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Abstract Phenotypic responses to climate affect individual fitness, but the extent to which this translates into effects on population dynamics remains poorly understood. We assemble 213 time series on phenotypes and population sizes of wild vertebrates globally and match them with local climate data. Our meta-analysis shows that morphological traits are mostly climate insensitive. However, phenology is earlier in warmer-than-average years, which contributes positively to population growth in most species. At lower latitudes, temperature has weaker effects on phenology but stronger direct negative effects on population growth, likely because these populations are less capable of tracking climate via plasticity. Variation in the phenology-mediated effect of temperature on population growth cannot be explained by latitude, generation time, migratory mode, or diet. This suggests that simple relationships between species characteristics and population responses to warming may not occur in nature. Instead, we may need to embrace ecological complexity by considering local-scale predictors that capture intra-specific variation. 

Abstract BackgroundSince the 1980s, Pacific Black Brant (Branta bernicla nigricans, hereafter brant) have shifted their winter distribution northward from Mexico to Alaska (approximately 4500 km) with changes in climate. Alongside this shift, the primary breeding population of brant has declined. To understand the population-level implications of the changing migration strategy of brant, it is important to connect movement and demographic data. Our objectives were to calculate migratory connectivity, a measure of spatial and temporal overlap during the non-breeding period, for Arctic and subarctic breeding populations of brant, and to determine if variation in migration strategies affected nesting phenology and nest survival. MethodsWe derived a migratory network using light-level geolocator migration tracks from an Arctic site (Colville River Delta) and a subarctic site (Tutakoke River) in Alaska. Using this network, we quantified the migratory connectivity of the two populations during the winter. We also compared nest success rates among brant that used different combinations of winter sites and breeding sites. ResultsThe two breeding populations were well mixed during the winter, as indicated by a migratory connectivity score close to 0 (− 0.06) at the primary wintering sites of Izembek Lagoon, Alaska (n = 11 brant) and Baja California, Mexico (n = 48). However, Arctic birds were more likely to migrate the shorter distance to Izembek (transition probability = 0.24) compared to subarctic birds (transition probability = 0.09). Nest survival for both breeding populations was relatively high (0.88–0.92), and we did not detect an effect of wintering site on nest success the following year. ConclusionsNest survival of brant did not differ among brant that used wintering sites despite a 4500 km difference in migration distances. Our results also suggested that the growing Arctic breeding population is unlikely to compensate for declines in the larger breeding population of brant in the subarctic. However, this study took place in 2011–2014 and wintering at Izembek Lagoon may have greater implications for reproductive success under future climate conditions. 

ABSTRACT Population ecology has amassed a significant volume of demographic data across the Tree of Life. Together, these data enable comparative analyses at unprecedented taxonomic and biogeographic scales to examine patterns of demographic performance and their mechanisms. However, macroecological analysis of heterogeneous data and models from diverse study systems comes with risks, and care must be taken to ensure that the patterns from comparative approaches are biologically meaningful, rather than driven by model‐specific artifacts. Recently, a balancing approach has been proposed as a solution to “distorted” population structure, particularly for evaluating transient (short‐term) population dynamics. We argue that some distortion is the result of true biological processes, and that balancing over‐corrects for distortion due to census timing (pre‐ vs. post‐breeding). We lay out the relationship between demographic census design and the issues purported to be solved by balancing. Using a large dataset of carefully‐selected matrix population models from plants and animals, we demonstrate that balancing changes biological interpretation of the relationship between reproductive traits and demographic resilience. We also highlight how application of balancing outside of its narrow original application to transient metrics can be problematic. We argue that meaningful comparisons require tailored approaches that respect the structure and context of demographic data. A more nuanced strategy–based on the biological realities of life cycles, census design, and reproductive strategies–will improve the robustness and interpretation of comparative demographic analyses. 

Abstract Age at first reproduction is an important life‐history trait that marks the beginning of reproductive allocation in long‐lived organisms and drives patterns of life‐history strategies. Demographic factors and environmental conditions likely affect age at first reproduction through multiple pathways: food resources availability and energy storage from birth to recruitment, competition for breeding sites and mate availability.Using a unique 35‐year dataset of individual‐based mark–recapture data from a wandering albatross (Diomedea exulans) population at Crozet (southern Indian Ocean), we investigated how demographic factors and environment influence age at first reproduction. The population experienced major fluctuations, declining by 50% in the 1970s before partially recovering in the 1980s. It was also exposed to important environmental changes, including variations in large‐scale climate phenomena and changes in subtropical anticyclone systems like the Mascarene high pressure system.We used multi‐event hidden Markov models to estimate age‐specific survival and breeding probabilities for each sex separately. From these models, we estimated the age at first reproduction through absorbing Markov chains while accounting for imperfect detection. We investigated how demographic factors (population density at birth and mate availability at recruitment) and environmental conditions (at birth and recruitment) influenced age at first reproduction through their effects on survival and breeding probabilities.Age at first reproduction declined across cohorts for both sexes from 1970 to the mid‐1980s, then stabilized. Females recruited at 9.0 years in early cohorts versus 7.5 years in later ones; males declined from 10.2 to 9.2 years. Environmental conditions at birth, particularly the El Niño Southern Oscillation and the Mascarene high, influenced recruitment timing through delayed effects of natal condition on breeding probability rather than survival. Mate availability strongly facilitated earlier recruitment in both sexes, while natal population density delayed male recruitment specifically.Recruitment timing in wandering albatrosses is shaped primarily by developmental programming during the natal period rather than by immediate environmental triggers at sexual maturity, with mate availability and population density modulating these early‐life effects in sex‐specific ways. Given that recruitment is an important life‐history event linked to population‐level reproductive rates, accurate demographic projections require models accounting for cohort‐specific effects under changing environments. 

Abstract Understanding and predicting the effects of climate change on populations requires linking the environmental conditions to demographic rates and the demographic rates to population‐level consequences, but often this complete demographic pathway is not studied. Integrated population models (IPMs) incorporate demographic data into a single analytical framework, allowing for the inclusion of environmental covariates to test hypotheses considering how the environment influences demographic rates, and consequently, to which demographic rates population growth rate is most sensitive. In birds, there is strong evidence that environmental conditions impact population growth, and that long‐distance migrant avian species with short phenological windows are at greatest risk of population decline due to changing environmental conditions. We built a Bayesian IPM with over 40 years of mark‐recapture, fecundity, and nest box occupancy data and incorporated environmental covariates hypothesized to be driving the observed changes in two populations of a fast‐lived long‐distance migrant, the European pied flycatcher. Using variance decomposition methods, we identified the demographic pathways through which environmental covariates were acting. While several environmental covariates impacted fecundity and survival, only precipitation acted via apparent juvenile and adult survival contributed significantly to variation in population growth rate. Increased precipitation during the nest initiation, incubation, and hatchling stages had negative carry‐over effects on juvenile survival during the post‐fledging and overwintering period, and increased precipitation negatively impacted adult apparent survival, likely due to the increased energetic demands of caring for eggs and hatchlings in challenging conditions and reduced availability of aerial prey. We show that linking environmental covariates to demographic rates does not sufficiently explain or predict population‐level consequences, and that decomposing variation along the complete demographic pathway is a necessary step to appropriately identify how covariates influence population dynamics. 

Abstract Understanding the drivers of fitness is a key goal of population and evolutionary ecology. However, measuring individual variation in demographic components in imperfectly observed populations of wild organisms is extremely challenging. Recent research has demonstrated that estimates of fixed individual variation in Bernoulli variables (e.g., survival and breeding propensity) are often unreliable in the face of imperfect detection and small sample sizes. Thus, we demonstrate the use of structural equation modeling approaches to simultaneously estimate latent variation in demographic performance and link said variation to individual demographic components. We demonstrate the use of this approach with 30+ year capture–recapture datasets collected on two passerine species (white‐throated dipper,Cinclus cinclus, and pied flycatcher,Ficedula hypoleuca) and simultaneously estimate latent variation in individual quality and age‐specific variation in demographic components. We found senescent decline in survival and fecundity in both species and demonstrated strong among‐individual heterogeneity in demographic performance. Notably, the residual reproductive value of older individuals of higher quality was greater than younger individuals of reduced and average quality. We demonstrate that this approach may be useful in a variety of situations, discuss its limitations, and make suggestions for future research. 

Abstract The Yukon‐Kuskokwim Delta has the largest intertidal wetland in North America, is a globally critical breeding area for waterbirds, and is home to the largest regional indigenous population in the Arctic. Here, coastal tundra ecosystems, wildlife, and indigenous communities are highly vulnerable to sea‐ice loss in the Bering Sea, sea‐level rise, storm flooding, erosion, and collapsing ground from permafrost thaw caused by climate warming. These drivers interact in non‐linear ways to increase flooding, salinization, and sedimentation, and thus, alter ecosystem trajectories and broader landscape evolution. Rapid changes in these factors over decadal time scales are highly likely to cause transformative shifts in coastal ecosystems across roughly 70% of the outer delta this century. We project saline and brackish ecotypes on the active delta floodplain with frequent sedimentation will maintain dynamic equilibrium with sea‐level rise and flooding, slightly brackish ecotypes on the inactive floodplain with infrequent flooding and low sedimentation rates will be vulnerable to increased flooding and likely transition to more saline and brackish ecotypes, and fresh lacustrine and lowland ecotypes on the abandoned floodplain with permafrost plateaus will be vulnerable to thermokarst, salinization and flooding that will shift them toward brackish ecosystems. This will greatly affect bird nesting and foraging habitats, with both winners and losers. Already, some Yup'ik communities are facing relocation of their low‐lying villages. The societal challenges and consequences of adapting to these changing landscapes are enormous and will require a huge societal effort. 

ABSTRACT It has recently been recognised that populations are rarely in demographic equilibrium, but rather in a ‘transient’ state. To examine how transient dynamics influence our empirical understanding of the links between changes in demographic rates and population growth, we conducted a 32‐year study of Columbian ground squirrels. The population increased rapidly for 10 years, followed by a 2‐year crash, and a gradual 19‐year recovery. Transient life table response experiment (LTRE) analysis showed that demographic stochasticity accounted for approximately one‐fourth of the variation in population growth, leaving the majority to be explained by environmental influences. These relatively small rodents appeared to have a slow pace of life. But unlike the general pattern for large mammals with slow life histories, ground squirrel survival did not exhibit low variation associated with environmental ‘buffering’; instead, survival varied substantially over time and contributed substantially (78%) to changes in abundance over the long‐term study, with minor contributions from reproduction and unstable stage structure. 

Abstract Estimating correlations among demographic parameters is an important method in population ecology. A recent paper by Deane et al. (Ecology and Evolution13:e9847, 2023) attempted to explore the effects of different priors for covariance matrices on inference when using mark‐recovery data. Unfortunately, Deane et al. (2023) made a mistake when parameterizing some of their models. Rather than exploring the effects of different priors, they examined the effects of the use of incorrect equations on inference. In this manuscript, we clearly describe the mistake in Deane et al. (2023). We then demonstrate the use of an alternative and appropriate method and reach different conclusions regarding the effects of priors on inference. Consistent with other recent literature, informative inverse Wishart priors can lead to flawed inference, while vague priors on covariance matrix components have little impact when sample sizes are adequate. 

ABSTRACT Mortality risk for animals often varies spatially and can be linked to how animals use landscapes. While numerous studies collect telemetry data on animals, the focus is typically on the period when animals are alive, even though there is important information that could be gleaned about mortality risk. We introduce a thinned spatial point process (SPP) modelling framework that couples relative abundance and space use with a mortality process to formally treat the occurrence of mortality events across the landscape as a spatial process. We show how this model can be embedded in a hierarchical statistical framework and fit to telemetry data to make inferences about how spatial covariates drive both space use and mortality risk. We apply the method to two data sets to study the effects of roads and habitat on spatially explicit mortality risk: (1) VHF telemetry data collected for willow ptarmigan in Alaska, and (2) hourly GPS telemetry data collected for black bears in Colorado. These case studies demonstrate the applicability of this method for different species and data types, making it broadly useful in enabling inferences about the mechanisms influencing animal survival and spatial population processes while formally treating survival as a spatial process, especially as the development and implementation of joint analyses continue to progress.