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Life History Cost of Trematode Infection in Helisoma Anceps Using Mark–Recapture in Charlie's Pond

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Life History Cost of Trematode Infection in Helisoma Anceps Using Mark–Recapture in Charlie's Pond J. Parasitol., 94(2), 2008, pp. 314–325 ᭧ American Society of Parasitologists 2008 LIFE HISTORY COST OF TREMATODE INFECTION IN HELISOMA ANCEPS USING MARK–RECAPTURE IN CHARLIE’S POND N. J. Negovetich* and G. W. Esch Department of Biology, Wake Forest University, Winston-Salem, North Carolina 27109. e-mail: [email protected] ABSTRACT: Parasitism has the potential to affect key life history traits of an infected host. Perhaps the most studied interactions are in snail–trematode systems, where infection can result in altered growth rates, survival, and/or fecundity of the individual. Positive correlations between host size and parasite prevalence are often attributed to changes in growth rates or mortality, which have been observed in the laboratory. Extending lab-based conclusions to the natural setting is problematic, especially when environmental conditions differ between the laboratory and the field. The present study uses reproduction experiments and mark– recapture methods to directly measure key life history traits of the pulmonate snail Helisoma anceps in Charlie’s Pond. Based on previous laboratory and field experiments on H. anceps, we predict a significant reduction in fecundity, but not growth rate or survival, of infected snails. Individual capture histories were analyzed with multistate models to obtain estimates of survival and infection probabilities throughout the year. Recaptured individuals were used to calculate specific growth rates. Trematode infection resulted in complete castration of the host. However, neither survival nor growth rates were found to differ between infected and uninfected individuals. The probability of infection exhibited seasonal variation, but it did not vary with size of the snail. These results suggest that the correlation between host size and trematode prevalence is not due to differential mortality or changes in growth rates. Instead, the infection accumulates in large snails via the growth of smaller, infected individuals. Trematode larvae commonly castrate their molluscan hosts. been observed from infections by both sporocysts (Makanga, The mechanism of castration depends on the specific larval 1981; Minchella and Loverde, 1981; Zakikhani and Rau, 1999) stage infecting the host. For example, rediae mechanically cas- and rediae (Dreyfuss et al., 1999; Sandland and Minchella, trate the host by consuming host tissue, including the high- 2003). Physical damage caused by the parasite during feeding energy fat of the gonads. Sporocysts, lacking a mouth and phar- and cercariae release, and the energetic cost of an immune re- ynx, likely castrate the host via chemical inhibition. In partic- sponse may contribute to, if not cause, the increase in mortality. ular, Trichobilharzia ocellata stimulates the release of schisto- Reinfection by cercariae has also been implicated in decreasing somin, which inhibits oviposition by Lymnaea stagnalis (De survival of the snail host (Kuris and Warren, 1980; Sandland Jong-Brink, 1995). Castration could be complete, as in the Hel- and Minchella, 2003). isoma anceps–Halipegus occidualis system (Crews and Esch, The difficulties in estimating the true cost of parasitism arise 1986), or partial, as in the mudsnail Hydrobia ventrosa (Kube when extending the results derived from laboratory experiments et al., 2006). The individual cost of castration includes the loss to observations in the field. For example, lab-reared Lymnaea elo- of future reproduction. Fecundity compensation has been pro- des grew faster and laid more eggs than snails raised in the field posed as a mechanism by which the host could potentially off- (Eisenberg, 1966, 1970). If food was supplied in the field, then set this negative effect (Minchella, 1985; Sorensen and Min- both growth and fecundity increased. Likewise, H. anceps in Char- chella, 1998). Compensation has been recorded in the T. ocel- lie’s Pond are protein deprived, and they exhibit lower fecundity lata–L. stagnalis, Schistosoma mansoni–Biomphalaria glabra- and growth rates than snails raised in the laboratory (Keas and ta, and S. mansoni–Biomphalaria pfeifferi systems (Sorensen Esch, 1997). To accurately assess the impact of parasitism, studies and Minchella, 2001), and it occurs by increasing reproductive should be performed under natural field conditions. effort, i.e., oviposition or maturation, before castration. Mark–recapture sampling protocols provide the data required Many researchers have noted a positive correlation between to estimate survival in the field. Moreover, recent advances prevalence of infection and size of the snail host. This has led have expanded the scope of analysis, such that simple estimates some to question whether growth schedules vary between in- of survival and population size are becoming secondary to more fected and uninfected hosts (Baudoin, 1975; Fernandez and complex questions. One advance is the development of multi- Esch, 1991a; Sorensen and Minchella, 2001). Common re- state models, which permit the estimation of transition proba- sponses to infection include gigantism (ϭthe rapid increase in bilities between states (Hestbeck et al., 1991; Lebreton et al., size after infection) and stunting. The growth response by a 1992; Brownie et al., 1993; Nichols et al., 1994; Nichols and snail may depend on when it was infected. For example, if Kaiser, 1999; Lebreton and Pradel, 2002; White et al., 2006). infected before reproductive maturity, B. glabrata experiences For example, many researchers have used multistate models to rapid growth until maturity, and then it grows less rapidly than estimate the cost of breeding on survival rates (White et al., uninfected individuals (Gerard and Theron, 1997). 2006), whereas others have calculated dispersal rates between Recently, trematode infections have been shown to increase various habitats (Hestbeck et al., 1991). Application of mark– mortality of the snail host. Negative effects on survival have recapture protocols to snail populations has been limited to a few studies (O’Keeffe, 1985; Woolhouse, 1988; Goater et al., 1989; Woolhouse and Chandiwana, 1990; Fernandez and Esch, Received 19 March 2007; revised 7 August 2007; accepted 8 August 2007. 1991a; Chlyeh et al., 2002, 2003). One reason for the lack of * Present address: St. Jude Children’s Research Hospital, Infectious Dis- interest may be the low recapture rate of aquatic snails, as a ease, 332 N. Lauderdale Street, MS #330, Memphis, Tennessee 38105. consequence of their vagility. In Charlie’s Pond, 97% of H. 314 NEGOVETICH AND ESCH—COST OF INFECTION IN A SNAIL HOST 315 anceps were collected within 1 m of the original release site class. Analysis of variance was performed in JMP 4.0.4 (SAS Institute, (Fernandez and Esch, 1991b), compared with the 28% of Physa Cary, North Carolina). If the variances of SGRs were not equal, then a Kruskal–Wallis (KW) test was performed. gyrina that moved more than 1.5 m away from the site of re- The mark–recapture protocol resulted in individual capture histories lease in just 2 wk (Snyder and Esch, 1993). Because of its low that span the entire collecting period. The capture histories consisted of vagility, H. anceps is a suitable candidate for an extensive an informational series of 0, A, and B. Each value holds unique infor- mark–recapture study to measure both growth rates and surviv- mation. Zero indicates that the snail was not captured during a specific al in the field. capture attempt. The letters indicate that the snail was captured and uninfected (A), or captured and infected (B). Although 11 trematode The goal of the present study was to determine how trema- species were identified in 2006 alone, the prevalence, and thus sample tode infections affect the life history traits of H. anceps as mea- size, for most of these infections was too small to adequately estimate sured in a natural setting. The traits being investigated include their effect on survival. Therefore, trematode infections were pooled survival, fecundity, and growth rates. Mark–recapture methods into a single infection category. Capture histories grouped by size at initial capture were analyzed with multistate models in Program MARK were used, and the capture histories were then analyzed using ⌽ ␳ (White and Burnham, 1999). The general model tested was s·i·t s·t multistate models. Based on field (Fernandez and Esch, 1991a) ⌿ ⌽ ⌿ s·i·t. In this model, survival ( ) and infection ( ) probabilities vary as and laboratory estimates (Keas and Esch, 1997), we hypothe- a function of site (s), time (t), and infection status (i). We have no reason size that infection will not alter the observed growth rates or to suspect that infection status affects recapture probability (␳); thus, ␳ survival probabilities of H. anceps. This investigation will also the general model allows to vary only with s and t. Akaike’s infor- mation criterion (AIC) was used for model selection and ranking (An- produce estimates for the probability of infection, which is pre- derson and Burnham, 1999a, 1999b). Parametric bootstrap procedures dicted to vary seasonally. were used to estimate cˆ, which is a measure of lack-of-fit (Cooch and White, 2006). This method produced simulated capture histories using MATERIALS AND METHODS parameter estimates from the general model. These capture histories were then used to obtain simulated parameter estimates, including de- Helisoma anceps were collected from 2 sites in Charlie’s Pond, viance of the model. A new set of capture histories was created for each Stokes County, North Carolina. Charlie’s Pond is approximately 1 ha, iteration. One thousand iterations were performed for each size class, and it has been described previously (Crews and Esch, 1986; Esch et and the model deviances were saved. The deviance from the general al., 1997). Beginning in May 2005, snails were collected by random model was divided by the mean deviance from the simulated models to sampling with a dip net for 1 hr each week. Weekly collecting sites obtain cˆ (Cooch and White, 2006). AIC was divided by cˆ to obtain a alternated between the northwest cove (NW) and east side (ES) of Char- quasi-likelihood adjust AIC (QAIC), which corrects for excess variation lie’s Pond.
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