DOI: 10.5061/dryad.v41ns1s3f
title: Mean survival rate and their temporal environmental (process) variance for 89 species of vertebrates

description: 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.,
 &lt; 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.
description: 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.<br>
description: # Mean survival rate and their temporal environmental (process) variance
 for 89 species of vertebrates
 A compilation of data on
 annual mean survival rates and its environmental (process) variance in
 studies of vertebrates published up to September 2018. We only included
 estimates on process variance when sampling variance was accounted for.
 The previous version included a few studies (n=8) using covariates in
 models estimating environmental variance and a studies based on survival
 estimates from a shorter time window than a year. We therefore omitted
 these studies. In this compilation only studies based on annual survival
 rates and on EV estimates from models without any environmental covariates
 (e.g., climate variables or population density) are included. Compared to
 the previous version we also added a column "AD/JUV" for the
 comparison between adults and juveniles and we recorded the column
 Ad/juv-imm according to the description below. Last we added a column
 called "population ID" to analyse within population contrasts of
 environmental variance. ## Description of the data and file structure Data
 is structured after alphabetic order of first authors of published papers.
 Description of the variables: * Common name of species * Latin name of
 species * Taxon - bird, mammal, reptile, amphibian or fish * Parameter -
 description of stage/age-related survival * Subpopulation - name of
 subpopulation, when several populations have been studied * Population ID
 - population number from 1-140 to be used for within-population
 adult-juvenile comparisons * AD/JUV - classification of juvenile (0) or
 adult (1) * Adult/juv-imm - category 1= adult survival, 0= juvenile
 survival, 2= immature survival * mean_surv = mean annual survival rate *
 process_variance = temporal environmental variance accounting for sampling
 variance * years = number of years of study, n/a - missing data * Method =
 method used to estimate process variance by accounting for sampling
 variance. References to the methods is found in the paper * Comment =
 comments on specifics for survival rate estimates or their EVs *
 Reference: full reference