Spatial Variation in the Parasite Communities and Genomic Structure of Urban Rats in New York City

Received: 26 March 2017

DOI: 10.1111/zph.12418

ORIGINAL ARTICLE

Spatial variation in the parasite communities and genomic structure of urban rats in New York City

1Department of Biology, Providence College, Providence, RI, USA Summary 2Louis Calder Center and Department of Brown rats (Rattus norvegicus) are a globally distributed pest. Urban habitats can sup- Biological Sciences, Fordham University, port large infestations of rats, posing a potential risk to public health from the para- Armonk, NY, USA sites and pathogens they carry. Despite the potential influence of rodent-borne 3Mailman School of Public Health, Columbia University, New York, NY, USA zoonotic diseases on human health, it is unclear how urban habitats affect the struc- 4School of BioSciences, The University of ture and transmission dynamics of ectoparasite and microbial communities (all Melbourne, Parkville, VIC, Australia referred to as “parasites” hereafter) among rat colonies. In this study, we use ecologi- 5New York State Integrated Pest Management Program, Cornell University, Geneva, NY, USA cal data on parasites and genomic sequencing of their rat hosts to examine associations between spatial proximity, genetic relatedness and the parasite communities Correspondence Jonathan L. Richardson, Department of associated with 133 rats at five sites in sections of New York City with persistent rat Biology, Providence College, Providence, RI, infestations. We build on previous work showing that rats in New York carry a wide USA. Email: [email protected] variety of parasites and report that these communities differ significantly among sites, even across small geographical distances. Ectoparasite community similarity was posi- Funding information National Science Foundation, Grant/Award tively associated with geographical proximity; however, there was no general associa- Number: DEB 145723 and DBI 1531639 tion between distance and microbial communities of rats. Sites with greater overall parasite diversity also had rats with greater infection levels and parasite species richness. Parasite community similarity among sites was not linked to genetic relatedness of rats, suggesting that these communities are not associated with genetic similarity among host individuals or host dispersal among sites. Discriminant analysis identified site-specific associations of several parasite species, suggesting that the presence of some species within parasite communities may allow researchers to determine the sites of origin for newly sampled rats. The results of our study help clarify the roles that colony structure and geographical proximity play in determining the ecology of R. norvegicus as a significant urban reservoir of zoonotic diseases. Our study also highlights the spatial variation present in urban rat parasite communities, indicating that rats across New York City are not reservoirs for a homogenous set of parasites and pathogens. As a result, the epidemiological risks may be similarly heterogeneous for people in urban habitats.

KEYWORDS bacteria, disease ecology, epidemiology, public health, urban ecology, viruses, zoonotic disease

1 | INTRODUCTION

Impacts The brown rat (Rattus norvegicus, AKA the Norway or city rat) is a • Rats in New York City harbour a heterogeneous commu- human commensal that is globally distributed throughout urban land- nity of microbes and ectoparasites, including pathogenic scapes. This species is well adapted to living in proximity to humans, species and known vectors of human disease. These com- and the high urban densities of rats result from their ability to ex- munities vary over fine spatial scales, even within several ploit human resources (Aplin, Chesser, & Ten Have, 2003; Feng & city blocks. Himsworth, 2014; Himsworth, Jardine, Parsons, Feng, & Patrick, • As a result, disease risk for people living in cities can be 2014). Brown rats are a ground-burrowing species (Himsworth, highly heterogeneous across the urban landscape. Bidulka et al., 2013), and the extensive sewer, subway and park infra- • Genomic sequence data suggest that urban rats disperse structure throughout cities provide them with substrate suitable for among similar habitat types (e.g., residential vs. parks vs. burrowing (Childs et al., 1998; Johnson, Bragdon, Olson, Merlino, & mixed-use infrastructure) but that genetic similarity Bonaparte, 2016). Furthermore, the growth of cities has led to an in- among rats does not explain parasite community crease in both human and rat populations in urban areas (Himsworth similarity. et al., 2014). In addition to the effects of rats on infrastructure and food supply (Doherty, Glen, Nimmo, Ritchie, & Dickman, 2016), rat infestations also pose health risks to humans (Himsworth, Parsons, & Schmid-hempel, 2017; Leu et al., 2010). Accordingly, a better un- Jardine, & Patrick, 2013; Himsworth, Bidulka et al., 2013; Ko, Reis, derstanding of the ecology and distribution of urban rats, and their Dourado, Johnson, & Riley, 1999; Meerburg, Singleton, & Kijlstra, parasite communities, can help identify conditions that foster zoonotic 2009). Brown rats are known hosts of several human pathogens pathogen transmission. that cause important zoonotic diseases, including Seoul hantavirus, Brown rats have small home-range sizes and can be territorial, leptospirosis and bubonic plague (Costa et al., 2014; Himsworth which can promote the separation of rat colonies without complete et al., 2014; Leibler, Zakhour, Gadhoke, & Gaeta, 2016). High rat physical isolation, and influence the spread of parasites between densities increase the likelihood of human–rat contact, posing an individuals (Davis, Emlen, & Stokes, 1948; Heiberg et al., 2012; acute risk to public health because zoonotic pathogens or ectopar- Himsworth et al., 2014). Variation in the availability of food through- asite vectors can be transmitted during rodent encounters (Frye out urban landscapes also influences colony sizes and parasite abun- et al., 2015; Himsworth, Parsons et al., 2013; Rogalski, Gowler, dance (Firth et al., 2014; Frye et al., 2015; Himsworth, Bidulka et al., Shaw, Hufbauer, & Duffy, 2016). For example, a recent review of 2013). Members from large colonies may also engage in more social published epidemiologic studies of zoonotic and vector-borne in- interactions, so direct parasite transmission in larger rat colonies may fections among urban homeless reported Bartonella spp. as the be more prevalent (Leu et al., 2010; Stanko, Miklisová, De Bellocq, & most frequently identified vector-borne infection (Leibler et al., Morand, 2002). For example, as ectoparasites are transmitted mostly 2016). Other zoonotic pathogens that were commonly detected through direct contact between rat hosts (Frye et al., 2015), colony among the people sampled included Seoul hantavirus, Leptospira size and distribution can play an important role in the spread of ecto- interrogans and Rickettsia typhi (Leibler et al., 2016). As the percent- parasites (Leu et al., 2010). In contrast, some internal microbial patho- age of people residing in urban areas continues to rise, the inci- gens are shed via urine or faeces and may remain viable outside of the dence of zoonotic diseases is also expected to increase (Himsworth body for up to several months (Karaseva, Chernukha, & Piskunova, et al., 2014; Patz et al., 2004). 1973). When these pathogens are present in the environment, the risk Previous studies suggest that the degree of ectoparasite and mi- of transmission may increase substantially, even without direct con- crobial pathogen (all called “parasites” hereafter for simplicity) trans- tact between rats (Gedeon, Bodelón, & Kuenzi, 2010; Hilton, Willis, mission between hosts of the same species depends on the level of & Hickie, 2002). connectivity between host populations in the landscape (Godfrey, While social dynamics may promote more insular rat colonies 2013; Kerth & Van Schaik, 2012; Leu, Kappeler, & Bull, 2010), and the and parasite communities, dispersal of rats can connect colonies social structure of the host species (Godfrey, 2013; Leu et al., 2010). and influence parasite dynamics. Consequently, geographical dis- A highly connected set of populations or colonies would likely share tance may influence the similarity of parasite communities among many dispersing individuals, creating ample opportunity for parasite rat colonies or populations. Very little is known about the move- transmission (Altizer et al., 2003; Kerth & Van Schaik, 2012). Thus, ment and dispersal of brown rats in urban landscapes, but recent highly social species, such as rats, are expected to exhibit a higher studies using tracking methods and genetic data indicate that probability of microbial and ectoparasite transmission (Altizer et al., brown rat movements are modest (mean of 100-200 metres), with 2003; Møller, Dufva, & Allander, 1993). For example, colonial social some instances of long-distance dispersal greater than 500 me- systems with shared nesting sites or mate competition and aggression tres (Gardner-Santana et al., 2009; Glass, Klein, Norris, & Gardner, are known to enhance the transmission of parasites between individ- 2016; Heiberg et al., 2012; Richardson et al., 2017). This pattern uals and increase disease prevalence (Brown & Brown, 2017; Durrer suggests that limited movement and dispersal of brown rats could ANGLEY et al. | 3 result in localized parasite communities that become less similar 2 | MATERIALS AND METHODS over short geographical distances (Diagne et al., 2017). However, 2.1 | Study area and parasite sampling transmission through indirect contact is also possible and may be facilitated by spatial overlap in rat home ranges without di- Brown rat and parasite samples were collected according to proce- rect host–host interactions (Leu et al., 2010), or through contact dures reported in Firth et al. (2014) and Frye et al. (2015). A total of with excreta (Felzemburgh et al., 2014). This mode of transmission 133 brown rats were collected across five sites in New York City: makes it less likely that geographical separation alone leads to di- three large residential buildings (RH1, RH2 and RH3), one multi-use, vergent parasite communities. However, the relationship between indoor location (RS contains transportation, retail and food services) geography, dispersal and parasite communities is unknown in and one outdoor green space (RP). Specific locations are not pro- urban rats. vided at the request of public officials (but see Figure 1d for map). Concerns for disease emergence in large cities, especially We calculated great-circle distance between sites using the distance through zoonotic transmission, continue to grow as global business, matrix command in the geosphere package of R (Hijmans & Van Etten, international travel and population sizes increase (Bradley & Altizer, 2014). These sites were chosen for their high human density and 2007). Large cities, such as New York City (NYC), are centres of persistent rat infestations. Ectoparasites were sampled by removing global trade and transportation that are susceptible to introduc- them from rats immediately following euthanasia and identified as tions of novel pathogens (Bradley & Altizer, 2007). For example, an described in Frye et al. (2015). Targeted molecular assays were used introduction of West Nile virus into NYC in 1999 quickly spread to identify known bacterial and viral pathogens in all individuals, and across the country and has become enzootic within parts of the high-throughput sequencing and metagenomic methods were used United States (Nash et al., 2001). Two previous studies have looked to identify novel viruses as described in Firth et al. (2014). These in- at the parasite species found on brown rats at five sites in the cluded 15 human pathogens previously associated with brown rats Manhattan section of New York City. Firth et al. (2014) identified and 18 novel viruses, many of which are related to known human a wide diversity of known and novel microbes within rats tested, pathogens. including several zoonotic pathogens. Frye et al. (2015) surveyed the ectoparasites on the same rats and found several species rele- 2.2 | Genomic Sequencing vant for public health, including the tropical rat mite (Ornithonyssus bacoti), the spiny rat mite (Laelaps echidnina/nuttalli), which can Using tissue samples collected by Firth et al. (2014), we extracted both cause skin irritation in humans, the spined rat louse (Polyplax genomic DNA using the DNeasy Blood and Tissue Kit with an RNase spinulosa), which can cause pruritus of the scalp, and the oriental treatment (Qiagen, Valencia, CA). We prepared double-digest re- rat flea (Xenopsylla cheopis), which is a vector of Yersinia pestis, the striction site associated DNA sequencing (ddRADseq) libraries by causative agent of plague. Our study includes the bacterial and viral first digesting 250 ng of high-quality DNA using the SphI and MluCl pathogens known to cause disease, as well as novel microbial spe- restriction enzymes and then cleaning the product with 1.5 × vol- cies without established pathogenic roles. For simplicity, we use the ume of Agencourt XP beads (Beckman Coulter, Brea, CA). To iden- term “parasite” throughout the manuscript to refer to both ectopar- tify rats after sequencing, we ligated “P1” primers that included one asites and all microbial species, regardless of pathogenicity. When of 48 unique five base pair (bp) barcodes to the fragmented DNA, necessary, we explicitly distinguish ectoparasites from bacteria and pooling products for sets of 48 and cleaning barcoded products viruses. with beads as described above. Next, we size-selected DNA frag- Here, we generate reduced representation genomic data for the ments using the Pippin Prep, isolating fragments between 376 bp same rats as Firth et al. (2014) and Frye et al. (2015) to evaluate the and 412 bp (Sage Science, Beverly, MA). We then conducted sev- relationship between connectivity of urban rats and the structure eral PCR amplifications using 20 ng of size-selected DNA with of their parasite communities, including many pathogens of public Phusion High-fidelity PCR reagents and the manufacturer’s recom- health concern. Our aim was to evaluate the movement and gene mended conditions (New England Biolabs, Ipswich, MA). This step flow of brown rats using genetic data in order to improve our under- added Illumina sequencing primers and a second unique “P2” index standing of urban rat ecology, including how colony structure and barcode to each pool of 48 samples, giving each sample an identifi- social behaviours influence parasite dispersal and transmission. We able P1/P2 combined identifier. PCR products were then run on an evaluated genomic variation and parasite communities in 133 rats Agilent 2100 Bioanalyzer to confirm the correct size distribution from the Manhattan borough of New York City, an area that has and concentration. Samples from sites RP and RS were sequenced been identified as a persistent reservoir of rat infestation (Childs at the New York Genome Center on one lane of an Illumina HiSeq et al., 1998; Johnson et al., 2016). We apply community ecology 2500, while samples from sites RH1, RH2 and RH3 were sequenced and population genomic analyses to a public health issue in order at New York University on one lane of a HiSeq 2000. to (i) examine dispersal and gene flow of rats across an urban land- Following sequencing, samples were demultiplexed and trimmed scape; (ii) provide novel insights into parasite dispersal among rat using the “process_radatags” script in Stacks 1.35 (Catchen, Hohenlohe, colonies; and (iii) facilitate future rodent control and epidemiological Bassham, Amores, & Cresko, 2013). We aligned the reads assigned to interventions. each rat to the most recent R. norvegicus reference genome, Rnor6.0 4 | ANGLEY et al. using Bowtie2 under default parameters (Langmead & Salzberg, 2012). sites were determined using Tukey post hoc tests. We used per rat esti- Individuals with alignment rates below 50% were removed and the re- mates of richness to account for unequal sampling across sites; however, sultant files were used to run the “ref_map” pipeline in Stacks to call there was also no association between rats sampled and parasite richness SNPs (single nucleotide polymorphisms), using parameters known to in a preliminary test (r2 = 0.008, p = .883; Fig. S1). We also used linear work well for brown rats (n = 2, m = 3) (Puckett et al., 2016). Finally, we regression to evaluate the association between parasite richness at each used the “populations” script in STACKS to filter for SNPs sequenced site and on each rat, after a quantile plot of the mean of the residuals in samples from all five sites (p = 5), and present in at least 60% of the found no severe deviations from the linear assumptions of these tests. samples (r = 0.6), with a minor allele frequency above 5%. Summary We wanted to test the ecological prediction that a rat occupying a site G statistics were reported from Stacks output, and ST differentiation with greater parasite richness is likely to harbour more diverse parasites. metrics between sites were calculated in the diveRsity package of R We predicted such a pattern in part because of an elevated risk of expo- G (Keenan, McGinnity, Cross, Crozier, & Prodöhl, 2013). ST is an alter- sure from the presence of a more diverse parasite community (Scordato native to FST estimates of genetic differentiation that accounts for dif- & Kardish, 2014). The analyses were performed using the base package ferences in samples size and genetic variation across sites (Hedrick, within R. 2005). To calculate genetic distance between individuals, we used Prevosti distance implemented in the poppr package of R (Kamvar, 2.5 | Effects of space on genetic similarity Tabima, & Grünwald, 2014), which is an absolute measure of shared alleles and can account for differences in missing data between individ- We used discriminant analysis of principal components (DAPC) to iden- uals. Finally, to identify pairs of individuals that were first- or second- tify genetic structure across our five sampling locations. This analysis, im- order relatives, we used the genome function in PLINK v1.07 (Purcell plemented in the adegenet package of R (Jombart, Devillard, & Balloux, et al. 2007) to calculate within-family kinship coefficients. 2010), identifies genetic structure by maximizing the genetic variation among sites while minimizing variation within identified groups. DAPC is particularly useful in visually assessing genetic variation along discri- 2.3 | Characterizing Parasite Communities minant function axes (Jombart et al., 2010). We also performed a Mantel We calculated species richness of the parasite community harboured test between genetic and geographical distances to detect the presence by each rat and at each sampling site using the number of unique ec- of genetic isolation by geographical distance (Jenkins et al., 2010). toparasite, bacterial and viral species observed in the sample. We also calculated abundance for ectoparasites, where the number of individ- 2.6 | Effects of genetic similarity on uals of each species was available. We used the Bray–Curtis ecological parasite community dissimilarity index to measure the differences in parasite communities between rats and sites (Bray & Curtis, 1957). This metric is common We evaluated the relationship between genetic divergence between in ecological studies on species community divergence between loca- rats and parasite community similarity to test the prediction that rats tions because it can be used for both abundance and presence–ab- that are more closely related genetically are also more likely to share sence data (Legendre & Gallagher, 2001). similar parasites, either through direct contact or dispersal-mediated parasite transmission (Beadell et al., 2004; Wassom, Dick, Arnason, Strickland, & Grundmannt, 1986). To test this relationship, we used 2.4 | Effects of spatial proximity on Mantel matrix correlation between genetic distance and Bray–Curtis parasite community distance matrices on both a site and individual level. To determine if We used canonical discriminant analysis (CDA) to summarize vari- there was a role for relatedness in parasite transmission, we also did a ation among parasite communities found at each site. This analysis principal component analysis on the parasite community data, which determines whether specific parasite species can aid in distinguish- summarizes multivariate data in new orthogonal axes. We then overlaid ing the origin of rats among the sampling sites based on occurrence highly related individuals onto the PCA biplot to see if they had more patterns and was performed in the candisc package of R (Friendly similar parasite communities than other, between-site pairs of rats. & Fox, 2016). We also used Mantel matrix correlations to determine the relationship between Bray–Curtis parasite dissimilarity 3 | RESULTS and Euclidean geographical distance between rats and sites. We log transformed the geographical distance data between rats to meet 3.1 | Genomic Sequencing the assumptions of normality. We predicted that rats located closer together would share a more similar parasite community. Mantel We retained genetic SNP profiles for 100 rats after filtering individuals tests account for non-independence among elements in distance for sequencing depth and genome alignment rate. SNP calling resulted matrices using permutations of the matrices for p-value calculations in 2,555 high-quality nuclear SNPs. Measures of genetic diversity var- (Legendre & Fortin, 2010; Mantel, 1967). ied across sites and include observed heterozygosity (mean = 0.108),

We evaluated differences in the levels of parasite richness across pi (0.122), and inbreeding coefficient FIS (0.086). Genetic differentia- G sites using analysis of variance (ANOVA). Significant differences among tion ( ST) between the five sites ranged from 0.116 to 0.278. ANGLEY et al. | 5

FIGURE 1 Canonical discriminant analysis of (a) ectoparasites, (b) bacteria and (c) viruses at each site. Blue arrows (and their length) represent the relative weight of each ectoparasite or microbe detected. Each site is represented by a black dot and label. Sites within the “Error” circle are all associated with the specified parasite species and cannot be discriminated from one another. Sites outside of this error range and along a blue arrow indicate that the parasite species on that arrow is strongly associated with only that sampling site. Panel (d) shows the location of the five study sites within the borough of Manhattan. [Colour figure can be viewed at wileyonlinelibrary.com]

highest site associations among the five locations. For ectoparasites, 3.2 | Effects of spatial proximity on parasite site RH3 was strongly associated with the presence of the oriental communities rat flea, while O. bacoti mites were associated with rats from the RS CDA of ectoparasites (Figure 1a), bacteria (Figure 1b) and viruses mixed-use location. Rats from RH1, RH2 and RP sites were weakly (Figure 1c) shows the linear combinations of species that have the associated with the presence of the spined rat louse and Laelaps rat 6 | ANGLEY et al.

FIGURE 3 Box plot showing total “per rat” parasite (ectoparasites and microbial pathogens) richness for each of the five sampling sites. There was a significant difference of total parasite richness across the

five sites [F(4,128) = 6.567, p < .001], with each colour and letter above the boxes representing the sites that differed significantly from each other (i.e., sites with the same letter were not significantly different from each other). [Colour figure can be viewed at wileyonlinelibrary. com]

had significantly lower richness (mean = 3.8 species per rat), followed by RH2 (mean = 5). The RP park site, RH1 and RH3 did not differ from each other and had the highest total richness (means = 6.1, 6.3 and 6.5, FIGURE 2 Regression analyses of pairwise geographical distance respectively). Viral richness differed significantly across the five sites between individuals and Bray–Curtis community dissimilarity for (F = 5.08, p < .001). The RS site had the lowest richness (mean = 1.0 (a) ectoparasite, (b) bacterial and (c) viral communities. Each dot represents a pair of rats, and as all pairs of rats trapped at the same virus per rat), followed by RH3 (mean = 2.1). The RH1 and RP sites location share a geographical distance of zero to each other; some did not differ significantly from each other and had the highest viral points overlap richness (means = 3.6 and 3.1, respectively). Bacterial richness also differed significantly across sites (F = 7.385, p < .001). The RH1, RH2 and mites (Figure 1a). In contrast, only a few microbes showed strong RS sites had significantly lower richness (mean = 0.6, 0.93, and 0.9). associations with a specific site. The outdoor RP site was the most The RH3 and RP sites did not differ from each other significantly and distinct from the other sites and was strongly associated with the had the highest bacterial richness (means = 1.75, 1.72). Ectoparasite presence of Campylobacter jejuni, L. interrogans, Shigella/Escherichia richness also differed across sites (F = 9.835, p < .001), with site RH3 coli (EIEC), Seoul hantavirus, orbivirus and calhevirus (Figure 1b). showing the highest richness (mean = 2.4 ectoparasite species per rat). The RH1 site was strongly associated with the presence of human The total count of parasite species richness also differed by site, sapovirus, porcine sapovirus, rosavirus and hepatitis E virus, and the with RH2 having the lowest and RP having the highest number of spe- RH3 site was strongly associated with the presence of Bartonella cies across all rats sampled (RH1 = 21; RH2 = 17; RH3 = 20; RP = 24; spp. (Figure 1c). RS = 18). Total parasite richness at each site explained 58% of the vari- There was a strong association between ectoparasite community ation in parasite richness harboured by individual rats (Figure 4), but dissimilarity and geographical distance between sites, with nearer sites the relationship was not significant (r2 = 0.586, p = .131). sharing more similar ectoparasite communities (r2 = 0.7295, p = .001; Figure 2a). A similar pattern was detected for the bacterial and viral 3.3 | Effects of space on genetic similarity communities, but with much less of the variation in community similarity explained by geographical distance (bacterial: r2 = 0.0855, p = .001; DAPC was conducted to partition the variance within the SNP geno- viral: r2 = 0.122, p = .001; Figure 2b,c). type data set across the five sampling locations (Figure 5). Individuals Total combined parasite species richness per rat differed signifi- from both RP and RS were genetically distinct from each other and cantly across the five sites (F = 6.567, p < .001; Figure 3). The RS site the three housing areas, which were more genetically similar to each ANGLEY et al. | 7

3.4 | Effects of genetic similarity on parasite communities

The relationship between the genetic data set of the 100 sequenced G individuals, using the ST pairwise genetic distance measure between sites, and the Bray–Curtis dissimilarity of parasite communities at each site was not statistically significant (r2 = 0.027, p = .525). A similar test was run at the individual level, which showed no relationship between pairwise genetic distances between rats and Bray–Curtis parasite dissimilarities (r2 = 0.003, p = .09). A separate principal components analysis with only the parasite community data found similar variation among sites as the CDA (Fig. S2). However, the three pairs of highly related individuals (r coefficient > 0.25) found at different sites did not share more similar parasite communities than indicated by the overall differences among sites (Fig. S2), further suggesting that FIGURE 4 Total parasite richness (ectoparasites and microbial genetic similarity is not associated with parasite community similarity. pathogens) at each site regressed onto individual rat parasite richness, with the line of best fit [r2 = 0.586, p = .131]. All 133 rats were included in this analysis; multiple points representing different rats overlap 4 | DISCUSSION

The parasite communities harboured by New York City rats are diverse and differ substantially between sites, even across small distances. There was a relationship between the similarities of parasite communities and how far apart the sites were from one another, as well as strong genetic differences among sites. In addition, certain parasite species were strongly associated with particular sites. This demonstrates how parasitic communities can be localized in an urban context and with further sampling of additional locations throughout NYC, and site-specific parasite associations may be useful for determining the site of origin for rats from unknown locations. Despite strong genetic differences among sites, there was no association between genetic divergence and parasite community similarity. The results from this study demonstrate how both parasite communities and host genetic structure may vary dramatically across fine spatial scales in an urban landscape. This variation also highlights how any public FIGURE 5 Discriminant analysis of principal components (DAPC) health strategy designed to reduce disease risk to humans must con- shows the genotypic variance within the SNP genotype data set of 100 of the 133 rats across the five sampling locations. Each rat sider that the rats across New York City do not carry a homogenous is denoted by a point, and each sampling location is represented set of parasites and pathogens. As a result, epidemiological risks may by colour and the ellipse surrounding the centroid of the rats’ be similarly heterogeneous for people in urban habitats. genotypes from that site. RP and RS are genetically distinct from In addition to spatial heterogeneity of the parasitic communities, the three housing complexes (RH1, RH2 and RH3), which are more certain species were strongly associated with particular sites, suggest- genetically similar to each other. [Colour figure can be viewed at wileyonlinelibrary.com] ing site specificity of some members of the parasite community. For example, discriminant analyses found that the oriental rat flea was strongly associated with the RH3 location, and the tropical rat mite other. Individuals from RH1 and RH3 are grouped close together with the RS location (Figure 1a). The combined association of RH1, in discriminant function space and also overlapped extensively with RH2 and RP with the spined rat louse and the spiny rat mite suggests RH2, which has more genetic variation than the other two hous- that these ectoparasites are more widely distributed throughout the ing areas. Importantly, this genetic differentiation is not consistent landscape and may be more prevalent across rat colonies. The pres- with geographical distance as RP and RH1 are closer geographically ence of certain microbial pathogens also characterized sites. Bartonella than RH1 and RH3. In addition, RH2 is located closest to RH3 geo- spp. were strongly associated with RH3, while L. interrogans, Shigella graphically, but not in terms of genetic similarity. Overall, there was spp./enteroinvasive E. coli and Campylobacter jejuni were found mostly G a weak correlation between the genetic data set, using ST, and the at the RP park site (Figure 1b). RP was also dominated by Seoul han- 2 geographical distance between sites (r = 0.261, p = .092). tavirus, orbivirus and calhevirus, while RH1 has a richer community of 8 | ANGLEY et al. site-specific viruses (Figure 1c). Ecological differences in the habitats capacity of these parasites is on rats. The movement of these rat res- across the five sites may drive site specificity among some members ervoirs is most likely driving any spatial patterns (or lack thereof) ob- of the parasite community. Despite close proximity, parasite commu- served in the parasite communities. nities can differ from one rat colony to the next, thus increasing the The divergence in parasite communities, even at neighbouring potential spread of a wider variety of zoonotic diseases across small sites, can be seen when comparing species richness and species com- areas of the city. By discriminating sites based on their unique par- position across sites. There was a significant difference in total spe- asite communities, and combining this with city data on rat and dis- cies richness across the five sites collectively (Figure 3). However, on ease “hotspots”, (e.g., Walsh 2014; Johnson et al., 2016), we may be a finer scale, sites that are closest in proximity, such as RP and RH1, able to predict the infection risks posed by specific rat colonies due had unique parasite communities (Figure 1) but similar species rich- to their small home-range size and limited dispersal. Also, with further ness (Figure 3). An ANOVA showed that RS had lower species rich- sampling of sites in NYC, site-specific parasites may be useful in de- ness compared to RH1, RH3 and RP. The relatively large geographical termining the site of origin in newly sampled rats across a similar geo- distance that separates RS from the other sites most likely isolates graphical scale. The heterogeneity of the parasites examined in this these rats and their parasitic species from those at the other sampled study suggests that some species may not be easily transmitted across locations. However, despite the smaller geographical range between colonies and may not persist in some colonies even if introduced, or the remaining sites, which we may expect to minimize parasite unique- that interactions between conspecifics in nearby colonies are lower ness, our results show distinct communities across fine spatial scales, than expected (Godfrey, 2013). as seen in the analyses of spatial proximity on parasite community When examining all rats in our study, parasite communities were (Figures 1 and 2). significantly more similar in rats located near each other. This pattern Analyses of our SNP genomic data for 100 of the 133 rats showed was driven by ectoparasites (Figure 2a), as there was a weak associa- no association between genetic divergence and parasite community tion between bacterial (Figure 2b) and viral (Figure 2c) similarity and divergence among sites or among individuals. Therefore, the genetic distance between hosts. Within a single colony, ectoparasites are structure occurring across the NYC landscape does not seem to influ- primarily transmitted through direct contact (Leu et al., 2010; Stanko ence the parasite communities harboured by rats. The genetic struc- et al., 2002). Shared nesting and communal care of young is common ture of entire colonies at a single site appears to have little effect on among rodents and may play an important role in the spread of ec- the parasites that may be specific to that location. This pattern may be toparasites (Hayes, 2000). Therefore, it may be the case that ecto- expected if the dominant modes of transmission do not include direct parasite similarities reflect sociality of rats and their proximity within contact between rats (Møller et al., 1993). Alternatively, if rats are able colonies, which promotes direct contact. However, despite the small to move between colonies and transmit parasites without breeding home-range size of most rats (Davis et al., 1948; Himsworth et al., (Leu et al., 2010), and hence without gene exchange, this could explain 2014), ectoparasites can still spread between members of different the lack of association between measures of gene flow and parasite colonies. This may occur when members leave in search for food re- community similarity. Lastly, founder effects could also lead to genetic sources or refuge (Glass et al., 2016), or when rats from nearby colo- divergence not corresponding to parasite community differences if the nies reinvade areas that have been subject to intensive pest control. parasite community is determined primarily by dispersing individuals Also, as rodent populations increase, territories may begin to overlap, founding a new colony and if the gene pool of the new colony experi- which promotes higher contact frequencies and ectoparasite trans- ences a genetic bottleneck resulting in strong genetic differences be- mission (Altizer et al., 2003; Davis et al., 1948; Kerth & Van Schaik, tween the source and new colonies. New parasite species only arrive 2012). Direct contact is not necessary for the transmission of many when rats successfully invade the colony or during movements within microbial pathogens (Himsworth, Bidulka et al., 2013; Himsworth, the small home ranges of R. norvegicus. However, more research will Parsons et al., 2013), which can also be transmitted through urine or be needed to identify the reason for this limited association. faeces and in some cases, remain viable outside of the body for some Additional analyses of the genomic data showed strong genetic G time (Karaseva et al., 1973). Because indirect transmission is possible differentiation between the five sites, with ST values ranging from in these cases, microbial communities are less likely to remain isolated 0.12 to 0.28. However, genetic differentiation was not strongly as- based on proximity among colonies, which is consistent with our re- sociated with geographical distance between sampling locations. For sults of a lack of association between distance and microbial commu- example, despite being close in proximity, rats from nearby sites such nity similarity in rats. Yet, we note that some microbial pathogens can as RP and RH1 were genetically isolated (Figure 5). In contrast, the res- also be spread through direct transmission from intermediate hosts idential sites were farther apart from each other, yet were more genet- or through arthropod vectors (e.g., Bartonella spp. and orbiviruses; ically similar (RH1, RH2 and RH3; Figure 5). Variation in the ecological Billeter, Levy, Chomel, & Breitschwerdt, 2008). However, the host characteristics of the sites may be driving the genetic structure among range is likely very narrow for the microbes and ectoparasites detected locations. This finding is consistent with growing evidence that non- in the rats in our study, especially considering the depauperate animal random dispersal resulting from habitat selection, known as “natal communities within lower Manhattan that could serve as reservoirs. habitat preference induction” in rodents, can lead to directed gene Additionally, none of the microbes detected are known to be vectored flow that promotes phenotypic and genotypic differences between by flying insects, suggesting that the maximum potential movement habitat types (Edelaar, Siepielski, & Clobert, 2008; Mabry & Stamps, ANGLEY et al. | 9

2008; Merrick & Koprowski, 2016; Rice, 1984). For an urban rat, hous- by National Science Foundation grant numbers DEB 145723 and ing, parks and green spaces and mixed-use infrastructure are very dif- DBI 1531639 to J. Munshi-South. J. Richardson was supported by a ferent habitats. Their neophobic behaviour also suggests that rats are Research Opportunity Award (ROA) supplement, and L. Angley by a likely to develop habitat preferences based on the environment they Research Experiences for Undergraduates (REU) supplement, to NSF are familiar with, so dispersing rats may seek out habitats similar to DEB 145723. their natal habitats (Barnett 1958). The three housing complexes are ecologically similar and share genetically similar rat communities. In CONFLICT OF INTEREST contrast, the park and mixed-use site are ecologically and genetically unique. In addition, the building structure, food supply, sewer systems The authors have no known conflict of interests related to this work. and dense human populations characteristics of residential housing complexes may provide the rats with a greater surplus of shelter and ORCID resources. The high resource levels may increase fecundity and drive the movement of these rats to the ecologically similar RH1, RH2 and J. L. Richardson http://orcid.org/0000-0002-3701-2115 RH3 sites (Himsworth et al., 2014). REFERENCES

Altizer, S., Nunn, C. C. L., Thrall, P. P. H., Gittleman, J. L. J., Antonovics, J., 5 | CONCLUSION Cunningham, A. A., … Pulliam, J. R. C. (2003). Social organization and parasite risk in mammals: Integrating theory and empirical studies. Here, we have provided an evaluation of the relationship between Annual Review of Ecology, Evolution, and Systematics, 34, 517–547. https://doi.org/10.1146/annurev.ecolsys.34.030102.151725 urban rat connectivity and associated parasite communities. These Aplin, K. P., Chesser, T., & Ten Have, J. (2003). Evolutionary biology of the findings provide important insights into how pathogens of public genus Rattus: Profile of an archetypal rodent pest. In G. R. Singleton, health concern are distributed in the urban core of New York City L. A. Hinds, C. J. Krebs, & D. M. Spratt (Eds.), Rats, Mice and People: and can be used to assist future rodent control and epidemiologi- Rodent Biology and Management (pp. 487–498). Canberra, Australia: cal interventions. The parasite communities harboured by rats were ACIAR. heterogeneous across the study area, which appears to be consistent Barnett, S. A. (1958). An analysis of social behaviour in wild rats. Proceedings of the Zoological Society of London, 130, 107–152. with modes of contact and transmission between rats. This pattern Beadell, J. S., Gering, E., Austin, J., Dumbacher, J., Peirce, M., Pratt, suggests that the risk of zoonotic infection to humans also varies dra- T., … Fleishcer, R. C. (2004). Prevalence and differential host- matically across fine spatial scales, creating a challenge to epidemiolo- specificity of two avian blood parasite genera in the Australo- gists and public health official tasked with monitoring and predicting Papuan region. Molecular Ecology, 13, 3829–3844. https://doi. org/10.1111/j.1365-294X.2004.02363.x disease risk. The genetic connectivity of rats in our study indicates Billeter, S. A., Levy, M. G., Chomel, B. B., & Breitschwerdt, E. B. (2008). that urban habitats are highly heterogeneous over fine spatial scales. Vector transmission of Bartonella species with emphasis on the poten- Researchers may need to take this heterogeneity into account when tial for tick transmission. Medical and Veterinary Entomology, 22, 1–15. predicting likely pathways of rat dispersal, as gene flow was not re- https://doi.org/10.1111/j.1365-2915.2008.00713.x Bradley, C. A., & Altizer, S. (2007). Urbanization and the ecology of wild- lated to simple distance on the landscape. Resource abundance and life diseases. Trends in Ecology and Evolution, 22, 95–102. https://doi. dwelling characteristics may drive the direction of dispersal more than org/10.1016/j.tree.2006.11.001 spatial distribution. Variation in the parasite communities and the ge- Bray, J. R., & Curtis, J. T. (1957). An Ordination of the upland forest com- netic structure of their hosts highlights the importance of strategic munity of southern Wisconsin. Ecological Monographs, 27(4), 325–349. https://doi.org/10.2307/1942268 approaches when dealing with New York City rats, and likely other Brown, C. R., & Brown, M. B. (2017). Empirical Measurement of Parasite cities as well. In order to reduce disease risk to humans, public health Transmission between Groups in a Colonial Bird. Ecology, 85, officials should consider different colonies of rats as reservoirs of 1619–1626. unique sets of zoonotic pathogens. Programs to prevent rodent-borne Catchen, J., Hohenlohe, P. A., Bassham, S., Amores, A., & Cresko, W. A. (2013). Stacks: An analysis tool set for population genomics. Molecular disease outbreaks in humans should include spatially appropriate field Ecology, 22, 3124–3140. https://doi.org/10.1111/mec.12354 monitoring and adaptive responses to variation in pathogen pres- Childs, J. E., McLafferty, S. L., Sadek, R., Miller, G. L., Khan, A. S., DuPree, ence across the cityscape. Understanding this connection between E. R., … Glass, G. E. (1998). Epidemiology of Rodent Bites and rat ecology and connectivity of these zoonotic reservoirs in an urban Prediction of Rat Infestation in New York City. American Journal of landscape is a required first step to predicting zoonotic disease risk to Epidemiology, 148, 78–87. https://doi.org/10.1093/oxfordjournals. aje.a009563 humans in these areas. Costa, F., Porter, F. H., Rodrigues, G., Farias, H., de Faria, M. T., Wunder, E. A., … Childs, J. E. (2014). Infections by Leptospira interrogans, Seoul virus, and Bartonella spp. among Norway rats (Rattus norvegicus) ACKNOWLEDGEMENTS from the urban slum environment in Brazil. Vector Borne and Zoonotic Diseases, 14, 33–40. https://doi.org/10.1089/vbz.2013.1378 We thank Matt Firth, Meera Bhat and Bobby Corrigan for assis- Davis, D. E., Emlen, J. T., & Stokes, A. W. (1948). Studies on Home Range tance in field collections of rats, and Miranda Gonzalez and Kaitlyn in the Brown Rat. Journal of Mammalogy, 29, 207–225. https://doi. Abrams for assisting with laboratory work. This work was supported org/10.2307/1375387 10 | ANGLEY et al.

Diagne, C. A., Galan, M., Tamisier, L., d’Ambrosio, J., Dalecky, A., Ba, K., Hilton, A. C., Willis, R. J., & Hickie, S. J. (2002). Isolation of Salmonella from … Brouat, C. (2017). Biological invasions in rodent communities: urban wild brown rats (Rattus norvegicus) in the West Midlands, UK. From ecological interactions to zoonotic bacterial infection issues. International Journal of Environmental Health Research, 12, 163–168. bioRxiv, 108423. https://doi.org/10.1101/10842 https://doi.org/10.1080/09603120220129328 Doherty, T. S., Glen, A. S., Nimmo, D. G., Ritchie, E. G., & Dickman, C. R. Himsworth, C. G., Bidulka, J., Parsons, K. L., Feng, A. Y. T., Tang, P., Jardine, (2016). Invasive predators and global biodiversity loss. Proceedings C. M., … Patrick, D. M. (2013). Ecology of Leptospira interrogans in of the National Academy of Sciences, 113, 11261–11265. https://doi. Norway Rats (Rattus norvegicus) in an Inner-City Neighborhood of org/10.1073/pnas.1602480113 Vancouver, Canada. PLoS Neglected Tropical Diseases, 7(6), e2270. Durrer, S., & Schmid-hempel, P. (2017). Shared use of flowers leads to https://doi.org/10.1371/journal.pntd.0002270 horizontal pathogen transmission. Proceedings of the Royal Society B: Himsworth, C. G., Jardine, C. M., Parsons, K. L., Feng, A. Y. T., & Patrick, Biological Sciences, 258(1353), 299–302. D. M. (2014). The characteristics of wild rat (Rattus spp.) populations Edelaar, P., Siepielski, A. M., & Clobert, J. (2008). Matching habitat choice from an inner-city neighborhood with a focus on factors critical to the causes directed gene flow: A neglected dimension in evolution and understanding of rat-associated zoonoses. PLoS ONE, 9(3), e91654. ecology. Evolution, 62, 2462–72. https://doi.org/10.1111/evo.2008.62. https://doi.org/10.1371/journal.pone.0091654 issue-10 Himsworth, C. G., Parsons, K. L., Jardine, C., & Patrick, D. M. (2013). Rats, Felzemburgh, R. D. M., Ribeiro, G. S., Costa, F., Reis, R. B., Hagan, J. E., cities, people, and pathogens: A systematic review and narrative syn- Melendez, A. X. T. O., … Ko, A. I. (2014). Prospective study of leptospiro- thesis of literature regarding the ecology of rat-associated zoonoses sis transmission in an urban slum community: Role of poor environment in urban centers. Vector Borne and Zoonotic Diseases, 13, 349–359. in repeated exposures to the Leptospira agent. PLoS neglected tropical https://doi.org/10.1089/vbz.2012.1195 diseases, 8, e2927. https://doi.org/10.1371/journal.pntd.0002927 Jenkins, D. G., Carey, M., Czerniewska, J., Fletcher, J., Hether, T., Jones, Feng, A. Y. T., & Himsworth, C. G. (2014). The secret life of the city rat: A., … Tursi, R. (2010). A meta-analysis of isolation by distance: Relic A review of the ecology of urban Norway and black rats (Rattus nor- or reference standard for landscape genetics Ecography, 74, 315–320. vegicus and Rattus rattus). Urban Ecosystems, 17, 149–162. https://doi. https://doi.org/10.1111/j.1600-0587.2010.06285.x org/10.1007/s11252-013-0305-4 Johnson, S., Bragdon, C., Olson, C., Merlino, M., & Bonaparte, S. (2016). Firth, C., Bhat, M., Firth, M. A., Williams, S. H., Frye, M. J., Simmonds, P., Characteristics of the Built Environment and the Presence of the Norway … Ian Lipkin, W. (2014). Detection of zoonotic pathogens and char- Rat in New York City: Results From a Neighborhood Rat Surveillance acterization of novel viruses carried by commensal rattus norvegicus Program, 2008–2010. Journal of Environmental Health, 78, 22–29. in New York city. mBio, 5(5), e01933-14. https://doi.org/10.1128/ Jombart, T., Devillard, S., & Balloux, F. (2010). Discriminant analysis of mBio.01933-14 principal components: A new method for the analysis of genet- Friendly, M., & Fox, J. (2016). Package candisc: Visualizing Generalized ically structured populations. BMC Genetics, 11, 94. https://doi. Canonical Discriminant and Canonical Correlation Analysis. R package org/10.1186/1471-2156-11-94 version. Kamvar, Z. N., Tabima, J. F., & Grünwald, N. J. (2014). Poppr: An R package Frye, M. J., Firth, C., Bhat, M., Firth, M. A., Che, X., Lee, D., … Lipkin, W. I. for genetic analysis of populations with clonal, partially clonal, and/or (2015). Preliminary survey of ectoparasites and associated pathogens sexual reproduction. PeerJ, 2, e281. https://doi.org/10.7717/peerj.281 from Norway rats in New York City. Journal of Medical Entomology, 52, Karaseva, E. V., Chernukha, Y. G., & Piskunova, L. A. (1973). Results of study- 253–259. https://doi.org/10.1093/jme/tjv014 ing the time of survival of pathogenic leptospira under natural condi- Gardner-Santana, L. C., Norris, D. E., Fornadel, C. M., Hinson, E. R., Klein, tions. Journal of Hygiene, Epidemiology, Microbiology, and Immunology, S. L., & Glass, G. E. (2009). Commensal ecology, urban landscapes, and 17, 339–45. their influence on the genetic characteristics of city-dwelling Norway Keenan, K., McGinnity, P., Cross, T. F., Crozier, W. W., & Prodöhl, P. A. rats (Rattus norvegicus). Molecular Ecology, 18, 2766–78. https://doi. (2013). diveRsity : An R package for the estimation and explora- org/10.1111/mec.2009.18.issue-13 tion of population genetics parameters and their associated errors. Gedeon, T., Bodelón, C., & Kuenzi, A. (2010). Hantavirus Transmission Methods in Ecology and Evolution, 4, 782–788. https://doi.org/10.1111/ in Sylvan and Peridomestic Environments. Bulletin of Mathematical mee3.2013.4.issue-8 Biology, 72, 541–564. https://doi.org/10.1007/s11538-009-9460-4 Kerth, G., & Van Schaik, J. (2012). Causes and consequences of living Glass, G., Klein, S., Norris, D., & Gardner, L. (2016). Multiple paternity in closed societies: Lessons from a long-term socio-genetic study in urban norway rats: Extended ranging for mates. Vector-Borne on Bechstein’s bats. Molecular Ecology, 21, 633–646. https://doi. and Zoonotic Diseases, 16(5), 342–348. https://doi.org/10.1089/ org/10.1111/j.1365-294X.2011.05233.x vbz.2015.1816 Ko, A. I., Reis, M. G., Dourado, C. M. R., Johnson, W. D., & Riley, L. W. Godfrey, S. S. (2013). Networks and the ecology of parasite transmis- (1999). Urban epidemic of severe leptospirosis in Brazil. The Lancet, sion: A framework for wildlife parasitology. International Journal 354, 820–825. https://doi.org/10.1016/S0140-6736(99)80012-9 for Parasitology: Parasites and Wildlife, 2, 235–245. https://doi. Langmead, B., & Salzberg, S. L. (2012). Fast gapped-read alignment with org/10.1016/j.ijppaw.2013.09.001 Bowtie 2. Nature Methods, 9, 357–359. https://doi.org/10.1038/ Hayes, L. D. (2000). To nest communally or not to nest communally: A re- nmeth.1923 view of rodent communal nesting and nursing. Animal Behaviour, 59, Legendre, P., & Fortin, M. J. (2010). Comparison of the Mantel test and al- 677–688. https://doi.org/10.1006/anbe.1999.1390 ternative approaches for detecting complex multivariate relationships Hedrick, P. W. (2005). A standardized genetic differentiation measure. in the spatial analysis of genetic data. Molecular Ecology Resources, 10, Evolution, 59, 1633–1638. https://doi.org/10.1111/evo.2005.59. 831–844. https://doi.org/10.1111/j.1755-0998.2010.02866.x issue-8 Legendre, P., & Gallagher, E. D. (2001). Ecologically meaningful transforma- Heiberg, A.-C., Sluydts, V., Leirs, H., Abdelkrim, J., Pascal, M., Calmet, C., tions for ordination of species data. Oecologia, 129, 271–280. https:// … Ward, J. H. (2012). Uncovering the secret lives of sewer rats (Rattus doi.org/10.1007/s004420100716 norvegicus): Movements, distribution and population dynamics re- Leibler, J. H., Zakhour, C. M., Gadhoke, P., & Gaeta, J. M. (2016). Zoonotic vealed by a capture - mark - recapture study. Wildlife Research, 39, 202. and vector-borne infections among urban homeless and marginal- https://doi.org/10.1071/WR11149 ized people in the United States and Europe, 1990–2014. Vector- Hijmans, R. J., & Van Etten, J. (2014). Raster: Geographic data analysis and Borne and Zoonotic Diseases, 16, 435–444. https://doi.org/10.1089/ modeling. R package version 2.2-31. vbz.2015.1863 ANGLEY et al. | 11

Leu, S. T., Kappeler, P. M., & Bull, C. M. (2010). Refuge sharing network pre- Richardson, J. L., Burak, M. K., Hernandez, C., Shirvell, J. M., Mariani, C., dicts ectoparasite load in a lizard. Behavioral Ecology and Sociobiology, Carvalho-Pereira, T. S. A., … Caccone, A. (2017). Using fine scale spatial 64, 1495–1503. https://doi.org/10.1007/s00265-010-0964-6 genetics of Norway rats to improve control efforts and reduce leptospi- Mabry, K. E., & Stamps, J. A. (2008). Dispersing brush mice prefer rosis risk in urban slum environments. Evolutionary Applications, 10(4), habitat like home. Proceedings of the Royal Society of London B: 323–337. https://doi.org/10.1111/eva.12449 Biological Sciences, 275(1634), 543–548. https://doi.org/10.1098/ Rogalski, M. A., Gowler, C. D., Shaw, C. L., Hufbauer, R. A., & Duffy, M. rspb.2007.1541 A. (2016). Human drivers of ecological and evolutionary dynamics in Mantel, N. (1967). The Detection of Disease Clustering and a Generalized emerging and disappearing infectious disease systems. Philosophical Regression Approach. Cancer Research, 27, 209–220. Transactions of the Royal Society of London B: Biological Sciences, Meerburg, B. G., Singleton, G. R., & Kijlstra, A. (2009). Rodent-borne dis- 372(1712), 20160043. https://doi.org/10.1098/rstb.2016.0043 eases and their risks for public health. Critical Reviews in Microbiology, Scordato, E. S. C., & Kardish, M. R. (2014). Prevalence and beta diversity 35, 221–270. https://doi.org/10.1080/10408410902989837 in avian malaria communities: Host species is a better predictor than Merrick, M. J., & Koprowski, J. L. (2016). Evidence of natal habitat prefer- geography. Journal of Animal Ecology, 83, 1387–1397. https://doi. ence induction within one habitat type. Proceedings of the Royal Society org/10.1111/1365-2656.12246 of London B: Biological Sciences, 283(1842), 20162106. https://doi. Stanko, M., Miklisová, D., De Bellocq, J. G., & Morand, S. (2002). org/10.1098/rspb.2016.2106 Mammal density and patterns of ectoparasite species richness and Møller, A. P., Dufva, R., & Allander, K. (1993). Parasites and the Evolution abundance. Oecologia, 131, 289–295. https://doi.org/10.1007/ of Host Social Behavior. Advances in the Study of Behavior, 22, 65–102. s00442-002-0889-5 https://doi.org/10.1016/S0065-3454(08)60405-2 Walsh, M. G. (2014). Rat sightings in New York City are associated with Nash, D., Mostashari, F., Fine, A., Miller, J., O’Leary, D., Murray, K., … Layton, neighborhood sociodemographics, housing characteristics, and prox- M. (2001). The Outbreak of West Nile Virus Infection in the New York imity to open public space. PeerJ, 2, e533. https://doi.org/10.7717/ City area in 1999. The New England, 334, 1807–1014. https://doi. peerj.533 org/10.1056/NEJM200106143442401 Wassom, D. L., Dick, T. A., Arnason, N., Strickland, D., & Grundmannt, A. W. Patz, J. A., Daszak, P., Tabor, G. M., Aguirre, A. A., Pearl, M., Epstein, J., … (1986). Host Genetics: A Key Factor in Regulating the Distribution of Zakarov, V. (2004). Unhealthy landscapes: Policy recommendations Parasites in Natural Host Populations. The Journal of Parasitology, 72, on land use change and infectious disease emergence. Environmental 334–337. https://doi.org/10.2307/3281615 Health Perspectives, 112, 1092–1098. https://doi.org/10.1289/ ehp.6877 Puckett, E. E., Park, J., Combs, M., Blum, M. J., Bryant, J. E., Caccone, A., … SUPPORTING INFORMATION Munshi-South, J. (2016). Global population divergence and admixture of the brown rat (Rattus norvegicus). Proceedings of the Royal Society Additional Supporting Information may be found online in the of London B: Biological Sciences, 283(1841), 20161762. https://doi. supporting information tab for this article. org/10.1101/065458 Purcell, S., Neale, B., Todd-Brown, K., Thomas, L., Ferreira, M. A. R., Bender, D., … Sham, P. C. (2007). PLINK: A tool set for whole-genome associa- How to cite this article: Angley LP, Combs M, Firth C, et al. tion and population-based linkage analyses. American Journal of Human Spatial variation in the parasite communities and genomic Genetics, 81(3), 559–575. https://doi.org/10.1086/519795 structure of urban rats in New York City. Zoonoses Public Rice, W. R. (1984). Disruptive selection on habitat preference and the evolution of reproductive isolation: A simulation study. Evolution, 38, Health. 2017;00:1–11. https://doi.org/10.1111/zph.12418 1251–1260. https://doi.org/10.1111/evo.1984.38.issue-6