The University of Chicago

Reciprocal Specialization in Multihost Malaria Parasite Communities of Birds: A TemperateTropical Comparison Author(s): Maria Svensson-Coelho, Vincenzo A. Ellis, Bette A. Loiselle, John G. Blake and Robert E. Ricklefs, Source: The American Naturalist, (-Not available-), p. 000 Published by: The University of Chicago Press for The American Society of Naturalists Stable URL: http://www.jstor.org/stable/10.1086/678126 . Accessed: 11/10/2014 17:00 Your use of the JSTOR archive indicates your acceptance of the Terms & Conditions of Use, available at . http://www.jstor.org/page/info/about/policies/terms.jsp

. JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about JSTOR, please contact [email protected].

.

The University of Chicago Press, The American Society of Naturalists, The University of Chicago are collaborating with JSTOR to digitize, preserve and extend access to The American Naturalist.

http://www.jstor.org

This content downloaded from 69.243.144.33 on Sat, 11 Oct 2014 17:00:37 PM All use subject to JSTOR Terms and Conditions

vol. 184, no. 5

the american naturalist

november 2014

Reciprocal Specialization in Multihost Malaria Parasite Communities of Birds: A Temperate-Tropical Comparison Maria Svensson-Coelho,* Vincenzo A. Ellis, Bette A. Loiselle,† John G. Blake,‡ and Robert E. Ricklefs Department of Biology, University of Missouri, St. Louis, Missouri 63121 Submitted December 2, 2013; Accepted May 28, 2014; Electronically published October 1, 2014 Online enhancement: appendixes. Dryad data: http://dx.doi.org/10.5061/dryad.6s0h6.

abstract: How specialization of consumers with respect to resources varies with respect to latitude is poorly understood. Coexistence of many species in the tropics might be possible only if specialization also increases. Alternatively, lower average abundance of more diverse biotic resources in the tropics might force consumers to become more generalized foragers. We examine levels of reciprocal specialization in an antagonistic system—avian malaria—to determine whether the number of host species used and/or parasite lineages harbored differ between a temperate and a tropical assemblage. We evaluate the results of network analysis, which can incorporate both bird and parasite perspectives on specialization in one quantitative index, in comparison to null models. Specialization was significantly greater in both sample sites than predicted from null models. We found evidence for lower perhost species parasite diversity in temperate compared to tropical birds. However, specialization did not differ between the tropical and temperate sites from the parasite perspective. We supplemented the network analysis with estimates of specialization that incorporate phylogenetic relationships of associates and found no differences between sites. Thus, our analyses indicate that specialization within an antagonistic host-parasite (resource-consumer) system varies little between tropical and temperate localities. Keywords: antagonistic interactions, coevolution, community ecology, Haemosporida, latitudinal gradient.

Introduction A nearly ubiquitous decreasing gradient in species richness occurs between tropical and temperate regions (Hillebrand * Corresponding author. Present address: Departamento de Gene´tica e Biologia Evolutiva, Instituto de Biocieˆncias, Universidade de Sa˜o Paulo, Rua do Mata˜o 277, Sa˜o Paulo 05508-090, Brazil; e-mail: [email protected]. † Present address: Department of Wildlife Ecology and Conservation and Center for Latin American Studies, University of Florida, Gainesville, Florida 32611. ‡ Present address: Department of Wildlife Ecology and Conservation and Center for Latin American Studies, University of Florida, Gainesville, Florida 32611. Am. Nat. 2014. Vol. 184, pp. 000–000. 䉷 2014 by The University of Chicago. 0003-0147/2014/18405-55128$15.00. All rights reserved. DOI: 10.1086/678126

2004). This has led to comparisons of consumer specialization (e.g., herbivores on plant resources, parasites on hosts) between the two regions (e.g., Novotny et al. 2002; Krasnov et al. 2008). Ecological specialization in consumer-resource systems might increase or decrease with respect to overall species richness, depending on several factors. On one hand, coexistence of many species might be possible only when resources are finely divided (i.e., greater specialization; Hutchinson 1959; MacArthur 1972; Connell 1978). On the other hand, greater resource (species) diversity might result in increased heterogeneity and decreased abundance of any one resource, causing foragers to adopt a generalist feeding strategy with greater niche overlap among species (Beaver 1979). Additionally, Dobzhansky (1950) famously called attention to the fact that organisms in temperate regions experience strong selective pressure from the abiotic environment, whereas organisms in tropical regions experience more selective pressure from other organisms (also see Fischer 1960; Schemske et al. 2009). The more benign tropical environment was expected to result in more stable populations (MacArthur 1955) and stronger selection by parasites (Janzen 1970; Connell 1971). When taken together with the older age of the tropics (Fischer 1960; Fine and Ree 2006), one might expect increased influence of biotic interactions and greater opportunities for specialized interactions to emerge in the tropics. Studies addressing whether specialization increases toward the equator have revealed contradictory results (e.g., Beaver 1979; Novotny et al. 2002; Dyer et al. 2007; Dalsgaard et al. 2011; Moles et al. 2011; Schleuning et al. 2012; Morris et al. 2014). Here, we extend this approach to an antagonistic parasite-host system, which would seem to provide greater opportunity for specialization than consumer-resource relationships among freeliving organisms. Specifically, we compare the community structure of haemosporidian (malaria) parasites within a temperate (southern Missouri) assemblage and a tropical

This content downloaded from 69.243.144.33 on Sat, 11 Oct 2014 17:00:37 PM All use subject to JSTOR Terms and Conditions

000 The American Naturalist (Amazonian Ecuador) assemblage of forest understory birds. Host-parasite interactions provide an excellent model with which to explore latitudinal gradients in specialization. The diversity of immune evasion proteins in parasites (Maizels et al. 1993; Kyes et al. 2001; Gardner et al. 2002) favors parasites capable of escaping the immune arsenal of hosts. Hosts counter these offenses with complex immune system defenses, including vertebrate major histocompatibility complex (MHC) alleles (Apanius et al. 1997; Sepil et al. 2013). The principle of allocation suggests that when the abiotic environment selects adaptations to extreme conditions, organisms are constrained in their evolutionary response to other factors (Lochmiller and Deerenberg 2000; Norris and Evans 2000), leading to a trade-off between immune function and other life-history traits (e.g., sexual ornamentation and reproductive output; Sheldon and Verhulst 1996). If such constraints influenced parasite-host coevolution, then one might expect to find more specialized parasites—as well as fewer parasite species per host species—in the tropics, where biotic interactions predominate. Alternatively, greater host species diversity might result in greater generalization of parasites on hosts, especially in the case of vector-borne parasites. Increased host species diversity reduces the encounter rate of any given parasite to a particular host species (Ostfeld and Keesing 2000; Keesing et al. 2010), which favors increased host breadth, provided that transmission by vectors is not specific (i.e., vectors do not show strong preferences for vertebrate host species). Finally, a tropics-temperate comparison of host-parasite specialization may depend on evolutionary relationships among the species involved. Parasite sharing is usually greater among closely related primate hosts than distantly related hosts (Davies and Pedersen 2008; Cooper et al. 2012). A likely mechanism for this pattern is that switching occurs more readily among closely related hosts (Davies and Pedersen 2008), whose immune defenses presumably are more similar than those among distant relatives. Similarly, closely related parasites would tend to share host species if similarity in host immune evasion proteins prevents hosts from distinguishing among them. Network analysis is an excellent tool for exploring assemblage structure of interacting species (e.g., Proulx et al. 2005; Bascompte and Jordano 2007; Poulin 2010; Schleuning et al. 2012). Hosts and parasites can be viewed in two-mode, or bipartite, networks, where one level contains hosts and the other parasites. In such networks, nodes represent species and links connect host species with parasite species, if they interact (fig. 1). The fewer links that emerge from a parasite species, the more specialized it is with respect to host breadth. The fewer links that emerge from a host species, the lower its parasite richness. Quan-

titative networks incorporate the strength of those links based on the number of individuals of a particular host species infected with a particular parasite species (e.g., Bascompte et al. 2006). Two network descriptors can be used to estimate specialization: network-wide specialization (H 2) and specieslevel specialization (d ; Blu¨thgen et al. 2006). The H 2 index estimates specialization over an entire assemblage, whereas d  yields estimates of specialization for each species within an assemblage (Blu¨thgen et al. 2008; fig. 1). Both H 2 and d  are entropy indexes, and they produce values that range from disordered to structured. However, total disorder in an interaction network is the same as generalization at both levels (i.e., all hosts associate with all parasite lineages), and extreme structure is the same as one-to-one reciprocal specialization. Our aims were to determine whether the level of host specialization of individual malaria parasite lineages and the diversity of parasites on individual species of birds differ between a tropical and a temperate assemblage. Additionally, we determined whether specialization is significantly different from null expectations. Finally, we investigated whether incorporating phylogenetic relationships of both hosts and parasites altered the difference in specialization between the two sites.

Methods Community Matrices Avian malaria parasites—globally common, abundant, and diverse vector-borne protozoan parasites (Apicomplexa: Haemosporida: Plasmodiidae: Plasmodium spp. and Haemoproteidae: Haemoproteus spp.; Valkiu¯nas 2005) of birds—are well suited to investigate differences in the organization of communities of parasites between tropical and temperate regions. Many parasite species span temperate and tropical latitudes, such that the major clades of these organisms are not strongly geographically structured (Ricklefs and Fallon 2002; Beadell et al. 2006; Svensson et al. 2007). Moreover, host breadth varies widely among malaria species within assemblages, and so strengths of interactions plausibly might also vary among regions. We compared two local assemblages of forest understory birds (primarily passerines, Aves: Passeriformes) and their malaria parasites: Tiputini, a tropical assemblage in the western Amazon basin (lat. 0⬚38S, long. 76⬚08W), and the Ozarks, a temperate assemblage in the Ozark Mountains of southern Missouri (lat. 37⬚14N, long. 90⬚58W). We examined 2,488 individual birds belonging to 104 species in Tiputini and 1,206 individual birds belonging to

This content downloaded from 69.243.144.33 on Sat, 11 Oct 2014 17:00:37 PM All use subject to JSTOR Terms and Conditions

Specialization in Avian Malaria 000

Figure 1: Diagram contrasting hypothetical host-parasite assemblages exhibiting complete generalization (A) and perfect reciprocal specialization (B). The Y-axis represents density of the null distribution (left, curve). The values of network-wide (H2 ) and average specieslevel (d ) specialization are indicated by dashed vertical lines. Cells in the host-parasite interaction matrices (middle) are gray if that hostparasite interaction was observed. The bipartite networks (right) order parasite species as nodes (black) on top and host species as nodes on bottom, with links (gray) connecting them if their interactions were observed. The width of each link is proportional to the abundance of each interaction, and the width of each node is proportional to the abundance of species. In this example, we set all species abundances equal so that H2 and d  range from 0 to 1. Images were produced using the bipartite package in R (R Development Core Team 2011).

51 species in the Ozarks (Ricklefs et al. 2005; SvenssonCoelho et al. 2013). All hosts were sampled nondestructively, and blood samples were screened for malaria infection following Fallon et al. (2003). We used parasite molecular (282⫺663 bp cytochrome b [cyt b]; mean 511 Ⳳ 121 SD) and host association data in both assemblages to assign infections to putative evolutionary lineages of parasite as described in Svensson-Coelho et al. (2013) and appendix A; appendixes A and B are available online. We conducted research in the Ozarks under federal permit no. 21688 and Missouri Department of Conservation permit no. 14967 and in accordance with the University of Missouri–St. Louis Institutional Animal Care and Use Committee (protocol 309824–1). Research at Tiputini Biodiversity Station was conducted in accordance with research permit no. 13-ICFAU-DFN (and renewals) from the Ministerio del Ambiente, Distrito Forestal Napo, Tena, Ecuador. The Ozarks site supports mostly migratory oscine passerines (dominated by the families Parulidae and Vireonidae), most of which migrate to the Caribbean basin in

winter. Transmission of malaria parasites on the breeding ground was verified by recovery of most parasite lineages in resident and/or juvenile birds (Ricklefs et al. 2005). Tiputini supports mostly resident, nonmigratory suboscine passerines (dominated by the families Furnariidae and Thamnophilidae). We sampled both the temperate and tropical birds during their breeding seasons, a time when their immune systems should be most compromised due to trade-offs in energy investments (Martin et al. 2004). Most of the temperate bird species spend the winter in the tropics and experience a benign climate year round. Nonetheless, parasite lineages observed in the Missouri Ozarks are transmitted locally and would, via vectors, experience different physical conditions. Thus, comparisons of resident assemblages from the parasite perspective should reflect temperate-tropical differences. A comparison of parasite specialization on resident and migratory hosts in the temperate area would be valuable, but we have too few resident species in our sample for such a comparison. Despite similar sampling methods and seasons of sampling, potentially confounding factors include the fact

This content downloaded from 69.243.144.33 on Sat, 11 Oct 2014 17:00:37 PM All use subject to JSTOR Terms and Conditions

000 The American Naturalist

Figure 2: Networks of bird species (lower nodes) and malaria parasite lineages (upper nodes) at the Tiputini Biodiversity Station, Ecuador (A), and in the Missouri Ozarks (B). The width of the links (gray) is proportional to the abundance of interactions within each diagram. See figure 1 for how to interpret these diagrams. Data underlying figure 2 are deposited in the Dryad Digital Repository: http://dx.doi.org /10.5061/dryad.6s0h6 (Svensson-Coelho et al. 2014).

that we sampled a smaller proportion of the avifauna in Tiputini (104 of ca. 450 species in Tiputini; J. G. Blake, personal observation) than in the Ozarks (51 of 93 recorded species, Shannon County, Missouri, during June– July 1999–2011; www.ebird.org). Sampling biases reflect both the relative abundance of species and their activity zones, as our mist nets were set at 0–2 m aboveground. Of course, habitats also differed between the locations (primary tropical forest in Tiputini and secondary deciduous forest in the Ozarks). We overcame some of this sampling bias by using randomizations (below). We pooled samples from several years in both sites (1999–2002, 2011 in the Ozarks and 2001–2010 in Tiputini). In addition to specialization indexes, we compared the average number of associates (species degree) from both parasite and bird perspectives between the two assemblages.

Network Analysis We used two indexes designed to estimate reciprocal specialization in a bipartite network: H 2 and d  (Blu¨thgen et al. 2006). The H 2 index, the standardized two-dimensional Shannon index of entropy, estimates assemblage-wide specialization. It gives overall insight to how close an assem-

blage is to containing only species with one-to-one interactions. The H 2 index is quantitative: in a matrix where host species are arranged in rows and parasite lineages are arranged in columns (fig. 1), the value in each cell represents the number of times a given parasite lineage has been recovered from a given host species. The H 2 statistic ranges from 0 (all species interact to equal degrees) to 1 (all interactions are cases of reciprocal specialization). The H 2 index estimates the structure of a whole matrix and returns one value per assemblage. On its own, it gives no insight into the variation in reciprocal specialization among species or to the variation in specialization from the host and parasite perspectives. That is, we would like to know not only whether tropical parasites tend to use fewer hosts on average (parasite specialization) but also whether tropical hosts tend to harbor fewer parasites (parasite diversity per host). To explore whether reciprocal specialization is greater in the tropics from both the host and parasite perspectives, we used the standardized Kullback-Leibler index of entropy, d , which returns a measure of specialization for each species (Blu¨thgen et al. 2006). The d  index incorporates (1) the frequency of a parasite species on all its hosts (and vice versa) and (2) the frequency of the focal species in relation to other species that interact with each of its associates. Thus, d  estimates re-

This content downloaded from 69.243.144.33 on Sat, 11 Oct 2014 17:00:37 PM All use subject to JSTOR Terms and Conditions

Specialization in Avian Malaria 000

Figure 3: Number of associates (species degree) of parasites (A) and birds (B) in Tiputini in Amazonian Ecuador and in the Missouri Ozarks. Species degree ranges from 1 to N number of associates per species. Value N for parasites is 63 and 28 in Tiputini and the Ozarks, respectively, and N for birds is 45 and 37 in Tiputini and the Ozarks, respectively. The horizontal line in the middle of the boxes represents the median, and the height of the boxes ranges from the twenty-fifth to the seventy-fifth percentiles. The whiskers represent the tenth and ninetieth percentiles, and points indicate outliers. Results from Mann-Whitney U-test comparisons between sites are reported at the top of each figure. Data underlying figure 3 are deposited in the Dryad Digital Repository: http://dx.doi.org/10.5061/dryad.6s0h6 (SvenssonCoelho et al. 2014).

ciprocal specialization. Like H 2, d  ranges from 0 (generalist) to 1 (specialist). We then compared the mean d  of parasites (and the mean d  of hosts) between the tropical and temperate sites using t-tests. More details of the indexes, including equations, can be found in appendix B. Null models. When two assemblages differ structurally (i.e., they have different numbers of species and/or different network dimensions), the observed network analysis indexes in different assemblages might not be directly comparable. For example, for a given sample size, connectance (proportion of realized links) will always be lower in larger networks (Dunne et al. 2002). With a smaller proportion of realized links, we would also expect greater estimates of specialization. Because our tropical site is more diverse than our temperate site and fewer of the resident species were sampled, we used null models (Gotelli and Graves 1996) to (1) estimate the expected pattern under random interactions (considering the size, dimensions, and connectance of the original matrix) and (2) calculate standardized effect sizes (SES; equivalent to Zscores) of observed values in each site. We used the null model described in Va´zquez et al. (2007), which creates random matrices with the same number of species, abundance, and connectance as the original matrix. We created 10,000 null matrices (method vaznull) in the package bipartite (Dormann et al. 2008) in R (R Development Core Team 2011). We estimated H 2 and d  for each of these 10,000 matrices, yielding a null distribution of index values in each assemblage. We calculated SES as (Obs ⫺ mnull)/SDnull, where Obs is the observed index value, mnull is the mean of the null

distribution based on our 10,000 randomized matrices, and SDnull is the standard deviation of our null distribution (Ulrich and Gotelli 2007 and references therein). For the d  null models, we obtained a unique mean per species. Thus, we compared the mean of species-specific null means to the observed mean d . Phylogenetic Specificity Indexes Failing to incorporate phylogeny might underestimate specialization (Novotny et al. 2002). That is, a species might appear to be generalized according to a nonphylogenetic index because (1) it has multiple associates and (2) its frequency distribution is even among those associates. However, specialization of a focal species increases with phylogenetic proximity among its associated species. Accordingly, including phylogeny might improve estimates of specialization and provide more meaningful comparisons between assemblages. Because network analysis does not account for phylogeny, we complemented the analysis with a specialization index that does. This index is the weighted mean pairwise distance (wMPD), originally used to compare species diversity among communities (Webb et al. 2002; Kembel et al. 2011). Methods for estimating wMPD and applying it to avian malaria assemblages are detailed in SvenssonCoelho et al. (2013) and appendix B. Briefly, wMPD uses genetic distance and frequency distribution among associates to produce an index with a minimum value of 0 (specialists with only one associate) and a maximum value where a species is evenly distributed among all sampled

This content downloaded from 69.243.144.33 on Sat, 11 Oct 2014 17:00:37 PM All use subject to JSTOR Terms and Conditions

000 The American Naturalist (app. B). We estimated wMPD using the package Picante (Kembel et al. 2010) in R. Statistical tests were conducted in SPSS, version 20 (IBM, New York), or in R. More details of methods are provided in appendix B. Results Assemblage Structure

Figure 4: Null distribution of network-wide specialization (H2 ) estimates of 10,000 randomized matrices compared to the observed estimate (dashed vertical line) in Tiputini in Amazonian Ecuador (A) and the Missouri Ozarks (B). Significance of the observed estimate is assessed by calculating the proportion of randomized estimates that are equal to or greater than the observed. Both assemblages are significantly specialized compared to the null model (P p 0). The H2 index ranges from 0.0 (generalized) to 1.0 (specialized). Data underlying figure 4 are deposited in the Dryad Digital Repository: http://dx.doi.org/10.5061/dryad.6s0h6 (Svensson-Coelho et al. 2014).

associates. This index, however, applies to one species at a time and can neither estimate the structure of a whole assemblage nor incorporate mutual exclusiveness of interactions. Nonetheless, wMPD can answer one important question that H 2 and d  cannot: do species on average interact with equally distantly related associates in our temperate and tropical sites? We included data from species with N ≥ 4 associates because this was considered the minimum sample size necessary to detect multiple associates in a previous study on the Tiputini assemblage (Svensson-Coelho et al. 2013). We then compared means of wMPD between Tiputini and the Ozarks. Variation of wMPD and d  was independent of sample size, but species degree increased significantly with increasing sample size

In total, 379 (of 539 positive infections) and 284 (of 429) individual parasite infections were assigned to cyt b lineages in Tiputini and the Ozarks, respectively. Failure to identify all positive infections could be due to DNA degradation or mismatches in primer sites. However, the nested cyt b protocol we use has amplified parasites with mismatches in the primer region. Data from the Ozarks described in Ricklefs et al. (2005) were supplemented by 124 infections from 2011. The Tiputini data comprise a matrix of 45 parasite lineages and 63 host species (matrix size M p 45 ⫹ 63 p 108). In this matrix, we observed n p 387 individual host-parasite interactions (p number of parasites) and 169 realized links (p number of nonzero cells in the interaction matrix), representing 6.0% of 2,835 possible links (p connectance). The Ozark data comprise a matrix of 37 parasite lineages and 28 host species (M p 65, n p 284 and 102 realized links [9.8% of 1,036 possible links]; fig. 2). Four lineages (POZ04L/PTI43L, POZ01L/ PTI37L, POZ09/PTI17, and HOZ21L/HTI5) were shared between the two regions and are referred to by their Ozarks code here. Lineage names include the parasite genus (P or H), location (OZ or TI), and a lineage number, with L indicating a set of closely related haplotypes considered to be of the same lineage. Bird species names follow the International Ornithological Committee (IOC) World Bird List, version 3.5 (Gill and Donsker 2013; supplementary information deposited in the Dryad Digital Repository: http://dx.doi.org/10.5061/dryad.6s0h6 [Svensson-Coelho et al. 2014]). Species Degree Both host and parasite richness were greater in our tropical sample than in our temperate sample. However, the difference in the lineage richness of parasites (which in the tropical sample was 1.2 times that of the temperate sample) was much smaller than the difference in the species richness of the birds (which in the tropical sample was two times that of the temperate sample). Associations between birds and malaria parasites appear similar in both sites (fig. 2), with few cases of perfect reciprocal specialization. The average number of associates (species degree) did not differ significantly between sites (fig. 3). Parasites infect, on average, three (the Ozarks) to four (Tiputini) host spe-

This content downloaded from 69.243.144.33 on Sat, 11 Oct 2014 17:00:37 PM All use subject to JSTOR Terms and Conditions

Specialization in Avian Malaria 000

Figure 5: Comparisons between null distributions (curves) and observed means (vertical line with shaded 95% confidence intervals) of species-level specialization (d ) in Tiputini in Amazonian Ecuador (A, B) and the Missouri Ozarks (C, D). We compared means between the null and the observed d  using t-tests. We used Cohen’s d (C’s d) to estimate the effect size between the observed mean and the null model. Data underlying figure 5 are deposited in the Dryad Digital Repository: http://dx.doi.org/10.5061/dryad.6s0h6 (Svensson-Coelho et al. 2014).

cies. Hosts harbor, on average, three (Tiputini) to four (the Ozarks) parasite lineages. Reciprocal Specialization Null models predicted network-wide specialization (H 2) to be somewhat larger in Tiputini (H 2null p 0.32 Ⳳ 0.024 SD) than in the Ozarks (H 2null p 0.27 Ⳳ 0.028 SD) as expected due to the greater matrix dimensions and lower connectance in our tropical site. However, the observed H 2 was lower in Tiputini (H 2 p 0.54) than in the Ozarks (H 2 p 0.60; fig. 4). Significance of the observed estimate is assessed by calculating the proportion of randomized estimates that are equal to or greater than the observed estimate. In both sites, network-wide specialization was significantly higher than expected (P p 0), indicating that birds and their malaria parasites do not interact with each other at random (fig. 4). However, the standardized effect size of H 2 (SESH2 ) was somewhat smaller in Tiputini (SESH2 p 9.4) than in the Ozarks (SESH2 p 11.6).

Average species-level specialization (d ) was significantly greater than expected by chance from both the host and parasite perspectives in both sites (fig. 5). Average specialization of parasites on birds was marginally significantly higher in the tropical site than in the temperate site, whereas average per-host-species parasite diversity was significantly lower in the temperate assemblage than in the tropical assemblage (fig. 6). However, the mean of the null d  estimates was greater in the tropical site than in the temperate site for parasites and, to a lesser extent, for hosts (fig. 6; gray density distributions), indicating that even under random expectations, we should see greater specialization in Tiputini. This cautions us to compare means between sites directly. We calculated the standardized effect size (Cohen’s d) for each mean comparison between the null and observed d  (Cohen 1977). Then we used these to estimate the difference in Cohen’s d between sites (DIFd). For parasites, DIFd p 0.15, and for hosts, DIFd p 3.19. A Cohen’s d less than 0.2 is considered a small effect, whereas a Cohen’s d above 0.8 is considered a large effect (Cohen 1977). With only a marginal signif-

This content downloaded from 69.243.144.33 on Sat, 11 Oct 2014 17:00:37 PM All use subject to JSTOR Terms and Conditions

000 The American Naturalist

Figure 6: Species-level specialization (d ) of parasites (A) and birds (B) in Tiputini in Amazonian Ecuador and the Missouri Ozarks. Value d  ranges from 0.0 (generalist) to 1.0 (specialist). Data underlying figure 6 are deposited in the Dryad Digital Repository: http://dx.doi.org /10.5061/dryad.6s0h6 (Svensson-Coelho et al. 2014).

icance when comparing the raw d  values and a small DIFd, parasite specialization on hosts does not appear to differ between sites. In contrast, the average temperate host harbors fewer parasite lineages (higher entropy d ) than the average tropical host does. Influence of Phylogenetic Relatedness on Specificity Sites did not differ in average wMPD from either the bird perspective or the parasite perspective (fig. 7). Average wMPD from the parasite perspective was 0.020 (Ⳳ0.016 SD) and 0.014 (Ⳳ0.010 SD) in Tiputini and the Ozarks, respectively. Average wMPD from the bird perspective was 0.078 (Ⳳ0.039 SD) and 0.082 (Ⳳ0.032 SD) for Tiputini and the Ozarks, respectively. Discussion We analyzed specialization in the antagonistic bird-malaria system to determine whether interactions are structured significantly and whether this structure varies between a tropical and a temperate assemblage. Latitudinal variation in specialization has been analyzed predominantly for herbivore-forager and mutualist interactions, although hostparasite/parasitoid studies are emerging (Va´zquez and Stevens 2004; Morris et al. 2014). Not surprisingly in our system, host species richness and parasite lineage richness in the tropical site exceeded those in the temperate site. This is consistent with the elevated richness of most organisms toward the equator (Hillebrand 2004). Because of this difference in richness between sites, we performed additional analyses of community connectance, which is highly correlated with species richness (Dunne et al. 2002; Olesen and Jordano 2002; Ollerton and Cranmer 2002), using an appropriate null model approach.

Previous studies have found network-wide specialization (H 2) an attractive index for comparing networks of different sizes, dimensions, and evenness of interactions, because it is robust to changes in these potentially confounding factors (Blu¨thgen et al. 2008; Dormann et al. 2009; Dalsgaard et al. 2011; Morris et al. 2014). In addition, network-wide specialization provides a standardized metric for comparing different types of bipartite networks (Blu¨thgen et al. 2006), for example, mutualistic versus antagonistic (Morris et al. 2014). Importantly, by comparing observed H 2 to null models, we determine whether interactions are significantly structured with respect to host and parasite specialization. Despite few cases of reciprocal specialization and frequent species overlap in the current networks, consistent positive deviations from null expectations in both assemblages and from both bird and parasite perspectives indicate that bird species and their malaria parasite lineages experience high levels of exclusiveness with respect to their associate species. Unlike mutualistic networks, where H 2 can be relatively low (Blu¨thgen et al. 2007; Schleuning et al. 2012), the H 2 values for our parasite-host assemblages of 0.54 (Tiputini) and 0.60 (the Ozarks) are high. Again, H 2 increases with increasing specialization. These high values are similar to the average H 2 (0.65 Ⳳ 0.31 SD) of host-parasitoid assemblages, suggesting that there is a limit to the number of associates that antagonistically interacting species can have (Morris et al. 2014). Based on what we know about human-Plasmodium interactions, we expected the avian malaria system to evolve toward increased levels of reciprocal specialization because many genes are involved in vertebrate host immunity and in the evasion of host immunity by parasites (e.g., Horrocks et al. 2005). Accordingly, interacting host and malaria parasite species are likely to evolve under negative frequency-dependent selection of coevolving polymorphisms, which would result

This content downloaded from 69.243.144.33 on Sat, 11 Oct 2014 17:00:37 PM All use subject to JSTOR Terms and Conditions

Specialization in Avian Malaria 000

Figure 7: Phylogenetic specialization (weighted mean pairwise distance [wMPD]) of parasites (A) and birds (B) in Tiputini in Amazonian Ecuador and the Missouri Ozarks. Theoretical wMPD ranges from 0.0 (specialist) to a maximum value where frequency distribution is even among all species in an assemblage. Maximum parasite wMPD is 0.107 and 0.066 in Tiputini and the Ozarks, respectively. Maximum bird wMPD is 0.274 and 0.265 in Tiputini and the Ozarks, respectively. Data underlying figure 7 are deposited in the Dryad Digital Repository: http://dx.doi.org/10.5061/dryad.6s0h6 (Svensson-Coelho et al. 2014).

in strong interactions primarily between one host and one parasite species (Thompson 2005, 2009). Patterns observed here are consistent with this hypothesis. From the parasite perspective, the high level of specialization is consistent with the hypothesis that a tradeoff exists such that fitness cannot be simultaneously high on multiple resources (Dethier 1954; MacArthur 1972; Futuyma and Moreno 1988). From the bird perspective, perhost parasite diversity is lower than expected by chance, suggesting either that they are not encountered by all local parasites or that immunity is efficient to ward off most but not all parasite species. Under the first alternative, one might expect vectors to play a major role if multiple mosquito species feeding on different bird species also transmit different parasite species. Research on avian malaria parasite vectors to date, however, suggests that vectors do not limit access of parasites to hosts (Gager et al. 2008; Njabo et al. 2011; Medeiros et al. 2013), although studies on vector involvement in parasite-bird encounters are still sparse, particularly in the tropics (Santiago-Alarcon et al. 2012). Instead, it is likely that avian immunity plays a dominant role in structuring parasite assemblages (Medeiros et al. 2013). Although the assemblages considered in this analysis are separated by nearly 40 degrees of latitude, we found no evidence for greater levels of specialization in the tropical site, thus failing to provide convincing support for the hypothesis that the more benign tropical climate favors increased specialization. From the bird perspective, we found more evidence for the opposite pattern; that specialization is greater in the temperate site (or, more intuitively, that per-host parasite diversity is lower). At present, we do not know whether increased parasite diversity

per host in the tropics is a result of increased parasite diversity overall, greater parasite virulence, or a combination of both, but one can speculate that, in areas of greater pathogen diversity, hosts might be overwhelmed and unable to mount immune responses to all types of pathogens. This would explain our results only if parasite diversity increases toward lower latitudes, as does bird diversity; however, we do not currently possess sufficient information about tropical parasites of wildlife to make this connection firmly (Dobson et al. 2008; Poulin and Forbes 2012), and our own sample of malaria parasite diversity cannot be evaluated independently of host diversity. The slight differences that exist between sites with respect to the standardized Kullback-Leibler index of entropy, d , disappeared when we incorporated phylogeny in the wMPD index. This indicates that associates (from both host and parasite perspectives) are, on average, equally divergent in both sites. Interestingly, parasites use equally divergent host species in both sites despite our sampled bird assemblage in Tiputini being, on average, more divergent than that in the Ozarks (table B1; tables A1, B1 are available online). The greater divergence in Tiputini is not surprising, given a mixture of both oscine and suboscine passerines in Tiputini, whereas the Ozarks contained only one suboscine species. Comparing the average pairwise distances among associates to average pairwise distances in the sampled assemblages revealed that only in Tiputini—and only from the parasite perspective—is there significant phylogenetic clustering on avian hosts (fig. B1; figs. A1–A4, B1 are available online). Bird species in our Tiputini sample exhibit an average recombination activating gene 1 (RAG1) sequence divergence of 5.5%,

This content downloaded from 69.243.144.33 on Sat, 11 Oct 2014 17:00:37 PM All use subject to JSTOR Terms and Conditions

000 The American Naturalist but individual parasite lineages use hosts with an average divergence of 3.3%. Thus, not only does the number of hosts per parasite lineage appear to be a limited, but so is the evolutionary divergence of hosts compared to a random selection. That elevated specialization in the tropics disappears after accounting for phylogeny is consistent with some studies on herbivore-plant interactions (Novotny et al. 2002, 2006). For example, Novotny et al. (2006) compared herbivore assemblages on groups of plants with similar divergence between the tropical and temperate regions, thus effectively controlling for the influence of plant phylogeny on herbivore community structure. They found, first, that single plant species did not harbor more diverse herbivore assemblages in the tropics than in a temperate region. Although they did not consider phylogenetic relationships among the herbivores, this is consistent with our finding of similar per-host parasite diversity between sites according to the wMPD index. Second, herbivore feeding specificity did not differ between the regions, which is consistent with parasite specialization being equivalent between our two sites when incorporating phylogenetic relationships of hosts in the wMPD index. To reiterate the differences among the indexes we used to understand variation in specialization between two sites: (i) species degree is a count of the number of associates, (ii) H 2 and d  are both estimates of the weighted number of associates and measures of exclusive access to associates, and (iii) wMPD is an index of evolutionary relationship among associates, weighted by the frequency distribution among those associates. Thus, the absence of differences in both species degree and wMPD suggests that differences between tropical and temperate communities lie in more exclusive access to associates in the temperate locality. That is, hosts harbor on average as many parasites in the temperate site as in the tropical site, exhibit similar frequency distributions of their parasites, and carry parasites that are, on average, equally divergent from each other; however, birds share parasite lineages to a higher degree in the tropical site than in the temperate site. Conclusions Several parasite and host species, in both the tropical and temperate sites, have multiple associates (apparent generalists). However, incorporating frequency distributions among associates indicates high nonrandom levels of exclusive access to associates from both bird and parasite perspectives. Such nonrandom exclusiveness may arise if birds and their malaria parasites coadapt to each other locally (Apanius et al. 2000; Ricklefs and Bermingham 2007). Lower than expected average phylogenetic divergence among bird hosts of tropical parasites further em-

phasizes that parasites do not infect hosts at random. The exclusiveness observed here might be a common feature of antagonistic networks, and it might provide little leeway for associations to vary geographically (Morris et al. 2014). Indeed, we found no strong evidence for either increased or decreased malaria parasite specialization on bird hosts in the tropical site compared to those in the temperate site. That tropical and temperate communities do not differ in degree of specialization is not surprising in the sense that these internal parasites are highly biologically controlled and are somewhat protected from the physical environment. We cannot yet determine with certainty what has caused this pattern. Latitudinal variation in specialization, particularly with respect to antagonistic interactions, is an important issue, with implications for the origin and maintenance of tropical diversity (Schemske et al. 2009). This study adds another example to growing evidence against the hypothesis that a benign tropical climate allows for increased species specialization. The methods used here are comparable among different systems (e.g., Blu¨thgen et al. 2007). With respect to host-parasite systems, it would be interesting to learn whether specialization varies depending on the nature of the system, including transmission mode (e.g., direct vs. vector) and taxon (e.g., protozoa vs. helminths).

Acknowledgments We are grateful to T. Day (editor), C. Ganser, S. R. Hall (associate editor), and two anonymous reviewers for insightful comments on the manuscript. N. Blu¨thgen and C. Dormann provided advice on the network analysis. K. Bird, A. Burke, E. Coffey, R. Dura˜es, J. Hidalgo, M. R. Kunkel, T. Ryder, and W. Tori helped in the field. We also thank the staff of the Tiputini Biodiversity Station, especially C. de Romo, J. Guerra, D. Mosquera, D. Romo, and K. Swing for facilitating our work at the station, and we thank the Missouri Department of Conservation for housing in the Ozarks. This project was funded in part by a University of Missouri–St. Louis Dissertation Fellowship (M.S.-C.), the Sweden-America Foundation (M.S.-C.), the John Denver Scholarship (M.S.-C.) and the Leo and Kay Drey (V.A.E.) Scholarship through the Whitney R. Harris World Ecology Center, the St. Louis Audubon Society (M.S.-C.), Sigma Xi (M.S.-C.), the National Science Foundation (DEB-0542390 to R.E.R.; IBN-0235141 to B.A.L., J.G.B., and P. G. Parker), the National Geographic Society (7113-01 to J.G.B. and B.A.L.), the Fulbright US Scholars Program (J.G.B.), and the Curators of the University of Missouri (R.E.R.).

This content downloaded from 69.243.144.33 on Sat, 11 Oct 2014 17:00:37 PM All use subject to JSTOR Terms and Conditions

Specialization in Avian Malaria 000 Literature Cited Apanius, V., D. Penn, P. R. Slev, L. R. Ruff, and W. K. Potts. 1997. The nature of selection on the major histocompatibility complex. Critical Reviews in Immunology 17:179–224. Apanius, V., N. Yorinks, E. Bermingham, and R. E. Ricklefs. 2000. Island and taxon effects in parasitism and resistance of Lesser Antillean birds. Ecology 81:1959–1969. Bascompte, J., and P. Jordano. 2007. Plant-animal mutualistic networks: the architecture of biodiversity. Annual Review of Ecology, Evolution, and Systematics 38:567–593. Bascompte, J., P. Jordano, and J. M. Olesen. 2006. Asymmetric coevolutionary networks facilitate biodiversity maintenance. Science 312:431–433. Beadell, J. S., F. Ishtiaq, R. Covas, M. Melo, B. H. Warren, C. T. Atkinson, S. Bensch, et al. 2006. Global phylogeographic limits of Hawaii’s avian malaria. Proceedings of the Royal Society B: Biological Sciences 273:2935–2944. Beaver, R. A. 1979. Host specificity of temperate and tropical animals. Nature 281:139–141. Blu¨thgen, N., J. Fru¨nd, D. P. Vazquez, and F. Menzel. 2008. What do interaction network metrics tell us about specialization and biological traits? Ecology 89:3387–3399. Blu¨thgen, N., F. Menzel, and N. Blu¨thgen. 2006. Measuring specialization in species interaction networks. BMC Ecology 6:9. Blu¨thgen, N., F. Menzel, T. Hovestadt, and B. Fiala. 2007. Specialization, constraints, and conflicting interests in mutualistic networks. Current Biology 17:341–346. Cohen, J. 1977. Statistical power analysis for the behavioral sciences. Academic Press, New York. Connell, J. H. 1971. On the role of natural enemies in preventing competitive exclusion in some marine animals and in rain forest trees. Pages 298–312 in P. J. den Boer and G. R. Gradwell, eds. Dynamics of numbers in populations. Centre for Agricultural Publication and Documentation, Wageningen, Netherlands. ———. 1978. Diversity in tropical rain forests and coral reefs: high diversity of trees and corals is maintained only in a non-equilibrium state. Science 199:1302–1310. Cooper, N., R. Griffin, M. Franz, M. Omotayo, and C. L. Nunn. 2012. Phylogenetic host specificity and understanding parasite sharing in primates. Ecology Letters 15:1370–1377. Dalsgaard, B., E. Maga˚rd, J. Fjeldsa˚, A. M. M. Gonza´lez, C. Rahbek, J. M. Olesen, J. Ollerton, et al. 2011. Specialization in plant-hummingbird networks is associated with species richness, contemporary precipitation and Quaternary climate-change velocity. PloS ONE 6:e25891. Davies, T. J., and A. B. Pedersen. 2008. Phylogeny and geography predict pathogen community similarity in wild primates and humans. Proceedings of the Royal Society B: Biological Sciences 275: 1695–1701. Dethier, V. G. 1954. Evolution of feeding preferences in phytophagous insects. Evolution 8:33–54. Dobson, A., K. D. Lafferty, A. M. Kuris, R. F. Hechinger, and W. Jetz. 2008. Homage to Linnaeus: how many parasites? how many hosts? Proceedings of the National Academy of Sciences of the USA 105:11482–11489. Dobzhansky, T. 1950. Evolution in the tropics. American Scientist 38:209–221. Dormann, C. F., J. Fru¨nd, N. Blu¨thgen, and B. Gruber. 2009. Indices,

graphs and null models: analyzing bipartite ecological networks. Open Ecology Journal 2:7–24. Dormann, C. F., B. Gruber, and J. Frund. 2008. Introducing the bipartite package: analysing ecological networks. R News 8:8–11. Dunne, J. A., R. J. Williams, and N. D. Martinez. 2002. Network structure and biodiversity loss in food webs: robustness increases with connectance. Ecology Letters 5:558–567. Dyer, L. A., M. S. Singer, J. T. Lill, J. O. Stireman, G. L. Gentry, R. J. Marquis, R. E. Ricklefs, et al. 2007. Host specificity of Lepidoptera in tropical and temperate forests. Nature 448:696–699. Fallon, S. M., R. E. Ricklefs, B. L. Swanson, and E. Bermingham. 2003. Detecting avian malaria: an improved polymerase chain reaction diagnostic. Journal of Parasitology 89:1044–1047. Fine, P. V. A., and R. H. Ree. 2006. Evidence for a time-integrated species-area effect on the latitudinal gradient in tree diversity. American Naturalist 168:796–804. Fischer, A. G. 1960. Latitudinal variations in organic diversity. Evolution 14:64–81. Futuyma, D. J., and G. Moreno. 1988. The evolution of ecological specialization. Annual Review of Ecology and Systematics 19:207– 233. Gager, A. B., J. Del Rosario Loaiza, D. C. Dearborn, and E. Bermingham. 2008. Do mosquitoes filter the access of Plasmodium cytochrome b lineages to an avian host? Molecular Ecology 17: 2552–2561. Gardner, M. J., N. Hall, E. Fung, O. White, M. Berriman, R. W. Hyman, J. M. Carlton, et al. 2002. Genome sequence of the human malaria parasite Plasmodium falciparum. Nature 419:498–511. Gill, F., and D. Donsker. 2013. IOC World Bird List. Version 3.5. http://www.worldbirdnames.org. Gotelli, N. J., and G. R. Graves. 1996. Null models in ecology. Smithsonian Institution, Washington, DC. Hillebrand, H. 2004. On the generality of the latitudinal diversity gradient. American Naturalist 163:192–211. Horrocks, P., S. A. Kyes, P. C. Bull, and K. W. Deitsch. 2005. Molecular aspects of antigenic variation in Plasmodium falciparum. Pages 399–415 in I. W. Sherman, ed. Molecular approaches to malaria. ASM, Washington, DC. Hutchinson, G. E. 1959. Homage to Santa Rosalia, or why are there so many kinds of animals? American Naturalist 93:145–159. Janzen, D. H. 1970. Herbivores and the number of tree species in tropical forests. American Naturalist 104:501–528. Keesing, F., L. K. Belden, P. Daszak, A. Dobson, C. D. Harvell, R. D. Holt, P. Hudson, et al. 2010. Impacts of biodiversity on the emergence and transmission of infectious diseases. Nature 468:647– 652. Kembel, S. W., P. D. Cowan, M. R. Helmus, W. K. Cornwell, H. Morlon, D. D. Ackerly, S. P. Blomberg, and C. O. Webb. 2010. Picante: R tools for integrating phylogenies and ecology. Bioinformatics 26:1463–1464. Kembel, S. W., J. A. Eisen, K. S. Pollard, and J. L. Green. 2011. The phylogenetic diversity of metagenomes. PLoS ONE 6:e23214. Krasnov, B. R., G. I. Shenbrot, I. S. Khokhlova, D. Mouillot, and R. Poulin. 2008. Latitudinal gradients in niche breadth: empirical evidence from haematophagous ectoparasites. Journal of Biogeography 35:592–601. Kyes, S., P. Horrocks, and C. Newbold. 2001. Antigenic variation at the infected red cell surface in malaria. Annual Review of Microbiology 55:673–707.

This content downloaded from 69.243.144.33 on Sat, 11 Oct 2014 17:00:37 PM All use subject to JSTOR Terms and Conditions

000 The American Naturalist Lochmiller, R. L., and C. Deerenberg. 2000. Trade-offs in evolutionary immunology: just what is the cost of immunity? Oikos 88:87–98. MacArthur, R. H. 1955. Fluctuations of animal populations, and a measure of community stability. Ecology 36:533–536. ———. 1972, Geographical ecology. Harper & Row, New York. Maizels, R. M., D. A. P. Bundy, M. E. Selkirk, D. F. Smith, and R. M. Anderson. 1993. Immunological modulation and evasion by helminth-parasites in human-populations. Nature 365:797–805. Martin, L. B., M. Pless, J. Svoboda, and M. Wikelski. 2004. Immune activity in temperate and tropical house sparrows: a commongarden experiment. Ecology 85:2323–2331. Medeiros, M. C. I., G. L. Hamer, and R. E. Ricklefs. 2013. Host compatibility rather than vector-host-encounter rate determines the host range of avian Plasmodium parasites. Proceedings of the Royal Society B: Biological Sciences 280:20122947. Moles, A. T., S. P. Bonser, A. G. Poore, I. R. Wallis, and W. J. Foley. 2011. Assessing the evidence for latitudinal gradients in plant defence and herbivory. Functional Ecology 25:380–388. Morris, R. J., S. Gripenberg, O. T. Lewis, and T. Roslin. 2014. Antagonistic interaction networks are structured independently of latitude and host guild. Ecology Letters 17:340–349. Njabo, K. Y., A. J. Cornel, C. Bonneaud, E. Toffelmier, R. N. M. Sehgal, G. Valkiu¯nas, A. F. Russell, and T. B. Smith. 2011. Nonspecific patterns of vector, host and avian malaria parasite associations in a central African rainforest. Molecular Ecology 20:1049– 1061. Norris, K., and M. R. Evans. 2000. Ecological immunology: life history trade-offs and immune defense in birds. Behavioral Ecology 11:19–26. Novotny, V., Y. Basset, S. E. Miller, G. D. Weiblen, B. Bremer, L. Cizek, and P. Drozd. 2002. Low host specificity of herbivorous insects in a tropical forest. Nature 416:841–844. Novotny, V., P. Drozd, S. E. Miller, M. Kulfan, M. Janda, Y. Basset, and G. D. Weiblen. 2006. Why are there so many species of herbivorous insects in tropical rainforests? Science 313:1115–1118. Olesen, J. M., and P. Jordano. 2002. Geographic patterns in plantpollinator mutualistic networks. Ecology 83:2416–2424. Ollerton, J., and L. Cranmer. 2002. Latitudinal trends in plant-pollinator interactions: are tropical plants more specialised? Oikos 98: 340–350. Ostfeld, R. S., and F. Keesing. 2000. Biodiversity and disease risk: the case of Lyme disease. Conservation Biology 14:722–728. Poulin, R. 2010. Network analysis shining light on parasite ecology and diversity. Trends in Parasitology 26:492–498. Poulin, R., and M. R. Forbes. 2012. Meta-analysis and research on host-parasite interactions: past and future. Evolutionary Ecology 26:1169–1185. Proulx, S. R., D. E. L. Promislow, and P. C. Phillips. 2005. Network thinking in ecology and evolution. Trends in Ecology and Evolution 20:345–353. R Development Core Team. 2011. R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna. Ricklefs, R. E., and E. Bermingham. 2007. The causes of evolutionary radiations in archipelagoes: passerine birds in the Lesser Antilles. American Naturalist 169:285–297. Ricklefs, R. E., and S. M. Fallon. 2002. Diversification and host

switching in avian malaria parasites. Proceedings of the Royal Society B: Biological Sciences 269:885–892. Ricklefs, R. E., B. L. Swanson, S. M. Fallon, A. Martı´nez-Abraı´n, A. Scheuerlein, J. D. Gray, and S. C. Latta. 2005. Community relationships of avian malaria parasites in southern Missouri. Ecological Monographs 75:543–559. Santiago-Alarcon, D., V. Palinauskas, and H. M. Schaefer. 2012. Diptera vectors of avian haemosporidian parasites: untangling parasite life cycles and their taxonomy. Biological Reviews 87:928–964. Schemske, D. W., G. G. Mittelbach, H. V. Cornell, J. M. Sobel, and K. Roy. 2009. Is there a latitudinal gradient in the importance of biotic interactions? Annual Review of Ecology, Evolution, and Systematics 40:245–269. Schleuning, M., J. Fru¨nd, A.-M. Klein, S. Abrahamczyk, R. Alarco´n, M. Albrecht, G. K. Andersson, et al. 2012. Specialization of mutualistic interaction networks decreases toward tropical latitudes. Current Biology 22:1925–1931. Sepil, I., S. Lachish, A. E. Hinks, and B. C. Sheldon. 2013. MHC supertypes confer both qualitative and quantitative resistance to avian malaria infections in a wild bird population. Proceedings of the Royal Society B: Biological Sciences 280:20130134. Sheldon, B. C., and S. Verhulst. 1996. Ecological immunology: costly parasite defences and trade-offs in evolutionary ecology. Trends in Ecology and Evolution 11:317–321. Svensson, L. M. E., K. C. Ruegg, C. H. Sekercioglu, and R. N. M. Sehgal. 2007. Widespread and structured distributions of blood parasite haplotypes across a migratory divide of the Swainson’s thrush (Catharus ustulatus). Journal of Parasitology 93:1488–1495. Svensson-Coelho, M., J. G. Blake, B. A. Loiselle, A. S. Penrose, P. G. Parker, and R. E. Ricklefs. 2013. Diversity, prevalence, and host specificity of avian Plasmodium and Haemoproteus in a western Amazon assemblage. Ornithological Monographs 76:1–47. Svensson-Coelho, M., V. A. Ellis, B. A. Loiselle, J. G. Blake, and R. E. Ricklefs. 2014. Data from: Reciprocal specialization in multihost malaria parasite communities of birds: a temperate-tropical comparison. American Naturalist, Dryad Digital Repository, http:// dx.doi.org/10.5061/dryad.6s0h6. Thompson, J. N. 2005. The geographic mosaic of coevolution. University of Chicago Press, Chicago. ———. 2009. The coevolving web of life. American Naturalist 173: 125–140. Ulrich, W., and N. J. Gotelli. 2007. Null model analysis of species nestedness patterns. Ecology 88:1824–1831. Valkiu¯nas, G. 2005. Avian malaria parasites and other Haemosporidia. CRC, Boca Raton, FL. Va´zquez, D. P., C. J. Melia´n, N. M. Williams, N. Blu¨thgen, B. R. Krasnov, and R. Poulin. 2007. Species abundance and asymmetric interaction strength in ecological networks. Oikos 116:1120–1127. Va´zquez, D. P., and R. D. Stevens. 2004. The latitudinal gradient in niche breadth: concepts and evidence. American Naturalist 164: E1–E19. Webb, C. O., D. D. Ackerly, M. A. McPeek, and M. J. Donoghue. 2002. Phylogenies and community ecology. Annual Review of Ecology and Systematics 33:475–505. Associate Editor: Spencer R. Hall Editor: Troy Day

This content downloaded from 69.243.144.33 on Sat, 11 Oct 2014 17:00:37 PM All use subject to JSTOR Terms and Conditions