GLOBAL EXPANSION OF ( ) AND THEIR ROLE IN MOVEMENT OF AVIAN HAEMOSPORIDIA

By

SHANNON PATRICIA MOORE

A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE

UNIVERSITY OF FLORIDA

2018

© 2018 Shannon Patricia Moore

To Mom, Dad, and Thomas

ACKNOWLEDGMENTS

I would first like to thank my thesis advisor Dr. Samantha Wisely for always being there to help troubleshoot problems or discussion questions about my research or writing. She allowed this research to be my own work, but steered me in the right direction whenever I need it. I would also like to acknowledge my committee, Dr. James

Austin, Dr. Abigail Powell, and Dr. Greg Glass. I am grateful for their comments and feedback throughout my thesis work.

I would like to thank the many people involved with sample collection, Mike

Milleson and the USDA BASH Biologists, Mike Legare and the Merritt Island National

Wildlife Refuge, Roger Widrick and the Sarasota International Airport, and Gene and

Laurent Lollis from Buck Island , without whom none of this research would have been possible.

I also thank Dr. Claudia Ganser for her training that prepared me for this project, as well as her assistance throughout and Lisa Shender for her assistance and training for conducting avian necropsies. I would also like to thank Hanna Innocent and

Gabriella Gonzalez, my enthusiastic mentees who assisted with this research and hopefully learned as much as they taught me about being a mentor.

I would like to thank the members of the Wisely Lab for their support and friendship throughout this process. In particular I would like to acknowledge Allison

Cauvin for travelling this process with me and being my exit buddy and Brandon Parker for always being supportive and providing coffee runs. I would like to thank Dr.

Geraldine Klarenberg for her mentoring and assistance in developing my skills in R. I would also especially like to thank Andrew Marx of the Austin Lab for taking time out of

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his own research to assist me with trouble shooting and brainstorming research complications, as well as offering guidance and advice.

Finally, I would like to offer the deepest thanks to my parents, fiancé, and friends for their continuous support, patience, and encouragement throughout my years of researching and writing this thesis. In particular, I would like to thank Kathleen Bonany for her countless hours editing and learning about my research to help improve my work. This would not have been possible without them. Thank you.

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TABLE OF CONTENTS

page

ACKNOWLEDGMENTS ...... 4

LIST OF TABLES ...... 8

LIST OF FIGURES ...... 10

ABSTRACT ...... 12

CHAPTER

1 INTRODUCTION: CATTLE (BUBULCUS IBIS) NATURAL HISTORY ...... 14

Invasive Species, Range Expansion, and Disease ...... 14 Natural History ...... 17 Habitat ...... 17 Diet ...... 18 Movement Patterns ...... 19 Documented Range Expansion ...... 19 and Europe ...... 20 The Americas ...... 20 ...... 21 and New Zealand ...... 22 Cattle Egret Pathogens and Parasites ...... 22 Range Expansion and Disease ...... 24

2 EXPANSION OF CATTLE EGRETS (BUBULCUS IBIS) IN RESPONSE TO GLOBAL LAND USE CHANGE ...... 29

Methods ...... 32 Data Collection ...... 32 Descriptive Data ...... 33 Statistical Relationship of Land Use Change and Cattle Egret Arrival ...... 33 Results ...... 37 Descriptive Data ...... 37 Statistical Relationship of Land Use Change and Cattle Egret Arrival ...... 41 Discussion ...... 42 Historical Expansion ...... 42 Land Use Change and Cattle Egret Arrival...... 43 Limitations of Historical Data ...... 46 Final Thoughts ...... 47

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3 DIVERSITY AND PHYLOGENETIC RELATIONSHIPS OF AVIAN HAEMOSPORIDIA IN CATTLE EGRETS (BUBULCUS IBIS), AND THEIR ROLE IN THE REGIONAL AND GLOBAL MOVEMENT OF HAEMOSPORIDIAN PARASITES ...... 66

Prevalence and Diversity of Haemosporidia in Cattle Egrets ...... 68 Regional Host and Geographic Specificity ...... 69 Global Movement of Haemosporidia ...... 69 Methods ...... 70 Sample Site and Field Methods ...... 70 Parasite Screening Using PCR ...... 71 Parasite Lineage Identification, Prevalence, and Diversity ...... 72 Regional Host and Geographic Specificity ...... 73 Global Movement of Haemosporidia ...... 74 Results ...... 74 Parasite Prevalence and Diversity ...... 74 Regional Host and Geographic Specificity ...... 76 Global Movement of Haemosporidia ...... 78 Discussion ...... 79 Parasite Prevalence and Diversity ...... 79 Regional Host and Geographic Specificity ...... 82 Global Movement of Haemosporidia ...... 83

4 CONCLUSION: CATTLE EGRET (BUBULCUS IBIS) AS A GLOBAL MOVER OF DISEASE ...... 111

LIST OF REFERENCES ...... 113

BIOGRAPHICAL SKETCH ...... 129

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LIST OF TABLES

Table page

1-1 Pathogens found in Cattle Egrets...... 25

1-2 Ectoparasites found in Cattle Egrets...... 26

1-3 Endoparasites found in Cattle Egrets...... 27

2-1 Land use change variables and corresponding shapefiles to be tested for correlation to Cattle Egret expansion...... 49

2-2 Corresponding time period, percent land use reference years, and sampling years for analysis of land use and Cattle Egret expansion...... 50

2-3 First occurrence of Cattle Egret in geographic regions based on museum record data...... 51

2-4 The correlation of the percent and rate of change (RoC) of each land use variable from the HYDE database...... 52

2-5 Generalized Linear Model results of top 20 models and the null model (no covariates) of Cattle Egret expansion and rate of change and percent of rain fed crops, irrigated crops, pasture land, and rangeland...... 53

2-6 The model fit for the best model based on Akaike’s Information Criteria from the Generalized Linear Model results of Cattle Egret expansion and land use change...... 54

3-1 Primers used for PCR of DNA extracted from Cattle Egrets to test for Haemoproteus spp., Plasmodium spp., and Leucocytozoon spp...... 86

3-2 Ratio of products used in PCR reactions to test DNA extracted from Cattle Egrets for Haemosporidia...... 87

3-3 Thermo-cycler profile for PCR reaction with outer primers HaemNFI and HaemNR3 to test DNA extracted from Cattle Egrets for Haemosporidia...... 88

3-4 Thermo-cycler profile for PCR reaction with inner primers HaemF and HaemR2 to test DNA extracted from Cattle Egrets for Plasmodium and Haemoproteus...... 89

3-5 Thermo-cycler profile for PCR reaction with inner primers HaemF and HaemR2 to test DNA extracted from Cattle Egrets for Leucocytozoon...... 90

3-6 Prevalence of parasite lineages of Plasmodium and Leucocytozoon found in Cattle Egrets in the southeast United States...... 91

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3-7 Lineages of Plasmodium spp. found in Cattle Egrets in the southeast United States with closest haplotype matches from GenBank database as of August 19, 2018 and corresponding sequence divergence...... 92

3-8 Lineages of Leucocytozoon spp. found in Cattle Egrets in the southeast United States with closest haplotype matches from GenBank database as of August 19, 2018 and corresponding sequence divergence...... 93

3-9 AMOVA results for Plasmodium and Leucocytozoon lineages from sampling locations across the southeast United States...... 94

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LIST OF FIGURES

Figure page

2-1 Cattle Egrets specimen locations over time, ranging from 1820 to 2017 ...... 55

2-2 Cattle Egret museum specimen occurrences from 1820 to 1870 ...... 56

2-3 Cattle Egret museum specimen occurrences from 1871 to 1921 ...... 56

2-4 Cattle Egret museum specimen occurrences from 1922 to 1972 ...... 57

2-5 Cattle Egret museum specimen occurrences from 1973 to 2017 ...... 57

2-6 Latitudinal distance from origin to first occurrences of Cattle Egrets in different regions ...... 58

2-7 Longitudinal distance from origin to first occurrences of Cattle Egrets in different regions ...... 59

2-8 Percentage of pasture land use with Cattle Egret expansion and absence from best fit GLM ...... 60

2-9 Percentage of irrigated crops land use with Cattle Egret expansion and absence from best fit GLM ...... 61

2-10 Rate of change of irrigated crops land use with Cattle Egret expansion and absence from best fit GLM ...... 62

2-11 Percentage of range land use with Cattle Egret expansion and absence from best fit GLM ...... 63

2-12 Percentage of rain fed crops land use with Cattle Egret expansion and absence from best fit GLM ...... 64

2-13 Rate of change of range land use with Cattle Egret expansion and absence from best fit GLM ...... 65

3-1 Sampling locations of Cattle Egret for Haemosporidia analysis...... 95

3-2 Phylogeny of all Plasmodium spp. lineages found in Cattle Egrets in the southeast United States ...... 96

3-3 Phylogeny of all Leucocytozoon spp. lineages found in Cattle Egrets in the southeast United States ...... 97

3-4 Phylogenetic tree of Plasmodium spp. lineages with additional Plasmodium spp. lineages found in the southeast United States and Caribbean basin from MalAvi database ...... 98

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3-5 Sequence identity matrix of Plasmodium spp. found in Cattle Egrets in the southeast United States with additional lineages sampled from in the southeast United States and Caribbean basin ...... 99

3-6 Phylogenetic tree of Leucocytozoon spp. lineages with additional Leucocytozoon spp. lineages found in the southeast United States and Caribbean basin from MalAvi database ...... 100

3-7 Sequence identity matrix of Leucocytozoon spp. found in Cattle Egrets in the southeast United States with additional lineages sampled from birds in the southeast United States and Caribbean basin ...... 101

3-8 Minimum spanning network of Plasmodium spp. mitochondrial DNA cytochrome b lineages from Cattle Egrets in the southeast United States ...... 102

3-9 Minimum spanning network of Leucocytozoon spp. mitochondrial DNA cytochrome b lineages from Cattle Egrets in the southeast United States ...... 103

3-10 Distribution of Plasmodium spp. lineages across the southeast United States 104

3-11 Distribution of Leucocytozoon spp. lineages across the southeast United States ...... 105

3-12 Binary connectivity map of sampling locations with lineage-level matches of Plasmodium ...... 106

3-13 Binary connectivity map of sampling locations with lineage-level matches of Leucocytozoon ...... 107

3-14 Phylogenetic tree of Plasmodium spp. lineages with closest NCBI BLAST matches from GenBank database ...... 108

3-15 Phylogenetic tree of Leucocytozoon spp. lineages with closest NCBI BLAST matches from GenBank database ...... 109

3-16 Key for family and continent labels in phylogenetic trees...... 110

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Abstract of Thesis Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Science

GLOBAL EXPANSION OF CATTLE EGRETS (Bubulcus ibis) AND THEIR ROLE IN MOVEMENT OF AVIAN HAEMOSPORIDIA

By

Shannon Patricia Moore

December 2018

Chair: Samantha Wisely Major: Wildlife Ecology and Conservation

Cattle Egrets (Bubulcus ibis) are a rapidly expanded species, yet little is known about the drivers of their expansion and their potential to transport pathogens. The objective of this thesis is to test the relationship of agricultural land use to Cattle Egret expansion and estimate their role in the movement of Haemosporidian parasites. A generalized linear model (GLM) was used with museum specimen to assess changes in land use as drivers of global Cattle Egret expansion. PCR and gel electrophoresis were used to determine prevalence of Plasmodium, Haemoproteus, and Leucocytozoon in samples from Cattle Egrets. Positive samples were sequenced for genetic analyses of

Haemosporidia parasites. The best model for Cattle Egret expansion included rate of change and percent of irrigated crops and rangeland, and percent of pasture land and rain fed crops. The GLM results indicated Cattle Egret expansion was correlated with the increase of more-intensively used agricultural land and with the decrease of less- intensively used agricultural land. Of the 516 Cattle Egrets, 0% screened positive for

Haemoproteus, 18.6% were positive for Plasmodium, and 39.1% screened positive for

Leucocytozoon. Lineages of Plasmodium and Leucocytozoon indicated differences in geographic structuring as a result of host generalist Plasmodium lineages and a host

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specific Leucocytozoon lineage. The Haemosporidia screening implicated Cattle Egrets as having the potential to move lineages globally and disperse them around a region.

This project provided a better understanding of the drivers that played a role in Cattle

Egret expansion and their ability to transport blood-borne pathogens.

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CHAPTER 1 INTRODUCTION: CATTLE EGRET (BUBULCUS IBIS) NATURAL HISTORY

Invasive Species, Range Expansion, and Disease

Invasive species are non-native species that cause damage in the habitats they expand into and are a global ecological and economic concern. There are several methods through which invasive species can expand. Accidental human introduction occurs when , such as the or Cuban tree , hitchhike on ships and other human transport to spread to new regions. In other incidences, animals are intentionally released by humans as in the case of unwanted Burmese pythons that were released due to the pet trade or Brazilian peppertree that was originally planted as an ornamental. The final major type of expansion is natural range expansion, such as in the case of kudzu or coyote. Natural range expansion can occur with several triggers, such as loss of competition, loss of predator or prey, climate change, or land use change (Amsellem et al. 2017, Mohan and Kariyanna 2008, Fiedler 2015, Balbontín et al. 2008, Martin et al. 2012). A prominent example of natural range expansion in

North America, the coyote, has spread rapidly due to loss of competition and land use change, resulting in their expansion into suburban habitats (Bordas 2016). Avian species have a high potential for natural range expansion due to their high mobility and capability to cross barriers.

Avian movement is distinctive for its diversity, ranging from transcontinental migration, regional migrations, wandering, juvenile dispersal, and even a lack of movement. Migration occurs seasonally between set geographic ranges and is influenced by changes in season resulting in fluctuations in resource availability, habitats, , and competition (Alerstam et al. 2003). Nomadism and juvenile

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dispersal are one-way movements with no consistent timing or direction. Nomadism, or wandering, is the most flexible of avian movements, with some birds moving hundreds of kilometers. Juvenile dispersal, or natal dispersal, occurs only in juveniles, rather than throughout the life of an individual (Coffey 1943, Browder 1973). Nomadism and juvenile dispersal are both thought to be triggered by resource availability or when a population density reached the habitat capacity.

As invasive species spread, they have the potential to transport novel pathogens into naïve environments. Invasive species can transport blood-borne pathogens and directly as in the case of feral hogs and pseudorabies in Florida (Pedersen et al.

2013, Giuliano 2010, Hernández 2017). Invasive species can also serve as mechanical transport, carrying or other vectors into new areas such as exotic and Cattle

Fever Ticks in Texas (Cárdenalis-Canales et al. 2011). The high mobility of avian species, particular via long-range and global migrations, makes them crucial epizootic factors and highly capable of transmitting diseases across the landscape (Figuerola et al. 2000). Diverse species can congregate at migrations stops, allowing for cross- species transmission or spillover to take place (Altizer et al. 2011). Nomadism and juvenile dispersal can result in diseases being carried to areas where birds had not previously contacted via regular migrations. Any of these long-distance movements could either increase transmission by transporting pathogens from one place to another, or reduce transmission risk by reducing the number of available hosts in an area (i.e.

“migratory escape”) (Loehle 1995).

Beyond the translocation of pathogens, the timing of movement and physiological stress of migration can play a role in the movement of pathogens. Timing of movement

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allows pathogens carried by migratory birds to warm climates to persist rather than dying off in cold weather in the extreme northern or southern latitudes, also known as

“over wintering” (Dowell 2001). Exposure to parasites in warm, tropical locations is a significant cost of migration when migratory birds return to their winter habitat

(Waldenström et al. 2002). The physiologic stress associated with migration can result in immunosuppression and increased susceptibility as well as the reactivation of otherwise latent infections (Reed et al. 2003). Long distance migration can also reduce pathogen prevalence by removing infected animals from the population, also known as

“migratory culling” (Bradley et al. 2005), resulting in a lower infection risk.

Environmental exposure along migratory routes and between wintering and breeding territories can also influence the pathogens carried. Exposure to feeding stations, domestic animals, and landfills all have implications in the transmission of diseases. Feeding stations result in artificially high densities and a high diversity of species, leading to high risk of transmission and contact with hosts, vectors, and pathogens they would not naturally encounter (Brown et al. 1982, Tarwater and Martin

2001, Altizer 2011). Shared water supply, pasture, and feeding with domestic animals can lead to birds sharing ectoparasites and diseases with susceptible livestock populations (Gortázar et al. 2007). Landfill sites can attract large numbers of birds

(Bowes et al. 1984, Sol et al. 1995), which then often roost in natural habitats, resulting in bacteria ingested at a landfill to reenter the food chain when excreted by birds

(Benskin et al. 2009).

Understanding avian movement and how it impacts the range expansion of individual species is vital to understanding natural history, species interactions, and the

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risk for disease transmission. The family’s global presence and migratory behavior makes them an excellent model for studying range expansion and applying landscape epidemiology. The heron family, Ardeidae, also known as the wading bird family, contains approximately 64 species with a nearly global distribution. are highly mobile and can be found in a wide variety of habitats. Flocking all year long,

Cattle Egrets are the most gregarious of all herons, forming dense breeding colonies and nonbreeding roosts, as well as being found in a variety of habitats, including, aquatic, domestic, and landfills.

Cattle Egrets (Bubulcus ibis) are one of the most widely and rapidly expanded birds, spreading globally in two centuries, and their adaptive behavior allows them to have an impact on both humans and wildlife. The distribution of Cattle Egrets was originally restricted to tropical and subtropical Africa and Asia, but spread to the

Americas in the late 1800s (Maddock and Geering 1994). The spread of human agriculture and the cattle industry, along with Cattle Egrets’ wandering and juvenile dispersal are believed to have facilitated this rapid expansion (Telfair II 2006, Hafner

1977, Siegfried 1978, Blaker 1971, Kopij 2008, Voison 1991, Myers 1979, Maddock and

Geering 1994, Hancock 1978).

Cattle Egret Natural History

Habitat

Cattle Egrets are habitat generalists, typically nesting and roosting in trees near marshlands or along rivers, similar to other species of the Ardeidae family, although water is not a requirement (Dusi and Dusi 1968, Krebs et al. 1994). Reports have also been made of Cattle Egrets roosting in close proximity to suburban neighborhoods, city trees, and heavily populated coastal areas (Mora and Miller 1998). Cattle Egrets often

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roost with other herons and egrets to lower the rate of fatality from predators such as rat snakes, Barred Owls, and alligators (Siegfried 1971b, Telfair II 2006). Cattle Egrets exhibit bi-parental care, keeping their nests continually attended with one parent present while the other forages or sleeps (Dusi et al. 1968).

Cattle Egrets can travel up to 60 km a day to suitable feeding habitat. Unlike other members of the Ardeidae family that are able to hunt in lakes or canals, Cattle

Egrets have adapted to forage on land and in shallow water and have lost the ability to forage in deeper water due to their inability to cope with light refraction (Katzir et al.

1999). Cattle Egrets are frequently found foraging in cow pastures, around other large herbivores, behind tractors and mowers, and in rice fields as it allows them to easily exploit food. As generalists, Cattle Egrets have also been seen foraging along highways, on air fields, and around fields disturbed by fire. Cattle, large herbivores, and tractors disturb the land, turning up , allowing nearby Cattle Egrets to consume more insects while exerting less energy (Heatwole 1965, Dinsmore 1973, Grubb 1976).

Similarly, Cattle Egrets forage in rice fields during winter months because they are plowed post-harvest and in the breeding season when the rice fields undergo hydrologic fluctuations. Cattle Egrets have also indicated a preference for shallow lakes or swamps as they also provide easily accessible food, similar to rice fields (Katzir et al.

1999, Lombardini et al. 2001). In addition to their generalism in foraging habitats, Cattle

Egret exhibit a generalist diet.

Diet

Cattle Egrets have broad, highly adaptable diets. While generally insectivorous with and crickets being the largest part of their diet, Cattle Egrets have also been known to consume , lizards, eggs, fish, and rodents (Ruiz 1984, Singh et

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al. 1988, Sodhi 1989, Telfair II 2006). Cattle Egrets have been observed catching on top of chicken coops and flies attracted to rotting fish from fish-cleaning operations

(Fogarty et al. 1973) and foraging in garbage (Feare 1975, Dean 1978). In the Dry

Tortugas in Florida, Cattle Egrets have been observed feeding on migrating warblers

(Browder 1973). The generalism of foraging behavior and diet are believed to have helped facilitate Cattle Egrets’ range expansion (Rice 1956, Skead 1952, Telfair II

2006).

Movement Patterns

In addition to Cattle Egrets’ generalist habitat and diet, they also exhibit generalism in their movement patterns. Cattle Egrets are partial migrators and exhibit juvenile dispersal and wandering habits (Browder 1973). Cattle Egret populations can either migrate seasonally or be sedentary and exhibit no migration, thus Cattle Egrets being described as partial migrators. The juvenile dispersal and wandering habits are believed to be triggered by resource limitations (Croteau 2010). Juvenile dispersal and wandering can be omnidirectional and is not confined by geographic locations or distance. Juvenile dispersal occurs during late summer and early fall and can cover distance of 1,900-5,000 km (Browder 1973, Telfair II 1983, Telfair II 1993). Wandering can be reoccurring but is not confined by a seasonal schedule, as in the case of migration. Dispersing juvenile and wandering Cattle Egrets are believed to provide a mechanism for colonizing new territories (Browder 1973, Massa et al. 2014) and enabling the establishment of migratory and sedentary populations across the world.

Documented Range Expansion

Cattle Egrets are one of the most rapidly expanded species in the world, spreading globally in two centuries. The rapid expansion of Cattle Egrets is believed to

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be facilitated by their generalist behavior and juvenile dispersal and wandering (Rice

1956, Skead 1952, Telfair II 2006). Cattle Egrets are native to east Africa, southern

Portugal, , and the Asian tropics (Brown et al. 1982). There are generally considered to be two main subspecies of Cattle Egrets: the

(Bubulcus ibis ibis) and the (Bubulcus ibis coromandus). The

Western Cattle Egret originated in east Africa, southern , and Spain and spread westward, while the Eastern Cattle Egret is native to the Asian tropics and spread eastward with their historic ranges being separated by the Iranian area (Vaurie 1963).

Africa and Europe

The historical population of Cattle Egrets in east Africa expanded across the continent since 1900 with a reported significant expansion between 1920 and 1940

(Maddock and Geering 1994). Cattle Egrets were present in southern Portugal and

Spain in the late 1800s which is considered part of their native range (Irby 1875, Rey

1872, d’Oliveira 1896). Cattle Egrets were reported in in the 1950s (Vaurie

1963), however overall colonies in Europe have been relatively small with small population growth (Voisin 1991).

The Americas

Cattle Egrets expanded from the west coast of Africa across the Atlantic to northeast South America where they were reported in Surinam between 1877 and 1882

(Palmer 1962) and in British Guiana between 1911 and 1912 (Westmore 1963) and considered established by 1950 (Havershmidt 1951). Cattle Egrets continued to expand throughout South America, eventually reaching Patagonia in 1977 (Crosby

1972, Telfair II 1983). Individual Cattle Egrets have been found south of Patagonia in

Antarctica as early as 1948 and at several other southern localities as recently as 1993,

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although these have all been individuals (Watson 1975, Strange 1979, Rootes 1988,

Prince & Croxall 1983, Silva et al. 1995).

During the Cattle Egret expansion across South America, Cattle Egrets also expanded northward into Central and (Crosby 1972). The first reported

North America sighting was in 1941 or 1942 in Florida where they became quickly established by 1954 (Maddock and Gerring 1994). The rapid establishment of Cattle

Egret in the southern United States suggests that Cattle Egrets moved directly from

South America, rather than island hopping through the Caribbean (Telfair II 1983). It is suggested that Cattle Egrets travelled with other birds that were migrating between

South and North America (Rice 1956). First sightings of Cattle Egrets across North

America, extending to Newfoundland, occurred during the 1950s to 1970s. Cattle

Egrets were reported reaching the west coast in in 1962, likely as a result of expansion through Central America, , and Texas (Telfair II 1983). Cattle Egrets reached Alaska by 1981 (Maddock and Geering 1994). Cattle Egrets now have established populations in southern North America that migrate to the north (Telfair II

2006). Cattle Egret migrating populations are suggested to still be expanding further northward in North America with the sedentary and wintering territory of Cattle Egrets in

North America also increasing to the north (Telfair II 2006).

Asia

The historic eastern range expansion of Cattle Egrets was not as well documented as the western range expansion, resulting in limited information regarding the path and exact years of Cattle Egrets’ expansion though Asia. Cattle Egrets historically found in the Asian tropics spread from the Indian subcontinent to the

Maldives and Sri Lanka, through south-eastern China, Thailand, Vietnam, and the

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Philippines (Maddock and Geering 1994). In north Asia, Cattle Egrets occur in southern

Japan and Korea (Hancock and Kushlan 1984).

Australia and New Zealand

Similarly to the western expansion, Cattle Egrets expansion in the east greatly increased in the 1940s, expanding to New Guinea, Australia, and New Zealand

(Maddock and Geering 1994). Cattle Egrets were first reported in New Guinea in 1941

(Lindgren 1971) and in the northern Territory of Australia in 1948, however, this was in large numbers, suggesting they may have been present much sooner (Deignan 1964).

Anecdotal evidence from Aborigines suggest that Cattle Egrets may have been present in Australia as early as 1907 (Hewitt 1960). The first sighting reported in New Zealand was in 1963 (Turbott et al. 1963), although they may have been present as early as

1956 (Brown 1980). However, it was not until the early 1970s that Cattle Egrets were considered well-established in New Zealand (Heather 1986).

Cattle Egret Pathogens and Parasites

With Cattle Egrets’ capability for long distance movement, they have the potential to transport pathogens, parasites, and ectoparasites between regions. As a communal species, they often and nest with other migratory avian species, allowing for horizontal transmission between species and increasing risk of spillover (Dusi et al.

1968, Arendt 1988, Hubalek 2004). Cattle Egrets’ ability to forage in open spaces without dense vegetation makes them ideal for the growing agricultural world. However,

Cattle Egrets’ expanded range and potential susceptibility to pathogens and parasites threatens wildlife and livestock globally.

Cattle Egrets have previously tested positive for a wide variety of pathogens

(Table 1-1) and parasites (Tables 1-2, 1-3). In a controlled study, Cattle Egrets were

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experimentally introduced to H5N1, however they were highly susceptible and either died within a week or had to be euthanized, indicating they are not a significant reservoir host for the H5N1 A1 (Phuong et al. 2011). Omonona et al. (2014) found a wide variety of parasites in Cattle Egrets in Nigeria and suggested that Cattle Egrets living around poultry pens could serve as a reservoir host for the transmission of parasitic diseases. In Egypt, Cattle Egrets shedding chlamydiae could expose humans that come into contact with them to zoonotic risks (El-Jakee et al. 2014). Cattle Egrets have also been found with several species of Salmonella spp. (Friend 2002, Locke et al.

1974, Phalen et al. 2010), potentially posing a health risk to humans living near Cattle

Egret colonies. One species of Salmonella, S. typhimurium, was found in a captive heron colony shortly after individuals were collected from the wild, demonstrating intraspecies transmission (Locke et al. 1974). Cattle Egrets were the first

Pelecaniformes reported with Toxoplasma gondii, indicating potential to contaminate soil in other locations with T. gondii oocysts (Costa et al. 2012).

Amblyomma variegatum, commonly known as the tropical bont , is an Africa tick species that was introduced to the Caribbean during the 18th or 19th century with cattle from Senegal (Barré et al. 1995). A. variegatum immatures and juveniles have been found to infest Cattle Egrets in Antigua and Guadeloupe (Corn et al. 1993, Barré et al. 1988). A. variegatum is a species of concern as it infests both livestock and wildlife and is a vector of heartwater (a rickettsial disease of ) and is associated with dematophilosis (a bacterial skin disease of animals) (Barré et al. 1998).

Circumstantial evidence strongly linked the increase in populations of Cattle Egrets in the Caribbean with increased colonization of A. variegatum (Barré et al. 1998).

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Considering the high mobility of Cattle Egrets, this raises concern that they could potentially transport A. variegatum to the American mainland through Florida. In contrast, Cattle Egrets have also been reported as biocontrol for vectors that could transmit diseases to cattle, including A. variegatum and Boophilus microplus (vector of babesiosis and anaplasmosis) (Mckilligan 1984, Barré et al. 1991).

Range Expansion and Disease

Cattle Egrets’ incredible flying ability, their complexity of diseases, and the close contact between Cattle Egrets and the cattle industry, as well as other avian species could allow them to have a major global impact. Gaining an understanding of Cattle

Egrets’ expansion, movement patterns, and potential to transport disease is vital to understanding how Cattle Egrets could be involved with the global spread of pathogens and parasites, as well as risk to wildlife, the cattle industry, and humans.

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Table 1-1. Pathogens found in Cattle Egrets.

Pathogen Disease Locality Source Avian influenza A/duck/Vietname/40D/04 H5N1 Influenza Vietnam (Experimental infection) Phuong et al. 2011 (H5N1) Chlamydia psittaci Chlamydiosis Egypt El-Jakee et al. 2014 Salmonella typhimurium Salmonellosis Salton Sea, Maryland (United Friend 2002, Locke et al. States, captive population)) 1974 Salmonella enterica subsp. enterica Salmonellosis Texas (United States) Phalen et al. 2010 West Nile Virus West Nile Fever Israel Mumcuoglu et al. 2005

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Table 1-2. Ectoparasites found in Cattle Egrets.

Ectoparasite Disease Locality Source Ornithoica confluent Alabama (United States) Dismukes et al. 1972 Ciconiphilus decimfasciatus Alabama (United States) Dismukes et al. 1972 Amblyomma variegatum Antigua, Guadeloupe Corn et al. 1993, Barré et al. 1988 Menopon gallinae Nigeria Omonona et al. 2014

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Table 1-3. Endoparasites found in Cattle Egrets.

Endoparasite Disease Locality Source Amplicaecum sp. Alabama (United States) Stuart et al. 1972 Apatemon gracilis Alabama (United States) Stuart et al. 1972 Ascaridia galli Nigeria Omonona et al. 2014 Capillaria spp. Nigeria Omonona et al. 2014 Centrorhynchus polymorphus Puerto Rico Whittaker et al. 2011 Clinostomum complanatum Alabama (United States) Stuart et al. 1972 Desportesius invaginatus Puerto Rico Whittaker et al. 2011 Echinoparyphium elegans King and Van As 1996 Euclinostomum heterostomum Jhansilakshmibai and Madhavi 1997 magna Nigeria Omonona et al. 2014 Habronema sp. Alabama (United States) Stuart et al. 1972 Hadjelia sp. Alabama (United States) Stuart et al. 1972 Haemoproteus spp. Avian Malaria Spain, Nigeria Ferraguti et al. 2013, Omonona et al. 2014 Heterakis spp. Nigeria Omonona et al. 2014 Leucocytozoon spp. Avian Malaria Nigeria Omonona et al. 2014 Microtetrameres (Gynaecophila) egrets Puerto Rico Whittaker et al. 2011 Microtetrameres spiralis Alabama (United States) Stuart et al. 1972 Nephrostomum oderolalensis Pakistan Khan and Ghazi 2011 Nephrostomum ramosum Korea, Alabama (United States) Choe et al. 2016, Stuart et al. 1972 Paratanaisia spp. Egypt Abdo and Sultan 2013 Pegosomum bubulcum Korea Choe et al. 2016 Pegosomum sp. Japan Murata et al. 1998 Physaloptera sp. Alabama (United States) Stuart et al. 1972 Plasmodium spp. Avian Malaria Spain, Nigeria Ferraguti et al. 2013, Omonona et al. 2014

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Table 1-3. Continued.

Endoparasite Disease Locality Source Prosthogonimus sp. Puerto Rico Whittaker et al. 2011 Syngamus trachea Nigeria Omonona et al. 2014 Synhimantus invaginatus Alabama (United States) Stuart et al. 1972 Tetrameres cochleariae Alabama (United States) Stuart et al. 1972 Toxoplamsa gondii Toxoplasmosis Costa et al. 2012 Trichostrongylus tenuis Nigeria Omonona et al. 2014

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CHAPTER 2 EXPANSION OF CATTLE EGRETS (BUBULCUS IBIS) IN RESPONSE TO GLOBAL LAND USE CHANGE

. A species’ geographic distribution is a reflection of its realized niche and is impacted by both biotic and abiotic variables, such as climate and land use change which alter habitat suitability (Holt and Keitt 2005, Parmesan et al. 2005, Frey 2009,

Gaston et al. 2003, Hutchinson et al. 2000). Suitability factors that influence a species’ distribution include community composition, predator-prey interactions, pathogen prevalence, and resource availability. For example, the expansion of American marten

(Martes americana) is related to climate and land cover change on the Kenai Peninsula in Alaska and changes in livestock densities influenced habitat suitability and distribution of Egyptian Vultures (Mateo-Tomás and Olea 2015). Variations in distribution, population size, and behavior of species can serve as biological indicators of global environmental change that would be impossible to achieve through other survey methods (Piersma and Lindtröm 2004). Understanding how a species’ geographic distribution changes in response to land use alteration can allow them to serve as indicators of global land use. With their varied distributions, often-specialized habitat requirements, and potential for wide-ranging movement, avian species can serve as sensitive sentinels for global environmental change.

Avian species exhibit wide variability in natural histories, movement ecology and ecological plasticity that influence changes in distribution and make them more or less sensitive to global change. Transcontinental migrations can engage wide ranging movement that are confined to specific habitats, while wandering and juvenile dispersal behaviors can allow for more plasticity in habitat associations (Coffey 1943, Browder

1973, Paradis 1998, Croteau 2010). Newbold et al. (2013) found that bird species that

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are non-migratory, forest habitat dependent, and/or primarily consume fruit or insects had a decline from intensively-used habitats, compared to bird species that are migratory, habitat generalists, with main diets other than fruit or insects. An example of distribution change due to land use change is the Red-winged Blackbird, which has seen declines due to changes in agriculture (Blackwell and Dolbeer 2001).

The global increase in commercial agriculture as a result of human population growth has resulted a 5.5-fold increase and pasture has seen a 6.6-fold increase in three centuries (Klein Goldewijk 2001) with various developments increasing the intensity of land use (Hueston and McLeod 2012, Netz 2004). This rapid increase in land use change has led to a change in species’ distributions across the globe

(Baltensperger et al. 2017, Mateo-Tomás and Olea 2015). In contrast to the Red-wing

Blackbird which have decreased in range due to changes in agriculture, Cattle Egrets have seen an increase in distribution that is believed to be facilitated by land-use change.

A rapidly expanding species, Cattle Egrets (Bubulcus ibis) are resilient fliers whose distribution has expanded globally without human aid (Massa et al. 2014), though there are some records of human-release (Lever 1987). The Cattle Egret is believed to have extended its range in response to widespread habitat alteration and husbandry practices (Sprunt 1955, Davis 1960, Blaker 1971, Crosby 1972,

Browder 1973, Bock and Lepthien 1976, Arendt 1988). Specifically, cattle farming and cropland have been implicated in the global expansion of this species (Table 2-1) although the relationship is presumed and not tested in any formal way.

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Cattle Egrets are native to east Africa, southern Portugal, Spain, and the Asian tropics (Brown et al. 1982). Their distribution has expanded since approximately the late

1870s, and they are now found on every continent except for Antarctica. Cattle Egrets are reported to be partial migrators with wandering habits and juvenile dispersal

(Browder 1973). Juvenile Cattle Egrets disperse in unconventional directions and can move up to 5,000 km from their birth place, which provides a mechanism for colonizing new territories (Browder 1973, Massa et al. 2014). Cattle Egrets now have established migratory and sedentary populations across the world and it is believed that their range is still expanding due to their wandering and juvenile dispersal.

Cattle Egrets are often found feeding in close proximity to agriculture operations and livestock (Menon 1981, Smallwood et al. 1982, Singh et al. 1988). In their native range, Cattle Egrets can be found foraging in the proximity of grazing herbivores such as camels, zebra, rhinoceros, elephant, and (Siegfried 1978, Burger and

Gochfeld 1993). In their non-native range, Cattle Egrets can be found foraging in close association with cattle and other livestock, but can also be found foraging in fields where fire, tractors, or cutting/mowing machinery are used (Smallwood et al. 1982).

Surface-irrigated fields are also important foraging areas in dry season and in arid regions (Singh et al. 1988, Mora 1992). A generalist species, Cattle Egrets are highly adaptable to land conversions to cattle pastures, rice fields, and seasonal wetlands

(Tourenq et al. 2001, Tourenq et al. 2004, Richardson and Taylor 2003, Ogden et al.

1980, Naugle et al. 1996).

In this study, I examined the global expansion of Cattle Egrets and the relationship between land use change and the expansion of this species. Because

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Cattle Egrets have a close relationship with large herbivores, including cattle, as well as with other forms of human agriculture and land use disturbance, I hypothesized that

Cattle Egret expansion would be positively correlated with the rate of increase in human land uses of crop agriculture and cattle ranching and with areas that were dominated by these land uses. Using 200 years of global museum records and hypothesized trends in historical land use change, I mapped the expansion of Cattle Egrets and tested the relationship of agricultural land use to Cattle Egret arrival to new areas.

Methods

Data Collection

I conducted a retrospective study of Cattle Egret distribution utilizing museum specimens on a global scale. Museum records of specimens were reviewed from two databases, Global Biodiversity Information Facility (GBIF, https://www.gbif.org/) and

Integrated Digitized Biocollections (iDigBio, https://www.idigbio.org/). In addition to these databases, record requests were made to museum collection managers or curators of museums that were not online or not included in either database. Duplicate records were removed, and data including Catalog Number, Year, and specimen locality were collated. Specimen location was recorded as decimal degree coordinates when available. Locations of specimens without coordinates were estimated as the center of the city, county or province in which they were collected, or estimated relative to a landmark using Google Maps (Cryan 2003). Records that did not have a location or collection year were removed (Cryan 2003). I mapped the location of all samples in 50- year time intervals using the World Robinson traditional layout base map, using Arc

Map 10.4.1 (ESRI Inc., Redlands, CA). The maps were graphed using the World

Geodetic System 1984 (WGS 84) projection.

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Descriptive Data

The earliest museum records collected on every continent and across major ecoregions, including the North American flyways, Caribbean Basin, Pacific Island,

South Sea Islands, and Iceland, were identified. North and east Africa and the eastern

Mediterranean basin were considered to be the center of the distribution and the point of origin for the expansion of the (Bocheński 1991, Massa et al.

2014). This assumption coincided with the earliest museum record which was from

Cyprus. The latitudinal and longitudinal spread in distribution was quantified separately by calculating the distance in degrees of each first occurrence record to the original record in Cyprus, providing an estimate for the distance to the north or south and east or west of the origin for each first occurrence. This estimated distance was graphed by date of collection to visually assess the expansion of the distribution of Cattle Egrets.

Statistical Relationship of Land Use Change and Cattle Egret Arrival

I assessed the influence of land use and of land use conversion to agriculture on the arrival of Cattle Egrets to locations around the world. I used the History Database of the Global Environment (HYDE version 3.2; Klein Goldewijk et al. 2017) map database to identify historical land uses. The HYDE database is a spatio-temporal database consisting of human population data and land use data estimated from 10,000 BCE to

2016 CE with a spatial resolution of 5 arc minutes (approximately 85 km2 at the equator). Human population data were based on weighted maps of historical population density (Klein Goldewijk 2001). Land use data, prior to FAO estimates of land use that started in the 1960s, were estimated using land use allocation algorithms. These hindcasting algorithms were based on assumptions about per capita use of cropland and agriculture that was adjusted over time to reflect changes in technology (Klein

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Goldewijk et al. 2011). The database includes rasterized data on the distribution of global cropland, grazing land, and population data. Cropland data were further defined as irrigated or rain fed for row crops, rice fields, and total crops; grazing lands were divided into more intensively used pasture (aridity index > 0.5) and less intensively used rangeland (aridity index < 0.5). HYDE land use data were quantified by total land use in km2 units per grid cell for each land use type. Data from years 1820 to 2016 were used.

Data for years 1820 to 2000 were recorded in 10-year intervals and data for years 2000 to 2016 were recorded in one-year intervals, however only 2010 and 2016 were used

(Table 2-2). The global map included data from 9,331,200 grid cells.

Seven land use descriptors were used for the analysis (Table 2-3). Data on six land uses (cropland, irrigated crops, rain fed crops, grazing, rangeland, and pasture) were collected from the HYDE database, because the expansion of these land uses were hypothesized to have facilitated the global expansion of Cattle Egrets (Sprunt

1955, Davis 1960, Blaker 1971, Crosby 1972, Browder 1973, Bock and Lepthien 1976,

Arendt 1988).

Aggregating cells made the database more manageable for analysis, and as

Cattle Egrets can fly as far as 20-60 km/day from roost or nesting colony to feeding areas, I assumed they could travel anywhere within the adjusted cell size in their daily movements. Grid cells in each map were aggregated in 2 by 2 cell groupings and the land use was totaled, resulting in a new cell size of 10 arc minutes or approximately 340 km2 at the equator and all subsequent analyses used the new cell size. The land use proportion and rate of change in land use were calculated for each variable in each cell to use for analysis. The land use proportion was calculated as the total km2 of each

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land use type divided by the cell size. The rate of change was calculated by subtracting land use at T0 from land use at T1 and dividing by the number of years between T0 and

T1 to determine the rate of change per year for each cell. A positive number indicated an increase in that land use type and a negative number indicated a decrease in that land use type.

In addition to assessing land use variables for each grid cell, I also assessed state changes in Cattle Egret presence from time periods T0 to T1 in each grid cell.

Each cell could contain one of four events in each time interval (T0-T1): (1) no record

(T0)-no record (T1) (continued absence event), (2) no record-presence (expansion event), (3) presence-no record (extirpation event), and (4) presence-presence

(persistence event). I assumed that the museum specimen location data reflected the presence of a species in the area. There are, however, no valid absence data in museum records, but rather “no record” events that could be interpreted several ways

(Lütolf et al. 2009). No records for a given location could indicate that the species was

(1) present but undetected (Mackenzie et al. 2003); (2) temporarily absent, such as source-sink dynamics (Pulliam 2000); (3) a true absence from the location, or (4) no survey was conducted in the area and thus its status was unknown.

To determine if the lack of a record was a possible absence, I validated the absence data with further museum records. Absences in grid cells were validated by using records of avian surveys that took place in the region during a particular time period and a Cattle Egret was not recorded. If specimen were collected at a location, but a Cattle Egret was not recorded, grid cells in that location at that time interval were marked as a possible absence. If no surveys took place at a grid cell, the grid cell was

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discarded at that time period from the analysis. This method allowed me to evaluate whether historical sampling across grid cells had the potential to record the presence of

Cattle Egrets (Frey 2009). This method allowed us to eliminate any cases where a cell grid was not visited (situation 4) and reduced our “no record” data set from 11,871,315 no records to 72,356 possible absences. We did not assess the probability that Cattle

Egrets were present but not detected (situation 1), nor did we assess if they were temporarily absent (situation 2), and thus the model assumed those to be true absences.

In order to test the hypothesis of land use facilitating the expansion of Cattle

Egrets, I selected the subset of validated absences where the target species was either considered absent in two consecutive decades (“absence-absence” events) or only in the later but not in the earlier decade (“absence-presence” events). This follows the hypothesis that land use/land use change occurring in the Cattle Egret “absence- absence” events did not lead to species appearance, whereas the land use or land use changes may have been beneficial for species’ expansion in the Cattle Egret “absence- presence” events.

To test the hypothesis of land use driving Cattle Egret expansion, I fit a generalized linear model (GLM) with the core R statistical software (version 3.5.0) to assess both proportion and rate of change of different land use types as drivers of

Cattle Egret expansion. Data for analysis of the relationship of land use to Cattle Egret state was composed of data from each aggregated geospatial grid cell and contained (i) the dependent binary response variable for Cattle Egrets (“absence-absence” [0] or

“absence-presence” [1]) between pairwise consecutive time periods, T0 - T1, (ii) the

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proportion of land for each land use type at T0 within each cell (Lütolf et al. 2009), (iii) the rate of change of land use from T0 to T1 for each land use type (Lütolf et al. 2009), and (iv) the GPS coordinates of the grid cell centroid.

Prior to initiating the GLM analysis, we estimated the correlation between land use proportions for each land use type and land use rate of change for each land use type to test for collinear variables. Moderately and highly correlated (> |0.3|) land uses were removed from the group models of all land use variables for both proportion and land use change. The estimated amount by which the log odds of presence would increase if the variable was one unit higher (referred to as ‘estimate’) and the p-value were used to determine the impact and significance of each variable on Cattle Egret expansion. Akaike’s Information Criteria (AIC) and pseudo-R2 were used to assess model fit and best models. The GLM for the Cattle Egret state and the non-correlated land use covariates was run using the glm function with a binomial family from the base

‘stats’ package in R version 3.5.0. The dredge function from the ‘MuMln’ package version 1.42.1 (Bartoń 2018) was used to generate model combinations, including the null model, and generate estimate and AIC values. The null model was the GLM of

Cattle Egret expansion events without any land use covariates (percentage and rate of change of cropland, irrigated crops, rain fed crops, grazing land, pasture land, rangeland). P-values and pseudo-R2 for the best model was recorded from the summ function from ‘jtools’ package version 1.1.1 (Long 2018) in R to assess model fit.

Results

Descriptive Data

Final data included 3,924 Cattle Egret records ranging globally from -62.25 to

64.92 latitude and -177.38 to 175.55 longitude and from years 1820 to 2017. The global

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expansion map illustrates the Cattle Egret specimen locations from 1820 to 2017

(Figure 2-1). The specimen locations of Cattle Egrets over time can be seen more clearly in the maps grouping the locations into four 50-year time periods (Figures 2-2, 2-

3, 2-4, 2-5). The oldest specimen in the museum records was collected in Cyprus in

1820. Within the following 50 years (1820-1870, Figure 2-2), Cattle Egret specimens were collected primarily in the Eastern hemisphere, predominantly in Africa and Asia, ranging from Tunisia to the Philippines. Cattle Egret specimen were collected across north, central, and south Africa; the northern-most point being in Tunisia and the southernmost occurrence in South Africa. The first recorded occurrences in Asia were in the Middle East in 1824, with more Cattle Egret specimen collected further onto the continent in the late 1870s. During the first 50 years of museum records, birds were collected from locations in southern Europe, and Cyprus, both bordering the

Mediterranean Sea. There was one record of a Cattle Egret specimen collected in New

York in 1860, however after further investigating it was determined this digital year label was inaccurate due to data management default settings and the correct year is unknown but likely between the 1950 and 1960s based on the collector and location.

In the following 50 years, 1871 to 1921 (Figure 2-3), collection of Cattle Egrets increased in geographic distribution, being found on every continent except Antarctica.

Collected Cattle Egret specimen ranged across northern Asia, northern Europe,

Australia, and the Western hemisphere. Museum records showed Cattle Egrets during this time were collected at more locations throughout Asia, including China, Japan,

Russia, Indonesia, and Malaysia. Cattle Egrets were also recorded for the first time throughout western Africa. Cattle Egrets were collected north through Europe and were

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collected in Spain and Azerbaijan. During this 50-year period, Cattle Egret specimens were collected on three additional continents, Australia, North America, and South

America, officially reaching all six continents they currently occupy. In Australia, the northernmost point they were recorded at was in Queensland, and the southernmost point was in the state of South Australia. In South America, one bird was recorded in

Argentina. In North America, one was recorded in Florida.

In the third time period (1922-1972, Figure 2-4), Cattle Egret specimen were collected across the six continents now occupied by Cattle Egrets. They were recorded across most of Africa and Asia. Collections across Australia and the western hemisphere increasing drastically after the 1920s, moving further south into Australia, west into Western Australia, and east into New South Wales. Cattle Egret specimens’ western collections during this time period was focused on North America, Central

America, the Caribbean and northern South America. In South America, birds were recorded in Bolivia, Peru, Colombia, Venezuela, Guyana, , and French

Guiana. In Central America, they were recorded in Guatemala, Nicaragua, Costa Rica, and Panama. In North America, they were recorded across the United States, Mexico, and . Records ranged east to west from Newfoundland to , and north to south from the Northwest Territories of Canada to Southern Mexico. The Hawaiian records are in agreement with one of the few examples of human-assisted Cattle Egret expansion, as 105 Cattle Egrets were released on the Hawaiian Islands in 1959 to control arthropod pests of cattle (Breese 1959, Lever 1987). During this time period,

Cattle Egrets were also introduced to the Chagos Archipelago in the Indian Ocean in

1955. Along with the Americas, they spread across the Caribbean. During this 50-year

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period, they were recorded on the islands of Puerto Rico, the Dominican Republic, and

Haiti.

In the most recent time period, 1973 to 2017 (Figure 2-5), Cattle Egrets specimen collections continued to the east and were recorded on a small island outside of Russia. Recordings of Cattle Egrets increased in northern North America, southern

South America, and Europe. Within the last 44 years, collected Cattle Egret specimen continued expanding south and were collected on the last unoccupied continent,

Antarctica. Recordings were collected between King George Island and Nelson Island, which are located 75 miles off of the northern coast of Antarctica. In the eastern hemisphere, Cattle Egrets were collected on Macquarie Island, an Australian island halfway between Australia and Antarctica.

To better understand the temporal pace of expansion, I selected the first occurrence location and date within continents and large geographic regions (Table 2-2,

Figures 2-6, 2-7). According to museum records of preserved specimen, the earliest record of Cattle Egrets was on the European island of Cyprus in 1820. There was one earlier preserved specimen from 1814, however it was missing location data. There was also a record of human observation of a Cattle Egret in Comoros, an island of the east coast of Africa in 1799 in Cattle Egrets prior to their expansion (Brown et al. 1982), however only collected specimen were used for analysis as identification could be confirmed. The species gradually moved north until the end of the 1800s but never moved more than 30 degrees north of the origin point in any of the first occurrences. In the 1900s, there was increased southwards latitudinal movement, eventually moving over 100 degrees south of the origin point. During the 1800s, Cattle Egret gradually

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moved east eventually reaching up 100 degrees longitude from the origin. The 1900s jump in movement was also seen in the longitude when Cattle Egrets began increased movement to the west, reaching as far as 200 longitudinal degrees west from the origin point.

Statistical Relationship of Land Use Change and Cattle Egret Arrival

Percentage of cropland and grazing land and rate of change of grazing lands and rain fed crops were removed from the GLM that estimated the relation of land use change to Cattle Egret expansion as they were highly correlated with the other variables

(Tables 2-4). The GLM of the remaining variables (percentage: irrigated crops, rain fed crops, pasture, and rangeland; rate of change: crops, pasture, rangeland, and irrigated crops) revealed that the best model for Cattle Egret expansion was rate of change and percent of irrigated crops, rate of change and percent of rangeland, percent of pasture, and percent of rain fed crops (AIC = 13891.7) (Table 2-5). The results from the best model (Table 2-6) indicated a significant, positive relationship between Cattle Egret expansion and percentage of pasture land use (Estimate = 0.01, p < 0.001, Figure 2-8), percentage of irrigated crops land use (Estimate = 0.01, p < 0.001, Figure 2-9), and rate of change of irrigated crops land use (Estimate = 0.14, p < 0.001, Figure 2-10), indicating that as these variables increased, Cattle Egret expansion increased. There was a significant, negative correlation between percentage rangeland use (Estimate = -

0.02, p < 0.001, Figure 2-11), percentage rain fed crops (Estimate = -0.01, p < 0.001,

Figure 2-12), and rate of change of rangeland (Estimate = -0.15, p < 0.01, Figure 2-13), indicating that as these variables decreased, Cattle Egret expansion increased. This model fit had a pseudo-R2 of 0.02.

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Discussion

The aim of this study was to map the global expansion of Cattle Egrets and explore the relationship between historical land use change and observed Cattle Egret expansion to test the hypothesis that Cattle Egret range expansion had a significant positive relationship to the increase of agricultural land uses. The widespread and rapid expansion of Cattle Egrets has been widely observed and documented but the drivers behind that spread have only been hypothesized and not statistically tested up to this point. This study was the first to map the global expansion of Cattle Egrets with museum specimens, illustrating their impressive distribution increase and confirming the many published observations of expansion.

Historical Expansion

The dataset of Cattle Egret specimen collected in this study differed from previous studies in some reports of earliest occurrences. Arrendt (1988) reported the

Cattle Egret expansion as beginning in the 1930s, however Cattle Egrets were reported beyond their native range in both the eastern and western hemispheres prior to the

1930s, indicating that the expansion occurred long before the 1930s although it rapidly increased in this time period. The early records of Cattle Egret specimen exemplified one of the advantages of working with museum specimen records by having easy-to- search, collated records in one central location.

Although the maps in this study did not allow differentiation between Cattle

Egrets’ arrival and establishment, the rapid expansion of collected specimen during the

1922 to 1972 period agreed with many reports of newly established Cattle Egret populations across the world (Dugand 1954, 1955, Lehmann 1959, Lowe-McConnell

1967, Hancock and Elliott 1978, Smith 1958). This expansion coincided with the

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historical expansion and intensification of modern agriculture which began with the industrial revolution in the 1760s and increased rapidly in the early to mid-1900s (Lanz et al. 2018). The growth of modern agriculture was faster in western settlement countries rather than the long-settled areas of Europe and Asia (Federico 2004). The production of various plows and commercial fertilizers in the early to mid-1800s led to the increase in commercial farming. The patent of Glidden barbed wire in the late

1800s and the increase in agriculture production facilitated the fencing of rangeland and the end of unrestricted, open-range grazing of cattle (Netz 2004). The development of machine tractors, increase in fertilizer, and changes in intercontinental trade use in the early to mid-1900s facilitated increases in agricultural production (Hueston and McLeod

2012).

The expansion of modern agriculture has generally been considered detrimental to many species and has been a primary cause of the loss of global biodiversity (Lanz et al. 2018, Newbold et al. 2013). However, in the case of Cattle Egret it is believed to have played a positive role in the increase in distribution which is observable in the alignment in years between increase in Cattle Egret specimen collection distribution and records of modern agriculture advances, expansion, and intensification. This relationship was supported by the statistical testing comparing Cattle Egret arrival and land use change.

Land Use Change and Cattle Egret Arrival

The Cattle Egret has increased its range in response to widespread land use change (Davis 1960, Blaker 1971, Crosby 1972, Browder 1973) but understanding how specific land use types have influenced this spread is essential to understanding how habitat alteration is impacting wildlife. The GLM quantifying the best model of land use

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change for Cattle Egret specimen indicated the percentage of land use for all types and the rate of change for irrigated crops and rangeland were significantly correlated to

Cattle Egret expansion. However, not all of these correlations were positively related.

Cattle Egret were specifically positively correlated to the land use types that are more intensively used and managed, irrigated crops and pasture land, whereas they were negatively correlated to the less intensively used and managed lands, rain fed crops and rangeland. These trends in more versus less intensively used land is seen in both the percentage and rate of change values and across all models.

Previous studies have generally predicted either cattle production or crop production as being the driver behind Cattle Egrets’ range expansion (Sprunt 1955,

Davis 1960, Blaker 1971, Crosby 1972, Browder 1973, Bock and Lepthien 1976, Arendt

1988). However, my analysis provided a more nuanced picture of the process underlying the expansion. It appears that the increase in more intensively used lands and decrease in the less intensively used land served as a driver for Cattle Egret range expansion. Although the variables were not highly correlated it is possible that the less intensively used land was decreasing because it was being replaced by the more favorable intensively used land or other human development that resulted in the correlation with Cattle Egret expansion. The correlation of Cattle Egret range expansion and the increase of more intensively used lands is further evidenced by the timing of key agricultural developments such as the patent of Glidden barbed wire in the 1870s leading to the decline of open rangeland and the development of machine tractors and increase in fertilizer in the mid-1900s leading to intensively used agricultural production

(Hueston and McLeod 2012, Netz 2004).

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Newbold et al. (2013) found that avian species that are non-migratory, forest habitat dependent, and/or are primarily frugivores or insectivores occur with lower probability and at lower abundances in intensively used habitats than migratory habitat generalists with primary diets other than invertebrates and fruit, such as Cattle Egrets.

Although Cattle Egrets are considered insectivorous, they are also known to consume small . Additionally, the unique foraging method of Cattle Egrets actually benefits from disturbances on the landscape providing easier access to food. The distinctive foraging of Cattle Egrets make them particularly specialized to highly disturbed and intensively used land compared to other avian species.

Additional human development beyond agricultural land use may also have played alternate roles in Cattle Egret expansion. It is also possible that the less- intensively used agricultural land was being replaced by human development, which although not tested in this study could play a role in Cattle Egret expansion with some

Cattle Egret roosts being reported in human subdivisions (Parkes 2007) and Cattle

Egrets being sighted foraging along roads and highways, as well as other locations where mowing occurs such as airports (Telfair II 2006, Paton et al. 1986). Whether or not human development of subdivisions or cities specifically played a role, human development is likely involved in Cattle Egret expansion as the increase in intensively used agriculture land use was necessary to meet human demand. The global increase in transportation may have also played a role in the expansion of Cattle Egrets with reports of Cattle Egret landing on ships in the middle of oceans as seen in the specimen collected from a research vessel in the Pacific Ocean during the 1922-1972 time period.

The assistance of intercontinental trade to Cattle Egret expansion is supported by the

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increase in intercontinental trade in the early to mid-1900s. The expansion of humans and human development related to land use change and Cattle Egret expansion requires further exploration and testing.

Climate change is also closely linked to land-use change, particularly to intensively used agricultural land with heavy use of fertilizers and cattle production resulting in the increased release of carbon and nitrogen (Rojas-Downing et al. 2017,

Foley et al. 2005). On such a large scale, the influence of climate change and land-use change would likely be highly confounded making it difficult to parse apart the impacts of each (Eglington and Pearce-Higgins 2012). Eglington and Pearce-Higgins (2012) reported that changes in land-use intensity exceeded the pace of climate change, due to the rapid intensification of agricultural lands and that European farmland birds were most strongly impacted by land-use intensity, with climate change being a relatively unimportant driver. Although Eglington and Pearce-Higgins (2012) report there was no evidence of a switch to climate becoming more important than land-use in its influence of farmland birds, it is suggested that changes in climate could be facilitating the continued expansion of Cattle Egrets (Telfair II 2006). While it is possible that other, untested factors such as climate change and human development may also be important, existing literature suggests I have considered the most important factors which influence Cattle Egret expansion. Further testing that is able to parse apart land use change and climate change could reveal potential future impacts on further Cattle

Egret expansion from climate change.

Limitations of Historical Data

A limitation of note in the use of museum specimen is risk of inaccurate digital records. This was evident in the Cattle Egret specimen with digital records indicating it

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was collected in New York in 1860. After further investigation of this anomalous record, it was discovered that the record year was inaccurate due to a problem with the data management system that was previously used by the museum containing the specimen.

This limitation can be relatively easily managed by contacting the curators of abnormal specimen to verify the data written on the specimen card. In the case of this Cattle

Egret specimen, there was no year recorded, thus the system auto-filling an inaccurate year. Similar to inaccurate data, sampling bias can also present a problem when using museum specimen. In the 1973-2017 time period, we saw a lack of museum specimen in a large part of Asia. This is most likely due to a lack of specimen collection during this period, rather than an absence of Cattle Egret.

Another limitation of the samples in this study is the lack of knowledge of the behavior of the individual bird at the time it was collected. It is impossible to know if, at the time of collection, the individual was wandering, dispersing, a sedentary resident, or a resident moving along a migration path. Given the large sample size of this study, this limitation is not enough to impact the visual representation of the global expansion of

Cattle Egrets, however it could impact the first occurrence in each region graph as seen in the first occurrence in South America (Table 2-3).

Final Thoughts

Intrinsic factors of Cattle Egrets, including dispersal and wandering tendencies, generalist behavior, and change of land use facilitated this species to expand in the face of global land use change. My analysis provided a more nuanced picture of the process underlying the expansion, expanding knowledge on Cattle Egret expansion beyond the suggested hypotheses. Overall, the interaction between the increase of more- intensively used irrigated crops and pasture land and the decrease of less-intensively

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used rain fed crops and rangeland played a role in Cattle Egret expansion. Cattle Egret range is believed to still be expanding as continued agricultural development and global climate change facilitates breeding population movement north into the northern US and

Canada and year-round population movement further into the southern US (Telfair II

2006). Further studies showing changes in established Cattle Egret populations and the impacts of the continued dispersal of Cattle Egrets could further reveal the relationship between agricultural land use and climate change and the Cattle Egret.

Cattle Egrets interact with many other avian species and have the potential to spread pathogens globally, understanding Cattle Egret movement and the drivers of that movement are important to understanding the role of Cattle Egrets in ecosystems across the globe and how land use is impacting conservation.

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Table 2-1. Land use change variables and corresponding shapefiles to be tested for correlation to Cattle Egret expansion.

Variable Reference HYDE shapefiles Cropland (total cropland area, Telfair II 2006 Cropland irrigated crops and rain fed crops) Irrigated (total irrigated area) Hafner 1977, Siegfried 1978, Irrigated Blaker 1971, Telfair II 2006 Rain fed (total rain fed crops) Rain fed Grazing (total land used for Blaker 1971, Hafner 1977, Grazing grazing, rangeland and Siegfried 1978, Kopij 2008 pasture) Rangeland (aridity index < 0.5) Blaker 1971, Hafner 1977, Rangeland Voison 1991, Myers 1979 Pasture (aridity index > 0.5) Blaker 1971, Hafner 1977, Pasture Maddock and Geering 1994, Hancock 1978 Land use change variables with references that hypothesized its positive influence on Cattle Egret expansion and the corresponding HYDE map shapefile for testing each variable.

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Table 2-2. Corresponding time period, percent land use reference years, and sampling years for analysis of land use and Cattle Egret expansion.

Time period Percent Value Year Sample Years 1820-1830 1820 1820-1829 1830-1840 1830 1830-1839 1840-1850 1840 1840-1849 1850-1860 1850 1850-1859 1860-1870 1860 1860-1869 1870-1880 1870 1870-1879 1880-1890 1880 1880-1889 1890-1900 1890 1890-1899 1900-1910 1900 1900-1909 1910-1920 1910 1910-1919 1920-1930 1920 1920-1929 1930-1940 1930 1930-1939 1940-1950 1940 1940-1949 1950-1960 1950 1950-1959 1960-1970 1960 1960-1969 1970-1980 1970 1970-1979 1980-1990 1980 1980-1989 1990-2000 1990 1990-1999 2000-2010 2000 2000-2009 2010-2016 2010 2010-2017 Time periods used for rate of change calculations and year used for land use percentage value with corresponding sample years. The time period are the range of years of the maps from the HYDE database used for analysis of the rate of change for each group of sample years. The percent value year is the year of the map from the HYDE database used to calculate the percent of land use for each group of sample years. The sample years are the time interval of the Cattle Egret specimen data used to determine expansion events.

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Table 2-3. First occurrence of Cattle Egret in geographic regions based on museum record data.

Geographic Location Country of Location Year Latitude Longitude Middle East (West Asia) Cyprus 1820 35.13 33.43 North Africa Egypt 1822 22.74 32.20 South Africa South Africa 1839 -29.85 31.00 Central Africa Kenya 1862 -3.45 37.73 South Asia India 1828 22.57 88.37 East Asia China 1869 15.00 115.00 North Asia Russia 1882 38.75 48.85 Southeast Asia Malaysia 1854 2.19 102.38 Australia Australia 1902 -15.59 136.56 Southern Europe Italy 1827 37.40 14.66 Western Europe Spain 1883 37.04 -6.43 Eastern Europe Germany 1961 52.50 13.53 British Isles 2012 54.93 -7.47 Northern Europe Iceland 1956 64.92 -14.68 Northern South America Columbia 1896 3.66 -76.69 Central South America Bolivia 1953 -16.47 -67.45 Southern South America Argentina 1979 -31.45 -60.92 South Sea Islands Macquarie Island 1975 -54.52 158.98 Antarctica Antarctica 1986 -62.25 -58.83 Central America Panama 1958 8.61 -80.73 Caribbean Puerto Rico 1956 18.05 -67.06 US Atlantic Flyway United States- Florida 1876 26.97 -82.06 US Mississippi Flyway United States- Louisiana 1957 29.99 -92.84 US Central Flyway United States- Oklahoma 1928 34.97 -97.09 United States- US Pacific Flyway 1955 47.67 -122.35 Washington Pacific Islands Hawaii 1959 21.27 -157.82 The geographic location is the geographic region of interest and the country of location is the specific country containing the first occurrence. The year is the year of the first occurrence with the specific latitude and longitude for each occurrence used to calculate the distance from the origin. The first occurrence in Cyprus in 1820 was used as the representative origin for calculations.

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Table 2-4. The correlation of the percent and rate of change (RoC) of each land use variable from the HYDE database.

% % % % % % RoC RoC RoC RoC RoC RoC Crop Graz Past Rang Irri Rain Crop Graz Past Rang Irri Rain % Crop 1.00 0.06 0.24 -0.09 0.29 0.94 -0.04 0.01 0.05 -0.03 0.03 -0.05 % Graz 0.06 1.00 0.38 0.80 0.02 0.05 0.01 -0.02 -0.05 0.03 0.01 0.00 % Past 0.24 0.38 1.00 -0.25 0.05 0.23 0.01 -0.04 0.03 -0.08 0.02 0.00 % Rang -0.09 0.80 -0.25 1.00 -0.01 -0.09 0.00 0.01 -0.07 0.08 0.00 0.00 % Irri 0.29 0.02 0.05 -0.01 1.00 -0.07 -0.05 0.01 0.01 0.00 -0.07 0.01 % Rain 0.94 0.05 0.23 -0.09 -0.07 1.00 -0.02 0.01 0.05 -0.04 0.06 -0.06 RoC Crop -0.04 0.01 0.01 0.00 -0.05 -0.02 1.00 0.02 0.01 0.02 0.18 0.75 RoC Graz 0.01 -0.02 -0.04 0.01 0.01 0.01 0.02 1.00 0.69 0.73 -0.02 0.03 RoC Past 0.05 -0.05 0.03 -0.07 0.01 0.05 0.01 0.69 1.00 0.02 -0.02 0.02 RoC Rang -0.03 0.03 -0.08 0.08 0.00 -0.04 0.02 0.73 0.02 1.00 -0.01 0.02 RoC Irri 0.03 0.01 0.02 0.00 -0.07 0.06 0.18 -0.02 -0.02 -0.01 1.00 -0.51 RoC Rain -0.05 0.00 0.00 0.00 0.01 -0.06 0.75 0.03 0.02 0.02 -0.51 1.00 Percent symbol (%) represents percent of that land use and RoC stands for rate of change of that variable. “Crop” is cropland, “Graz” is grazing land, “Past” is pasture land, “Rang” is rangeland, “Irri” is irrigated cropland, and “Rain” is rain fed cropland. Variables with moderate or high correlation (> |0.3|) are highlighted in grey.

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Table 2-5. Generalized Linear Model results of top 20 models and the null model (no covariates) of Cattle Egret expansion and rate of change and percent of rain fed crops, irrigated crops, pasture land, and rangeland.

RoC RoC RoC Intercept RoC Irri % Irri % Past % Rain % Rang df AICc delta weight Rain Past Rang -3.708 NA 0.134 NA -0.149 0.011 0.009 -0.014 -0.015 7 13891.7 0.0 0.478 -3.707 -0.016 0.138 NA -0.148 0.011 0.009 -0.014 -0.015 8 13893.4 1.7 0.202 -3.709 NA 0.134 0.011 -0.149 0.011 0.009 -0.014 -0.015 8 13893.6 1.9 0.182 -3.708 -0.017 0.138 0.012 -0.148 0.011 0.009 -0.014 -0.015 9 13895.3 3.6 0.078 -3.717 NA 0.134 NA NA 0.011 0.010 -0.014 -0.016 6 13897.2 5.5 0.030 -3.715 -0.019 0.139 NA NA 0.011 0.010 -0.014 -0.016 7 13898.8 7.1 0.013 -3.718 NA 0.134 0.007 NA 0.011 0.010 -0.014 -0.016 7 13899.2 7.5 0.011 -3.716 -0.020 0.139 0.008 NA 0.011 0.010 -0.014 -0.016 8 13900.8 9.1 0.005 -3.682 NA 0.145 NA -0.148 NA 0.010 -0.015 -0.015 6 13909.7 18.0 0.000 -3.680 -0.018 0.149 NA -0.147 NA 0.010 -0.015 -0.015 7 13911.3 19.7 0.000 -3.683 NA 0.145 0.012 -0.148 NA 0.010 -0.015 -0.015 7 13911.6 19.9 0.000 -3.709 NA NA NA -0.150 0.011 0.009 -0.014 -0.015 6 13912.7 21.1 0.000 -3.682 -0.018 0.149 0.013 -0.147 NA 0.010 -0.015 -0.015 8 13913.2 21.6 0.000 -3.711 0.027 NA NA -0.152 0.012 0.009 -0.014 -0.015 7 13913.9 22.2 0.000 -3.710 NA NA 0.006 -0.151 0.011 0.009 -0.014 -0.015 7 13914.7 23.0 0.000 -3.691 NA 0.145 NA NA NA 0.010 -0.015 -0.016 5 13915.2 23.5 0.000 -3.711 0.027 NA 0.005 -0.152 0.012 0.009 -0.014 -0.015 8 13915.9 24.2 0.000 -3.689 -0.021 0.150 NA NA NA 0.010 -0.015 -0.016 6 13916.8 25.1 0.000 -3.691 NA 0.145 0.008 NA NA 0.010 -0.015 -0.016 6 13917.2 25.5 0.000 -3.718 NA NA NA NA 0.011 0.010 -0.014 -0.016 5 13918.5 26.8 0.000 -3.920 NA NA NA NA NA NA NA NA 1 14159.8 268.1 0.000 The value under each variable is the estimated amount by which the log odds of presence would increase if that variable was one unit higher. The df is the degrees freedom for each model. AICc is the Akaike’s Information Criteria which assesses the best model. The delta is the change in the AICc and weight is the weights in the final iterations of the iteratively reweighted least squares (IWLS) fit.

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Table 2-6. The model fit for the best model based on Akaike’s Information Criteria from the Generalized Linear Model results of Cattle Egret expansion and land use change.

Coefficents Estimate Std. Error z value p (Intercept) -3.71 0.04 -95.56 0.00 *** Percent pasture 0.01 0.00 5.73 0.00 *** Percent rangeland -0.02 0.00 -8.41 0.00 *** Percent irrigated 0.01 0.00 4.89 0.00 *** Percent rain fed -0.01 0.00 -9.30 0.00 *** RoC rangeland -0.15 0.05 -2.94 0.00 ** RoC irrigated 0.13 0.02 5.52 0.00 *** Signifance codes are 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1. The model fit was χ²(8) = 280.12, p = 0.00, Pseudo-R² (Cragg-Uhler) = 0.02, Pseudo-R² (McFadden) = 0.02, AIC = 13891.67, and BIC = 13956.14. X2 is the chi-squared value with the corresponding significance (p). Pseudo-R2 is the model fit from two di fferent methods. AIC is the Akaike’s Information Criteria. BIC is the Bayesian Information Criterion. The coefficients are the covariates from the best model. Estimate is the estimated amount by which the log o dds of presence would increase if that variable was one unit higher. Std. error is the standard error or the average distance that the observed values fall from the regression line. The z value is the estimate divide d by the standard error and p is the corresponding significance with the included significance codes.

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Figure 2-1. Cattle Egrets specimen locations over time, ranging from 1820 to 2017. Each point represents one specimen occurrence.

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Figure 2-2. Cattle Egret museum specimen occurrences from 1820 to 1870. Each point represents one specimen occurrence. The single point in North America was identified as inaccurately labeled and actually belongs in the 1950-1960s.

Figure 2-3. Cattle Egret museum specimen occurrences from 1871 to 1921. Each point represents one specimen occurrence.

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Figure 2-4. Cattle Egret museum specimen occurrences from 1922 to 1972. Each point represents one specimen occurrence.

Figure 2-5. Cattle Egret museum specimen occurrences from 1973 to 2017. Each point represents one specimen occurrence.

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40 Iceland Ireland 20 Cyprus US-Oklahoma 0 1800 1850 1900 1950 2000 2050 -20

-40

-60 South Africa -80

-100 Antarctica Degrees Change in Latitude from Origin Origin fromPoint in Change Degrees Latitude -120 Year

Figure 2-6. Latitudinal distance from origin to first occurrences of Cattle Egrets in different regions. X-axis is the year of occurrence and y-axis is the distance from the origin in latitudinal degrees. The orange point is the representative origin point of Cattle Egret native range. Each point is a first occurrence of a Cattle Egret museum specimen across global geographic regions.

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150 Macquarie Island

100 Australia

50 Cyprus 0 1800 1850 1900 1950 2000 2050

-50 Ireland Point

-100

Italy -150

-200 Hawaii Degrees Change in Longitude from Origin Origin from in Change Degrees Longitude

-250 Year

Figure 2-7. Longitudinal distance from origin to first occurrences of Cattle Egrets in different regions. X-axis is the year of occurrence and y-axis is the distance from the origin in longitudinal degrees. The orange point is the representative origin point of Cattle Egret native range. Each point is a first occurrence of a Cattle Egret museum specimen across global geographic regions.

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Log(y) = -3.71+0.01x

Figure 2-8. Percentage of pasture land use with Cattle Egret expansion and absence from best fit GLM. This plot shows the coefficient estimate and 95% confidence interval over the range of percentage of pasture land use with the expansion (presence) and absence points.

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Log(y) = -3.71+0.01x

Figure 2-9. Percentage of irrigated crops land use with Cattle Egret expansion and absence from best fit GLM. This plot shows the coefficient estimate and 95% confidence interval over the range of percentage of irrigated crops land use with the expansion (presence) and absence points.

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Log(y) = -3.71+0.13x

Figure 2-10. Rate of change of irrigated crops land use with Cattle Egret expansion and absence from best fit GLM. This plot shows the coefficient estimate and 95% confidence interval over the range of rate of change of irrigated crops land use with the expansion (presence) and absence points.

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Log(y) = -3.71-0.02x

Figure 2-11. Percentage of range land use with Cattle Egret expansion and absence from best fit GLM. This plot shows the coefficient estimate and 95% confidence interval over the range of percentage of range land use with the expansion (presence) and absence points.

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Log(y) = -3.71-0.01x

Figure 2-12. Percentage of rain fed crops land use with Cattle Egret expansion and absence from best fit GLM. This plot shows the coefficient estimate and 95% confidence interval over the range of percentage of rain fed crops land use with the expansion (presence) and absence points.

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Log(y) = -3.71-0.15x

Figure 2-13. Rate of change of range land use with Cattle Egret expansion and absence from best fit GLM. This plot shows the coefficient estimate and 95% confidence interval over the range of rate of change of range land use with the expansion (presence) and absence points.

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CHAPTER 3 DIVERSITY AND PHYLOGENETIC RELATIONSHIPS OF AVIAN HAEMOSPORIDIA IN CATTLE EGRETS (BUBULCUS IBIS), AND THEIR ROLE IN THE REGIONAL AND GLOBAL MOVEMENT OF HAEMOSPORIDIAN PARASITES

Birds play an important role in the global movement of pathogens (Hubálek 2004) because they can be both reservoir hosts and transporters of pathogens (Crowl et al.

2008). Long distance migrations can transport pathogens across continents and introduce emerging diseases to vulnerable populations (Keymer 1958, Pavlovsky and

Tokarevich 1966, McDiarmid 1969, Davis et al. 1971, Lvov and Ilichev 1979, Cooper

1990, Hubálek 1994, Nuttall 1997, Wobeser 1997, Hubálek 2004). The transport of pathogens can occur by migratory birds through several pathways, including vector- borne transmission, such as West Nile virus (WNV), in which birds act as an amplifying or reservoir host to the pathogen, or non-vectored transmission pathways which can include host to host contact or indirect transmission via the environment (e.g. avian influenza) (Rappole et al. 2000, Reed et al. 2003). Knowledge of the movement of pathogens carried by migratory birds across the landscape informs global epidemiology and the management of pathogen transmission; and increases understanding of the risks of zoonotic disease dispersal by both hosts and vectors.

The heron family, Ardeidae, has a global presence and migratory behavior that make members of this family an excellent model for the study of pathogen transport and emergence. Expanding globally within two centuries (see Chapter 1), Cattle Egrets

(Bubulcus ibis) are one of the most widely and rapidly expanding species. Cattle Egrets are capable of 1,660 km of non-stop direct flights and move as far as 20-60 km from nesting colony to feeding area in their daily cycle (Telfair II 2006). Flocking all year long, Cattle Egrets are the most gregarious of all herons, forming dense breeding

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colonies and nonbreeding roosts. Cattle Egrets are habitat and food generalists; they nest, roost, and feed in habitats ranging from upland trees, swamps or marshes, human residential areas, and grasslands. Their diet is also highly plastic and they have been found to feed on insects, frogs, fish, and juvenile rodents (Krebs et al. 1994, Mora and

Miller 1998, Ruiz 1984, Singh et al. 1988, Sodhi 1989).

Although Cattle Egret movement has not been thoroughly researched, observations indicate that they are partial obligatory migrators with wandering habits

(Browder 1973). Juvenile Cattle Egrets also exhibit widespread, long-distance post- breeding dispersal and establishment 1,900- 5,000 km from their natal colonies (Telfair

II 1983, Telfair II 1993). In North America, Cattle Egrets in the southeast United States migrate from the Caribbean up through Florida and along the Atlantic and Mississippi flyways, with a sedentary population remaining in the Caribbean and south Florida.

Migrating from a tropical region, Cattle Egrets are at increased risk for exposure to pathogens and ectoparasites throughout the Americas (Reed et al. 2003).

Given the plasticity of their habits and large scale movement of individuals, Cattle

Egrets have the potential to transport and transmit pathogens. They have been implicated as a mechanical vector of ticks from the Caribbean (Corn et al. 1993, Bram et al. 2002, Kasari et al. 2010), but little research has been conducted on their ability to transport microparasites. With their global expansion and ability for long distance movement, Cattle Egrets have the potential to be carriers or reservoirs for globally transmitted pathogens, making them a model for understanding the role of avian species in transporting exotic pathogens to naïve hosts, distributing pathogens into new locations, and the global epidemiology of pathogens carried by migratory birds.

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Haemosporidia (phylum Apicomplexa; Levine, 1988) are arthropod-borne blood parasites with a wide distribution and exploit hosts from most avian families (Martinsen et al. 2006, Valkiūnas 2005). Haemosporidia can be used to model arboviruses because of the similarity in vectors and hosts such as West Nile virus (Boothe et al.

2015). Avifauna are the intermediate hosts of Haemosporidia, which persist in the birds for many years or even for life, acting as a source of infection for vectors (Ricklefs et al.

2005, Atkinson and Van Riper 1991). The three main genera of Haemosporidia are

Plasmodium, Haemoproteus, and Leucocytozoon; each is vectored by a different family. Plasmodium is vectored by genera of the mosquito family, Culicidae.

Paraphyletic with Plasmodium, Haemoproteus is vectored by biting midges, Culicoides spp. (Family Caratopogonidae). Relatively understudied, Leucocytozoon has a basal position within Haemosporidia (Borner et al. 2016) and is vectored by the black flies

(Simuliidae family). In addition to parasitizing many species of arthropods,

Haemosporidia can be both host generalists or host specialists (Olsson-Pons et al. 2015, Beadell et al. 2006, 2009, Ishtiaq et al. 2006, Marzal et al. 2011, Hellgren et al. 2007, Ricklefs et al. 2005, Svensson-Coelho et al. 2013, Medeiros et al. 2013).

Prevalence and Diversity of Haemosporidia in Cattle Egrets

Cattle Egrets have previously tested positive for three lineages of Plasmodium and two lineages of Haemoproteus in other parts of the world (Ferraguti et al 2013, Lutz et al 2015). Cattle Egret in Nigeria have also tested positive for Plasmodium,

Haemoproteus, and Leucocytozoon (Omonona et al. 2014). In the southeast United

States, avian species have tested positive for lineages of Plasmodium, Haemoproteus, and Leucocytozoon. Given that Cattle Egrets are habitat generalists, can share habitats with the three vectors of Haemosporidia, have previously been found positive for all

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three genera, and that all three genera of Haemosporidia have been found in the study area, I hypothesized that I too would find all three genera of Haemosporidia in Cattle

Egrets in the southeastern US. I determined the prevalence and diversity of

Haemosporidian parasite genera in Cattle Egrets in the southeast United States.

Regional Host and Geographic Specificity

Cattle Egrets are gregarious and interact with other members of the Ardeidae family in their freshwater nesting habitat, as well as with grassland species found in their foraging habitat, which increases the risk of cross-species transmission via an arthropod vector. Given that Cattle Egrets are highly mobile and interact closely with many species, I expected that Cattle Egrets could be reservoirs for both host specific and host generalist lineages, and that the characteristics of both avian host and haemoparasite would create locally high admixture with little spatial structuring of haemoparasite lineages. To test this hypothesis, I constructed a phylogeny of Haemosporidia with additional samples from within the study area, mapped the connectivity of

Haemosporidia in Cattle Egrets between sampling locations, and assessed geographic structuring to determine the extent of spatial patterning in Haemosporidia in Cattle

Egrets.

Global Movement of Haemosporidia

As a globally distributed species that interacts with other avian species as well as livestock and large , Cattle Egrets have the potential to play an important role in the spread of pathogens over long distances which increases the likelihood of introducing novel parasite species to naïve ecosystems. With their capability to disperse and colonize beyond the study region, I hypothesized that the presence of both host specific and host generalist lineages of Haemosporidia with high geographic

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admixture would be evident on a global scale. I compared parasite lineages found in

Cattle Egrets in the southeast United States to previously published lineages and their sampling location and host to estimate the role of Cattle Egrets in the global spread of

Haemosporidia.

Methods

Sample Site and Field Methods

Field collection took place from July 2016- February 2018 at 25 locations in 6 states in the southeast United States (Figure 3-1). USDA Bird Aircraft Strike Hazard

(BASH) airport biologists euthanized animals during routine animal control efforts throughout the study area; animals were not euthanized as a result of this study.

Euthanized Cattle Egrets were placed in a labelled bag and frozen until necropsied.

Whole spleen was collected in Whirl-Paks from euthanized animals for pathogen testing to avoid bias associated with latent or active infections.

Live trapping was used to supplement BASH collection locations. Live trapping was conducted at the Merritt Island National Wildlife Refuge in Merritt Island, Florida and at the Buck Island Ranch in Lake Placid, Florida. Egrets were captured either with a net gun (CODA Enterprises) or net launcher (CODA Enterprises). Each trapped bird was weighed, banded with a U.S. Geological Survey numbered aluminum band, and a blood sample equaling no more than 1% of the body weight was taken by brachial venipuncture and stored in an EDTA tube for pathogen testing. All animal handling protocols were approved by the University of Florida Institutional Animal Care and Use

Committee Study #201508865.

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Parasite Screening Using PCR

DNA was extracted from avian spleen and whole blood using Qiagen DNeasy Blood and Tissue Kit (Qiagen, Valencia, CA, USA) and quantified using a NanoDrop™

Spectrophotometer (Thermo Fisher Scientific Inc., Wilmington, DE, USA). Extracted samples were screened for species of Haemoproteus, Plasmodium, and Leucocytozoon using nested polymerase chain reaction (PCR) to amplify regions of the mitochondrial cytochrome b gene (Tables 3-1, 3-2, 3-3, 3-4, 3-5). All PCR products were viewed on

2.0% agarose gels stained with ethidium bromide. Positive PCR products were purified using Zymo PCR Purification kit and sent to Eurofins Genomics, LLC (Louisville, KY,

USA) for bi-directional sequencing. Sequences were edited and aligned using

Geneious (version 10.2.4, Kearse et al. 2012).

There are no widely used criteria for defining lineages and species of

Haemosporidia (Smith et al. 2018, Outlaw and Ricklefs 2014). Wood et al. (2007) and

Marzal et al. (2011) separated lines that were different by 1 bp. Ricklefs and Fallon

(2002) reported the average LogDet genetic distance (dij) between lineages was 0.012 ±

0.011. Hellgren et al. (2007) proposed a sequence divergence cutoff of 5% to separate lineages, though this was with the caveat that corresponding morphological data would be provided to strengthen the results. Defining lineages as being separated by 1 bp is the strictest possible definition and accounts for cases where sequences had differing morphologies or reproductive or geographic isolation but only differed by 1 bp, however, it can also artificially increase diversity (Bensch et al. 2004, 2009, Palinauskas et al.

2015). In this study, a haplotype was defined as a unique sequence with less than one base pair difference, a lineage was defined as a collection of haplotypes with less than

1% divergence (1-4 bp), and each genus was a predetermined clade of

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Haemosporidians. Sequences were identified to genus by identifying their closest matches in GenBank using the National Center for Biotechnology Information (NCBI) nucleotide BLAST search. Final sequences were subsequently deposited to GenBank.

Parasite Lineage Identification, Prevalence, and Diversity

I determined local prevalence and diversity of Haemosporidians in Cattle Egrets throughout the southeastern United States. Analyses were performed based on a

≥400bp region of the cytochrome b (cyt-b) gene of Haemosporidia found in Cattle

Egrets in the southeast United States. Haplotypes less than 400 bp were labeled as

“unidentified” lineages to limit misidentification from a lack of base pair information.

Unidentified sequences were included in prevalence comparisons but were removed from all phylogenetic analyses. All analyses were repeated for Plasmodium and

Leucocytozoon, separately. Pairwise distances were calculated in MEGA to confirm unique lineages. Unique lineages were defined as sequences that shared <1% sequence divergence (0-4 bp of ~400bp) (Ricklefs et al. 2005, Ellis et al. 2017).

Unique lineages were visualized by estimating the phylogeny of sequences for every sequence across all genera using 1000 bootstrap replicates of the PhyML

(Guindon et al. 2010) analysis extension in Geneious. The best fit evolutionary model for this inclusive phylogeny was determined using maximum likelihood analyses and

Bayesian information criteria (BIC) in MEGA7. Plasmodium falciparum (AF069605), a human plasmodium, was used to root all trees. The prevalence of each lineage was calculated, and NCBI BLAST was used to determine closest matching sequence in the

GenBank database and corresponding divergence as of August 19, 2018.

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Regional Host and Geographic Specificity

DNA sequences of avian Haemosporidians from any avian species found in the southeast United States and Caribbean basin were collected from the MalAvi database

(Bensch et al. 2009) and GenBank and subsequently used to determine host-parasite specificity at the regional scale. The best fit evolutionary model for both genera was determined using maximum likelihood analyses and BIC in MEGA7. Phylogenetic trees were made in Geneious using the PhyML extension with 1000 bootstrap replicates using lineages found in Cattle Egrets and the additional lineages from MalAvi and

GenBank to determine the host specificity of lineages found in Cattle Egrets at the regional scale. Host specificity was determined by comparing the number of avian families infected by unique lineages.

Haplotype networks, connectivity maps, and Analysis of Molecular Variance

(AMOVA) were used with the Haemosporidian sequences to assess the geographic structuring of Haemosporidia in Cattle Egrets on a regional scale. Haplotype networks organized by haplotype and by geography were made with PopArt 1.7 (Leigh and

Bryant, 2015). All sequences found in Cattle Egrets that were previously assigned to lineages were shortened to the same length of 350 bp for network analysis per PopArt requirements. Parasite diversity was quantified per sampling site by calculating

Shannon’s diversity index using the “vegan” package in R (Oksanen et al. 2018).

Binary matrix maps illustrating connectivity between sampling sites were created using the “gdistance” (van Etten 2018) and “igraph” (Csárdi 2018) packages in R.

AMOVA was performed in ARLEQUIN 3.5.2.2 (Excoffier et al. 2005) to determine the extent of geographic structuring of parasite lineages. Sequences were shortened to equal lengths to meet ARLEQUIN requirements. Within ARLEQUIN, sequence

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divergence, calculated as Tamura and Nei parameter distances (Tamura and Nei 1993), and the frequency of each lineage that occurred at each location were used to estimate the proportion of total covariance distributed within versus among each geographic location. The Monte Carlo permutation test in AMOVA was used to determine the statistical significance of variance terms with 1000 permutations (Excoffier et al. 1992).

Global Movement of Haemosporidia

The closest matches from any families or geographic locations to each lineage of

Haemosporidian found in a Cattle Egret were collected from the GenBank database and analyzed along with the Cattle Egret Haemosporidian lineages to analyze the global extent of Haemosporidian dispersal. Maximum likelihood analyses and BIC in MEGA7 were used to determine the best fit evolutionary model for each genera. Phylogenetic trees were made in Geneious using the PhyML extension with 1000 bootstrap replicates.

Results

Parasite Prevalence and Diversity

A total of 516 Cattle Egrets were screened for avian malaria (2016: 197; 2017:

319). A total of 51.2% (N=264 of 516) were infected with parasites of the genera

Plasmodium (18.6%, N= 96 of 516) and/or Leucocytozoon (39.1%, N= 202 of 516), and

34 of these individuals were co-infected with both Plasmodium and Leucocytozoon

(6.6%; Table 3-6). No birds were found with Haemoproteus spp. infections. The

TN93+G model for sequence evolution best fit our cyt-b mitochondrial DNA lineage dataset for both Plasmodium spp. (N= 95 individuals) and Leucocytozoon spp. (N=188 individuals) (Figures 3-2, 3-3). The 1% divergence definition of lineages in this study was supported by sequence divergence estimates which indicated natural phylogenetic

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grouping of sequences that were supported by the trees using all sequences for each genus. The 1% divergence definition was further supported by the lack of geographic isolation within the trees using all sequences.

In total, 26 haplotypes were found which were collapsed into 14 lineages of

Haemosporidia between two genera. Six lineages identified to the genus Plasmodium and eight lineages identified to the genus Leucocytozoon. Three Plasmodium were identified to morphologically described and named species: Lineage

CAEG_FL_SPM_P1 (P. nucleophilum), Lineage CAEG_FL_SPM_P2 (P. paranucleophilum), and Lineage CAEG_FL_SPM_P3 (P. elongatum), with the Lineage

CAEG_FL_SPM_P2 being an exact match. Two additional Plasmodium lineages had lineage level correspondence to lineages of Plasmodium that have not been morphologically described and named: Lineage CAEG_FL_SPM_P4 (Plasmodium sp.

NYCNYC01) and Lineage CAEG_FL_SPM_P6 (Plasmodium sp. AM051). Lineage

CAEG_FL_SPM_P5 did not have a lineage level match with the closest match having a

1.1% divergence to Plasmodium sp. CRAM-2278.

No lineages of Leucocytozoon were identified based on previously morphologically defined and named species. One lineage of Leucocytozoon, Lineage

CAEG_LA_SPM_L3, corresponded exactly to an unidentified species of Leucocytozoon with a 0% divergence to Leucocytozoon sp. eruvetpar2. Another lineage,

CAEG_FL_SPM_L6, had a lineage level match to an unidentified species,

Leucocytozoon sp. B30. This same lineage was the closest match for three additional lineages (CAEG_FL_SPM_L5, CAEG_LA_SPM_L7, and CAEG_FL_SPM_L8) though not at a lineage level. Lineage CAEG_LA_SPM_L4 did not have a lineage level match

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with a 3.1% divergence to Leucocytozoon sp. V. Lineages CAEG_FL_SPM_L1 and

CAEG_FL_SPM_L2 did not have lineage level matches with their closest matches being 6.1% divergence from Leucocytozoon sp. L-SC-P01 and 5.8% divergence from

Leucocytozoon sp. GHOW93-74-48, both of which are outside of even the broadest lineage definition (Hellgren et al. 2007, Genbank accession numbers and divergence for closest matched lineages in Tables 3-7, 3-8).

Regional Host and Geographic Specificity

To identify potential host switching, phylogenetic trees were constructed from lineages from this study and additional lineages found from other avian species within the study area. The TN93+G model was determined as the best fit model for both genera using maximum likelihood analyses and BIC in MEGA7. The comparison of databased lineages from within the study area to lineages from Cattle Egrets revealed similar lineages found in Cattle Egrets and Blue-winged Teal (Anas discors), House

Sparrow (Passer domesticus), House Finch (Carpodacus mexicanus), and White-eyed

Vireo (Vireo griseus) (Figures 3-4, 3-5). Lineage CAEG_FL_SPM_P2 was identical to a lineage found in Blue-winged Teal in Louisiana, USA. A total of five lineages in four different host species from four families were similar to lineages found in Cattle Egrets.

No Leucocytozoon spp. lineages from this study grouped to any published lineages found in the southeast United States or Caribbean Basin (Figures 3-6, 3-7).

Only one other study has found and published Leucocytozoon spp. lineages from within the study area, all from Blue-winged Teals in Louisiana, USA (Ramey et al. 2016).

The haplotype network based on haplotype of Plasmodium spp. lineages from

Cattle Egrets in the southeast United States displayed six clusters, supporting the six lineages of Plasmodium spp. identified in Cattle Egrets in the southeast United States

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(Figure 3-8). There was no apparent geographic clustering, though Lineage

CAEG_FL_SPM_P2 was not found south of north Florida (latitude 30.39) and Lineages

CAEG_FL_SPM_P1 and CAEG_FL_SPM_P4 were not found south of Sarasota

(latitude 27.39) and Tampa (Latitude 27.86), respectively. The haplotype network based on haplotype of Leucocytozoon spp. lineages from Cattle Egrets in the southeast

United States displayed eight clusters, supporting the eight lineages of Leucocytozoon spp. identified in Cattle Egrets in the southeast United States (Figure 3-9). There was no apparent geographic clustering, though the prevalence of all lineages except for lineage CAEG_FL_SPM_L6 was too small to draw any conclusions.

The haplotype network based on geography illustrated the proportion of

Plasmodium lineages at each sample location, with overall prevalence and Shannon’s

Diversity Index at each location supporting a lack of geographic clustering (Figure 3-10).

As seen in the haplotype network based on haplotype, Lineage CAEG_FL_SPM_P2 was not found south of north Florida (latitude 30.39) and Lineages CAEG_FL_SPM_P1 and CAEG_FL_SPM_P4 were not found south of Sarasota (latitude 27.39) and Tampa

(Latitude 27.86), respectively. The proportion of Leucocytozoon lineages at each sample location supports a lack of geographic clustering (Figure 3-11). Lineage

CAEG_FL_SPM_L6 was present at all locations with positive samples for

Leucocytozoon spp. except for St. Louis, however, the sample size (N=1) was too small at this location to draw any conclusions.

Binary matrix maps illustrated the broad connectivity of both Plasmodium spp.

(Figure 3-12) and Leucocytozoon spp. (Figure 3-13) lineages from Cattle Egrets across the study area. Both maps indicated that these Haemosporidians were geographically

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widespread and highly connected among pairwise sites across the study area. For the

Leucocytozoon spp. matrix map, one lineage, CAEG_FL_SPM_L6, was responsible for the high connectivity. In contrast, the Plasmodium spp. matrix map had several lineages of relatively equal prevalence spread across the landscape. AMOVA revealed statistically significant structuring of Plasmodium spp. among geographic locations and no statistical significance of Leucocytozoon spp. among geographic locations (Table 3-

9).

Global Movement of Haemosporidia

The closest phylogenetic matches to each lineage showed the wide host and global geographic range of lineages found in Cattle Egrets (Figures 3-14, 3-15).

Maximum likelihood analyses and BIC in MEGA7 were used to determine TN93+G as the best fit model for both genera. Plasmodium lineages with a lineage-level match to sequences from this study were from a total of 28 different families and 6 continents.

Individual Plasmodium spp. lineage groups ranged from 2-16 families and 2-6 continents. The Plasmodium tree was split into two clades. The first clade was spread globally, on all six continents where avian malaria is found, and it was all matched to one lineage found in Cattle Egrets. The second clade contained the other five lineages found in Cattle Egrets. All lineages in the second clade were from either North or South

America, which are connected by several flyways. Only two lineages of Leucocytozoon spp. found in Cattle Egrets had lineage level matches from a total of 5 families and 4 continents. Individual Leucocytozoon spp. lineage groups ranged from 1-5 families and

2-3 continents. Six of the Leucocytozoon lineages were novel, with no lineage level matches. Lineage CAEG_LA_SPM_L3 had broad host and geographic range with five families and three continents supporting the lack of host and geographic specificity.

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Lineage CAEG_FL_SPM_L6 matched to a lineage in one additional species in the same family as Cattle Egrets, found in Benin.

Discussion

The rapid and global expansion of Cattle Egrets appears to have influenced the distribution and diversity of Haemosporidians. Due to their widespread movement, close interaction with other species, and generalist behavior, Cattle Egrets have the potential to spread pathogens long distances and to multiple hosts. Cattle Egrets in the southeast United States had a high prevalence of Plasmodium and Leucocytozoon which were highly connected between sampling locations. In general, lineages found in

Cattle Egrets in this study mostly lacked geographic or host specificity. One lineage of

Leucocytozoon, Lineage CAEG_FL_SPM_L6, implicated Cattle Egrets specifically in the ability to transport pathogens across continents. The results from this study indicated that Cattle Egrets have the capability to spread pathogens across their global distribution and to a variety of other hosts.

Parasite Prevalence and Diversity

Due to their generalist and wide-ranging behavior, I expected that Cattle Egrets would have highly prevalent and diverse Haemosporidia (Jenkins et al. 2012). The prevalence of Plasmodium in Cattle Egrets of 18.6% was within the previously observed range of 13.4-27.8% in studies of multiple bird species with similar sample sizes (Baillie and Brunton 2011, Loiseau et al. 2010, Levin et al. 2013, Wood et al. 2007, Smith et al.

2018). We found no evidence of Haemoproteus in Cattle Egrets, compared to the previously observed prevalences of 0.9-38.4% (Loiseau et al. 2010, Balasubramaniam et al. 2013, Wood et al. 2007, Smith et al. 2018).

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Leucocytozoon spp. is understudied compared to Haemoproteus and

Plasmodium with few studies of comparable sample size. Cattle Egrets in the southeast

United States had a relatively high prevalence of 39.1%, with comparable studies reporting 6.6% prevalence in Passeriformes species (Smith et al. 2018) and 53.9% in a

Sphenisciformes species (Argilla et al. 2013), both in the temperate region. The overall prevalence of Haemosporidia in Cattle Egrets of 51.2% was higher than that reported by comparable studies, with 39.8% in songbirds in central California (Walther et al. 2016) and 41.2% in songbirds in Michigan (Smith et al. 2018).

It is possible that the prevalence of Haemosporidia in this study differs compared to other studies due to the use of PCR over microscopy and the testing of primarily spleen rather than blood. Due to the life cycle of Haemosporidia parasites, the parasite could be in present in the organs but not actively circulating in the blood stream at the time of sampling. Spleen likely gives a more accurate representation of the number of individuals carrying Haemosporidia parasites, whether or not they are actively circulating in the blood.

The lack of Haemoproteus spp. in Cattle Egrets in the southeast United States indicates habitat interactions may have a role in the presence or lack of particular genera of Haemosporidia. Haemoproteus spp. has previously been found in the southeastern United States (Ricklefs and Fallon 2002, Kimura et al. 2006, Marzal et al.

2011, Villar et al. 2013, Lewicki et al. 2015, Ramey et al. 2016) and in Cattle Egrets in other countries (Ferraguti et al. 2013, Lutz et al. 2015), but given the lack of

Haemoproteus spp. in Cattle Egrets in the southeastern US, it is possible that there was

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not an orniphilic midge capable of spreading Haemosporidian parasites in the habitats used by Cattle Egrets (e.g. freshwater marsh, pasture).

I expected that Cattle Egrets would have a relatively high diversity of

Haemosporidia lineages compared to other species. Limited diversity data is available from previous studies with similar sampling effort that test for Plasmodium,

Haemoproteus, and Leucocytozoon. Smith et al. (2018) reported high diversity with 51 lineages of Haemosporidia present in Passeriformes in Michigan. However, this was cumulative in multiple species in the order Passeriformes as opposed to a single species. Smith et al. (2018) reported the highest individual species diversity as eight lineages in two different species, American Robin (Turdus migratorius) and Northern

Cardinal (Cardinalis cardinalis), compared to the 14 lineages found in Cattle Egrets in this study (six Plasmodium and eight Leucocytozoon). The higher diversity in Cattle

Egrets could be due to their wide-ranging behavior compared to either American Robin or Northern Cardinal.

The number of lineages identified in this study increases the previously recorded number of lineages found in Cattle Egrets (2 Haemoproteus and 3 Plasmodium) to a total of 18 lineages, as one lineage found in Cattle Egrets in the southeast United States was a lineage level match to a lineage found in a Cattle Egret in Spain (Plasmodium sp.

GRW6, DQ368381.1). Of the total 14 lineages identified in Cattle Egrets in the southeast United States, seven had lineage level-matches to previously published lineages in the NCBI database. The remaining seven lineages, 1 Plasmodium and 6

Leucocytozoon, were novel haplotypes, not reported previously.

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Regional Host and Geographic Specificity

I expected that Cattle Egrets in the southeastern US would carry pathogens identified as a mix of host specific and generalist lineages, with high admixture within geographic locations, and little spatial structuring, given that Cattle Egrets are highly mobile and interact closely with native species. My data exhibited high connectivity and admixture of Haemosporidia between sampling locations, but indicated variations in the geographic structuring of Plasmodium spp. and Leucocytozoon spp. The AMOVA indicated Plasmodium spp. had a significant geographic structure among sampling locations whereas Leucocytozoon spp. had a lack of geographic structure. This difference in geographic structuring is possibly driven by the differences in host specificity between lineages of the two genera.

When compared to lineages from other avian species within the region, four

Plasmodium spp. lineages were considered host generalists as they had lineage level matches to parasite lineages from hosts of other avian families. Three of the four

Plasmodium spp. lineages matched to lineages found in the Blue-winged Teal, a migratory bird that can be found in marsh habitats in the Americas. The overlap in lineages could indicate transmission from one host species to another (via an arthropod vector) that was facilitated by close proximity and shared habitat between Cattle Egrets and Blue-winged Teal. Cattle Egrets are gregarious and often sharing roosting habitat and forage with other aquatic and semi-aquatic birds (Vincent 1947, Blaker 1971,

Siegfried 1971a).

The lack of comparable published sequences for Leucocytozoon spp. lineages made inferences about transmission more difficult. However, based on the prevalence records and haplotype networks, it is evident that lineage CAEG_FL_SPM_L6

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dominated the Leucocytozoon spp. infections and was present across the landscape, leading to homogeneity and the lack of geographic structure significance seen in the

AMOVA. Leucocytozoon lineages were also found in Blue Winged Teal, but not the

CAEG_FL_SPM_L6 lineage, despite its high prevalence across the landscape, suggesting that, indeed, this lineage may be phylogenetically constrained. The domination of lineage CAEG_FL_SPM_L6 and its impact on the geographic structure of

Leucocytozoon spp. on the regional scale was further supported when global scale analysis indicated it as a host specialist as discussed below.

Global Movement of Haemosporidia

The ability to migrate and disperse long distances increases the likelihood of

Cattle Egrets to carry Haemosporidia long distance, which in turn increases their likelihood of introducing novel parasite species to naïve ecosystems. My data demonstrated the potential for Cattle Egrets to transport blood parasites globally and impact a variety of other host families and orders. The two clades of the Plasmodium spp. that I found in Cattle Egrets in the southeastern US suggest two different global movement patterns of Haemosporidians, and both indicate host switching. Clade 1 is highly generalist with the one lineage being found on all continents and in a wide variety of host families, indicating high levels of host switching. Clade 2 is also generalist with a majority of the lineages found in Cattle Egrets being found in many families but only between North and South America. It is possible that the many migration paths between North and South America facilitated this pattern. Lineage CAEG_FL_SPM_P5 is the lone example of a possible geographic and host specific Plasmodium sp. lineage as it did not have lineage level matches. Despite the lack of published lineages for comparison, one lineage Leucocytozoon spp. found in this study mirrored the pattern of

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geographic and host diversity seen in the Plasmodium spp., with lineage

CAEG_LA_SPM_L3 being present in five different families and across three continents.

While it appears that multiple lineages in both Plasmodium spp. and

Leucocytozoon spp. gained a broad distribution via a generalist strategy (Peréz-Tris and

Bensch 2005, Hellgren et al. 2009, Poulin et al. 2011), one lineage of Leucocytozoon gained its broad distribution by using a specialist strategy (Poulin 1998). Patterns in both the regional maps and global phylogenetic tree suggest host specificity of the

CAEG_FL_SPM_L6 lineage and possible origin in Benin, Africa. The host specificity suggested by lineage CAEG_FL_SPM_L6 exemplified the specialist strategy: infecting one avian family, spreading between Africa and North America, and dominating the

Leucocytozoon sp. infections in Cattle Egrets in the southeastern US. Lineage

CAEG_FL_SPM_L6 made up 82.4% of the positive Leucocytozoon spp. lineages in this study and had a lineage level match with a lineage found in a Striated Heron (Butorides striata) in Benin, Africa. The Striated Heron is a fellow member of the Ardeidae family and Africa is the native range of Cattle Egrets. Benin is along the suggested pathway that Cattle Egrets used to spread to the Americas. Without additional sequences for further comparison it is not possible to verify that Lineage CAEG_FL_SPM_L6 is host specific to the Ardeidae family, but it is evidence in support of Cattle Egrets’ capability to transport pathogens long distances and proliferate a pathogen throughout a region.

The high prevalence and diversity, lack of geographic or host specificity within the study area and around the world, and the only host-specific lineage, Lineage

CAEG_FL_SPM_L6, supports Cattle Egrets as playing a role in the global movement of

Haemosporidia. Future comparison to Cattle Egrets’ genetic data could yield more

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information about the movement of Haemosporidia relative to that of Cattle Egrets within the southeast United States. The seven novel lineages of Haemosporidia found in this study indicate that there is still much unknown about the prevalence, diversity, and phylogeny of avian malaria in many regions of the world. Additional Haemosporidia testing, particularly of Leucocytozoon, within the southeast United States and in members of the Ardeidae family will help develop even further of understanding of how

Haemosporidia parasites are moving around the world.

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Table 3-1. Primers used for PCR of DNA extracted from Cattle Egrets to test for Haemoproteus spp., Plasmodium spp., and Leucocytozoon spp.

Genus Outer Primers Inner Primers Haemoproteus spp. HaemNFI/HaemNR3 (Hellgren HaemF/HaemR2 (Bensch et Plasmodium spp. et al. 2004) al. 2000) HaemNFI/HaemNR3 (Hellgren HaemFL/HaemR2L (Hellgren Leucocytozoon spp. et al. 2004) et al. 2004)

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Table 3-2. Ratio of products used in PCR reactions to test DNA extracted from Cattle Egrets for Haemosporidia.

Primer HaemNFI/HaemNR3 HaemF/HaemR2 HaemFL/HaemR2L Reaction Size (uL) 25.0 25.0 25.0 Buffer (X) 1.0 1.0 1.0 MgCl (mM) 2.75 1.5 1.5 dNTPs (mM) 0.2 0.2 0.2 primer-F (uM) 0.5 0.5 0.5 primer-R (uM) 0.5 0.5 0.5 Taq, Promega (U/ul) 0.025 0.05 0.05 1.5 µL of DNA/PCR product were used in each reaction.

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Table 3-3. Thermo-cycler profile for PCR reaction with outer primers HaemNFI and HaemNR3 to test DNA extracted from Cattle Egrets for Haemosporidia.

HaemNFI/HaemNR3 Temperature (°C) Time (seconds) # of cycles Initial Denaturation 95 120 1 Denaturation 95 50 35 Annealing 50 50 Extension 72 66 Final Extension 72 180 1 Soak 4

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Table 3-4. Thermo-cycler profile for PCR reaction with inner primers HaemF and HaemR2 to test DNA extracted from Cattle Egrets for Plasmodium and Haemoproteus.

HaemF/HaemR2 Temperature (°C) Time (seconds) # of cycles Initial Denaturation 95 120 1 Denaturation 95 50 35 Annealing 55 50 Extension 72 66 Final Extension 72 300 1 Soak 4

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Table 3-5. Thermo-cycler profile for PCR reaction with inner primers HaemF and HaemR2 to test DNA extracted from Cattle Egrets for Leucocytozoon.

HaemFL/HaemR2L Temperature (°C) Time (seconds) # of cycles Initial Denaturation 95 120 1 Denaturation 95 50 35 Annealing 50 50 Extension 72 66 Final Extension 72 300 1 Soak 4

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Table 3-6. Prevalence of parasite lineages of Plasmodium and Leucocytozoon found in Cattle Egrets in the southeast United States.

Parasite taxon Lineage N positive Prevalence (%) Plasmodium nucleophilum CAEG_FL_SPM_P1 2 0.4 Plasmodium paranucleophilum CAEG_FL_SPM_P2 24 4.7 Plasmodium elongatum CAEG_FL_SPM_P3 8 1.6 Plasmodium sp. CAEG_FL_SPM_P4 18 3.5 Plasmodium sp. CAEG_FL_SPM_P5 19 3.7 Plasmodium sp. CAEG_FL_SPM_P6 24 4.7 Plasmodium sp. unidentified 1 0.2 Pooled Plasmodium --- 96 18.6 Leucocytozoon sp. CAEG_FL_SPM_L1 1 0.2 Leucocytozoon sp. CAEG_FL_SPM_L2 8 1.6 Leucocytozoon sp. CAEG_LA_SPM_L3 3 0.6 Leucocytozoon sp. CAEG_LA_SPM_L4 5 1.0 Leucocytozoon sp. CAEG_FL_SPM_L5 2 0.4 Leucocytozoon sp. CAEG_FL_SPM_L6 166 32.2 Leucocytozoon sp. CAEG_LA_SPM_L7 1 0.2 Leucocytozoon sp. CAEG_FL_SPM_L8 2 0.4 Leucocytozoon sp. unidentified 14 2.7 Pooled Leucocytozoon --- 202 39.1 Plasmodium + Leucocytozoon coinfection --- 34 6.6 Total individuals infected --- 264 51.2

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Table 3-7. Lineages of Plasmodium spp. found in Cattle Egrets in the southeast United States with closest haplotype matches from GenBank database as of August 19, 2018 and corresponding sequence divergence.

Cattle Egrets Lineage code, GenBank no. Genus species Sequence divergence (%) Plasmodium lineage CAEG_FL_SPM_P1 HMA-2012, JN819335 Plasmodium nucleophilum 0.1 CAEG_FL_SPM_P2 CPCT57, KX159495 Plasmodium paranucleophilum 0.0 CAEG_FL_SPM_P3 DENVID02, KU057965 Plasmodium elongatum 0.2 CAEG_FL_SPM_P4 NYCNYC01, KU057967 Plasmodium sp. 0.2 CAEG_FL_SPM_P5 CRAM-2278, KJ777724 Plasmodium sp. 1.1 CAEG_FL_SPM_P6 AM051, MF953290 Plasmodium sp. 0.2

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Table 3-8. Lineages of Leucocytozoon spp. found in Cattle Egrets in the southeast United States with closest haplotype matches from GenBank database as of August 19, 2018 and corresponding sequence divergence.

Cattle Egrets Lineage code, GenBank no. Genus species Sequence divergence (%) Leucocytozoon lineage CAEG_FL_SPM_L1 L-SC-P01, KP688303 Leucocytozoon sp. 6.1 CAEG_FL_SPM_L2 GHOW93-74-48, EU627821 Leucocytozoon sp. 5.8 CAEG_LA_SPM_L3 eruvetpar2, KC962152 Leucocytozoon sp. 0.0 CAEG_LA_SPM_L4 V, KX832576 Leucocytozoon sp. 3.1 CAEG_FL_SPM_L5 B30, MG018662 Leucocytozoon sp. 1.9 CAEG_FL_SPM_L6 B30, MG018662 Leucocytozoon sp. 0.4 CAEG_LA_SPM_L7 B30, MG018662 Leucocytozoon sp. 1.2 CAEG_FL_SPM_L8 B30, MG018662 Leucocytozoon sp. 2.1

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Table 3-9. AMOVA results for Plasmodium and Leucocytozoon lineages from sampling locations across the southeast United States.

d.f. SS % Variation P-value Plasmodium lineages Among sampling locations 17 228.848 12.82 0.00098±0.00098 Within sampling locations 76 589.863 87.18 Leucocytozoon lineages Among sampling locations 21 89.554 4.65 0.17791±0.01122 Within sampling locations 165 509.910 95.35

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Latitude

Longitude

Figure 3-1. Sampling locations of Cattle Egret for Haemosporidia analysis. (1) Barksdale, LA (2) Beaufort, SC (3) Belle Chasse, LA (4) Charleston, SC (5) Duke Air Field, FL (6) Eglin Air Force Base, FL (7) Harold (8) Homestead, FL (9) Jacksonville, FL (10) Key West, FL (11) Lake Placid, FL (12) Mayport (13) Merritt Island, FL (14) NASJacksonville (15) Preston, MS (16) Santa Rosa, FL (17) Sarasota, FL (18) Savannah, GA (19) South Lake, FL (20) Spencer (21) Saint Louis, MO (22) Summerdale, AL (23) Tampa, FL (24) Valdosta, GA (25) Whiting, FL. (11) Lake Placid, FL was a live capture location and (13) Merritt Island, FL was a combination of live capture and euthanized sampling. (19) South Lake, FL was a single Cattle Egret found dead in a parking lot. All other locations were samples from euthanized Cattle Egrets from regular air strike management efforts.

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Figure 3-2. Phylogeny of all Plasmodium spp. lineages found in Cattle Egrets in the southeast United States. N equals the number of individuals with each lineage. Labels along the bars are the bootstrap support percentages.

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Figure 3-3. Phylogeny of all Leucocytozoon spp. lineages found in Cattle Egrets in the southeast United States. N equals the number of individuals with each lineage. Labels along the bars are the bootstrap support percentages.

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Figure 3-4. Phylogenetic tree of Plasmodium spp. lineages with additional Plasmodium spp. lineages found in the southeast United States and Caribbean basin from MalAvi database. Colored boxes indicate <1% divergence from the Cattle Egret lineage contained within the box. Squares represent host family based on Figure 3-16. Triangles indicate lineages found in Cattle Egrets. Values are bootstrap support percentages.

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Figure 3-5. Sequence identity matrix of Plasmodium spp. found in Cattle Egrets in the southeast United States with additional lineages sampled from birds in the southeast United States and Caribbean basin. Additional lineages are from the MalAvi database.

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Figure 3-6. Phylogenetic tree of Leucocytozoon spp. lineages with additional Leucocytozoon spp. lineages found in the southeast United States and Caribbean basin from MalAvi database. No additional sequences had a <1% divergence from any of the lineages identified in Cattle Egrets. Squares represent host family based on Figure 3-16. Triangles indicate lineages found in Cattle Egrets. Values indicated bootstrap support percentages.

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Figure 3-7. Sequence identity matrix of Leucocytozoon spp. found in Cattle Egrets in the southeast United States with additional lineages sampled from birds in the southeast United States and Caribbean basin. Additional lineages are from the MalAvi database.

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Figure 3-8. Minimum spanning network of Plasmodium spp. mitochondrial DNA cytochrome b lineages from Cattle Egrets in the southeast United States. Sequences shortened to equal length at 350 bp. Each circle represents a haplotype with circle drawn proportional to the frequency each haplotype was observed. Hash marks on lines separating nodes represent the number of differing base pairs between the nodes and boxes indicated grouping of lineages. The nucleotide diversity was 0.047 and Tajima’s D equals 2.81 (p(D≥2.81)=0.007). There were 77 segregating sites and 66 parsimony informative sites.

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Figure 3-9. Minimum spanning network of Leucocytozoon spp. mitochondrial DNA cytochrome b lineages from Cattle Egrets in the southeast United States. Sequences shortened to 350 bp. Each circle represents a haplotype with circle drawn proportional to the frequency each haplotype was observed. Hash marks on lines separating nodes represent the number of differing base pairs between the nodes and boxes indicated grouping of lineages. The nucleotide diversity was 0.016 and Tajima’s D equals -1.698 (p(D≥- 1.698)=0.062). The number of segregating sites was 77 and the number of parsimony informative sites was 66.

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Figure 3-10. Distribution of Plasmodium spp. lineages across the southeast United States. P is the prevalence and D is the Shannon’s Diversity Index at each location. Relative circle size indicates the number of positive lineages.

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Figure 3-11. Distribution of Leucocytozoon spp. lineages across the southeast United States. P is the prevalence and D is the Shannon’s Diversity Index at each location. Relative circle size indicates the number of positive lineages.

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Figure 3-12. Binary connectivity map of sampling locations with lineage-level matches of Plasmodium. Lines indicate that the connected locations share at least one of the same lineage.

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Figure 3-13. Binary connectivity map of sampling locations with lineage-level matches of Leucocytozoon. Lines indicate that the connected locations share at least one of the same lineage.

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Clade 1

Clade 2

Figure 3-14. Phylogenetic tree of Plasmodium spp. lineages with closest NCBI BLAST matches from GenBank database. Additional lineages have an equivalent divergence to each lineage found in Cattle Egrets as that listed in Table 3-5. Colored boxes indicate <1% divergence from Cattle Egret lineage contained within color box. Squares represent host family and circles represent continent based on Figure 3-16. Value represent boot strap support percent. Triangles indicate lineages found in Cattle Egrets.

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Figure 3-15. Phylogenetic tree of Leucocytozoon spp. lineages with closest NCBI BLAST matches from GenBank database. Additional lineages have an equivalent divergence to each lineage found in Cattle Egrets as that listed in Table 3-5. Colored boxes indicate <1% divergence from Cattle Egret lineage contained within box. Squares represent host family and circles represent continent based on Figure 3-16. Values represent boot strap support percent. Triangles indicate lineages found in Cattle Egrets.

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Figure 3-16. Key for family and continent labels in phylogenetic trees.

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CHAPTER 4 CONCLUSION: CATTLE EGRET (BUBULCUS IBIS) AS A GLOBAL MOVER OF DISEASE

Cattle Egrets’ movement and expansion has been shown to be closely tied to intensive agricultural land use (see Chapter 2) and has been implicated in the ability to spread a parasite between countries (see Chapter 3). Although Cattle Egrets can only be implicated and not verified as transporting these parasites either in the instances of host generalism as seen in many of the Plasmodium spp. lineages or even in the host specific CAEG_FL_SPM_L6, they are clearly still connected to the ecosystems in which these parasites circulate. The presence of numerous generalist parasites as seen in the Plasmodium lineages of this study results in high invasive potential to novel habitats and host species. The Plasmodium lineages CAEG_FL_SPM_P1,

CAEG_FL_SPM_P2, CAEG_FL_SPM_P4, and CAEG_FL_SPM_P6 all support migration as an important pathway for diseases with the connection of all of these lineages between North and South America, which are connected by commonly used flyways for migratory birds.

Many of the conclusions drawn in Chapter 3 regarding the global spread of

Haemosporidia were dependent on previous publications and shared sequences. This dependency is especially impactful in Leucocytozoon spp. as it is understudied. The lack of sequences limited the global knowledge of Leucocytozoon spp. for comparison.

Future testing could reveal further connections to the novel lineages identified in Cattle

Egrets and provide further information about potential connections to other hosts or locations for both Plasmodium spp. and Leucocytozoon spp. lineages.

A large knowledge gap that still needs to be addressed is the modern movements of Cattle Egrets and how they could still be moving diseases around the

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world. As seen in Chapter 1, Cattle Egrets have been found with a wide variety of diseases including zoonotic pathogens. With Cattle Egrets’ range still expanding, there is still high potential for them to establish in novel locations and transport diseases into naïve populations. Cattle Egrets’ regular movement patterns of partial migration, juvenile dispersal, and wandering could also still allow them to be transporting diseases across the landscape. Understanding modern movement using either genetic methods or GPS tracking could allow for a global understanding of the modern movement of

Cattle Egrets.

As Cattle Egrets continue to move and expand it is also important to understand what factors are facilitating this change. Climate change has been suggested as an important factor in facilitating modern change (Rodenhouse et al. 2008). Warming temperatures and increasing prey abundance in northern habitats could allow Cattle

Egrets’ breeding territory to expand northwards. In addition to climate change, the rapidly increasing human population causes an increase in food demand and further increase in intensive agricultural land use, which, as seen in Chapter 2, is significantly correlated to Cattle Egrets’ expansion.

Cattle Egrets are a widespread species with a global impact on wildlife, livestock, and humans. This study has provided new details about the relationship to Cattle

Egrets’ expansion and land use change as well as their potential for spreading diseases. Continual monitoring of Cattle Egrets’ modern movement and testing for

Haemosporidia across their global range as well as other diseases and ectoparasites could allow Cattle Egrets to be used as a model for climate change impacts, agricultural land use change, and global disease movement.

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BIOGRAPHICAL SKETCH

Shannon Patricia Moore received her Bachelor of Science in Wildlife Ecology and Conservation from the University of Florida in 2015. Prior to her graduation,

Shannon travelled to Eswatini as part of the UF in Eswatini study abroad program where she also assisted in sample collection for research on the conservation genetics of an isolate giraffe population. Shannon worked as a research technician in the Cuda

Lab at the University of Florida Entomology Department where she assisted with a study on the viability of weevils as biocontrol for the Brazilian peppertree. Shannon also volunteered in the Austin Lab at the University of Florida Department of Wildlife Ecology and Conservation where she assisted with population genetics of Eswatini rodents using microsatellites and co-authored a paper on the conservation genetics of an isolated giraffe population in Eswatini.

Upon graduation, Shannon worked as a research technician in the Wisely Lab in the Department of Wildlife Ecology and Conservation at the University of Florida. As part of the Wisely Lab, Shannon worked on a wide variety of projects including pathogens of cattle and wildlife in Florida, land use of mesocarnivores in Eswatini, pathogens of migratory birds, and Hemorrhagic Disease in Florida cervids. While working on her Master of Science degree, Shannon served as the outreach technician for the Cervidae Health Research Initiative and mentored two undergraduate students while conducting her research on the global expansion of Cattle Egrets and their role in the movement of avian Haemosporidia.

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