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Exurban Feral Cat Seroprevalence of Feline Leukemia and Feline Immunodeficiency Viruses and Adult Survival
Catherine M. Normand and Rachael E. Urbanek

Southeastern Naturalist, Volume 16, Issue 1 (2017): 1–18

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Southeastern Naturalist 1 C.M. Normand and R.E. Urbanek 22001177 SOUTHEASTERN NATURALIST Vol1.6 1(61,) :N1–o1. 81 Exurban Feral Cat Seroprevalence of Feline Leukemia and Feline Immunodeficiency Viruses and Adult Survival Catherine M. Normand1,2,* and Rachael E. Urbanek1,3 Abstract - Feral Felis catus (Domestic Cat) can potentially transmit feline leukemia virus (FeLV) and feline immunodeficiency virus (FIV) to other species, but seroprevalence research in exurban areas is sparse. We quantified seroprevalence of FeLV and FIV and estimated adult survival for feral Domestic Cats in an exurban city. We tested 55 cats from developed and natural habitats for FeLV and FIV and fit 31 adult cats with radiocollars for known-fates survival analysis. Combined seroprevalence (FeLV or FIV or both; 32.73%) did not differ by sex, habitat at capture location, or body condition. Annual survival was 0.86; male cats had a greater survival rate than females. Seroprevalence of FeLV and FIV in this study was greater than rates reported in other studies in the US, indicating that seroprevalence studies should be conducted at local scales. Introduction Feral Felis catus (Domestic Cat, hereafter Cat) have the potential to carry and transmit diseases and parasites to domestic pets, humans, and other wildlife (Andersen et al. 2004, Levy and Crawford 2004, Mitchell and Beck 1992, Nutter et al. 2004a, Schmidt et al. 2007). Among the most common infectious diseases of Cats are the retroviruses feline immunodeficiency virus (FIV) and feline leukemia virus (FeLV), both of which cause immunosuppression in Cats and occur worldwide (Lee et al. 2002, Little 2005). Transmission of FIV is highly associated with territorial fighting behaviors of intact male Cats (Lee et al. 2002), but also has potential for venereal transmission (Little 2005). The major modes of FeLV transmission are grooming behavior (Fromont et al. 1997), milk, blood, and urine. Kittens are more susceptible to FeLV infections than adults (Lee et al. 2002). Transmission of FIV from one species to another is rare; however, FeLV has been identified in populations of the endangered Puma concolor cougar (Kerr) (Florida Panther) and the critically endangered Lynx pardinus (Temminck) (Iberian Lynx) (O’Brien et al. 2012). It is unknown how these felids first contracted FeLV, but contact with or consumption of an infected Domestic Cat are the leading hypotheses (Clarke and Pacin 2002). Epidemiologic studies conducted in Florida and North Carolina estimated FIV and FeLV prevalence in feral Cats at 3.5% and 4.3%, respectively (Lee et al. 2002), but infection rates vary regionally (Little 2005). For instance, feral populations may 1Department of Biological Sciences, Arkansas Tech University, 1605 Coliseum Drive, Russellville, AR 72801. 2Current address - Louisiana Department of Wildlife and Fisheries, 2415 Darnall Road, New Iberia, LA 70560. 3Current address - Department of Environmental Studies, University of North Carolina Wilmington, 601 South College Road, Wilmington NC 28403. *Corresponding author - cnormand@wlf.la.gov. Manuscript Editor: Roger Applegate Southeastern Naturalist C.M. Normand and R.E. Urbanek 2017 Vol. 16, No. 1 2 have similar infection rates for both viruses, or one virus may be disproportionately more prevalent than the other in the same population (Lee et al. 2002, Little 2005). Within the same area, infection rates can vary widely between categories (i.e., feral, stray, and free–roaming) of populations or among populations of the same category (Little 2005, Natoli et al. 2005). A coarsely grained regional study of feral, stray, and free–roaming Cats tested in veterinary clinics in North America identified seroprevalence in the South (including Puerto Rico and all continental US states south and east of Oklahoma, Arkansas, Kentucky, West Virginia, Maryland, and Delaware) at 2.3% for FeLV and 2.9% for FIV (Levy et al. 2006). A finer-grained study that examined FeLV and FIV patterns by state across the USA occurred during 2000 –2011 (Chhetri et al. 2013). Chhetri et al. (2013) obtained 47,125 positive FIV/ FeLV test results from across the contiguous USA, but they did not have precise information on the category (i.e., feral, stray, free–roaming pet, or indoor pet) of the Cats tested. They calculated the proportional morbidity ratio (PMR) as number of FIV positive tests / number of FeLV positive tests and constructed a choropleth map of PMRs by state to identify infection patterns across the country. Infections of FeLV occurred more frequently than FIV (PMR < 0.67) in the western US, whereas FIV infections occurred more frequently than FeLV (PMR > 1) in the southern and eastern portions of the US. Survival rates among adult feral Cats are difficult to quantify because of undetected deaths, dispersal from study areas, and removal by humans (Baker et al. 2010). For instance, a 42-month study of feral Cats (n = 39) in inner-city Berlin, Germany, reported 9 disappearances, 15 deaths, and 4 adoptions, with only a 33% survival rate (Kalz et al. 2000). Semi-feral Cats whose diets are subsidized by human feeding appear to have higher survival rates than other feral Cats (Schmidt et al. 2007). Schmidt et al. (2007) monitored feral (n = 29) and semi-feral (unowned but directly fed by a resident; n = 14) Cats in a suburban area of Texas and calculated 14-month survival at 56% and 90%, respectively. Horn et al. (2011) examined 27 unowned Cats in Champaign-Urbana, IL, and determined that only 50% survived longer than 392 days. No telemetry study has estimated the life span of adult feral cats, but anecdotal reports estimate 2–3 years (Andersen et al. 2004). Most feral Cat research in the United States has been conducted in rural (Mitchell and Beck 1992, Nutter et al. 2004a) or urban and suburban areas (Calhoon and Haspel 1989; Horn et al. 2011; Lee et al. 2002; Mitchell and Beck 1992; Schmidt et al. 2007, 2009), and information regarding exurban feral Cats is scant. There is no decisive definition for exurban (Ban and Ahlqvist 2009, Walter 2011), but it is typically characterized as having relatively low housing density in a heterogeneous landscape, combining natural and anthropogenic features, and existing within a matrix of natural landscapes such as state and national parks and conservation areas (Hansen et al. 2005, Theobald 2004). Exurban development is the fastest growing land-use form in the United States, covering 5–10 times more land area than urban and suburban areas in the year 2000 and increasing at a rate of 10–15% per year (Theobald 2004). Native species tend to concentrate in natural areas associated with this kind of land use; thus exurban Southeastern Naturalist 3 C.M. Normand and R.E. Urbanek 2017 Vol. 16, No. 1 development may have greater impact on natural communities than other types of development (Hansen et al. 2005). The ability of feral Cats to exploit different habitats and prey sources may exacerbate the impacts of exurban development on surrounding natural communities. Understanding feral Cat seroprevalence and survival is essential for effective Cat management. To our knowledge, no one has examined FeLV and FIV seroprevalence in an exurban area. Therefore, our goal was to quantify FeLV and FIV seroprevalence within a feral Cat population and to estimate survival of adult feral Cats in an exurban site in Arkansas. Field-Site Description Russellville (35°17'23"N, 93°08'11"W) is a growing city in central northwest Arkansas, located in the Arkansas River Valley between the Ouachita and Ozark National Forests. Its overall character is exurban, as we have defined the term. In 2012, the estimated population of Russellville was 28,533 people (389 people/km2; United States Census Bureau 2014), which had increased 20.6% from the year 2000 (23,682 people; 323 people/km2; United States Census Bureau 2000). During our study, Russellville covered 73 km2, 46% of which consisted of developed land: 24.97 km2 (34%) open-to-low-intensity developed areas having less than 49% impervious surfaces, and 9.21 km2 (12%) medium-to-high-intensity developments having 50–100% impervious surfaces (Jin et al. 2013). Forests covered 31% (16.64 km2) of Russellville, pasture and hay fields comprised 19% (13.71 km2), and the remaining 4% of land covers included grassland/shrub/scrub, open water, wetlands, cultivated crops, and barren rock (Jin et al. 2013). During the study, Russellville’s mean monthly temperature for the cold seasons (November–March) was 7.65 ± 3.99 °C (monthly mean ± SD for all weather-related numbers), and the coldest month was December 2013 (monthly mean = 4.44 °C) Weather Underground 2014). The mean monthly temperature for the warm season (April–October) was 22.46 ± 4.78 °C, and the warmest month was August 2013 (monthly mean = 27.22 °C) (Weather Underground 2014). Mean monthly precipitation during the 15-month study was 7.98 ± 4.06 cm and did not differ between the cold and warm seasons (PROC TTEST: t14 = 0.70 P = 0.249; α = 0.05 for all statistical analyses; SAS Institute, Cary, NC). Methods Capture and animal handling We conducted trapping and handling activities in accordance with the guidelines of the American Society of Mammalogists (Sikes and Gannon 2011) and consulted 2 veterinarians regarding our anesthesia and handling methods to ensure the ethical treatment and safety of all captured animals. During October 2012–August 2013, we set at least 25 custom-made live-cage traps (30 cm x 30 cm x 70 cm) 2–5 nights per week from 1700 to 2030 hr. We placed traps in 38 locations that included 23 developed areas and 15 relatively natural areas (Fig. 1). We determined trapping locations based on the land owner or manager granting permission to trap Cats on Southeastern Naturalist C.M. Normand and R.E. Urbanek 2017 Vol. 16, No. 1 4 their property. We checked and retrieved traps the following mornings between 0600 and 1030 hr and immediately released all captured non-target animals (e.g., Procyon lotor (L.) [Raccoon], Didelphis virginiana Kerr [Virginia Opossum], Mephitis mephitis (Schreber) [Striped Skunk]) and all Cats wearing collars because they were likely free-roaming owned cats (n = 1). We also used a remote microchip reader (Biomark model 604; Biomark, Boise, ID) to scan for passive integrated transponder (PIT) tags. If a PIT tag was present, we presumed the Cat was owned and released it immediately. We considered all Cats without PIT tags or collars to be unowned (Horn et al. 2011) and feral. We estimated the weight of each captured feral Cat and anesthetized them in situ via an intramuscular injection of ~0.04 mg/kg of dexmedatomidine HCL (Dexdomitor; Orion Corporation, Espoo, Finland; Granholm et al. 2006); an intramuscular Figure 1. Trapping locations for exurban feral Felis catus (Domestic Cat) in Russellville, AR 2012–2014. All locations include a 250-m buffer so that small locations would be visible at this scale. Locations outside of city limits are parks managed by the City of Russellville. Southeastern Naturalist 5 C.M. Normand and R.E. Urbanek 2017 Vol. 16, No. 1 injection of 0.04 mg/kg antagonist atipamezole HCL was used to reverse sedation (Antisedan; Orion Corporation; Granholm et al. 2006). If a feral Cat appeared especially excited or resilient to sedation, a cumulative dose not exceeding 0.10 mg/kg of each drug was required (Horn et al. 2011). After sedation, we weighed and sexed cats, and then examined their reproductive status by palpating the abdomen to feel for scar tissue of females or by the presence or absence of testicles in males. We assigned each Cat a body condition score (BCS) from 1 (emaciated) to 9 (grossly obese), with a score of 5 being ideal based on palpability of ribs and spine, definition of waist, and presence or absence of an abdominal fat pad (Laflamme 1997, Scott et al. 2002). In addition, we collected 0.3–1.0 mL of blood to test for FeLV antigen and FIV antibodies (SNAP FIV/FeLV Combo Test; IDEXX Laboratories, Westbrook, ME) in the laboratory. We aged Cats into broad groups of immature (up to 6 months old) or adult (older than 6 months old) based on body size, tooth wear and color, and observed reproductive status (i.e., adult female Cats were pregnant, lactating, or had larger nipples indicating prior lactation, and adult males had larger, well-developed testicles) (M. Lombardi, US Fish and Wildlife Service, Arkansas Ecological Services Field Office, Conway, AR, pers. comm.). Prior to release of the cats, we implanted a 9-mm 134.2-kHz PIT tag (Biomark HPT) subcutaneously to mark each feral Cat for identification in the event of recapture and fit mortality-sensing radiocollars (38 g, 150–152 MHz; Advanced Telemetry Systems, Isanti, MN) on a subset of adult Cats (n = 31/ 101). We only radiocollared adult Cats weighing at least 1.3 kg to ensure the radiocollar weight did not exceed 3% of the body mass of the Cat (Horn et al. 2011, Schmidt et al. 2007). We released all healthy feral Cats at the capture site after they recovered from sedation, but we took Cats that were in extremely poor condition (BCS < 2 and apparently suffering) to Russellville Animal Control for euthanasia. Seroprevalence We refrigerated (1–4 °C) 90 blood samples from captured Cats in microtainer plasma separator tubes with lithium heparin (Becton, Dickinson, and Company, Franklin Lakes, NJ). In the laboratory, we centrifuged blood samples to separate the plasma, which we then used to conduct SNAP FIV/ FeLV Combo Tests. SNAP FIV/ FeLV Combo Tests have result windows that develop color in specific locations to indicate presence of FeLV antigen (sensitivity = 98.6%, specificity = 98.2%) and FIV antibody (relative sensitivity = 93.5%, specificity = 100%) in the sample. Unfortunately, we collected 35 blood samples up to 2 months before procuring the tests (due to a backorder of tests), and therefore those samples were stored longer than the 7-day maximum recommended by the test manufacturer. Although these 35 SNAP tests showed results and positive control indicators, we assumed the improper storage rendered the results unreliable and excluded the m from analyses. We compared FIV and FeLV seroprevalence between sexes, BCS, and habitat of capture location (i.e., natural vs. developed) for the tested feral cats. We calculated seroprevalence as a proportion of Cats that tested positive for FeLV and/or FIV and ran G-tests (PROC FREQ) to determine if virus infection status was independent of Southeastern Naturalist C.M. Normand and R.E. Urbanek 2017 Vol. 16, No. 1 6 sex, BCS, and habitat at capture location. We calculated PMR within Russellville to compare against the PMR for Arkansas and surrounding states in Chhetri et al. (2013). We also calculated the PMR for male and female Cats in this stud y. Survival We used ground-based radiotelemetry techniques to track all radiocollared Cats and determine their survival from October 2012 to December 2013. We began monitoring survival of adult feral Cats within 4 days of collar deployment by listening for a signal on each Cat 2–3 times per week. If we lost a signal (i.e., radiocollar failure or Cat dispersed from study area), we recorded it as a censored observation, meaning the fate of the Cat was unknown (Brasher et al. 2006, Cooch and White 2012, Horn et al. 2011). If a radiocollar exhibited a mortality signal, we immediately collected the Cat and identified the cause of mortality. A licensed veterinarian performed a necropsy on each deceased Cat to confirm cause of death. We classified cause of mortality into 4 categories: predation, disease, vehicle collision, and unknown (Urbanek et al. 2009). We calculated the naïve annual (52 weeks) survival estimate as: ([1 - (m / c)] / w) * 52, where m = number of mortalities, c = total number of Cats tracked that were not censored, and w = number of weeks tracked. We also used the staggered entry and the known-fate survival estimator in Program MARK (Colorado State University, Fort Collins, CO) to estimate the maximum likelihood annual survival of feral Cats. The factors likely to influence survival of feral Cats are sex, infection status, BCS, season, and whether the Cat’s home range is located in a developed or natural area (Table 1). Unfortunately, we had reliable FeLV/FIV results for only 14 of the 31 radiocollared Cats, so we could not include infection status in our survival models. Therefore, we developed 10 a priori linear models based on the remaining factors and used Akaike information criterion adjusted for small sample size (AICc) to determine their effects on feral Cat survival (Table 2). The set of models considered included those with a single variable that may have an effect on the survival of feral Cats (Table 2). Male feral Cats tend to have larger home ranges than females (Guttilla and Stapp 2010, Horn et al. 2011, Jones and Coman 1982, Schmidt et al. 2007), which may increase risk exposure of males as they traverse their regular territories. Feral Cats in poor body condition (BCS < 5) are likely unhealthy or physically weak, and consequently, these individuals may Table 1. Variable abbreviations, descriptions, and binomial numbers assigned to each covariate for a priori models to evaluate survival of exurban feral Felis catus (Domestic Cat) in Russellville, AR, 2012–2014. Variable Abbreviation Description (assigned binomial covariate) Body condition score BCS Continuous variable ranging 1–9 Habitat of capture location Hab Natural (0) or developed (1) Season in which mortality occurred Seas Cold: Nov–Mar (0) or warm: Apr–Oct (1) Sex of the cat Sex Male (0) or female (1) Southeastern Naturalist 7 C.M. Normand and R.E. Urbanek 2017 Vol. 16, No. 1 have lower survival than Cats with BCS greater than 5. Summer in Russellville is hot and dry, so few ditches hold water year round. Therefore, feral Cats may have difficulty obtaining water during the warm season, which could result in reduced survival compared to the cold season. Feral Cats residing in more-developed areas of the city have more reliable food resources from anthropogenic sources, which may reduce mortality risks associated with foraging effort compared to Cats in more-natural areas of an exurban landscape. We also considered models with linear combinations of variables that may have synergistic effects on feral Cat survival in the model set (Table 2). Female feral Cats may have higher survival during the warm season because they will likely spend less time traversing their home ranges with their young; thus, this behavior may potentially reduce their exposure to mortality risks compared to male Cats during that time of year. Cats in developed areas have more stable food sources due to human refuse or subsidized food than Cats residing mostly in natural areas, a condition that may be more pronounced during winter. Thus, the reduced foraging effort and exposure to risks may increase survival of Cats in developed areas compared to Cats in natural areas during the cold season. In addition, urban feral Cats typically form colonies around concentrated food sources whereas rural Cats are usually solitary (Liberg et al. 2000); hence, male Cats in natural areas may need to travel farther than males in developed areas of the study area to find mates, likely increasing exposure to mortality risks and reducing their survival. Consequently, female Cats in developed areas may have higher survival during the cold season than males in the same area or both sexes in natural areas. We considered as supported only models less than or equal to 2 ΔAICc values from the most parsimonious model (Burnham and Anderson 2004, Cooch and White 2012) and with AICc values less than the model holding survival constant (Burnham and Anderson 2004, Cooch and White 2012). We examined model Table 2. A priori models for estimating annual survival of exurban feral Felis catus (Domestic Cat) in Russellville, AR, 2012–2014. Table includes unstandardized parameter estimates and standard error, the number of parameters (K), AICc, distance from the lowest AICc values (ΔAICc), Akaike model weights (ω), and model deviance (Dev) used to evaluate models. Descriptions of variables are in Table 1. Model K AICc ΔAICc ω Dev 21.33 ± 0.00 (Intercept) - 16.92 ± 0.00 (Sex) + 1.61 ± 1.16 (Se as) 3 52.57 0.00 0.24 46.55 22.05 ± 0.00 (Intercept) - 16.94 ± 0.00 (Sex) 2 52.87 0.30 0.21 48.86 20.85 ± 0.00 (Intercept) - 16.99 ± 0.00 (Sex) + 1.57 ± 1.16 (Se as) ) 4 53.77 1.20 0.13 45.73 + 0.92 ± 1.01 (Hab 20.73 ± 0.00 (Intercept) - 16.24 ± 0.00 (Sex) + 0.99 ± 1.00 (Ha b) 3 53.95 1.38 0.11 47.93 33.45 ± 0.00 (Intercept) - 23.34 ± 0.00 (Sex) + 1.65 ± 1.17 (Se as) 5 54.54 1.97 0.09 44.49 + 2.71 ± 1.84 (Hab) - 1.54 ± 1.23 (BCS) 5.71 ± 0.50 (Intercept) 1 55.73 3.16 0.05 53.72 5.11 ± 0.58 (Intercept) + 1.47 ± 1.16 (Seas) 2 55.82 3.25 0.05 51.81 4.81 ± 0.71 (Intercept) + 1.37 ± 1.00 (Hab) 2 55.99 3.42 0.04 51.98 4.17 ± 0.77 (Intercept) + 1.49 ± 1.16 (Seas) + 1.40 ± 1.00 (Hab ) 3 56.02 3.46 0.04 50.00 1.55 ± 4.29 (Intercept) + 0.85 ± 0.90 (BCS) 2 56.81 4.25 0.03 52.80 Southeastern Naturalist C.M. Normand and R.E. Urbanek 2017 Vol. 16, No. 1 8 deviance, AICc relative importance weights, unstandardized parameter estimates and standard error, and signs of overdispersion for supporting evidence that a variable affected survival. Known-fate models in Program MARK are considered saturated and thought to fit the data perfectly. Thus, there is no goodness-of-fit test for known-fate data (Brasher et al. 2006, Cooch and White 2012, Urbanek et al. 2009). Consequently, we examined for potential overdispersion by adjusting the variance inflation factor (ĉ) in increments of 0.25 from 1 (model fits the data) to 3 (model is overdispersed) and examined changes in model ranks (Brasher et al. 2006, Urbanek et al. 2009). Results We set 2307 traps (1149 in natural areas and 1158 in developed areas) and had a total of 2120 effective trap nights. Twenty-one of the captured Cats were recaptures, and of the 101 unique Cats captured, 1 was a pet and 7 escaped before processing, so we collected data from 93 feral Cats (64 males—8 of which were neutered—and 29 non-neutered females). Most of the Cats sampled were adult (n = 75; 52 males and 23 females), but we also sampled 18 immature Cats (12 males and 6 females). We had greater trapping success at developed sites (n = 68; 49 males and 19 females, 58 adults and 10 juveniles) than natural sites (n = 25; 15 males and 10 females, 17 adults and 8 juveniles), although we visually detected several uncaptured Cats at the natural sites. Overall catch per unit effort was 1 unique cat/25 trap nights, but catch per unit effort was 3 times lower in natural areas (1 cat/50 trap nights) than developed areas (1 cat/16.7 trap nights). The majority of the Cats sampled (n = 58) were in ideal body condition (BCS = 5), 22 Cats were underweight (BCS between 2–4), and 13 were overweight (BCS of 6 or 7). Sample sizes of Cats for each BCS, particularly the lower and upper values, were too small to run valid statistical analyses, so we grouped Cats by body condition into the aforementioned categories of underweight, ideal, and overweight. Body condition did not differ by sex (G2 = 4.57 P = 0.102). However, we trapped more underweight and less ideal-weight Cats than expected at natural sites, and more ideal-weight Cats than expected at developed sites (G2 = 7.38 P = 0.025). One captured Cat was transported to Russellville Animal Control for euthanasia because he was in poor condition (BCS = 2) and had bleeding tumors on the pads of all 4 feet. Seroprevalence We originally ran 90 FeLV/FIV SNAP tests, but excluded 35 tests as aforementioned, so we included only 55 in seroprevalence analyses. Over all seroprevalence was 32.73% (12.73% FeLV positive, 16.36% FIV positive, and 3.64% positive for both FeLV and FIV). Sample sizes for Cats that were positive for FeLV, FIV, or FeLV/FIV were too small for valid statistical analyses, so we grouped Cats by infected or uninfected status to examine seroprevalence (Fig. 2). Seroprevalence (Fig. 3) did not differ by sex (41 males and 14 females; G1 = 1.15 P = 0.284), habitat at capture location (49 developed, 6 natural; G1 = 0.88 P = 0.349), or body condition Southeastern Naturalist 9 C.M. Normand and R.E. Urbanek 2017 Vol. 16, No. 1 (16 underweight, 35 ideal weight, 4 overweight; G2 = 3.49 P = 0.175). Calculated PMR of feral Cats in Russellville was 1.22, and female feral Cats had a lower PMR (0.50) than male Cats (1.43). Infection prevalence of FeLV and/or FIV ranged from 0 to 100% at any given trapping location, but 2 (1 natural, 1 developed) of the 3 locations with 100% prevalence had sample sizes of only 1 cat. Of the locations with more than 1 feral Cat tested, we identified 1 with 100% infection prevalence (2/2 Cats), 1 with 66.67% infection prevalence (6/9 Cats), and 2 with 50.00% infection prevalence (1/2 and 2/4 Cats), all of which were developed locations. Figure 2. Virus infections status of captured feral Felis catus (Domestic Cat) in Russellville, AR, 2012–2014. Positive feral Cats are those that tested seropositive for feline immunodeficiency virus (FIV) antibodies, feline leukemia virus (FeLV) antigen, or both FIV and FeLV. Negative feral Cats tested negative for FIV antibodies and FeLV antigen. Southeastern Naturalist C.M. Normand and R.E. Urbanek 2017 Vol. 16, No. 1 10 Survival Of the 31 adult feral Cats radiocollared, we tracked 29 Cats (13 males and 16 females; 22 Cats caught in developed areas and 7 Cats captured in natural areas; BCS median of 5 [range = 2–7]) for 3–57 weeks (41.83 ± 0.58 SE). Two radiocollars were apparently fit on semi-feral Cats (i.e., not considered pets, but regularly fed by humans) and were removed by their caregivers within 1 day of collar deployment, and 19 Cats were censored during the course of the study. In addition, we recorded 4 mortalities: 1 vehicle collision, 1 disease (probable Streptococcus pnuemoniae [Bacterial Pneumonia]), and 2 from unknown causes. All Cats that died during the study were female; 2 occupied developed areas, and 2 were from natural areas; 3 were in ideal body condition at the time of capture (BCS = 5), and 1 was slightly underweight (BCS = 4). The female that died from probable bacterial pneumonia was pregnant with 4 kittens and ~10 days from parturition. The naïve annual survival estimate for adult Cats in this study was 0.73. Of the 10 a priori models, we identified 5 competing models that included 78% of the Akaike model weight (Table 2). Feral Cat survival was mostly influenced by sex of the Cat, which was a variable included in all competing models (relative Akaike weight ω = 0.78). Given that only female feral Cats experienced known mortalities during the study, male feral Cats had higher rates of survival (1.00) Figure 3. Seroprevalence (%) for feline leukemia virus (FeLV) and feline immunodeficiency virus (FIV) by sex, habitat at capture location, and body condition score (BCS; underweight: BCS ≤ 4, ideal: BCS = 5, overweight: BCS ≥ 6) of feral Felis catus (Domestic Cat) in Russellville, Arkansas 2012–2014. There were no differences of infection prevalence within groups (G1-2= 0.88–3.49 P = 0.175–0.349). Southeastern Naturalist 11 C.M. Normand and R.E. Urbanek 2017 Vol. 16, No. 1 than female feral Cats (0.73). The remaining variables in the competing models included season in which mortality occurred (ω = 0.46), habitat of capture location (ω = 0.33), and BCS (ω = 0.09). These models indicated that feral Cats experienced higher survival rates in the warm season compared to the cold season, feral Cats captured in developed areas of the city had higher survival rates than Cats captured in natural locations, and that survival had a slight inverse relationship with BCS. The models that included both habitat and season had lower deviance than the most parsimonious model, which provided some evidence that these parameters may contribute to annual survival rates in addition to the variable sex. Conversely, the regression coefficients for season, habitat, and BCS parameters had less influence within the models than did the sex of the Cats. Moreover, unlike the 95% confidence intervals for the coefficient of the sex parameter (-16.92 to -16.92), those for the coefficients of season (-0.66 to 3.88), habitat (-1.05 to 2.90), and BCS (-3.95 to 0.87) overlapped 0, indicating non-significance. Adjusting ĉ changed rank order of the models suggesting overdispersion of the data, and the models that included season of mortality, habitat of capture location, and BCS were unsupported. Adjusting ĉ resulted in the top model descending in rank order, but the model containing only the sex variable became the top model at ĉ = 1.25 and remained stable through ĉ = 2.25, and thus we have evidence that sex of the Cat was the strongest contributing factor to survival in this study. The estimated annual survival for all Cats in this study from this model was 0.86. Discussion Given that FeLV and FIV prevalence can vary across regions and that survival of feral Cats influences potential impacts these Cats have within their communities, our objectives were to quantify FeLV and FIV seroprevalence within a feral Cat population and estimate survival of adult feral Cats within an exurban city. We detected higher prevalence of FIV than FeLV and found an overall seroprevalence of nearly 33% in the city. Feral Cats infected with FeLV or FIV pose health risks to free-roaming pet Cats and other wild felids. Survival of adult feral Cats in Russellville falls on the higher end of survival rates reported in other feral Cat studies, and males appear to have higher survival rates than females. Seroprevalence Lee et al. (2002) identified overall seroprevalence of FeLV at 4.3% and FIV at 3.5% among feral Cats in Gainesville, FL, and Raleigh, NC. Seroprevalence in Russellville was much higher and may exist as part of the regional variation reported in the literature (Lee et al. 2002, Little 2005, Natoli et al. 2005). However, the higher seroprevalence in our study may result from the lack of feral Cat management in Russellville, whereas in both Gainesville and Raleigh, feral Cats tested were part of an ongoing trap–neuter–release program. Given that FIV is most commonly transmitted between intact male Cats during territorial disputes and a common mode of FeLV transmission is from mother to kittens (Lee et al. 2002), the act of neutering feral Cats may reduce FeLV and FIV transmission within a population. In our study, Southeastern Naturalist C.M. Normand and R.E. Urbanek 2017 Vol. 16, No. 1 12 5 of the 41 male Cats tested for FeLV/FIV were neutered and infection prevalence was 20% among neutered males versus 40% among intact males. These findings provide some evidence that neutered Cats have a lower risk of infection, but further research is warranted. Lee et al. (2002) observed a higher seroprevalence of FeLV infection (5.3%) compared to FIV (2.3%) in NC, but not in FL (3.7% and 4.3%, respectively). In addition, they found male feral Cats were more likely than female Cats to test positive for FIV but not FeLV. In Russellville, we observed a slightly higher percentage of FIV-positive tests than FeLV-positive tests; however, the difference in combined FeLV and FIV seroprevalence between male and female feral Cats was insignificant. The disadvantage of combining FeLV and FIV in our statistical analyses was the inability to detect the risk of FeLV or FIV infection between the sexes. However, calculating PMR for each sex enabled identification of higher frequency of FeLV infections relative to FIV infections in female Cats and the inverse relationship in male cats, which is consistent with the infection-sex relationship identified in previous studies (Lee et al. 2002, Levy and Crawford 2004). The calculated PMR in Russellville indicated a higher occurrence of FIV relative to FeLV infections compared to the estimated PMR for all of Arkansas (0.48– 0.67; Chhetri et al. 2013). This disparity likely resulted from the different sampling techniques and target populations; Chhetri et al. (2013) did not distinguish among feral, stray, free-roaming pet cats, or indoor pet Cats, whereas we targeted feral Cats specifically. From Arkansas, Chhetri et al. (2013) collected 28 positive results (FIV = 10, FeLV = 18) from 12 counties (results of only FIV from 2 counties, only FeLV from 7 counties, and both FeLV positive and FIV positive from 3 counties), but none from Pope County where Russellville is located (IDEXX Laboratories 2011). Russellville’s PMR was higher than the range of PMRs that Chhetri et al. (2013) calculated for Oklahoma, Missouri, Tennessee, and Mississippi (0.67–1.10) and within the range of PMRs in the remaining 2 bordering states, Texas and Louisiana (1.10–2.05). Although there was no difference in infection prevalence between natural and developed areas, the 4 trapping locations where we trapped more than 1 Cat and that had at least 50% seroprevalence were all in developed areas. Epidemiologic studies in France (Fromont et al. 1997) and Canada (Little et al. 2011) have identified higher seroprevalence in developed areas compared to more-rural areas, but seroprevalence in our study did not differ by habitat of capture location. Therefore, these high-seroprevalence locations in Russellville may be indicative of a higher concentration of infected Cats in this localized area, but not higher seroprevalence throughout the developed areas relative to natural areas in the city. Models of FeLV dynamics indicate transmission rates depend on the size of the feral Cat population and the relationship between Cat density and patterns of contact among Cats (Fromont et al. 1998). Availability and distribution of food resources lies on a spectrum with urban areas generally having abundant, clumped food in the form of refuse and artificial feeding stations, and undeveloped landscapes generally characterized by sparsely distributed food. Areas with dense resources support large, Southeastern Naturalist 13 C.M. Normand and R.E. Urbanek 2017 Vol. 16, No. 1 high-density Cat populations and high frequencies of contact between individual cats, and therefore have higher seroprevalence of FeLV than undeveloped areas (Fromont et al. 1998). Within Russellville, catch per unit effort was 3 times greater in developed areas than in natural areas, resulting in the majority of the feral Cats that we tested for FeLV and FIV having been captured in developed locations. Further testing of feral Cats in natural areas would determine if no difference in seroprevalence of Cats in developed and natural areas truly exists in Russellville or if the results from this study stem from the smaller sample sizes in natural areas of the city. Survival Censored individuals occur in many feral Cat telemetry studies because Cats disperse from study areas or are removed by humans (Baker et al. 2010, Centonze and Levy 2002, Kalz et al. 2000). Less than half (42%) of all censoring of Cats occurred over the first 92% of our study period, which was consistent with the number of censored feral Cats in other survival studies (Centonze and Levy 2002, Kalz et al. 2000). The remaining 58% of censors happened during the last 5 weeks of the study. Recovered radiocollars were generally in poor condition with ther rubber casing that protects antennas and battery housings having been scratched and cut, which exposed the antennas and batteries to the elements. In addition, December 2013 was the coldest month during the study; thus, radiocollar failure from the combination of poor collar condition (T. Garin, Advanced Telemetry Systems, Isanti, MN, pers. comm.) and cold weather was the most probable explanation for the loss of radio signal from those censored cats. We observed few known mortalities of feral Cats in Russellville. Both calculated naïve survival and modeled annual survival for feral Cats in this study were within the range of survival estimates reported in other feral Cat studies (Horn et al. 2011, Kalz et al. 2000, Schmidt et al. 2007), but modeled survival was on the higher end of the range. Given that only female Cats experienced known mortalities, sex of the Cat had the strongest effect on annual survival. This finding may reflect the hardships associated with parturition and raising young, but it is more likely the result of demographic stochasticity. Schmidt et al. (2007) reported higher rates of survival for female feral Cats (0.88) than male Cats (0.52), but they also observed more mortalities (Schmidt et al.: 8, this study: 4) during their study despite the smaller sample size (Schmidt et al.: 20, this study: 31) and slightly shorter study period (Schmidt et al.: 14 months, this study: 16 months). Half of the mortalities observed in our study and in Horn et al.’s (2011) study were from unknown causes, but Schmidt et al. (2007) reported vehicle collisions as the major cause of mortalities. Survival of feral Cats infected with FIV or FeLV is understudied, but is important for understanding virus transmission within and among populations. A study by Mari et al. (2004) found that pet Cats infected with FeLV were asymptomatic for 80–300 days before developing clinical symptoms of the disease, after which approximately 80% died within 2.5–3.5 years. Hofmann-Lehmann et al. (1997) estimated the asymptomatic phase lasted ~3.5 years in pet Cats infected with FIV, and Southeastern Naturalist C.M. Normand and R.E. Urbanek 2017 Vol. 16, No. 1 14 the measured biochemical parameters of infected Cats and control groups were not statistically different until 9 months after infection. They also reported that all 15 Cats experimentally infected with FIV and housed in hygienic conditions were alive at the end of their 6.5-year study. Considering that feral Cats infected with FeLV or FIV may survive for several years before and after developing clinical signs of the disease, there are likely ample opportunities for virus transmission within outdoor populations. The number of disappearances reported in survival studies suggests that many Cats disperse from their regular territories (Baker et al. 2010, Katz et al. 2000), thus increasing the potential for virus transmission among feral populations. In addition, wildlife biologists and natural resource managers cannot determine the health status of feral Cats by physical appearance alone because seemingly healthy Cats may be in the asymptomatic phase of infection (Hofmann-Lehmann et al. 1997). Unfortunately, we were unable to include infection status in our survival models, but this should be an area of interest for future studies. To our knowledge, this is the first published study of FeLV and FIV seroprevalence and survival of feral Cats in an exurban area. Overall, the biggest limitations regarding these analyses were the small sample sizes, especially because we had to exclude 39% of our FeLV/FIV tests, and the short temporal scale that prevented detailed analyses of trends in FeLV and FIV seroprevalence and ability to extrapolate results to other exurban areas. Also, larger sample sizes and a longer study period would have identified if the observed mortalities resulted from demographic stochasticity and provided more accurate modeling of the parameters that influence survival of feral cats. Although the small spatial scale and sample size of this study prevents extrapolation to other exurban areas, this case study can be used comparatively with future feral Cat research in other exurban areas. Additionally, research at the local level should provide sufficient information and incentives for Russellville’s municipal government to consider developing a feral Cat management plan. Management implications High seroprevalence of FeLV and FIV in this feral Cat population suggests that free-roaming pet Cats and potentially native wild felids may have high risk of infection in the Russellville area. We were unable to determine if pet Cats in Russellville have a similar seroprevalence to feral Cats in the area because the Arkansas Department of Public Health, State of Arkansas Veterinary Medical Examining Board, and the Arkansas Veterinary Medical Association do not maintain records of FeLV/ FIV testing or vaccinations in the state (S. Weinstein DVM, Arkansas Department of Health, Little Rock, AR, pers. comm.). Currently, feral Cats in Russellville are unmanaged, but high seroprevalence indicates an urgent need for a comprehensive feral Cat management plan at the city level. Control of feral Cats is among the most contentious and widely debated issues in animal control, yet few governments or private agencies implement comprehensive management efforts (Levy and Crawford 2004). Regardless of the management strategy implemented, education of veterinarians and the public about FeLV and FIV risks and importance of testing and vaccinations for pet Cats is paramount. Research indicates that only 54% of veterinarians in the United States followed Southeastern Naturalist 15 C.M. Normand and R.E. Urbanek 2017 Vol. 16, No. 1 recommendations regarding educating Cat owners and following-up with owners to encourage compliance with the full series of FeLV and FIV tests and vaccines (Little et al. 2011). A survey of veterinarians within Russellville and throughout Arkansas would identify the efficacy of local veterinary protocols regarding education of Cat owners and compliance with testing and vaccination recommendations. Pet owners having doorstep food and other people who facilitate artificial feeding stations for feral Cats should also be aware of the potential for increased risks of contact and virus transmission around clumped food resources (Fromont et al. 1998). Encouraging effective refuse containment by businesses and residences would reduce the abundance of food resources to ultimately reduce the frequency of contact among feral Cats and aid management ef forts. Nearly 24 trap nights were expended to capture each Cat in our study, which is considerably higher than trap effort in other feral Cat studies that also used live cage traps (8.9–10.6 trap nights/cat; Nutter 2005, Nutter et al. 2004b, Short et al. 2002). Throughout the course of this study, we observed a few characteristics of trap locations that appeared to influence trap success. We had nearly 3 times higher trapping success in developed locations relative to natural locations. Feral Cats living in developed areas are most likely acclimated to anthropogenic objects and are more accustomed to climbing in or through these objects to obtain food compared to Cats who occupied natural locations. Thus, feral-Cat–trapping efforts for either research, removal, or trap–neuter–release will likely be more efficient in developed areas than natural locations because of the cats’ willingness to enter a trap to obtain food. However, several locations where we attempted to trap feral Cats that had constant access to feeding stations were unsuccessful, indicating that too much access to food will likely result in Cats being satiated and therefore unwilling to enter traps regardless of their acclimation to anthropogenic objects. In these locations, managers can attempt to gain cooperation from the people who provide the food (i.e., requesting that feeding station caretakers suspend feeding for a few days), which will likely increase trapping success. The greater trapping success in developed areas suggests that pre-baiting traps or providing supplemental food to Cats in natural areas may increase trapping success. Nutter et al. (2004b) concluded pre-baiting traps did not increase trapping success, but their study was conducted in well-fed, managed Cat colonies where Cats were likely satiated. Pre-baiting or providing supplemental food in natural areas should acclimate Cats to anthropogenic objects and increase trapping success, but may also increase contact among individuals, possibly increasing rates of virus transmission, and may facilitate higher feral Cat fecundity and survival by providing a stable food source. When trapping feral Cats in natural areas, the best course of action is probably to set up anthropogenic objects (i.e., boxes, traps, food dishes) and provide supplemental food in and around these objects for periods of time long enough for Cats to become acclimated, but not so long that it initiates a population incr ease. Feral Cat management requires a community effort because there are many stakeholder groups. Effective feral Cat management requires long-term, intensive efforts because, in addition to being elusive, Cats are prolific breeders (Nutter Southeastern Naturalist C.M. Normand and R.E. Urbanek 2017 Vol. 16, No. 1 16 2005). Just a few intact individuals remaining in a colony after management can repopulate the group rapidly, and abandoning pet Cats is a common practice, so intact Cats may be added to a population continuously (Nutter 2005). Considering the effort required to control feral Cats throughout the entire city, concentrating management and education efforts in the areas of Russellville that very have high (≥ 50%) seroprevalence may be the most economical solution. Acknowledgments Financial assistance and support was provided by the Arkansas Center for Energy, Environment, and Natural Resources; the Graduate School, School of Natural Health and Sciences, and the Department of Biological Sciences at Arkansas Tech University; Ecological Software Services; and K. Smith and the Parkway Animal Hospital. We thank T. Nupp, C. Kellner, and C. Jacobs for their technical assistance and B. Jennings and A. Klais for their field assistance. Literature Cited Andersen, M.C., B.J. Martin, and G.W. Roemer. 2004. Use of matrix population models to estimate the efficacy of euthanasia versus trap–neuter–return for management of freeroaming cats. Journal of the American Veterinary Medical Association 225:1871–1876. Baker, P.J., C.D. Soulsbury, G. Iossa, and S. Harris. 2010. Domestic Cat (Felis catus) and Domestic Dog (Canis familiaris). Pp. 157–171, In S.D. Gehrt, S.P.J. Riley, and B.L. Cypher (Eds.). Urban Carnivores: Ecology, Conflict, and Conservation. John Hopkins University Press, Baltimore, MD. 285 pp. Ban, H., and O. Ahlqvist. 2009. Representing and negotiating uncertain geospatial concepts: Where are the exurban areas? Computers, Environment, and Urban Systems 33:233–246. Brasher, M.G., T.W. Arnold, J.H. Devries, and R.M. Kaminski. 2006. Breeding-season survival of male and female Mallards in Canada’s prairie–parklands. Journal of Wildlife Management 63:880–888. Burnham, K.P., and D.R. Anderson. 2004. Multimodel inference: Understanding AIC and BIC in model selection. Sociological Methods and Research 33:26 1–304. Calhoon, R.E., and C. Haspel. 1989. Urban cat populations compared by season, subhabitat, and supplemental feeding. Journal of Animal Ecology 58:321–328. Centonze, L.A., and J.K. Levy. 2002. Characteristics of free-roaming cats and their caretakers. Journal of American Veterinary Medical Association 220:1627–1633. Chhetri, B.K., O. Berke, D.L. Pearl, and D. Bienzle. 2013. Comparison of the geographical distribution of feline immunodeficiency virus and feline leukemia virus infections in the United States of America (2000–2011). Bio Med Central Veterinary Research 9:2. Clarke, A.L., and T. Pacin. 2002. Domestic Cat “colonies” in natural areas: A growing exotic species threat. Natural Areas Journal 22:154–159. Cooch, E., and G. White. 2012. Program Mark: A gentle introduction. Available online at http://www.phidot.org/software/mark/docs/book. Accessed 20 March 2013. Fromont, E., M. Artois, M. Langlais, F. Courchamp, and D. Pontier. 1997. Modelling the feline leukemia virus (FeLV) in natural populations of cats (Felis catus). Theoretical Population Biology 52:60–70. Fromont, E., D. Pontier, and M. Langlais. 1998. Dynamics of a feline retrovirus (FeLV) in host populations with variable spatial structure. Proceedings of the Royal Society London Biology 265:1097–1104. Southeastern Naturalist 17 C.M. Normand and R.E. Urbanek 2017 Vol. 16, No. 1 Granholm, M., B.C. McKusick, F.C. Westerholm, and J.C. Aspergrén. 2006. Evaluation of the clinical efficacy and safety of dexmedetomidine or medetomidine in cats and their reversal with atipamezole. Veterinary Anesthesia and Analgesia 33:214–223. Guttilla, D.A., and P. Stapp. 2010. Effects of sterilization on movements of feral cats at a wildland–urban interface. Journal of Mammalogy 91:482–489. Hansen, A.J., R.L. Knight, J.M. Marzluff, S. Powell, K. Brown, P.H. Gude, and K. Jones. 2005. Effects of exurban development on biodiversity: Patterns, mechanisms, and research needs. Ecological Applications 15:1893–1905. Hofmann-Lehmann, R., E. Holznagel, P. Ossent, and H. Lutz. 1997. Parameters of disease progression in long-term experimental feline retrovirus (feline immunodeficiency virus and feline leukemia virus) infections: hematology, clinical chemistry, and lymphocyte subsets. Clinical and Diagnostic Laboratory Immunology 4:33–42. Horn, J.A., N. Meteus–Pinilla, R.E. Warner, and E.J. Heske. 2011. Home range, habitat use, and activity patterns of free-roaming Domestic Cats. Journal of Wildlife Management 75:1177–1185. IDEXX Laboratories. 2011. Protect your cat—kittytest.com. Available online at http:// www.kittytest.com/kittytest/ results.jsp?st=AR&ct=Pope&age=1&env=0&submit. x=60&submit.y=8. Accessed 27 September 2014. Jin, S., L. Yang, P. Danielson, C. Homer, J. Fry, and G. Xian. 2013. A comprehensive change-detection method for updating the National Land Cover Database to circa 2011. Remote Sensing of Environment 132:159–175. Jones, E., and B.J. Coman. 1982. Ecology of the feral cat, Felis catus (L.), in southeastern Australia. III. Home ranges and population ecology in semiarid North-West Victoria. Australian Wildlife Research 9:409–420. Kalz, B., K.M. Scheibe, I. Wegner, and J. Priemer. 2000. Health status and causes of mortality in feral cats in a delimited area of the inner city of Berlin. Berl Munch Tieraztl Wochenschr 113:417–422. Laflamme, D.P. 1997. Development and validation of a body condition score system for cats: A clinical tool. Feline Practice 25:13–17. Lee, I.T., J.K. Levy, S.P. Gorman, P.C. Crawford, and M.R. Slater. 2002. Prevalence of feline leukemia virus infection and serum antibodies against feline immunodeficiency virus in unowned free-roaming cats. Journal of the American Veterinary Medical Association 220:620–622. Levy, J.K., and P.C. Crawford. 2004. Humane strategies for controlling feral cat populations. Journal of the American Veterinary Medical Association 225:1354–1360. Levy, J.K., H.M. Scott, J.L. Lachtara, and P.C. Crawford. 2006. Seroprevalence of feline leukemia virus and feline immunodeficiency virus infection among cats in North America and risk factors for seropositivity. Journal of the American Veterinary Medical Association 228:371–376. Liberg, O., M. Sandell, D. Pontier, and E. Natoli. 2000. Density, spatial organization and reproductive tactics in the Domestic Cat and other felids. Pp. 119–149, In D.C. Turner and P. Bateson (Eds.). The Domestic Cat: The Biology of Its Behavior. Second Edition. Cambridge University Press, Cambridge, UK. 288 pp. Little, S.E. 2005. Feline immunodeficiency virus testing in stray, feral, and client-owned cats of Ottawa. Canadian Veterinary Journal 46:898–901. Little, S., D. Bienzle, L. Carioto, H. Chisholm, E. O’Brien, and M. Scherk. 2011. Feline leukemia virus and feline immunodeficiency virus in Canada: Recommendations for testing and management. Canadian Veterinary Journal 52:849–855. Southeastern Naturalist C.M. Normand and R.E. Urbanek 2017 Vol. 16, No. 1 18 Mari, K., L. Maynard, A. Sanquer, B., Lebreux, and H.M. Eun. 2004. Therapeutic effects of recombinant feline interferon–co on feline leukemia virus (FeLV)-infected and FeLV/feline immunodeficiency virus (FIV)–coinfected symptomatic cats. Journal of Veterinary Internal Medicine 18:477–482. Mitchell, J.C., and R.A. Beck. 1992. Free–ranging Domestic Cat predation on native vertebrates in rural and urban Virginia. Virginia Journal of Science 43:197–207. Natoli, E., L. Say, S. Cafazzo, R. Bonanni, M. Schmid, and D. Pontier. 2005. Bold attitude makes male urban feral Domestic Cats more vulnerable to feline immunodeficiency virus. Neuroscience and Biobehavioral Reviews 29:151–157. Nutter, F.B. 2005. Evaluation of a trap–neuter–return management program for feral cat colonies: Population dynamics, home ranges, and potentially zoonotic diseases. Ph.D. Dissertation. North Carolina State University, Raleigh, NC. 241 pp. Nutter, F.B., J.F. Levine, and M.K. Stoskopf. 2004a. Reproductive capacity of free-roaming Domestic Cats and kitten survival rate. Journal of the American Veterinary Medical Association 225:1399–1402. Nutter, F.B., M.K. Stoskopf, and J.F. Levine. 2004b. Time and financial costs of programs for live-trapping feral cats. Journal of the American Veterinary Medical Association 225:1403–1405. O’Brien, S.J., J.L. Troyer, M.A. Brown, W.E. Johnson, A. Antunes, M.E. Roelke, and J. Pecon–Slattery. 2012. Emerging viruses in the Felidae: Shifting paradigms. Viruses 4:236–257. Schmidt, P.M., R.R. Lopez, and B.A. Collier. 2007. Survival, fecundity, and movements of free–roaming cats. Journal of Wildlife Management 71:915–919. Schmidt, P.M., T.M. Swannack, R.R. Lopez, and M.R. Slater. 2009. Evaluation of euthanasia and trap–neuter–return (TNR) programs in managing free-roaming cat populations. Wildlife Research 36:117–125. Scott, K.C., J.K. Levy, and S.P. Gorman. 2002. Body condition of feral cats and the effect of neutering. Journal of Applied Animal Welfare Science 5:203–213. Short, J., B. Turner, and D. Risbey. 2002. Control of feral cats for nature conservation. III. Trapping. Wildlife Research 29:475–487. Sikes, R.S., and W.L. Gannon. 2011. Guidelines of the American Society of Mammalogists for the use of wild mammals in research. Journal of Mammalogy 9 2:235–253. Theobald, D.M. 2004. Placing exurban land-use change in a human-modification framework. Frontiers in Ecology and the Environment 2:139–144. United States Census Bureau. 2000. American fact finder profile of general demographic characteristics 2000: Russellville city, Arkansas. Available online at http://factfinder2. census.gov/faces/tableservices/jsf/pages/productview.xhtml?pid=DEC_00_SF1_ DP1&prodType=table. Accessed 1 September 2012. United States Census Bureau. 2014. State and county quick facts: Arkansas. Available online at http://quickfacts.census.gov/qfd/states/05000.html. Accessed 1 September 2014. Urbanek, R.E., C.K. Nielsen, and S.E. Wilson. 2009. Survival of unexploited Raccoons on a rural refuge in southern Illinois. Transactions of the Illinois State Academy of Science 102:217–223. Walter, P. 2011. Amenity migration, exurbia, and emerging rural landscapes. GeoJournal 76:441–443. Weather Underground. 2014. Weather history for Russellville, AR. Available online at http:// www.wunderground.com/history/airport/KRUE/2014/1/18/MonthlyHistory.html. Accessed 18 August 2014.