embryogrowth (version 5.0)

tsd: Estimate the parameters that best describe temperature-dependent sex determination

Description

Estimate the parameters that best describe temperature-dependent sex determination

Usage

tsd(males = NULL, females = NULL, N = NULL, temperatures = NULL,
  df = NULL, l = 0.05, parameters.initial = c(P = NA, S = -0.5, K = 0),
  males.freq = TRUE, las.x = 1, las.y = 1,
  lab.PT = "Pivotal temperature",
  lab.TRT = paste0("Transitional range of temperatures l=", l * 100, "%"),
  col.TRT = "gray", col.TRT.CI = rgb(0.8, 0.8, 0.8, 0.5),
  col.PT.CI = rgb(0.8, 0.8, 0.8, 0.5), equation = "logistic",
  replicate = 1000, range.CI = 0.95, print = TRUE, ...)

Arguments

males

A vector with male numbers

females

A vector with female numbers

N

A vector with total numbers

temperatures

The constant incubation temperatures or any covariate used to fit sex ratio

df

A dataframe with at least two columns named males, females or N and temperatures column

l

The limit to define TRT (see Girondot, 1999)

parameters.initial

Initial values for P, S or K search as a vector, ex. c(P=29, S=-0.3)

las.x

las parameter for x axis

las.y

las parameter for y axis

lab.PT

Label to describe pivotal temperature

lab.TRT

Label to describe transitional range of temperature

males.freq

Should the graph uses males frequency [TRUE] or females [FALSE]

equation

Could be "logistic", "Hill", "Richards" or "GSD"

replicate

Number of replicate to estimate SE of TRT

range.CI

The range of confidence interval for estimation, default=0.95

col.TRT

The color of TRT

col.TRT.CI

The color of CI of TRT based on range.CI

col.PT.CI

The color of CI of PT based on range.CI

print

Do the results must be printed at screen? TRUE or FALSE

...

Graphical parameters for plot(), exemple xlab="", ylab="", main=""

Value

• A list the pivotal temperature, transitional range of temperatures and their SE

Details

tsd estimates the parameters that best describe temperature-dependent sex determination

References

Girondot, M. 1999. Statistical description of temperature-dependent sex determination using maximum likelihood. Evolutionary Ecology Research, 1, 479-486.

Godfrey, M.H., Delmas, V., Girondot, M., 2003. Assessment of patterns of temperature-dependent sex determination using maximum likelihood model selection. Ecoscience 10, 265-272.

Hulin, V., Delmas, V., Girondot, M., Godfrey, M.H., Guillon, J.-M., 2009. Temperature-dependent sex determination and global change: are some species at greater risk? Oecologia 160, 493-506.

Examples

CC_AtlanticSW <- subset(STSRE_TSD, RMU=="Atlantic, SW" &
                          Species=="Caretta caretta" & Sexed!=0)
par(mar=c(4,4,5,1)+0.1)
tsdL <- with (CC_AtlanticSW, tsd(males=Males, females=Females,
                                 temperatures=Incubation.temperature-Correction.factor,
                                 equation="logistic"))
tsdH <- with (CC_AtlanticSW, tsd(males=Males, females=Females,
                                 temperatures=Incubation.temperature-Correction.factor,
                                 equation="Hill"))
tsdR <- with (CC_AtlanticSW, tsd(males=Males, females=Females,
                                 temperatures=Incubation.temperature-Correction.factor,
                                 equation="Richards"))
gsd <- with (CC_AtlanticSW, tsd(males=Males, females=Females,
                                 temperatures=Incubation.temperature-Correction.factor,
                                 equation="GSD"))
compare_AIC(Logistic_Model=tsdL, Hill_model=tsdH, Richards_model=tsdR, GSD_model=gsd)