Survival of three cereal-aphid species across a broad range of stressful high
and low temperatures, the model-ready frame for the multi-species case study.
Aphids of three ages (2, 6, 12 days old) were exposed to a heat branch
(34–40 degrees C) or a cold branch (-11 to -3 degrees C) for a range of
durations and scored alive/dead after recovery. One row per assay group;
branch flags the heat vs cold series. Subset to one branch (and
typically one age) and fit CTmax and z as functions of
species in one joint 4PL to compare species with profile-likelihood
confidence intervals on those direct parameters.
Format
A data frame with 3041 rows and 7 variables:
- species
Species, a factor with levels
M_dirhodum(Metopolophium dirhodum),S_avenae(Sitobion avenae),R_padi(Rhopalosiphum padi).- age
Age in days, a factor with levels
2,6,12.- branch
Stress branch, a factor with levels
heat(34–40 degrees C),cold(-11 to -3 degrees C).- temp
Assay temperature (degrees C).
- duration_min
Exposure duration (minutes).
- n_total
Number of aphids treated.
- n_surv
Number surviving after treatment and recovery.
Source
Li Y-J, Chen S-Y, Jørgensen LB, Overgaard J, Renault D,
Colinet H, Ma C-S (2023). Data for: Interspecific differences in thermal
tolerance landscape explain aphid community abundance under climate change.
Dryad, doi:10.5061/dryad.mcvdnck4j
(Dryad CC0). Associated article:
Journal of Thermal Biology 114: 103583, doi:10.1016/j.jtherbio.2023.103583
.
Raw file:
system.file("extdata", "data_lethal_TDT_aphid.csv", package = "freqTLS").
Examples
# \donttest{
a <- subset(aphid_tdt, branch == "heat" & age == "6")
std <- standardize_data(a, temp = "temp", duration = "duration_min",
n_total = "n_total", n_surv = "n_surv",
duration_unit = "minutes")
wf <- fit_4pl(std, ctmax = ~ 0 + species, z = ~ 0 + species,
low = ~ 1, up = ~ 1, k = ~ temp_c, t_ref = 60)
tls(wf, by = "species", lethal = FALSE) # z and CTmax; no Tcrit here
#> <tls> relative threshold; quantities: z, CTmax (profile intervals)
#> # A tibble: 6 × 5
#> species quantity median lower upper
#> <chr> <chr> <dbl> <dbl> <dbl>
#> 1 M_dirhodum CTmax 35.2 35.0 35.4
#> 2 S_avenae CTmax 36.5 36.4 36.6
#> 3 R_padi CTmax 37.2 37.1 37.3
#> 4 M_dirhodum z 4.75 4.52 5.02
#> 5 S_avenae z 3.61 3.46 3.77
#> 6 R_padi z 3.97 3.70 4.25
# }