1 Behavior and Genetic Aspects of Boldness

Behavior and genetic aspects of boldness and aggression in urban coyotes (Canis latrans)

Dissertation

Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy

in the Graduate School of The Ohio State University

Ashley Wurth

Graduate Program in Environment and Natural Resources

The Ohio State University

2018

Dissertation Committee

Stanley Gehrt, Advisor

Elizabeth Marschall, Committee Member

Jeremy Bruskotter, Committee Member

Copyrighted by

Ashley Wurth

2018

Abstract

Animals exhibit behaviors that may differ based on factors such as learning, social cues, the environment, and genetics. Coyotes are a large carnivore that inhabit the spectrum from rural to highly developed landscapes and have a tumultuous relationship with humans. To increase coexistence and decrease human-coyote conflict, it is important to analyze how urbanization may influence coyote behavior and genetics, and ultimately, coyote relationships with humans. My dissertation examines coyote genetics and behavior across a variety of urbanization levels in Illinois, from rural to the urban core of

Chicago from 2014-2018. Through genotyping regions or specific SNPs associated with behavior (particularly boldness and aggression) in other species including the domestic dog, I first detected genetic polymorphisms in the coyote in these regions and then tested for differences in genotypic frequency based on landscape type. Through trapping coyotes in the Chicago Metropolitan Area, I studied behavioral actions across six contexts and tested for a relationship between boldness and aggression. Finally, I tested for correlations between behavior and genetic polymorphisms. I found 34 potential SNP locations in the dog and/or coyotes, with 11 SNPs only found in the coyote and 7 only found in the dog. In landscape analysis, 9 of the 21 polymorphic SNPs and 1 of 2 microsatellites had genotypic frequencies that varied based on urbanization level.

Coyotes exhibited varying behavioral actions within behavioral contexts with low ii boldness and aggression scores across all contexts and measures. For individuals that we were able to recapture (n = 14), boldness was repeatable but aggression had low repeatability and varied between contexts. Urban individuals were more likely to be bold and more likely to be aggressive. However, we did not find support for a single behavioral syndrome that underlies boldness and aggression, as there was no linear relationship between boldness and aggression. We found 9 SNPs and 1 microsatellite correlated with boldness and/or aggression measures, with 2 of these markers also correlated with behavior in dogs. Overall, coyotes had polymorphism within behavioral regions and exhibited various behaviors with frequencies that differed based on landscape type. Therefore, coyote boldness and aggression may be under genetic control with urban conditions acting as a selective pressure.

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Dedication

I want to dedicate this dissertation to my mom who has always loved and supported me no matter how far away I lived, how unique my career path, or how stressed I became. I could not have done this without her.

Acknowledgments

I would like to acknowledge all the support I received from my family, friends, fellow

SENR graduate students, and technicians at Max McGraw Wildlife Foundation. I would also like to thank my committee members for helping me to improve my dissertation and provide guidance when needed and Dr. Jean Dubach for teaching me new genetic techniques and mentoring me when experiments did not go as planned. Without all the hard work from lab mates and the many different project personnel and technicians, I could not have collected all the necessary data I needed for my dissertation. In particular,

I want to thank Andy Burmesch, Shane McKenzie, Abby-Gayle Prieur, Katie Robertson, and Lauren Ross who worked alongside me during almost all of my field work and who had valuable contributions when I was first designing and testing out my research protocols. Thank you to my friends and family for the personal support when I needed it the most as I could not have done it without you.

Vita

May 2009………………………………… Blue Valley West High School

2013…………………………………….... B.S. Fish, Wildlife and Conservation Biology

and B.S. Equine Science, Colorado State

University

2013 to present…………………………... Graduate Fellow, School of Environment and

Natural Resources,

Fields of Study

Major Field: Environment and Natural Resources

Table of Contents

Abstract ...... ii Dedication ...... iv Acknowledgments ...... v Vita ...... vi List of Tables ...... x List of Figures ...... xii Chapter 1. Detection of neurotransmitter and other behavioral gene regions in a carnivore with differentiation among urbanization levels ...... 1 Abstract ...... 1 Introduction ...... 2 Methods...... 5 Study Area and Subjects.- ...... 5 Classification.- ...... 7 Genetic Methods.- ...... 8 Statistical Analysis.- ...... 11 Results ...... 11 Discussion ...... 14 Literature Cited ...... 17 Chapter 2. Measuring coyote behavior in an urbanized landscape ...... 36 Abstract ...... 36 Introduction ...... 37 Coding and Comparing Classifications and Contexts.- ...... 44 Trap bias and Repeatability.- ...... 46 Results ...... 46 Comparisons across Scoring Measures and Contexts.- ...... 48 Repeatability.- ...... 50 Behavioral issues.- ...... 51 Discussion ...... 51 vii

Literature Cited ...... 58 Chapter 3: Does urbanization matter? Boldness and aggression across different urbanization levels ...... 74 Abstract ...... 74 Introduction ...... 75 Methods...... 79 Study location and subjects.- ...... 79 Behavior Tests.- ...... 80 Landscape classification.- ...... 82 Statistical analysis.- ...... 82 Results ...... 83 Behavior based on landscape type.- ...... 84 Discussion ...... 86 Literature Cited ...... 91 Chapter 4: Linking behavior and genes: Can genetics explain coyote behavior towards humans? ...... 108 Abstract ...... 108 Introduction ...... 109 Methods...... 112 Study Area and Subjects.- ...... 112 Genetics.- ...... 113 Behavior.- ...... 114 Analyses-...... 115 Results ...... 116 Discussion ...... 118 Literature Cited ...... 121 Bibliography ...... 138 Appendix A. The chromosome and gene name with their respective forward and reverse primer and the method used to genotype each coyote located within the Chicago Metropolitan Area or rural Illinois between 2014-2017...... 172 Appendix B. Coyote behavior sheet used during each capture to note behavior. The summary section was filled out independently be each observer to prevent bias...... 173 Appendix C. Protocol document for the manipulate hand test performed on each captured coyote...... 175 viii

Appendix D. The marker or chromosome name with their respective forward and reverse primer and the method used to genotype each coyote located within the Chicago Metropolitan Area between 2014-2017...... 176 Appendix E. Table of polymorphism location, novelty, and allele proportions for Chicago Metropolitan Area coyotes from 2014-2017...... 177

List of Tables

Table 1.1 Polymorphism locations, novelty, and alleles for dogs and coyotes. Novel SNPs and major and minor alleles were obtained from captured coyote samples in Illinois from

2014-2017...... 30

Table 1.2 P-values for comparisons among genotypic frequencies of coyotes captured during 2013-2017 living in different landscape types using Fisher’s exact test. For all significant comparisons(p<0.05), post-hoc pairwise comparisons were conducted between each landscape type and p-values were corrected using FDR Benjamini and

Hochberg method...... 32

Table 2.1 Mean behavioral scores and proportion of coyotes with each binary behavior classification in the Chicago Metropolitan Area between 2014-2018 for 137 coyotes. ... 69

Table 2.2 Spearman’s correlation (rs) (lower half of matrices) and p-values (top half of matrices) between contexts(C) and behavior scores of coyotes in the Chicago

Metropolitan Area between 2014-2018 (n = 151). Aggression Intensity was only measured from 2017-2018 (n = 151). Aggression Intensity was only measured from

2017-2018 (n = 53)...... 70

Table 2. 3 Spearman’s correlation (rs) (lower half of matrices) and p-values (top half of matrices) between contexts (C) and behavior intensity scores of eye contact and

x movement for coyotes in the Chicago Metropolitan Area between 2014-2018 (n = 151).

...... 71

Table 2.4 Repeatability (RM) values at different contexts and behaviors of coyotes recaptured in the Chicago Metropolitan Area between 2014-2018 (n=14). Context 5 and 6 were not included because there was no variability during first capture for these individuals...... 72

Table 3.1 Mean scores of each behavior measure by urbanization level in coyotes from

2014-2017 in the Chicago Metropolitan Area where C= context and the sum of the context scores is the Aggressive Comprehensive Scores...... 102

Table 3.2 GLM models of boldness, each aggression context (C), aggression comprehensive (AC), and aggression comprehensive_b (AC_b) for coyotes in the

Chicago Metropolitan Area between 2014-2018. AC_b included the variable boldness and boldness2 as dependent as dependent variables. All models were executed with

Natural CMA individuals as the reference. Any blanks indicate a variable that was not included in the model and aExp[B] is the exponentiated regression coefficient for quasi- poisson models...... 103

Table 4.1 Table of polymorphism location, behavior origin, and behavior model p-values for Chicago Metropolitan Area coyotes, where AC= Aggressive Comprehensive and

AB= Aggressive Binary model...... 134

Table 4.2 Allele frequency of Androgen Receptor gene Q1 and Q2 separated by sex for coyotes in the Chicago Metropolitan Area from 2014-2017...... 136

List of Figures

Figure 1.1 A) Approximate locations of coyotes captured throughout Illinois with a red star for the Chicago Metropolitan Area. B) Approximate capture locations of all coyotes caught within the Chicago Metropolitan Area between 2014-2017...... 34

Figure 1.2 Genotypic frequencies from Chicago Metropolitan Area and rural Illinois coyotes from 2014-2017 at all SNPs and microsatellites that varied significantly by landscape type. Listed as Chromosome: SNP number or microsatellite region where U=

Urban Core (n = 21), M= Matrix (n = 43), N= Natural CMA (n = 64), and R=Rural (n =

45)...... 35

Figure 2.1 Histograms of coyote aggression scores (0-4) in the Chicago Metropolitan

Area from 2014-2018 for each context (n = 137)...... 73

Figure 3.1 Example of annual home ranges (95% minimum convex polygons) for each landscape classification [Natural CMA (green), Matrix (blue), and Urban Core (red)] in three Chicago Metropolitan coyotes during study period 2014-2018...... 104

Figure 3.2 A) Proportion of coyotes with each binary classification type (neutral removed) in the Chicago Metropolitan Area from 2014-2017 where S=scared, B= bold,

A= aggressive, and N=not-aggressive (n=104). B) Fight/flee persistence length recorded from 2016-2017 where short= stopped before being restrained by person (n=44) and long= never stopped or only after being restrained with pole...... 105

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Figure 3.3 Predicted response of A) Boldness and B) Aggression Comprehensive scores based on landscape classification and sex (red=female, blue=male) of coyotes in the

Chicago Metropolitan Area from 2014-2017...... 106

Figure 3.4 Relationship between boldness and comprehensive aggression for each landscape type separately (color dotted lines) and together (black solid line) using the best fit Quasi-Poisson quadratic model for coyotes in the Chicago Metropolitan Area from 2014-2017. Individual scores are denoted as Urban Core (red triangles), Matrix

(gray circles), and Natural CMA (green squares)...... 107

Figure 4.1 Proportion of genotyped coyotes in the Chicago Metropolitan Area from 2014-

2017 with each A) Aggression Comprehensive score and B) Aggression Binary

Classification binned into 0= not aggressive and 1= aggressive...... 137

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Chapter 1. Detection of neurotransmitter and other behavioral gene regions in a carnivore

with differentiation among urbanization levels

Abstract

Several gene regions have been linked to behavior in a variety of species. Differences in behavior or genetics in wildlife can occur due to factors such as urbanization and environmental conditions. Furthermore, urban conditions may also select for certain behaviors that are under genetic control. Carnivores such as coyotes (Canis latrans) are increasingly present in city and suburban landscapes, pose a possible risk to people and pets, and are sometimes considered a nuisance by the general public. We genotyped coyotes across various urbanization landscape types at several gene and microsatellite regions that have been correlated with behavior, including genes DRD1, HTR1D, and

SLC6A1. Gene regions were generally selected due to the inclusion of specific single nucleotide polymorphisms (SNPs) that were correlated with bold or aggressive behavior in previous studies of domestic dogs. In the regions that were sequenced, we found 34 potential SNP locations in the dog and/or coyote, with 11 novel SNPs found in the coyote and 7 SNPs that were not polymorphic in the coyote but were in the dog. Of the 10 SNPs that were correlated with boldness or aggression in the dog, 4 were not polymorphic and

3 had a change in the major allele in the coyote. Seven of 21 polymorphic SNPs had 1

genotypic frequencies that were significantly different based on landscape type at p<0.05 and 2 were significant at 0.05

Introduction

Genetics, the environment, and learned behavior interact to shape behavior (Tierney

1986, Bakermans-Kranenburg and van Ijzendoorn 2011, Renn and Schumer 2013).

Personalities are individual behavior differences that are consistent over context and/or time (Réale et al. 2007), and publications on this subject in animals have been steadily increasing (Gosling 2008). Behavioral syndromes are suites of correlated behaviors within a given behavioral context or across different contexts (Sih et al. 2004).

Behavioral syndromes and personalities in animals have been documented across a wide variety of species (Verbeek et al. 1994, Coleman and Wilson 1998, Gosling 1998, 2001,

Dochtermann and Jenkins 2007). Aggression and other behaviors in both humans and non-human animals can be under the control of neural circuits (Nelson and Trainor

2007), neurotransmitters, neuropeptides, genes (Chen et al. 1994, Siever 2008), gene expression (Jørn Våge et al. 2010), and environmental conditions and social interactions

(Ditchkoff et al. 2006, Beisner et al. 2011, Flint et al. 2016). In addition, explicit types of behavior are generally linked to several genes and likely under polygenic control (Tecott and Barondes 1996).

There are many ways to investigate if and how genetics are linked to behavior.

Early studies performed genetic crossing experiments between lines of different 2

behaviors and examined offspring behavior (Riechert and Smith 1989). More recent studies used well-distributed sets of single nucleotide polymorphisms (SNPs) across a species genome (Jones et al. 2008), genome wide association studies (GWAS) (Zapata et al. 2016), genes associated with neurotransmitters (van den Berg et al. 2008, Inoue-

Murayama 2009), or analyzed gene expression levels (Dierick and Greenspan 2006), and then tested for correlations with different behaviors. For example, domestic dog (Canis lupus familiaris) studies have explored correlations in genetics and behavior among breeds (Jones et al. 2008, Zapata et al. 2016) and individuals (Ruefenacht et al. 2002,

Wan et al. 2013, Proskura et al. 2014). These studies support that various behaviors can be correlated with genetic markers, especially in certain regions, and provide a foundation for analyzing behavior-genetic linkages in other species.

Neurotransmitters dopamine and serotonin can affect mood, emotions, anxiety, impulsivity, and aggression (Winberg and Nilsson 1993, Winstanley et al. 2005, Hariri and Holmes 2006, Ruhé et al. 2007). In fact, research suggests that serotonin (5- hydroxytryptamine) may have the biggest influence on some types of aggression (Nelson and Chiavegatto 2001). The connection between serotonin and behavior varies depending on the type of behavior; for example, low serotonin levels are related to increased aggressive behavior but decreased boldness. Lower serotonin levels have been linked to aggressive behavior in humans (Birger et al. 2003), rhesus monkeys (Macaca mulatta;

Higley et al. 1992), and dogs, with the lowest levels in dogs that exhibited defensive aggressive behavior (Rosado et al. 2010b). An increase in 5-HT and other biogenic amines resulted in decreased aggression and increased boldness in spiders (DiRienzo et

al. 2015). Higher plasma levels of serotonin were associated with low fear and boldness in red junglefowl (Gallus gallus) (Agnvall et al. 2015). When exposed to a selective serotonin reuptake inhibitor (SSRI), some fish decreased boldness levels and also decreased consistency of behavior (Dzieweczynski et al. 2016).

In addition, genes that are related to dopamine and serotonin neurotransmitter functions, can also affect behavior such as aggression and boldness (Inoue-Murayama

2009, Veroude et al. 2016). A change in alleles in a monoamine oxidase A gene promoter region that impacts serotonin and dopamine oxidative deamination, influences aggressive behavior in monkeys (Newman et al. 2005). Variations in dopamine and serotonin related genes SLC1A2 (Takeuchi et al. 2009b), DRD1, HTR1D, HTR2C, SLC6A1 (Våge et al.

2010), and DRD4 (Proskura et al. 2014) have been correlated with aggressive behavior in the dog. The gene DRD4 has been linked to aggression and impulsivity in both humans and nonhuman species (Schmidt et al. 2002, Hejjas et al. 2007, Kang et al. 2008, Wan et al. 2013). The SMAD2 gene has been linked to excitability, along with body weight and size (Jones et al. 2008). Aggression can also be affected by androgens or estrogens. The

Androgen Receptor gene (AR) impacts aggressiveness in male Akitas (Konno et al.

2011) and male humans (Hurd et al. 2011) and testosterone has been linked to aggressiveness (Delville et al. 1996, Birger et al. 2003). Estrogen and their receptors regulate aggression in mice (Scordalakes and Rissman 2004).

Recent studies suggest a link between genetics, behavior, and urbanization.

Differences in genetics can occur based on urbanization and habitat type (Delaney et al.

2010, Munshi-South and Kharchenko 2010). Urbanization may also select for certain

behaviors that are under genetic control (Partecke et al. 2004). As coyotes are increasingly present in a gradient of urbanization levels, pose a possible risk to people and pets, and are sometimes considered a nuisance by the general public, it is important to determine if urbanization and genetics may influence coyote behavior. However, no research has genotyped or analyzed potential behavioral regions in the coyotes across different levels of urbanization. Therefore, we genotyped coyotes (Canis latrans) across a developmental landscape gradient at several gene and microsatellite regions that have been correlated with aggressive and/or bold behavior including genes DRD1, HTR1D, and SLC6A1. Many gene regions were selected due to the inclusion of specific SNPs that were correlated with bold or aggressive behavior in dogs in previous studies. Our objectives were to determine if coyotes exhibited polymorphism within these behavioral regions, if there were differences in these gene sequences between coyotes and dogs, and if there were differences in coyote genotypic frequencies based on landscape type.

Methods

Study Area and Subjects.-

Coyotes used in this study were captured in the Chicago Metropolitan Area (CMA) during 2014-2017 or in rural areas throughout Illinois during the 2016-2017 trapping season in November- January (Figure 1.1). The CMA is the 3rd most populated metropolitan area in the USA with just under 10 million people (U.S. Census Bureau

2016). Most CMA coyotes were captured and tracked within Cook County where landscape development spans from managed natural areas called forest preserves in the suburbs to heavily developed residential and industrial areas in the core of the city. In 5

1998, Cook County was composed of 33% urban, 21.3% residential without trees, 24.2% residential with trees, and the remaining 21.5% of forests, grasses, crops, water, or miscellaneous vegetation (Iverson and Cook 2000). Located within Cook County is the city of Chicago that is more urbanized and possesses less vegetation and fewer green areas, with 49.3% urban, 32.8% residential without trees, and 13.7% residential with trees, and the remaining 4.2% of forests, grasses, crops, water, or miscellaneous vegetation (Iverson and Cook 2000). In contrast, rural areas have higher percentages of forests, plains, agriculture, or other undeveloped lands.

CMA coyotes were captured opportunistically using cable restraint devices or

MB-550 footholds by project personnel mainly during the months of November-March as part of an ongoing long-term coyote research project that started in 2000. Traps were checked 1-2 times per day depending on location and captured coyotes were taken back to the processing facility where they were immobilized using Telazol (Fort Dodge

Animal Health, Iowa). Coyotes recaptured within 4 weeks were released immediately at the site. Hair, whisker, and blood samples were collected and biometrics, age, sex, reproductive condition, and ectoparasite presence were recorded. Blood was stored in

EDTA and frozen for storage until time of DNA extraction. All animals were given a unique ID, ear tags, and either a VHF radio collar (Advanced Telemetry Systems, Isanti,

MN, USA) or a GPS collar (Lotek, Newmarket, Ontario, Canada) and then released back at the initial site of capture within 12 hours of removal from the trap. All animals were trapped and processed under Ohio State University’s Institutional Animal Care and Use

Committee (IACUC 2003R0061). Rural coyote information on age, sex, weight, and

length, along with a frozen tongue sample for genetic analysis, was obtained from coyote carcasses provided by local trappers.

Classification.-

Radiolocations from CMA coyotes were obtained through triangulation by using program

LOCATE III (Pacer, Truro, Nova Scotia, Canada) in the Universe Transverse Mercator grid system using a truck mounted antennae or through direct visual observations using a

Global Positioning System if fitted with a VHF collar. Day locations were collected for each individual at minimum once a week. In addition, 1 location per hour for 5 hours was collected during the night once every other week. Locations were automatically obtained via satellite for animals fitted with a GPS collar but were also validated by triangulation and direct visual observations.

Home ranges were calculated using a 95% Minimum Convex Polygon (MCP) in the AdehabitatHR package (Calenge 2006a) in program R for animals with a minimum number of 30 locations. Habitat classifications were determined via The National Land

Cover Database (NLCD) in ArcMap 10. All levels of development (open, low, medium, and high) were combined to make a developed category. Designated forest preserves, water, grasslands, wooded areas, and other natural habitats were classified as natural.

Coyotes were classified as Natural CMA if >60% of their home range was natural in a suburban landscape, as Matrix if < 60% home range was natural in a suburban landscape, as Urban Core if the home range was within the city limits of Chicago, or as Rural if caught by trappers outside of any incorporated city limits.

Genetic Methods.-

DNA was extracted through blood samples using the MegaZorb DNA Mini-prep kit

(Promega, Madison, Wisconsin) or tongue (tissue) samples using the DNeasy blood and tissue kit (Qiagen, Los Angeles, California). Individuals were genotyped using three different methods depending on the region and size of interest: capillary electrophoresis to estimate fragment size, restriction fragment length polymorphisms (RFLPs), or sequencing. All individuals were genotyped at several markers or gene regions that were correlated with aggressive or bold behavior in published dog studies. In this study, 8 unique gene regions were selected to be genotyped on 7 different chromosomes

(Chromosome 2 [gene HTR1D], 4 [DRD1+ unknown gene], 7 [SMAD2], 17, 20

[SLC6A1], 22, and X [Androgen Receptor]).

For each region, a first polymerase chain reaction (PCR) amplification was performed using its unique forward and reverse primer (Appendix A) on a BioRad iCycler (Bio-Rad Laboratories, Hercules, California). A 12.5 µl PCR amplification containing 7 pmol of mixed forward and reverse primer, 40 ng of DNA, 0.2 mM dinucleotide triphosphate, 0.5 U of Taq polymerase, 1X reaction buffer,1.6–2.0 mM

MgCl2, and 18 Milli-Q H2O was used. For microsatellite analysis, the forward primer was fluorescently labeled. The following protocol was used: initial denaturation at 94˚C

(5 min), then 35 cycles of denaturation at 95˚C (40 sec), annealing temperature (45 seconds) and an extension at 72˚C (40 sec), and finally an extension of 72 ˚C (5 minutes).

Annealing temperatures were as follows: 60 ˚C for regions on chromosome 4, 7

(SMAD2), 17, and 22, 63 ˚C for HTR1D and SL6CA1, and 65 ˚C for Androgen

Receptors.

Amplified products for the microsatellites on Androgen Receptors (AR) Q1 and

Q2 (Maejima et al. 2005, Konno et al. 2011) were sized using a Beckman-Coulter CEQ

8000XL automated capillary electrophoresis system (Beckman-Coulter, Inc., Fullerton,

California) and a 400-base-pair internal size standard. Microsatellite products were validated by sequencing a subset of samples to determine the number of repeats and that the correct sequence was amplified.

Chromosome 4 and Chromosome 7 (gene SMAD2) SNPs from Jones et al.

(2008), were obtained through RFLP analysis using restriction enzymes MBoII (5 U/µl) and SSP1 (10 U/µl) respectively. PCR products were then restricted using 0.4µl enzyme,

18 Milli-Q H2O, and 4-5 µl PCR product for a final volume of 8 µl overnight at 37˚C.

Fragments were separated on a 3.5% agarose gel and visualized with ethidium bromide to determine genotype. Unclear bands were redone and 20% of RFLPs were reanalyzed using Sanger sequencing for validation.

Sanger sequencing and/or Next Generation Sequencing (NGS) was performed for regions on Chromosome 17 and 22 (Jones et al. 2008), and genes DRD1, HTR1D, and

SLC6A1 (Våge and Lingaas 2008, J. Våge et al. 2010). Each region was sequenced on both NGS and Sanger sequencing to validate that the same result and sequences were obtained. For Sanger sequencing, the GenomeLab DTCS Quick Start Kit (Beckman-

Coulter, Inc., Fullerton, California) standard protocol was followed. A PCR tube containing 25-100 fmol of the first PCR product, 2.0 µL (1.6pMol/µL), 2.0 µL 10X

sequencing reaction Buffer, 8.0 µL Quick Start Master Mix, and Milli-Q H2O to add up to a total volume of 20 µl was used and put into a BioRad iCycler. The protocol that was used was initial denaturation at 96˚C (1 min), then 30 cycles of denaturation at 96˚C (20 sec), annealing at 50 ˚C (20 seconds) and an extension at 60˚C (20 sec). This product was sequenced on a Beckman-Coulter CEQ 8000XL automated capillary electrophoresis system. Appropriate nucleotide(s) were recorded for each possible SNP location.

For NGS, each region was amplified using the same sequence specific primers as for sanger sequencing during the first PCR step, but with an Illumina sequencing adapter on both primers. A subsample of PCR products were analyzed on the Qubit for quality and size assurance. All amplified samples from the same individual were then pooled and a second PCR was performed to add dual-index barcodes to the amplicon targets. The final PCR products were purified using the Agencourt AMPure XP system (Beckman

Coulter) and pooled together in equimolar concentrations to create a final library ready for the Illumina MiSeq bench-top sequencer rendering 250 bp paired-end reads. Files were taken from the sequencer and analyzed on the public server usegalaxy.org (Afgan et al. 2016). Tools FASTQ Groomer (Blankenberg et al. 2010), Trimmomatic (Bolger et al.

2014) with average quality > 30, and Map with BWA-MEM (Li 2013) were used to process the data. BAM files were referenced to CANFAM 3.0 and visualized on

Integrative Genomics Viewer to find SNPs and record genotypes at each location

(Thorvaldsdóttir et al. 2013, Robinson et al. 2017).

Statistical Analysis.-

We recorded genotypes at all locations where polymorphism was recorded in the NCBI database for the dog and visualized all sequenced regions for SNPs that were novel to the coyote. We compared the number of repeats in the AR gene and SNP major and minor alleles differences between dogs and coyotes. We used Fisher’s exact tests with an alpha

= 0.05 and 0.10 to test for differences in frequencies of genotypes at polymorphic alleles by landscape classification. We used the same method to test for allele difference in the

AR gene by landscape classification but tested females and males separately, as the AR gene is located on the X chromosome. For all tests that were significant, multiple comparisons were performed using FDR Benjamini and Hochberg method (Benjamini and Hochberg 1995).

Results

Genetic analyses were conducted on 45 Rural coyotes (male = 24, female = 21) and 128

CMA coyotes (m = 78, f = 49). Of the 128 CMA coyotes, 64 were classified as Natural

CMA, 43 were Matrix, and 21 were Urban Core. Some individuals were not successfully genotyped at all regions. In the regions that were sequenced, we found 34 potential SNP locations in the dog and/or coyote, with 11 novel SNPs found in the coyote and 7 SNPs that were not polymorphic in the coyote but were in the dog (Table 1.1). Of the 10 SNPs that were correlated with boldness or aggression in the dog in the literature, 4 were not polymorphic and 3 differed in the major allele in coyotes.

Some SNP locations within the gene exhibited little to no polymorphism in the coyote and were excluded from further analysis or contained linked alleles that were then 11

combined for analysis. Gene DRD1 SNP location 1 and 2 exhibited no polymorphism after 28 individuals were genotyped and were therefore not included in further analysis.

DRD1 SNP location 4 (n = 78), HTR1D SNP location 9, 10, 11, (n = 152) and SLC6A1

SNP location 2 (n = 160) also exhibited no polymorphism. HTR1D SNP location 3 and 8

(n = 155) were linked genes with only one individual, coyote 868, being heterozygous

AG instead of homozygous GG at both locations. HTR1D SNP 1 and 4 (n = 154) were linked genes of CT or TC. Lastly, SNP region 1, 2, and 3 on Chromosome 22 (n = 167) were linked as either GCT or ATA on each strand.

Seven of the 21 polymorphic SNPs that were used in the landscape analysis had genotypes that varied significantly based on landscape type at p < 0.05 and 2 were significant at 0.05 < p < 0.10 (Table 1.2; Figure 1.2). For the 7 SNPs with p < 0.05, FDR

Benjamini and Hochberg method was then conducted. There was a difference between

Urban Core and Matrix populations at HTR1D SNP 5 (p = 0.075) and SLC6A1 SNP3 (p

= 0.009), a difference between Urban Core and Natural at SLC6A1 SNP3 (p = 0.012), a difference between Urban Core and Rural at SLC6A1 SNP 3 (p < 0.001), a difference between Matrix and Rural at HTR1D SNP 1 (p = 0.067), SLC6A1 SNP 1 (p = 0.042),

Chromosome 17 SNP 2 (p = 0.006) and 3 (p = 0.009), and a difference between Natural and Rural at HTR1D SNP 5 (p = 0.081). There was no difference between Matrix and

Natural populations after correction for multiple tests. Overall, the majority of differences occurred between animals in landscape types Matrix and Rural.

We detected 6 alleles in the Q1 region: Q1-11, Q1-12, Q1-13, Q1-14, Q1-15, and

Q1-16 alleles with 11, 12, 13, 14, 15, and 16 tandem repeats of CAG respectively. The

most common allele was Q1-13 in both females and males. The most common genotype in females was Q1-13/Q1-13 and the second most common was Q1-13/Q1-14. In a study of 30 dog breeds and 2 wolf species, 3 alleles were detected at 10, 11, and 12 repeats, with Q-10 and Q-11 being the most common and wolves missing Q1-12 (Maejima et al.

2005). The coyote has a larger number of repeats and a wider diversity of alleles than the domestic dog.

We detected 3 alleles in the Q2 region in coyotes: Q2-20, Q2-21, and Q2-22 alleles. The most common allele was Q2-21 and the rarest allele was Q2-22 in both males and females. The 2 most common genotypes in females were Q2-20/Q2-21 and Q2-

21/Q2-21. This is in comparison to the dog with 21-26 repeats and the wolf with 26-27 repeats (Maejima et al. 2005, Konno et al. 2011). All coyote nucleotide sequences also varied from the dog and wolf. The coyote Q2 sequence is CAG(8-

9)CAACAGCAA(CAG)6-7CAA(CAG)2 where Q2-20 repeats is 8/6, Q2-21 is 8/7 and Q2-

22 is 9/7 for the first and second set of CAG repeats respectively. Dog and wolf sequences were CAG(9-14)CAACAGCAA(CAG)6CAA(CAG)2 or Q2-27 modified sequence of CAG(16)CAACAGCAA(CAG)5CAA(CAG)2.

The Q2 region varied by landscape type in males (p = 0.008) but not females (p =

0.844 and p = 0.510 for allele and genotype frequency respectively; Table 1.2). After

FDR Benjamini and Hochberg method correction, there was a difference between Matrix and Rural (p = 0.009) and Natural CMA and Rural (p = 0.030). There was no difference between males (p = 0.770) or females (p = 0.248 for allelic and p = 0.874 for genotypic frequency) in the Q1 region.

Discussion

While overall sequences and many SNPs were similar between the dog and the coyote, we did find some differences in SNP presence/absence and in the number of androgen receptor gene repeats in the coyote compared to the dog. We also found some differences in the major and minor alleles between the coyote and dog. Canids are closely related but have different life history strategies and environmental pressures, which should result in behavioral regions having some variability between species. All regions that were sequenced were shown to be correlated with bold or aggressive behavior in prior studies of dogs and other species, suggesting that coyotes may also exhibit varying levels of boldness or aggression compared to congeneric species. A behavior can be context dependent (Coleman and Wilson 1998, Dammhahn and Almeling 2012) and controlled by different or many genetic regions (Takeuchi et al. 2009b). For example, an individual may possess different levels of aggression towards conspecifics versus other species and may display aggression for different reasons, such as fear, anxiety, possessiveness, dominance, or reactivity (van den Berg et al. 2003, Arata et al. 2014). Animal personalities have been linked to life history traits and fitness (Smith and Blumstein

2007, Biro and Stamps 2008); therefore, coyotes and dogs should differ in SNP presence/absence and in genotypic frequencies at behavioral regions as the more successful behavior may vary due to different environmental pressures or context.

We found a larger number of repeats in the Q1 region and a shorter and modified repeat sequence in the Q2 region compared to dogs (Shibuya et al. 1993, Maejima et al.

2005, Konno et al. 2011). In Akitas ( a large breed “working group” dog), an 14

aggressiveness score (combining items relating to dominance, defiance, moodiness, irritableness, and threatening or initiating fights with disliked people or other dogs) was correlated with a shorter number of repeats (Q2-23) in the Q2 region for males (Konno et al. 2011). Coyotes have a much shorter number of repeats than the domestic dog with 20-

22 repeats found and Q2-22 being the rarest allele. This may indicate that coyotes could display higher dominance, defiance, or aggressiveness towards conspecifics and/or people. Coyotes are highly territorial and territory holders experience increased survival and reproduction (Gese 2001). Higher territorial quality has also been linked to aggressive behavior in birds (Scales et al. 2013). Therefore, higher dominance or aggression levels may help individuals to obtain or defend territories and mates.

Our study found that males, but not females, exhibited a difference in Q2 allele frequencies depending on landscape type. Other studies have found that sex can affect the relationship between behavior and a gene (Kang et al. 2008), including for this region

(Konno et al. 2011). For example, while a genotype may be correlated with behavior in males, this might not occur in females. Males and females may benefit from different behavior (Dall 2004) and differences in female and male roles and hormones could influence the expression of the gene or exhibited behavior (Rosado et al. 2010a,

Dammhahn 2012).

The presence and absence of SNPs in serotonin and dopamine regions DRD1,

SLC6A1, and HTR1D are important to detect to create the foundation for future behavioral correlations studies. Links between genes that control such neurotransmitter regions and aggression have been found in humans (Siever 2008), monkeys (Newman et

al. 2005), and rodents (Cases et al. 1995, Veroude et al. 2016). Some behaviors may be problematic, such as overly bold or aggressive behavior, especially in larger bodied species. To properly manage wildlife, it is important to understand the genetic, along with environmental, basis to behavior.

Urbanization may lead to a shift in genotypic frequencies in a population as environmental conditions can influence or create feedbacks with and among behavior

(Ditchkoff et al. 2006), stress (Partecke et al. 2006, Sih 2011), and genetics (Mueller et al. 2013). We found differences in genotypic frequency based on landscape type at several SNPs located within behavioral regions. Previous studies have found increased boldness and/or aggression in urban landscapes (Parker and Nilon 2008, Evans et al.

2010, Lowry et al. 2013) and differences in behavior between habitats (Møller 2008,

Bókony et al. 2012). However, much of this research has been on birds or small mammals and not on larger carnivores.

To our knowledge, no other study has compared differences between coyote and dog sequences, analyzed carnivore genetics in behavioral regions, or analyzed differences in carnivore behavioral regions based on urbanization. Larger mammalian carnivores may differ in behavior from birds and small mammals based on landscape type in that they have a tumultuous relationship with humans, can be a perceived or real threat towards humans or pets, and require larger tracts of land. Thus, these carnivores must balance competing evolutionary forces, some of which demand bold and/or aggressive behavior in order to compete with conspecifics, and others that demand the opposite (i.e., bold or aggressive behavior are more likely to lead to death or injury from humans). As

many carnivores are increasingly in closer contact with humans and inhabiting cities

(Gehrt et al. 2010), it is important to understand how animal behavior and underlying genetics may change in urban areas. Detecting polymorphisms in behavioral regions or genes, particularly those related to serotonin or dopamine neurotransmitters, is the first step towards finding a relationship between behavior, environment, and genetics.

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Coyote SNP # Position SNP Major/ or or start of Novelty of Behavior Dog Minor Chromosome Gene Namea positionb SNPc origin alleled Allele 2 HTR1D SNP-1 76198905 Novel C* C/T^1 HTR1D SNP-2 76198952 Novel C* C/T HTR1D SNP-3 76198953 rs851456111 ‡ G/A G/A^2 HTR1D SNP-4 76198956 Novel T* T/C^1 HTR1D SNP-5 76199025 rs22791521 T/C C/T HTR1D SNP-6 76199027 rs850895241 C/T T/C HTR1D SNP-7 76199193 Novel G* G/T HTR1D SNP-8 76199267 rs851378220 G/A G/A^2 HTR1D SNP-9 76199364 rs852864217 G/A G* HTR1D SNP-10 76199400 rs850840197 C/T C* HTR1D SNP-11 76199438 rs851318122 T/C T* HTR1D SNP-12 76199482 Novel G* G/A HTR1D SNP-13 76199509 Novel C* C/T HTR1D SNP-14 76199525 rs22791523 ‡ G/A G/A HTR1D SNP-15 76199538 rs22791524 G/A G/A HTR1D SNP-16 76199577 rs852247328 G/A G/A HTR1D SNP-17 76199613 rs852716529 G/A G/A 4 DRD1 SNP-1 37551821 rs851192913 ‡ G/A G* DRD1 SNP-2 37551833 rs850646662 ‡ T/C C* DRD1 SNP-3 37552229 rs852331175 C/T C/T DRD1 SNP-4 37552277 rs852622318 ‡ C/T C* DRD1 SNP-5 37552406 Novel G* G/A 4 SNP-6 37590553 rs24057738 ¶ G/T T/G 7 SMAD2 SNP-1 43719549 rs24445718 ¶ A/G A/G 17 SNP-1 12505660 Novel A* A/C SNP-2 12505705 Novel C* C/T SNP-3 12505775 rs22508983 ¶ C/T C/T SNP-4 12505873 Novel G* G/A Continued

Table 1.1 Polymorphism locations, novelty, and alleles for dogs and coyotes. Novel SNPs

and major and minor alleles were obtained from captured coyote samples in Illinois from

2014-2017.

Table 1.1 Continued

Coyote SNP # Position or SNP Major/ or start of Novelty of Behavior Dog Minor Chromosome Gene Namea positionb SNPc origin alleled Allele 20 SLC6A1 SNP-1 7358401 rs853048122 C/T T/C SLC6A1 SNP-2 7358498 rs851337353 ‡ G/C C* SLC6A1 SNP-3 7358551 Novel G* G/T 22 SNP-1 22498919 rs23016304 ¶ G/A G/A^3 SNP-2 22498948 rs23016305 C/T C/T^3 SNP-3 22498991 rs23016306 T/A T/A^3 X AR Q1 51969947 § X AR Q2 51970322 § a Given SNP number from this study or named region for Q1 and Q2 b Position location of SNP or start of location of microsatellite region in CanFam3.0 NCBI database c Reference number of published SNPs or recorded as Novel d Many major/minor alleles are unpublished. Only alleles with a SNP behavior origin have alleles recorded as major/minor ¶ Jones et al 2008 § Konno et al 2011 and Maejima et al 2005 ‡ Våge et al 2010 ^ Linked polymorphisms within that chromosome with the number representing which positions are linked * Either no polymorphism recorded in CanFam or no polymorphism found in coyote sequences

Overall Urban Urban Urban Fisher Core- Core- Core- Matrix- Matrix- Natural- Locationa Testb Matrixc Naturalc Ruralc Naturalc Ruralc Ruralc 2:1 and 4 0.046 0.560 1.000 0.444 0.381 0.067 0.546 2:2 0.695 2:5 0.007 0.060 0.264 0.064 0.264 0.126 0.060 2:6 0.427 2:7 0.360 2:12 0.091 0.769 0.153 0.390 0.153 0.692 0.366 2:13 0.676 2:14 0.084 0.627 0.268 1.000 0.834 0.480 0.210 2:15 0.131 2:16 0.020 0.697 0.078 0.199 0.078 0.310 0.229 2:17 0.229 4:3 0.254 4:6 0.688 7:1 0.396 17:1 0.599 17:2 0.010 0.158 0.341 0.374 0.158 0.006 0.334 17:3 0.004 0.246 0.231 0.231 0.948 0.006 0.006 17:4 0.676 Continued

Hochberg method.

Table 1.2 Continued

Overall Urban Urban Urban Fisher Core- Core- Core- Matrix- Matrix- Natural- Locationa Testb Matrixc Naturalc Ruralc Naturalc Ruralc Ruralc 20:1 0.017 0.114 0.114 0.739 0.589 0.042 0.075 20:3 <0.001 0.006 0.006 <0.001 0.888 0.067 0.043 22:1,2, 3 0.937 X:Q1 f 0.257;0.874 X:Q2 f 0.844;0.510 X:Q1 m 0.77 X:Q2 m 0.008 0.51 0.523 0.125 0.645 0.004 0.012 a Location listed as chromosome: SNP number or named region b Fisher’s test p-values for comparison of genotypes among all 4 classification types: Rural, Natural, Matrix, and Urban Core. Q female regions were tested for differences between allelic and genotypic frequencies respectively c FDR Benjamini and Hochberg method adjusted p-value for each pairwise comparison to account for multiple post hoc tests f Female comparisons as Q regions were conducted separately for males and females m Male comparisons as Q regions were conducted separately for males and females

A B

Figure 1.1 A) Approximate locations of coyotes captured throughout Illinois with a red star for the Chicago Metropolitan Area. B)

Approximate capture locations of all coyotes caught within the Chicago Metropolitan Area between 2014-2017. 34

1.0 1.0 1.0 1.0 1.0 TC TT GG GG 0.8 0.8 0.8 0.8 0.8 TC GG 0.6 0.6 0.6 0.6 0.6 AG AG Chr 2:1 Chr 2:5 Chr CC Chr 2:12 Chr 2:14 Chr 2:16 Chr 0.4 0.4 0.4 0.4 0.4 CC 0.2 0.2 0.2 0.2 0.2 AA AA AG 0.0 0.0 0.0 0.0 0.0 U M N R U M N R U M N R U M N R U M N R 1.0 1.0 1.0 1.0 TT 276 TT TT TT TC 275 0.8 0.8 0.8 0.8 TC TG 274 0.6 0.6 0.6 0.6 TC 273 Chr 17:2 Chr 17:3 Chr 20:1 Chr 20:3 Chr 0.4 0.4 0.4 0.4 CC Males Chr X:Q2Chr Males CC 272 GG 0.2 0.2 0.2 0.2 271 CC 270 0.0 0.0 0.0 0.0 U M N R U M N R U M N R U M N R U M N R

Urban Core (n = 21), M= Matrix (n = 43), N= Natural CMA (n = 64), and R=Rural (n = 45). 35

Chapter 2. Measuring coyote behavior in an urbanized landscape

Abstract

Carnivores such as coyotes (Canis latrans) increasingly inhabit cities and suburban landscapes, pose a possible risk to people and pets, and can be considered a nuisance by the general public. Increased predator proximity to humans also elicits fear of predators acting boldly and/or aggressively towards humans. However, to our knowledge, no research studies quantify carnivore boldness and aggression towards humans in urban landscapes. We recorded and analyzed behavior of coyotes living within the Chicago

Metropolitan Area (CMA) to determine if coyotes exhibited varying behaviors, if behaviors were consistent across context and time, and to examine boldness and aggression levels. We found that CMA coyotes generally exhibited low boldness and aggression scores across all contexts and measures, though scores varied substantially between individuals. Further, we found that the same coyotes reliably exhibited bold behaviors, but aggressive behaviors had low repeatability and varied between contexts.

Behavior in contexts between the field (4 contexts) and lab (2) settings were not highly correlated within an individual. However, some behavior contexts were statistically correlated within a setting, albeit low to moderate. Less-aggressive individuals were more likely to be recaptured and on average aggression levels stayed the same or decreased between captures. Lastly, we found that all 3 measures of aggression were highly 36

correlated, indicating that individual rater scoring could be reliable but that scales were more valid than binary measures of aggression. Our results support that coyotes exhibit varied behaviors and that boldness may be a repeatable trait, while aggression may be context specific. Our research also suggests that location of testing is important and may result in different displayed behaviors as some coyotes that were aggressive in one setting

(i.e. field or lab) were not aggressive in the other setting. Lastly, a boldness-aggression syndrome was not supported as individuals were classified as both scared-aggressive and bold-aggressive.

Introduction

Differences in individual behavior have been observed in a variety of species with consistent individual behaviors called personality (Gosling 2001), temperament (Réale et al. 2007) or behavioral syndromes (Sih et al. 2004). Personalities in various animal species have been documented in both lab and field settings (Gosling 1998, Svartberg et al. 2005, Cote et al. 2011) and have been linked to adaptation and life history traits

(Wilson 1998, Adriaenssens and Johnsson 2011). Depending on how and what behavior is measured, behaviors such as boldness may (Ward et al. 2004), or may not (Coleman and Wilson 1998), be correlated between contexts. For example, bold behavior may be reliably reproduced within a behavioral context (e.g., across multiple observations of foraging) but very across different contexts (e.g., foraging vs. predation)(Šlipogor et al.

2016). When correlations occur between different personality traits, this is called a behavioral syndrome. For example, correlations can occur between behaviors such as activity level, exploratory behavior, dominance, foraging behavior, and/or risk taking 37

(Beauchamp 2000, van Oers et al. 2004a, Moule et al. 2015). Boldness and aggression have been positively correlated in several studies across a variety of wildlife species

(Huntingford 1976, Verbeek et al. 1996, Dingemanse and Réale 2005). However, the measures and wildlife populations used to quantify boldness or aggression may impact this relationship (Myers and Hyman 2016). Therefore, syndromes may only be present in certain contexts, with certain measures, or in certain populations of a species. For example, a bold-aggression behavioral syndromes may occur in a population when measuring boldness using alarm calls but not when measuring boldness using FID.

Wildlife populations have been increasing in urban areas where unique conditions impact wildlife in numerous ways (Ditchkoff et al. 2006, T. M. Newsome et al. 2015), such as changing activity levels or movements (George and Crooks 2006), dietary shifts

(Murray et al. 2015), and changes in reproductive timing (Eden 1985, Beck and Heinsohn

2006). These changes in behavior or environmental conditions can also impact survival

(Prange et al. 2003, Lehrer et al. 2012), fitness (Chamberlain et al. 2009, Teglhøj 2017), and body condition (Kark et al. 2007, Murphy et al. 2015) negatively or positively.

Lastly, these changing conditions can also impact behavior such as boldness, aggression, and tameness (Luniak 2004, Galbreath et al. 2014, Ducatez et al. 2017).

The coyote is a species common around suburban and city centers (Grinder and

Krausman 2001, Crooks 2002, Gehrt et al. 2011), usually taking the role of the top carnivore (Gompper 2002). Human-coyote conflict in these areas can range from visual nuisance complaints, to pet attacks, to rare human attacks (White and Gehrt 2009, Poessel et al. 2013) and the number of conflicts may vary based on region, landscape design, and

management (Poessel et al. 2017). While attacks on people in the Chicago Metropolitan

Area are rare, there have been attacks in other areas, such as California (Baker and Timm

1998).

To our knowledge, there has only been limited research measuring non-captive mammalian carnivore boldness or aggression. In urban areas, this is particularly important as larger human populations are in proximity to wildlife. Therefore, we recorded and analyzed the behavior of coyotes towards humans that were living within an urbanized landscape to determine if coyotes exhibited varying behaviors, if individual behaviors varied consistently across context and time, and to examine boldness and aggression levels. We hypothesized that the coyote would exhibit varying individual behaviors, vary in their levels of boldness and aggression, and that these measures would be correlated across contexts and time within an individual. To test these hypotheses, we quantified coyote boldness and aggression in an extreme urban-suburban gradient across several contexts in both a field and lab setting. For recaptured individuals, we also tested for repeatability of aggression and boldness.

Methods

Study location and subjects.-

Coyotes used in this study were captured from September 2014 to March 2018 as part of a long-term coyote monitoring project that started in 2000 in the Chicago Metropolitan

Area (CMA) (Gehrt et al. 2009). The CMA includes the city of Chicago, Illinois and its suburbs and is the 3rd most populated metropolitan area in the US with just under 10 million residents in 2016 (U.S. Census Bureau 2016). Paved road density is 6.11 km/km2

(Illinois Department of Transportation, Springfield, Illinois) but does not seem to be a barrier to movement or dispersal as many of our study coyotes regularly cross roads

(Gehrt et al. 2010). Most of our coyotes were captured and tracked within Cook County, but also were tracked in DuPage, Kane, Kendall, McHenry, and Will County. Coyotes >4 months old were captured using cable restraint devices or foothold traps in forest preserves or private land such as golf courses, cemeteries, and undeveloped lots with owner permission. Recaptured coyotes were immediately released without holding if recaptured within 4 weeks of previous capture. Behavioral bias based on trapping method was tested using Welch two sample t-tests. Traps were checked 1-2 times per day

(morning and evening) depending on location. Over the study period time frame, only 3 of 207 animals were found in a trap in the late afternoon/early evening checks. Coyotes were restrained, placed into separate 0.88 x 0.61 x 0.66 meter monkey squeeze cages

(Harford Metal Products Inc.), and then transported by truck to the lab facility where behavioral tests could be performed and immobilizations could be carefully monitored and controlled.

After arrival at the lab facility, 2 behavioral tests were performed. Once behavior tests were completed, animals were immobilized with an intramuscular injection of

Telazol (Fort Dodge Animal Health, Iowa). Each coyote was weighed, measured, sexed, and aged. Hair, whisker, and blood samples were collected as part of other ongoing research. Unmarked coyotes were given a unique ID and numbered plastic ear tags

(NASCO Farm & Ranch, Fort Atkinson, Wisconsin) and a VHF radio collar (Advanced

Telemetry Systems, Isanti, MN, USA) or a GPS collar (Lotek, Newmarket, Ontario,

Canada). Coyotes were classified as a pup (<1 year), a subadult (between 1 to < 2 years), or as an adult (2+) based on teeth, reproductive status, or known birth year. Once coyotes had recovered from immobilization, they were released at the initial capture site within

12 hours of removal from trap. Three out of 207 (1.45%) trapped coyotes died or were euthanized due to project-related factors during the time period of this study (2 trap related injuries and 1 possible heart attack or stress). Trapping and handling protocols were approved by Ohio State University’s Institutional Animal Care and Use Committee

(IACUC 2003R0061) and followed guidelines by the American Society of Mammalogists

(Sikes and the Animal Care and Use Committee of the American Society of

Mammalogists 2016).

Behavior Tests.-

Behavior was recorded in 6 different contexts: 4 field (including reaction to a restraint pole) and 2 lab via standardized behavior sheets (Appendix B and C). Care was taken to control factors that could impact coyote behavior as much as possible. Only 1 person was an active participant in all contexts in the field unless the safety of the coyote or person required additional help. Additional personnel remained at a distance and recorded the actions of the coyote with the help of the person who approached the coyote. Lab contexts were performed by the same person with additional observers remaining at a distance. As animals were followed until collar failure or mortality, we also recorded mortality and nuisance complaints to record any behavioral issues of coyotes in our study. Behavioral responses to stimuli have been measured in various ways including through Likert-style intensity or response scales (Svartberg and Forkman 2002, Mirkó et

al. 2012) or having an observer record the individual’s specific action (Ruefenacht et al.

2002). Both coding behaviors/actions as a certain score and having observers rate a trait

(e.g.- the aggressiveness of an individual) have been used in many studies and have been found to be reliable but have different challenges (Gosling 2001). In this study, we used both categorical coding of behaviors and response scales.

Field Contexts.-

At each of the 4 contexts in the field, the following categories were recorded: coyote movement, body language, body position, eye contact, ear position, tail position, mouth position, and vocalization to classify behavior. The 4 contexts were as follows: 1) when the person and coyote first spotted each other at a distance, 2) once the person arrived at the edge of the capture circle, 3) reaction to the restraint pole, and 4) once the coyote was restrained with restraint pole. The capture circle is the area in which the coyote can still freely move while trapped. The restraint pole is a circular plastic covered wire that can be adjusted to tighten around the coyote’s neck. During Context 3, only the reaction to the pole was recorded. Starting in 2016, the length of the fight/flight response was also recorded as: 0=never resisted, 1=stopped during initial walk towards coyote, 2=stopped once person approached edge of capture circle, 3=stopped once restrained, and 4=never stopped.

Lab Contexts.-

After transportation to the lab, coyotes were given a 15-minute adjustment period in the dark and quiet with a sheet covering the cage before further tests were performed. The 5th context consisted of a person slowly removing the sheet from the cage and then watching

the coyote as they walked back and forth in front of the cage and crouched down and stood up in front of the cage. The same categories as in the field were recorded: coyote movement, body language, body position, eye contact, ear position, tail position, mouth position, and vocalization.

Finally, the 6th context consisted of a manipulated behavior test using an artificial hand connected to the same person who performed the 5th context. This step was performed to test how a coyote would react if cornered and a human chose to approach the animal. Several studies have used an artificial hand that is extended by a pole and covered by a sleeve to safely mimic how a dog would react to a person’s hand (Netto and

Planta 1997, van den Berg et al. 2003), and has been found to be a reliable indicator of actual dog aggression towards people (Kroll et al. 2004). A blocking mechanism was first inserted into the back of the cage to prevent the door from opening all the way in case a coyote tried to lunge up or get out. This mechanism slightly protruded into the cage at the opposite end of where the hand was inserted. The door was then slid open enough for the hand to be slowly dropped into the cage. A timer was started once the hand entered the cage and after 15 seconds of holding the hand still, the hand was then slowly moved side to side for another 15 seconds before it was removed from the cage. The hand never deliberately touched or moved towards the coyote. All reactions from the time the blocking mechanism was inserted to the withdrawal of the hand were recorded. Actions towards the hand and experimenter and scales on fearfulness, aggression, and boldness during the hand test were recorded. All reactions in the lab were recorded via a hand-held video recorder by a separate person at the back of the lab.

Coding and Comparing Classifications and Contexts.-

Behavior for each recorded category in each context were recoded as an “intensity” scale where 0= least intensive/no action (Svartberg et al. 2005). Eye contact ranged from 0-2 and movement from 0-3. Aggression scores were calculated for each of the 6 contexts based on the following aggressive actions: 0=none, 1=present teeth some or vocalize some, 2= present teeth + vocalize some growl or constant bark, 3= actively baring teeth and/or actively growling, 4= biting/snapping motion, lunged or attacked. An Aggression

Comprehensive score (AC) was calculated by adding up all 6 aggression scores.

Each observer (average = 2.41, range = 1-4) in addition to aiding in recording the actions of the coyote as noted previously, also recorded separate classifications for each animal as one of the following categories: 1) scared but not aggressive, 2) scared and aggressive, 3) neutral, 4) bold but not aggressive, and 5) bold and aggressive. Shy-bold- aggressive categories were separated into boldness and aggression classifications for further analysis. Boldness Classification (BC) was coded as 0= scared/shy, 1=neutral, 2= bold. Aggression Binary (AB) was coded as 0=not aggressive, 1= aggressive. Starting in

2017, a 4-point (1-5) Aggression Intensity (AI) scale was also recorded by each observer where 1= never, 2= low intensity, 3= low intensity repeats, 4= high intensity/many signs, and 5= very/always aggressive. For this study, aggression towards humans was defined as a coyote projecting an intent to threaten and/or attack a person. Boldness was defined as a coyote projecting confidence, comfortableness or ease, and/or lack of fear around people.

For every individual, average boldness classification (BC), aggressive binary classification (AB), and aggression intensity scale (AI) were calculated from all observers. Deviations from the mean were calculated for each coyote by rater. After examining the deviation distributions of individuals with >2 raters, we removed outliers that approached the next score (i.e. >0.5 for 0 to 1 scale, >1 for a 0 to 2 scale, and >1 for a 0-4 scale. Krippendorff’s alpha was used to calculate reliability with all scores included and with outliers removed for comparison using package irr (Gamer et al. 2012).

To test for a relationship between binary aggression and boldness classifications, individuals were grouped into Aggressive (AB>0.5) or Not Aggressive (AB<0.5) and

Scared (BC<0.5) or Bold (BC>1.5) Individuals with scores not included in these values were removed from this analysis. Pearson’s Chi-squared test with Yates’ continuity correction was used to test for differences between the proportion of individuals that were rated as bold-aggressive v scared-aggressive and bold-aggressive v bold-not aggressive.

Rank order aggression correlations between contexts and among aggression comprehensive (AC), aggression intensity (AI), and aggression binary (AB) were tested by Spearman’s correlations. Aggression scores were also compared using Spearman’s correlation to determine consistency between measurements. Interpretations of correlations were: ±0.90-1.00 very high, ±0.70-.090 high, ±0.50-0.70 moderate, ±0.30-

0.50 low, ±0.00-0.30 little to none, with the sign indicating a positive or negative relationship (Hinkle et al. 2002).

Trap bias and Repeatability.-

Coyotes are difficult to recapture and all coyotes that were caught within the same trapping period (4 weeks) were immediately released. Therefore, we could measure repeatability for a small subsample of coyotes. For all recaptured individuals, Welch’s t- test was performed to determine if recaptured individuals were bolder or more aggressive than unrecaptured individuals. We calculated repeatability of the population (RM) using the rptR package (Stoffel et al. 2017) where RM= between individual variance/ (between individual variance + residual variance) where 0= low repeatability and 1= high repeatability. We also calculated 95% confidence intervals for all aggressive contexts, binary aggression, aggression comprehensive, and boldness. To compare repeatability with binary aggression scores (0-1); values were assigned to the closest value between (0,

0.5, and 1). A paired t-test was performed to determine if aggression or boldness changed between first and second capture.

Results

During Fall 2014-Spring 2018, 137 unique (151 total) coyotes (54 females and 83 males), were captured, completed all behavioral contexts, and given AC and AB scores within the CMA. Fight/Flee (FF) and AI scores were also assigned to 53 (44 previously uncaptured) coyotes. There was no difference in AB (t = 0.484, df = 41.775, p = 0.6309),

AI (t = -0.11018, df = 10.788, p = 0.9143), or BC (t = 0.70659, df = 41.139, p = 0.4838) between individuals caught in snare and footholds but there was a difference in AC (t =

2.15752, df = 49.394, p = 0.03443). Foothold individuals had a mean AC score 1.741 points higher than individuals caught in snares. This indicates that while individuals in 46

may have a slightly more aggressive action in a context if caught in a foothold, the overall aggression intensity and classification did not differ.

For all aggression and boldness classifications, coyotes exhibited low scores.

Coyotes were more likely to be classified as not aggressive and not bold (Table 2.1). AC scores theoretically could range from 0-24 with higher scores denoting more aggressive actions. AC scores were low (mean = 5.336; actual range = 0-19) and AI scores (1-5 scale) for the subset of 44 unique coyotes were also low (mean = 2.057; mode = 1), where a 2 indicated low intensity single aggressive action such as presenting teeth once

(Table 2.1). The highest mean aggressive score was during Context 3: Reaction to stick, followed by Context 2: Capture circle, while all other contexts had a mean score = 0 (no aggressive action) (Table 2.1; Figure 2.1).

For length of fight/flee persistence, 18% (n = 8 of 44) did not completely submit after being restrained by the pole, and 34% submitted after being restrained by the pole.

Only 5 out of 137 first-captured coyotes (3.65%) bit the fake arm and an additional 6 coyotes bared teeth at the arm. No other individuals displayed aggressive actions towards the arm. Lastly, many animals exhibited extreme submissive behavior (cowering and/or tail tucked) in the field during Context 2 (40.91%) and 4 (59.09%). Submissive behavior was not noted in Context 3: Restraint pole and Context 1. While there was a minimal trend towards bolder and more aggressive males, only AB was significant (t = -2.8428, df

= 127.08, p = 0.005) and the mean difference was minimal (0.204) with both sex average scores < 0.5.

Animals were binned into the following categories: aggressive/bold, aggressive/scared, nonaggressive/bold, and nonaggressive/scared and all combinations were present. Most individuals were classified as nonaggressive/scared and the least number of individuals were classified as aggressive/bold (Table 2.1). There was no difference between the proportion of individuals that were rated as aggressive/bold v aggressive/scared or aggressive/bold v nonaggressive/bold (c2= 0.016334, df = 1, p =

0.8983).

Comparisons across Scoring Measures and Contexts.-

For all animals that were captured and completed all behavioral contexts, Krippendorrf’s alpha was used to determine the reliability between observers. Aggression binary classifications (AB) for 151 subjects had a Krippendorff’s alpha of 0.684 without removal of raters and 0.887 with removal of 16 out of 367 ratings that were >0.50 away from the mean. BC had a Krippendorff’s alpha of 0.665 without removal of raters and

0.802 with removal of 10 out of 367 ratings that were >1 away from the mean.

Aggression intensity (AI) (1-5 scale) for 52 subjects had a Krippendorff’s alpha of 0.594 without removal of raters and a Krippendorff’s alpha of 0.675 with removal of only 3 out of 132 ratings were >1 away from the mean.

For aggression scores that were combined to create the Aggression

Comprehensive (AC) from all 151 coyotes, little to no correlation was found between

Context 1: Field Approach and all other contexts (Table 2.2). Context 2: Capture Circle had moderate correlation with 3: Restraint Pole, and low correlation to 4: After restrained. Context 4 had low correlation to 2 and 3. Context 4: Lab cage and 5: Artificial

Arm had low to no correlation with any other context but were most correlated with each other (rp = 0.46). All other comparisons were little to none based on Hinkle et al. 2002 standards. AC was mainly driven by Context 2 (0.72), 3 (0.79), and 4 (0.61).

All 3 aggression measurements (AI, AC, AB) and aggression scores at each context were gathered on 53 coyotes. Aggression binary scores without (AB) and with removal (ABR) of outlying ratings were compared to all other measurements. High correlation (> 0.90) was found between AI and all other measures (AC, AB, ABR) and moderate correlation between AC and AB/ABR (Table 2.2). Correlations to AI and AC were minimally higher with AB than with ABR and AB and ABR were correlated at

0.96.

With the reduced, first-captured individual’s dataset (n=44), AI had high correlation with the coyote’s reaction to the restraint pole (0.70) and low correlation with all the other contexts (0.31-0.48). Using the same 44 individuals, AB, ABR, and AC showed similar patterns as the full dataset with AB/ABR moderate correlation with

Context 2 (0.55/0.53) and 3 (0.62/0.54), low correlation with 5 (0.4/0.38) and 6

(0.45/0.5), and none with the rest. AC was mainly driven by Context 2 (0.71), 3 (0.86), and 4 (0.64).

For movement intensity field contexts, Context 2: Capture circle and 4: After restrained had a significant (but low) correlation (rp = 0.21, p = 0.015). Context 1 and 2

(rp =0.04) and 1 and 4 (rp =0.030) were not significant. Eye intensity actions were compared between Context 1, 2, 4, 5, and 6. Eye contact correlations varied between contexts with little to no correlations between Context 6 and Context 1(RM= 0.06) and

Context 2 (RM= 0.13). Eye correlations were most correlated within lab or within field contexts (Table 2.3).

Repeatability.-

We recaptured and repeated behavioral observations and manipulation tests on 15 individuals. Recaptured individuals had lower aggressive comprehensive scores (t =

2.084, df = 46.016, p = 0.043) but did not differ in boldness scores (t = -0.220, df =

38.119, p = 0.827) compared to the entire population. Boldness scores showed high repeatability (RM = 0.658; Table 2.4) and did not change between first and second capture

(t = 1.2041, df = 13, p = 0.25).

For almost all individuals and contexts, aggressive scores remained the same or decreased. Aggression comprehensive score repeatability was fair (RM = 0.598; Table

2.4) and decreased by a mean of 1.93 points (t = 2.4897, df = 14, p = 0.02613) between first and second capture. Aggression binary score repeatability was low (RM = 0.278;

Table 2.4) and there was no difference in overall aggression binary scores (t = 0.71478, df

=13, p = 0.4874). All aggression binary scores remained the same or decreased except for one case: ID 854. Furthermore, only 3 individuals increased at least one aggression context score by more than 1 point: ID 965, ID 977 and 854. For example, coyote ID 965 elevated aggression in Context 3: Restraint pole, but was the same or less in all other contexts.

For all recaptured individuals, the first score of Lab: Context 5 and Context 6 was

0, therefore repeatability was not estimated. However, two individuals (ID 854 and 977) increased aggression in Context 5 and/or 6. While 854 was more subdued in the field for

the second capture, he had increased aggression in the both lab contexts including biting the fake hand. The only individual to increase comprehensive aggression score >1 was ID

977. This individual had higher comprehensive aggression (6 and then 9) compared to the rest of the population and the second higher aggressive score was mainly due to Context

6: Artificial hand. All remaining individuals and contexts either stayed the same aggression score or decreased.

Behavioral issues.-

Seven of the 137 (5.11%) unique coyotes used in this study were reported as nuisances with complaints ranging from being visual (n = 2), acting sick (n = 4), to acting aggressively (n = 1). All of these animals except 1 were located within residential suburban areas (n = 4) or the urban core of Chicago (n = 2). The one aggressive individual was hazed and 1 sick coyote was lethally removed. In addition to the 7 reported nuisances, 2 coyotes were lethally removed due to being present on airport property.

Discussion

We found that coyotes living within the CMA were most likely to be classified as scared and not aggressive, all measures indicated population level averages of low boldness and low aggression, and that correlations varied between behavior measures, contexts, and recaptures. In birds, urban populations tend to be more aggressive and bold (Miranda et al. 2013) and may exhibit decreased wariness towards human approach (Møller 2008,

Kitchen et al. 2010). Being bold and/or aggressive may be beneficial for coping with urban environments, using anthropogenic resources, or defending territories (Lowry et al. 51

2011, Hardman and Dalesman 2018). In song sparrows (Melospiza melodia), individuals with increased aggression occupied historically better nesting territories (Scales et al.

2013), and urban areas may have smaller areas of high quality habitat. However, most of the studies that measure aggression do not measure aggression towards humans, but rather towards conspecifics and/or other wildlife species (territoriality, speaker playback approach) and do not study larger carnivores (Evans et al. 2010, Scales et al. 2013,

Bhardwaj et al. 2015). Carnivore aggression or boldness (decreased wariness) towards humans could have high risk with negative consequences such as lethal removal or hazing and little to no reward, which may promote decreased aggression and boldness.

Behaviors may also be context-specific and therefore individuals may increase behavior where benefits are high but less where benefits may be low. Fish change boldness levels depending on experience, environmental conditions, and mates (Conrad et al. 2011). While coyotes are generally less bold towards humans in our tested contexts where benefits may be low, they may more readily approach a novel stimulus or a person with food. Correlations between behavior during handling and in the field in Big Horn

Sheep were mostly insignificant and weak (Réale et al. 2000) and we found particularly low correlations between field and lab contexts in coyotes. For example, one coyote showed no signs of aggression in the field but when brought back to the lab continuously bared teeth and growled, snapped at the experimenter, and bit the hand. Another coyote displayed high aggressive actions in the field, including lunging at the field personnel, but was docile once brought back to the lab. Aggression comprehensive scores were mostly driven by coyote’s scores in Context 3: Restraint Pole, followed by Context 2:

Capture circle and Context 4: After restrained. The highest aggression scores that were found in the majority of individuals were in these 3 contexts. Furthermore, the only average population aggression score over 0 was Context 2 and 3, which were contexts with the highest threat potential by humans in their natural environment and may be more likely to initiate a flight or fight response. Overall, we captured more individuals rated as nonaggressive/scared than any other category and had very few nuisance cases.

Trapability of individuals has been associated with personality for various species

(Biro and Dingemanse 2009, Merrick and Koprowski 2017). We used two different trap methods to capture individuals which could impact personality: cable restraints where individuals walk through the trap unsuspectingly and footholds where individuals purposely approach and investigate the trap area. However, we found no difference in boldness or between most measures of aggression based on trap type. While it is possible that scared/shy individuals may be more likely to be captured, many studies have found that bold individuals are more likely to be captured (Wilson et al. 1993, Carter et al.

2012). We found that boldness did not differ between recaptured and non-recaptured individuals and that boldness in recaptured individuals remained consistent. Bighorn sheep (Ovis canadensis) boldness was also highly consistent between repeated measures

(Réale et al. 2000). We did find that aggression generally decreased or remained the same at second capture and less aggressive individuals were more likely to be recaptured.

Decreased aggression could have been a result of learned behavior or due to the capture process. In electro-fished trout, individuals decreased conspecific aggression after being captured even though most other behaviors were unchanged or resumed normal activity

within a few hours (Mesa and Schreck 1989). Other species can be aggressive in traps

(Parker et al. 2008). Therefore, it is more probable that the population consists of individuals that are less bold and potentially less aggressive if the intitial trapping process was more likely to elicit an aggressive response.

The presence of aggression in both scared and bold individuals suggests that boldness and aggression towards humans is not a behavioral syndrome or genetically linked in this context. Both abnormally high or low anxiety (fear) can result in an increased aggression response (Neumann 2010). In dogs, a lower threshold for behaving aggressively was present in scared or anxious animals (Reisner 2003). Another possibility is that boldness and aggression may be linked in coyotes using other context measures such as behavior towards conspecifics. In song sparrows, the context influenced the relationship between boldness and aggression (Myers and Hyman 2016). Environmental conditions may also lead to a changing relationship between boldness and aggression

(Bell and Sih 2007) and urban condition may lead to a syndrome no longer being present

(Scales et al. 2011, Hardman and Dalesman 2018).

Although we had a low sample size due to difficulty of recapturing coyotes, we found that boldness had high repeatability, but that aggression diminished or stayed the same in most cases. Repeatability of behaviors may be diminished in urban areas

(Hardman and Dalesman 2018), where greater flexibility or learning may be required.

Variability in aggression or boldness affecting fitness and survival may maintain variation in personality in a population (Boon et al. 2008, Dammhahn 2012) or may result in individual plasticity rather than consistency. While most individuals remained

relatively consistent or decreased aggressive actions in every context, 2 individuals increased aggression >1 point and both occurred in the lab context. The increase in aggression for these individuals could have been due to feeding by humans (Flint et al.

2016), resulting in decreased wariness or increased aggression to compete for a clumped reosurce, a change in environmental conditions (Basquill and Grant 1998), resource availability, or genetics. One of these coyotes, ID 854, changed territories from a nature preserve and surrounding matrix area to almost solely inhabiting a golf course where he was fed. It is also important to note that this individual became an aggressive nuisance animal after residing on the golf course. Aggression and boldness have been linked to genes in the other species (Dierick and Greenspan 2006, van Oers and Mueller 2010,

Veroude et al. 2016), including canids (van den Berg et al. 2003, J. Våge et al. 2010).

Gene expression can also impact behavior and can be meditated or increased due to environmental factors (Saetre et al. 2004, Jørn Våge et al. 2010, Tung et al. 2012).

Therefore, the shift in home range composition or environmental factors could have provided the conditions for the aggressive gene to be expressed.

In the future, it may be useful for studies to calculate aggression scales separately for different contexts, especially under unique conditions or settings (i.e.- field v lab) as past studies have suggested that personality or behavior can be specific to condition

(Coleman and Wilson 1998, Réale et al. 2000). In our study, lab contexts were more highly correlated with each other (r = 0.46) and some of the field contexts were more highly correlated with each other (Context 2, 3, and 4). The difference between field and lab settings could also account for the differences between rater scores if the 3rd rater did

not see the coyote in both settings. Our study supports that using one measure of a personality trait may incorrectly label a personality trait or animal (Stamps and Biro

2016), as different conditions may elicit different responses. Future studies should analyze coyote behavior in other contexts and compare to the behavior during trapping.

We found that binary aggression scores were not as accurate and were too narrow compared to aggression scales. While reliability according to Krippendorff’s alpha was increased when outliers were removed, binary aggression scores were more highly correlated with other aggression scores when no outliers were removed. This suggests that binary aggression scores are not accurate enough to describe individuals and that differences in rater scores usually occurred when individuals displayed low level aggressive signs. Individuals are not “aggressive” vs “not aggressive”, but rather display a range of intensity of aggressive signs. Higher correlations between aggression comprehensive scores and aggression scales compared to binary aggression classifications support that individual aggression is a more reliable as a continuous variable. Aggression is a continuum and binary 0 or 1 aggression classifications led to mismatches between rater scores, especially when coyotes exhibited few or low signs of aggression and did not account for the varying levels of aggression. Boldness and aggression should be collected as a scale in future studies using a 5-7 Point scale to better account for variability within a trait and test for correlations between individuals, as has been used in other studies quantifying behavior (Hsu and Serpell 2003, Svartberg 2005,

Mirkó et al. 2012).

Understanding the mechanisms behind boldness and aggression is crucial towards mitigating human-coyote conflicts. We provided a baseline of measuring aggression and boldness of coyotes towards humans that could be quantified and used to determine actual aggressive responses and the extent to which they were elicited in an urban population. We identified variation in bold/aggressive behavior in a coyote population, and determined that, on average, coyotes in the CMA exhibited low boldness and aggression. However, our results indicate that coyotes are more likely to act aggressively when scared and behaving defensively. Coyotes may also adapt to situations and change their behavior accordingly, by reducing or enhancing a behavior. Therefore, people have the potential to influence and prevent human-coyote conflict by their actions. Human behavior such as feeding, habituation, and cornering of wildlife may elicit negative aggressive responses from carnivores. Further research on how people, urban conditions, and genetics affect wildlife behavior are important to prevent future conflict of species dwelling within developed landscapes.

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Mean Standard Error Range Proportion Boldness Classification 0.646 0.067 0-2 Aggression Binary 0.333 0.037 0-1 Aggression Comprehensive 5.336 0.368 0-24 -Context 1: Field Approach 0.000 0.085 0-4 -Context 2: Capture Circle 1.000 0.124 0-4 -Context 3: Pole 2.000 0.161 0, 2, 4 -Context 4: Restrained 0.000 0.115 0-4 -Context 5: Lab Cage 0.000 0.053 0-4 -Context 6: Arm Test 0.000 0.095 0-4 Aggression Intensity 2.057 0.152 1-5 [n=44] Aggressive/Scared 0.272 Aggressive/Bold 0.107 Nonaggressive/Bold 0.155 Nonaggressive/Scared 0.466

Table 2.1 Mean behavioral scores and proportion of coyotes with each binary behavior classification in the Chicago Metropolitan Area between 2014-2018 for 137 coyotes.

C1 C2 C3 C4 C5 C6 AC AB ABR AI

Context 1: Field Approach 0.0002 0.0680 0.0844 0.7615 0.5774 0.0000 0.1301 0.3192 0.0230 Context 2: Capture Circle 0.30 0.0000 0.0000 0.4056 0.4925 0.0000 0.0000 0.0000 0.0020 Context 3: Pole 0.15 0.52 0.0000 0.2693 0.0622 0.0000 0.0000 0.0000 0.0000 Context 4: Restrained 0.14 0.32 0.38 0.1394 0.0440 0.0000 0.0004 0.0005 0.0003 Context 5: Lab Cage 0.02 0.07 0.09 0.12 0.0000 0.0001 0.0001 0.0000 0.0044 Context 6: Arm -0.05 0.06 0.15 0.16 0.46 0.0000 0.0000 0.0000 0.0005 Aggression Comprehensive (AC) 0.40 0.72 0.79 0.61 0.31 0.42 0.0000 0.0000 0.0000 Binary Aggression (AB) 0.12 0.44 0.48 0.28 0.30 0.42 0.66 0.0000 0.0000 Binary Aggression Reduced (ABR) 0.08 0.45 0.45 0.28 0.31 0.46 0.62 0.96 0.0000 Aggression Intensity (AI) [n=53] 0.31 0.42 0.70 0.48 0.38 0.46 0.75 0.75 0.72

Table 2.2 Spearman’s correlation (rs) (lower half of matrices) and p-values (top half of matrices) between contexts(C) and behavior scores of coyotes in the Chicago Metropolitan Area between 2014-2018 (n = 151). Aggression Intensity was only measured from

2017-2018 (n = 151). Aggression Intensity was only measured from 2017-2018 (n = 53). 70

Eye Contact Movement

C1 C2 C4 C5 C6 C1 C2 C4 C5

Context 1: Field Approach 0.000 0.0585 0.0711 0.4616 0.6509 0.7564 0.3101 Context 2: Capture Circle 0.34 0.0000 0.0534 0.1506 0.6509 0.0147 0.7835 Context 4: Restrained 0.16 0.48 0.0000 0.0002 0.7564 0.0147 0.0303 Context 5: Lab Cage 0.16 0.17 0.36 0.0000 0.3101 0.7835 0.0303 Context 6: Arm 0.06 0.13 0.32 0.47

Table 2. 3 Spearman’s correlation (rs) (lower half of matrices) and p-values (top half of matrices) between contexts (C) and behavior intensity scores of eye contact and movement for coyotes in the Chicago Metropolitan Area between 2014-2018 (n = 151).

Behavior/Context RM s.e.m 95% CI [lower, upper] P-value Context 1: Field Approach 0.661 0.156 [0.28, 0.86] 0.002 Context 2: Capture Circle 0.126 0.18 [0.00, 0.58] 0.361 Context 3: Pole 0.378 0.207 [0.00, 0.74] 0.082 Context 4: Restrained 0.237 0.197 [0.00, 0.64] 0.212 Binary Aggression 0.278 0.215 [0.00, 0.71] 0.170 Boldness Classification 0.658 0.166 [0.24, 0.87] 0.003

Context 1:Field Approach Context 2:Capture Circle Context 3:Pole 120 120 120 100 100 100 80 80 80 60 60 60 Count 40 40 40 20 20 20 0 0 0

0 1 2 3 4 0 1 2 3 4 0 2 4

Aggression Score

Context 4:Restrained Context 5:Lab Cage Context 6:Arm Test 120 120 120 100 100 100 80 80 80 60 60 60 Count 40 40 40 20 20 20 0 0 0

0 1 2 3 4 0 1 3 4 0 1 2 3 4

Aggression Score

Figure 2.1 Histograms of coyote aggression scores (0-4) in the Chicago Metropolitan

Area from 2014-2018 for each context (n = 137).

Chapter 3: Does urbanization matter? Boldness and aggression across different

urbanization levels

Abstract

Development, heavily trafficked road networks, varying food availabilities, and human presence may cause species to alter their behavior to survive in an urban landscape.

However, although predators may react differently than prey due to life history strategies and interactions with people, research on behavioral differences of predators in urban ecosystems is lacking. Coyotes (Canis latrans) are one carnivore that commonly inhabits city and suburban landscapes in North America. One concern with increased carnivore population sizes in closer proximity to humans is that wildlife could become bolder or more aggressive in urban areas, increasing the risk of human-carnivore conflict. We analyzed coyote boldness and aggression towards humans across an urbanization gradient in the Chicago Metropolitan Area (CMA) to test for differences in behavior based on landscape type. We further tested for a boldness-aggression syndrome and analyzed each context separately to determine whether context influenced aggressive action based on landscape type. We found that coyotes living within the most highly developed landscape, the urban core, were more aggressive and bolder than coyotes living within the more natural areas of the suburbs as well as the suburban matrix. However, we did not find support for a bold-aggressive syndrome. For all field contexts, there was a trend of increased aggression and boldness from matrix (suburban), to natural CMA

(suburban), to urban core. Overall, there were low aggression and boldness rates, and

only 1 individual was reported as acting aggressively towards the general public. Our results support the idea that urbanization can impact coyote behavior towards humans in certain contexts but that aggression can arise from both bold and scared individuals.

Introduction

Urban areas possess unique conditions for wildlife such as increased road density, decreased natural landscape, anthropogenic resources, and the potential for higher levels of interactions with humans. These urban conditions may impact both basal and acute stress levels but in various ways. For example, urban dwelling great tits (Parus major) show an increased stress response compared to forested dwelling birds when being handled (Torné-Noguera et al. 2014). Urban and forest dwelling European blackbirds

(Turdus merula) that were taken as nestlings and raised in captivity had similar baseline corticosteroid levels, but during some seasons, urban birds had lower acute corticosteroid stress during handling (Partecke et al. 2006). In contrast, urban Abert’s Towhee

(Melozone aberti) had lower initial plasma corticosterone (CORT) and lower plasma testosterone, but the same stress-induced CORT levels (Davies et al. 2016). Lastly, expression of stress-linked genes was higher in urban birds, suggesting that urban populations had more experience with stressful situations (Watson et al. 2017).

Animals may attempt to avoid or adapt to urban stressors by modifying movement patterns (Prange et al. 2004), avoiding roads (Dickson et al. 2005, Kertson et al. 2011), utilizing railway corridors (Adkins and Stott 1998; Gehrt unpublished data), or changing their diet (S. D. Newsome et al. 2015, T. M. Newsome et al. 2015). Variation in behavior may also increase in urban areas, even if average behaviors of populations remain similar 75

(Lehrer et al. 2012). Some species select for anthropogenic structures or resources (Breck et al. 2009, Jameson and Willis 2014), while others may avoid urban areas (Ordeñana et al. 2010). Lastly, some species have become habituated to people (Thompson and

Henderson 1998, Kitchen et al. 2010).

Urban conditions and stressors may also affect animal behavior or personalities.

One major concern is that urban conditions may select for bolder or more aggressive wildlife, particularly in carnivores. Behavioral differences in boldness, aggression, and exploratory behavior between animals living in different urbanization levels has been tested, but mainly in birds (Bókony et al. 2012, Miranda et al. 2013). Some researchers speculate that increased boldness may allow individuals to take advantage of urban resources (Short and Petren 2008, Lowry et al. 2013) and that increased proximity or density of wildlife due to clumped resources in urban environments (Fedriani et al. 2001,

Prange et al. 2004) may lead to increased intra-specific aggression (Flint et al. 2016), resulting in bolder and aggressive individuals. Birds in urban areas are bolder and/or have higher levels of territorial aggression (Evans et al. 2010, Hardman and Dalesman 2018) or even higher aggression towards humans (Galbreath et al. 2014). These behavioral responses may vary based on species, study, season, and landscape characteristics. For example, urban squirrels had shorter flight initiation distances (Uchida et al. 2016), while urban spiders showed no difference in startle response/boldness compared to rural individuals (Halpin and Johnson 2014).

Boldness can have different definitions or testing measurements leading to varied results. Some studies have shown that escape distance measurements may be misleading

for boldness measurements, as Anolis sagrei lizards were more tolerant of humans but were more cautious (Lapiedra et al. 2017). In another study, urban birds were rated as bolder, due to approaching food earlier after human presence, but more neophobic, as they approached food by a novel object later (Audet et al. 2016). Thus, the test for measuring boldness may change the behavior classification or score for individuals or for populations.

A correlation of multiple behaviors within a given context or across different contexts is a behavioral syndrome. Activity level, exploratory behavior, dominance, foraging behavior, and/or risk taking can be correlated (Beauchamp 2000, van Oers et al.

2004a, Moule et al. 2015). Some studies have found linear positive relationships between boldness and aggression in certain species (Verbeek et al. 1996, Sih and Giudice 2012).

However, other studies have found high levels of aggression in scared or anxious individuals (Reisner 2003, Bamberger and Houpt 2006). The relationship between boldness and aggression may also be impacted by the testing method (Myers and Hyman

2016). We found only two mammalian wildlife studies comparing behavioral traits in different levels of urbanization: woodchucks (Lehrer et al. 2012) and Meriam’s kangaroo rat (Hurtado and Mabry 2017). Hurtado and Marby 2017, found a correlation between boldness and aggression but did not find a difference in boldness or aggression based on urbanization. However, this may have been because the habitat types between the two sites were similar. No study that we are aware of has examined differences or correlations in behaviors or personalities between carnivores living in different levels of urbanization.

Carnivore-human interactions are particularly important in urban areas as there is increased perceived and real risk of interactions that could be harmful to either people, pets, and/or carnivores. Besides disease and provocation, habituation and highly modified environments were factors associated with wolf attacks on humans (Linnell et al. 2002).

There have only been 2 reported human mortalities caused by coyotes, but coyote attacks on people and pets can occur. Coyote attacks are more common in the western US

(White and Gehrt 2009) and human-coyote conflict may be increasing in suburban areas

(Timm et al. 2004, Poessel et al. 2013). Conflict may increase during certain seasons such as pup rearing (Lukasik and Alexander 2011), but may not (White and Gehrt 2009). Pet attacks are also a threat (Farrar 2007, Alexander and Quinn 2011). Therefore, knowledge of what may cause aggressive behavior or negative interactions should be studied to prevent conflict.

Boldness and aggression levels may vary based on intrinsic or extrinsic factors.

Bold (Fraser et al. 2001, Dingemanse et al. 2003, Rehage and Sih 2004) or aggressive

(Duckworth and Badyaev 2007) individuals may be more or less likely to disperse to new habitat depending on the species, habitat quality, age, and sex (Cote et al. 2010). Season impacted flight initiation distance of rural, but not urban squirrels, possibly due to year- round availability of supplemental feeding (Uchida et al. 2016). The same behavior in the same environment may impact sexes differently due to different roles, resulting in sex biased behavior levels (Gosling 1998, Dall 2004). For example, some males have been found to be bolder (Ingley et al. 2014) and have more repeatable behavior (Dammhahn

2012). With the great tit, there is an opposite benefit to being bold/shy for each sex based on the quality of winter (Dall 2004).

We analyzed boldness and aggression of coyotes towards humans across an urban gradient in the Chicago Metropolitan Area (CMA) to test for differences in behavior based on landscape type and we incorporated sex as a possible factor. We tested for a boldness-aggression syndrome and analyzed each context separately to determine if context influenced aggressive action based on landscape type.

Methods

Study location and subjects.-

We collected behavioral data on coyotes between September 2014-March 2018 from individuals that were captured as part of an 18+ year coyote monitoring project in the

Chicago Metropolitan Area (CMA) (Gehrt et al. 2009). Coyotes > 4 months old were captured using cable restraint devices or foothold traps and mainly tracked within Cook

County, but were also located within DuPage, Kane, Kendall, McHenry, and Will counties. Our study area and capture locations ranged from naturalized areas in the suburbs called Forest Preserves (FP) to the core of the city of Chicago. Trapping sites were located within FPs, private lands such as golf course and cemeteries, or undeveloped lots. Traps were checked every morning at all sites and also during the evening at sites near human activity. Only 3 of 207 captured animals were found in a trap during late afternoon checks. Once coyotes were restrained, coyotes were put into a 0.88 x 0.61 x 0.66 meter monkey squeeze cage (Harford Metal Products Inc.) and transported by truck back to the lab facility for processing and behavioral tests. 79

After behavioral tests were performed, animals were immobilized with an intramuscular injection of Telazol (Fort Dodge Animal Health, Iowa). Hair, whisker, and blood samples were collected for each coyote and weight, sex, measurements, and suspected age were recorded. Age was assigned as pup (<1 year), subadult, or adult (2+ years) based on tooth wear, reproductive status, and known history (i.e-. PITT tag for year of birth). Unmarked coyotes were given a unique ID and colored numbered plastic ear tags (NASCO Farm & Ranch, Fort Atkinson, Wisconsin) and a VHF radio collar

(Advanced Telemetry Systems, Isanti, MN, USA) or a GPS collar (Lotek, Newmarket,

Ontario, Canada). Within 12 hours of removal from trap but after complete recovery from immobilizing drug, coyotes were released back at the initial site of capture.

Trapping and handling protocols were approved by Ohio State University’s

Institutional Animal Care and Use Committee (IACUC 2003R0061) and guidelines by the American Society of Mammalogists were followed (Sikes and the Animal Care and

Use Committee of the American Society of Mammalogists 2016). Three out of 207

(1.45%) captures were euthanized or died due to project related factors during the time period of this study (2 from trap related injuries and 1 from a possible heart attack or stress).

Behavior Tests.-

Behavior was recorded in 4 field contexts and in 2 lab contexts. Behavioral actions were recorded in the field: 1) when the coyote first saw people, 2) when a person approached the capture circle, 3) reaction to a restraint pole, and 4) once the coyote was restrained by the pole. Starting in 2016, the length of Fight/Flee persistence was recorded. We

separated length of time into “short” and “long” where short indicated movement stopped at any point before being restrained while long indicated movement stopped only after restrained or the animal never stopped attempting to fight/flee.

At the lab actions were recorded: 5) while in the cage and 6) during a manipulated arm experiment. In the manipulated arm experiment, an artificial hand was slowly inserted into the cage and kept stationary for 15 seconds and then was slowly moved side to side for 15 seconds. An artificial hand attached to a stick and hidden by a sleeve has been used in dog aggression tests (Netto and Planta 1997) and was a reliable indicator of aggression towards people (Kroll et al. 2004). Behavioral categories of eye contact, movement, vocalization, teeth display, body position, tail position was recorded.

Separate overall boldness and aggression scores were given based on coyote actions over all contexts by several observers (average observers = 2.36, range = 1-4). The average boldness (Boldness Classification-BC) and aggression scores (Aggression Binary-AB) across all observers was then used for further analysis. Lastly, aggression scores were also calculated for each of the 6 contexts based on aggressive actions: 0=none, 1=present teeth some or vocalize some, 2= present teeth + vocalize some growl or constant bark, 3= actively baring teeth and/or actively growling, 4= biting/snapping motion, lunged or attacked. An Aggression Comprehensive score (AC) was calculated by adding up the 6 aggression context scores. More thorough details on behavioral tests are explained in

Chapter 2. To visualize behavior proportions in each landscape type, individuals were binned into Aggressive (AB>0.5) or Not Aggressive (AB<0.5) and Scared (BC<0.5) or

Bold (BC>1.5) from Aggression Binary and Boldness Classification averaged scores.

Landscape classification.-

For all coyotes used in this study, we estimated locations using program LOCATE III

(Pacer, Truro, Nova Scotia, Canada) via triangulation from bearings using a truck- mounted antenna or through direct visual observation with a handheld Global Positioning

System (GPS). Coyotes were located at minimum 1x/week during the day (0600-1700 hrs) and 5x/night (2000-0400 hrs) at 1 hour intervals every 2 weeks. We calculated annual home ranges using a 95% minimum convex polygon with the adehabitatHR package (Calenge 2006b) in program R (R Core Team 2017) for individuals with at least

30 locations. We used 95% MCPs to determine the landscape that was located within areas a coyote used. Using the National Land Cover Database in ArcMap 10, we combined all development categories into one developed category and combined designated forest preserves, water, grasslands, wooded areas, and other natural habitats into a natural category. We classified animal landscape use as “Natural CMA” if >60% of their home range was located in natural areas, “Matrix” if <60% of their home range was located in natural areas in the suburbs, and “Urban Core” if they were located within the core area of Chicago (Figure 1). We captured and monitored coyotes moving within the developmental gradient in the CMA, from small intact natural areas called forest preserves to the inner city.

Statistical analysis.-

We tested for trapping method bias based on landscape type and behavior using chi- square analysis. Differences between landscape types in binary classification methods

was also tested using chi-square, and fight/flee persistence length was tested using Fisher

Exact Test due to smaller sample size.

We used generalized linear models (GLMs) with aggression and boldness as dependent variables and sex and landscape type as independent variables. A Gaussian model was used for boldness while Quasi-Poisson models were used with AC models and each individual aggression context model to account for over-dispersion. We analyzed each aggression context individually to see if context changed the relationship between aggression and landscape classification. Sex was removed from aggression context models as this was not significant in the overall AC model. Natural CMA individuals were set as the reference level and Tukey pair-wise comparisons were used to compare differences in scores by landscape classifications post-hoc. To test for a relationship between aggression and boldness, we then reanalyzed the best aggression comprehensive model with boldness included. An ANOVA global F test was used to determine if interaction terms between boldness and landscape type was needed.

Results

During Fall 2014-Spring 2018, 137 unique coyotes, 151 total, were captured and tested in all behavioral contexts. Only unique coyotes were used to identify linkages between behavior, landscape type, and gender to prevent pseudoreplication or learning effects for all animals that were classified at all aggression classifications (n = 137). Sixty-eight individuals were classified as Natural Suburb (n = 28 f, 39 m), 45 as Matrix Suburb (n =

16, 29), and 25 as Urban Core (n = 10, 15). There were low boldness and aggression scores for each landscape type at each behavioral measure, with more variation in urban 83

core individuals (Table 3.1). Seven of the 137 (5.11%) coyotes used in the study were reported as nuisances. Only 1 of these was due to aggressive behavior towards humans, while all other reports were due to coyotes acting sick or just being seen. All of these animals except 1 were located within the matrix (n = 4) or the urban core (n = 2).

There was no bias in trapping method based on landscape type for all 137 unique individuals (c2 = 0.746, df = 2, p = 0.689). There was no difference in AB (t = 0.484, df =

41.775, p = 0.631) or BC (t = 0.707, df = 41.139, p = 0.484) between individuals caught in snare and footholds but there was a difference in AC (t = 2.16, df = 49.394, p = 0.034).

The mean AC score for foothold individuals was 1.741 points higher than individuals caught in snares. This indicates that while individuals in one context may have a slightly more aggressive action if caught in a foothold, the overall aggression and boldness classification did not differ.

Behavior based on landscape type.-

While not statistically significant (c2 = 10.466, df = 6, and p = 0.106), Urban Core individuals were more evenly distributed amongst binary behavior classification types, while Matrix and Natural CMA had higher proportions of scared individuals and secondarily as not-aggressive (Figure 3.2A). All landscape types had individuals with all classification types. There was a trend towards coyotes having a longer fight/flee persistence in Urban Core and shorter in the Matrix (p = 0.068; Figure 3.2B).

For the boldness model, there was no difference between sex (p = 0.196) or in Tukey- contrasts between Matrix and Natural CMA (p = 0.960) but there was a difference

between Matrix and Urban Core (p = 0.001) and Natural CMA and Urban Core (p <

0.001) with bolder individuals in Urban Core (Table 3.3; Figure 3.2).

For the Comprehensive Aggression (AC) Quasi-Poisson model, sex (p = 0.28) and Tukey contrasts between Matrix-Natural CMA were also not significant (p = 0.263) but there was a difference between Matrix and Urban Core (p = 0.001) and Natural CMA and Urban Core (p = 0.005) with more aggressive individuals in Urban Core (Table 3.2;

Figure 3.3). Sex was not significant and the reduced model performed better in a global F test (p = 0.281). The quadratic boldness model outcompeted the linear model in a global

F test (p = 0.021; Figure 3.4) and there was not support for an interaction model (p =

0.184).

For aggressive scores separated by context, there were no differences between any landscape classification types for either lab context 5 or 6 after Tukey’s correction

[Urban Core and Matrix (p = 0.226; p = 0.924), Urban Core and Natura CMA (p = 0.140; p = 0.994;), Natural CMA and Matrix (p = 0.998; p = 0.801)]. For field contexts, there was a general trend of higher aggressive actions in Urban Core and lower aggressive actions in Matrix (Table 3.1). For context 1, 2, 3, and 4, there was a difference between

Urban Core and Matrix (p = 0.019; p = 0.041; p = 0.008, p = 0.002 respectively) and for context 1 there was a difference between Urban Core and Natural CMA (p = 0.014) but not for contexts 2, 3, and 4 (p = 0.115; p = 0.164; p = 0.098). For all contexts 1, 2, 3, and

4 there was no difference between Matrix and Natural CMA (p = 0.967; p = 0.739; p =

0.237; p = 0.096 respectively).

Discussion

Urban core coyotes were more likely to be aggressive and bold and to have a prolonged fight/flee response, indicating a selection for elevated action responses towards humans in highly urbanized areas. However, very few individuals over all landscape types

(5.11%) were reported as being nuisances, and only 1 was classified as acting aggressively. While not significant at all contexts, there was a trend of Matrix individuals being the least bold and least aggressive. Matrix individuals are more likely to come into contact with humans as they live in areas such as neighborhoods, parks, and golf courses with increased visibility to humans. Therefore, there may be more pressure to be less aggressive due to high potential of negative interactions with humans such as lethal removal. Conversely, urban core individuals may have more refuge from people as they travel along railroad or transportation lines and overgrown abandoned lots (Ellington et al. in press) which provide them cover and protection from humans. In these areas, lethal removal may also be harder to perform. Lastly, Natural CMA individuals have more space to avoid humans but still have access to anthropogenic resources, such as trash cans, in forest preserves. This larger intact space in an urban area may provide benefits and alleviate impact from urbanization (Markovchick-Nicholls et al. 2008).

Males had only slightly, nonsignificant increased levels of boldness and aggression at all landscape types. Other studies’ results vary, with some showing no effect on behavior based on sex or age (van Oers et al. 2004a, Šlipogor et al. 2016), and others showing increased aggression (Fuentes and Gamerl 2005) or boldness in males

(Ingley et al. 2014). Male and female coyotes share parenting, territory defense, and other 86

responsibilities (Andelt 1985, Harrison and Gilbert 1985, Gese 2001), which may be a reason why sex did not significantly affect behavior. We also did not test behavior during the breeding season, a time period where hormones may alter behavior or increase aggression (Cavigelli and Pereira 2000).

Human directed aggression may be related to conspecific aggression. In dogs, stranger (human)-directed aggression was positively correlated with conspecific aggression (Barnard et al. 2012). Aggression towards conspecifics may be important to defend or acquire territory and mates (Watson and Miller 1971, Yasukawa and Searcy

1982). Both male and females coyotes are highly territorial, with territory holders exhibiting increased survival and reproduction (Gese 2001). Genetic links to behavior have also been found in several species, from humans to flies (Kang et al. 2008, Johnson et al. 2009, Konno et al. 2011). Urban environments may lead to a selection of certain genotypes (Mueller et al. 2013), including within gene regions that impact boldness or aggression. Carryover effects can occur if a linked behavior is beneficial in one context but detrimental in another (Sih et al. 2004). If behavior in different contexts are linked, a balancing selection may occur due to a behavior having positive consequences towards conspecifics (territory defense) but negative consequences towards humans (lethal removal).

Higher aggression levels can be beneficial for colonizing habitat, but may decrease after colonization due to other selection pressures (Duckworth and Badyaev

2007). Coyote populations living and reproducing in the urban core area is still relatively new, especially compared to the natural CMA. Increased aggression level in urban

coyotes may be a result of relatively new colonizers that have not yet undergone reverse selection. Resource spatial pattern and availability may also drive aggression levels. The presence of clumped resources in urban areas, whether anthropogenic (trash cans, garbage dumps, feeding) or natural (such as a small patches of natural landscape), may lead to urban individuals being more aggressive (Flint et al. 2016). Conversely, a rural area with a clumped resource, especially in areas with low overall availability of food, may also lead to increased aggression. In song sparrows, aggression increased with urbanization and with supplemental feeding, especially in rural populations (Foltz et al.

2015). In this study, we did not measure behavior in rural areas, but did find an increase in aggression with increased development.

While we found increased boldness and aggression with urbanization, we did not find a linear correlation between boldness and aggression, but rather had high and low aggression scores in all levels of scared/boldness. More information should be collected to determine what may impact behavior and lead to aggression towards humans.

Aggression can be elicited because of different factors (i.e.- fear, habituation, predatory, sickness). For example, abnormally high or low anxiety can result in an increased aggression response (Neumann 2010). In dogs, a lower threshold for behaving aggressively was present in scared or anxious animals (Reisner 2003). In some studies, gene expression in regions related to stress or CORT levels were increased in urban individuals (Meillère et al. 2016, Watson et al. 2017) while in others levels were reduced but increased more during stress events (Davies et al. 2016). In our study, urban core

coyotes were more likely to behave aggressively in almost all contexts, suggesting that anxiety or stress levels may be increased.

Other studies have found that the bold-aggression syndrome breaks down (is no longer present) in urban populations (Scales et al. 2011, Hardman and Dalesman 2018).

We did not test behavior in a rural population, so we are unable to determine whether this syndrome is present in rural individuals but breaks down with urbanization. However, even our most natural population did not have a positive linear relationship between aggression or boldness (Figure 3.3). We measured aggression and boldness towards humans in a setting that may have affected normal behavior. Behavior can be context specific (this study, Coleman and Wilson 1998) and individuals may be plastic in their behavior (Stamps and Biro 2016). Therefore, there may be aggression-boldness correlations in other contexts (ex- towards conspecifics), even if they were not measured under our testing methods or conditions.

Quantifying behavior can help in managing species, as personality may affect survival or fitness (Dingemanse and Réale 2005, Biro and Stamps 2008, May et al. 2016) or human-wildlife interactions and high population sizes of carnivores in urban areas can create fear of increased human-wildlife conflict. While our research indicated that urban individuals were bolder and more aggressive, the level of aggression was still fairly low even in an extreme context where interaction with humans was unavoidable. Individuals that did behave aggressively could be bold or scared, and bold individuals were not always aggressive. In addition, only 1 study individual (who was being fed) was reported as acting aggressively. Therefore, even coyotes with high aggressive scores did not

behave aggressively outside of our testing. Our research suggests that coyotes behave differently, even within the same environment, and most coyotes do not cause conflict.

Therefore, coyotes can inhabit areas of high human population centers with low aggressive conflict. Further research into what causes aggression in urban carnivores should be used to prevent human-wildlife conflict and targeted removal of problem coyotes, rather than general removal, should be used for management.

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Behavior Measure Natural CMA Matrix Urban Core Range of Mean (SE) Mean (SE) Mean (SE) Possible Values Boldness Classification 0.534 (0.09) 0.513 (0.10) 1.33 (0.17) 0-2 Aggressive Binary 0.322 (0.05) 0.261 (0.06) 0.493 (0.09) 0-1 Aggressive Comprehensive 5.10 (0.48) 3.98 (0.59) 8.4 (0.90) 0-24 - C1: Approach 0.463 (0.11) 0.422 (0.11) 1.16 (0.27) 0-4 - C2: Capture Circle 1.37 (0.16) 1.18 (0.22) 2.08 (0.32) 0-4 - C3: Stick 1.85 (0.23) 1.29 (0.27) 2.72 (0.34) 0-4 - C4: Restrained 0.896 (0.16) 0.422 (0.13) 1.60 (0.35) 0-4 - C5: Cage 0.149 (0.06) 0.156 (0.08) 0.440 (0.20) 0-4 - C6: Arm 0.373 (0.13) 0.511 (0.18) 0.400 (0.22) 0-4

Table 3.1 Mean scores of each behavior measure by urbanization level in coyotes from 2014-2017 in the Chicago Metropolitan Area where C= context and the sum of the context scores is the Aggressive Comprehensive Scores.

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Modela Family Intercept Male Matrix Urban Core Boldness Boldness2 Dispersion Estimate (SE) Estimate Estimate Estimate Estimate Estimate Parameter [exp(B)]a (SE) (SE) [exp(B)] (SE) (SE) (SE) [exp(B)] [exp(B)] [exp(B)] [exp(B)] Boldness Gaussian 0.430 (0.12) 0.178 (0.13) -0.032 (0.14) 0.630 (0.17) AC Quasi-Poisson 1.541(0.123) 0.149 (0.14) -0.259 (0.17) 0.496 (0.16) 3.23 [4.668] [1.161] [0.772] [1.641] AC_b Quasi-Poisson 1.611 (0.112) -0.218 (0.16) 0.399 (0.17) -0.650 (0.37) 0.481 (0.18) 3.16 [5.009] [0.804] [1.490] [0.522] [1.519] C1: Field Quasi-Poisson -0.770 (0.228) -0.092 (0.37) 0.919 (0.33) 1.61 Approach [0.463] [0.913] [2.507] C2:Capture Quasi-Poisson 0.312 (0.126) -0.154 (0.21) 0.415 (0.21) 1.45 Circle [1.373] [0.858] [1.514] C3:Pole Quasi-Poisson 0.616 (0.13) -0.362 (0.11) 0.385 (0.21) 1.98 [1.851] [0.696] [1.470] C4: Quasi-Poisson -0.111 (0.18) -0.752 (0.36) 0.580 (0.28) 1.92 Restrained [0.900] [0.471] [1.787] C5:Cage Quasi-Poisson -1.90 (0.41) 0.041 (0.643) 1.081 (0.57) 1.71 [0.149] [1.042] [2.95] C6:Arm Quasi-Poisson -0.99 (0.34) 0.315 (0.50) 0.070 (0.64) 2.97 [0.373] [1.370] [1.072]

Table 3.2 GLM models of boldness, each aggression context (C), aggression comprehensive (AC), and aggression comprehensive_b

(AC_b) for coyotes in the Chicago Metropolitan Area between 2014-2018. AC_b included the variable boldness and boldness2 as dependent as dependent variables. All models were executed with Natural CMA individuals as the reference. Any blanks indicate a variable that was not included in the model and aExp[B] is the exponentiated regression coefficient for quasi-poisson models. 103

Figure 3.1 Example of annual home ranges (95% minimum convex polygons) for each landscape classification [Natural CMA (green),

Matrix (blue), and Urban Core (red)] in three Chicago Metropolitan coyotes during study period 2014-2018.

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A) B) 1.0 1.0 0.8 0.8 Short SN 0.6 0.6 0.4 0.4 Binary Classifications Binary SA Long 0.2 0.2 BN BA 0.0 0.0 Natural CMA Matrix Urban Core Natural CMA Matrix Urban Core

Landscape Type

Figure 3.2 A) Proportion of coyotes with each binary classification type (neutral removed) in the Chicago Metropolitan Area from 2014-2017 where S=scared, B= bold,

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A) 1.2

1.0

0.8

response Predicted

0.6

0.4

Natural CMA Matrix Urban Core B) 9

Predicted response Predicted 5

Natural CMA Matrix Urban Core

Figure 3.3 Predicted response of A) Boldness and B) Aggression Comprehensive scores based on landscape classification and sex (red=female, blue=male) of coyotes in the

Chicago Metropolitan Area from 2014-2017.

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Model Natural CMA Matrix Urban Core 15 10 5 Comprehensive Aggression Comprehensive 0

0.0 0.5 1.0 1.5 2.0

Boldness

(gray circles), and Natural CMA (green squares).

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Chapter 4: Linking behavior and genes: Can genetics explain coyote behavior towards

humans?

Abstract

Behavior has been linked to hormones, neurotransmitters, gene expression, and gene regions. Serotonin, dopamine, and androgen-linked gene regions impact emotions and behaviors such as aggression, boldness, anxiety, and activity. However, behavioral- genetic linkages have been mainly researched in people, domestic animals such as dogs

(Canis lupus familiaris), birds, or in a lab setting. We captured, analyzed behavior, and genotyped 122 coyotes in the Chicago Metropolitan Area during 2014-2017. We assigned boldness and aggression scores and calculated an aggression comprehensive score based on actions in 4 field and 2 lab contexts. We used generalized linear models to test for correlations between behavior and genetics using microsatellites (2) and single nucleotide polymorphisms (SNPs; 17) that were found to be correlated with dog behavior or were located in behavioral gene regions. Eight markers were correlated with boldness and/or aggression measures. Two of these markers were also correlated with behavior in the dog. These correlations indicate that certain gene regions may be associated with behavior in coyotes. Such markers (SLC6A1, HTR1D, Androgen Receptor) may be useful for understanding human-carnivore conflicts in urban settings.

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Introduction

Behavior is influenced by environmental, social, learned, and genetic influences and interactions (Wahlsten et al. 2003; Robinson et al. 2008; Tung et al. 2012). Urbanization

(Ditchkoff et al. 2006; McDonnell and Hahs 2015), food availability (Zabel and Taggart

1989) and population densities (Iossa et al. 2009) are some factors that can modify behavior of individuals or select for behaviors in populations. Personalities, individual differences that are consistent over context and/or time (Réale et al. 2007), have been document in numerous animal species ranging from insects (Niemelä et al. 2012) and other invertebrates (Kralj-Fišer and Schuett 2014) to large herbivores (Bergvall et al.

2011) and carnivores (Gosling 1998). Personalities in wildlife can impact fitness (Smith and Blumstein 2007) and therefore be regulated by genetics and natural selection

(Dingemanse and Réale 2005).

There are several methods for identifying if behaviors or personalities are under genetic control. These methods include cross-fostering, twin studies, artificial breeding

(Breed and Moore 2012; Veroude et al. 2016), heritability studies (Van Oers et al. 2005), microarray expression levels (Dierick and Greenspan 2006), and testing for behavioral differences between hand-reared animals obtained from different populations in the wild

(Kroodsma and Canady 1985). More recent studies search for correlations between specific gene regions and behavior. Genome wide association studies (GWAS) (Zapata et al. 2016), single gene knockouts (Veroude et al. 2016), common sets of SNP markers

(Jones et al. 2008) candidate genes (Takeuchi et al. 2009a), microarray expression analysis of behavior-related genes (Alaux et al. 2009), and using gene regions correlated 109

with behavior in other species (Hejjas et al. 2007) are all ways to test for particular gene and behavior links. For example, the expression levels of heme related sequences differed in tame selected versus non-selected foxes (Lindberg et al. 2007).

Monoamine neurotransmitters levels can affect mood (Ruhé et al. 2007), aggression (Edwards and Kravitz 1997; Siever 2008), emotions, anxiety and impulsivity

(Westenberg et al. 1996). Monoamine oxidase A (MAOA) impacts serotonin, norepineprine, dopamine, and phenethylamine and has been linked to mood disorders and aggressive behavior (Shih and Thompson 1999). Serotonin is a major regulator of emotions and has important roles in development and cognition (Birger et al. 2003).

Activation of various serotonin receptors can increase or decrease aggression and different receptors control different aggression methods (Johnson et al. 2009). Increased activity of dopaminergic systems may stimulate aggressive behavior (Winberg and

Nilsson 1993).

Most recently, behavior-genetic linkages have been tested by examining polymorphisms in these monoamine neurotransmitter genes. Many genes that regulate neurotransmitters have been linked to behavioral traits in human and non-human species

(Newman et al. 2005; Inoue-Murayama 2009). For example, DRD4 is correlated with activity-impulsivity (Hejjas et al. 2007; Congdon et al. 2008; Wan et al. 2013) and aggression (Fresan et al. 2007; Farbiash et al. 2014). In Zebrafish (Danio rerio), fgfr1a polymorphisms were associated with aggression, boldness, and explorative activity

(Norton et al. 2011). Some serotonin genes have also been linked to impulsivity (Nomura et al. 2015), anxiety (Lesch et al. 1996), various affective disorders (Caspi et al. 2003;

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Murphy et al. 2013), and aggression (Davidge et al. 2004; Retz et al. 2004).

Polymorphisms in genes regulating MAOA has been correlated with antisocial, violent, and criminal behavior (Caspi et al. 2002; Newman et al. 2005; Nilsson et al. 2006).

However, linkages between gene regions and behavior are not always consistent and can vary based on species studied, sex, sample size, the exact location within a gene that is studied, and behavioral measure (Schmidt et al. 2002; Dmitrieva et al. 2011).

DRD4 has been linked to aggressiveness (Proskura et al. 2014) and was linked to impulsivity in German shepherds used as police dogs, but not pet German shepherds

(Hejjas et al. 2007). Androgen receptor Q2 was correlated with aggressive behavior in males but not females (Konno et al. 2011). Furthermore, only certain polymorphisms within a gene region may be correlated with the tested behavior or the combination of alleles for statistical analysis may change results (Comings et al. 1999; Davidge et al.

2004). While serotonin linked gene HTR1B was not linked to human-directed aggression in dogs (and neither was HTR1A, HTR2A, or SLC6A4) (van den Berg et al. 2008),

HTR1B was linked to anger and hostility in human males (Conner et al. 2010). Other serotonin and dopamine linked genes DRD1, HTR1D, HTR2C, SLC6A1 (Våge et al.

2010) and SLC1A2 (Takeuchi et al. 2009b) were found to related to aggression in dogs.

Most of the research into genetic linkages to behavior have been studied in people or domestic/lab animals (Van Oers et al. 2005; Jones et al. 2008). Even fewer genetic- behavior linkages have been tested on wildlife species and most of these have been in birds (van Oers et al. 2004b). To our knowledge, no study has tested behavioral-genetic links in wild carnivores. Previous research found polymorphisms in neurotransmitter

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regions and/or dog behavior-related genes in the coyote and found differences in genotypic frequencies based on urbanization (Chapter 1), that coyotes exhibited various levels of boldness and aggression (Chapter 2), and that these behaviors varied based on urbanization level (Chapter 3). This chapter builds upon this foundation by examining the relationship between the behavior and genetic polymorphisms through studying a population of coyotes living within a suburban-urban gradient in the Chicago

Metropolitan Area (CMA).

Methods

Study Area and Subjects.-

The Chicago Metropolitan Area (CMA) is a heavily populated area with approximately

10 million residents (U.S. Census Bureau 2016). We captured and tracked CMA coyotes mainly within Cook County but also within the counties of DuPage, Kane, Kendall,

McHenry, and Will. Our coyotes inhabited areas from suburban natural areas (Forest

Preserves), to the suburban matrix, to the inner core of Chicago. Coyotes in our study area resided near and within high areas of human activity. Coyotes >4 months of age were captured using cable restraint devices or foothold traps between September 2014-

March 2018 as part of a long-term coyote monitoring project (Gehrt et al. 2009).

Trapping locations were located mainly in Forest Preserves, but also on private land such as cemeteries, golf courses, and undeveloped lots. Traps were checked 1-2 times per day

(morning and evening) depending on location and any coyotes recaptured within 4 weeks of initial capture were immediately released. All other coyotes were restrained, put into a

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cage, and transported by truck back to the lab facility for additional behavioral testing and for careful monitoring during processing.

Animals were immobilized after behavioral testing with an intramuscular injection of Telazol (Fort Dodge Animal Health, Iowa) at the lab. Biometrics were recorded for each coyote including weight, sex, measurements, and age. Blood samples were collected for genetic analysis. Hair, whisker, and fecal samples were also collected for other studies. Each coyote was given a unique ID and numbered plastic ear tags

(NASCO Farm & Ranch, Fort Atkinson, Wisconsin) and fitted with a VHF radio collar

(Advanced Telemetry Systems, Isanti, MN, USA) or a GPS collar (Lotek, Newmarket,

Ontario, Canada). Coyotes were released at the initial capture site within 12 hours of removal from trap once fully recovered from immobilization. Trapping and handling protocols were approved by The Ohio State University’s Institutional Animal Care and

Use Committee (IACUC 2003R0061) and followed guidelines by the American Society of Mammalogists (Sikes and the Animal Care and Use Committee of the American

Society of Mammalogists 2016).

Genetics.-

Coyotes were genotyped at 2 microsatellites and 17 SNP behavioral markers using the methods described in Chapter 1. Primers and listed genotypic frequencies of all individuals can be found in Appendix D and E. SNPs or gene regions were selected from regions correlated with aggressive or bold behavior in published dog or other species studies. DNA was extracted through blood samples using the MegaZorb DNA Mini-prep kit (Promega, Madison, Wisconsin). Restriction fragment length polymorphisms

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(RFLPs), sequencing, and estimating fragment size by capillary electrophoresis were used to genotype individuals depending on the region and size of interest. In this study, eight unique gene regions were selected to be genotyped on 7 different chromosomes

(Chromosome 2 [gene HTR1D], 4, 7 [SMAD2], 17, 20 [SLC6A1], 22, and X [Androgen

Receptor]).

RFLP analysis using restriction enzymes MBoII (5 U/µl) and SSP1 (10 U/µl) were used to genotype SNPS on Chromosome 4 and Chromosome 7 (gene SMAD2) respectively from Jones et al. (2008) with known controls. Sanger sequencing and/or

Next Generation Sequencing (NGS) was done for a region on Chromosome 17 and 22

(Jones et al. 2008), and portions of genes HTR1D and SLC6A1 (Våge and Lingaas 2008,

J. Våge et al. 2010). Any unclear genotypes were reanalyzed and all methods were cross- validated.

Behavior.-

Behavioral tests were performed in the field (4 contexts) and the lab (2 contexts). More thorough details are described in Chapter 2. The 4 field contexts were as follows: 1) when the person and coyote first spotted each other at a distance, 2) once the person arrived at the edge of the capture circle, 3) reaction to the restraint pole, and 4) once the coyote was restrained with restraint pole. A capture circle is the area in which the captured coyote is free to move and the restraint pole is a circular plastic covered wire that can be adjusted to tighten around the coyote’s neck. Lab contexts were performed after coyotes were brought to the lab and given a quiet, dark, 15-minute adjustment period in the cage. The 2 lab contexts were as follows: 5) person in front of cage and 6) during an extended arm

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test. The extended arm test consisted of an artificial hand placed in the cage stationary for

15 seconds and then moved back and forth for 15 seconds. The artificial hand was connected to the same person who performed the 5th context.

Aggression scores were calculated for each of the 6 contexts based on the following aggressive actions: 0=none, 1=present teeth some or vocalize some, 2= present teeth + vocalize some growl or constant bark, 3= actively baring teeth and/or actively growling, 4= biting/snapping motion, lunged or attacked. An Aggression Comprehensive score (AC) was calculated by adding up all 6 aggression scores. Each observer (average =

2.45, range = 1-4) also recorded separate classifications for each animal as one of the following categories: 1) scared but not aggressive, 2) scared and aggressive, 3) neutral, 4) bold but not aggressive, and 5) bold and aggressive. These categories were separated into boldness and aggression classifications for further analysis. Boldness Classification (BC) was coded as 0= scared/shy, 1=neutral, 2= bold. Aggression Binary (AB) was coded as

0=not aggressive, 1= aggressive. After averaging scores, AB scores were binned into 0

(AB < 0.4) or 1 (AB > 0.6) for further analysis. AC is a measure of amount and intensity of aggressive actions overall contexts whereas AB just denotes if an individual was overall rated as aggressive or not aggressive.

Analyses-.

To determine if SNPs or microsatellite repeats were significantly correlated to behavior, we tested three GLM models where Y1= boldness (Gaussian), Y2= Comprehensive

Aggression (Quasi-Poisson), and Y3= Binary Aggression (Binomial). Our independent variables included each SNP and alleles were coded as 0=homozygous major,

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1=heterozygous, and 2=homozygous minor (Vattikuti et al. 2012). For example, for the

SNP on Chr. 22 gene region PCDH9: GG=0, AG=1, AA=2. As linear regression models require full datasets or they omit the individual and we had some missing SNP values, we partitioned our dependent variables into 3 sets: 1) SNPs on chromosome 17, 2) SNPs on chromosome 2 (gene HTR1D), and 3) SNPs on chromosome 4, 7 (gene SMAD2), 20

(gene SLC6A1), and 22. Lastly, as the Q1 and Q2 androgen receptor genes are sex- linked, we separated males and females and coded repeats as short (0) or long (1) for males and short (0), short/long (1), or long/long (2) for females where Q1: short=11, 12 or 13 repeats, 1ong= 14 or 15 and Q2: short= 20, long= 21 or 22 repeats. We used an alpha of 0.10 to test for correlations.

Using previously publicized dog studies, we determined if behavioral alleles in the dog were also correlated with behavior in CMA coyotes. We also determined if genotypes that were correlated with behavior in the coyote also had different genotypic frequencies based on urbanization level.

Results

Behavioral contexts and genotypes were recorded for 122 unique coyotes (49 female and

73 male). All genotypic frequencies are recorded in Appendix E. Aggression

Comprehensive (AC) scores ranged from 0-19 with a mean score of 5.29 (SE = 0.39)

(Figure 4.1A). On a scale of 0-2, mean boldness score = 0.65 (SE = 0.07) and on a scale of 0-1, mean aggression binary score = 0.35 (SE = 0.04). After binning aggression binary

(AB), the majority of individuals were classified as not-aggressive (Figure 4.1B).

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For the first SNP set (region on chromosome 17), 1 allele was correlated with

Boldness at p < 0.10 and no alleles were correlated with AC or AB (Table 4.1). For the second SNP set (HTR1D), there were 2 alleles correlated with Boldness, 3 with AC, and

1 with AB respectively where alpha = 0.10. For the third SNP set, there were 2 alleles correlated with Boldness, 0 with AC, and 1 with AB respectively where alpha = 0.10.

Four of the 5 SNPs that were correlated with behavior in the dog were not correlated with coyote behavior: HTR1D:F (Våge et al. 2010) or on Chromosomes 17:N,

4:J, or 7:K (Jones et al. 2008) (Table 4.1). We did find correlations between AB and

Chromosome 22:R (Jones et al. 2008) (p = 0.034) (Table 4.1). 4 alleles were correlated with behavior in the coyote but were not polymorphic in the dog. One of 7 SNPs with genotypic frequencies that differed based on urbanization level were also correlated with behavior (Table 4.1).

For coyotes in the CMA, we detected 5 alleles in the Q1 region and 3 alleles in the Q2 region. The most common allele for Q1 was 13 repeats and the most common allele for Q2 was 21 repeats for both males and females (Table 4.2). The short allele was most common for Q1 and the long allele was most common for Q2 for both males and females (Appendix E). We found no evidence that aggression (binary or comprehensive respectively) was correlated with androgen receptor number for Q1 (p = 0.284; p =

0.285) or Q2 (p = 0.879; p = 0.869) in females, for males at Q1 (p = 0.788; p = 0.340), or for male Q2 AC (p = 0.484) but the shorter allele in Q2 was correlated with increased AB

(p = 0.036) (Table 4.1). There also was no evidence that boldness was correlated for females (p = 0.641; p = 0.450) or males (p= 0.788; p =0.484) in the Q1 or Q2 region

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respectively. The Q2 region allele frequencies in males also differs based on urbanization

(Chapter 1).

Discussion

We found tentative correlations between SNPs and boldness and/or aggression in

7 of our studied SNPs. Many of these behavioral links were found in serotonin regions, and some of these SNPs were found in locations that were not polymorphic in the dog.

While most of our behavioral markers were correlated with aggression in other studies, we also found several alleles that were correlated with boldness. We found few links between aggression and our studied SNPs, even in SNPs that were correlated with aggression in the dog. Boldness can be more repeatable than other measures such as aggression (Svartberg et al. 2005; White et al. 2015; Ariyomo et al. 2017), including in coyotes (Chapter 2), which may lead to a greater chance of identifying boldness-genetic links. Aggressive behavior can also have many different components (Svartberg 2005).

Therefore, while many SNPs were not correlated with aggression in our study, they might be with other measures of aggression in the coyote such as defensive or intraspecific aggression.

Male coyotes with shorter repeated sequences in the androgen repeat sequence

Q2 were more likely to be aggressive. Akita Inu’s were also more aggressive with a shorter allele (23 repeats) compared to the longer allele (24 or 26) in the Q2 region

(Konno et al. 2011) in males only. In coyotes, our short allele was 20 and our long allele was 21 and 22 repeats. This may indicate that coyotes may have more aggression under

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certain conditions that were not measured in this study. Like Konno et al. 2011, this study also did not find a difference in aggression based on alleles for females.

It is possible that we did not find relationships between some of the polymorphisms in our study that are actually correlated with behavior and aggression.

Small effect sizes, polygenic inheritance, and the measure of personality can all result in failing to find or replicate relationships between personality and polymorphisms (Ebstein

2006). Aggression and boldness can occur under numerous contexts and for various reasons. For example, a defensive aggression may be under different genetic control than a bold aggression or a territorial aggression may be under different genetic control than a mating aggression. For simplicity and adequate sample size, we did not differentiate between aggressive individuals that were bold versus aggressive individuals that were shy/scared.

As even the same behavior is most likely controlled by multiple genes (Tecott and

Barondes 1996), there may be an interaction or amplifying effect of having certain alleles at several behavioral markers. Furthermore, a gene may only be expressed under certain conditions or may allow for better adaption to certain environments (Fox et al. 2005;

Bakermans-Kranenburg and van Ijzendoorn 2011). In this study for example, an individual may have an “aggressive” gene, but aggression may not be expressed unless certain internal or external settings are met. This is an example of how the gene and context/environment may interact. Another example is that individuals with a certain allele may be less likely to act aggressively in an urban setting compared to individuals without that allele. In male monkeys, an interaction between early rearing environment

119

and alleles within a certain polymorphism in the MAOA gene affected aggressive behavior (Newman et al. 2005).

As behavioral-genetic research continues across a variety of species, the role of genetics and environment in the expression of behavior will be better understood. There are many other genes that have been correlated with boldness, aggression, or other personality aspects including DRD4 (Kang et al. 2008; Verhulst et al. 2016), DRD1 and

HTR2C (Våge et al. 2010), HTR1B (Conner et al. 2010), and SLC1A2 (Takeuchi et al.

2009b) and more will continue to be discovered. The environment can impact the relationship between genetic polymorphisms, neurotransmitter function, or expression and behavior (Bennett et al. 2002; Bakermans-Kranenburg and van Ijzendoorn 2011). We studied coyotes living within a gradient from natural forest preserves to suburban neighborhoods to the highly-urbanized “inner core” of Chicago. Individuals living within these areas have unique stressors based on their environment. Stress may also correlate with aggressive behavior, with elevated cortisol levels and lower central serotonin fluid concentrations in animals that are more aggressive (Higley et al. 1992). Therefore, the physical expression of a genotype may be mediated by environmental factors, resulting in difficulties in finding correlations.

By understanding links between behavior and genetics, people can better manage both domestic and wildlife species. The selection for (or against) behaviors with a genetic basis would be important. Animals may be screened or selected genetically for predispositions towards or against certain behaviors (Houpt 2007) such as aggressive and bold behavior for guard dogs, or gentleness and trainability for guide dogs (Takeuchi et

120

al. 2009a). For wildlife management, selected removal of individuals with negative behaviors could prevent increased human-wildlife conflict without using general removal which can be more controversial and/or ineffective (Reiter et al. 1999; Martínez-

Espiñeira 2006; Eklund et al. 2017; Swan et al. 2017). Early selection for behaviors (and their corresponding genotypes) can provide better management success as behaviors can be correlated to fitness (Biro and Stamps 2008) and improve success of translocation projects (May et al. 2016). Lastly, studying the allele frequencies of different populations may indicate potential environments or circumstances that select for certain behaviors.

These conditions can then be studied and better managed to provide better human- wildlife interactions and prevent the selection for negative behaviors.

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Assigned Behavior Dog Coyote Major/ Bold AC AB Sample Chr. Gene Namea Positionb origin allelec Minor Alleled P-valuee P-valuee P-valuee Sizef 2 HTR1D A 76198905 C* C/T 0.673 0.604 0.418 75 HTR1D B 76199025 T/C C/T 0.863 0.582 0.879 75 HTR1D C 76199027 C/T T/C 0.093 0.058 0.065 75 HTR1D D 76199193 G* G/T 0.025 0.081 0.132 75 HTR1D E 76199482 G* G/A 0.940 0.086 0.993 75 HTR1D F 76199525 ‡ G/A G/A 0.706 0.863 0.972 75 HTR1D G 76199538 G/A G/A 0.558 0.917 0.928 75 HTR1D H 76199577 G/A G/A 0.754 0.257 0.995 75 HTR1D I 76199613 G/A G/A 0.331 0.044 0.994 75 4 J 37590553 ¶ G/T T/G 0.742 0.537 0.832 110 7 SMAD2 K 43719549 ¶ A/G A/G 0.455 0.308 0.326 110 17 L 12505660 A* A/C 0.063 0.582 0.377 65 M 12505705 C* C/T 0.786 0.615 0.794 65 N 12505775 ¶ C/T C/T 0.263 0.525 0.797 65 20 SLC6A1 O 7358401 C/T T/C 0.968 0.626 0.404 110 SLC6A1 P 7358551 G* G/T 0.041 0.707 0.358 110 22 R 22498919 ¶ G/A G/A 0.290 0.318 0.034 110 X AR Q1 51969947 § 10-12 11-15 0.641 0.869 0.665 49 repeats repeats (0.683) (0.787) (0.453) (71) X AR Q2 51970322 § 21-26 20-22 0.450 0.285 0.358 49 repeats repeats (0.940) (0.484) (0.036) (71) Continued

Table 4.1 Table of polymorphism location, behavior origin, and behavior model p-values for Chicago Metropolitan Area coyotes, where AC= Aggressive Comprehensive and AB= Aggressive Binary model. 134

Table 4.1 Continued a Given SNP ID for this study or named region for Q1 and Q2 b Position location of SNP or start of location of microsatellite region in CanFam3.0 NCBI database c Only alleles with a SNP behavior origin have alleles recorded as major/minor, all rest are unpublished where * denotes no polymorphism recorded in CanFam3.0. AR regions are CAG repeated sequences with a modified sequence in Q2 for coyotes. d Differences in genotypic frequencies based on urbanization level at p < 0.05 from Chapter 1 are underlined eP-values <0.05 are bolded and 0.10 > p < 0.05 are italicized. For AR gene, females and (males) were analyzed separately f Sample size for each model for that allele. AB models sample size is reduced by 3 individuals. ¶ Jones et al 2008 § Konno et al 2011 and Maejima et al 2005 ‡ Våge et al 2010

135

Sex Q1 Number of Repeats Q2 Number of Repeats 11 12 13 14 15 20 21 22 Males 0.000 0.041 0.589 0.260 0.110 0.288 0.644 0.068 Females 0.010 0.031 0.643 0.224 0.092 0.357 0.582 0.061

Table 4.2 Allele frequency of Androgen Receptor gene Q1 and Q2 separated by sex for coyotes in the Chicago Metropolitan Area from 2014-2017.

136

A B

0.6

0.15

0.4

0.10 Density Density

0.2 0.05

0.00 0.0

0 5 10 15 20 0 1 Aggression Comprehensive Aggression Binary

Figure 4.1 Proportion of genotyped coyotes in the Chicago Metropolitan Area from 2014-2017 with each A) Aggression

Comprehensive score and B) Aggression Binary Classification binned into 0= not aggressive and 1= aggressive.

137

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