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Maternal characteristics, social dynamics, and environmental factors can all influence reproduction and survival and shape trade‐offs that might arise between these components of fitness. Short‐lived mammals like the golden‐mantled ground squirrel (GMGS; Callospermophilus lateralis) tend to maximize effort toward current reproduction at the expense of survival but may be complicated by other aspects of the species' life history and environment. Here, we use 25 years of data (1995–2020) collected from a population of GMGS at the Rocky Mountain Biological Research Laboratory in Gothic, Colorado, to test the effect of several maternal characteristics (e.g., age, experience, and timing of litter emergence), social context (e.g., litter sex ratio and kin density), and environmental context (e.g., date of bare ground and length of vegetative growing season) on survival of reproductive female GMGS using Cox proportional hazard models. Our results indicated that social dynamics (i.e., density) and environmental conditions (i.e., standardized first day of permanent snow cover and length of growing season) explained significant variation in annual maternal survival, while maternal characteristics did not. A higher density of related breeding females and the total number of females (both related and unrelated to the focal mother) were associated with an increase in the mortality hazard. A later standardized date of the first day of permanent snow cover and a shorter growing season both reduced the maternal mortality hazard. Together, our results suggest that factors extrinsic to the squirrels affect maternal survival and thus may also influence local population growth and dynamics in GMGS and other short‐lived, territorial mammal species. We used 25 years of longitudinal data collected from golden‐mantled ground squirrel females to test the effects of individual characteristics, the social context, and the environment on female mortality using Cox proportional hazard models. Both female kin density and the environmental context explained significant variation in female mortality, while individual characteristics did not. Our results suggest that both kin density and climate metrics related to growing season phenology swamp individual characteristics in explaining variability in maternal mortality. This is an important finding in a rather short‐lived species where every additional active season survived has a lot of weight in improving lifetime reproduction. [ABSTRACT FROM AUTHOR]

Global climate change and associated regional climate variability is impacting the phenology of many species, ultimately altering individual fitness and population dynamics. Yet, few studies have considered the effects of pertinent seasonal climate variability on phenology and fitness. Hibernators may be particularly susceptible to changes in seasonal climate since they have a relatively short active season in which to reproduce and gain enough mass to survive the following winter. To understand whether and how seasonal climate variability may be affecting hibernator fitness, we estimated survival from historical (1964–1968) and contemporary (2014–2017) mark–recapture data collected from the same population of Uinta ground squirrels (UGS, Urocitellus armatus), a hibernator endemic to the western United States. Despite a locally warming climate, the phenology of UGS did not change over time, yet season‐specific climate variables were important in regulating survival rates. Specifically, older age classes experienced lower survival when winters or the following springs were warm, while juveniles benefited from warmer winter temperatures. Although metabolic costs decrease with decreasing temperature in the hibernacula, arousal costs increase with decreasing temperature. Our results suggest that this trade‐off is experienced differently by immature and mature individuals. We also observed an increase in population density during that time period, suggesting resources are less limited today than they used to be. Cheatgrass is now dominating the study site and may provide a better food source to UGS than native plants did historically. [ABSTRACT FROM AUTHOR]

Understanding the processes behind change in reproductive state along life-history trajectories is a salient research program in evolutionary ecology. Two processes, state dependence and heterogeneity, can drive the dynamics of change among states. Both processes can operate simultaneously, begging the difficult question of how to tease them apart in practice. The Neutral Theory for Life Histories ( NTLH) holds that the bulk of variations in life-history trajectories is due to state dependence and is hence neutral: Once previous (breeding) state is taken into account, variations are mostly random. Lifetime reproductive success ( LRS), the number of descendants produced over an individual's reproductive life span, has been used to infer support for NTLH in natura. Support stemmed from accurate prediction of the population-level distribution of LRS with parameters estimated from a state dependence model. We show with Monte Carlo simulations that the current reliance of NTLH on LRS prediction in a null hypothesis framework easily leads to selecting a misspecified model, biased estimates and flawed inferences. Support for the NTLH can be spurious because of a systematic positive bias in estimated state dependence when heterogeneity is present in the data but ignored in the analysis. This bias can lead to spurious positive covariance between fitness components when there is in fact an underlying trade-off. Furthermore, neutrality implied by NTLH needs a clarification because of a probable disjunction between its common understanding by evolutionary ecologists and its translation into statistical models of life-history trajectories. Irrespective of what neutrality entails, testing hypotheses about the dynamics of change among states in life histories requires a multimodel framework because state dependence and heterogeneity can easily be mistaken for each other. [ABSTRACT FROM AUTHOR]