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How demographic factors lead to variation or change in growth rates can be investigated using life table response experiments (LTRE) based on structured population models. Traditionally, LTREs focused on decomposing the asymptotic growth rate, but more recently decompositions of annual 'realized' growth rates using 'transient' LTREs have gained in popularity.Transient LTREs have been used particularly to understand how variation in vital rates translate into variation in growth for populations under long‐term study. For these, complete population models may be constructed to investigate how temporal variation in environmental drivers affect vital rates. Such investigations have usually come down to estimating covariate coefficients for the effects of environmental variables on vital rates, but formal ways of assessing how they lead to variation in growth rates have been lacking.We extend transient LTREs to further partition the contributions from vital rates into contributions from temporally varying factors that affect them. The decomposition allows one to compare the resultant effect on the growth rate of different environmental factors, as well as density dependence, which may each act via multiple vital rates. We also show how realized growth rates can be decomposed into separate components from environmental and demographic stochasticity. The latter is typically omitted in LTRE analyses.We illustrate these extensions with an integrated population model (IPM) for data from a 26 years study on northern wheatears (Oenanthe oenanthe), a migratory passerine bird breeding in an agricultural landscape. For this population, consisting of around 50–120 breeding pairs per year, we partition variation in realized growth rates into environmental contributions from temperature, rainfall, population density and unexplained random variation via multiple vital rates, and from demographic stochasticity.The case study suggests that variation in first year survival via the unexplained random component, and adult survival via temperature are two main factors behind environmental variation in growth rates. More than half of the variation in growth rates is suggested to come from demographic stochasticity, demonstrating the importance of this factor for populations of moderate size. [ABSTRACT FROM AUTHOR]

1. Adult individuals that do not breed in a given year occur in a wide range of natural populations. However, such nonbreeders are often ignored in theoretical and empirical population studies, limiting our knowledge of how nonbreeders affect realized and estimated population dynamics and potentially impeding projection of deterministic and stochastic population growth rates. 2. We present and analyse a general modelling framework for systems where breeders and nonbreeders differ in key demographic rates, incorporating different forms of nonbreeding, different life histories and frequency-dependent effects of nonbreeders on demographic rates of breeders. 3. Comparisons of estimates of deterministic population growth rate, λ, and demographic variance, σd², from models with and without distinct nonbreeder classes show that models that do not explicitly incorporate nonbreeders give upwardly biased estimates of σd², particularly when the equilibrium ratio of nonbreeders to breeders, N*nb/N*b, is high. Estimates of k from empirical observations of breeders only are substantially inflated when individuals frequently re-enter the breeding population after periods of nonbreeding. 4. Sensitivity analyses of diverse parameterizations of our model framework, with and without negative frequency-dependent effects of nonbreeders on breeder demographic rates, show how changes in demographic rates of breeders vs. nonbreeders differentially affect k. In particular, λ is most sensitive to nonbreeder parameters in long-lived species, when N*nb/N*b > 0, and when individuals are unlikely to breed at several consecutive time steps. 5. Our results demonstrate that failing to account for nonbreeders in population studies can obscure low population growth rates that should cause management concern. Quantifying the size and demography of the nonbreeding section of populations and modelling appropriate demographic structuring is therefore essential to evaluate nonbreeders' influence on deterministic and stochastic population dynamics. [ABSTRACT FROM AUTHOR]

1. The aim of the present study is to model the stochastic variation in the size of five populations of great tit Parus major in the Netherlands, using a combination of individual-based demographic data and time series of population fluctuations. We will examine relative contribution of density-dependent effects, and variation in climate and winter food on local dynamics as well as on number of immigrants. 2. Annual changes in population size were strongly affected by temporal variation in number of recruits produced locally as well as by the number of immigrants. The number of individuals recruited from one breeding season to the next was mainly determined by the population size in year t, the beech crop index (BCI) in year t and the temperature during March–April in year t. The number of immigrating females in year t + 1 was also explained by the number of females present in the population in year t, the BCI in autumn year t and the temperature during April–May in year t. 3. By comparing predictions of the population model with the recorded number of females, the simultaneous modelling of local recruitment and immigration explained a large proportion of the annual variation in recorded population growth rates. 4. Environmental stochasticity especially caused by spring temperature and BCI did in general contribute more to annual fluctuations in population size than density-dependent effects. Similar effects of climate on local recruitment and immigration also caused covariation in temporal fluctuations of immigration and local production of recruits. 5. The effects of various variables in explaining fluctuations in population size were not independent, and the combined effect of the variables were generally non-additive. Thus, the effects of variables causing fluctuations in population size should not be considered separately because the total effect will be influenced by covariances among the explanatory variables. 6. Our results show that fluctuations in the environment affect local recruitment as well as annual fluctuations in the number of immigrants. This effect of environment on the interchange of individuals among populations is important for predicting effects of global climate change on the pattern of population fluctuations. [ABSTRACT FROM AUTHOR]

1. Population extinction is a fundamental ecological process. Recent experimental work has begun to test the large body of theory that predicts how demographic, genetic and environmental factors influence extinction risk. We review empirical studies of extinction conducted under controlled laboratory conditions. Our synthesis highlights four findings. First, extinction theory largely considers individual, isolated populations. However, species interactions frequently altered or even reversed the influence of environmental factors on population extinction as compared to single-species conditions, highlighting the need to integrate community ecology into population theory. 2. While most single-species studies qualitatively agree with theoretical predictions, studies are needed that quantitatively compare observed and predicted extinction rates. A quantitative understanding of extinction processes is needed to further advance theory and to predict population extinction resulting from human activities. 3. Many stresses leading to population extinction can be assuaged by migration between subpopulations. However, too much migration increases synchrony between subpopulations and thus increases extinction risk. Research is needed to determine how to strike a balance that maximizes the benefit of migration. 4. Results from laboratory experiments often conflict with field studies. Understanding these inconsistencies is crucial for extending extinction theory to natural populations. [ABSTRACT FROM AUTHOR]

1. Using data on breeding birds from a 35-year study of Florida scrub-jays Aphelocoma coerulescens (Bosc 1795), we show that survival probabilities are structured by age, birth cohort, and maternal family, but not by sex. Using both accelerated failure time (AFT) and Cox proportional hazard models, the data are best described by models incorporating variation among birth cohorts and greater mortality hazard with increasing age. AFT models using Weibull distributions with the shape parameter > 1 were always the best-fitting models. 2. Shared frailty models allowing for family structure greatly reduce model deviance. The best-fitting models included a term for frailty shared by maternal families. 3. To ask how long a data set must be to reach qualitatively the same conclusions, we repeated the analyses for all possible truncated data sets of 2 years in length or greater. Length of the data set affects the parameter estimates, but not the qualitative conclusions. In all but three of 337 truncated data sets the best-fitting models pointed to same conclusions as the full data set. Shared frailty models appear to be quite robust. 4. The data are not adequate for testing hypotheses as to whether variation in frailty is heritable. 5. Substantial structured heterogeneity for survival exists in this population. Such structured heterogeneity has been shown to have substantial effects in reducing demographic stochasticity. [ABSTRACT FROM AUTHOR]

1. The effects of changes in habitat size and quality on the expected population density and the expected time to extinction of Sorex araneus are studied by means of mathematical models that incorporate demographic stochasticity. 2. Habitat size is characterized by the number of territories, while habitat quality is represented by the expected number of offspring produced during the lifetime of an individual. 3. The expected population density of S. araneus is shown to be mainly influenced by the habitat size. The expected time to extinction of S. araneus populations due to demographic stochasticity, on the other hand, is much more affected by the habitat quality. 4. In a more general setting we demonstrate that, irrespective of the actual species under consideration, the likelihood of extinction as a consequence of demographic stochasticity is more effectively countered by increasing the reproductive success and survival of individuals then by increasing total population size. [ABSTRACT FROM AUTHOR]