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Life table response experiments (LTREs) decompose differences in population growth rate between environments into separate contributions from each underlying demographic rate. However, most LTRE analyses make the unrealistic assumption that the relationships between demographic rates and environmental drivers are linear and independent, which may result in diminished accuracy when these assumptions are violated. We extend regression LTREs to incorporate nonlinear (second‐order) terms and compare the accuracy of both approaches for three previously published demographic datasets. We show that the second‐order approach equals or outperforms the linear approach for all three case studies, even when all of the underlying vital rate functions are linear. Nonlinear vital rate responses to driver changes contributed most to population growth rate responses, but life history changes also made substantial contributions. Our results suggest that moving from linear to second‐order LTRE analyses could improve our understanding of population responses to changing environments.

 

Hybridization between taxa generates new pools of genetic variation that can lead to different environmental responses and demographic trajectories over time than seen in parental lineages. The potential for hybrids to have novel environmental tolerances may be increasingly important in mountainous regions, which are rapidly warming and drying due to climate change. Demographic analysis makes it possible to quantify within‐ and among‐species responses to variation in climate and to predict population growth rates as those conditions change. We estimated vital rates and population growth in 13 natural populations of two cinquefoil taxa (Potentilla hippianaandP. pulcherrima) and their hybrid across elevation gradients in the Southern Rockies. Using three consecutive years of environmental and demographic data, we compared the demographic responses of hybrid and parental taxa to environmental variation across space and time. All three taxa had lower predicted population growth rates under warm, dry conditions. However, the magnitude of these responses varied among taxa and populations. Hybrids had consistently lower predicted population growth rates thanP. hippiana. In contrast, hybrid performance relative toP. pulcherrimavaried with population and climate, with the hybrid maintaining relatively stable growth rates while populations ofP. pulcherrimashrank under warm, dry conditions. Our findings demonstrate that hybrids in this system are neither intrinsically unfit nor universally more vigorous than parents, suggesting that the demographic consequences of hybridization are context‐dependent. Our results also imply that shifts to warmer and drier conditions could have particularly negative repercussions forP. pulcherrima, which is currently the most abundant taxon in the study area, possibly as a legacy of more favorable historical climates. More broadly, the distributions of these long‐lived taxa are lagging behind their demographic trajectories, such that the currently less commonP. hippianacould become the most abundant of thePotentillataxa as this region continues to warm and dry.

 

Abstract Standard procedures for capture–mark–recapture modelling (CMR) for the study of animal demography include running goodness-of-fit tests on a general starting model. A frequent reason for poor model fit is heterogeneity in local survival among individuals captured for the first time and those already captured or seen on previous occasions. This deviation is technically termed a transience effect. In specific cases, simple, uni-state CMR modeling showing transients may allow researchers to assess the role of these transients on population dynamics. Transient individuals nearly always have a lower local survival probability, which may appear for a number of reasons. In most cases, transients arise due to permanent dispersal, higher mortality, or a combination of both. In the case of higher mortality, transients may be symptomatic of a cost of first reproduction. A few studies working at large spatial scales actually show that transients more often correspond to survival costs of first reproduction rather than to permanent dispersal, bolstering the interpretation of transience as a measure of costs of reproduction, since initial detections are often associated with first breeding attempts. Regardless of their cause, the loss of transients from a local population should lower population growth rate. We review almost 1000 papers using CMR modeling and find that almost 40% of studies fitting the searching criteria (N = 115) detected transients. Nevertheless, few researchers have considered the ecological or evolutionary meaning of the transient phenomenon. Only three studies from the reviewed papers considered transients to be a cost of first reproduction. We also analyze a long-term individual monitoring dataset (1988–2012) on a long-lived bird to quantify transients, and we use a life table response experiment (LTRE) to measure the consequences of transients at a population level. As expected, population growth rate decreased when the environment became harsher while the proportion of transients increased. LTRE analysis showed that population growth can be substantially affected by changes in traits that are variable under environmental stochasticity and deterministic perturbations, such as recruitment, fecundity of experienced individuals, and transient probabilities. This occurred even though sensitivities and elasticities of these parameters were much lower than those for adult survival. The proportion of transients also increased with the strength of density-dependence. These results have implications for ecological and evolutionary studies and may stimulate other researchers to explore the ecological processes behind the occurrence of transients in capture–recapture studies. In population models, the inclusion of a specific state for transients may help to make more reliable predictions for endangered and harvested species. 

Conspecific populations living in adjacent but contrasting microenvironments represent excellent systems for studying natural selection. These systems are valuable because gene flow is expected to force genetic homogeneity except at loci experiencing divergent selection. A history of reciprocal transplant and common garden studies in such systems, and a growing number of genomic studies, have contributed to understanding how selection operates in natural populations. While selection can vary across different fitness components and life stages, few studies have investigated how this ultimately affects allele frequencies and the maintenance of divergence between populations. Here, we study two sunflower ecotypes in distinct, adjacent habitats by combining demographic models with genome‐wide sequence data to estimate fitness and allele frequency change at multiple life stages. This framework allows us to estimate that only local ecotypes are likely to experience positive population growth (λ > 1) and that the maintenance of divergent adaptation appears to be mediated via habitat‐ and life stage‐specific selection. We identify genetic variation, significantly driven by loci in chromosomal inversions, associated with different life history strategies in neighbouring ecotypes that optimize different fitness components and may contribute to the maintenance of distinct ecotypes.