ashrafi5_2018: Ashrafi V model for fitting thermal performance curves

In padpadpadpad/rTPC: Fitting and Analysing Thermal Performance Curves

Ashrafi V model for fitting thermal performance curves

Description

Ashrafi V model for fitting thermal performance curves

Usage

ashrafi5_2018(temp, a, b, c, d)

Arguments

temp	temperature in degrees centigrade
a	dimensionless parameter
b	dimensionless parameter
c	dimensionless parameter
d	dimensionless parameter

Details

Equation:

rate = a + b \cdot log(temp + 273.15)^2 + c \cdot log(temp + 273.15) + \frac{d \cdot log(temp + 273.15)}{temp + 273.15}

Start values in get_start_vals are derived from the data or sensible values from the literature.

Limits in get_lower_lims and get_upper_lims are derived from the data or based extreme values that are unlikely to occur in ecological settings.

Value

a numeric vector of rate values based on the temperatures and parameter values provided to the function

Note

Generally we found this model easy to fit.

Author(s)

Daniel Padfield

References

Ashrafi, R. et al. Broad thermal tolerance is negatively correlated with virulence in an opportunistic bacterial pathogen. Evolutionary Applications 11, 1700–1714 (2018).

Examples

# load in ggplot
library(ggplot2)

# subset for the first TPC curve
data('chlorella_tpc')
d <- subset(chlorella_tpc, curve_id == 1)

# get start values and fit model
start_vals <- get_start_vals(d$temp, d$rate, model_name = 'ashrafi5_2018')
# fit model
mod <- nls.multstart::nls_multstart(rate~ashrafi5_2018(temp = temp, a, b, c, d),
data = d,
iter = c(4,4,4,4),
start_lower = start_vals - 10,
start_upper = start_vals + 10,
lower = get_lower_lims(d$temp, d$rate, model_name = 'ashrafi5_2018'),
upper = get_upper_lims(d$temp, d$rate, model_name = 'ashrafi5_2018'),
supp_errors = 'Y',
convergence_count = FALSE)

# look at model fit
summary(mod)

# get predictions
preds <- data.frame(temp = seq(min(d$temp), max(d$temp), length.out = 100))
preds <- broom::augment(mod, newdata = preds)

# plot
ggplot(preds) +
geom_point(aes(temp, rate), d) +
geom_line(aes(temp, .fitted), col = 'blue') +
theme_bw()

padpadpadpad/rTPC documentation built on Feb. 21, 2025, 5:30 a.m.