Data from: Interactive life-history traits predict sensitivity of plants and animals to temporal autocorrelation

Temporal autocorrelation in demographic processes is an important aspect of population dynamics, but a comprehensive examination of its effects on different life-history strategies is lacking. We use matrix populations models from 454 plant and animal populations to simulate stochastic population growth rates (log λs) under different temporal autocorrelations in demographic rates, using simulated and observed covariation among rates. We then test for differences in sensitivities, or changes, of log λs to changes in autocorrelation among two major axes of life-history strategies, obtained from phylogenetically-informed principal component analysis: the fast-slow and semelparous-iteroparous continua. Fast life histories exhibit highest sensitivities to simulated autocorrelation in demographic rates across reproductive strategies. Slow life histories are less sensitive to temporal autocorrelation, but their sensitivities increase among highly iteroparous species. We provide cross-taxonomic evidence that changes in the autocorrelation of environmental variation may affect a wide range of species, depending on complex interactions of life-history strategies.phyloSpeciesAll species used in analysesSv1_PCASensitivities of the stochastic growth rate to temporal autocorrelation in vital rates - results of simulations simLambdaTAC.RSv1_PCA_varCovSensitivity of stochastic population growth rate to temporal autocorrelation in vital rates using observed vital-rate covariances in simulations - results from simLambdaTAC_VarCov.RmatsMeanRData containing average MPMs for 454 study speciesmatsVarCovRData including MPMs for 109 species with information on vital-rate correlation