Browse Subject Areas

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here.

  • Loading metrics

The Relationship between Parasite Fitness and Host Condition in an Insect - Virus System

The Relationship between Parasite Fitness and Host Condition in an Insect - Virus System

  • Michelle Tseng, 
  • Judith H. Myers


Research in host-parasite evolutionary ecology has demonstrated that environmental variation plays a large role in mediating the outcome of parasite infection. For example, crowding or low food availability can reduce host condition and make them more vulnerable to parasite infection. This observation that poor-condition hosts often suffer more from parasite infection compared to healthy hosts has led to the assumption that parasite productivity is higher in poor-condition hosts. However, the ubiquity of this negative relationship between host condition and parasite fitness is unknown. Moreover, examining the effect of environmental variation on parasite fitness has been largely overlooked in the host-parasite literature. Here we investigate the relationship between parasite fitness and host condition by using a laboratory experiment with the cabbage looper Trichoplusia ni and its viral pathogen, AcMNPV, and by surveying published host-parasite literature. Our experiments demonstrated that virus productivity was positively correlated with host food availability and the literature survey revealed both positive and negative relationships between host condition and parasite fitness. Together these data demonstrate that contrary to previous assumptions, parasite fitness can be positively or negatively correlated with host fitness. We discuss the significance of these findings for host-parasite population biology.


Parasites play a significant role in the ecology and evolution of their hosts. For example, parasites can regulate host population dynamics [1][3], drive the maintenance of host sexual reproduction [4][6], and shape the evolution of sexually dimorphic traits [7]. Environmental variation can play a large role in mediating the immediate outcome of parasite infection, as hosts that are reared in crowded conditions or with limited food can suffer greater morbidity or mortality from parasitism compared to hosts in better health [8][14]. Far less is known about how stressful conditions for the host such as crowding or food limitation affect the fitness of the parasites. Examining this question is a subtle but significant departure from most host-parasite studies, where the focus is primarily on host performance. Understanding how environmental factors affect parasite fitness might result in more accurate predictions regarding the number of parasite propagules available for subsequent infection. This information can in turn result in more accurate predictions regarding both the likelihood of infection, and the severity of infection.

How might variation in the host’s environment affect parasite fitness? For parasites that depend solely on their hosts for resources and shelter, a poor environment for the host may translate into a poor environment for the parasite. For example, parasites inhabiting low-quality hosts may have less to eat (both quantitatively and qualitatively), which may reduce parasite production [15], [16]. Conversely, hosts in poor condition may have fewer resources to allocate to immune functions or to other defenses against parasites [17], [18] thus leaving parasite growth and or reproduction less inhibited by attack from host defenses.

As a sidebar, we note here that in general, lifetime parasite fitness is typically defined as the parasite basic reproductive ratio, R0, but because of the multiple components that make up R0 [19][22], many studies instead use parasite productivity as a measure of parasite fitness (e.g. [16], [22][24] but see [25] for measures of lifetime parasite fitness). Parasite productivity is a reasonable proxy for R0, if productivity is correlated with the number of transmission propagules produced, and if the latter is positively correlated with the likelihood of infecting a susceptible host (e.g. [26], [27]).

Here we use the term ‘potential parasite fitness’ (PPF) because we do not directly measure parasite R0. Rather, we measure components of parasite fitness that are typically positively correlated with R0. In this study we ask whether parasite productivity is positively correlated with host food availability (a proxy of host condition) in the virus Autographa californica multiple nucleopolyhedrovirus (AcMNPV), and one of its natural hosts, the cabbage looper moth (Trichoplusia ni, Hübner, Lepidoptera: Noctuidae).


Parasite biology

AcMNPV is the type species of the genus Alphabaculovirus in the family Baculoviridae [28]. Baculoviruses are DNA viruses that primarily infect Lepidoptera [29], [30]. Caterpillars typically become infected upon ingesting virus occlusion bodies (OB), which are proteinaceous structures that contain virions (virus particles) [30]. Virions released by OBs spread throughout the larval body, and eventually the bulk of host tissue is converted into OBs [30][32]. At the end of a successful infection, the larva dies and OBs are released into the environment. AcMNPV has a wide host range and can infect species of at least 15 families of Lepidoptera [30].

Host biology

Trichoplusia ni are typically found in the subtropics worldwide [33] and are also common pests of greenhouse vegetables and agricultural cole crops at higher latitudes [34]. AcMNPV has been considered as a possible biological control agent of T. ni [35], [36] because it infects T. ni in the wild and has high virulence. This virus-host system is thus ideal for addressing questions related to PPF because the laboratory results could be applicable in nature, as well as to other lepidopteran hosts.

Insect collections and colony maintenance

Cabbage loopers were collected from commercial greenhouses in the lower mainland of British Columbia, Canada and maintained continuously in the laboratory at the University of British Columbia for 10 years (∼50 generations). AcMNPV was originally isolated from naturally infected T. ni early 2000s. The virus was used in various laboratory experiments and was purified and stored at −20°C when not in use [37].

To maintain T. ni colonies, neonates were reared in groups of 25 in 200 mL Styrofoam cups filled with 25 mL wheat-germ based diet [38]. Pupae were transferred to in emergence cages. Adults mated in these cages and females laid their eggs on a paper towel lining of the mating cage. Larval rearing cups and adult mating cages were maintained at 26±1°C 16∶8 light:dark. Egg-impregnated paper towels were stored at 5° until eggs were needed. Trichoplusia ni eggs readily hatch at room temperature.

Experimental design

We conducted two experiments to examine the relationship between parasite potential fitness and host condition in this host-parasite system. In both experiments we infected 4th instar larvae with virus, but the larvae used in experiment 1 were of lower initial condition than those used in experiment 2. We conducted these two experiments to gain a preliminary understanding in how host condition at the time of infection affects both host and parasite overall response to infection. Table 1 lists the differences between the two experiments. The experiments were conducted at two different times because of logistical constraints.

For each experiment, 120 larvae were each assigned to one of three food regimes: low (4–5 hours access to food/day), medium (12 hours food/day), or high (continuous access to food). Larvae were reared in 25 mL cups and the food source was a wheat germ-based diet modified from [38]. Larvae in experiment 1 were assigned to their food treatment after infection and larvae in experiment 2 were assigned to their food treatment before infection (Table 1).

One day after moulting into 4th instar, 90 of the 120 larvae were each given one 0.125 cm3 piece of diet dosed with 5 µL of 1000 OB/µL virus suspension. Preliminary data have shown this infection method to be sufficient to infect ≥95% of larvae. After 24-hour access to the virus-dosed diet, larvae were assigned to their food treatment (experiment 1), or returned to their initial food treatment (experiment 2). The remaining thirty larvae were each fed a 0.125 cm3 piece of diet dosed with 5 µL distilled water. These uninfected larvae were randomly and evenly distributed into the three food treatments (i.e. 10 uninfected larvae per food treatment, experiment 1), or returned to their original food treatment (experiment 2).

Data collected and statistical analyses

Infected larvae were maintained on low, medium or high food treatments until death. One day prior to death, when larvae were rendered immobile, bloated and discoloured by virus infection, larvae were weighed and transferred to 1.5 mL eppendorf tubes. After death, the tube containing the virus-killed larva was filled with distilled water so that the total volume (dead larva plus water) equaled 1 mL. The entire sample was macerated and total OB number was quantified using a hemocytometer. Virus OBs were counted in each of ten 0.2×0.2 mm squares. The average number of OBs per ten squares was then multiplied by 4×106 to obtain the total OB per larva. We collected data on days to death, weight at death, and total OBs per larva. We use virus OB number as our measure of PPF.

We used ANOVA to examine whether food treatment had a statistically significant effect on larval weight at death, days to death, and on virus OB number. We transformed both OB number (log OB number +1) and larval weight (log-weight) to meet assumptions of ANOVA. To better understand the functional relationship between virus productivity and host size, we used ANCOVA to examine whether food treatment mediated the relationship between OB number and larval weight (dependent variable: log OB+1), explanatory variable: food treatment, covariate: log (weight at death); interaction: food * log(weight at death). All statistical analyses were conducted in R version 3.0.2 (R Core Team 2013). Because the two experiments were conducted at different times and thus larvae could have been exposed to different environmental conditions in the laboratory, all statistics were run separately for the two experiments.

Literature survey

We used the Web of Science to search for papers that experimentally addressed whether parasite fitness (e.g. parasite growth rate, reproduction, development, transmission potential) was affected by host condition (e.g. food quality or quantity). We did not include parasitoids in our search. We examined correlational or observational studies between host quality and potential parasite fitness separately from experimental papers. We do not claim to have found all relevant published studies: our goal was primarily to develop a broad understanding of whether general patterns exist between host and parasite fitness.


Infection rate and overall sample size

None of the control, uninfected cabbage loopers died of viral infection. Because the goal of this study was to examine the effect of host food levels on parasite fitness, these uninfected control larvae were not included in statistical analyses. Larvae that did not develop full viral infections were also not included in the analysis. In experiment 1, three larvae that had been dosed with virus did not produce any virus OBs (1 larva from the low food treatment; 2 from the medium food treatment). Also for one or two larvae from each food treatment we missed the death date, or were unable to collect weight data because the larva had burst before its intact post-death weight could be recorded. Across the three food levels, data for days to death were collected from 81 larvae, and data for OB number and weight at death were collected from 83 larvae.

In experiment 2, no virus OBs were produced in 18 larvae (n = 13, 1, 4, in the low, medium and high food treatments respectively). Because almost half of the larvae (13/30) in the low food treatment did not develop a typical virus infection, we took a closer look at these unsuccessful infections. It appears that not only did these larvae not develop a proper virus infection, but they also barely grew at all. Unsuccessfully infected larvae died at a much lighter weight than infected larvae (F1,26 = 13.78, = 0.001), but there was no difference in days to death (Kruskal-Wallis χ2 = 1.78, p = 0.18). It is unclear why so many of the larvae in the low food treatment did not become infected with virus or why they did not grow in general. Overall, the infection rate was 57%, 97% and 87% for the low, medium and high food treatments respectively.

In addition, two infected larvae from the low food treatment burst before they were weighed, so we could not collect weight data for those individuals. Thus, across the three food levels, data for OB number and days to death were collected from 72 larvae, and weight at death were collected from 70 larvae.

Host weight at death, time to death, and virus OB production

Host weight at death and virus OB production increased with increasing food availability in both experiments (Fig. 1a, d; Fig. 1c, f; Table 2). In experiment 1, larvae that were fed medium and high food lived longer than those given low food (Fig. 1b; Table 2). Food treatment did not affect days to death in experiment 2 (Fig. 1e; Table 2).

Figure 1. The effect of food treatment on host weight, host days to death, and total virus OB production for experiment 1 (a–c) and experiment 2 (d–f).

Virus OB units are Log(OB per larva +1). Error bars are +/−1 S.E.M. Food treatments: 1 = low, 2 = medium, 3 = high. See Table 2 for ANOVA results.

Table 2. a. ANOVA table showing a significant effect of host food level on host weight, host days to death and virus production in Experiment 1, and on host weight and virus production in Experiment 2.

Relationship between virus production, host weight and food treatment

We examined the slope of the relationship between virus production and host weight for each food treatment. In both experiments 1 and 2, the slope of this relationship was shallowest for the low food treatment (Fig. 2a, b; Table 2).

Figure 2. The relationship between virus productivity and host weight depends on host food treatment (a: experiment 1, b: experiment 2).

Slopes of the relationships are shown in light blue, dark blue and green for the low, medium and high food treatments respectively. See Table 2 for ANCOVA results and for slope values.

Literature survey

We found 21 studies that demonstrated an increase in PPF with increasing host condition. We also found five studies where PPF decreased with increasing host condition, seven studies where PPF increased or decreased with host condition (depending on the parasite trait), and one study in which there was no change in parasite potential fitness (Table 3). Of these 34 papers, 17 documented host-parasite interactions in invertebrate hosts, 12 in vertebrate hosts, four in plant hosts and one paper investigated parasites of protists.

Table 3. Summary of experiments examining the effect of host food availability or food quality on fitness-related parasite traits.

The types of parasites investigated included virus, bacteria, fungi, tapeworms, trematodes, nematodes, protozoans, insects, cowbirds and mistletoes. The parasite fitness traits quantified included: production of reproductive bodies (spores, oocysts) or transmission stages, growth, development time, abundance and survival (Table 2).

Although they were not included in Table 3, we also found seven studies that used correlational or observational studies to examine the relationship between parasite fitness traits and host condition. These papers included parasite fitness data for vertebrate hosts (stickleback/cestodes [15], voles/trypanosomes [39], doves/lice [40], rodent/cestode [41]; small mammals/protozoans and helminthes: [42]), and in a plant-mistletoe host-parasite system [43], [44]. The results of these correlational studies showed no clear relationships between parasite fitness and host condition.


Empirical results

Our experiments revealed a strong positive relationship between virus productivity and host food availability. These results suggest that virus potential fitness likely benefits from increased resource availability to hosts in this host-parasite system.

We have also shown that the rate of virus OB production was lowest in hosts given the lowest access to food (Fig. 2a, b; Table 2). This result implies that in poorly-fed hosts, the virus is less efficient at converting host tissue to virus tissue. It is unclear why this might be the case; perhaps a stressed, low-condition larva translates into a low-quality or low-quantity resource for the virus. In a laboratory experiment with western tent caterpillar, low food availability appeared to reduce the susceptibility of western tent caterpillars to NPV infection [45]. The authors suggested that this result was related to the immune function of the host when food deprived, or the ability of the virus to replicate for some other reason.

The overall positive relationship between virus productivity and host food availability across the three food treatments could also be linked to the relationship between larval mass and larval volume; in other words, virus OB production may be constrained by the volume of the insect. Previous literature [46] examined the relationship of larval weight to volume in Heliconius cydno (Lepidoptera: Nymphalidae) and Trirhabda germinata (Coleoptera: Chyrsomelidae) and found it to be linear on a log-log scale. The slope of the relationship was 1.03 for T. germinata and 0.95 for H. cydno. Overall, this linear log-log relationship is similar to the pattern observed in our experiments, and may suggest that virus production may be bounded by the rate at which larval volume increases with larval mass.

We conducted two experiments with slightly different starting conditions in order to gain a preliminary understanding of how host condition at the time of infection might affect overall host condition and parasite fitness. Because of logistical constraints, the two experiments were conducted at different times, so we make comparisons between the two experiments with some caution. Data for final host weight suggest that larvae in experiment 1 were had lower overall condition than those in experiment 2 (Fig. 1a, d). In fact the final weight of larvae in the lowest food treatment in experiment 2 overlapped with the final weight of larvae in the highest food treatment in experiment 1. Thus, transferring larvae from group rearing cups to individual cups at the third instar stage had a considerable affect on the overall size of the larvae, and on overall virus production. Unfortunately because of the small time-window available for larval infections at the early 4th instar stage, we did not collect data on initial larval weight, so we do not have data on how much growth took place during the experiments. However, we still feel confident in the overall conclusion that increases in host condition are beneficial to the PPF in this host-parasite system.

With respect to ‘days to death’, infected larvae that had greater access to food also lived longer in Experiment 1, but in Experiment 2 food availability did not affect survival. The range of days to death observed here (4.5∼6.5 days; experiments combined), is within the range documented by other experiments with T. ni and AcMNPV [47][49], and the results for experiment 2 approach the upper end of those seen in comparable studies. The data suggest that across the two experiments hosts that were fed more also took longer to die, but again we say this with caution because the experiments were conducted at two different times.

Although we were unable to find published studies that similarly experimentally examined virus yield in response to host food availability, other authors have demonstrated that virus OB production was influenced by the type of plant fed to the host [50], [51]. Virus yield was highest in larvae of the western tent caterpillar (Malacosoma californicum pluviale) that were fed alder plants, versus wild rose or apple [50]. Similarly, virus yield was highest when winter moth (Operopthera brumata) larvae were fed oak, versus Sitka spruce or heather [51]. Together these data suggest that viral fitness is potentially affected by both larval food quantity and quality.

Literature survey

The literature survey revealed that potential parasite fitness typically increased with host food availability in invertebrate, plant and protist hosts (Table 3). Our empirical data are consistent with these results.

For vertebrate hosts, the relationship between potential parasite fitness and host condition was more variable and tended to depend on the host-parasite system or on the parasite trait measured.

Overall, data from studies included in this literature survey suggest that PPF can both increase and decrease with host condition. We caution that this is a preliminary survey of the literature and a more comprehensive literature review or meta-analysis, which corrects for phylogenetic biases and variation in sample sizes are required to discuss any trends with quantitative rigor.

Implications for understanding parasite fitness and disease ecology

Previous work in this area [13], [52] postulated that low condition hosts can be both more susceptible to parasites, and can suffer more from infection, than hosts in better condition. This increased susceptibility and suffering lead to what the authors termed a ‘vicious circle’, in which poor condition leads to higher parasite loads, which in turn keeps the host in poor condition. These ‘vicious circles’ can lead to individual reproductive failure and death, as well as host population decline [13]. Our empirical data and preliminary literature survey have demonstrated that poor condition hosts may have lower parasite productivity than higher condition hosts; thus in some host-parasite combinations, the ‘vicious circle’ may not lead to a continuous increase in parasite propagule pressure. Poor condition hosts may still suffer more from parasites than hosts in better condition, but they may end up contributing fewer parasites to the overall parasite population pool. If environmental conditions are poor across a large landscape (e.g. widespread drought), this may result in large numbers of poor-condition hosts, and for some taxa, in a decrease in parasite population size, rather than an increase.

We propose that the next step to a better understanding the relationship between host and parasite fitness is to examine in greater detail whether groups of taxa exhibit similarities with respect to the effect of environmentally-mediated variation in host condition on parasite fitness. Analytical or simulation models can then incorporate these general patterns to make predictions regarding the overall effect of variation in host condition on host-parasite dynamics (e.g. Daphnia/bacteria: [53]; Lepidopteran/virus: [26], [54], [55].

Given that the world is a heterogeneous place, environmentally-mediated variation in host condition is likely to be ubiquitous in nature. However, the outcome of parasite infection is not only affected by food availability or quality, as documented here, but also by factors such as variation in temperature [56][59] and salinity [60]. The goal moving forward is to determine whether broad patterns exist in how hosts and parasites respond to variation in these biotic and abiotic factors, and to use these patterns to inform how environmental heterogeneity affects host-parasite interactions at the population and community levels.


This manuscript benefitted from discussions with Jenny Cory. We thank one anonymous reviewer for helpful comments on the initial version of the manuscript.

Author Contributions

Conceived and designed the experiments: MT. Performed the experiments: MT. Analyzed the data: MT JHM. Contributed reagents/materials/analysis tools: JHM. Contributed to the writing of the manuscript: MT JHM.


  1. 1. Hudson PJ, Dobson a P, Newborn D (1998) Prevention of population cycles by parasite removal. Science 282: 2256–2258.
  2. 2. Pedersen AB, Greives TJ (2008) The interaction of parasites and resources cause crashes in a wild mouse population. J Anim Ecol 77: 370–377
  3. 3. Klemola N, Andersson T, Ruohomäki K, Klemola T (2010) Experimental test of parasitism hypothesis for population cycles of a forest lepidopteran. Ecology 91: 2506–2513.
  4. 4. Jaenike J (1978) An hypothesis to account for the maintenance of sex within populations. Evol Theory 3: 191–193.
  5. 5. Hamilton WD (1980) Sex versus non-sex versus parasite. Oikos 35: 282–290
  6. 6. Lively CM (1987) Evidence from a New Zealand snail for the maintenance of sex by parasitism. 328: 519–521.
  7. 7. Moore SL, Wilson K (2002) Parasites as a viability cost of sexual selection in natural populations of mammals. Science 297: 2015–2018
  8. 8. Agrios GN (1988) Plant Pathology. Sixth. San Diego: Academic Press.
  9. 9. Lively CM, Johnson SG, Delph LF, Clay K (1995) Thinning reduces the effect of rust infection on jewelweed (Impatiens capensis). Ecology.
  10. 10. Laine A-L (2007) Pathogen fitness components and genotypes differ in their sensitivity to nutrient and temperature variation in a wild plant-pathogen association. J Evol Biol 20: 2371–2378
  11. 11. Brown MJF, Loosli R, Schmid-Hempel P (2000) Condition-dependent expression of virulence in a trypanosome infecting bumblebees. Oikos 91: 421–427.
  12. 12. Pedersen S, Saeed I, Friis H, Michaelsen KF (2001) Effect of iron deficiency on Trichuris suis and Ascaris suum infections in pigs. Parasitology 122: 589–598.
  13. 13. Beldomenico PM, Begon M (2010) Disease spread, susceptibility and infection intensity: vicious circles? Trends Ecol Evol 25: 21–27
  14. 14. Prüss-Üstün A, Corvalán C (2006) Preventing disease through healthy envionments. Geneva: WHO Press.
  15. 15. Barber I, Wright HA, Arnott SA, Wootton RJ (2008) Growth and energetics in the stickleback-Schistocephalus host-parasite system: a review of experimental infection studies. Behaviour 145: 4–5.
  16. 16. Seppälä O, Liljeroos K, Karvonen A, Jokela J (2008) Host condition as a constraint for parasite reproduction. Oikos 117: 749–753
  17. 17. Sheldon BC, Verhulst S (1996) Ecological immunology - costly parasite defenses and trade- offs in evolutionary ecology. Trends Ecol Evol 11: 317–321.
  18. 18. Sadd BM, Schmid-Hempel P (2008) Principles of ecological immunology. Evol Appl 2: 113–121
  19. 19. Anderson RM, May RM (1981) The population dynamics of microparasites and their invertebrate hosts. Philos Trans R Soc B Biol Sci 291: 451–524.
  20. 20. Anderson RM, May RM (1992) Infectious Diseases of Humans: Dynamics and Control. Oxford University Press.
  21. 21. Scott ME, Smith G (1994) Parasitic and Infectious Diseases: Epidemiology and Ecology. Academic Press.
  22. 22. Refardt D, Ebert D (2007) Inference of parasite local adaptation using two different fitness components. J Evol Biol 20: 921–929
  23. 23. Ebert D, Zschokke-Rohringer CD, Carius HJ (2000) Dose effects and density-dependent regulation of two microparasites of Daphnia magna. Oecologia 122: 200–209.
  24. 24. Bedhomme S, Agnew P, Sidobre C, Michalakis Y (2004) Virulence reaction norms across a food gradient. Proc R Soc B Biol Sci 271: 739–744
  25. 25. De Roode JC, Yates AJ, Altizer S (2008) Virulence-transmission trade-offs and population divergence in virulence in a naturally occurring butterfly parasite. Proc Natl Acad Sci 105: 7489–7494.
  26. 26. Dwyer G, Elkinton J, Buonaccorsi J (1997) Host heterogeneity in susceptibility and disease dynamics: tests of a mathematical model. Am Nat 150: 685–707
  27. 27. De Roode JC, Chi J, Rarick RM, Altizer S (2009) Strength in numbers: high parasite burdens increase transmission of a protozoan parasite of monarch butterflies (Danaus plexippus). Oecologia 161: 67–75
  28. 28. Harrison RL, Popham HJR, Breitenbach JE, Rowley DL (2012) Genetic variation and virulence of Autographa californica multiple nucleopolyhedrovirus and Trichoplusia ni single nucleopolyhedrovirus isolates. J Invertebr Pathol 110: 33–47
  29. 29. Volkman LE (1997) Nucleopolyhedrovirus interactions with their insect hosts. Adv Virus Res 48: 313–348.
  30. 30. Cory J, Myers J (2003) The ecology and evolution of insect baculoviruses. Annu Rev Ecol Evol Syst 34: 239–272
  31. 31. Keddie BA, Aponte GW, Volkman LE (1989) The pathway of infection of Autographa californica nuclear polyhedrosis virus in an insect host. Science 243: 1728–1730.
  32. 32. Fuxa JR (2004) Ecology of insect nucleopolyhedroviruses. Agric Ecosyst Environ 103: 27–43
  33. 33. Mitchell ER, Chalfant RB (1984) Biology, behaviour, and disperasal of adults. In: Lingren PD, Greene RL, editors. Suppression and management of cabbage looper populations. Technical Bulleton of the U.S. Department of Agricuture. pp. 10–20.
  34. 34. Franklin MT, Ritland CE, Myers JH (2010) Spatial and temporal changes in genetic structure of greenhouse and field populations of cabbage looper, Trichoplusia ni. Mol Ecol 19: 1122–1133
  35. 35. Hernandez-Crespo P, Hails RS, Sait SM, Green BM, Carty TM, et al. (1999) Response of hosts of varying susceptibility to a recombinant baculovirus insecticide in the field. Biol Control 16: 119–127.
  36. 36. Wilson KR, O’Reilly DR, Hails RS, Cory JS (2000) Age-Related Effects of the Autographa californica Multiple Nucleopolyhedrovirus egt Gene in the Cabbage Looper (Trichoplusia ni). Biol Control 19: 57–63
  37. 37. Erlandson M, Newhouse S, Moore K, Janmaat A, Myers J, et al. (2007) Characterization of baculovirus isolates from Trichoplusia ni populations from vegetable greenhouses. Biol Control 41: 256–263
  38. 38. Jaques RP (1967) The persistence of a nuclear polyhedrosis virus in the habitat of the host insect, Trichoplusia ni. II. Polyhedra in soil. Can Entomol 99: 820–829.
  39. 39. Beldomenico PM, Telfer S, Gebert S, Lukomski L, Bennett M, et al. (2009) The vicious circle and infection intensity: The case of Trypanosoma microti in field vole populations. Epidemics 1: 162–167
  40. 40. Booth DT, Clayton DH, Block BA (1993) Experimental demonstration of the energetic cost of parasitism in free-ranging hosts. Proc R Soc B Biol Sci 253: 125–129
  41. 41. Winternitz JC, Yabsley MJ, Altizer SM (2012) Parasite infection and host dynamics in a naturally fluctuating rodent population. Can J Zool 90: 1149–1160
  42. 42. Crompton DWT (1987) Host diet as a determinant of parasite growth, reproduction and survival. Mamm Rev 17: 117–126.
  43. 43. Bickford CP, Kolb TE, Geils BW (2005) Host physiological condition regulates parasitic plant performance: Arceuthobium vaginatum subsp. cryptopodum on Pinus ponderosa. Oecologia 146: 179–189
  44. 44. Glatzel G, Geils BW (2009) Mistletoe ecophysiology: host–parasite interactions. Botany 87: 10–15
  45. 45. Myers JHJ, Cory JSJ, Ericsson JJD, Tseng MML (2011) The effect of food limitation on immunity factors and disease resistance in the western tent caterpillar. Oecologia 167: 647–655
  46. 46. Smiley JT, Wisdom CS (1982) Photographnic estimation of weight of insect larvae. Ann Entomol Soc Am 75: 616–618.
  47. 47. Burden JP, Hails RS, Windass JD, Suner M-M, Cory JS (2000) Infectivity, speed of kill, and productivity of a baculovirus expressing the itch mite toxin Txp-1 in second and fourth instar larvae of Trichoplusia ni. J Invertebr Pathol 75: 226–236
  48. 48. Cory JS, Clarke EE, Brown ML, Hails RS, O’Reilly DR (2004) Microparasite manipulation of an insect: the influence of the egt gene on the interaction between a baculovirus and its Lepidopteran host. Funct Ecol 18: 443–450
  49. 49. Zwart MP, van der Werf W, Georgievska L, van Oers MM, Vlak JM, et al. (2010) Mixed-genotype infections of Trichoplusia ni larvae with Autographa californica multicapsid nucleopolyhedrovirus: Speed of action and persistence of a recombinant in serial passage. Biol Control 52: 77–83
  50. 50. Cory JS, Myers JH (2004) Adaptation in an insect host-plant pathogen interaction. Ecol Lett 7: 632–639
  51. 51. Raymond B, Vanbergen A, Pearce I, Hartley S (2002) Host plant species can influence the fitness of herbivore pathogens: the winter moth and its nucleopolyhedrovirus. Oecologia 131: 533–541
  52. 52. Beldomenico PM, Telfer S, Gebert S, Lukomski L, Bennett M, et al. (2008) Poor condition and infection: a vicious circle in natural populations. Proc R Soc B Biol Sci 275: 1753–1759
  53. 53. Vale PF, Wilson AJ, Best A, Boots M, Little TJ (2011) Epidemiological, evolutionary, and coevolutionary implications of context-dependent parasitism. Am Nat 177: 510–521
  54. 54. Dwyer G, Firestone J, Stevens TE (2005) Should models of disease dynamics in herbivorous insects include the effects of variability in host-plant foliage quality? Am Nat 165: 16–31
  55. 55. Abbott KC, Dwyer G (2007) Food limitation and insect outbreaks: complex dynamics in plant-herbivore models. J Anim Ecol 76: 1004–1014
  56. 56. Blanford S, Thomas MB, Pugh C, Pell JK (2003) Temperature checks the Red Queen? Resistance and virulence in a fluctuating environment. Ecol Lett 6: 2–5.
  57. 57. Mitchell SE, Rogers ES, Little TJ, Read AF (2005) Host-parasite and genotype-by-environment interactions: temperature modifies potential for selection by a sterilizing pathogen. Evolution 59: 70–80.
  58. 58. Duncan AB, Fellous S, Kaltz O (2011) Temporal variation in temperature determines disease spread and maintenance in Paramecium microcosm populations. Proc R Soc B Biol Sci 278: 3412–3420
  59. 59. Garamszegi LZ (2011) Climate change increases the risk of malaria in birds. Glob Chang Biol 17: 1751–1759
  60. 60. Studer A, Poulin R (2012) Effects of salinity on an intertidal host–parasite system: Is the parasite more sensitive than its host? J Exp Mar Bio Ecol 412: 110–116
  61. 61. Ryder JJ, Hathway J, Knell RJ (2007) Constraints on parasite fecundity and transmission in an insect-STD system. Oikos 116: 578–584
  62. 62. Fellous S, Koella JC (2009) Infectious dose affects the outcome of the within-host competition between parasites. Am Nat 173: E177–E184
  63. 63. Tseng M (2006) Interactions between the parasite’s previous and current environment mediate the outcome of parasite infection. Am Nat 168: 565–571
  64. 64. Sadd BM (2011) Food-environment mediates the outcome of specific interactions between a bumblebee and its trypanosome parasite. Evolution 65: 2995–3001
  65. 65. Shostak AW, Walsh JG, Wong YC (2008) Manipulation of host food availability and use of multiple exposures to assess the crowding effect on Hymenolepis diminuta in Tribolium confusum. Parasitology 135. doi:10.1017/S0031182008004459.
  66. 66. Hall SRR, Simonis JLL, Nisbet RMM, Tessier AJJ, Cáceres CEE (2009) Resource ecology of virulence in a planktonic host-parasite system: An explanation using dynamic energy budgets. Am Nat 174: 149–162
  67. 67. Hall SR, Knight CJ, Becker CR, Duffy MA, Tessier AJ, et al. (2009) Quality matters: resource quality for hosts and the timing of epidemics. Ecol Lett 12: 118–128
  68. 68. Vale PF, Choisy M, Little TJ (2013) Host nutrition alters the variance in parasite transmission potential Host nutrition alters the variance in parasite transmission potential. 9: 20121145.
  69. 69. Ebert D, Joachim Carius H, Little T, Decaestecker E (2004) The evolution of virulence when parasites cause host castration and gigantism. Am Nat 164: S19–S32
  70. 70. Hall MD, Ebert D (2012) Disentangling the influence of parasite genotype, host genotype and maternal environment on different stages of bacterial infection in Daphnia magna. Proc R Soc B Biol Sci 279: 3176–3183
  71. 71. Stjernman M, Little TJ (2011) Genetic variation for maternal effects on parasite susceptibility. J Evol Biol 24: 2357–2363
  72. 72. Benesh DP (2010) Developmental inflexibility of larval tapeworms in response to resource variation. Int J Parasitol 40: 487–497
  73. 73. Krist AC, Jokela J, Wiehn J, Lively CM (2003) Effects of host condition on susceptibility to infection, parasite developmental rate, and parasite transmission in a snail-trematode interaction. J Evol Biol 17: 33–40
  74. 74. Yih W, Coats DW (2000) Infection of Gymnodinium sanguineum by the Dinoflagellate Amoebophrya sp.: Effect of nutrient environment on parasite generation time, reproduction, and infectivity. J Eukaryot Microbiol 47: 504–510.
  75. 75. Lecompte F, Abro MA, Nicot PC (2010) Contrasted responses of Botrytis cinerea isolates developing on tomato plants grown under different nitrogen nutrition regimes. Plant Pathol 59: 891–899
  76. 76. Abrahamson WG, Anderson SS, McCrea KD (1988) Effects of manipulation of plant carbon nutrient balance on tall goldenrod resistance to a gallmaking herbivore. Oecologia 77: 302–306
  77. 77. Bize P, Jeanneret C, Klopfenstein A, Roulin A (2008) What makes a host profitable? Parasites balance host nutritive resources against immunity. Am Nat 171: 107–118
  78. 78. Zanette L, Clinchy M (2010) Food supplementation leads to bottom-up and top-down food-host-parasite interactions. J Anim Ecol 79: 1172–1180
  79. 79. Rueesch S, Lemoine M, Richner H (2012) Ectoparasite reproductive performance when host condition varies. Parasitol Res 111: 1193–1203
  80. 80. Tschirren B, Bischoff LL, Saladin V, Richner H (2007) Host condition and host immunity affect parasite fitness in a bird-ectoparasite system. Funct Ecol 21: 372–378
  81. 81. Murray DL, Keith LB, Cary JR (1998) Do parasitism and nutritional status interact to affect production in snowshoe hares? Ecology 79: 1209–1222.
  82. 82. Gouagna LC, Ferguson HM, Okech BA, Killeen GF, Kabiru EW, et al. (2004) Plasmodium falciparum malaria disease manifestations in humans and transmission to Anopheles gambiae: a field study in Western Kenya. Parasitology 128: 235–243
  83. 83. Johansen M V, Bogh HO, Giver H, Eriksen L, Nansen P, et al. (1997) Schistosoma japonicum and Trichuris suis infections in pigs fed diets with high and low protein. Parasitology 115: 257–264.
  84. 84. Vicente J, Höfle U, Fernández-De-Mera IG, Gortazar C (2007) The importance of parasite life history and host density in predicting the impact of infections in red deer. Oecologia 152: 655–664
  85. 85. Guinnee MA, Gemmill AW, Chan BHK, Viney ME, Read AF (2003) Host immune status affects maturation time in two nematode species – but not as predicted by a simple life-history model. Parasitology 127: 507–512
  86. 86. Krasnov BR, Khokhlova IS, Arakelyan MS, Degen AA (2005) Is a starving host tastier? Reproduction in fleas parasitizing food-limited rodents. Funct Ecol 19: 625–631
  87. 87. Rosario C, Fried B (1999) Effects of a protein-free diet on worm recovery, growth, and distribution of Echinostoma caproni in ICR mice. J Helminthol 73: 167–170.