Sv1_PCA_varCov

Sensitivity of stochastic population growth rate to temporal autocorrelation in vital rates using observed vital-rate covariances in simulations - results from simLambdaTAC_VarCov.

matsVarCov

RData including MPMs for 109 species with information on vital-rate correlation

matsMean

RData containing average MPMs for 454 study specie

dataDroso - census data

Demographic transitions of Drosophyllum lusitanicum populations recorded in annual censuses (from 2011 to 2015) in five populations. These data are used to quantify vital rates of above-ground individuals

dataDrosoSB

Seed fates (in a binary format) inferred from two experiments. These data are used to quantify the transitions related to the seedbank

sLambdaSimul - stochastic lambda simulations

Runs simulations, based on different fire return intervals, of the stochastic population growth rate using IPMs constructed (A) from mean parameter values, (B) from perturbed vital rates, and (C) for each posterior sample of the parameters describing seed-bank ingression (goSB), stasis (staySB) and egression (outSB); calculates the stochastic population growth rate, its elasticities, and the probability of quasi-extinction at time t. The structure of the code is based on Tuljapurkar et al. (2003), Am. Nat., 162, 489-502 and Trotter et al. (2013), Methods Ecol. Evol., 4, 290-298

Overview of the R code provided in the manuscript

Here, we provide an overview of the R scripts and data files to accompany the main text, "Interacting livestock and fire may both threaten and increase viability of a fire-adapted Mediterranean carnivorous subshrub" and found in this depository. The .R files should be opened with an R editor (e.g., R Studio). The R code is fully commented

perturbVR - vital rate perturbations

Demonstrates how to construct IPMs from perturbed vital rates. Each IPM is obtained by (a) perturbing a vital rate by its mean or standard deviation (see makeVRmu.R on constructing mean vital-rate kernels) and (b) constructing a new IPM kernel incorporating the perturbed vital rat

mcmcOUT - parameter samples

In case the reader wishes to forego the step of fitting the Bayesian models, we provided a mcmcOUT.csv file with 1000 posterior parameter values for each of the parameters estimated with Bayesian models using uninformative prior

sLambdaRmpi - stochastic simulations on parallel processors

Implements the simulations of the stochastic population growth rate using parallel processing, where simulations are split into different processors of a supercomputer to greatly speed up computational time