rate_TPC: Intrinsic growth rate dependent on temperature
In epcc: Simulating Populations of Ectotherms under Global Warming

Description Usage Arguments Details Value References Examples

This function allows to obtain the intrinsic growth rate following a thermal performance curve (TPC). A cubic polynomial is used considering Saldaña et al (2019).

1	rate_TPC(T, ro, temp_cmin, temp_cmax, temp_op)

`T`	Temperature trend at which the population dynamics are studied.
`ro`	Population growth rate at optimal temperature.
`temp_cmin`	Minimum critical temperature.
`temp_cmax`	Maximum critical temperature.
`temp_op`	Optimum performance temperature.

The intrinsic growth rate is represented by a thermal performance curve (TPC). These curves associate the performance of ectothermic organisms as a function of body temperature. These curves have a characteristic unimodal asymmetric shape skewed to the left. Its main descriptors are minimum and maximum critical temperatures, which indicate the thermal tolerance range, and the optimum temperature, which indicates the temperature at which performance is at its maximum value (Anguilleta, 2006; Huey et al., 2012). The function implements a cubic expression that follows the characteristic shape of TPCs as described in Saldaña et al. (2019).

No return value, called for side effects.

Angilletta, M. J. (2006). Estimating and comparing thermal performance curves. Journal of Thermal Biology, 31(7), 541-545. doi:10.1016/j.jtherbio.2006.06.002

Huey, R. B., Kearney, M. R., Krockenberger, A., Holtum, J. A. M., Jess, M., & Williams, S. E. (2012). Predicting organismal vulnerability to climate warming: roles of behaviour, physiology and adaptation. Philosophical Transactions of the Royal Society B: Biological Sciences, 367(1596), 1665-1679. doi:10.1098/rstb.2012.0005

Saldaña-Núñez, V.N., Córdova-Lepe, F.D. & Moreno-Gómez, F.N. (2019). Population dynamics in the face of climate change: Analysis of a cubic thermal performance curve in ectotherms. J. Phys.: Conf. Ser. 1329 012007. doi:10.1088/1742-6596/1329/1/012007

times<- seq(2005, 2100, 1/12)
temp_cmin <- 18
temp_cmax <- 26

# Temperature at which performance is at its maximum value.
temp_op <- (temp_cmax+temp_cmin)/3+sqrt(((temp_cmax+temp_cmin)/3)^2-
           (temp_cmax*temp_cmin)/3)

ro <- 0.8

# Temperature that occurs in the minimum time of the simulation.
temp_i <- 20

temp <- get_RCP8.5(times)+temp_i

rate <- rate_TPC(temp,ro,temp_cmin,temp_cmax,temp_op)

plot(times,rate, type="l")