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Electronic Theses and Dissertations Graduate Studies, Jack N. Averitt College of
Spring 2018
Movement in Cats
Valerie N. Plummer
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MOVEMENT IN CATS by
VALERIE PLUMMER
(Under the Direction of Michelle Cawthorn) ABSTRACT
Feral cats (Felis catus) are listed as one of the '100 world's worst invasive alien species'. There are as many as 70-100 million feral cats in the United States as well as an estimated 117-157 million domestic indoor and outdoor cats. Management efforts include a nonlethal feeding and sterilization program known as "trap-neuter-release" (TNR) where cats are surgically sterilized and returned to the environment. Population size and structure, immigration rates, spay/neuter rates, and data on spatial use all play a role in whether TNR is a viable management option. This study focuses on population structure and spatial use. To infer the population structure of a population of campus free-roaming cats at the individual level I used pairwise maximum likelihood estimates of relatedness and relationship category (unrelated, half-sib, full-sib, parent-offspring). Home range and movement patterns of domestic free-roaming indoor/outdoor cats were estimated with 100% and 50% adaptive local convex hull and 100% minimum convex polygon for comparison with previous studies. No differences in home range were found between sex, age, and season.
INDEX WORDS: Relatedness, Genetics, Ecology, Felis catus, Home-range, GIS, Thesis, College of Graduate Studies
MOVEMENT IN CATS by
VALERIE PLUMMER
B.S., Georgia Southern University, 2012
A Thesis Submitted to the Graduate Faculty of Georgia Southern University in Partial Fulfillment of the Requirements for the Degree
MASTER OF SCIENCE STATESBORO, GEORGIA
2018
VALERIE PLUMMER All Rights Reserved
MOVEMENT IN CATS by
VALERIE PLUMMER
Major Professor: Michelle Cawthorn Committee: C. Ray Chandler
J. Scott Harrison
Electronic Version Approved: May 2018
TABLE OF CONTENTS LIST OF TABLES ... 3 LIST OF FIGURES ... 4 CHAPTER 1 ... 5 CHAPTER 2 ... 14 Field Methods ... 14 Genetic Analysis ... 14 Data Analysis ... 15
GPS and harness fitting ... 16
Data processing and home range ... 17
CHAPTER 3 ... 19
Kin structure and relatedness ... 19
Movement Data ... 22
CHAPTER 4 ... 27
Kin Structure and Relatedness ... 27
Movement Analysis ... 29
REFERENCES ... 33
APPENDIX A GENOTYPES OF INDIVIDUAL CATS ACROSS NINE LOCI ... 47
APPENDIX B ALLELE FREQUENCIES ... 48
APPENDIX C PID AND PIDsibs PER LOCUS AND ACROSS ALL LOCI .. 49
APPENDIX D GENETIC VARIATION PER LOCUS AVERAGE ... 50
APPENDIX E MATRIX OF RELATEDNESS (RELATIONSHIP) ... 51
APPENDIX F MATRIX OF RELATEDNESS (R) ... 52
LIST OF TABLES
Table 1: Sex, Age, and Reproductive Status... 24
Table 2: Home Range Estimates ... 24
Table 3: Mean Home Range Estimates by Season ... 25
LIST OF FIGURES
Figure 1: Trapping and Feeding Sites ... 20
Figure 2: Relatedness at Feeding Sits ... 20
Figure 3: Proportion of Related Individuals ... 21
Figure 4: Home-range Indicators of an Adult Male ... 23
Figure 5: Female Domestic Free-Roaming Cat with Harness... 23
CHAPTER 1 INTRODUCTION
Biodiversity levels are declining due to habitat loss, pollution, overharvesting, disease, and the spread of invasive species (Wilson, 1992). Approximately 42% of threatened or endangered species are at risk because of invasive species (Wilcove et al. 1998; Pimentel et al. 2004), and economic damages associated with controlling invasive species and their effects amount to approximately $120 billion a year in the United States (Pimentel et al. 2004).
The spread of an invasive species is influenced by landscape structure, dispersal mode, and reproductive mode (Moody and Mack, 1988); multiple introductions are often correlated with the success of invasive species (Barrett and Husband, 1990). Multiple introductions of the Thiarid snail (Melanoides tuberculata) on Martinique showed increasing adaptive potential for traits with each successful invasion (Facon et al. 2008). Other common features of successful vertebrate invaders include a close association with humans, high population numbers, broad diet and an ability to function in a wide range of physical conditions (Ehrlich, 1989). The direct and indirect effects of invasive species are generally negative (Eubanks 2001; Preston et al. 2012). Native to the South Pacific and Australia, predation from the introduced brown tree snake (Boiga irregularis) has led to extirpations of 10 native bird species, 6 native lizard species, and 2 native bat species on the island of Guam (Rodda and Savidge, 2007). Arctic foxes (Alopex lagopus) introduced to the Aleutian archipelago indirectly induced shifts in plant productivity and community structure by preying on local seabirds. A reduction in nutrient transport from ocean to land by seabirds affected soil fertility such that the overall plant composition of the
environment changed from grasslands to dwarf shrub/forb-dominated ecosystems (Croll et al. 2005). Studies of Rattus sp. effects on the soil fertility of offshore islands of New Zealand showed similar indirect effects (Fukami et al. 2006).
Among extant mammal species, 124 (2.6%) have established a self-sustaining wild population in at least one location outside their natural range and are classified as successful invaders (Clout and Russell, 2008). Feral domestic animals (horses, sheep, goats, cats, dogs) with the help of humans are a part of the relatively few mammal species that have successfully established populations at more than 30 locations around the world (Long, 2003). One of the most successful mammalian invaders is the domestic cat (Felis
catus). Listed as one of the '100 world's worst invasive alien species' (Lowe et al. 2000)
there are as many as 70-100 million feral cats in the United States (Jessup, 2004) as well as an estimated 117-157 million domestic indoor and outdoor cats (Dauphine and
Cooper, 2009). Free-roaming cats (both domestic and feral) are efficient predators and are generally found at densities 10-100 times higher than native predators (200-1,500 cats km2: Liberg et al. 2000; Baker et al. 2008) leading to direct impacts on native predators
and native species.
Feral free-roaming cats may survive as lone individuals, or they may be part of “cat colonies”. Typically, cat colonies are considered to be a group of three or more individuals living and feeding in close proximity to one another (Slater, 2004). Colonies may be fully managed (regularly fed, given vaccines, and the population is
spayed/neutered) or semi-managed (regularly fed by a human caretaker), or completely unmanaged. According to Toukhsati et al., (2007), the persistence of many cat colonies is likely due to feeding by humans. However, other than feeding no other veterinary care
such as spaying and neutering is provided (“semi-ownership” behavior) and thus, the number of individuals in the colonies varies over time. The breeding system of Felis
catus is conducive to living in a colony as Felis catus is promiscuous (Wilkins, 2007).
Maternal care can either be done individually or communally with the aid of other mothers in the colony or non-breeder helper cats who provide assistance with grooming and playing with kittens, guarding the nest or providing food to the mother or kittens (Kerby, 1988). Females give birth to two to ten kittens per litter with most mating
occurring during the spring and summer due to increasing daylight (Hildreth et al. 2010), and females can produce up to five litters a year.
All free-roaming cats, including domestic pets, prey on a wide assortment of native birds (Fitzgerald, 1988), mammals, reptiles, and amphibians (Dunn and Tessaglia, 1994; Crooks and Soule, 1999; Baker et al. 2008). Domestic cats and feral cat diets are similar with hunting occurring in both domestic and feral free-roaming cats even though they are given food rations due to natural hunting instincts (Liberg, 1984). Free-roaming cats are estimated to predate 1.3-4.0 billion birds and 6.3-22.3 billion mammals in the United States annually (Loss et al. 2013). In addition to the loss of prey species due to hunting, cats can cause indirect effects on reproductive success of nearby species.The presence of a free-roaming cat at avian nesting sites reduced feeding rates and induced a lethal “trait-mediated indirect” effect (Bonnington et al. 2013). Giving up densities and overall costs of foraging for North American tree squirrels (Sciurus sp., fox/gray) were higher with the persistent presence of cats and dogs (van der Merwe et al. 2007). Cat presence also altered the foraging behavior of the dusky hopping-mouse (Notomys
Prolific reproduction with early reproductive maturity (as early as six months of age), relative ease of habitat acclimation, and an innate desire to hunt all make the free-roaming cat a successful invasive species.
Oceanic islands have provided many examples of the negative ecological impacts of free-roaming cats (Nogales et al. 2004). Australia has seen a high rate of native
mammal decline. Approximately 33% of all mammals and about 90% of medium-sized mammals are either extinct or have seen range contractions in Australia (Burbidge and McKenzie, 1989) and feral cats are widely seen as a significant threat to native fauna and native fauna conservation. In New Zealand, the extinction of the Stephen’s Island Wren (Xenicus lyalli) is widely attributed to feral cats. The species was never observed in the wild and most of the museum specimens collected came from a single cat (Dickman 1996; Fuller 2001).
Previous studies of cat predation have used homeowner reports of prey type and frequency (Lepczyk et al. 2003; Woods et al. 2003; Baker et al. 2008). However, Lloyd et al. (2013) quantified domestic cat predation using collar cameras and found that less than a quarter of cats brought back prey to their residence, suggesting previous homeowner reports had vastly underestimated the totality of cat predation. Thus, detailed
observations of cats in the field and a description of what and how many prey they kill are essential to understanding the extent of predatory behavior among free-roaming cats (Woods et al. 2003).
As our understanding of the overall effects free-roaming cats exert on the
environment and other organisms increases there has been a push for the improvement of management protocols for cat populations in communities across the United States and
worldwide. Management efforts through both lethal (shooting, trapping, poisoning, hunting) and non-lethal (biological control, exclusion fencing) methods have all been used in Australia as the native fauna are imperiled (Biodiversity Group Environment Australia, 1999). However, these methods are seen as expensive and time-consuming endeavors (Environment Australia, 2001). Lethal methods such as "trap and euthanize" have been met with opposition from various animal rights groups and the public (Perry and Perry, 2008). Feline panleukopenia, a virus that primarily attacks the gastrointestinal system, has been introduced into feral populations on the islands of Jarvis and Marion and may be effective according to models (Nogales et al. 2004). Poisoning through oral grooming could potentially be used in the near future (Read, 2010). After many failed attempts at using a fox/dog baiting strategy, a highly effective baiting technique using poison laced sausages showed an increase in mortality rates close after bait application and has been used to eradicate feral cats from two islands off of the Australian coast (Algar and Burrows, 2004). In the short term, lethal methods tend to rapidly depopulate cat colonies but they rarely prove to be effective in the long term when colonies are located on mainland areas (Nutter, 2005). A constant supply of cats from ill-informed owners ensures complete eradication is nearly impossible.
Non-lethal management methods include a feeding and sterilization program known as "trap-neuter-release" (TNR) where cats are surgically sterilized and returned to the environment (Dauphine and Cooper, 2009). Using mathematical models, Andersen et al. (2004) reported effective population control with the neutering of more than 75% of the population or the removal of at least 50% of the population. Wallace and Levy,
(2006) suggest more ovariohysterectomies than castrations should be performed due to the predominance of intact females being caught in TNR programs in the United States.
Many factors determine whether TNR will work in a specific circumstance. Population size and structure, immigration rates, spay/neuter rates, and data on spatial-use all play a role in whether TNR is a viable option for a group of cats. Feral cat management according to Stoskopf (2004) should not be a “one size fits all” concept especially since cats are such an adaptable species. This suggests the most successful management programs will collect data about the factors presented above, especially population size and structure prior to implementing a management protocol.
Characterizations of population structure of a species can be useful in many contexts and is important for understanding the effects of various processes on populations (Millar and Libby, 1991). Molecular methods of identifying population structure can be a tool for the management and ecology of wildlife, especially when paired with behavioral, demographic, or spatial information (DeYoung and Honeycutt, 2005). Identifying population structure through molecular means is valuable when trying to define significant units of management and conservation (Moritz et al. 1996)
especially for species that are elusive, migratory, or continuously distributed (DeYoung and Honeycutt, 2005).
Multiple factors can influence allele frequency and diversity including
bottlenecks, founders events, migration, and population size fluctuations. A decrease in genetic variability is expected to be related to a decrease of population size (Chakraborty and Nei, 1977). There is large variability in mating tactics within and between
populations of the same species (Lott, 1991) and mating systems and dispersal both have impacts on genetic variability within populations.
Microsatellite loci, a specific sequence of DNA base repeats, have been used in the analysis of natural populations and provide a greater understanding of population structure (Slatkin, 1995). They can also be used to identify population attributes such as relatedness for sensitive or elusive animals (DeYoung and Honeycutt, 2005). A relatively easy and minimally invasive method to acquire DNA samples is through hair collection where samples can be directly obtained from a mammal (Higuchi et al. 1988), or collected as shed hair (Morin et al. 1993). Another source of DNA are fecal samples (Hoss et al. 1992). While more DNA is found in fecal samples (Broquet et al. 2007), fresh hair provides higher quality DNA samples versus the other methods (Valderrama et al. 1999). Hair samples have been used for molecular studies of a wide array of animals including grizzly bears (Mowat and Strobeck, 2000), black bears (Boerson et al. 2003), American martens (Pauli et al. 2008), chimpanzees (Morin et al. 1993) and feral cats (Anile et al. 2012).
Suburban and campus environments serve as habitats to a wide array of
mammals, reptiles, and amphibians as well as resident and migratory songbirds and birds of prey (Crooks, 2002) and they support local and regional diversity (Angold et al. 2006; Tratalos et al. 2007). Concerns about depredation of wildlife by free-roaming cats should extend to these environments (Longcore et al. 2009) because suburban and campus environments contain fragmented “islands” of natural habitats surrounded by roads and development (Crooks 2002) that can act as barriers to wildlife movement. This is especially important because cat abundance generally increases with increasing habitat
fragmentation (Crooks 2002), and cat predation is particularly influential in insular habitats (Nogales et al. 2004). Abundant food sources, like dump and feeding sites, tend to increase cat survival and population density and subsidized colonies may serve as source populations for surrounding areas (Schmidt et al. 2007).
Georgia Southern University has an issue with feral cat management. To date, management decisions have been primarily led by disjointed public efforts. Data on the current population structure of these cats are unknown and population estimates vary widely from 20 to 40 individuals. There are several discrete feeding stations scattered throughout campus that have varying degrees of management. Feeding stations, dumpsters near academic buildings, and drains tend to have a higher number of cats present. The spatial ecology of these animals also needs further investigation and how individuals occupy and use the campus environment specifically is largely unclear.
This study aims to build upon what is known about both feral and domestic free-roaming cat behavior and biology by investigating the relatedness of feral free-free-roaming individuals and the movement and spatial-use of domestic free-roaming cats.
First, I studied a population of feral free-roaming cats (n=24) to obtain data on the degree of relatedness between individuals. In order to assess the population structure of free-roaming cats in this area, I calculated pairwise relatedness values and the likelihood of two individuals being first-ordered relatives (full-siblings, parent-offspring), second-order relatives (half-siblings) or unrelated to address these questions: 1) What is the relatedness of adult males in this population? 2) What is the relatedness of adult females in this population? And 3) are related individuals utilizing the same feeding stations? Since free-roaming cats exhibit male-biased dispersal and sociality in free-roaming cats is
based on females, their relatives, and kittens (Turner, 2000), I predict males will have a lower degree of relatedness relative to adult females. Social groups in free-roaming cats form around abundant and rich resources like feeding stations (Macdonald et al. 1987; Mirmovitch, 1995; Liberg et al. 2000) and individuals are more likely to tolerate and share resources with kin (Hamilton, 1964) therefore I predict to see kin structure at feeding stations.
Second, I estimated the home ranges and movement patterns of owned free-roaming cats in order to gain a better understanding of how cats use and occupy suburban environments. With GPS tracking data, I aim to address these questions about the spatial-use of domestic cats: 1) Do home range sizes vary by sex? 2) Does season affect home range size? And 3) Do domestic cats move more diurnally or nocturnally? I predict home ranges will vary by sex with males having a larger home range due to male biased
dispersal (Turner, 2000) and I predict a larger home range size in warmer seasons with more movement occurring nocturnally.
CHAPTER 2 METHODS
Field Methods
I studied a population of free-roaming cats located in Statesboro, Georgia (32.4453° N, 81.7792° W) (Figure 1). I trapped cats 2 to 3 days a week from dusk until sunrise from March 2014 - January 2016 (IACUC Protocol I13011/I16008). Using a humane trap (large 32”x10”x12” and extra-large 42”x15”x15” Havahart traps,
Woodstream Corporation, Litiiz, PA) I baited traps with sardines and cat food. A total of 27 cats were captured for this study. Trapping locations were selected prior to trapping via camera trapping and visual confirmation of the presence of cats. After low trap success, I deployed a targeted trapping approach at known feeding stations (Figure 1). To prevent unnecessary mortality, I was present when any trap was deployed and the total time in the trap for the cat never exceeded 30 minutes. Approximate age (adult, juvenile, kitten), physical description, and sex (if possible) were recorded at the time of capture. Wearing gloves, I collected approximately 20 hairs with forceps through the trap to maximize hair follicle collection for analysis. All samples were placed in small, labeled envelopes and stored at room temperature at Georgia Southern University.
Genetic Analysis
To maximize DNA extraction hair follicles in each sample were separated from the shaft using a disposable razor blade. DNA was extracted from 5-10 hair follicles using a Qiagen DNeasy Blood and Tissue kit following the suggested protocol of the manufacturer. I used polymerase chain reaction (PCR) to amplify DNA at 10
(FCA 733, FCA 723, FCA 731, FCA 441, FCA 736, F 124, SRY, FCA 742, FCA 740, and F 85) were selected from a forensic panel (Menotti-Raymond, 2005). Amplifications were performed in 20 uL reaction volumes containing 6 uL of DNA, 4 uL cat primer mix, and 10 uL of 2X Apex Taq Polymerase Master Mix with final reaction concentrations of: 1.5 mM magnesium chloride (MgCl2), 200 uM of four deoxyribonucleoside
5’-triphosphates (dATP, dCTP, dGTP, and dUTP), 2.0 units of DNA polymerase, and 0.16 mg/mL bovine serum albumin. In order to allow for multiplexing, the markers were labeled with blue (6-FAM) (FCA 733, FCA 723, FCA 731), green (VIC) (FCA 441, FCA 736, F 124, SRY), and yellow (NED) (FCA 742, FCA 740, F 85) fluorescent dyes at the five prime end of the reverse or forward primers distinguishing alleles and loci that overlapped in size. Thermal cycling conditions were taken from Menotti-Raymond et al. 2005 and performed with the GeneAmp 9700. PCR products were visualized on a 2% agarose gel.
PCR products were combined with an internal size standard and fragment analysis was performed on an ABI 3500 Genetic Analyzer (Applied Biosystems). Genotypes were scored using GeneMapper software v4.0 (Applied Biosystems). Alleles were binned by hand and checked for null alleles and scoring errors with Micro-Checker (Van Ooserhout et al. 2004).
Data Analysis
To assess the differentiation power of the 10 marker panel (without the SRY marker) the probability of identity (PID) was calculated (Waits et al. 2001). The
probability of identity with the presence of siblings (PID-sib), defined as the probability that two randomly drawn sibling individuals from a population have the same multilocus
genotype, was also calculated. PID-sib is a conservative upper limit of the possible ranges for observing identical multilocus genotypes since PID estimates tend to be lower than observed PID in wildlife populations (Waits et al. 2001).
To determine the likelihood individuals are related I used the program ML-Relate (Kalinowski et al. 2006). The program calculates maximum likelihood estimates of relatedness (r) and relationship for codominant genetic data like microsatellites or single nucleotide polymorphisms (SNPs). The coefficient of relatedness is the probability of two individuals inheriting an allele identical by descent from a common ancestor. Relatedness values range from 0 to 1. R values greater than 0 indicate increasing relatedness. For relationship estimates (unrelated, half-sibling, full-sibling, parent-offspring) each pair is given a likelihood ratio for a null (Ho) vs. an alternative hypothesis (i.e not related vs. related). Each hypothesis has two variables, Rm (relatedness maternal) and Rp
(relatedness paternal) that define the probability that two individuals (dyads) share an allele by direct descent from their mother or father. Three alternative hypotheses were tested: dyads are half siblings, full siblings, or parent-offspring.
I calculated the relatedness of all adult males and all adult females in the study separately. Kin structure analysis was done at feeding stations where more than 3 individuals were caught (n=3). All relatedness values are presented as the mean ± standard error.
GPS and harness fitting
Research on domestic cat movement was carried out in Statesboro, GA (32.4453° N, 81.7792° W) during 2013 – 2016 (IACUC Protocol I13011/I16008). The subjects of this study were adult house-based domestic cats. Owners in the study area were contacted
and asked to participate in the study beginning in December of 2013. A total of eight spayed/neutered (at least one year prior to the beginning of the study) cats (3 F, 5 M) were tracked. The mean approximate age of the domestic cats used in this study was 6.3 years (Table 1). After acquiring permission from the cats’ owners, I fitted each animal with a waterproof GPS (CatTrack, Perthold Engineering, USA) that was attached to a backpack-style harness (Figure 5). As a safety measure, the harness was designed with a release clip that unfastened when pulled. The GPS unit weighed 22g and was well below the 5% weight limit for each cat (Sikes et al. 2011). Cats were given at least 30 minutes to acclimate to the GPS and harness. A location was recorded in 5-minute intervals. I chose this fixed time period to investigate fine-scale movement. When a location fix was unable to be recorded, the unit would not record until a signal was re-established.
Each cat was tracked for up to eight 24-h periods. No cat was tracked multiple times or within different seasons. For the welfare of the cat, owners monitored their cats during deployment and if distress was observed the units were removed immediately.
Data processing and home range
Data recorded on the GPS data loggers included the date, time, longitude, latitude, altitude, speed, direction, and distance moved by the cat. Before data analysis in ArcGIS (Version 10.3) location points from the first 30 minutes were removed to account for harness fitting and re-adjustment time. To define significant movement, the average distance between two movement points was calculated and any distance below each cat’s average distance was removed. I estimated home ranges using 100% and 50% adaptive local convex hull (aLoCoH). This nonparametric kernel method has been shown to be a better fit for home range estimation due to its ability to identify boundaries in the
environment and for convergence to the true distribution as sample size increases (Getz et al. 2007). For comparison with previous studies, home range was also estimated using 100% minimum convex polygons (MCP) calculated using ArcGIS software. Points were classified as occurring diurnally or nocturnally by the sunrise and sunset time each day. Total distance traveled per day and total mean distance traveled per tagging period were also calculated.
To normalize data, home range estimates were log10 transformed. A t-test was used to test for differences in home range size for each of the estimators (aLoCoH, MCP) by sex. The effects of sex and age on home range size were evaluated using an
ANCOVA. Seasonal effects on home range size were calculated using the Kruskal-Wallis test. Diurnal and nocturnal movement data met normality and equal variance assumptions and were tested for significance using a paired t-test. All data analyses were done using JMP (12th edition).
CHAPTER 3 RESULTS
Kin structure and relatedness
Out of 27 hair samples collected, DNA was extracted from 24 individuals (20 males, 4 females). The sex ratio of caught individuals in this study is highly skewed to males. All microsatellites were polymorphic and the number of alleles per locus ranged from 5-16 (average = 8.667±1.155). Observed and expected heterozygosity was
0.662±0.070 and 0.748±0.048 (ns). The combined probability of identity (PID) using 9 loci is 1.4x10-10 and the PID-sib value is 2.5x10-04. Heterozygote deficiencies were found
in 4 loci (FCA731, FCA 736, F124, and FCA740).
I assessed relatedness at feeding stations where more than 3 individuals were trapped (Math/Physics, COBA, and Marvin). Mean relatedness at the Math/Physics (n=5), COBA (n=5) and Marvin (n=5) feeding stations were 0.102±0.037, 0.103±0.042 and 0.338±0.056 respectively. In this population (n=24) overall, adult males had a mean relatedness of 0.062 ±0.029 while females had a mean relatedness of 0.065±0.065.
Unrelated individuals made up 68% of the individuals found at feeding stations, followed by 17% of first-order relatives (full siblings, parent-offspring) and 14% of second-order relatives (half siblings). First-order relatives had a mean relatedness of 0.44±0.03ranging from 0.338 to 0.6925. Second-order relatives had a mean relatedness of 0.27±0.04 and relatedness values ranged from 0.1467 to 0.397. Unrelated individuals had a mean relatedness of 0.063±0.014 with relatedness values ranging from 0 to 0.3257. No parent-offspring pairs were found at any of the feeding sites.
Figure 1 - Trapping and feeding sites located around Georgia Southern University in Statesboro, Georgia. Circled stars indicate the three main feeding stations.
Figure 2 – Relatedness values at the three feeding stations sampled. 0
0.1 0.2 0.3 0.4
Math/Physics COBA Marvin
Re lat ed n es s (r) Feeding Station n=5 n=5 n=5 n=5 n=5 n=5 n=5 n=5 n=5
a) b) 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
First Order Second Order Unrelated
Pro p o rtio n o f Re lat ed Dy ad s Degree of Relationship 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
First Order Second Order Unrelated
Pro p o rtio n o f Re lat ed Dy ad s Degree of Relationship
c)
Figure 3 – Proportion of related individuals at a) Math/Physics b) COBA c) Marvin by first-order (full-siblings, parent-offspring), second-order (half-siblings) and unrelated relationship.
Movement Data
Between 318 and 625 locations were recorded per individual. Over the course of this study, home range sizes ranged from 2.90 ha to 35.98 ha per cat. No significant differences were found in home range size by sex (Table 1) for any of the home range estimators (ns). There were no significant effects of sex or age on home range size estimators (ns). Since no significant differences between sex or age were found males and females were combined for seasonal analysis. I found no seasonal difference (Figure 7) between home ranges (ns) or diurnal and nocturnal movement (ns). Mean distance traveled per day (Table 3) varied from 1.45 km to 5.12 km with an overall mean of 3.10 km ±0.418 and showed no statistical differences in sex (ns).
0 0.1 0.2 0.3 0.4 0.5 0.6
First Order Second Order Unrelated
Pro p o rtio n o f Re lat ed Dy ad s Degree of Relationship
Figure 4 – Minimum convex polygon, 50% aLoCoH and 100% aLoCoH of an adult male cat in Statesboro, Georgia.
Table 1: Sex, reproductive status, and approximate ages of owned free-roaming cats used to determine home ranges in Bulloch County, GA.
Table 2: Home range estimates by sex (ha; 100% adaptive local convex hull (aLoCoH), 50% aLoCoH, 100% minimum convex polygon) for owned free-roaming cats in Bulloch County, GA. Untransformed means are presented along with the log10 transformed means and standard error (SE).
Home Range Estimator Sex Mean Mean
log SE M 7.9021944 0.85121 ±0.16649 F 18.314094 1.0749 ±0.21494 M 0.1735374 -0.8436 ±0.18102 F 0.188509 -0.98578 ±0.23369 M 15.791953 1.13962 ±0.16187 F 34.306826 1.39246 ±0.20897 100% aLoCoH 50% aLoCoH 100% MCP
Table 3: Mean home range estimates by season (spring, summer, winter) for domestic free-roaming cats in Statesboro, GA. a) 100% aLoCoH b) 50% aLoCoH c) 100% MCP.
Figure 6: Domestic free-roaming cat diurnal and nocturnal movement events. Area (ha) 100% aLoCoH 50% aLoCoH 100 % MCP Spring 4 9.45 0.18 20.869801 Summer 2 5.35 0.08 16.73 Winter 2 22.97 0.28 32.47 Mean 12.59 0.18 23.35 Season N 0 50 100 150 200 250 300 Diurnal Nocturnal N u m b e r o f Lo cation s Time of Day
Table 4: Total tracking duration in days, total linear distance traveled in km, and mean distance traveled in km for each cat.
Cat ID Total Tracking Duration (days) Total Distance Trave lle d (km) Me an Distance Trave lle d (km) 1 7 25.84791 3.23098 2 7.8 46.1103 5.12336 3 8 19.88664 2.20962 4 7.4 11.6211 1.45263 5 8.5 38.55547 4.28394 6 6.7 17.57074 2.5101 7 5.2 15.37243 2.56207 8 4 17.44899 3.48979 Me an 6.825 24.0516975 3.10781125
CHAPTER 4 DISCUSSION
Kin Structure and Relatedness
Kin structure and dispersal have important consequences for social behavior and genetic structure (Clutton-Brock and Lukas, 2012). In most promiscuous species of mammals, males are the predominant dispersers while in monogamous species dispersal is not skewed towards one sex or the other (Dobson, 1982). Dispersal in feral free-roaming cats follows the pattern of most mammals where males tend to be the sex that disperses while females are the philopatric sex (Turner, 2000). Female dispersal, however, has been previously documented in urban feral cat colonies (Devillard et al., 2003) where the driving force for mature female dispersal was local resource competition for quality den sites. When social groups contain more than one breeding female (plural breeders) and cooperative interactions are common, most females in that group tend to be related (Sterck et al., 1997) so it is expected free-roaming cats are more related among females and not males.
Results indicate that adult males in this population had a low mean relatedness. Low relatedness among males of a promiscuous species is expected due to male-biased dispersal. Of the 4 females caught only one dyad was related and they were found in different places on campus (Math/Physics and COBA). Spatial-use data on these two individuals could potentially reveal shared home ranges. The sampling of more males than females in this study could be attributed to male-biased dispersal behavior. Further trapping of individuals, especially females, is needed to accurately assess relatedness in this population.
Two out of the three feeding stations sampled had low relatedness values (Math/Physics and COBA) with unrelated individuals making up the majority of each colony. Both Denny et al. 2002 and Shreve, 2014 reported low relatedness values within their study colonies. The male-biased sex ratio could have contributed to the lower levels of relatedness observed at these colonies. The Marvin feeding station however had a higher level of relatedness among individuals caught (0.338±0.056) potentially leading to more group affiliative behaviors. This feeding station could be a periphery colony since it is located on the other side of a major road. The road could be a barrier to individual movement and that could explain the higher observed relatedness values of this feeding station. If food is dispersed and highly available, like the feeding stations found on and near campus, cats may not have to compete as fiercely for access and may choose to eat alone or near relatives (Bradshaw and Hall, 1999).
Previous studies on the effects of TNR on feral cat populations indicates at least 50-75% of the population should be neutered to reduce population numbers and 90% to offset immigration (Anderson et al. 2004). Some cats are resistant to trapping, as experienced in this study, and a large amount of abandonment happens on or near the campus environment making 90% or 100% neutering difficult. In Rome, where there has been a law mandating the use of TNR programs for a little over 10 years, there has been a slight decrease in population numbers, but the immigration rate remains high at around 21% (Natoli, 2006), resulting in the necessity of continuing intense efforts of TNR, which is costly in terms of both economics and time. Without proper education efforts regarding the behavior and ecology of feral and free-roaming cats and a clear organized campus and
public effort unwanted cats will be abandoned negating the results TNR programs may produce.
Movement Analysis
Much of the research on the spatial ecology of Felis catus and other mammals utilized very-high-frequency (VHF) radio transmitters. VHF technology requires receivers to be close enough to triangulate the position of the animal requiring
researchers to be in close proximity, potentially altering animal behavior (Cagnacci et al. 2010). The alternative to VHF tracking used in this study is the use of a global
positioning system (GPS). GPS tracking allows for the collection of animal positions in remote and poorly accessible areas and during all periods of time and weather conditions while avoiding altered animal behavior due to researcher proximity (Recio et al. 2011). In the beginning of GPS development, devices were only suitable for tracking large animals due to the relatively large receiver and collar. Recently, improvements in battery life and device size have been developed to track a wider range of animals including hedgehogs, possums, and feral cats (Recio et al. 2011).
Effective free-roaming cat population control strategies should include a broad understanding of how they occupy and move through the environment (Bengsen et al. 2012) especially in areas with high conservation value. Spatial information can aid in predicting the efficiency of different control strategies (Alterio et al. 1999) which include the method of control, frequency of control efforts, and any costs associated with control.
The majority of studies concerning Felis catus focus on feral free-roaming cat movement patterns and spatial-use (Liberg 1980; Mirmovitch 1995; Schmidt et al. 2007; Recio and Seddon, 2013; Kitts-Morgan et al. 2015). Several studies have included domesticated free-roaming cat home ranges and generally report smaller home range
sizes for domestic cats (Schmidt et al. 2007; Horn et al. 2011) than feral free-roaming cats.
Home range sizes were highly variable among individuals in this study and did not show statistical differences (Table 2). None of the cats were close enough in proximity to have overlapping home ranges. The density of cats in the area and habitat composition may factor into home range determination. In feral free-roaming cats
increasing urbanization and density of cats tend to decrease home range size and if that is the case for domestic cats further investigation into multiple cat households and
neighborhoods could shed a light on the determinants of home range size and use. This also poses a management issue since a decrease in cat density could increase overall home ranges of the cats left in the environment (Thomas et al. 2014) and increase the probability of mortality and disease.
Home ranges of female cats were not significantly different than male cats in this study (Table 1) although the youngest female cat in this study had the largest home range size (35.91 ha) and the largest core home range size (0.46 ha). Younger cats in other studies, however, tended to have smaller home ranges (Hervias et al., 2014). Reports of significantly different home ranges vary with some previous studies reporting no difference in home range size between males and females (Hall et al. 2000; Horn et al. 2007). Other studies indicated males tend to have a larger home range than females (Liberg 1980; Langham and Porter 1991; Liberg 2000) much like feral free-roaming cats (Schmidt et al. 2007). Since all the cats were spayed/neutered, reproductive strategies of space use do not seem to be a driving factor in home range determination in this study. Domestic free-roaming cats are an interesting case because they are provided with food
and shelter and owners residences are a focal point in their home ranges (Thomas et al. 2014). Major roads might be more of a barrier to movement for cats in this area as no major roads were crossed by any cat in this study.
Future Directions and Conclusions
TNR programs have been implemented on several university campuses in the United States and abroad with varying success including the University of Central Florida, Stanford University, Auburn University, Arizona State University, Texas A&M at College Station and the University of West Georgia. An evaluation of TNR programs on the University of Central Florida campus found an overall reduction of feral cat populations over an 11-year period with TNR programs in place (Levy et al. 2003). TNR programs remain controversial for most campuses. Since feral cats are known to hunt even with access to supplemental food (Hutchings, 2003) the benefits of feeding stations, however, are to the cats only and not to reduction population or predation rates (Jones and Downs, 2011). Feral free-roaming cats are also the definitive host for Toxoplasma
gondii, which is linked to birth defects in humans and they carry other zoonotic diseases
that are of increasing concern to colony caretakers and the community.
The Wildlife Resources Division of the Georgia Department of Natural Resources has feral cats listed as priority three invasive species falling behind priority one species like the feral swine (Sus scrofa) and the Coyote (Canis latrans). Nationally, Georgia ranks 8th in the number of imperiled species and 4th in known or suspected extinctions
(Stein et al. 2000). Sustained monitoring of predation rates and population numbers with sterilization is needed to determine if the effectiveness of TNR will outweigh its potential
costs especially since colony managers tend to underestimate the number of cats present (Jones and Downs, 2011). Since feral cats are known to hunt even with access to
supplemental food (Hutchings, 2003) the benefits of feeding stations are to the cats only and not to reduction population or predation rates (Jones and Downs, 2011).
In group-living mammals, individuals are more likely to associate, display affiliative behaviors, and display less agonistic behaviors with kin over non-kin. Social organization can influence contact among individuals and the distribution and spread of disease (Blanchong et al. 2007; Cross et al. 2009). Collecting spatial-use data in
conjunction with social behavior data can help model how diseases move through these populations (Sanchez, 2012) and aid in management decisions for this controversial species.
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APPENDIX A
GENOTYPES OF INDIVIDUAL CATS ACROSS NINE LOCI
KH012 183 183 252 284 342 366 131 135 167 183 292 292 155 159 268 288 318 318 KH016 179 207 284 288 338 342 131 131 167 169 268 268 268 159 244 288 314 318 KH017 179 179 248 272 346 350 127 131 171 171 272 280 123 143 244 264 318 318 KH018 179 207 274 284 342 366 131 131 167 169 268 268 123 159 204 288 318 330 KH019 179 179 248 256 350 366 123 127 183 183 272 304 143 155 272 292 314 318 KH020 179 207 252 272 366 366 119 135 167 201 280 292 147 155 204 288 314 318 KH002 183 207 248 276 342 342 131 131 171 175 292 296 143 143 238 296 318 318 KH21 179 207 244 276 342 370 123 131 183 183 272 276 127 159 276 292 322 330 KH22 179 179 256 272 346 350 127 127 183 183 272 280 123 155 182 272 318 318 KH23 191 207 244 288 346 366 127 131 171 171 268 296 123 143 244 296 314 326 KH24 179 207 268 272 338 346 127 127 171 171 280 296 123 143 244 296 314 318 KH25 179 207 256 268 342 346 127 131 171 171 272 292 123 155 204 268 318 318 KH27 179 207 256 268 342 370 127 135 205 205 292 296 123 147 204 296 318 318 KH28 179 179 256 284 342 342 127 135 167 167 284 296 155 159 266 288 318 318 MA003 179 179 256 262 350 350 131 131 175 175 272 296 147 147 244 244 318 318 MA004 179 179 256 256 350 394 119 131 171 171 272 296 155 163 244 282 338 338 MA005 179 179 262 274 346 394 119 131 175 179 272 296 147 163 188 282 338 338 MA006 179 179 256 256 346 394 119 131 183 201 260 260 147 163 245 245 318 318 MA007 179 179 262 274 346 346 119 131 175 175 272 296 147 163 188 282 318 337 MA009 187 191 256 274 346 346 127 131 179 183 260 284 147 163 244 244 318 318 MA010 179 179 256 256 346 346 119 131 167 179 296 296 147 163 238 244 338 338 MA013 179 179 256 262 346 350 131 131 171 171 272 296 147 163 272 296 318 318 MA014 179 179 272 278 354 354 119 123 169 183 296 296 147 163 262 296 318 338 MA015 179 179 256 262 346 346 131 131 171 179 272 296 147 163 272 296 318 318 FCA 742 F 85 FCA 740
LOCI
SampleAPPENDIX B ALLELE FREQUENCIES
Locus Allele/n Locus Allele/n Locus Allele/n Locus Allele/n FCA 733 N 24 FCA 441 N 24 FCA 742 N 24 FCA 740 N 24
179 0.688 119 0.146 123 0.146 314 0.104 183 0.063 123 0.063 127 0.021 318 0.646 187 0.021 127 0.229 143 0.125 322 0.021 191 0.042 131 0.479 147 0.271 326 0.021 207 0.188 135 0.083 155 0.146 330 0.042 FCA 723 N 24 FCA 736 N 24 159 0.104 338 0.167 244 0.042 167 0.146 163 0.188 248 0.063 169 0.063 F 85 N 24 252 0.042 171 0.292 182 0.021 256 0.313 175 0.125 188 0.042 260 0.104 179 0.083 204 0.083 268 0.063 183 0.208 238 0.042 272 0.188 201 0.042 244 0.250 276 0.063 205 0.042 262 0.021 284 0.083 F 124 N 24 264 0.021 288 0.042 260 0.063 266 0.021 FCA 731 N 24 268 0.104 268 0.042 338 0.042 272 0.229 272 0.083 342 0.208 276 0.021 276 0.021 346 0.333 280 0.083 282 0.063 350 0.146 284 0.042 288 0.104 354 0.042 292 0.125 292 0.042 366 0.125 296 0.313 296 0.146 370 0.042 304 0.021 394 0.063
APPENDIX C
PID and PIDsibs PER LOCUS AND ACROSS ALL LOCI
Population N FCA 733 FCA 723 FCA 731 FCA 441 FCA 736 F 124 FCA 742 F 85 FCA 740
PID
24
3.0E-01
4.5E-02
6.5E-02
1.4E-01
5.5E-02 6.0E-02 5.5E-02 2.5E-02 2.5E-01
PIDsibs
24
5.8E-01
3.5E-01
3.7E-01
4.4E-01
3.5E-01 3.6E-01 3.5E-01 3.2E-01 5.4E-01
Population N FCA 733 FCA 723 FCA 731 FCA 441 FCA 736 F 124 FCA 742 F 85 FCA 740
PID
24
3.0E-01
1.4E-02
9.0E-04
1.3E-04
6.9E-06 4.1E-07 2.3E-08 5.7E-10 1.4E-10
PIDsibs
24
5.8E-01
2.0E-01
7.4E-02
3.3E-02
1.2E-02 4.2E-03 1.5E-03 4.6E-04 2.5E-04
PID and PIDsibs by Locus
APPENDIX D
APPENDIX E
MATRIX OF RELATEDNESS(RELATIONSHIPS)
CAT KH012 KH016 KH017 KH018 KH019 KH020 KH002 KH021 KH022 KH023 KH024 KH025 KH027 KH028 MA003 MA004 MA005 MA006 MA007 MA009 MA010 MA013 MA014 MA015
KH012 -KH016 HS -KH017 U U -KH018 HS FS U -KH019 U U HS U -KH020 HS U U HS U -KH002 HS U U U U U -KH021 U U U U HS U U -KH022 U U FS U PO U U U -KH023 U HS U U U U U U U -KH024 U U PO U U U U U HS FS -KH025 HS U U U U U U U U U HS -KH027 U U U U U U U U U U HS FS -KH028 HS HS U HS U U U U U U U U U -MA003 U U U U U U U U U U U U U U -MA004 U U U U U U U U U U U U U U U -MA005 U U U U U U U U U U U U U U HS FS -MA006 U U U U U U U U U U U U U U U HS U -MA007 U U U U U U U U U U U U U U FS HS FS U -MA009 U U U U U U U U U U U U U U U U U FS U -MA010 U U U U U U U U U U U U U U U FS FS HS HS HS -MA013 U U U U U U U U U U U U U U FS HS U U HS U U -MA014 U U U U U U U U U U U U U U U U HS U U U U U -MA015 U U U U U U U U U U U U U U FS U HS U FS U HS FS U
