In lucasnell/clonewars: Clonal Evolution in Aphid Metapopulations

knitr::opts_chunk$set(collapse = TRUE, comment = "#>")

This vignette outlines the internal data present in gameofclones. These data inform some of the default parameters in sim_experiments but are not always identical because sim_experiments was designed to simulate the experimental cages that differed in size from those used to calculate these parameter values.

The code was initially set up for 2 clones that have different life histories. The life histories are taken from lab experiments and correspond to demographic parameters at 20º and 27º C. See Meisner et al. (2014). They also include parameters related to parasitoid wasps and aphid resistance to them.

Parameters from this document are saved into 4 lists present as exported data for this package:

| | | |:--------------|:-------------------------------------------------------------------| | dev_times | Development times for aphids and wasps | | populations | Population rates and starting values for aphids and wasps | | wasp_attack | Wasp attack rate parameters | | environ | Parameters associated with environmental effects and stochasticity |

Parameters were wrapped into lists to avoid namespace conflicts and to allow me to use the same names as those in the paper.

Development times

• instar_days: number of days per instar, for low (20º C, lowT) and high (27º C, highT) temperatures
• mum_days: number of days per stage of an aphid being parasitized: living and dead ("mummy"), respectively.

dev_times <- list(
    instar_days = list(lowT = c(2, 2, 2, 2, 19), 
                       highT = c(1, 1, 1, 2, 23)),
    mum_days = cbind(7, 3)
)

Populations

These are the stage-structured parameters that specify demographic rates by aphid age, for low-growth (low) and high-growth (high) clonal lines.

• surv_juv: juvenile (instar 1-4) daily survival; same for all juvenile ages.
• surv_adult: adult survival; different by day. Data are from two clones, one with a high population growth rate, and another with a low rate.
• repro: daily fecundity for adults of the two clones, one with a high population growth rate, and another with a low rate.

populations <- list(
    surv_juv = list(low = 0.9745, high = 0.9849),
    surv_adult = list(
        low = rbind(c(1.0000, 0.9949, 0.9818, 0.9534, 0.8805, 0.8367, 0.8532, 0.8786, 
                      0.8823, 0.8748, 0.8636, 0.8394, 0.8118, 0.8096, 0.8240, 0.8333, 
                      0.7544, 0.5859, 0.4155, 0.2216, rep(0, 180))),
        high = rbind(c(1.0000, 0.9986, 0.9951, 0.9874, 0.9675, 0.9552, 0.9550, 0.9549, 
                       0.9462, 0.8992, 0.8571, 0.8408, 0.8281, 0.8062, 0.7699, 0.7500, 
                       0.7559, 0.7649, 0.7240, 0.4367, rep(0, 180)))),
    repro = list(
        low = rbind(c(0, 2.5925, 4.4312, 5.1403, 5.5190, 5.6633, 5.6010, 5.4577, 5.2904, 
                      5.0613, 4.6970, 3.3577, 1.5946, 1.0817, 0.9666, 0.8333, 0.4689, 
                      0.0709, 0, 0, 0, 0, rep(0, 178))),
        high = rbind(c(0, 3.1975, 5.4563, 6.2996, 6.7372, 6.9030, 6.8210, 6.6100, 
                       6.1962, 5.1653, 4.1837, 3.6029, 3.1023, 2.4799, 1.6909, 1.1750, 
                       1.0148, 0.9096, 0.7821, 0.6430, 0.5000, 0.3531, rep(0, 178))))
)

Other parameters:

These are other population-level parameters for both aphids and wasps. Parameters K, K_y, and s_y are directly from the paper; sex_ratio was "hard-coded" into the paper's model but is allowed to change here. The rest were chosen as reasonable starting values for experiments.

• K: aphid density dependence
• K_y: parasitized aphid density dependence
• s_y: parasitoid adult daily survival
• sex_ratio: proportion of female wasps
• aphids_0: initial density of aphids
• wasps_0: initial densities of wasps
• prop_resist: proportion of resistant clones

populations[["K"]] <- 4.67e-4
populations[["K_y"]] <- 7.33e-4
populations[["s_y"]] <- 0.69
populations[["sex_ratio"]] <- 0.5
populations[["aphids_0"]] <- 20
populations[["wasps_0"]] <- 1
populations[["prop_resist"]] <- 0.05

Wasp attack

These parameters are from equation 6 in Meisner et al. (2014). Relative attack rates on the different instars are from Ives et al (1999). The survivals of attacked, resistant aphids is from unpublished code by Anthony Ives. This will obviously differ significantly among clones, but was considered a good starting point for a resistant line.

• a: parasitoid attack rate
• k: aggregation parameter of the negative binomial distribution
• h: parasitoid attack rate handling time
• rel_attack: relative attack rates on the different instars
• attack_surv: the survivals of singly attacked and multiply attacked resistant aphids

wasp_attack <- list(
    a = 2.32,
    k = 0.35,
    h = 0.008,
    rel_attack = c(0.12, 0.27, 0.39, 0.16, 0.06),
    attack_surv = c(0.9, 0.6)
)

Environment

Parameters associated with environmental effects. It's assumed that alates (winged aphids) are the primary mode of disperal among patches, and alates' wings aren't fully developed until adulthood. So, the day at which aphids can begin dispersing unsurprisingly depends on how quickly the aphids are developing.

• harvest_surv: aphid survival rate at harvesting
• disp_aphid: dispersal rates between fields for aphids, adult wasps
• disp_wasp: dispersal rates between fields for aphids, adult wasps
• pred_rate: predation rate for aphids and non-adult wasps
• cycle_length: time between harvests (typical for alfalfa)
• field_disp_start: when aphids disperse by flying, for low (20º C; lowT) and high (27º C; highT) temperatures

environ <- list(
    harvest_surv = 0.05,
    disp_aphid = 0.05,
    disp_wasp = 1,
    pred_rate = 0.8,
    cycle_length = 30,
    field_disp_start = list(
        lowT = sum(dev_times$instar_days$lowT[1:4]) + 1, 
        highT = sum(dev_times$instar_days$highT[1:4]) + 1)
)

Parameters associated with environmental stochasticity.

rho was estimated at 1.0 in Meisner et al. (2014), but that estimate "... was largely an artifact of the fitting procedure" (p 468). The number here is from unpublished code by Anthony Ives that works to simulate the cages we are using for experiments.

For their simulations, Meisner et al. (2014) multiplied the original estimated values of sigma_x and sigma_y by half to "emphasize the demographic stochasticity" (p 469). The values below are the original estimated values, not those used for their simulations.

• sigma_x: environmental std dev for aphids
• sigma_y: environmental std dev for wasps
• rho: environmental correlation among instars

environ[["sigma_x"]] <- 0.44
environ[["sigma_y"]] <- 0.70
environ[["rho"]] <- signif(2/(1+exp(-environ[["sigma_y"]]))-1, 2)

Saving data

Saving the created objects as internal data for gameofclones.

usethis::use_data(dev_times, populations, wasp_attack, environ)

lucasnell/clonewars documentation built on Oct. 12, 2023, 4:39 p.m.