torpor: torpor: torpor: Mixture model aimed at assigning metabolic...

In vullioud/torpor: Assigning metabolic rate measurements to torpor and euthermia in heterothermic endotherms

torpor: torpor: Mixture model aimed at assigning metabolic rate measurements (M) to torpor and euthermia in heterothermic endotherms.

Description

This package enables the assignment of M to torpor or euthermia. It uses the v ariation in M measured during euthermic rest and torpor at different ambient temperatures (Ta) to estimate the lower critical temperature (Tlc) of the thermoneutral zone (TNZ) and determine physiological state membership using mixture models. In addition, this package enables the further prediction of M during rest and torpor along Ta, including resting metabolic rate within the TNZ.

Details

This package is aimed to support any physiologist working in thermal energetics. More information can be found on the companion article Fasel et al. (Biol Open 15 April 2022; 11 (4): bio059064. doi: https://doi.org/10.1242/bio.059064) and in the vignettes.

This package is center around the tor_fit() function which enables to fit mixture models on metabolic rates data using Bayesian inference.

tor_fit

The function tor_fit() considers the relation between metabolic rate (M) and ambient temperature (Ta) assumed by the Scholander-Irving model and its later extensions.

Resting M measured within the thermoneutral zone (TNZ) is independent of Ta. This rate is hereafter referred to as Mtnz, although it would correspond to the basal metabolic rate (BMR) provided that the specific criteria for the BMR are met (see Fasel et al. in prep.). Below the lower critical temperature of TNZ (Tlc), M of euthermic animals increases linearly with decreasing Ta. M of torpid animals increases linearly with decreasing Ta to maintain a minimal body temperature below some threshold ambient temperature (Tt). This state is usually referred to as "regulated torpor". Between Tt and Tlc, M of torpid animals follows an exponential curve. In this Ta range, torpor is referred to as "conforming torpor".

tor_plot

The function tor_plot() is a wrapper function around the [tor_fit())] and [tor_predict()].

It uses [tor_fit()] to fit a mixture model using#'Bayesian inference and plot the predicted value as well as the raw data. Measures are presented in different colors depending on the metabolic state. Predicted values as well as 95% credible interval (segmented lines) are also presented. This function enables the user to replicate the analysis done in Fasel et al. (in prep).

[tor_fit())]: R:tor_fit()) [tor_predict()]: R:tor_predict() [tor_fit()]: R:tor_fit()

tor_predict

The function provides the predicted M and 95% credible interval boundaries at a defined Ta given a certain model, in euthermic and/or torpid state.

tor_assign

The function assign the individual points according to their estimated state.

tor_summarise

The function gives a summary statistic of the model fit.

vullioud/torpor documentation built on Nov. 27, 2024, 2:28 a.m.