key: cord-0914732-9myiiuzd
authors: Turmelle, Amy S.; Olival, Kevin J.
title: Correlates of Viral Richness in Bats (Order Chiroptera)
date: 2010-01-05
journal: Ecohealth
DOI: 10.1007/s10393-009-0263-8
sha: da47cadf1cef48d1fbcac6f6301899a970ccca7c
doc_id: 914732
cord_uid: 9myiiuzd

Historic and contemporary host ecology and evolutionary dynamics have profound impacts on viral diversity, virulence, and associated disease emergence. Bats have been recognized as reservoirs for several emerging viral pathogens, and are unique among mammals in their vagility, potential for long-distance dispersal, and often very large, colonial populations. We investigate the relative influences of host ecology and population genetic structure for predictions of viral richness in relevant reservoir species. We test the hypothesis that host geographic range area, distribution, population genetic structure, migratory behavior, International Union for Conservation of Nature and Natural Resources (IUCN) threat status, body mass, and colony size, are associated with known viral richness in bats. We analyze host traits and viral richness in a generalized linear regression model framework, and include a correction for sampling effort and phylogeny. We find evidence that sampling effort, IUCN status, and population genetic structure correlate with observed viral species richness in bats, and that these associations are independent of phylogeny. This study is an important first step in understanding the mechanisms that promote viral richness in reservoir species, and may aid in predicting the emergence of viral zoonoses from bats.

Emerging infectious diseases (EIDs) are mostly viral and zoonotic in origin Wolfe et al., 2007) and a growing number are discovered each year (Woolhouse et al., 2008) . Several studies have undertaken large-scale analyses to determine risk factors associated with EIDs Jones et al., 2008) , and have identified host range, as well as pathogen taxonomy and molecular characteristics as the most important (Cleaveland et al., 2001; Woolhouse and Gowtage-Sequeria, 2005; Holmes and Drummond, 2007; Pulliam and Dushoff, 2009) . Molecular characteristics of viruses that likely contribute to emergence in novel hosts include physical or biochemical features, e.g., the ability to replicate in the cytoplasm (Pulliam and Dushoff, 2009) , and evolutionary potential, e.g., rapid mutation rates and processes such as recombination or reassortment (Holmes and Drummond, 2007) . Additionally, viruses that utilize highly conserved cell receptors (e.g., rabies virus) may have higher probabilities of successful cross-species transmission and emergence (Holmes and Drummond, 2007) .

Despite the importance of intrinsic pathogen characteristics, host life history, ecology, and spatial structure also contribute to the emergence, persistence, and intensity of zoonotic outbreaks (Bolzoni et al., 2007; Webb et al., 2007; Plowright et al., 2008) .

As viruses may be relatively unstable outside their hosts, the dynamics and frequency of intra-or interspecific host interactions will largely affect encounter probabilities related to disease emergence (Pulliam, 2008) . The structure of wildlife populations across the landscape also has strong implications for infectious disease dynamics and emergence (Real and Biek, 2007) . Major developments have been made in theoretical (Rand et al., 1995; Sasaki, 1999, 2000; Haraguchi and Sasaki, 2000; Boots et al., 2004; Cross et al., 2005; Webb et al., 2007) and experimental (Bull et al., 1991; Messenger et al., 1999; Kerr et al., 2006; Boots and Mealor, 2007) studies linking population structure, disease dynamics, and pathogen evolution, with particular advances in our understanding of how contact networks regulate pathogen persistence and virulence. Evidence from natural systems has validated the ecological theories on spatial infection processes (Ewald, 1991; Herre, 1993; de Roode et al., 2008) , and recent studies have highlighted the importance of contact and transmission heterogeneities in modeling disease prevalence and control strategies (Barlow, 1996; Lloyd-Smith et al., 2005; Donnelly et al., 2006; May, 2006; Bolzoni et al., 2007; Bohm et al., 2009) .

Another key factor in predicting the emergence of zoonoses is the number of viruses, or viral richness, found in natural reservoir species (Wolfe et al., 2005) . This largely unknown, natural diversity of pathogens in wildlife hosts has been termed the ''zoonotic pool'' (Morse, 1993) . The fields of phylogenetics, population genetics, and biogeography have led to key advancements in our understanding of host-pathogen coevolution in relation to pathogen diversity (Pybus et al., 2000; Grenfell et al., 2004) , and numerous studies have documented coevolution between pathogens and their hosts (Smith, 1996; Asikainen et al., 2000; Gaunt et al., 2001; Nieberding et al., 2004; Criscione et al., 2005; Biek et al., 2006; Dragoo et al., 2006; Criscione and Blouin, 2007; Liu et al., 2008) . However, we know little about which factors are most important in creating and sustaining pathogen richness within reservoir hosts. Comparative approaches are needed that test for patterns of pathogen richness across multiple factors for groups of potential reservoir host species.

Few studies have simultaneously examined phylogenetic and socioecological factors affecting parasite richness, and the majority have focused on primates. Davies and Pedersen (2008) found that host geographic range overlap was a significant determinant of viral communities in primates, although phylogenetic relatedness was also an important predictor of richness for other taxonomic groups of parasites in their analysis. A separate study found a significant correlation between viral species richness, host geographic range area, and population density across primates when corrections for phylogeny and sampling effort were included (Nunn et al., 2003) . A similar study also found a correlation between viral richness, host phylogenetic diversity, and host geographic range overlap (Nunn et al., 2004) . In a more recent study, threatened primates harbored lower parasite species richness compared to nonthreatened hosts, although this effect was not significant for viruses when other host socioecological traits were included (Altizer et al., 2007) . Ezenwa (2004) found that group size and social behavior were important correlates with parasite diversity in African bovids. Gregory (1990) found positive correlations between helminth richness and geographic range, but no associations with host socioecological traits, in Holarctic waterfowl. Across studies, host population density, geographic range area, and phylogeny emerge as consistent predictors of parasite richness. All of these studies also report highly significant positive correlations between parasite richness and sampling effort, which suggests that parasite richness has been largely underestimated for many vertebrate hosts.

Bats (Order Chiroptera), which comprise nearly 1200 species, have been linked as natural reservoir hosts to a rapidly growing number of EIDs (Calisher et al., 2006) . This includes several viruses that cause severe disease in humans: Ebola (Leroy et al., 2005) and Marburg (Swanepoel et al., 2007) filoviruses, SARS and related coronaviruses (Li et al., 2005; Dominguez et al., 2007; Muller et al., 2007; Carrington et al., 2008; Gloza-Rausch et al., 2008; Tong et al., 2009) , as well as Nipah (Johara et al., 2001) , Hendra (Halpin et al., 2000) and related paramyxoviruses (Drexler et al., 2009 ). It has recently been suggested that two human cases of acute respiratory illness in Malaysia may be linked to reoviruses of bat origin (Chua et al., 2007; Chua et al., 2008) . Furthermore, evidence supports the association of bats with lyssavirus infection in humans globally (Lumio et al., 1986; Allworth et al., 1996; Warner et al., 1999; Favi et al., 2002; Messenger et al., 2002; Fooks et al., 2003; da Rosa et al., 2006; van Thiel et al., 2008) . The importance of bat-borne zoonoses has only recently been appreciated, and no studies to date have examined factors that may explain the large diversity of viruses in the Order Chiroptera. Bats exhibit a wide range of morphological, ecological, and behavioral characteristics, and similarly, are characterized by highly variable patterns of genetic population structure (Nowak, 1999; Burland and Worthington-Wilmer, 2001) . These features make the Order Chiroptera ideal for testing hypotheses regarding patterns of hostpathogen coevolution and viral richness.

Many hypotheses have been suggested for the association of bats and EIDs, some of which include high species diversity, long life spans, capacity for long-distance dispersal, dense roosting aggregations (colony size) for many species, the use of torpor and hibernation, unique immunology, and spatial population structure (Messenger et al., 2003a; Calisher et al., 2006) . While all of these factors are likely to be important, we investigate the significance of colony size, migratory ability, population genetic structure, geographic range area and distribution (continental vs. island), International Union for Conservation of Nature and Natural Resources (IUCN) threatened status, and body mass in generalized linear models of viral richness across Chiroptera, while accounting for sampling effort and phylogeny. We hypothesize that larger colony sizes will be positively correlated with viral richness, as a larger number of susceptible individuals in a population will permit greater viral establishment and persistence (Anderson and May, 1986) . We also hypothesize that stronger population structure will be positively associated with viral richness, due to coevolutionary forces as a driver of within-lineage pathogen diversity and the importance of metapopulation structure in invasion and enzootic infection processes (Webb et al., 2007) . As island taxa tend to have more restricted geographic ranges, and may be more prone to extinction, we predict that species with an island distribution will have fewer viruses than bats with a continental range distribution. Threatened bat species may have fewer viruses than nonthreatened taxa because parasites may be more likely to go extinct in smaller fragmented host populations . However, threatened species may be more susceptible to multihost pathogens, potentially as a result of reduced immunological diversity, stress, and poor nutritional status of hosts across fragmented landscapes (Lyles and Dobson, 1993; Messenger et al., 2003a) . Migratory species are expected to harbor more viruses than nonmigratory species as they sample more diverse habitats and may be subject to greater interspecific contact. Larger hosts with greater body mass may harbor greater viral richness, as has been suggested from studies in primates (Nunn et al., 2003) . Although we explore associations of life history, genetics, and ecology with viral infection in bats, these factors may predict infection but not disease in bats. It has been suggested that bats may not develop clinical disease from infection with certain viral pathogens, such as filoviruses, henipaviruses, and coronaviruses; however, clinical signs of disease are observed following infection with other viral pathogens such as lyssaviruses. This is, to our knowledge, the first metaanalyses to quantitatively investigate the effect of these explanatory variables on viral richness in bats.

Population genetic structure data were gathered from published literature by searching Science Citation Index Expanded and ISI Zoological Record for the years 1985-2009 with various combinations of keywords: population, structure, genetic*, bat*, mammal*, and Chiroptera. Additional references not identified during keyword searches were collected from published reviews (Burland and Worthington-Wilmer, 2001) , literature cited, and the Digital Dissertation Database. Population genetic data for 54 species of bats were compiled. Representative nuclear allelic F ST (Wright, 1951) or mitochondrial haplotypic u ST (Excoffier et al., 1992) estimates of population structure from each species were calculated separately as the mean of all pairwise F ST or u ST values in a study, and taken across multiple studies for the same species when available. A global mean value was also obtained by averaging F ST and u ST when available. Thus, the global F ST value for each bat species summarizes data from single or multiple, mitochondrial and nuclear, empirical estimates. The advantage of F ST over direct measures of genetic diversity such as nucleotide diversity is that, as a ratio that describes the proportion of population genetic subdivision, it is largely independent from the mutation process so that data from different molecular markers can be easily compared (Pannell and Charlesworth, 2000) . This comparability, along with its common use, makes F ST the most appropriate statistic for comparative analyses of population structure across studies using different molecular markers. As previous studies have suggested potential correlations between population structure indices and geographic sampling distance (Burland and Worthington-Wilmer, 2001) , the average geographic sampling distance (km) between populations was calculated from empirical studies to test for this bias.

Bat species were assigned as being migratory or nonmigratory based on definitions presented in Fleming and Eby (2003) and data from previous ecological studies (including capture-mark-recapture data) or published reviews (McCracken, 1987; Burland and Worthington-Wilmer, 2001; Fleming and Eby, 2003) . If a species had populations that were both migratory and nonmigratory, e.g., Tadarida brasiliensis (McCracken and Gassel, 1997), then the species was coded as migratory. Average colony size was recorded from the Mammalian Species account for a species when available, or the IUCN Red List database, or reconciled from both sources. The distribution of a species was coded from geographic range data presented in the IUCN Red List database (IUCN, 2009), and was either ''continental'' or ''island.'' If a species distribution included continental and island areas, assignment reflects the majority of the geographic range. IUCN Red List status was obtained directly from the database (IUCN, 2009). Body mass data were gathered from Norberg and Rayner (1987) , and we used geographic range area estimates from Jones et al. (2003) .

We then searched the literature and compiled records for all known viruses occurring in the 54 bat species with available population structure data. Viral information was available for 33 of 54 (61%) species for which we also had population structure estimates. The majority of the viral associations were obtained from previously published reviews (Messenger et al., 2003a; Calisher et al., 2006; Wong et al., 2007) , but additional literature searches on PubMed and Web of Science were conducted to identify recent events. When possible, we also recorded the method of viral detection from the original papers cited. Typical methods of detection included mouse inoculation or cell culture for viral isolation, although alternate methods included the fluorescent antibody test (FAT) or polymerase chain reaction (PCR) to detect viral antigen from organs or tissues of bats. One exclusion criterion was employed in our database, and this was for records of arbovirus detection through serology only. As bats are likely to be incidental hosts to most arboviruses, and positive serological results may be nonspecific in differentiating viruses with noted cross-reactivity (e.g., genus Flavivirus), serological detection of arbovirus antibodies was not considered as evidence of a viral association. All viral records were considered unique for subsequent analysis with the exception of bat gammaherpesviruses (BatGHV), where BatGHV-1, 2, 4, 6, and 7 were considered one viral species, and the phylogenetically distant BatGHV-3 was considered to be a separate unique virus (Wibbelt et al., 2007) .

Previous studies have demonstrated that sampling effort is likely to be uneven across species, and can confound interpretations with other biological variables of interest. To account for variation in sampling effort across species, we searched the ISI Zoological Record from 1945 to 2009 for each bat species. The number of citations per species was recorded, and used as an index of sampling effort (Gregory, 1990; Nunn et al., 2004 Nunn et al., , 2005 Altizer et al., 2007) . Only bat species with one or more known viral associations were included in our dataset (n = 33), as we found that sampling effort was a highly significant predictor of the presence or absence of viral records across all taxa (n = 54; r 2 = 0.56; P < 0.0001).

In the full dataset for bats with population structure and viral information (n = 33), the global F ST statistic averaged nuclear and mitochondrial indices (n = 8), or represented a single nuclear (n = 17) or mitochondrial (n = 8) statistic. Generalized linear models of the viral richness data included migration, distribution, and IUCN status as binomial categorical predictors, and colony size, population genetic structure, body mass, geographic range area, and sampling effort as covariates. Covariates were log-transformed to satisfy normality criteria. There were no significant covariate interactions in our analyses, and our limited sample sizes precluded us from testing across multiple levels for all categorical interactions. A mixed stepwise variable selection procedure was employed in JMP v.7.0.1 (SAS Institute, Inc., Cary, NC) to identify optimal models, with the cutoff value for variables to enter and leave set at a = 0.20. As we had incomplete information for the geographic range area of all taxa (28 of 33), the stepwise procedure was run with and without this variable included for optimal model selection. The Egyptian fruit bat (Rousettus aegyptiacus) had the most viral records (n = 8), was identified as an outlier in the generalized linear model testing (Studentized residual >3), and was omitted from subsequent analyses. The best model and subsets identified from the stepwise procedure were then analyzed in the generalized linear framework using a normal distribution and identity link function. For categorical levels, means and standard deviation of viral richness estimates are presented.

The best model and subsets were reanalyzed to test for phylogenetic dependence, as traits among related species may be more similar due to common ancestry and should not be considered independent in comparative analyses (Felsenstein, 1985; Harvey and Pagel, 1991) . A generalized least squares (GLS) framework (Grafen, 1989; Martins and Hansen, 1997; Garland and Ives, 2000) , using the APE package (Paradis et al., 2004) in R (The R Foundation for Statistical Computing, http://www.R-project.org) and supplementary code (Duncan et al., 2007) , was used to estimate k, a parameter that tests whether the evolution of phenotypic traits are independent of phylogenetic relationships among taxa. As comparative sequence data were not available for all of the bats with viral information, a mammalian supertree with branch length information was used as a source tree for the phylogenetic correlation matrix (Bininda-Emonds et al., 2007) . After excluding one outlier, 29 of the 32 taxa of interest were represented in the mammalian supertree, and a pruned phylogeny with branch lengths was extracted (Fig. 1a) . The remaining (three) taxa not found in the supertree were manually added to the pruned phylogeny in a way that minimized assumptions of relationships (i.e., branch length = 0) (Fig. 1b) . A correlation matrix was computed from the expected variances and covariances of shared branch lengths between taxa, assuming a model of Brownian motion (Martins and Hansen, 1997; Garland and Ives, 2000) . The PGLS function (Duncan et al., 2007) was used to find the maximum likelihood estimate of k, as well as estimated coefficients and confidence intervals on regression predictor variables. The parameter k varies between 0 and 1, with zero values indicating independent phenotypic trait evolution with respect to phylogeny, and values close to one indicating dependence between trait evolution and phylogeny (Pagel, 1999; Freckleton et al., 2002) . A null distribution of k was also created, through 1000 randomizations of the model and data, to evaluate the significance of the observed estimate. Akaike information criterion scores corrected for small sample sizes (AICc) were used to identify the best model among subsets (Burnham and Anderson, 2002) .

One hundred unique viral records were obtained for 33 bat species (Table 1 ). The majority of the viral records, 31% (31 of 100), were from the Family Rhabdoviridae and most of these were lyssaviruses (i.e., rabies and related viruses). Viruses from the Flaviviridae and Paramyxoviridae were the second and third most frequent, accounting for 13% (13 of 100) and 12% (12 of 100) of associations, respectively. Each bat species was associated with 1-8 viruses, and the mean number of viral records per bat (Fraser et al., 1996; Halpin et al., 1996; Speare et al., 1997; Philbey et al., 1998; Halpin et al., 2000 Halpin et al., , 2007 Pteropodidae (Kalunda et al., 1986; Wellenberg et al., 2002; Calisher et al., 2006; McKnight et al., 2006; Rector et al., 2006; Muller et al., 2007; Swanepoel et al., 2007; Towner et al., 2007; Markotter et al., 2008) Pteropodidae (Johara et al., 2001; Arguin et al., 2002; Reynes et al., 2004; Calisher et al., 2006; Cui et al., 2007) Molossidae (Enright et al., 1955; Burns et al., 1956; Burns and Farinacci 1956; Constantine and Woodall, 1964; Sulkin et al., 1966) Phyllostomidae Range distribution is continental (C) or island (I) species was 3.03 ± 1.83 (Fig. 2) . Average sampling distance was a marginal predictor of global F ST in a univariate regression (n = 31, P = 0.06), and was not included in subsequent analyses.

The mixed stepwise variable selection procedure converged on a model including IUCN status, distribution, logtransformed global F ST , and log-transformed sampling effort as covariates. The stepwise procedure omitted migratory status and log-transformed average colony size as model predictors (P > 0.2). The multivariate model explained 37% of the viral richness data (Likelihood Ratio v 2 4;27 ¼ 14:7, P = 0.005). IUCN status was a significant predictor of viral richness among bats (P = 0.02), and near-threatened or vulnerable bats had higher mean viral richness (4.00 ± 2.16) compared to bats of least concern (2.71 ± 1.51) (Fig. 3a) . Global F ST was positively associated with viral richness (P = 0.03) (Fig. 3b) , as was sampling effort (P = 0.007) (Fig. 3c) . Species range distribution (i.e., island vs. continental) was not a significant predictor of viral richness (P = 0.12). A reduced multivariate model excluding distribution as a predictor explained 32% of the viral richness data (Likelihood Ratio v 2 3;28 ¼ 12:4, P = 0.006) ( Table 2 ). In the reduced model, all three predictors significantly explained variation in viral richness (P < 0.03). The maximum likelihood estimate of phylogenetic signal in the full or reduced models was k = 0 (Table 2), indicating that patterns of viral richness are independent from the phylogenetic relationships among bats in this study. Effect tests for parameters in the full or reduced models were similar when compared to the generalized linear models without any phylogenetic correction. The reduced model provided the best explanation of the data ( Table 2 ). The randomization of viral richness trait values across taxa to obtain a null distribution of k revealed that we cannot reject that our observed value is outside of the null distribution (P = 0.22), indicating a lack of power. To test the estimation procedure, a dummy phenotypic data set was created with trait values skewed to match the phylogeny, and an estimate of k = 1 was obtained (data not shown).

Zoonotic disease emergence is a multipart process which includes: the build-up of risk factors during a ''pre-spillover'' period; a spillover event-when an infected individual from a reservoir population transmits the disease to a new host (Power and Mitchell, 2004) ; a period of local transmission in the new host that may or may not die out depending on characteristics of the pathogen and host population; and, a potentially self-sustaining transmission period within the new host (Anderson and May, 1986) . Risk factors that exist in the ''pre-spillover'' period can be environmental, demographic, or evolutionary; these can be viewed as existing along an eco-evolutionary continuum. Successful cross-species transmission is usually the result of repeated spillover events, i.e., ''viral chatter'' (Wolfe et al., 2005) . Standing pathogen diversity in reservoir populations can be critically important for promoting the evolutionary flexibility of pathogens, and likelihood of successful spillover and emergence in a new host (Morse, 1993) . Thus, the taxonomic diversity of pathogens in hosts and the genetic diversity of each respective pathogen may both be important predictors of spillover success, or emergence. Mechanisms that promote diversity on either level may increase the likelihood of emergence.

Population genetic structure and sampling effort were correlated with viral richness in bats. Although a positive linear fit best described the relationship between population genetic structure and viral richness, compared to other polynomial models (data not shown), it is possible that population structure may have a nonlinear impacts on epizootiology and subsequent viral evolution within a host. Modeling, coupled with empirical observations, has shown that the spatial structure of host populations can influence the likelihood of disease establishment (Rodriguez and Torres-Sorando, 2001) , rate of pathogen spread (Caraco et al., 2002) , duration of epidemics (Park et al., 2002) , as well as pathogen virulence (Boots et al., 2004) . Extremely low levels of population genetic structure predict a homogeneously mixing population, potentially leading to viral epidemics that rapidly burn out without establishing an enzootic state. This is supported by metapopulation models that have shown an increased extinction probability in cases with increasing migration rates and moderate pathogen virulence (Hess, 1996) . In hosts that exhibit extremely high levels of population structure, characterized by little migration between demes and small effective populations, localized disease extinction may preclude viral establishment. However, point estimates of population genetic structure may not capture all migration or fissionfusion dynamics that impact epizootiology, as this one statistic generally describes population substructure that relates to mating probabilities. Furthermore, the duration of incubation and infectious periods has equal importance for predicting the potential reproductive capabilities of a pathogen in any population, structured or not. While we did not examine the genetic diversity within host-specific viral lineages, the epizootiology of lyssaviruses in bats suggests that moderate levels of host population structure can positively influence viral genetic diversity within hosts (Smith, 1996; Messenger et al., 2003b; Davis et al., 2005; Hughes et al., 2005; Franka et al., 2006; Velasco-Villa et al., 2006) . Bats with increasing population genetic structure are positively associated with viral richness in this study. However, the current host sampling excludes several families, hundreds of species, and may not be representative for all bats. Furthermore, it will be important to distinguish between pathogens that are directly transmitted or vectorborne, and those that infect single or multiple hosts, as additional data become available. The influence of host population genetic structure may be negligible for vectorborne or multihost viruses, where pathogen distribution and richness may be determined by spatial structure of vectors and all competent hosts. Low sample sizes in the current study precluded partitioned statistical treatment for all possible transmission strategies. There is also evidence that many other factors, such as host immune response, may promote lineage diversity within pathogens . However, the spatial genetic structure of hosts can serve as a starting point for investigating pathogen distribution, diversification, and spatial control strategies.

Theoretical modeling of epizootic and enzootic processes predicts that larger populations generally will increase the likelihood of viral establishment ; however, host colony size was not correlated with viral richness across bats in this study. Bat colony sizes can be extremely variable across species (Kunz, 1982; O'Shea and Bogan, 2003) , and are known to be seasonally dynamic in response to variation in prey and habitat resource availability and life history. There is evidence that Brazilian free-tailed bats (Tadarida brasiliensis) migrate from Mexico to track seasonal insect abundance in conjunction with formation of large maternity colonies in the southwestern United States (McCracken, 2003) . The straw-colored fruit bat (Eidolon helvum) also exhibits seasonal fluctuations in colony size correlated with temporal and geographic variation in fruit availability across sub-Saharan Africa (Richter and Cumming, 2006) . Colony sizes of the large flying fox (Pteropus vampyrus) in Malaysia fluctuate dramatically over time, and dispersal behavior may reflect variation in fruit availability and hunting pressure (Epstein et al., 2009) . Although generalized predictions can be made from longterm summary statistics on host aggregation, seasonality also plays a critical role in epizootiological processes and disease emergence (Altizer et al., 2006) . In our search of the literature for species-specific colony size estimates, there were frequent references to seasonal and gender variation in gregarious behavior. Seasonal variation in colony size may be more important than typical colony size per se in terms of understanding the importance of contact networks for viral emergence and persistence in bat hosts. Irrespective of potential intra-annual variation, the typical colony sizes of individual host species may also be less important when considering vector-borne and multihost pathogens.

Host geographic range may be an important determinant of pathogen richness, as larger geographic ranges encompass a greater diversity of ecosystems, faunal communities, and may lead to greater spatial population substructure. Geographic range area was not a significant predictor of viral richness among bats in this study, but other studies have highlighted that host geographic range may be an important predictor of parasite richness (Gregory, 1990; Nunn et al., 2003) . Smaller geographic ranges have been linked to increased extinction risk across bats , and may similarly govern parasite dynamics associated with such hosts. However, a study across primates found evidence that host relatedness and the presence of conspecific range overlap were significant predictors of parasite community similarity across taxa (Davies and Pedersen, 2008) . Given recent implication of bats in EID spillover events (Halpin et al., 2000; Johara et al., 2001; Leroy et al., 2005; Li et al., 2005; Swanepoel et al., 2007) , additional studies on pathogen community similarity that include multiple pathogen taxonomic groups and tests of phylogenetic dependence across bats are needed. Although several socioecological variables were not significant predictors of viral richness across bats in this study, it would be prudent to search more exhaustively among known viral hosts, without limiting the search to species with characterized genetic spatial structure.

IUCN threat status, which combines data on population sizes, distribution, and geographic range area, was a significant predictor of viral richness across bats in this study, whereas individual contributing factors were nonsignificant. In this study, bats that were near-threatened (n = 3) or vulnerable (n = 1) had higher viral richness compared to bats of least concern (n = 28). This result contrasts a previous study in primates (Altizer et al., 2007) , where threatened taxa harbored lower parasite richness compared to nonthreatened taxa. Although the categories of threat status under comparison were not identical compared to the Altizer et al. (2007) study, the current study was also much more limited in taxonomic scope for both hosts and parasites under consideration. Although the data suggest that near-threatened or vulnerable bats may be more susceptible to viral infection compared to bats of least concern, the current result warrants caution given the uneven and limited sampling across IUCN threat categories.

Although significant links between phylogeny and parasite richness have been demonstrated in other studies (Nunn et al., 2004) , there was no evidence of phylogenetic dependence for patterns of viral richness in this study. Familial monophyly across bats was well supported for the phylogeny used in this study (Bininda-Emonds et al., 2007) . However, small sample sizes and the lack of phylogenetic resolution within and among bat genera may have lessened our power to detect dependence between phylogenetic relatedness and patterns of viral richness, as demonstrated by our inability to reject that our estimate of k was not nested within the null distribution. It is also possible that viral richness traits may not be evolving under the model of Brownian motion that was employed in our test (Freckleton et al., 2002) . Sampling that is more broadly representative of chiropteran diversity may allow for more powerful tests of phylogenetic dependence for trait evolution.

Although estimates of F ST provide information on historic dispersal and social organization of reservoir species over relatively large geographic or temporal scales, studies of emerging zoonoses and wildlife EIDs would benefit from collecting fine-scale, or real-time spatial data on host movement. Few studies have focused on this, but examples include studies of the reservoir hosts for chronic wasting disease (Conner and Miller, 2004) , canine pathogens (Riley et al., 2004) , the use of satellite telemetry to quantify migration activity for flying fox reservoirs of Nipah virus (Epstein et al., 2009) , and use of contact transmitters on domestic animals and wildlife (Bohm et al., 2009) . It is often logistically difficult to collect these data, but the combination of population genetic data with direct measures of host dispersal and contact have the potential to more accurately predict the spatial patterns of host-pathogen dynamics across the landscape (Hess et al., 2004; Real and Biek, 2007; Olival, 2008) . Thus, biogeographic inferences can make important macroecological predictions on pathogen richness and epizootiological processes, but control strategies for zoonotic disease will also require attention to multihost interactions, as well as local geographic and temporal scales.

As this study was only able to include a small fraction of bat species (33 of 1200) for which both population genetic and viral richness data were available, it also highlights how little we know about this diverse group of animals that are key players in the health of ecosystems and emergence of infectious diseases globally. Viral richness estimates in this study surely underestimate the real number of viruses associated with bats, in part due to a lack of population structure estimates for the overwhelming majority of bat species and also incomplete disease surveillance. Models fit to the temporal emergence of viruses suggests that, even for human pathogens, the process of discovery is far from complete (Woolhouse et al., 2008) . A number of recently discovered viruses, in addition to many other previously published associations, could not be included in our data set because they were found in species for which we did not have population genetic structure data or other host socioecological variables. This points to a number of considerations for future studies. First, more bat species should be examined using population genetic markers, and efforts should be made to collect samples for genetic work at the same time that animals are captured and handled during viral surveillance or telemetry studies. Second, more standardized methods for detecting viruses in wildlife reservoirs are needed. The majority of studies target limited taxonomic breadth in viral surveillance efforts, and often serology alone can be problematic due to cross-reactivity (Hanlon et al., 2005; Hayman et al., 2008) . Novel methods, such as multiplex PCR and DNA microarrays, in addition to diverse collaborative research teams, have the capacity to revolutionize the information gained through viral surveillance efforts and will surely advance our understanding of the processes of pathogen richness, coinfection, and emerging bat zoonoses. Lastly, this study highlights the importance of species-specific evolutionary and life-history characteristics for predicting viral richness in wildlife, and this should be examined for other taxonomic groups. This approach could greatly aid pathogen discovery by focusing sampling efforts to host species with potentially greater viral richness and, hence, greater likelihood of harboring novel zoonotic pathogens.

Dengue virus in Mexican bats

A human case of encephalitis due to a lyssavirus recently identified in fruit bats

Seasonality and the dynamics of infectious diseases

Do threatened hosts have fewer parasites? A comparative study in primates

Temporal dynamics of European bat lyssavirus type 1 and survival of Myotis myotis bats in natural colonies

Population biology of infectious diseases: part I

The invasion, persistence and spread of infectious diseases within animal and plant communities

Serologic evidence of lyssavirus infections among bats, the Philippines

Population structure and sex-biased dispersal in the forest dwelling vespertilionid bat, Myotis septentrionalis

Molecular evolution of Puumala hantavirus in Fennoscandia: phylogenetic analysis of strains from two recolonization routes, Karelia and Denmark

The ecology of wildlife disease control: simple models revisited

Australian bat lyssavirus: observations of natural and experimental infection in bats

The delayed rise of present-day mammals

Rabies surveillance in the United States during

Contact networks in a wildlife-livestock host community: identifying high-risk individuals in the transmission of bovine TB among badgers and cattle

Transmission heterogeneity and control strategies for infectious disease emergence

Large shifts in pathogen virulence relate to host population structure

Local interactions select for lower pathogen infectivity

Small worlds' and the evolution of virulence: infection occurs locally and at a distance

The evolutionary dynamics of local infection and global reproduction in host-parasite interactions

Novel lyssaviruses isolated from bats in Russia

Selection of benevolence in a host-parasite system

Population genetic structure and gene flow in a gleaning bat

Seeing in the dark: molecular approaches to the study of bat populations

Farinacci CJ (1956) Virus of bats antigenically related to St. Louis encephalitis

Insectivorous bats naturally infected with rabies in the southwestern United States

Isolations of Nepuyo virus strains from Honduras

Bats: important reservoir hosts of emerging viruses

Comparative population structure of Cynopterus fruit bats in peninsular Malaysia and southern Thailand

Stage-structured infection transmission and a spatial epidemic: a model for Lyme disease

Detection and phylogenetic analysis of group 1 coronaviruses in South American bats

Exploring population genetic structure in three species of Lesser Antillean bats

Contrasted patterns of mitochondrial and nuclear structure among nursery colonies of the bat Myotis myotis

Is the Gibraltar strait a barrier to gene flow for the bat Myotis myotis (Chiroptera: Vespertilionidae)?

Update: West Nile virus activity-Northeastern United States

A previously unknown reovirus of bat origin is associated with an acute respiratory disease in humans

Isolation of Nipah virus from Malaysian Island flyingfoxes

Identification and characterization of a new orthoreovirus from patients with acute respiratory infections

Tioman virus, a novel paramyxovirus isolated from fruit bats in Malaysia

Diseases of humans and their domestic mammals: pathogen characteristics, host range and the risk of emergence

Movement patterns and spatial epidemiology of a prion disease in mule deer population units

Bats in relation to the health, welfare, and economy of man

Latent infection of Rio Bravo virus in salivary glands of bats

Epidemic strain of Venezuelan equine encephalomyelitis virus from a vampire bat captured in Oaxaca

Parasite phylogeographical congruence with salmon host evolutionarily significant units: implications for salmon conservation

Molecular ecology of parasites: elucidating ecological and microevolutionary processes

Duelling timescales of host movement and disease recovery determine invasion of disease in structured populations

Evolutionary relationships between bat coronaviruses and their hosts

Bat-transmitted human rabies outbreaks, Brazilian Amazon

Phylogeny and geography predict pathogen community similarity in wild primates and humans

Phylogeography, population dynamics, and molecular evolution of European bat lyssaviruses

Virulence-transmission trade-offs and population divergence in virulence in a naturally occurring butterfly parasite

Detection of group 1 coronaviruses in bats in North America

Positive and negative effects of widespread badger culling on tuberculosis in cattle

Tacaribe virus, a new agent isolated from Artibeus bats and mosquitoes in Trinidad, West Indies

Phylogeography of the deer mouse (Peromyscus maniculatus) provides a predictive framework for research on hantaviruses

Henipavirus RNA in African bats

Testing the metabolic theory of ecology: allometric scaling exponents in mammals

Isolation of rabies virus from an insectivorous bat (Tadarida mexicana) in California

Management of Pteropus vampyrus, a hunted migratory species with a multinational home-range

Waterborne transmission and the evolution of virulence among gastrointestinal bacteria

Analysis of molecular variance inferred from metric distances among DNA haplotypes-application to human mitochondrial DNA restriction data

Host social behavior and parasitic infection: a multifactorial approach

First case of human rabies in Chile caused by an insectivorous bat virus variant

Phylogenies and the comparative method

Ecology of bat migration

Case report: isolation of a European bat lyssavirus type 2a from a fatal human case of rabies encephalitis

Correlates of Viral Richness in Bats 535

A new phylogenetic lineage of rabies virus associated with western pipistrelle bats (Pipistrellus hesperus)

Encephalitis caused by a lyssavirus in fruit bats in Australia

Phylogenetic analysis and comparative data: a test and review of evidence

Nelson Bay virus. A novel reovirus

Using the past to predict the present: confidence intervals for regression equations in phylogenetic comparative methods

Phylogenetic relationships of flaviviruses correlate with their epidemiology, disease association and biogeography

Detection and prevalence patterns of group I coronaviruses in bats, northern Germany

The phylogenetic regression

Parasites and host geographic range as illustrated by waterfowl

Unifying the epidemiological and evolutionary dynamics of pathogens

Emerging viruses: coming in on a wrinkled wing and a prayer

Identification of likely natural hosts for equine morbillivirus

Isolation of Hendra virus from pteropid bats: a natural reservoir of Hendra virus

Efficacy of rabies biologics against new lyssaviruses from Eurasia

The evolution of parasite virulence and transmission rate in a spatially structured population

Evidence of henipavirus infection in West African fruit bats

The roles of geological history and colonization abilities in genetic differentiation between mammalian populations in the Philippine archipelago

Population-structure and the evolution of virulence in nematode parasites of fig wasps

Disease in metapopulation models: implications for conservation

Spatial aspects of disease dynamics

Implications of contrasting patterns of genetic variability in two vespertilionid bats from the Indonesian archipelago

The evolutionary genetics of viral emergence

Evolutionary timescale of rabies virus adaptation to North American bats inferred from the substitution rate of the nucleoprotein gene

Occurrence, distribution and incidence of lyssavirus in bats

IUCN Red List of Threatened Species

Characterization of Oita virus 296/1972 of Rhabdoviridae isolated from a horseshoe bat bearing characteristics of both lyssavirus and vesiculovirus

Nipah virus infection in bats (Order Chiroptera) in Peninsular Malaysia

Global trends in emerging infectious diseases

Biological correlates of extinction risk in bats

Morphological and allozyme variation of Eidolon helvum (Mammalia: Megachiroptera) in the islands of the Gulf of Guinea

Allozyme variation of the Egyptian rousette (Rousettus aegyptiacus) in the Gulf of Guinea

Kasokero virus: a new human pathogen from bats (Rousettus aegyptiacus) in Uganda

Haemagglutination inhibition antibodies against influenza virus in bats

Ife: a new African orbivirus isolated from Eidolon helvum bats captured in Nigeria, Cameroon and the Central African Republic

Local migration promotes competitive restraint in a host-pathogen 'tragedy of the commons'

A new natural reservoir of hantavirus: isolation of hantaviruses from lung tissues of bats

The mammals of guinea as reservoirs and carriers of

Olival arboviruses

Roosting ecology of bats

Lagos bat virus in Kenya

Isolation of strains of the Hong Kong complex (H3N2) influenza virus from Nyctalus noctula bats in Kazakhstan

Issyk-Kul virus, a new arbovirus isolated from bats and Argas (Carios) Vespertilionis (Latr., 1802) in Kirghiz S

Fruit bats as reservoirs of Ebola virus

Bats are natural reservoirs of SARS-like coronaviruses

Molecular ecology and natural history of simian foamy virus infection in wild-living chimpanzees

Superspreading and the effect of individual variation on disease emergence

Human rabies of bat origin in Europe

Survey for bat lyssaviruses

Infectious disease and intensive management: population dynamics, threatened hosts, and their parasites

Relationships between morphology, genetics, and geography in the cave fruit bat Eonycteris spelaea (Dobson, 1871) from Indonesia

Epidemiology and pathogenicity of African bat lyssaviruses

Phylogenies and the comparative method: a general approach to incorporating phylogenetic information into the analysis of interspecific data

Mitochondrial DNA phylogeography reveals marked population structure in the common vampire bat, Desmodus rotundus (Phyllostomidae)

Network structure and the biology of populations

Population biology of infectious diseases: part II

Genetic structure of bat social groups

Estimates of population sizes in summer colonies of Brazilian free-tailed bats

Social organization and kinship in the polygynous bat Phyllostomus hastatus

Genetic structure in migratory and nonmigratory populations of Brazilian free-tailed bats

Papillomavirus-associated basosquamous carcinoma in an Egyptian fruit bat (Rousettus aegyptiacus)

Virulence evolution in a virus obeys a trade-off

Emerging epidemiology of bat-associated cryptic cases of rabies in humans in the United States

Bats, emerging virus infections, and the rabies paradigm

Emerging pattern of rabies deaths and increased viral infectivity

Small-scale fragmentation effects on local genetic diversity in two phyllostomid bats with different dispersal abilities in Panama

Strong population substructure is correlated with morphology and ecology in a migratory bat

Coronavirus antibodies in African bat species

Spill-over of European bat lyssavirus type 1 into a stone marten (Martes foina) in Germany

Spatial distribution of mitochondrial and microsatellite DNA variation in Daubenton's bat within Scotland

A parasite reveals cryptic phylogeographic history of its host

Ecological morphology and flight in bats (Mammalia, Chiroptera)-wing adaptations, flight performance, foraging strategy and echolocation

Comparative tests of parasite species richness in primates

Parasites and the evolutionary diversification of primate clades

Latitudinal gradients of parasite species richness in primates

Population genetic structure and phylogeography of Southeast Asian flying foxes: implications for conservation and disease ecology

Inferring the historical patterns of biological evolution

Effects of metapopulation processes on measures of genetic diversity

APE: analyses of phylogenetics and evolution in R language

Extinction times for closed epidemics: the effects of host spatial structure

Kyasanur forest disease virus infection in the frugivorous bat, Cynopterus sphinx

Genetic differentiation in Philippine bats of the genera Cynopterus and Haplonycteris

Male dispersal in the noctule bat (Nyctalus noctula): where are the limits?

An apparently new virus (family Paramyxoviridae) infectious for pigs, humans, and fruit bats

Molecular phylogeny of North American long-eared bats (Vespertilionidae: Corynorhinus); inter-and intraspecific relationships inferred from mitochondrial and nuclear DNA sequences

Reproduction and nutritional stress are risk factors for Hendra virus infection in little red flying foxes (Pteropus scapulatus)

Identification of a novel coronavirus in bats

Pathogen spillover in disease epidemics

Rabies virus and antibody in bats in Grenada and Trinidad

Pulau virus; a new member of the Nelson Bay orthoreovirus species isolated from fruit bats in Malaysia

Ability to replicate in the cytoplasm predicts zoonotic transmission of livestock viruses

Viral host jumps: moving toward a predictive framework

An integrated framework for the inference of viral population history from reconstructed genealogies

Microsatellite DNA polymorphism confirms reproductive isolation and reveals differences in population genetic structure of cryptic pipistrelle bat species

Invasion, stability and evolution to criticality in spatially extended, artificial hostpathogen ecologies

Partial molecular characterization of alphaherpesviruses isolated from tropical bats

Spatial dynamics and genetics of infectious diseases on heterogeneous landscapes

Genetic characterization of the first chiropteran papillomavirus, isolated from a basosquamous carcinoma in an Egyptian fruit bat: the Rousettus aegyptiacus papillomavirus type 1

Serologic evidence of lyssavirus infection in bats, Cambodia

Food availability and annual migration of the straw-colored fruit bat (Eidolon helvum)

Exposure to feline and canine pathogens in bobcats and gray foxes in urban and rural zones of a National Park in California

Genetic population structure of Natterer's bats explained by mating at swarming sites and philopatry

Models of infectious diseases in spatially heterogeneous environments

Genetic variation and population structure in the endangered greater horseshoe bat Rhinolophus ferrumequinum

Genetic consequences of the ice ages on nurseries of the bat Myotis myotis: a mitochondrial and nuclear survey

Italy as a major Ice Age refuge area for the bat Myotis myotis (Chiroptera: Vespertilionidae) in Europe

Genetic variation and migration in the Mexican free-tailed bat (Tadarida brasiliensis mexicana)

Sex differences in population genetics, home range size and habitat use of the parti-colored bat (Vespertilio murinus, Linnaeus 1758) in Switzerland and their consequences for conservation

A new virus, Phnom-Penh bat virus, isolated in Cambodia from a short-nosed fruit bat, Cynopterus brachyotis angulatus Miller, 1898

European bat lyssavirus infection in Spanish bat populations

Venezuelan encephalitis virus infection in neotropical bats. I. Natural infection in a Guatemalan enzootic focus

A review of studies on animal reservoirs of the SARS coronavirus

Genetic variation in the little red flying-fox Pteropus scapulatus (Chiroptera: Pteropodidae): implications for management

New aspects of rabies with emphasis on epidemiology, diagnosis, and prevention of the disease in the United States

Australian bat lyssavirus infection in three fruit bats from north Queensland

Genetic consequences of polygyny and social structure in an Indian fruit bat, Cynopterus sphinx. I. Inbreeding, outbreeding, and population subdivision

Studies of arthropod-borne virus infections in chiroptera. VI. Isolation of Japanese B encephalitis virus from naturally infected bats

Isolation of St. Louis encephalitis virus from bats (Tadarida b. mexicana) in Texas

Studies of reservoir hosts for Marburg virus

Risk factors for human disease emergence

Detection of novel SARS-like and other coronaviruses in bats from Kenya

Marburg virus infection detected in a common African bat

Naturally occurring rabies virus and neutralizing antibody in two species of insectivorous bats of New York State

Fatal case of human rabies (Duvenhage virus) from a bat in Kenya: The Netherlands

Molecular diversity of rabies viruses associated with bats in Mexico and other countries of the Americas

Laboratory investigation of human deaths from vampire bat rabies in Peru

Mobility of Australian flyingfoxes, Pteropus spp. (Megachiroptera): evidence from genetic variation

Host-parasite interactions between the local and the mean-field: how and when does spatial population structure matter

Presence of European bat lyssavirus RNAs in apparently healthy Rousettus aegyptiacus bats

Phylogeographic structuring and volant mammals: the case of the pallid bat (Antrozous pallidus)

First isolation of a rabies-related virus from a Daubenton's bat in the United Kingdom

Discovery of herpesviruses in bats

The social organization of the common vampire bat. 2. Mating system, genetic structure, and relatedness

Bushmeat hunting, deforestation, and prediction of zoonotic disease

Origins of major human infectious diseases

Bats as a continuing source of emerging infections in humans

Host range and emerging and reemerging pathogens

Temporal trends in the discovery of human viruses

The genetical structure of populations

Genetic and acoustic population structuring in the Okinawa least horseshoe bat: are intercolony acoustic differences maintained by vertical maternal transmission?

The authors thank the International Society of Biogeography, S. Scheiner, and K. Smith, for organizing and supporting the Biogeography of Disease Symposium and its participants. This research was supported in part by two NIH/NSF ''Ecology of Infectious Diseases'' awards (R01-TW05869 and 0430418). AST thanks G. McCracken, the