Current environmental changes may increase temporal variability of life-history traits of species, which can significantly affect their long-term population growth rate and their extinction risk. There is a need to estimate environmental variance (i.e., process variance) of life-history traits (EV). For example, if there is a general relationship between EVs and mean annual survival rates of species, that relationship could be used as a guideline for analyses of population growth and extinction risk for populations where data on EVs are missing. For this purpose we present a comprehensive compilation of 252 EV estimates from 89 species belonging to five vertebrate taxa (mammals, birds, reptiles, amphibians and fish) covering mean annual survival rates from 0.01 to 0.98. Since variances of survival rates are constrained by their means, particularly for low and high mean survival rates, we assessed whether any observed relationship persisted after applying two types of commonly used variance stabilizing transformations: relativized EVs (observed / mathematical maximum) and logit scaled EVs. With raw EVs at the arithmetic scale, mean-variance relationships of annual survival rates were hump-shaped with small EVs at low and high mean survival rates, and higher (and widely variable) EVs at intermediate mean survival rates. When mean annual survival rates were related to relativized EVs the hump-shaped pattern remained albeit less distinct than for raw EVs, but when transforming EVs to logit scale the pattern of the relationship between mean annual survival rates and EVs largely disappeared. The within-species juvenile- adult slopes were mainly positive at low survival rates (i.e., < 0.5; birds) and negative s at high survival rates for raw and relativized variances while these patterns disappeared when EVs were logit transformed. Uncertainties in how to interpret the results of relativized and logit scaled EVs, and the observed high variation in EV’s for similar mean annual survival rates, illustrates that extrapolations of observed EVs and tests of life history drivers of survival-EV relationships need to also acknowledge the large variation in these parameters.

We extracted all studies up to and including 2018 from Web of Science that cited the following publications describing methods for estimating EV of life-history traits, i.e., Link & Nichols (1994), Engen, Bakke & Islam (1998), Gould & Nichols (1998), Kendall (1998), White & Burnham (1999), Akcakaya (2002), Burnham & White (2002), and Altwegg, Schaub & Roulin (2007). White & Burnham (1999) has a very large number of citations because it is the primary reference for the program MARK. For these studies we therefore used the additional search terms “reproduction AND variance”, “survival AND variance”, “environmental varia*”, “process variance”, “sampling variance”, “vital rates” and “(reproduction OR fecundity OR fertility) AND variance” to filter the citations. We also included other relevant studies, such as papers referenced in Morris et al. (2011) and data in Morris & Doak (2002).

We only used data from studies that explicitly partitioned observed variance into process and sampling variance. We furthermore selected studies estimating only mean annual survival rates (studies based on survival during shorter time periods were discarded). Also, we only kept studies where EVs were estimated from models without any environmental covariates (e.g., climate variables or population density) as that would reduce EVs and make them incomparable across species. Using these criteria, we retrieved 69 studies. All methods to partition variance considered in this paper are listed in the data file.