# The package embryogrowth Tools to analyze the embryo growth and the sexualisation thermal reaction norms. The latest version of this package can always been installed using: install.packages("https://hebergement.universite-paris-saclay.fr/marcgirondot/CRAN/HelpersMG.tar.gz", repos=NULL, type="source") install.packages("https://hebergement.universite-paris-saclay.fr/marcgirondot/CRAN/embryogrowth.tar.gz", repos=NULL, type="source") ## Details Fit a parametric function that describes dependency of embryo growth to temperature ||| |:--|:--| |Package:|embryogrowth| |Type:|Package| |Version:|9.5 build 1827| |Date:|2024-08-23| |License:|GPL (>= 2)| |LazyLoad:|yes| ## Examples ```r ## Not run: library("embryogrowth") packageVersion("embryogrowth") data(nest) formated <- FormatNests(nest) # The initial parameters value can be: # "T12H", "DHA", "DHH", "Rho25" # Or # "T12L", "DT", "DHA", "DHH", "DHL", "Rho25" x <- structure(c(115.758929130522, 428.649022170996, 503.687251738993, 12.2621455821612, 306.308841227278, 116.35048615105), .Names = c("DHA", "DHH", "DHL", "DT", "T12L", "Rho25")) # or x <- structure(c(118.431040984352, 498.205702157603, 306.056280989839, 118.189669472381), .Names = c("DHA", "DHH", "T12H", "Rho25")) # pfixed <- c(K=82.33) or rK=82.33/39.33 pfixed <- c(rK=2.093313) ################################################################################ # # The values of rK=2.093313 and M0=1.7 were used in # Girondot, M. & Kaska, Y. 2014. A model to predict the thermal # reaction norm for the embryo growth rate from field data. Journal of # Thermal Biology. 45, 96-102. # # Based on recent analysis on table of development for both Emys orbicularis and # Caretta caretta, best value for rK should be 1.209 and M0 should be 0.34. # Girondot M, Monsinjon J, Guillon J-M (2018) Delimitation of the embryonic # thermosensitive period for sex determination using an embryo growth model # reveals a potential bias for sex ratio prediction in turtles. Journal of # Thermal Biology 73: 32-40 # # See the example in the stages datasets # ################################################################################ resultNest_4p_SSM <- searchR(parameters=x, fixed.parameters=pfixed, temperatures=formated, integral=integral.Gompertz, M0=1.7, hatchling.metric=c(Mean=39.33, SD=1.92)) data(resultNest_4p_SSM) par(mar=c(4, 4, 1, 1)) plot(resultNest_4p_SSM$data[[1]][, 1]/60/24,resultNest_4p_SSM$data[[1]][, 2], bty="n", las=1, xlab="Days of incubation", ylab="Temperatures in °C", type="l", xlim=c(0,70),ylim=c(20, 35)) for (i in 2:resultNest_4p_SSM$data$IndiceT[["NbTS"]]) { par(new=TRUE) plot(resultNest_4p_SSM$data[[i]][, 1]/60/24,resultNest_4p_SSM$data[[i]][, 2], bty="n", las=1, xlab="", ylab="", type="l", xlim=c(0,70),ylim=c(20, 35), axes = FALSE) } par(mar=c(4, 4, 1, 1)) pMCMC <- TRN_MHmcmc_p(resultNest_4p_SSM, accept=TRUE) # Take care, it can be very long, sometimes several days resultNest_mcmc_4p_SSM <- GRTRN_MHmcmc(result=resultNest_4p_SSM, parametersMCMC=pMCMC, n.iter=10000, n.chains = 1, n.adapt = 0, thin=1, trace=TRUE) data(resultNest_mcmc_4p_SSM) out <- as.mcmc(resultNest_mcmc_4p_SSM) # This out obtained after as.mcmc can be used with coda package # plot() can use the direct output of GRTRN_MHmcmc() function. plot(resultNest_mcmc_4p_SSM, parameters=1, xlim=c(0,550)) plot(resultNest_mcmc_4p_SSM, parameters=3, xlim=c(290,320)) # But rather than to use the SD for each parameter independantly, it is # more logical to estimate the distribution of the curves new_result <- ChangeSSM(resultmcmc = resultNest_mcmc_4p_SSM, result = resultNest_4p_SSM, temperatures = seq(from = 20, to = 35, by = 0.1), initial.parameters = NULL) par(mar=c(4, 4, 1, 5)+0.4) plotR(result = resultNest_4p_SSM, parameters = new_result$par, ylabH = "Temperatures\ndensity", ylimH=c(0, 0.3), atH=c(0, 0.1, 0.2), ylim=c(0, 3), show.hist=TRUE) # Beautiful density plots plotR(result = resultNest_4p_SSM, resultmcmc=resultNest_mcmc_4p_SSM, curve = "MCMC quantiles", show.density=TRUE) plotR(resultNest_6p_SSM, resultmcmc=resultNest_mcmc_6p_SSM, ylim=c(0, 4), show.density=TRUE, show.hist=TRUE, curve = "MCMC quantiles", ylimH=c(0,0.5), atH=c(0, 0.1, 0.2)) # How many times this package has been download library(cranlogs) embryogrowth <- cran_downloads("embryogrowth", from = "2014-08-16", to = Sys.Date() - 1) sum(embryogrowth$count) plot(embryogrowth$date, embryogrowth$count, type="l", bty="n") ## End(Not run) ``` ## References \insertRef 1515embryogrowth \insertRef 3534embryogrowth \insertRef 9039embryogrowth \insertRef 8589embryogrowth \insertRef 10871embryogrowth \insertRef 8566embryogrowth \insertRef 11124embryogrowth \insertRef 10620embryogrowth \insertRef 11754embryogrowth \insertRef 12168embryogrowth \insertRef 10870embryogrowth \insertRef 13669embryogrowth \insertRef 5790embryogrowth \insertRef 13271embryogrowth \insertRef 11893embryogrowth ## Author(s) Marc Girondot marc.girondot@gmail.com

embryogrowth-package