Draw bootstrapped Thermal Performance Curves (TPCs) to visualize uncertainty in parameter estimation of TPC fitting

Draw bootstrapped Thermal Performance Curves (TPCs) to visualize uncertainty in parameter estimation of TPC fitting

Usage

plot_uncertainties(
  temp = NULL,
  dev_rate = NULL,
  bootstrap_tpcs = NULL,
  species = NULL,
  life_stage = NULL,
  alpha = 0.2
)

Source

The dataset used in the example was originally published in Satar & Yokomi (2022) under the CC-BY-NC license

Arguments

temp

a vector of temperatures used in the experiment. It should have at least four different temperatures and must contain only numbers without any missing values.

dev_rate

a vector of estimated development rates corresponding to each temperature. These rates are calculated as the inverse of the number of days to complete the transition from the beginning of a certain life stage to the beginning of the following at each temperature. It must be numeric and of the same length as temp.

bootstrap_tpcs

a tibble A tibble object as produced by predict_curves(), containing bootstrapped TPCs to propagate uncertainty.

species

a string of the target species that will constitute the plot title. Must be of type "character".

life_stage

a string of the target life stage that will constitute the plot subtitle. Must be of type "character".

alpha

a number between 0 and 1 to choose transparency of the bootstrapped curves (0 = complete transparency, 1 = solid line).

Value

A ggplot object containing the visual representation of the estimate TPC and the bootstrapped uncertainty curves as a ribbon. Each model is represented in a facet, and data points are also explicit.

References

Angilletta, M.J., (2006). Estimating and comparing thermal performance curves. J. Therm. Biol. 31: 541-545. (for model selection in TPC framework)

Padfield, D., O'Sullivan, H. and Pawar, S. (2021). rTPC and nls.multstart: A new pipeline to fit thermal performance curves in R. Methods Ecol Evol. 12: 1138-1143.

Rebaudo, F., Struelens, Q. and Dangles, O. (2018). Modelling temperature-dependent development rate and phenology in arthropods: The devRate package for R. Methods Ecol Evol. 9: 1144-1150.

Satar, S. and Yokomi, R. (2002). Effect of temperature and host on development of Brachycaudus schwartzi (Homoptera: Aphididae). Ann. Entomol. Soc. Am. 95: 597-602.

See also

browseVignettes("rTPC") for model names, start values searching workflows, and bootstrapping procedures using both rTPC::get_start_vals() and nls.multstart::nls_multstart()

fit_devmodels() for fitting Thermal Performance Curves to development rate data, which is in turn based on nls.multstart::nls_multstart(). predict_curves() for bootstrapping procedure based on the above-mentioned rTPC vignettes.

Examples

if (FALSE) { # interactive()
data("aphid")

fitted_tpcs <- fit_devmodels(temp = aphid$temperature,
                             dev_rate = aphid$rate_value,
                             model_name = "all")

plot_devmodels(temp = aphid$temperature,
               dev_rate = aphid$rate_value,
               fitted_parameters = fitted_tpcs,
               species = "Brachycaudus swartzi",
               life_stage = "Nymphs")

# Obtain prediction TPCs with bootstraps for propagating uncertainty:
boot_tpcs <- predict_curves(temp = aphid$temperature,
                            dev_rate = aphid$rate_value,
                            fitted_parameters = fitted_tpcs,
                            model_name_2boot = c("lactin2", "briere2", "beta"),
                            propagate_uncertainty = TRUE,
                            n_boots_samples = 10)

print(boot_tpcs)

# Plot bootstrapped curves:

plot_uncertainties(temp = aphid$temperature,
                   dev_rate = aphid$rate_value,
                   bootstrap_tpcs = boot_tpcs,
                   species = "Brachycaudus schwartzi",
                   life_stage = "Nymphs")
}