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Life-cycle mediated effects of urbanization on parasite communities in the estuarine fish, Fundulus heteroclitus

  • James M. Alfieri ,

    Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Visualization, Writing – original draft, Writing – review & editing

    JamesMAlfieri@gmail.com

    Affiliation Ecology and Evolutionary Biology Interdisciplinary PhD Program, Texas A&M University, College Station, TX, United States of America

  • Tavis K. Anderson

    Roles Conceptualization, Funding acquisition, Methodology, Project administration, Resources, Supervision, Writing – review & editing

    Affiliation Virus and Prion Research Unit, National Animal Disease Center, USDA—ARS, Ames, IA, United States of America

Life-cycle mediated effects of urbanization on parasite communities in the estuarine fish, Fundulus heteroclitus

  • James M. Alfieri, 
  • Tavis K. Anderson
PLOS
x

Abstract

This study examined the relationship between urbanization and parasite community structure in the estuarine fish, Fundulus heteroclitus. We measured landscape and physicochemical factors associated with urbanization at 6 sites from 4 collection periods. Concurrently, we quantified the metazoan parasite community in F. heteroclitus collected at those sites, with 105 fish studied per site during the 4 collection periods. Parasite community composition differed among sites. Host size was the most important variable for direct life-cycle parasite assemblages and indirect life-cycle parasites at the individual fish level, while landscape and physicochemical factors determined the structure of indirect life-cycle parasite assemblages at the population scale. Variation in the prevalence and intensity of infection of two indirect life-cycle parasites, Lasiocotus minutus and Glossocercus caribaensis, were the primary parasites that drove differences across sites. Variation in the presence/absence of these indirect life-cycle parasite species was associated with sediment Ni concentrations, patch density, and marsh size. Our data support the hypothesis that urbanization, acting at both landscape and physicochemical scales, can have a significant impact on parasite community structure. This, however, varied by parasite life history: there was little effect of urbanization on the prevalence and intensity of direct life-cycle parasites, but significant variation was detected for indirect life-cycle parasites. This study demonstrates how anthropogenically driven landscape change influences fine-scale population dynamics of parasites.

Introduction

Urbanization significantly alters estuaries and the free-living animal populations within these environments[1,2]. Animal parasites, which are intrinsically connected to their hosts, are also impacted by the consequences of urbanization. Urbanization can directly affect parasites through exposure to an altered physicochemical environment [3,4] or indirectly through changes in host population dynamics [5]. Parasites co-occurring in an individual–the parasite infracommunity [6]–simultaneously use the same host resource, but each parasite species may have a different life history strategy which may be differently affected by urbanization. Notably, indirect life-cycle (more than one host species) parasites have life stages that are exposed to the external environment and are dependent upon trophic interactions; whereas direct life-cycle (one host species) parasite transmission largely does not involve trophic interactions. Consequently, urbanization may differentially affect parasite species [7], but data that associates urbanization with parasite communities and life history strategy are sparse (but see [8,9]).

Parasite life-cycles can be broadly characterized as either indirect or direct. Indirect life-cycle parasites require different species of hosts to complete their life-cycle and are largely dependent on trophic interactions which occur more frequently in locally stable communities [10]. This essential interaction has been used to demonstrate how parasites can be indicators of free-living diversity [11], and as such, it has been argued that a healthy ecosystem is one that is rich in parasites [12]. In urbanized estuaries, host population dynamics may be less stable, resulting in reduced diversity or less predictable host dynamics, causing a concomitant decrease in the species richness of indirect life-cycle parasites [5]. On the other hand, direct life-cycle parasites require only one species of host to complete their life-cycle and are largely dependent on host population densities, as abundant hosts increase the probability of a parasite encountering a suitable environment to colonize [13,14]. A feature of urbanized estuaries is habitat fragmentation, which can result in increased host densities and a concomitant increase in the species richness of direct life-cycle parasites [15]. Generally, parasite communities are described using terms such as prevalence (the number of hosts infected with a parasite species divided by the number of hosts examined), and intensity of infection (number of individuals of a parasite species in a single host species) [6]. These measures are calculated by quantifying the parasite species in a host individual–the parasite infracommunity [6]–and then aggregating these data to consider all the parasite species–the parasite “component” community–found in a subset of a host species collected from a subset of a sampled abiotic environment [6].

Many of the studies that examine the interaction between host and parasite in urbanized ecosystems have been conducted with human pathogens [16], consider a single host and a single parasite [17], or a single contaminant and landscape factor. Further, linking the regional process of urbanization to local transmission and diversity of parasite communities has yet to reveal consistent patterns [1820]. One potential explanation for the absence of consistent results is that urbanization differentially affects parasite species: the size and direction of effect is contingent upon parasite life history. In this study, we assessed the effect of multiple landscape composition and physicochemical factors on 24 parasite communities of the salt marsh fish, Fundulus heteroclitus. The parasite community in F. heteroclitus includes indirect and direct life-cycle species, and the impact of urbanization on the structure parasite communities should be mediated through different life-cycle strategies. We predicted that urbanized sites would have low diversity and prevalence of indirect life-cycle parasites; but direct life-cycle parasites would increase in diversity and abundance.

Materials and methods

Ethics statement

Field collections were conducted under scientific permits issued by the Georgia Department of Natural Resources approved collection under Scientific Collecting Permit number 29-WJH-15-182. Prior to necropsy, fish were maintained briefly in aquaria following animal care protocols approved by The Animal Care and Use Committee at Georgia Southern University (protocol #I14013). Fish euthanasia was conducted in accordance with the 2000 Report of the American Veterinary Medical Association Panel on Euthanasia, approved by The Animal Care and Facilities Committee at Georgia Southern University under the protocol described above (protocol #I14013): fish were placed in a buffered 300 mg/L solution of tricaine methanesulfonate (MS-222) until cessation of opercula movement, followed by pithing of the brain and spinal cord.

Study site description

We examined 6 sites along the coastline of Georgia, USA, that reflected variation in urbanization, measured through % impervious surface within a 250 m radius around each site (Fig 1). We used this metric to select sites because impervious surface is a strong predictor of different effects of urbanization, such as landscape composition changes, habitat fragmentation, and contaminants [2,21]. The 250 m radius around each site was chosen because this is similar to the home range size of F. heteroclitus [22,23]. The 250 m radius criteria was used as an objective measure to select sites representing a range of urbanization and its effects, however, for the landscape composition analyses we used the watershed level as our spatial scale (described below).

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Fig 1. Map of 6 salt marsh study sites in coastal Georgia, USA with 2011 land cover data.

The sites include Fort Pulaski (FP), Cockspur Island (CI), Tybee (TB), and Skidaway Island (SK) in the Savannah River Estuary; Shellman Bluff (SB) as a representative of the Sapelo Sound; and St. Marys (SM) as part of the St. Marys Estuary. Red circles represent a 250 m buffer around the study site. For the purpose of this work, land cover data was reclassified from the original 21 categories to 10 (Salt Marsh, Developed, Freshwater Wetland, Open Water, Forest, Agriculture, Bare Land, and Grassland): 2 land cover categories were not present in the study area (Freshwater Aquatic Bed and Unconsolidated Shore).

https://doi.org/10.1371/journal.pone.0225896.g001

Quantifying the landscape and physicochemical environment

We defined the boundaries of the landscape to the lowest level watershed provided by the United States Geological Survey (USGS) Watershed Boundary Dataset (WBD): the hydrological unit code (HUC) 12-digit boundary [24]. We used the 2011 National Land Cover Dataset (NLCD) and National Oceanic and Atmospheric Administration’s (NOAA) Coastal Change Analysis Program (C-CAP) for the regional land cover analysis [25,26]. Regional landscape composition and change were measured using ArcGIS (ArcGIS Version 10.3, Environmental Systems Research Institute, Redlands, California). We also calculated a series of regional landscape metrics: patch density, largest patch index, edge density, mean salt marsh size, % salt marsh, % developed land, and total area using FRAGSTATS software [27]. Patch density is an index that expresses the number of continuous habitat types, or patches, per unit area, and is a metric for landscape heterogeneity. Largest patch index is the size of the largest habitat patch relative to the size of the landscape, and is a measure of landscape dominance. Edge density is an index of the amount of habitat edges per unit area, and the contrast between developed land and salt marsh was weighted at 0.5 to evaluate salt marsh habitat fragmentation by urban structures or landscapes. Mean salt marsh size is an index of the size of a salt marsh habitat patch, with larger patches weighted in order to decrease the sensitivity of the mean to small habitat patch sizes. The % salt marsh and developed land is the percentage of the landscape comprised of those categories, and is a metric for habitat size and dominance. Total area refers to the area of the watershed. In addition, we used the National Oceanic and Atmospheric Administration’s (NOAA) Coastal Change Analysis Program (C-CAP) to evaluate % landscape change within the HUC-12 digit watersheds for the period of time from 1996–2010.

We collected information on the physicochemical environment from each site at flow and ebb tide in March, June, September 2015 and February 2016. Flow and ebb tide measurements were averaged for each site and time point for analysis. We measured pH, temperature, salinity, and conductivity using a handheld multiparamenter instrument (Yellow Springs Instruments Professional Plus; Yellow Springs Instruments, Yellow Springs, Ohio). In addition, we quantified the trace metal composition, nutrient concentrations, and chlorophyll a concentration during these dates. To extract chlorophyll a, we followed a standard acidification method (EPA 445.0), whereby a volume of 100 ml was filtered using Whatman GF/F filters (47 mm; 0.7 μm nominal pore size). Phytoplankton pigments were then extracted from the filters in 8 ml of 90% acetone at 0°C for 24 hours. Fluorescence was measured using a Trilogy fluorometer (Turner Designs, San Jose, California). For the nutrient and trace metal quantification, 2 samples from each collection time and site were sent to the University of Georgia Laboratory for Environmental Analysis (Athens, Georgia). These samples were filtered using a microwave-assisted nitric acid method (EPA 3015), and total nitrogen, total phosphorus, and 72 metals were analyzed with inductively coupled plasma mass spectrometry (ELAN 9000; PerkinElmer, Waltham, Massachusetts). In addition to water analyses, we quantified the trace metal composition of sediment by collecting 3–8 cm core samples from randomized locations within each site in September 2015. These samples were sent to the University of Georgia Laboratory for Environmental Analysis (Athens, Georgia), and were prepared using a microwave-assisted nitric acid method (EPA 3052).

Quantifying the parasite community in F. heteroclitus

We used the parasite community of a focal species, the common marsh killifish F. heteroclitus, to assess the impact of human modification of the environment on parasite establishment and richness. The common killifish inhabits coastal waters along the Atlantic coast of North America, typically living in dense shoals that may include thousands of individuals: they are oviparous and spawn from late spring to early fall, depending on latitude [28]. Notably, F. heteroclitus survive large temperature and salinity ranges [29] and appear to tolerate a wide range of contaminants (Burnett, 2007). Additionally, F. heteroclitus are omnivorous and act as a major prey source for fish-eating birds and other predatory fishes [30]. This trophic centrality has been suggested to be a driver of indirect life-cycle parasite persistence [31], and in other parasite community studies they have been found to host at least 22 species of helminth parasites [32]. In Georgia, USA, at least three species of metazoan parasite with indirect life-cycles have been described infecting F. heteroclitus. These include a trematode, Lasiotocus minutus, that has F. heteroclitus as the definitive host, molluscs as the first intermediate host, and fish or crustaceans as the second intermediate host [33]. A cestode, Glossocercus caribaensis, that has fish-eating birds as the definitive host, crustaceans as the first intermediate host, and F. heteroclitus as the second intermediate host [34]. The last indirect life-cycle parasite was a nematode, Contraceacum sp., that can parasitize fish-eating birds and mammals as definitive hosts, and F. heteroclitus as the sole intermediate host.

At each timepoint, 5 baited minnow traps were randomly placed at every site, during the flood tide and collected during the ebb tide. We placed all fish from the 5 traps into a holding tank, and randomly subsampled 30 killifish to obtain a representative population of each site and date combination. This sampling did not take into consideration the size or age of the fish, however prior research has suggested that a sample size of 30 from a host population is appropriate to capture parasite community diversity within a host population [35]. The fish from each collected site were separately housed in the animal facility at Georgia Southern University and necropsied within 1 week (IACUC #I14013).

Each fish was euthanized in a buffered 300 mg L-1 solution of tricaine methanesulfonate (MS-222) until cessation of opercula movement followed by sex determination and measurements of total length and weight. The MS-222 solution, all external surfaces, gills, and opercula were examined for ectoparasites and helminths. The viscera, gonads, spleen, liver, heart, intestine, and bladder were removed and examined for helminths. All helminths from the first collection were heat fixed, stored in 70% ethanol, stained in acetocarmine, and mounted in Permount. Parasites from all collections were identified with keys and primary literature [32,36].

Statistical analyses

To visualize the variation in parasite component community and infracommunity structure, we performed non-metric multi-dimensional scaling (NMDS). In the NMDS for component communities, average abundances were calculated and square root transformed to control for the effect of high abundance parasite taxa. In the NMDS for infracommunities, raw abundances were ln(x + 1) transformed. Resemblance matrices were constructed using Bray-Curtis dissimilarity distance, and stress was calculated using Kruskal’s stress formula 1. To determine whether there were significant differences in parasite component community structure, we performed a permutational multivariate ANOVA (PerMANOVA). For this analysis, we used site as a factor and performed 999 permutations. Additionally, we performed a 2-way crossed similarity percentage (SIMPER) analysis to identify the parasite species that contributed to 5% or greater of the variation in parasite community structure among sites. These analyses were conducted in R statistical environment using package "vegan" [37,38].

To determine the roles of landscape composition and physicochemical factors in structuring the parasite infracommunity and component community, we built multivariate random forest (MRF) models using R package randomForestSRC [39]. MRF is an ensemble machine learning method, that builds a suite of bootstrapped multivariate regression trees [40]. MRFs are increasingly being used in ecological studies because they allow multivariate species composition response data, do not assume independence among samples, make no a priori assumptions on the relationships between the response and predictor variables, and can account for imbalanced data [41,42]. Our response variable was the multivariate parasite species data, and our predictor variables included 8 landscape factors (Table 1), 23 physicochemical concentrations (Tables 2 and 3), and host length, weight, and sex. We built 4 MRFs, examining landscape and physicochemical factors effects on direct and indirect parasite communities at the infracommunity and component community scale. MRFs were built using 1000 trees and "Breiman-Cutler" variable importance was calculated through permutation. Variable importance was standardized to average variable effect across species. In these variable importance permutations, each predictor variable is placed in the out-of-sample (out-of-bag for univariate analyses) data for the tree model. The out-of-sample prediction error is then calculated with and without the permutation and averaged over the MRF trees. Greater differences between the permuted and non-permuted out-of-sample prediction error equate to greater variable importance.

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Table 3. Mean metal concentration (mg/kg) in sediment of salt marsh sites.

https://doi.org/10.1371/journal.pone.0225896.t003

Results

Parasite community in F. heteroclitus

Eight taxa of metazoan parasites were identified from 630 fish, representing 24 different parasite communities. The direct life-cycle parasites included the branchiuran Argulus funduli, the copepod Ergasilus funduli, the leech Myzobdella lugubris, and the monogeneans Swingleus ancistrus and Fundulotrema prolongis. The indirect life-cycle parasites included the digenean Lasiotocus minutus, the cestode Glossocercus caribaensis, and the nematode genera Contracaecum sp. These 8 taxa of parasites infected more than 70% of the killifish examined (Tables 4 and 5).

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Table 4. Prevalence (%) and mean intensity (SE) of the 3 indirect life-cycle parasite taxa infecting the salt marsh fish, F. heteroclitus.

https://doi.org/10.1371/journal.pone.0225896.t004

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Table 5. Prevalence and mean intensity (SE) of the 5 direct life-cycle parasite taxa infecting the salt marsh fish, F. heteroclitus.

https://doi.org/10.1371/journal.pone.0225896.t005

Assessed with NMDS and PerMANOVA, infracommunity composition differed among sites (P < 0.001, Pseudo F5,629 = 15.691; Fig 2A). Additionally, the parasite component community composition differed among sites (P < 0.001, Pseudo F5,12 = 6.11; Fig 2B). SIMPER analysis indicated that the observed differences in parasite community structure were driven by indirect life-cycle parasites: the digenean Lasciotocus minutus, and the cestode Glossocercus caribaensis. This pattern was consistent when considering the parasite component community and the parasite infracommunity. This analysis demonstrated that direct life-cycle parasites did not contribute to the variation in parasite community structure.

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Fig 2.

Non-metric multidimensional scaling plots of parasite infracommunities (A) and component communities (B) of the salt marsh fish, F. heteroclitus, from 6 sites in coastal Georgia, USA. Infracommunity (A) distances are based on Bray-Curtis dissimilarities of the ln(x +1) transformed abundances of 8 parasite taxa. Component community (B) distances are based on Bray-Curtis dissimilarities of the square-root transformed average abundances of 8 parasite taxa. The sites include: Fort Pulaski (FP) (salmon triangles), Cockspur Island (CI) (aquamarine circles), Tybee (TB) (yellow stars), and Skidaway Island (SK) (pink crosses) in the Savannah River Estuary; Shellman Bluff (SB) (blue squares) as a representative of the Sapelo Sound; and St. Marys (SM) (green crossed squares) as part of the St. Marys Estuary.

https://doi.org/10.1371/journal.pone.0225896.g002

Landscape and physicochemical predictors of parasite community in F. heteroclitus

We identified 12 metals from water analyses and 5 metals from sediment analyses that surpassed concentration thresholds (Tables 2 and 3), and our spatial analysis included 9 landscape metrics that varied across our collection sites (Table 1). We built MRF models to determine important variables associated with direct and indirect life-cycle parasites at the infracommunity (within an individual host) and component community (within a host population at a collection site) scales. The model predicting direct life-cycle parasite community structure at the infracommunity scale explained 40.18% variance, with fish weight and length being the most important variables (Fig 3A). The model predicting indirect life-cycle parasite community structure at the infracommunity scale explained 21.4% variance, with fish weight, fish length, and percent change in developed land being the most important variables (Fig 3B). The model predicting direct life-cycle parasite community structure at the component community scale explained 70.67% variance, with fish weight and length being the most important predictors (Fig 3C). The model predicting indirect life-cycle parasite community structure at the component community scale explained 73.43% variance, with sediment Ni, patch density, and marsh size being the most important predictors (Fig 3D).

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Fig 3. Multivariate random forest model standardized variable importance.

Variable importance in the model predicting: direct life-cycle parasite community structure at the infracommunity scale (A); indirect life-cycle parasite community structure at the infracommunity scale (B); direct life-cycle parasite community structure at the component community scale (C); and indirect life-cycle parasite community structure at the component community scale (D).

https://doi.org/10.1371/journal.pone.0225896.g003

Discussion

The goal of this study was to determine the effects of urbanization, mediated through alterations in landscape composition and physicochemical factors, in structuring parasite communities. Our sampling in coastal Georgia, USA provided evidence supporting the role of urbanization in impacting salt marshes via increased metal contamination, altering landscape composition at a fine spatial scale (250 m), and at the watershed level. We determined that parasite community composition differed among sites with different levels of urbanization. Variation in the prevalence and intensity of infection by indirect life-cycle parasites, the digenean L. minutus and the cestode G. caribaensis, were the primary drivers for the differences in parasite communities. Although the prevalence of direct life-cycle parasites differed among sites, this difference did not contribute to overall variation in component community composition. We found that factors driving community structure differed between the infracommunity and component community for indirect life-cycle parasites. Host size was the most important variable for direct life-cycle parasite assemblages and indirect life-cycle parasites at the infracommunity level, while landscape and physicochemical factors determined the structure of indirect life-cycle parasite assemblages at the component community scale. These data support the prediction that in the common marsh killifish, parasite community composition is explained by metrics associated with human modification of the environment, and parasite responses to urbanization are dependent upon life history.

Our results indicate that anthropogenic physicochemical and landscape factors structure indirect life-cycle parasites at the component community scale. The most important physicochemical factor was sediment nickel concentration, and although nickel occurs naturally and is essential to most organisms as a trace mineral, increased concentrations due to human activities (i.e., burning fuel [44]) can be toxic to salt marsh benthic organisms. For example, Field et al. (2002) built a suite of logistic regression models based on toxicity assays of marine amphipods, and predicted that 50% of the population would show toxicity effects at concentrations of 47 ppm [45]. The concentrations we observed exceed this level, and may affect intermediate host populations that are an integral part of the transmission of the indirect life-cycle parasites we described in our study, the digenean Lasiotocus minutus and the cestode Glossocercus caribaensis. Additionally, these indirect life-cycle parasites have life stages that are external to the host, and the nickel concentrations we measure may be toxic to these free-living parasite life stages further impacting parasite component community diversity.

The most important landscape factors for indirect parasites at the component community level were marsh size and patch density. Marsh size has been shown to affect carbon pathways to resident invertebrates, suggesting potential impacts on animal community and resultant trophic structure and interactions that are exploited by indirect life-cycle parasites for transmission [46]. For example, Lowe and Peterson (2014) found marsh size to be positively correlated with abundances of Gulf Menhaden and brown shrimp, though they did not find an association with blue crab abundance in the same sites[1]. Patch density is a measure for landscape heterogeneity. In urbanized estuaries, salt marshes become increasingly fragmented and the landscape increases in heterogeneity [47]. This often has the result of isolating habitat patches, leading to alterations in animal community structure and trophic interactions [48,49]. For example, Rudershausen (2018) found that salt marsh connectivity influenced fish community structure and the probability of F. heteroclitus movement [50]. These studies illustrate that landscape alterations have the potential to alter free-living host community structure; given that indirect life-cycle parasites require stable trophic interactions [5] between animals across trophic levels, altering the structure of the free-living community will necessarily be reflected in the parasite community [51].

Although the infracommunity is a sample within the component community, we found the factors that structure indirect life-cycle parasites differ between these two levels. Parasite transmission is inherently a local phenomenon, and individual risk factors do not necessarily equate to population risk factors. For example, the encounter-dilution effect hypothesizes that individuals can decrease their individual risk of parasitic infection through the formation of groups [52] even as the population level of infection increases. We found that the diversity of parasites in an individual fish was driven by host size (length and weight), but the diversity of parasites in the population was mostly affected by abiotic measures (sediment Ni, patch density, and marsh size). This subtle difference is because parasite community assembly is influenced by processes operating at a range of spatial and temporal scales. Parasite species are found within a regional species pool that is constrained by evolutionary processes, and only a subset of the species from the regional pool will colonize a site depending on ecological factors such as dispersal and the probability of encountering a suitable host. Subsequently, a subset of the species from the regional pool will colonize a particular site depending on dispersal and exposure probability. In essence, our data suggests that the observed parasite community within a host and the factors that determine what parasites you find in that host are dependent on the scale at which the study is conducted because of different abiotic and biotic filters [20,51,53,54].

Finally, our results indicate that host body size was the strongest determinant of direct life-cycle parasites at the infracommunity and component community scales. Individual hosts can be thought as habitat "islands" for parasites [55]. For direct life-cycle parasites, island biogeography theory can be applied [56], wherein larger hosts are larger islands, and consequently provide a larger habitat for a parasite to colonize, allowing for a greater number of parasite individuals and concurrent coexisting species [57,58]. In fish, body growth is largely indeterminate, and is associated with age, which may result in older fish harboring more parasite species and individuals simply because of an increase in the opportunity for acquiring an infection.

Previous studies have shown a relationship between urbanization and parasite community variation. Blanar et al. (2016) demonstrated a correlation between parasite community structure and local contaminants and land use within 5 km [9]. In this study, the relative abundance of the indirect life-cycle digenean was positively associated with an increase in crude oil contaminants, whereas the opposite pattern was observed for the directly transmitted monogenean parasites. This observation follows results of an earlier meta-analysis, where parasite life history (>1 obligatory host in life-cycle vs. 1 obligatory host in life-cycle) and habitat (external vs. internal) informed whether aquatic pollution had a significant effect on parasite population dynamics [59]. Additionally, Calegaro-Marques and Amato (2014) revealed an association between an urban-rural gradient and life-cycle variation in parasite communities of Rufous-bellied thrushes [8]. Our results agree with these studies, and support the proposition that urbanization disproportionately affects indirect life-cycle parasites, which is then reflected in the parasite component community structure.

Coastal urbanization and anthropogenic disturbance are rapidly altering free-living and parasite community dynamics. Our results suggest that urbanization and its effects are important in structuring parasite communities of the common marsh killifish, indirect life-cycle parasites are more affected than direct life-cycle parasites, and the degree to which individual parasite species respond to urbanization is determined by their specific life history strategy. Further, our data suggest that urbanization likely affects interactions of free-living hosts, and their environment which is then detected as variation in the parasite community.

Acknowledgments

We acknowledge the advice and support provided by Dr. Clark Alexander and Mike Robinson at the Applied Coastal Research Laboratory (Georgia Southern University), and Dr. Sayed Hassad at the Laboratory of Environmental Analysis (University of Georgia). Field assistance was provided by Emily Dodd, Sarah Dunn, Maria St. Jean, and Jackson Tomlinson. Comments on an earlier draft by Drs. Risa Cohen, James Roberts, and Oscar Pung improved this manuscript. Mention of trade names or commericial products in this article is solely for the purpose of providing specific information and does not imply recommendation or endorsement by the USDA. USDA is an equal opportunity provider and employer.

References

  1. 1. Lowe MR, Peterson MS. Effects of Coastal Urbanization on Salt-Marsh Faunal Assemblages in the Northern Gulf of Mexico. Marine and Coastal Fisheries. 2014;6: 89–107.
  2. 2. Lerberg SB, Holland AF, Sanger DM. Responses of tidal creek macrobenthic communities to the effects of watershed development. Estuaries. 2000;23: 838.
  3. 3. Anderson TK, Sukhdeo MVK. Abiotic versus biotic hierarchies in the assembly of parasite populations. Parasitology. 2010;137: 743–754. pmid:20025818
  4. 4. Blanar CA, Marcogliese DJ, Couillard CM. Natural and anthropogenic factors shape metazoan parasite community structure in mummichog (Fundulus heteroclitus) from two estuaries in New Brunswick, Canada. Folia Parasitol (Praha). 2011;58: 240–248.
  5. 5. Anderson TK, Sukhdeo MVK. The relationship between community species richness and the richness of the parasite community in Fundulus heteroclitus. J Parasitol. 2013;99: 391–396. pmid:23198795
  6. 6. Bush AO, Lafferty KD, Lotz JM, Shostak AW. Parasitology meets ecology on its own terms: Margolis et al. revisited. J Parasitol. 1997;83: 575–583. pmid:9267395
  7. 7. Dugarov ZN, Baldanova DR, Khamnueva TR. Impact of the degree of urbanization on composition and structure of helminth communities in the Mongolian racerunner (Eremias argus) Peters, 1869. J Helminthol. 2018;92: 178–186. pmid:28349852
  8. 8. Calegaro-Marques C, Amato SB. Urbanization breaks up host-parasite interactions: a case study on parasite community ecology of rufous-bellied thrushes (Turdus rufiventris) along a rural-urban gradient. PLoS One. 2014;9: e103144. pmid:25068271
  9. 9. Blanar CA, Hewitt M, McMaster M, Kirk J, Wang Z, Norwood W, et al. Parasite community similarity in Athabasca River trout-perch (Percopsis omiscomaycus) varies with local-scale land use and sediment hydrocarbons, but not distance or linear gradients. Parasitol Res. 2016;115: 3853–3866. pmid:27314231
  10. 10. Anderson TK, Sukhdeo MVK. Qualitative community stability determines parasite establishment and richness in estuarine marshes. PeerJ. 2013;1: e92. pmid:23802092
  11. 11. Hechinger RF, Lafferty KD, Huspeni TC, Brooks AJ, Kuris AM. Can parasites be indicators of free-living diversity? Relationships between species richness and the abundance of larval trematodes and of local benthos and fishes. Oecologia. 2007;151: 82–92. pmid:17024376
  12. 12. Hudson PJ, Dobson AP, Lafferty KD. Is a healthy ecosystem one that is rich in parasites? Trends Ecol Evol (Amst). 2006;21: 381–385. pmid:16713014
  13. 13. Arneberg P, Skorping A, Grenfell B, Read AF. Host densities as determinants of abundance in parasite communities. Proc R Soc Lond B. 1998;265: 1283–1289.
  14. 14. Nunn CL, Altizer S, Jones KE, Sechrest W. Comparative tests of parasite species richness in primates. Am Nat. 2003;162: 597–614. pmid:14618538
  15. 15. Hussain S, Ram MS, Kumar A, Shivaji S, Umapathy G. Human presence increases parasitic load in endangered lion-tailed macaques (Macaca silenus) in its fragmented rainforest habitats in Southern India. PLoS One. 2013;8: e63685. pmid:23717465
  16. 16. Bradley CA, Altizer S. Urbanization and the ecology of wildlife diseases. Trends Ecol Evol (Amst). 2007;22: 95–102. pmid:17113678
  17. 17. Johnson DS, Fleeger JW, Deegan LA. Large-scale manipulations reveal that top-down and bottom-up controls interact to alter habitat utilization by saltmarsh fauna. Mar Ecol Prog Ser. 2009;377: 33–41.
  18. 18. Schotthoefer AM, Rohr JR, Cole RA, Koehler AV, Johnson CM, Johnson LB, et al. Effects of wetland vs. landscape variables on parasite communities of Rana pipiens: links to anthropogenic factors. Ecol Appl. 2011;21: 1257–1271. pmid:21774428
  19. 19. Chapman JM, Marcogliese DJ, Suski CD, Cooke SJ. Variation in parasite communities and health indices of juvenile Lepomis gibbosus across a gradient of watershed land-use and habitat quality. Ecol Indic. 2015;57: 564–572.
  20. 20. Johnson PTJ, Wood CL, Joseph MB, Preston DL, Haas SE, Springer YP. Habitat heterogeneity drives the host-diversity-begets-parasite-diversity relationship: evidence from experimental and field studies. Ecol Lett. 2016;19: 752–761. pmid:27147106
  21. 21. Paul MJ, Meyer JL. Streams in the Urban Landscape. Annu Rev Ecol Syst. 2001;32: 333–365.
  22. 22. Lotrich VA. Summer home range and movements of Fundulus heteroclitus (Pisces: Cyprinodontidae) in a tidal creek. Ecology. 1975;56: 191–198.
  23. 23. Teo SLH, Able KW. Habitat use and movement of the mummichog (Fundulus heteroclitus) in a restored salt marsh. Estuaries. 2003;26: 720–730.
  24. 24. Federal standards and procedures for the National Watershed Boundary Dataset (WBD). 4th ed. Reston, VA: U.S. Geological Survey; 2013. Report No.: 11-A3.
  25. 25. Yang L, Jin S, Danielson P, Homer C, Gass L, Bender SM, et al. A new generation of the United States National Land Cover Database: Requirements, research priorities, design, and implementation strategies. ISPRS Journal of Photogrammetry and Remote Sensing. 2018;146: 108–123.
  26. 26. NOAA Office for Coastal Management. Coastal Change Analysis Program (C-CAP) Regional Land Cover. National Oceanic and Atmospheric Administration, Office for Coastal Management;
  27. 27. McGarigal K, Marks BJ. FRAGSTATS: spatial pattern analysis program for quantifying landscape structure. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station; 1995. https://doi.org/10.2737/PNW-GTR-351
  28. 28. Valiela I, Wright JE, Teal JM, Volkmann SB. Growth, production and energy transformations in the salt-marsh killifish Fundulus heteroclitus. Mar Biol. 1977;40: 135–144.
  29. 29. Abraham BJ. Species Profiles. Life Histories and Environmental Requirements of Coastal Fishes and Invertebrates (Mid-Atlantic). Mummichog and Striped Killifish. 1985.
  30. 30. Kneib RT. The Role of Fundulus heteroclitus in Salt Marsh Trophic Dynamics. Am Zool. 1986;26: 259–269.
  31. 31. Anderson TK, Sukhdeo MVK. Host centrality in food web networks determines parasite diversity. PLoS One. 2011;6: e26798. pmid:22046360
  32. 32. Harris CE, Vogelbein WK. Parasites of Mummichogs, Fundulus heteroclitus, from the York River, Virginia, U.S.A., with a Checklist of Parasites of Atlantic Coast Fundulus Spp. Comp Parasitol. 2006;73: 72–110.
  33. 33. Stunkard HW. The morphology, life history, and systematic relations of Lasiotocus elongatus (Manter, 1931)(Trematoda: Digenea). Biol Bull. 1981;160: 155–160.
  34. 34. Ortega-Olivares MP, García-Prieto L, García-Varela M. Gryporhynchidae (Cestoda: Cyclophyllidea) in Mexico: species list, hosts, distribution and new records. Zootaxa. 2014;3795: 101–125. pmid:24870465
  35. 35. Dove ADM, Cribb TH. Species accumulation curves and their applications in parasite ecology. Trends Parasitol. 2006;22: 568–574. pmid:17035087
  36. 36. Khalil LF. Order Cyclophyllidea (diagnosis and key to families). Key to the cestode parasites of vertebrates. Wallingford, UK: CAB International; 1994.
  37. 37. Oksanen J, Blanchet FG, Friendly M, Kindt R, Legendre P, McGlinn D, et al. vegan: Community Ecology Package. R package version 2.5–6 [Internet]. 2019. Available: https://CRAN.R-project.org/package=vegan
  38. 38. R Core Team. R: A Language and Environment for Statistical Computing [Internet]. Vienna, Austria: R Foundation for Statistical Computing; 2019. Available: https://www.R-project.org
  39. 39. Ishwaran H, Kogalur U. Fast Unified Random Forests for Survival, Regression, andClassification (RF-SRC). 2019.
  40. 40. Breiman L. Random Forests. Springer Science and Business Media LLC. 2001;
  41. 41. Eldridge A, Guyot P, Moscoso P, Johnston A, Eyre-Walker Y, Peck M. Sounding out ecoacoustic metrics: Avian species richness is predicted by acoustic indices in temperate but not tropical habitats. Ecol Indic. 2018;95: 939–952.
  42. 42. Miller K, Huettmann F, Norcross B, Lorenz M. Multivariate random forest models of estuarine-associated fish and invertebrate communities. Mar Ecol Prog Ser. 2014;500: 159–174.
  43. 43. Buchman MF. Screening Quick Reference Tables (SQuiRTs). 2008;
  44. 44. Cempel M. Nickel: A Review of Its Sources and Environmental Toxicology. Polish Journal of Environmental Studies. 2006;
  45. 45. Field LJ, MacDonald DD, Norton SB, Ingersoll CG, Severn CG, Smorong D, et al. Predicting amphipod toxicity from sediment chemistry using logistic regression models. Environ Toxicol Chem. 2002;21: 1993–2005. pmid:12206441
  46. 46. Guest MA, Connolly RM. Movement of carbon among estuarine habitats: the influence of saltmarsh patch size. Mar Ecol Prog Ser. 2006;310: 15–24.
  47. 47. Peterson MS, Lowe MR. Implications of cumulative impacts to estuarine and marine habitat quality for fish and invertebrate resources. Reviews in Fisheries Science. 2009;17: 505–523.
  48. 48. Partyka ML, Peterson MS. Habitat Quality and Salt-Marsh Species Assemblages along an Anthropogenic Estuarine Landscape. Journal of Coastal Research. 2008;246: 1570–1581.
  49. 49. Layman CA, Quattrochi JP, Peyer CM, Allgeier JE. Niche width collapse in a resilient top predator following ecosystem fragmentation. Ecol Lett. 2007;10: 937–944. pmid:17845294
  50. 50. Rudershausen PJ, Merrell JH, Buckel JA. Fragmentation of habitat affects communities and movement of nekton in salt marsh tidal creeks. Mar Ecol Prog Ser. 2018;586: 57–72.
  51. 51. Anderson TK, Sukhdeo MVK. The worm’s eye view of community ecology. A Century of Parasitology: Discoveries, ideas and lessons learned by scientists who published in the Journal of Parastiology, 1914–2014. Chichester, UK: John Wiley & Sons, Ltd; 2016. pp. 110–130. https://doi.org/10.1002/9781118884799.ch8
  52. 52. Mooring MS. Animal Grouping for Protection from Parasites: Selfish Herd and Encounter-Dilution Effects. Behaviour. 1992;123: 173–193.
  53. 53. Sousa WP. Spatial scale and the processes structuring a guild of larval trematode parasites. In: Esch GW, Bush AO, Aho JM, editors. Parasite communities: patterns and processes. Dordrecht: Springer Netherlands; 1989. pp. 41–67. https://doi.org/10.1007/978-94-009-0837-6_3
  54. 54. Byers JE, Malek AJ, Quevillon LE, Altman I, Keogh CL. Opposing selective pressures decouple pattern and process of parasitic infection over small spatial scale. Oikos. 2015;124: 1511–1519.
  55. 55. Kuris AM, Blaustein AR, Alio JJ. Hosts as Islands. Am Nat. 1980;116: 570–586.
  56. 56. MacArthur RH, Wilson EO. An equilibrium theory of insular zoogeography. Evolution. 1963;17: 373–387.
  57. 57. Guégan J-F, Lambert A, Lévêque C, Combes C, Euzet L. Can host body size explain the parasite species richness in tropical freshwater fishes? Oecologia. 1992;90: 197–204. pmid:28313714
  58. 58. Morand S, Poulin R. Density, body mass and parasite species richness of terrestrial mammals. Evolutionary Ecology. 1998;12: 717–727.
  59. 59. Blanar CA, Munkittrick KR, Houlahan J, Maclatchy DL, Marcogliese DJ. Pollution and parasitism in aquatic animals: a meta-analysis of effect size. Aquat Toxicol. 2009;93: 18–28. pmid:19349083