 NA NA 0 0 0 0 0 0 NA 0 0 NA NA 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 0 0 NA NA 0 NA 0 0 0 acan.sp.1 NA 0 0 0 0 0 NA NA 0 0 0 0 0 0 NA 0 0 NA NA 0 0 0 0 0 NA 0 0 0 0 0 0 1 0 0 0 NA NA 0 NA 0 0 0 acan.sp.2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Number of trematodes NA 0 0 0 0 0 NA NA 0 0 0 0 0 0 NA 0 0 NA NA 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 0 0 NA NA 0 NA 0 0 0 Brachylaima microti) 161 F M F F F M M M M M M M M M M M F F M M M F M 496 Peromyscus maniculatus 497 Peromyscus maniculatus 498 Reithrodontomys megalotis 499 Peromyscus maniculatus 500 Peromyscus maniculatus 501 Peromyscus maniculatus 502 Peromyscus maniculatus 503 Peromyscus maniculatus 504 Peromyscus maniculatus 505 Peromyscus maniculatus 506 Microtus longicaudus 507 Peromyscus maniculatus 508 Peromyscus maniculatus 509 Reithrodontomys megalotis 510 Peromyscus maniculatus 511 Peromyscus maniculatus 512 Peromyscus maniculatus 513 Peromyscus maniculatus 514 Peromyscus maniculatus 515 Tamias dorsalis 516 Tamias dorsalis 517 Peromyscus maniculatus 518 Peromyscus maniculatus 519 Peromyscus maniculatus 520 Peromyscus maniculatus 521 Reithrodontomys megalotis 522 Peromyscus maniculatus 523 Peromyscus maniculatus 524 Peromyscus maniculatus 525 Peromyscus maniculatus 526 Peromyscus maniculatus 527 Peromyscus maniculatus 528 Peromyscus maniculatus 529 Peromyscus maniculatus 530 Peromyscus maniculatus 531 Peromyscus maniculatus 532 Peromyscus maniculatus 533 Peromyscus maniculatus 534 Peromyscus maniculatus 535 Peromyscus maniculatus AWB 496 AWB 497 AWB 498 AWB 499 AWB 500 AWB 501 AWB 502 AWB 503 AWB 504 AWB 505 AWB 506 AWB 507 AWB 508 AWB 509 AWB 510 AWB 511 AWB 512 AWB 513 AWB 514 AWB 515 AWB 516 AWB 517 AWB 518 AWB 519 AWB 520 AWB 521 AWB 522 AWB 523 AWB 524 AWB 525 AWB 526 AWB 527 AWB 528 AWB 529 AWB 530 AWB 531 AWB 532 AWB 533 AWB 534 AWB 535 M F M F F F M M F M M M M M F M M M 495 Peromyscus maniculatus M sex AWB 495 Species 494 Peromyscus maniculatus num AWB 494 Host Number 21 17 19 10.5 15 15 20.5 19.5 14 15 14.5 16.5 18 20 11.5 16 17.5 19 18.5 34.0 71.0 17.5 20.5 14 19 18 8.0 17.5 26 25.0 23 15 16 12 21 13.5 20 11.5 20 17 16.5 17 mass 0 0 0 0 0 0 0 0 0 0 0 0 1 0 NA 0 NA 0 0 0 0 0 0 NA 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 ticks 0 0 1 0 1 1 1 1 1 1 0 0 0 1 NA 1 NA 11 1 0 0 4 1 NA 0 4 0 8 3 0 1 0 2 1 0 0 1 0 0 1 2 0 1 0 0 0 0 1 0 1 1 0 0 0 0 0 NA 0 NA 0 0 0 0 0 0 NA 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 fleas lice 3 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 5 5 0 0 1 0 0 5 0 0 0 0 0 0 0 0 0 0 2 0 0 Number of nematodes 1 0 0 0 0 0 0 0 0 0 0 0 0 0 NA 0 0 0 0 NA NA 0 0 0 0 0 NA 0 0 NA 0 0 0 0 0 0 0 NA 0 0 0 0 Protospirura numidica 0 1 0 0 0 0 0 0 0 0 0 0 0 0 NA 0 0 0 5 NA NA 0 0 0 0 0 NA 0 5 NA 0 0 0 0 0 0 0 NA 0 0 0 0 Mastophorus muris 2 0 0 0 0 0 0 0 1 0 0 0 0 0 NA 0 0 0 0 NA NA 0 0 0 1 0 NA 0 0 NA 0 0 0 0 0 0 0 NA 0 0 0 0 Pterygodermatites peromysci 0 0 0 0 0 0 0 0 0 0 0 0 0 0 NA 0 0 0 0 NA NA 5 0 0 0 0 NA 0 0 NA 0 0 0 0 0 0 0 NA 0 2 0 0 Syphacia peromysci 0 0 0 0 0 0 0 0 0 0 0 0 0 0 NA 0 0 0 0 NA NA 0 0 0 0 0 NA 0 0 NA 0 0 0 0 0 0 0 NA 0 0 0 0 12 Aspiculuris americana 0 0 0 0 0 0 0 0 0 0 0 0 0 0 NA 0 0 0 0 NA NA 0 0 0 0 0 NA 0 0 NA 0 0 0 0 0 0 0 NA 0 0 0 0 Heligmosomoides vandegrifti 0 0 0 0 0 0 0 0 0 0 0 0 0 0 NA 0 0 0 0 NA NA 0 0 0 0 0 NA 0 0 NA 0 0 0 0 0 0 0 NA 0 0 0 0 Syphacia montana 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 0 1 2 0 0 0 2 0 1 0 0 0 0 0 0 0 0 1 0 1 0 Number of cestodes 0 0 0 0 0 0 0 0 1 0 0 0 0 0 NA 0 0 1 0 NA NA 1 1 0 0 0 NA 1 0 NA 0 0 0 0 0 0 0 NA 0 0 0 0 cest.sp.1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 NA 0 0 1 0 NA NA 0 0 0 0 0 NA 1 0 NA 0 0 0 0 0 0 0 NA 1 0 1 0 Hymenolepis sp. 0 0 0 0 0 0 0 0 0 0 0 0 0 0 NA 0 0 0 0 NA NA 0 1 0 0 0 NA 0 0 NA 0 0 0 0 0 0 0 NA 0 0 0 0 cest.sp.3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 NA 0 0 0 0 NA NA 0 0 0 0 0 NA 0 0 NA 0 0 0 0 0 0 0 NA 0 0 0 0 cest.sp.4 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Number of acanthocephalans 0 0 0 0 0 0 0 0 0 0 0 0 0 0 NA 0 0 0 0 NA NA 0 0 0 0 0 NA 0 0 NA 0 0 0 0 0 0 0 NA 0 0 0 0 acan.sp.1 0 0 0 0 0 0 0 0 0 0 0 0 0 2 NA 0 0 0 0 NA NA 0 0 0 0 0 NA 0 0 NA 0 0 0 0 0 0 0 NA 0 0 0 0 acan.sp.2 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Number of trematodes 0 0 0 0 0 0 3 0 0 0 0 0 0 0 NA 0 0 0 0 NA NA 0 0 0 0 0 NA 0 0 NA 0 0 0 0 0 0 0 NA 0 0 0 0 Brachylaima microti) 162 F F F M M M M F M M M M F M M M M M M F M F M 538 Peromyscus maniculatus 539 Peromyscus maniculatus 540 Peromyscus maniculatus 541 Peromyscus maniculatus 542 Peromyscus maniculatus 543 Peromyscus maniculatus 544 Reithrodontomys megalotis 545 Peromyscus maniculatus 546 Peromyscus maniculatus 547 Peromyscus maniculatus 548 Peromyscus maniculatus 549 Peromyscus maniculatus 550 Peromyscus maniculatus 551 Reithrodontomys megalotis 552 Peromyscus maniculatus 553 Peromyscus maniculatus 554 Peromyscus maniculatus 555 Peromyscus maniculatus 556 Peromyscus maniculatus 557 Peromyscus maniculatus 558 Peromyscus maniculatus 559 Peromyscus maniculatus 560 Peromyscus maniculatus 561 Peromyscus maniculatus 562 Peromyscus maniculatus 563 Peromyscus maniculatus 564 Peromyscus maniculatus 565 Peromyscus maniculatus 566 Peromyscus maniculatus 567 Peromyscus maniculatus 568 Peromyscus maniculatus 569 Peromyscus maniculatus 570 Peromyscus maniculatus 571 Peromyscus maniculatus 572 Peromyscus maniculatus 573 Peromyscus maniculatus 574 Peromyscus maniculatus 575 Peromyscus maniculatus 576 Peromyscus maniculatus AWB 538 AWB 539 AWB 540 AWB 541 AWB 542 AWB 543 AWB 544 AWB 545 AWB 546 AWB 547 AWB 548 AWB 549 AWB 550 AWB 551 AWB 552 AWB 553 AWB 554 AWB 555 AWB 556 AWB 557 AWB 558 AWB 559 AWB 560 AWB 561 AWB 562 AWB 563 AWB 564 AWB 565 AWB 566 AWB 567 AWB 568 AWB 569 AWB 570 AWB 571 AWB 572 AWB 573 AWB 574 AWB 575 AWB 576 F F M M M F F F F M F M M M M F F 537 Peromyscus maniculatus M sex AWB 537 Species 536 Peromyscus maniculatus num AWB 536 Host Number 15 23.5 14.5 21 14 10 12.5 20.5 24 20 15 19.5 18 18 18.5 19 20 15 20 14 19 11 17 26.5 14 9.5 13 15.5 19 20 17 16.5 8.5 17.5 14 20 19 20 16 16.5 12.5 mass 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 38 1 10 0 0 0 11 0 0 0 0 0 0 0 0 0 NA 2 5 0 11 6 0 2 4 ticks 1 2 1 3 1 2 0 1 4 3 0 1 1 0 2 0 0 0 0 0 2 1 1 1 1 0 0 0 2 1 0 0 NA 1 1 1 1 2 0 2 1 7 0 1 0 0 0 0 0 2 2 0 0 0 0 0 0 4 0 0 9 1 4 16 0 1 0 0 0 0 0 0 6 NA 0 1 0 6 0 0 0 0 fleas lice 0 0 1 0 0 0 0 0 1 0 0 1 0 0 6 2 0 2 0 1 6 0 0 0 0 9 0 0 1 1 0 0 0 0 0 1 0 2 1 0 2 Number of nematodes 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 0 2 0 0 0 0 0 0 0 NA 0 0 1 0 0 0 NA 0 0 1 0 2 0 0 2 Protospirura numidica 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 6 0 0 0 0 NA 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 Mastophorus muris 0 0 0 0 0 0 0 0 1 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 NA 0 0 0 1 0 0 NA 0 0 0 0 0 1 0 0 Pterygodermatites peromysci 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 NA 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 Syphacia peromysci 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 13 Aspiculuris americana 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 Heligmosomoides vandegrifti 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 Syphacia montana 0 7 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 1 0 0 0 1 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 Number of cestodes 0 5 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 1 0 0 0 0 0 NA 0 0 0 0 1 0 NA 0 0 0 0 0 0 0 0 cest.sp.1 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 NA 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 Hymenolepis sp. 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 cest.sp.3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 cest.sp.4 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 24 0 0 1 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Number of acanthocephalans 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 acan.sp.1 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 24 0 0 1 0 NA 2 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 acan.sp.2 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Number of trematodes 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 Brachylaima microti) 163 F M M M F M F 595 Peromyscus maniculatus 596 Lemmiscus curtatus 597 Peromyscus maniculatus 598 Peromyscus maniculatus 599 Peromyscus maniculatus 600 Peromyscus maniculatus 601 Peromyscus maniculatus 602 Peromyscus maniculatus 603 Peromyscus maniculatus 604 Peromyscus maniculatus 605 Peromyscus maniculatus 606 Peromyscus maniculatus 607 Peromyscus maniculatus 608 Peromyscus maniculatus 609 Peromyscus maniculatus 610 Tamias dorsalis AWB 595 AWB 596 AWB 597 AWB 598 AWB 599 AWB 600 AWB 601 AWB 602 AWB 603 AWB 604 AWB 605 AWB 606 AWB 607 AWB 608 AWB 609 AWB 610 618 Peromyscus maniculatus M 594 Peromyscus maniculatus AWB 594 AWB618 F 593 Peromyscus maniculatus AWB 593 617 Peromyscus maniculatus F 592 Peromyscus maniculatus AWB 592 AWB617 M 591 Peromyscus maniculatus AWB 591 616 Peromyscus maniculatus F 590 Peromyscus maniculatus AWB 590 AWB616 M 589 Peromyscus maniculatus AWB 589 615 Peromyscus maniculatus F 588 Peromyscus maniculatus AWB 588 AWB615 M 587 Peromyscus maniculatus AWB 587 614 Peromyscus maniculatus M 586 Microtus longicaudus AWB 586 AWB614 M 585 Peromyscus maniculatus AWB 585 613 Peromyscus maniculatus M 584 Peromyscus maniculatus AWB 584 AWB613 F 583 Peromyscus maniculatus AWB 583 611 Peromyscus maniculatus M 582 Peromyscus maniculatus AWB 582 612 Peromyscus maniculatus F 581 Peromyscus maniculatus AWB 581 AWB612 F 580 Peromyscus maniculatus AWB 580 AWB611 M 579 Peromyscus maniculatus AWB 579 M F F F M F M F F M M F F M F M M F 578 Peromyscus maniculatus F sex AWB 578 Species 577 Peromyscus maniculatus num AWB 577 Host Number 14.5 9.5 9 19.5 20 25 17 16.5 52.5 14.5 18 13 20 27.5 23.5 21.5 15 20 18 20 18 12 16.0 18 14 20 15 11.5 16.5 21 12 22 34.0 15 19 16 11.5 14.5 18.5 15 11 14 mass 0 0 0 3 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 2 1 0 0 0 0 0 0 0 0 0 0 ticks 1 1 2 3 6 2 10 8 1 3 6 0 2 2 0 0 1 3 0 0 0 0 0 1 0 0 0 3 0 1 1 0 1 1 1 2 0 1 1 2 1 3 0 1 0 0 4 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 3 0 0 0 3 0 0 10 0 0 0 0 0 0 0 0 0 fleas lice 0 0 0 0 0 1 0 0 7 0 4 0 0 0 6 0 0 3 0 6 1 0 0 13 0 1 0 0 0 27 0 0 0 0 1 16 0 0 0 0 0 1 Number of nematodes 0 0 0 0 0 0 0 0 NA 0 4 0 0 0 1 0 0 3 0 2 1 0 NA 0 0 1 0 0 0 27 0 0 NA 0 0 0 0 0 0 0 0 0 Protospirura numidica 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 0 0 0 1 0 NA 13 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 0 Mastophorus muris 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 5 0 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 0 NA 0 1 16 0 0 0 0 0 1 Pterygodermatites peromysci 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 0 0 4 0 0 NA 0 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 0 Syphacia peromysci 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 0 14 Aspiculuris americana 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 0 Heligmosomoides vandegrifti 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 0 Syphacia montana 0 0 0 0 0 0 1 0 0 0 0 0 0 1 2 0 0 0 0 0 0 0 2 1 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 Number of cestodes 0 0 0 0 0 0 1 0 NA 0 0 0 0 1 2 0 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 0 cest.sp.1 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 0 0 0 0 0 NA 1 0 0 0 0 0 0 0 0 NA 0 0 1 1 0 0 0 0 0 Hymenolepis sp. 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 0 cest.sp.3 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 0 cest.sp.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8 0 0 0 0 0 0 Number of acanthocephalans 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 0 NA 0 0 8 0 0 0 0 0 0 acan.sp.1 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 0 2 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 0 acan.sp.2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Number of trematodes 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 0 0 0 0 Brachylaima microti) 164 M NA M M M M M F M M F M F M F F M M M F M M M 621 Peromyscus maniculatus 622 Peromyscus maniculatus 623 Peromyscus maniculatus 624 Peromysus truei 625 Peromyscus maniculatus 626 Peromyscus maniculatus 627 Peromyscus maniculatus 628 Peromyscus maniculatus 629 Peromyscus maniculatus 630 Peromyscus maniculatus 631 Peromyscus maniculatus 632 Peromyscus maniculatus 633 Peromyscus maniculatus 634 Peromyscus maniculatus 635 Peromyscus maniculatus 636 Peromyscus maniculatus 637 Peromyscus maniculatus 638 Peromyscus maniculatus 639 Peromyscus maniculatus 640 Peromyscus maniculatus 641 Peromyscus maniculatus 642 Peromyscus maniculatus 643 Peromyscus maniculatus 644 Peromyscus maniculatus 645 Peromyscus maniculatus 646 Peromyscus maniculatus 647 Peromyscus maniculatus 648 Peromyscus maniculatus 649 Peromyscus maniculatus 650 Peromyscus maniculatus 651 Peromyscus maniculatus 652 Peromyscus maniculatus 653 Peromyscus maniculatus 654 Peromyscus maniculatus 655 Peromyscus maniculatus 656 Peromyscus maniculatus 657 Peromyscus maniculatus 658 Peromyscus maniculatus 659 Peromyscus maniculatus AWB621 AWB622 AWB623 AWB624 AWB625 AWB626 AWB627 AWB628 AWB629 AWB630 AWB631 AWB632 AWB633 AWB634 AWB635 AWB636 AWB637 AWB638 AWB639 AWB640 AWB641 AWB642 AWB643 AWB644 AWB645 AWB646 AWB647 AWB648 AWB649 AWB650 AWB651 AWB652 AWB653 AWB654 AWB655 AWB656 AWB657 AWB658 AWB659 M F F M M M M F M M M M M M M M M 620 Peromyscus maniculatus M sex AWB620 Species 619 Peromyscus maniculatus num AWB619 Host Number NA 13 26 13.5 14 17 15 14.5 20 19.5 15 17 16 16.5 23.5 14 22 16.5 15 16 14 15 14.5 23 10.5 16 9.5 15.5 18.5 21 26 17 21 19.5 17 25 17.5 21.5 18.5 20.5 19.5 mass 9 0 3 8 7 5 1 0 1 0 1 0 1 0 8 3 1 0 1 17 1 2 0 3 1 0 3 0 3 0 1 0 1 0 1 NA 3 4 1 3 2 ticks 6 3 1 6 2 4 4 0 6 4 1 2 3 0 5 4 5 7 3 2 11 2 0 7 5 4 3 0 5 1 2 6 4 1 3 NA 2 14 3 6 8 0 0 2 3 1 5 0 0 7 5 3 1 36 0 0 0 0 0 0 0 0 55 0 2 4 0 2 11 2 0 0 0 0 4 0 NA 0 0 0 0 0 fleas lice 0 0 0 3 0 0 0 0 0 0 0 2 0 0 0 0 1 25 0 0 0 0 0 0 0 0 0 0 0 5 0 1 0 14 18 NA 1 0 0 0 5 Number of nematodes 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 NA 0 0 0 0 5 Protospirura numidica 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 Mastophorus muris 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 Pterygodermatites peromysci 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 Syphacia peromysci 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 15 Aspiculuris americana 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 Heligmosomoides vandegrifti 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 Syphacia montana 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 0 0 0 0 0 0 0 1 Number of cestodes 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 NA 0 0 0 0 1 cest.sp.1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 0 0 0 NA 0 0 0 0 0 Hymenolepis sp. 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 cest.sp.3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 cest.sp.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Number of acanthocephalans 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 acan.sp.1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 acan.sp.2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Number of trematodes 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 NA 0 0 0 0 0 Brachylaima microti) 165 F F M F M M F F M M F M M M M 662 Peromyscus maniculatus 663 Peromyscus maniculatus 664 Peromyscus maniculatus 665 Peromyscus maniculatus 666 Peromyscus maniculatus 669 Ammospermophilus leucurus 670 Ammospermophilus leucurus 671 Perognathus 672 Ammospermophilus leucurus 673 Ammospermophilus leucurus 675 Peromysus truei 676 Peromysus truei 677 Peromysus truei 678 Peromysus truei 679 Peromysus truei 680 Peromysus truei 681 Peromysus truei 683 Peromysus truei AWB662 AWB663 AWB664 AWB665 AWB666 AWB669 AWB670 AWB671 AWB672 AWB673 AWB675 AWB676 AWB677 AWB678 AWB679 AWB680 AWB681 AWB683 NA F M M 661 Peromyscus maniculatus M sex AWB661 Species 660 Peromyscus maniculatus num AWB660 Host Number NA 17.5 26.0 17.0 20.0 14.0 19.0 17.0 125.0 66.0 24.0 73.5 96.0 18 24 15.5 8 16.5 17 18 mass NA 10 0 6 1 0 6 3 9 0 NA 0 1 0 0 2 2 1 2 1 ticks NA 2 4 3 2 0 3 0 6 25 NA 2 10 10 5 5 0 4 5 4 NA 0 0 2 0 13 2 10 0 15 NA 34 2 1 0 1 0 1 1 0 fleas lice NA NA NA NA NA NA NA NA NA NA NA NA NA 0 0 0 0 4 0 0 Number of nematodes NA NA NA NA NA NA NA NA NA NA NA NA NA 0 0 0 0 0 0 0 Protospirura numidica NA NA NA NA NA NA NA NA NA NA NA NA NA 0 0 0 0 0 0 0 Mastophorus muris NA NA NA NA NA NA NA NA NA NA NA NA NA 0 0 0 0 0 0 0 Pterygodermatites peromysci NA NA NA NA NA NA NA NA NA NA NA NA NA 0 0 0 0 0 0 0 Syphacia peromysci NA NA NA NA NA NA NA NA NA NA NA NA NA 0 0 0 0 0 0 0 16 Aspiculuris americana NA NA NA NA NA NA NA NA NA NA NA NA NA 0 0 0 0 0 0 0 Heligmosomoides vandegrifti NA NA NA NA NA NA NA NA NA NA NA NA NA 0 0 0 0 0 0 0 Syphacia montana NA NA NA NA NA NA NA NA NA NA NA NA NA 0 0 0 0 0 0 0 Number of cestodes NA NA NA NA NA NA NA NA NA NA NA NA NA 0 0 0 0 0 0 0 cest.sp.1 NA NA NA NA NA NA NA NA NA NA NA NA NA 0 0 0 0 0 0 0 Hymenolepis sp. NA NA NA NA NA NA NA NA NA NA NA NA NA 0 0 0 0 0 0 0 cest.sp.3 NA NA NA NA NA NA NA NA NA NA NA NA NA 0 0 0 0 0 0 0 cest.sp.4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Number of acanthocephalans NA NA NA NA NA NA NA NA NA NA NA NA NA 0 0 0 0 0 0 0 acan.sp.1 NA NA NA NA NA NA NA NA NA NA NA NA NA 0 0 0 0 0 0 0 acan.sp.2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Number of trematodes NA NA NA NA NA NA NA NA NA NA NA NA NA 0 0 0 0 0 0 0 Brachylaima microti) 166 APPENDIX E HISTOPATHOLOGY RESULTS OF RODENTS Table E.1. Results of histopathology for rodents captured in the Great Basin. Heart, lung, kidney, and liver tissue was examined for diseases and parasites using histology. Listed are the collection numbers, species of rodent, and any parasites and pathologies found. Rodent tissues were examined and diagnosed by Dr. David Gardiner, Animal Reference Pathology. Collection number* Rodent species Parasites found Pathology AWB7 Peromyscus maniculatus None Small amount of interstitial nephritis AWB9 Peromyscus maniculatus None Pneumonia-cause unknown AWB26 Peromyscus maniculatus None Small amount of interstitial nephritis AWB27 Peromyscus maniculatus None Some mild renal mineralization AWB28 Peromyscus maniculatus None Small amount of interstitial nephritis AWB33 Tamias dorsalis None Mild crhronic pyelitis and rare inflammation in the liver AWB34 Tamias dorsalis None Mild chronic pyelitis AWB35 Tamias dorsalis None Hyperplastic bronchial associated lymphoid tissue (BALT) AWB36 Tamias dorsalis None AWB38 Peromyscus maniculatus None AWB41 Peromyscus maniculatus None Both adrenal glands present. Mild chronic pyelitis Liver has extramedullary hematopoiesis (EMH), contains a nodule of lymphoid tissue in the perirenal soft tissue Abnormal adrenal gland morphology (either congenital or developmental abnormality) 168 Table E.1. continued Mild lymphocytic infiltrates present in liver Focal area of hepatic mineralization; focal area of interstial lymphocytic inflammation AWB43 Peromyscus maniculatus None AWB44 Peromyscus maniculatus None AWB45 Peromyscus maniculatus None Mild pyelitis, hyperplastic BALT AWB46 Tamias minimus None Mild pyelitis AWB48 Peromyscus maniculatus None Mild EMH in liver AWB50 Peromyscus maniculatus None Mild liver EMHand mild mineralization AWB51 Peromyscus maniculatus None Mild BALT hyperplasia; both adrenal glands present AWB62 Peromyscus maniculatus Capillaria hepatica Capillariasis AWB64 Peromyscus maniculatus Emmonsia crescens Adiaspiromycosis AWB71 Peromyscus maniculatus None Mild EMH in liver AWB72 Peromyscus maniculatus None Hyperplastic BALT, adrenal gland present AWB78 Peromyscus maniculatus None EMH in liver AWB83 Peromyscus maniculatus None Hyperlastic BALT AWB84 Peromyscus maniculatus None EMH in liver AWB85 Peromyscus maniculatus None EMH in liver AWB86 Peromyscus maniculatus None EMH focus in lung AWB93 Peromyscus maniculatus None Focus of mineralization in liver; hyperplastic BALT; focus of EMH in kidney AWB95 Peromyscus maniculatus None Small amount of EMH in kidney AWB96 Tamias dorsalis None Abundant EMH in liver, hyperplastic BALT 169 Table E.1. continued AWB97 Neotoma lepida None Focus of EMH in lung AWB98 Peromyscus truei None Hyperplastic BALT, pyelitis, EMH in liver AWB107 Peromyscus maniculatus None Mild EMH AWB109 Peromyscus maniculatus None Mild liver EMH AWB113 Peromyscus truei None Two pulmonary granulomas-cause not apparent AWB115 Peromyscus maniculatus None Hyperplastic BALT AWB117 Peromyscus maniculatus Emmonisa crescens Adiaspiromycosis AWB120 Peromyscus maniculatus None Mild pyelitis AWB121 Peromyscus maniculatus None Severe interstitial nephritis-cause not apparent AWB127 Peromyscus maniculatus None Small amount of pancreas present AWB130 Micotus montanus Emmonisa crescens Adiaspiromycosis AWB133 Peromyscus maniculatus None Mild EMH in liver AWB140 Peromyscus maniculatus None Mild EMH in liver AWB143 Microtus longicaudus Emmonsia crescens Adiaspiromycosis, inflammation around bile duct * Animals are located at the Natural History Museum of Utah in Salt Lake City, UT APPENDIX F SEQUENCES OF PARASITE SPECIES OF DEER MICE Table F.1. Cytochrome oxidase I (COI) gene sequences of parasite species of deer mice collected in the Great Basin. Sequences are the sequences from one representative individual of each species. Group Nematode Nematode Parasite species Sequence of representative individual Protospirura numidica GAGGTTTATATTATTATTTTGCCGGCGTTTGGTGT TATCAGGGAGGCTGTGCTTTTTCTAACTGATAAG GAGCGTTTGTTTGGGCAAACTAGAATGACCTTTG CTTCTATTTGAATTGCTATTTTAGGTACTTCTGTA TGAGGTCATCATATATATACTGCTGGTTTGGATAT TGATACTCGTACTTATTTTAGTGCTGCTACTATGA TTATTGCTATTCCTAGGGCTGTTAAGGTTTTTAAT TGGTTGGGAACTTTATTTGGTTCTCGGCAGATTTT TCAGCCTTTGTGGTGTTGAACTTATAGTTTTATTT TATTGTTTACTGTAGGGGGGTTGAGAGGAATTAT TTTGAGTACTGCTAGTCTGGATATTGTTTTGCATG ATACTTATTATGTAGTTGCCCATTTTCATTATGTT TTAAGTTTTAGGTGCTA Pterygodermatites peromysci CCTGAGGTTTATATTATTATTTTGCCGGCTTTTGG TATTGTGAGAGAGTGTGTTTTGCAGTTAAGTGAT AAGGAGTATTTATTTGGTCAGATAAGAATGATTT TTGCTTCTGTTTGGATTGCTGTTTTGGGCCTGACT GTGTGAGGGCATCATATGTATACAGCTGGGCTGG ATATTGATACTCGTGTGTATTTTAGTGCGGCTACT ATGATTATTGCTGTTCCTAGCGCAGTTAAGATTTT TAATTGGTTATCTACTCTTTATGGCTCTGATCAGG TTTTTCAGCCTTTATTGTGTTGGACTTATAGTTTTA TTTTGATATTTGCTACTGGTGGTATTACTGGTATT GTTTTGAGGGCGGCTAGGTTGGATGTGTTATTAC ATGATACATATTATGTGGTTGCTCATTTTCATTAT G 171 Table F.1. continued. Nematode Nematode Nematode Mastophorus muris TGAGGTTTATATTATTATTTTACCTGCTTTTG GTATTATTAGTGAGTCGGTTTTGTTTTTAACT GATAAGGAGCGTTTGTTTGGTCAAACTAGGA TAACTTTCGCTTCTATTTGAATTGCTGTTTTA GGTACTTCGGTCTGGGGGCATCATATATACA CGGCTGGTTTGGATATCGATACCCGGACTTA TTTCAGGGCTGCTACTTTAATTATTGCTATCC CTAGGGCTGTAAAGGTTTTTAATTGGCTAGG GACTTTTTTTGGGTCTCATCAAAATATGCAG CCTTTGTGATGTTGAACTTATAGTTTTATTTT TTTGTTTACTTTGGGTGGTTTAAGTGGTATTA TTTTGAGTACCGCTAGTTTGGATATTATTCTT CATGACACTTATTATGTGGTGGCTCATTTTC ATTATGTTTTAAG Heligmosomoides vandegrifti CCTGAGGTTTATATTTTGATTTTACCTGCATT TGGTATTACCAGGCAGTCAACTTTATATTTA ACAGGTAAAAAGGAGGTTTTTGGTTCATTAG GAATGGTATATGCTATTTTAAGTATTGGATT GATTGGTTGTGTGGTTTGGGCTCATCATATG TATACTGTTGGTATGGATTTGGATTCTCGTG CTTATTTTACGGCTGCTACGATAGTTATTGCT GTACCTACTGGAGTAAAAGTGTTTAGGTGAT TAGCTACTTTGTTTGGTATAAAAATGAATTT TCAACCTGTTTTGTTATGAGTTTTAGGTTTTA TTTTTTTGTTTACTATTGGTGGTTTAACTGGG GTGGTTTTATCTAATTCTAGTTTGGATATTAT TTTACATGACACTTATTATGTGGTTAGACAT TTTCATTATGTTTTAAGTTTAGGTGCTA CCTGAGGTTTATATTCTTATTTTGCCTGCTTT TGGAATTATTAGACATAGGATTTTGTATTTG ACTGGTAAAAAGGAAGTTTTTGGTCATGTGG GAATAATTTATGCTGTTGTTTCTATTGCTTTA ATTGGGAGAGTAGTTTGGGGGCATCATATGT TTACTGTTGGTTTTGATGTTAGTGTACGTTTA TATTTTATGGTTGCTACTATGATTATTGCTGT Syphacia peromysci TCCTACAGGTATTAAGGTTTTTAGGTGGTTG TTGACTTTGTTGGGTGGTAAGTGTGTGTTTC ATCCTTTGTTGTTATGGGTTGTTGGTTTTATT TTTATGTTTACTTTGGGTGGTTTAACTGGAAT TATGGTAGCTAATCCTGTTTTGGATAATTTG TTTCATGATACTTATTTTGTAGTTGCGCATTT TCATTATGTTTTAAGTTTAGGTGCT 172 Table F.1. continued Nematode Nematode Cestode Aspiculuris americana TGAGGTTTATATTCTTATTTTACCGGCTTTTGG TATTATTAGTCATAGTGTGTTATATTTGACTGG TAAAAAGGAAGTTTTTGGTCATTTGGGCATGG TTTATGCTATTATTTCTATTGCTTTAATTGGGA GTGTTGTTTGAGGGCATCATATGTTTACTGTA GGTTTTGATATAAGAACTCGTTTATATTTTATG GCTGCTACTATAATTATTGCTGTGCCTACTGG GATTAAGGTTTTTAGTTGGTTGTTGACTTTGGT GGGTAATAATATAGTTTTTCAGCCTTTGCTTTT GTGGGTTATGGGGTTTATTTTTATGTTTACTTT GGGGGGTTTAACTGGTATTATGGTTGCTAATC CTGTTTTGGATAATTTGTTTCATGATACTTATT TTGTTGTTGCTCATTTTCATTATGTTTTAAGTT TAGGTGCTA Syphacia montana TGAGGTTTATATTTTGATTTTGCCTGCTTTTGG TATTATTAGTCATAGTATTTTGTATTTAACTGG TAAAAAAGAGGTGTTTGGTCATTTAGGTATGG TTTATGCTGTTATTTCTATTGCTTTGGTTGGTA GTGTTGTCTGGGGACATCATATATTTACTGTT GGTTTTGATATGAGTACTCGTTTGTATTTTATG GCTGCTACTATAATTATTGCTGTTCCTACTGGT ATTAAGGTTTTTAGTTGATTGATAACTTTGTTG GGGGGTTATTTTGTTGTTCATCCTTTGTTGATG TGAGTGATTGGTTTTGTTTTTATGTTTACATTG GGTGGTTTGACTGGTATTATGGTTGCTAATCC Hymenolepis sp. ATAATGAAAATGAGCCACAACAAATCACGTA TCATGCAAAACTTTATCTAAAACACAAGCAGA TAACACTATGCCCGTAACTCCACCAAAAGTAA AAAGAACTATAAAAGAAATTATTCATCATAAT ATGGGATCCATAGAACTAACCCGACATTTCAT CAGCATATATAATCAAGTAAAAACCTTAATAC CAGTGGGGACCCCTATAATCATAGTGACAGA CCTAAAAAAAACAGCCGTCTTAACATCCAAA CCAACAGTAAACATATGGTGGCCTCAAACACT ACTTCCTAAACACACTATAGAAAACATCGCAA ATAATAAACCGTAATAACCAAATACATCTGCA TTCATACTCAACCTCAAACAAATATGACTTAT AATTCCAAACCCTGGTAATATTAACACATAAA CCTCA 173 Table F.1. continued Acanth. Acanth. Moniliformis sp.1 ACGATCCAACAGTAACATAGTCAAAGCAGCCG CCAAAACAGGTACAGTTAAAATGATCAACCCA GATGTTACAATTAAAGATCACACAAACAATGT TAATTTTTCCAACCTAATACCCATCTCCTCATA CACACACCAAACAGTAGATACAATATTAACAG AAGCCAAGATAGAAGACAAACCTGCTACATGT AAAGATAAAACTATTAAATCCACAGAAACCCC TCTTCTAAACCCATAGGACCTTAAGGGAGGGT ATATAGTTCACCCAGTACCAGCCCCGTCTACTA ACATTGACATTATCAATAATACTAATGACCCTG GAAGTAACCAAAACCTAAAGTTGTTCAAGCGA GGAAATGCCATGTCACCCACACCTAGTATTAC TGGAACCATCCAATTACCAAACCCCCCTATCAT AATAGGTATAACCAAAAAGAAAATCATCAAAA TAGCATGTGACCTTACCAGTACATTATACAGGT GATCGTCTATCAACAAAGACCCTACACATCCC AACTCCAAACGAATTACCACCCTTAAAACTAC CCCCATTAGCCCCCTCCACAAAGCAAACAGAA CATACAACACACC Moniliformis sp. 2 CCAAAAGCAGCATCGTAAGAGCAGCCGCCAAA ACTGGCACAGTTAAAATAATCAACCCAGATGT AACAACCAAAGACCATACAAACAATGTTAGTT TTTCCAACCTGATACCCATATCCTCATACACAC ACCAAACAGTAGATACAATATTAACAGAAGCC AAAATAGAAGACAAACCTGCCACATGAAGAG ATAAAATCATTAAGTCCACAGAGACACCCCTA CTAAACCCATAAGACCTTAGGGGTGGGTACAC AGTTCACCCTGTACCCGCCCCATCTACTAGTAT TGACATCATTAACAATACTAACGATCCCGGTA ACAACCAAAATCTAAAATTATTTAATCGGGGG AATGCCATATCCCCTACACCTAGTATCACAGG AACCATCCAATTACCAAACCCCCCTATCATAAT AGGTATAACCAAAAAGAAGATCATCAAAATAG CATGTGACCTTACCAATACGTTATATAGGTGAT CGTCTATCAACAAAGACCCAACACACCCCAAC TCCAAACGAATTACCACCCTTAAGACCACCCC TATTAAACCACTCCACAAAGCAAACAAAACAT ACATGACA 174 Table F.1. continued Trematode Brachylaima microti GCAAAAGGTAAGATACTTTCAGCAACCTACT TCAACACAGTCTCTCAACTTTTGAAAGCAAC CACACAGTATCAATACTTTACAAAAGTACCA TTTTACAATAAACTACACTTTCAACGCAGGG TATCATCCTCAAAACAATAATATTTAGGGCA TCCTACGTACAAACCATGATGTGGTAAAGGT ACTGTACAAACATTCACCGCTACAGAAGGTG CTCCTCATAAACCCAAAATCTTATTACCTACA ACAATTGACTCTCACAATATAAACACTAAAA AGACACCTCTTATCACAGAAATTATACCACC AAGCGATGAAATTTTTTTCATTCAATAAAAT GCAGGATCATAGCAACACACCCGCCGAGGA AGCCCATACAAACCAAGAAAATGCATTGGAA AAAAACACAGATTAAATCCAACAATAGACAC CAACCAATGCCCCTGTAGTAAATACTTATTTA AACTACATCCGGTAATCACAGGCCACCACCA AAGTAAAAAAATAACTACAGTCCTGTAAGAA CCCAACGACAAAACGTAATGAAAATGAGCC ACAACAAACCACGTATCATGAAACAACGAAT CTAAAACAGAAGCTGACAAAACAATACCAGT AACACCCCCCACAGTAAACAAAAAGATAAA AGCAATTATTCACCACACCACAGGATCGAAT ATGGAATTTCGACTACTACCCAACATGTACA ACCACGAAAAAACCTTTATCCCCGTTGGAAT ACCAATAACCATAGTTACTGATCTAAAAAAA ACAGTCGTCTTTACATCTAACCCAACAACAA ACATATGATGAACCCATACAACACTCCCAAG ACATACAATAGCCCCCATAGCAGAAACTAAA CCATAGTAGCCAAACAGAGACTCATTATTAC TCAGCCTAGAACAGATATGCCCAACAACTCC GAACCCAGGTAGGATAAGAACATAAACCTC