Food quality effects on instar-specific life histories of a holometabolous insect

Abstract

It is a long-standing challenge to understand how changes in food resources impact consumer life history traits and, in turn, impact how organisms interact with their environment. To characterize food quality effects on life history, most studies follow organisms throughout their life cycle and quantify major life events, such as age at maturity or fecundity. From these studies, we know that food quality generally impacts body size, juvenile development, and life span. Importantly, throughout juvenile development, many organisms develop through several stages of growth that can have different interactions with their environment. For example, some parasitoids typically attack larger instars, whereas larval insect predators typically attack smaller instars. Interestingly, most studies lump all juvenile stages together, which ignores these ecological changes over juvenile development.We combine a cross-sectional experimental approach with a stage-structured population model to estimate instar-specific vital rates in the bean weevil, Callosobruchus maculatus across a food quality gradient. We characterize food quality effects on the bean weevil's life history traits throughout its juvenile ontogeny to test how food quality impacts instar-specific vital rates.Vital rates differed across food quality treatments within each instar; however, their effect differed with instar. Weevils consuming low-quality food spent 38%, 37%, and 18% more time, and were 34%, 53%, and 63% smaller than weevils consuming high-quality food in the second, third, and fourth instars, respectively. Overall, our results show that consuming poor food quality means slower growth, but that food quality effects on vital rates, growth and development are not equal across instars. Differences in life history traits over juvenile ontogeny in response to food quality may impact how organisms interact with their environment, including how susceptible they are to predation, parasitism, and their competitive ability.

Keywords: cowpea weevil; juvenile ontogeny; phytophagous consumer; stage‐structured population model.

Figure 1

Boxplots of head capsule widths (mm) of Callosobruchus maculatus measured across juvenile stages of development (1st, 2nd, 3rd, and 4th larval instars) for each pellet quality treatment (90% black‐eye pea: 10% filler, 95% black‐eye pea: 5% filler, and 100% black‐eye pea: 0% filler, represented by red, yellow, and blue, respectively). The horizonal line within the box indicates the median, the lower, and the upper boundaries of the box indicate the 25th and 75th percentiles, respectively, and the upper and lower whiskers (dashed lines protruding from each box) represent largest and smallest nonoutlier head capsule widths, respectively. Points above and below each whisker represent potential outliers, as they are more than 1.5 times either the upper or the lower boundary, respectively. The full model with an interaction term between pellet quality and juvenile stage of development computed the lowest qAIC (qAIC = 137,045.4), indicating that the interaction between pellet quality and juvenile stage best models the distribution of head capsule width. Head capsule width generally increased with pellet quality and juvenile stage, beginning in larval instar 2. Boxplots with different letters are significantly different (p < .01)

Figure 2

Boxplots of log dry biomass of Callosobruchus maculatus measured in milligrams across juvenile stages of development (1st, 2nd, 3rd, and 4th larval instars) for each pellet quality treatment (90% black‐eye pea: 10% filler, 95% black‐eye pea: 5% filler, and 100% black‐eye pea: 0% filler, represented by red, yellow, and blue, respectively). Other details are as in Figure 1. The full model with an interaction term between pellet quality and juvenile stage of development computed the lowest qAIC (qAIC = 137,045.4), indicating that the interaction between pellet quality and juvenile stage best models the distribution of dry biomass. Dry biomass generally increased with pellet quality and juvenile stage, beginning in larval instar 2, but differences in dry biomass among 95% black‐eye pea: 5% filler and 100% black‐eye pea: 0% filler are not apparent until the fourth larval instar. Boxplots with different letters are significantly different (p < .01)

Figure 3

Fitted stage‐structured model to time‐series data comprising the number of Callosobruchus maculatus in a particular stage of development (1st, 2nd, 3rd, and 4th instar, pupal and adult) through time (left), and the cumulative number of C. maculatus that died in each stage of development (right) for each pellet quality (90% black‐eye pea: 10% filler, 95% black‐eye pea: 5% filler, and 100% black‐eye pea: 0% filler). Left: observed (symbols) and predicted (lines) number of living C. maculatus individuals recorded daily for each stage of development and pellet quality treatment. Predicted number of C. maculatus were estimated by solving a distributed‐delay model with a set of ordinary differential equations using an objective function that assumes a Poisson error distribution that compared the predicted number of individual weevils from the stage‐structured population model to the observed data and calculated the likelihood of the distribution as a function of the initial parameters. Right: observed (bars) and predicted (symbols) number of dead C. maculatus individuals recorded for each stage of development and pellet quality treatment

Figure 4

Mean and 95% confidence intervals of 30,000 bootstrapped parameter estimates of Callosobruchus maculatus development time for three pellet qualities (90% black‐eye pea: 10% filler, 95% black‐eye pea: 5% filler, and 100% black‐eye pea: 0% filler) in each stage of weevil development (1st, 2nd, 3rd, and 4th instars, pupal and adult). The distribution of 30,000 bootstrapped parameter estimates was computed by fitting a stage‐structured model to time‐series data that comprised resampling the number of C. maculatus in a particular stage of development (1st, 2nd, 3rd, and 4th instar, pupal and adult) through time, and the cumulative number of C. maculatus that died in each stage of development. To infer significance of pellet quality differences on development time of C. maculatus within each stage of development, development time differences across pellet qualities estimated from the observed data were compared with null distributions of differences of resampled development times for each pellet quality comparison (90%–95%, 95%–100%, and 90%–100% black‐eye pea flour). Pellet quality comparisons of C. maculatus development time labeled with different letters within each stage of weevil development, are significantly different from the null difference of resampled C. maculatus development times, (p < .05)

Figure 5

Mean and 95% confidence intervals of survivorship ($e^{-\delta {\alpha }^{-1}}$) of C. maculatus through each stage of development (1st, 2nd, 3rd, and 4th instars, and pupal) for three pellet qualities (90% black‐eye pea: 10% filler, 95% black‐eye pea: 5% filler, and 100% black‐eye pea: 0% filler). Survivorship means and 95% confidence intervals were computed from distributions of 30,000 bootstrapped development, α and mortality δ parameter estimates. Significance of pellet quality effects on survivorship was computed following the same methods described in Figure 4. Pellet quality comparisons of C. maculatus survivorship labeled with different letters within each stage of weevil development, are significantly different from the null difference of resampled C. maculatus survivorship, (p < .05)

Figure 6

Probability density function estimating the length of time C. maculatus spends in each stage of development (1st, 2nd, 3rd, and 4th instars) for three pellet qualities (90% black‐eye pea: 10% filler, 95% black‐eye pea: 5% filler, and 100% black‐eye pea: 0% filler) in red, yellow, and blue lines, respectively. The length of time C. maculatus spent in each stage of development was estimated for each pellet quality from a Gamma density distribution function using the most likely parameter values, α and k as the scale and shape parameters in the function dgamma, respectively

Figure 7

Percent differences of Callosobruchus maculatus development time and dry biomass in each instar stage of development (L1, L2, L3, and L4) comparing two pellet qualities (90% black‐eye pea: 10% filler and 100% black‐eye pea: 0% filler)