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  1. 1. 69The parasite Lernaeocera branchialis on caged cod :infection pattern is caused by differences in hostsusceptibilityD. A. L Y S N E "* and A. S K O R P I N G #" Finnmark University College, Follumsvei 31, N-9509 Alta, Norway# Department of Zoology, University of Bergen, Realfagbygget, AlleT gaten 41, 5007 Bergen, Norway(Received 23 January 2001 ; revised 5 May 2001 and 1 August 2001 ; accepted 1 August 2001)Variation in host susceptibility causes significant differences in infection rates between hosts living in a semi-naturalsituation. Such knowledge has implications for population dynamics and evolutionary models of host–parasite interactionsas well as for estimations of parasite abundance. Infection rates by Lernaeocera branchialis (L.) were measured throughtime and space on caged Atlantic cod (Gadus morhua L.). One group of hosts, identified by their infection history,developed significantly higher infection rates than the others. These were fish which had been infected previously, but hadlost their infection. Differences between groups were consistent through both time and space. Two types of cod seem tohave been present in the caged population ; a small group of inherently susceptible fish, which were infected, and reinfectedif the parasite was lost, and another group of resistant hosts with a small chance of becoming infected.Key words : Atlantic cod, Gadus morhua, Lernaeocera branchialis, susceptibility. studies where the effect of heterogeneities in ex- posure rate to infective stages can be separated fromMost macroparasites show a non-random distri- heterogeneities in host susceptibility. As pointed outbution across their host population (Shaw, Grenfell by Clayton, Pruett-Jones & Lande (1992), a major& Dobson, 1998). The level of parasite aggregation shortcoming in many studies has been that workershas consequences for population regulation have been using variation in parasite numbers as a(Anderson & May, 1978 ; May & Anderson, 1978), as measure of variation in susceptibility. Experimentalwell as for epidemiological studies since, at in- studies in the laboratory, where individuals arecreasing levels of aggregation, a larger number of exposed to a known number of infective stages, havehosts must be sampled in order to estimate parasite repeatedly shown that host susceptibility variesabundance. Furthermore, several evolutionary between individuals (Chevassus & Dorson, 1990 ;models hypothesize that parasites can be important Bakke et al. 1992 ; Wakelin, 1994). These are notselective agents on their hosts (Barbehenn, 1969 ; easily extrapolated to natural situations becauseHamilton & Zuk, 1982 ; Freeland, 1983 ; Hamilton, exposure rates may differ widely from those in theAxelrod & Tanese, 1990). A necessary requirement field (Quinnell & Keymer, 1990), and also becausefor such parasite-mediated selection is that the trait host susceptibility may be affected by conditions into be selected must covary with parasite numbers the laboratory (Lloyd, 1995). An alternative is to run(Goater & Holmes, 1997 ; Skorping, 1998). For field experiments where hosts can be exposed toexample, in the hypothesis proposed by Hamilton & naturally occurring transmission stages under en-Zuk (1982) on sexual selection, it is assumed that vironmental conditions more similar to those ex-differences in male heritable susceptibility will be perienced in the wild. By using ectoparasites onreflected in the distribution of parasites. The im- individually marked hosts, it should be possible toportance of parasites as selective agents is likely to compare infection rates between host individuals,increase when parasite distribution becomes less and examine if differences in rates are consistentaggregated because more hosts harbour a higher through time.number of parasites. This paper describes fluctuations in the population In order to understand why wild-living parasites of Lernaeocera branchialis (L.) on caged cod (Gadusaggregate within their host populations we need morhua L.) for 598 days. L. branchialis uses mainly different species of flatfish as intermediate hosts (Kabata, 1979), but can also develop on other fish* Corresponding author : Finnmark University College,N-9509 Alta, Norway, Tel : j 47 78 45 03 56. Fax : j47 species (Lester & Roubal, 1995). After mating, the78 43 44 38. E-mail : daga!hifm.no pregnant female has a short free-living periodParasitology (2002), 124, 69–76. " 2002 Cambridge University PressDOI : 10.1017S0031182001008848 Printed in the United Kingdom
  2. 2. D. A. Lysne and A. Skorping 70Fig. 1. Chart of Kvalfjorden with cage locations marked by dots. Four net bags were placed in cage A, while cages Band C had 1 net bag each.searching for the definitive host, a gadoid fish. If   successful, she will settle at the base of the gill archeson the ventral side, and undergo a metamorphosis Six hundred cod were caught by floating trawl off thewhere the head penetrates into the heart region of the coast of Finnmark County, Norway, and caged infish (Grabda, 1991). The parasite is known to Kvalfjorden (70m 42h N and 23m 48h E). The fish wereinfluence both growth and level of liver fat, and may allowed to recover from capture and acclimatized forbe lethal, especially to young fish (Khan, Lee & 2 weeks while fed several times a day with artificialBarker, 1990). The parasite may live up to 18 months food. Thereafter, the fish were caged in 6 net bags(Lester & Roubal, 1995) and can not move between (height 4 m, volume 40 m$ each) at 3 differenthosts. locations in the fjord. One hundred cod were placed In the present study a field experimental approach in each of 4 net bags in cage A (see Fig. 1). Thesewas used to address the following question. Do were all free from infection by L. branchialis, with 3infection rates vary between hosts due to inherent accidental exceptions. The depth at low tide was 8 mdifferences in susceptibility? Exposure can be at this cage. This paper is part of a larger study, andassumed to be random within each of the host fish from another 2 cages, which were placed in thelocations used in this experimental set-up. If then study area for other reasons (labelled B and C in Fig.the pattern of infection is caused mainly by factors 1), were also included in the present data. At cagingunrelated to host susceptibility, infection rates 100 cod were placed at random, with respect toshould show random variations between host indi- infection, in one net bag in each of cage B and Cviduals. (Table 1). The cages were placed 200 m and 50 m
  3. 3. Variation in susceptibility to L. branchialis 71 Table 1. Infection levels of Lernaeocera branchialis on the caged cod at the start of the experiment are given separately for the 3 cages in the experiment together with the mean and range of both body mass and length of the fish at caging, as well as increase in body mass and length through the study period (Cage-labelling refers to Fig. 1) Cage A Cage B Cage C Infection Abundance 0n01 0n85 0n71 Prevalence 1n1 % 38n5 % 40n9 % Mass (g) Mean 1876n4 1855n2 2013n2 Range 1025n0–2905n0 1110n0–2525n0 1110n0–4300n0 Increase, mean 2454n6 2408n6 2248n7 Increase, range 410n0–4170n0 705n0–4490n0 310n0–5070n0 Length (cm) Mean 60n6 60n5 61n2 Range 47n5–71n0 48n0–66n0 50n0–79n5 Increase, mean 10n6 10n3 9n5 Increase, range 3n5–21n0 2n0–18n5 1n0–20n5from the shore respectively. Depths at low tide were (i) included fish where numbers of parasites in-31n5 m at cage B and 18n5 m at cage C. In the fjord creased during a time-period, and group (ii) includedthe average water level change is 1n8 m (Statens fish where numbers of parasites did not increase.Kartverk, 2001) between high to low tide. Strong The data were used in a logistic regression modeltidal currents, which are especially pronounced close with binomial errors in Glim4 (Crawley, 1993).to the shores (Fig. 1), continuously replaced the Groups of cod, identified by infection history, werewater within the cages. tested for differences in age distributions using Before the separation into different cages fish were contingency tables (GLM with Poisson errors andinspected for L. branchialis, and length and mass log link function). The variables were included in thewere recorded (Table 1). All fish were also in- models in a forward stepwise manner. Significancedividually tagged with external anchor tags (T-tags). of effects in the models were tested by comparing theBefore handling, each fish was anaesthetized in change in deviance by the removal of a term from the0n15 % chlorobutanol (C H Cl O). During the ex- model with the values of Chi-square tables in % ( $perimental period the fish were anaesthetized, L. accordance with Crawley (1993).branchialis counted and length and mass recorded 6times ; on days 0, 74, 327, 431, 522 and 598 after caging. The large gap in collection times between thesecond and third sample was caused by bad weather A total of 495 cod survived the experimental period.conditions which made it impossible to transport the Of the survivors, 339 fish could be identifiedfish between the cages and the location where they throughout the study, while the remaining indi-were anaesthetized and inspected. On day 598 all viduals had lost their tags and were subsequently re-surviving fish were killed and sexed. The otoliths tagged. Of the 339 cod, which were identifiedwere removed for age determination. During the throughout the study, 79 % remained uninfected,experiment cod were fed cuttings from the codfillet while the rest of the fish harboured the parasite atindustry and herring meal mixed with commercial one or more sampling points. During the studyfish food (‘ Salmomix 45 % ’). Food was added to the period there was a decline in numbers of hostscages twice a week, and what was not eaten, sank out harbouring more than 1 L. branchialis (Fig. 2 ; χ# lof the cage within a period of less than 30 sec. 9n29 ; P l 0n0023 at 1 ..). The death of 22 fish was Only fish which survived longer than day 327, caused by predation by the otter, Lutra lutra, whichwere included in the analyses. All statistical tests in most cases made the fish impossible to inspect forwere run using generalized linear models (GLMs) in parasites. These killings took place during the darkthe Glim4 computer package (Crawley, 1993). period each year, between late November and earlyChanges in frequency distribution of parasites February. The otter entered the cages through self-through time were tested using a contingency table made holes in the net. However, among the dead fish(Poisson errors and log link function). Changes in which could be inspected, intensity and prevalencerates of infection were treated as binary data : group were within the levels measured among the survivors
  4. 4. D. A. Lysne and A. Skorping 72 40 30Number of fish 20 10 0 0 74 327 431 522 598 June August April August November January 1993 1993 1994 1994 1994 1995 Days after caging and month and year of samplingFig. 2. Numbers of cod harbouring different numbers of Lernaeocera branchialis during the period of caging. Onlyfish which appeared in all samples (n l 339) were included. Number of L. branchialis per fish 1; 2; 3; 8 4;: 5 ; 5 6.Fig. 3. Infection rates, with standard errors, by Lernaeocera branchialis for fish which were free from infection at thestart of a time-period (open columns), compared to rates for fish which harboured the parasite (filled columns). ‘ 0 ’ lNo fish acquired new infections.(intensity l 1.78, prevalence l 0n36, n l 22). Data the changes in infection rates were not apparent fromon the surviving fish therefore seem not to have been the analyses. Inclusion of a second order and thirdbiased by parasite-related deaths. order parameter of the ‘ time ’ variable did not exert The rate at which L. branchialis established within significant influence on infection rates (χ# l 0n30 ; Pthe caged population was high during the first time l 0n58 at 1 ., and χ# l 2n56 ; P l 0n11 at 1 ..,period (Fig. 3), but then dropped to a lower level ( χ# respectively).l 50n5 ; P 0n001 at 1. ..). Seasonal fluctuations in Infection rates were compared between groups of
  5. 5. Variation in susceptibility to L. branchialis 73 Table 2. The influence of infection history and location on infection rates of Lernaeocera branchialis on cod during successive time-periods (‘ Infection history ’ identifies 2 groups among the cod. Fish which were un- infected at the start of the time-period are compared to fish which harboured the parasite (see also Fig. 3). ‘ Location ’ refers to the 3 locations in the fjord where the cod were caged. In the analysis ‘ infection rate ’ was treated as a binary response variable, and included in models (GLMs) with binomial errors.) Inf. history Location Inf. history i Days after caging (.. l 1) (.. l 2) loc. (.. l 2) 0–74 χ# l 1n93 χ# l 4n94 χ# l 0n31 P l 0n16 P l 0n09 P l 0n86 74–327 χ# l 1n37 χ# l 2n44 χ# l 0n38 P l 0n24 P l 0n30 P l 0n83 327–431 χ# l 0n28 χ# l 0n92 χ# l 0n002 P l 0n60 P l 0n63 P l 0n999 431–522 χ# l 1n76 χ# l 1n64 χ# l 0n001 P l 0n19 P l 0n44 P l 0n999 522–598 χ# l 0n13 χ# l 0n30 χ# l 3n099 P l 0n72 P l 0n86 P l 0n21Fig. 4. Infection rates, with standard errors, by Lernaeocera branchialis for 2 subgroups of the fish classified as‘ uninfected ’ in Fig. 3. Fish which had lost the infection, and therefore were free from the parasite at the start of thetime-period (open columns), are compared to fish which were not recorded as infected prior to the start of the time-period (filled columns). ‘ 0 ’ l No fish acquired new infections.cod identified by their infection history. Rates did of the 4 time-periods, these cod were more likely tonot differ between fish which were uninfected at the be infected than the cod which had never harbouredstart of a time-period, compared to infected fish (Fig. the parasite at any of the previous sampling points3). This was shown statistically by the lack of (the statistics are given in Table 3). In the seconddifference within all of the 5 time-periods which interval in Fig. 4, where infection rate is zero in thewere compared (the statistics are given in Table 2). group of previously infected cod, only 11 of theHowever, 1 subgroup among the uninfected fish individuals which were free from infection after 327showed significantly higher rates of infection than days in the cage, had been recorded as infectedthe others. These were the fish which had been earlier in the study. None of these were recorded asinfected, but had lost their infection prior to the start infected after 431 days in the cage. Furthermore,of the time-period under investigation (Fig. 4). This when compared to the group of cod which harbouredloss of infection was identified among individuals the parasite at the start of a time-period, the group ofwhich had harboured the parasite at one or more of cod which had lost all their parasites, showedthe previous samplings but were free from infection significantly higher infection rates in 2 of the 4 time-at the start of the time-period in question. Within 3 periods (the statistics are given in Table 4). This
  6. 6. D. A. Lysne and A. Skorping 74 Table 3. Fish which had been infected by Lernaeocera branchialis, but had lost their infection prior to the start of the time-period, are compared to fish which were not recorded as infected (see Fig. 4) (These are subgroups of the ‘ uninfected ’ fish in Fig. 3. In the analyses ‘ infection rate ’ was treated as a binary response variable, and included in models (GLMs) with binomial errors.) Inf. history Location Inf. history Days after caging (.. l 1) (.. l 2) i location 74–327 χ# l 7n92 χ# l 2n14 χ# l 3n06 P l 0n005 P l 0n34 P l 0n08 (1 ..) 327–431 χ# l 0n11 χ# l 0n61 χ# l 0n0002 P l 0n74 P l 0n74 P l 0n999 (2 ..) 431–522 χ# l 13n60 χ# l 3n58 χ# l 0n24 P l 0n001 P l 0n17 P l 0n89 (2 ..) 522–598 χ# l 7n03 χ# l 1n66 χ# l 0n118 P l 0n008 P l 0n44 P l 0n94 (2 ..) Table 4. Fish which had been infected by Lernaeocera branchialis previous to the time-period in question, but had lost the infection (a subgroup of the ‘ uninfected ’ in Fig. 3), are compared to fish which harboured the parasite at the start of the period (the ‘ infected ’ fish in Fig. 3) (In the analyses ‘ infection rate ’ was treated as a binary response variable, and included in models (GLMs) with binomial errors.) Inf. history Location Inf. history Days after caging (.. l 1) (.. l 2) i location 74–327 χ# l 7n31 χ# l 4n64 χ# l 0n0008 P l 0n007 P l 0n10 P l 0n977 (1 ..) 327–431 χ# l 0n21 – – P l 0n65 – – 431–522 χ# l 10n68 χ# l 3n22 χ# l 0n001 P l 0n001 P l 0n20 P l 0n999 (2 ..) 522–598 χ# l 2n41 χ# l 0n34 χ# l 2n82 P l 0n12 P l 0n84 P l 0n24 (2 ..)pattern may have been caused by age-related as uninfected. This difference was consistent throughdifferences in infection rates. If so, age of the fish time and between locations. With respect to infectionshould differ between groups identified by infective rates, 2 types of cod therefore appear to have beenhistory. This was not found to be the case within any present in the caged population ; one large groupof the time-periods (χ# 8n57 ; P 0n29 at 7 ..). with a relatively small chance of becoming infected Differences in infection rates between individuals and another smaller group with a much higher risk ofdid not depend on which location the fish were acquiring the parasite. The strong water currents inplaced in. This appeared from the fact that ‘ location ’ the caging area, which caused continuously re-neither affected infection rate (Tables 2, 3 and 4), placement of the water within the cages, shouldnor influenced the effect of ‘ infection history ’ within produce random variation in exposure to infectiveany of the time-periods (non-significant effects of the stages among fish within each cage. Furthermore,‘ infection historyilocation ’ interactions ; Tables 2, during the experimental period there were no3 and 4). significant differences in infection rates between the cages. Therefore, the differences in rates between the 2 groups of cod, could not have been caused by differences in the rate of exposure, but must haveIn this study, infection rates did not vary randomly been related to phenotypic differences.between individual cod. Fish which had been An alternative explanation would be that theinfected previously with L. branchialis and had lost smaller group of hosts may have differed in theirthe infection, had a significantly higher rate of behaviour in a way that made them more frequentlyinfection than cod which previously were recorded exposed to transmission stages, for example, by
  7. 7. Variation in susceptibility to L. branchialis 75occupying the bottom of the net bags. Poulin, Rau Susceptibility can appear as a gradient from highlyCurtis (1991) showed that variation in behaviour susceptible to resistant hosts. This view does notinfluenced infection rates among laboratory reared change the argument that infection rates decreasedbrook trout fry (Salvelinus fontinalis) infected by the through time due to declining probability of encoun-crustacean ectoparasite Salmincola edwardsii. How- tering susceptible hosts because the highly sus-ever, if host behaviour were an important factor in ceptible individuals were infected during the firstthe present study the frequently exposed hosts part of the study and moved into the infected classshould show high levels of infection rates throughout with a low probability of reinfection.the study period, independent of their previous Other explanations for the observed decrease ininfection status. This was not observed. infection rate with time are possible, but less likely. The assumption that the caged cod population A decrease in rates of infection with time could beinitially consisted of a small group of inherently caused by stress during the caging process, whichsusceptible fish among a larger group of resistant may increase initial susceptibility to parasites (Lloyd,ones, would explain both the decrease in the infection 1995). However, fish seem to acclimatize to cagesrates within the whole group of cod, and the over a short time. Pickering (1987) argued thatfluctuating rate of infection among the fish which within 3 weeks most individuals of several species dohad carried the parasite earlier, but lost it. The not show signs of immune suppression. Seasonal orinfection rate within the whole group should decline annual changes in densities of transmission stagesbecause the number of susceptibles rapidly became may cause a decrease in rate of infection throughinfected and moved into the infected class with a low time. If densities decreased through the first autumnprobability of reinfection. Since this parasite may and winter, the rates of infection should havelive for 18 months (Lester Roubal, 1995), few of increased again over the second summer (from Aprilthese fish had lost their infection after 327 days in the to early November which would be from 327 to 522cage. This may explain the lack of new infections days in the cage). This did not happen. Neither is itamong the group of susceptibles during the second likely that annual fluctuations in densities of trans-time-interval. mission stages caused the observed pattern, because Are cod with a previous record of carrying the changes in rates of infection with time differedparasite more vulnerable to reinfection due to between groups of cod. For example, infection ratesparasite-induced increase in susceptibility ? Such increased in the group of infected cod between thepatterns were observed in the laboratory on juvenile second-to-last and the last time-period. At the samesticklebacks (Gasterosteidae) infected by the crus- time the group of cod which had lost their infection,tacean ectoparasite Argulus canadensis (Wilson, 1916 ; showed a 40 % decrease in infection rates. It isPoulin FitzGerald, 1989), and on brook trout therefore reasonable to conclude that the decrease infry infected by another crustacean ectoparasite S. infection rates with time was caused by a decliningedwardsii (Poulin et al. 1991). However, the present number of susceptible hosts.data seem not to fit this explanation. L. branchialis Are the present results comparable to the wilddid not induce higher infection rates among the fish situation ? It is not likely that factors tied to theharbouring the parasite, because the number of fish caging situation, for example stress, would affect acarrying more than 1 parasite did not increase with fraction of the caged cod, i.e. the susceptible fishtime, and fish infected by the parasite at the start of identified by their infection history, more seriouslya given time-period did not show higher infection than the rest of the population. However, therates than uninfected hosts. A supposed increase in availability of food may be more uniformly distri-susceptibility due to earlier infection may also take buted, and for part of the year more abundant,effect only after the fish have lost the infection. between caged individuals than experienced by wild-However, if parasite-induced facilitation of re- living fish. As a consequence, differences in hostinfection were the most important factor causing resistance caused by fluctuation in nutritional re-changes in infection rates, we would expect rates to source may be more pronounced among wild-livingbe low at the start of the study period, and thereafter hosts. The frequent availability of high quality foodincrease as parasites died and numbers of previously may explain why the numbers of multi-infectedinfected fish increased through time. This was not hosts decreased throughout the study period.observed. Since this is a relatively pathogenic parasite (Khan, The argument that the caged cod initially con- 1988 ; Khan et al. 1990), cod that are able to avoid itsisted of a small group of inherently susceptible fish should have a fitness advantage relative to theamong a larger group of resistant ones, depends on susceptible group. Why then, does resistance notthe assumption that the observed temporal variations spread to the whole cod population ? We suggest 2in infection rate are caused by changes in availability possible mechanisms that may maintain such poly-of susceptibles. The distribution of the cod popu- morphism in susceptibility.lation in 2 distinct groups, susceptible or resistant Given that parasites show virulence specific tohosts, may, however, not be a realistic model. genotypes, Hamilton (1980) hypothesized that be-
  8. 8. D. A. Lysne and A. Skorping 76cause of frequency-dependent selection, parasites , . (1991). Marine Fish Parasitology. Polishmay generate cyclical processes where the fre- Scientific Publishers.quencies of host genotypes are changing with time. , . . (1980). Sex versus non-sex versus Susceptibility to L. branchialis may also be parasite. Oikos 35, 282–290.maintained if resistance is costly and therefore affects , . ., , .  , . (1990). Sexual reproduction as an adaptation to resistsome other factors related to fitness. Life-history parasites (a review). Proceedings of the Nationaltheory suggests that hosts may increase their fitness Academy of Sciences, USA 87, 3566–3573.by suppressing responses against parasites, in order , . .  , . (1982). Heritable true fitnessto restrict the operation of the immune system for and bright birds : A role for parasites? Science 218,frequently occurring and pathogenic parasites 384–386.(Behnke, Barnard Wakelin, 1992). , . (1979). Parasitic Copepoda of British fishes. The present data show that variation between The Ray Society, London.individuals in rates of infection was consistent , . . (1988). Experimental transmission,through time and space when living in environments development, and effects of a parasitic copepod,similar to the natural one. We conclude that this Lernaeocera branchialis, on Atlantic cod, Gaduspattern was caused by inherent differences in host morhua. Journal of Parasitology 74, 586–599.susceptibility. , . ., , . .  , . (1990). Lernaeocera branchialis : a potential pathogen to cod ranching. Journal of Parasitology 76, 913–917.We thank the staff at Finnmark Research Centre for their , . . .  , . . (1995). Phylumcooperation, Ellen Andersen and Sissel Kaino for technical Arthropoda. In Fish Diseases and Disorders. Vol. I.assistance. We also acknowledge Peter Hudson for con-structive comments and discussions, and for improving Protozoan and Metazoan Infections (ed. Woo,the English. This study was financially supported by the P. T. K.), pp. 475–598. CAB International,Norwegian Research Council. Wallingford, UK. , . (1995). Environmental influences on host immunity. In Ecology of Infectious Diseases in Natural Populations (ed. Grenfell, B. T. Dobson, A. P.), pp. 327–361. Cambridge University Press, Cambridge., . .  , . . (1978). Regulation and , . .  , . . (1978). Regulation and stability of host–parasite population interactions. stability of host-parasite population interactions. II. I. Regulatory Processes. Journal of Animal Ecology 47, Destabilizing processes. Journal of Animal Ecology 47, 219–247. 249–267., . ., , . ., , . .  , . . , . . (1987). Stress responses and disease (1992). Host specificity and dispersal strategy in resistance in farmed fish. Aqua Nor 87, 35–49. gyrodactylid monogeneans, with particular reference , .  , . . (1989). A possible to Gyrodactylus salaris (Platyhelminthes, Monogenea). explanation for the aggregated distribution of Argulus Diseases of Aquatic Organisms 13, 63–74. canadensis Wilson, 1916 (Crustacea : Branchiura) on, . . (1969). Host–parasite relationships and juvenile sticklebacks (Gasterosteidae). Journal of species diversity in mammals : an hypothesis. Parasitology 75, 58–60. Biotropica 1, 29–35. , ., , . .  , . . (1991). Infection, . ., , . .  , . (1992). of brook trout fry, Salvelinus fontinalis, by Understanding chronic namatode infections : ectoparasitic copepods : the role of host behaviour and Evolutionary considerations, current hypotheses and initial parasite load. Animal Behaviour 41, 467–476. the way forward. International Journal for Parasitology , . .  , . . (1990). Acquired 22, 861–907. immunity and epidemiology. In Parasites : Immunity, .  , . (1990). Genetics of and Pathology. The Consequences of Parasitic Infection resistance to disease in fishes. Aquaculture 85, 83–107. in Mammals (ed. Behnke, J. M.), pp. 317–343. Taylor, . ., -, . .  , . (1992). and Francis Ltd, London. Reappraisal of the interspecific prediction of parasite- , . ., , . .  , . . (1998). mediated sexual selection : opportunity knocks. Patterns of macroparasite aggregation in wildlife host Journal of Theoretical Biology 157, 95–108. populations. Parasitology 117, 597–610., . . (1993). Methods in Ecology, Glim for , . (1998). Macroparasites as selective agents Ecologists. Blackwell Science Ltd, Oxford. in birds. Bulletin of the Scandinavian Society for, . . (1983). Parasites and the coexistence of Parasitology 8, 33–38. animal host species. American Naturalist 121,  ,  (2001). 223–236. Tidevannstabeller for den norske kyst med Svalbard, . .  , . . (1997). Parasite-mediated samt. Dover, England. natural selection. In Host–Parasite Evolution. General , . (1994). Host populations : Genetics and Principles and Avian Models (ed. Clayton, D. H. immunity. In Parasitic and Infectious Diseases, Moore, J.), pp. 9–29. Oxford University Press, Epidemiology and Ecology (ed. Scott, M. E. Smith, Oxford. G.), pp. 83–100. Academic Press, London.