Energetic trade-offs in migration decision-making, reproductive effort and subsequent parental care in a long-distance migratory bird.

Migratory species trade-off long-distance movement with survival and reproduction, but the spatio-temporal scales at which these decisions occur are relatively unknown. Technological and statistical advances allow fine-scale study of animal decision-making, improving our understanding of possible causes and therefore conservation management. We quantified effects of reproductive preparation during spring migration on subsequent breeding outcomes, breeding outcomes on autumn migration characteristics and autumn migration characteristics on subsequent parental survival in Greenland white-fronted geese (Anser albifrons flavirostris). These are long-distance migratory birds with an approximately 50% population decline from 1999 to 2022. We deployed GPS-acceleration devices on adult females to quantify up to 5 years of individual decision-making throughout the annual cycle. Weather and habitat-use affected time spent feeding and overall dynamic body acceleration (i.e. energy expenditure) during spring and autumn. Geese that expended less energy and fed longer during spring were more likely to successfully reproduce. Geese with offspring expended more energy and fed for less time during autumn, potentially representing adverse fitness consequences of breeding. These behavioural comparisons among Greenland white-fronted geese improve our understanding of fitness trade-offs underlying abundance. We provide a reproducible framework for full annual cycle modelling using location and behaviour data, applicable to similarly studied migratory animals.

Differing drivers of decline within a migratory metapopulation has implications for future conservation.

Researchers generally ascribe demographic drivers in a single sub-population and presume they are representative. With this information, practitioners implement blanket conservation measures across metapopulations to reverse declines. However, such approaches may not be appropriate in circumstances where sub-populations are spatiotemporally segregated and exposed to different environmental variation. The Greenland White-fronted Goose, Anser albifrons flavirostris, is an Arctic-nesting migrant that largely comprises two sub-populations (delineated by northerly and southerly breeding areas in west Greenland). The metapopulation has declined since 1999 but this trend is only mirrored in one sub-population and the causes of this disparity are unclear. Here we compare the drivers and trends of productivity in both sub-populations using population- and individual-level analysis. We examined how temperature and precipitation influenced population-level reproductive success over 37 years and whether there was a change in the relationship when metapopulation decline commenced. In addition, we used biologging devices to remotely classify incubation events for 86 bird-years and modelled how phenology and environmental conditions influenced individual-level nest survival. Correlations between reproductive success and temperature/precipitation on the breeding grounds have weakened for both sub-populations. This has resulted in lower reproductive success for the northerly, but not southerly breeding sub-population, which at the individual-level appears to be driven by lower nest survival. Earlier breeding ground arrival and less precipitation during incubation increased nest survival in the northerly breeding population, while no factors examined were important for the southerly breeding sub-population. This suggests reproductive success is driven by different factor(s) in the two sub-populations. Demographic rates and their environmental drivers differ between the sub-populations examined here and consequently we encourage further decomposition of demography within metapopulations. This is important for conservation practitioners to consider as bespoke conservation strategies, targeting different limiting factors, may be required for different sub-populations.

Long-term trends in grassland bird relative abundance on focal grassland landscapes in Missouri.

North American grassland birds have widely declined over the past 50 years, largely due to anthropogenic-driven loss of native prairie habitat. In response to these declines, many conservation programs have been implemented to help secure wildlife habitat on private and public lands. The Grasslands Coalition is one such initiative established to advance the conservation of grassland birds in Missouri. The Missouri Department of Conservation conducted annual point count surveys for comparison of grassland bird relative abundance between focal grassland areas and nearby paired (i.e., containing no targeted management) sites. We analyzed 17 years of point count data with a generalized linear mixed model in a Bayesian framework to estimate relative abundance and trends across focal or paired sites for nine bird species of management interest that rely on grasslands: barn swallow (Hirundo rustica), brown-headed cowbird (Molothrus ater), dickcissel (Spiza americana), eastern meadowlark (Sturnella magna), grasshopper sparrow (Ammodramus savannarum), Henslow's sparrow (A. henslowii), horned lark (Eremophila alpestris), northern bobwhite (Colinus virginianus), and red-winged blackbird (Agelaius phoeniceus). Relative abundance of all species except eastern meadowlarks declined regionally. Relative abundance of barn swallows, brown-headed cowbirds, dickcissels, eastern meadowlarks, Henslow's sparrows, and northern bobwhites was higher in focal than paired sites, though relative abundance trends were only improved in focal vs. paired areas for dickcissels and Henslow's sparrows. Relative abundance increased with increasing grassland cover at the local (250-m radius) scale for all species except horned larks and red-winged blackbirds and at the landscape (2,500-m radius) scale for all species except dickcissels, eastern meadowlarks, and northern bobwhites. Our results suggest focal areas contained greater relative abundances of several grassland species of concern, likely due to increased availability of grassland habitat at local and landscape scales. Further efforts to decrease landscape-scale fragmentation and improve habitat quality may be needed to achieve conservation goals.

Joint use of location and acceleration data reveals influences on transitions among habitats in wintering birds.

Quantifying relationships between animal behavior and habitat use is essential to understanding animal decision-making. High-resolution location and acceleration data allows unprecedented insights into animal movement and behavior. These data types allow researchers to study the complex linkages between behavioral plasticity and habitat distribution. We used a novel Markov model in a Bayesian framework to quantify the influence of behavioral state frequencies and environmental variables on transitions among landcover types through joint use of location and tri-axial accelerometer data. Data were collected from 56 greater white-fronted geese (Anser albifrons frontalis) across seven ecologically distinct winter regions over two years in midcontinent North America. We showed that goose decision-making varied across landcover types, ecoregions, and abiotic conditions, and was influenced by behavior. We found that time spent in specific behaviors explained variation in the probability of transitioning among habitats, revealing unique behavioral responses from geese among different habitats. Combining GPS and acceleration data allowed unique study of potential influences of an ongoing large-scale range shift in the wintering distribution of a migratory bird across midcontinent North America. We anticipate that behavioral adaptations among variable landscapes is a likely mechanism explaining goose use of highly variable ecosystems during winter in ways which optimize their persistence.

Time-varying effects of local weather on behavior and probability of breeding deferral in two Arctic-nesting goose populations.

Arctic-nesting geese face energetic challenges during spring migration, including ecological barriers and weather conditions (e.g., precipitation and temperature), which in long-lived species can lead to a trade-off to defer reproduction in favor of greater survival. We used GPS location and acceleration data collected from 35 greater white-fronted geese of the North American midcontinent and Greenland populations at spring migration stopovers, and novel applications of Bayesian dynamic linear models to test daily effects of minimum temperature and precipitation on energy expenditure (i.e., overall dynamic body acceleration, ODBA) and proportion of time spent feeding (PTF), then examined the daily and additive importance of ODBA and PTF on probability of breeding deferral using stochastic antecedent models. We expected distinct responses in behavior and probability of breeding deferral between and within populations due to differences in stopover area availability. Time-varying coefficients of weather conditions were variable between ODBA and PTF, and often did not show consistent patterns among birds, indicating plasticity in how individuals respond to conditions. An increase in antecedent ODBA was associated with a slightly increased probability of deferral in midcontinent geese but not Greenland geese. Probability of deferral decreased with increased PTF in both populations. We did not detect any differentially important time periods. These results suggest either that movements and behavior throughout spring migration do not explain breeding deferral or that ecological linkages between bird decisions during spring and subsequent breeding deferral were different between populations and across migration but occurred at different time scales than those we examined.

Carry-over effects of weather and decision-making on nest success of a migratory shorebird.

Weather conditions experienced by birds can influence their migration decision-making and strategy both within and across seasons. Additionally, decision-making during migration may influence subsequent fitness (reproductive success and/or survival). Examining the effects of fine-scale weather variables on individuals throughout the year could help identify stages of the annual cycle when species may be most affected by weather. In this study, we captured 24 black-bellied plovers (gray plovers; Pluvialis squatarola) on nonbreeding areas along the western Gulf of Mexico coast and tracked their locations once every 2 h through their breeding season in the Alaskan and Canadian Arctic. We quantified migration strategies and weather conditions experienced by each individual throughout the nonbreeding, northward migration, and breeding seasons. We used a Bayesian hierarchical model which connected regressions linking weather with migration metrics, and migration metrics and breeding season weather with reproductive success. We found strong negative relationships between two migration metrics (migration duration and number of stopovers) and reproductive success, but no substantial relationships between breeding season weather variables and reproductive success. We found negative relationships between nonbreeding season temperature, migration temperature, and migration NDVI and both migration duration and number of stopovers, in addition to positive relationships between the number of stopovers and storms during migration, migration duration, and nonbreeding season precipitation. These results suggest that reproductive success is influenced by weather throughout the annual cycle and migration strategy is a key mechanism through which these effects operate. Our findings suggest that environmental factors throughout the year influence shorebird fitness, and, because black-bellied plovers are often associated with mixed-species flocks, many species likely experience similar constraints.

Joint analysis of structured and semi-structured community science data improves precision of relative abundance but not trends in birds.

Estimating absolute and relative abundance of wildlife populations is critical to addressing ecological questions and conservation needs, yet obtaining reliable estimates can be challenging because surveys are often limited spatially or temporally. Community science (i.e., citizen science) provides opportunities for semi-structured data collected by the public (e.g., eBird) to improve capacity of relative abundance estimation by complementing structured survey data collected by trained observers (e.g., North American breeding bird survey [BBS]). We developed two state-space models to estimate relative abundance and population trends: one using BBS data and the other jointly analyzing BBS and eBird data. We applied these models to seven bird species with diverse life history characteristics. Joint analysis of eBird and BBS data improved precision of mean and year-specific relative abundance estimates for all species, but the BBS-only model produced more precise trend estimates compared to the joint model for most species. The relative abundance estimates of the joint model were particularly more precise than the BBS-only estimates in areas where species detectability was low resulting from either low BBS survey effort or low abundance. These results suggest that community science data can be a valuable resource for cost-effective improvement in wildlife abundance estimation.

Relative effects of sample size, detection probability, and study duration on estimation in integrated population models.

Understanding mechanistic causes of population change is critical for managing and conserving species. Integrated population models (IPMs) allow for quantifying population changes while directly relating environmental drivers to vital rates, but power of IPMs to detect trends and environmental effects on vital rates remains understudied. We simulated data for an IPM fewer than 41 scenarios to determine the power to detect trends and environmental effects on vital rates based on study duration, sample size, detection probability, and effect size. Our results indicated that temporal duration of a study and effect size, rather than sample size of each individual data set or detection probability, had the greatest influence on the power to identify trends in adult survival and fecundity. When using only 10 years of data, we were unable to identify a 50% increase in adult survival but were able to identify this increase with 22 years of data. When using only capture-recapture data in a traditional Cormack-Jolly-Seber analysis, we lacked sufficient power to identify trends in survival, and power of the Cormack-Jolly-Seber model was always less than the IPM. The IPM had greater power to identify trends and environmental effects on fecundity (e.g., we detected a 58% change in fecundity using 12 years of data). Models with effects of environmental variables on vital rates had less power than trends, likely to be due to increased annual variation in the vital rate when modeling responses to environmental effects that varied by year. Lack of power in the Cormack-Jolly-Seber analysis could be due to the relatively small variability in adult survival compared with fecundity, given the life history of our simulated species. As interannual variation in environmental conditions will probably increase with climate change, this type of analysis can help to inform the study duration needed, which may be a shifting target given future climate uncertainty and the complex nature of environmental correlations with demography.

Compensation for wind drift prevails for a shorebird on a long-distance, transoceanic flight.

BACKGROUND: Conditions encountered en route can dramatically impact the energy that migratory species spend on movement. Migratory birds often manage energetic costs by adjusting their behavior in relation to wind conditions as they fly. Wind-influenced behaviors can offer insight into the relative importance of risk and resistance during migration, but to date, they have only been studied in a limited subset of avian species and flight types. We add to this understanding by examining in-flight behaviors over a days-long, barrier-crossing flight in a migratory shorebird. METHODS: Using satellite tracking devices, we followed 25 Hudsonian godwits (Limosa haemastica) from 2019-2021 as they migrated northward across a largely transoceanic landscape extending > 7000 km from Chiloé Island, Chile to the northern coast of the Gulf of Mexico. We identified in-flight behaviors during this crossing by comparing directions of critical movement vectors and used mixed models to test whether the resulting patterns supported three classical predictions about wind and migration. RESULTS: Contrary to our predictions, compensation did not increase linearly with distance traveled, was not constrained during flight over open ocean, and did not influence where an individual ultimately crossed over the northern coast of the Gulf of Mexico at the end of this flight. Instead, we found a strong preference for full compensation throughout godwit flight paths. CONCLUSIONS: Our results indicate that compensation is crucial to godwits, emphasizing the role of risk in shaping migratory behavior and raising questions about the consequences of changing wind regimes for other barrier-crossing aerial migrants.

Integrated population modelling reveals potential drivers of demography from partially aligned data: a case study of snowy plover declines under human stressors.

Knowledge of demography is essential for understanding wildlife population dynamics and developing appropriate conservation plans. However, population survey and demographic data (e.g., capture-recapture) are not always aligned in space and time, hindering our ability to robustly estimate population size and demographic processes. Integrated population models (IPMs) can provide inference for population dynamics with poorly aligned but jointly analysed population and demographic data. In this study, we used an IPM to analyse partially aligned population and demographic data of a migratory shorebird species, the snowy plover (Charadrius nivosus). Snowy plover populations have declined dramatically during the last two decades, yet the demographic mechanisms and environmental drivers of these declines remain poorly understood, hindering development of appropriate conservation strategies. We analysed 21 years (1998-2018) of partially aligned population survey, nest survey, and capture-recapture-resight data in three snowy plover populations (i.e., Texas, New Mexico, Oklahoma) in the Southern Great Plains of the US. By using IPMs we aimed to achieve better precision while evaluating the effects of wetland habitat and climatic factors (minimum temperature, wind speed) on snowy plover demography. Our IPM provided reasonable precision for productivity measures even with missing data, but population and survival estimates had greater uncertainty in years without corresponding data. Our model also uncovered the complex relationships between wetland habitat, climate, and demography with reasonable precision. Wetland habitat had positive effects on snowy plover productivity (i.e., clutch size and clutch fate), indicating the importance of protecting wetland habitat under climate change and other human stressors for the conservation of this species. We also found a positive effect of minimum temperature on snowy plover productivity, indicating potential benefits of warmth during night on their population. Based on our results, we suggest prioritizing population and capture-recapture surveys for understanding population dynamics and underlying demographic processes when data collection is limited by time and/or financial resources. Our modelling approach can be used to allocate limited conservation resources for evidence-based decision-making.

Northern bobwhite select for shrubby thickets interspersed in grasslands during fall and winter.

Resource selection is a key component in understanding the ecological processes underlying population dynamics, particularly for species such as northern bobwhite (Colinus virginianus), which are declining across their range in North America. There is a growing body of literature quantifying breeding season resource selection in bobwhite; however, winter information is particularly sparse despite it being a season of substantial mortality. Information regarding winter resource selection is necessary to quantify the extent to which resource requirements are driving population change. We modeled bobwhite fall and winter resource selection as a function of vegetation structure, composition, and management from traditionally (intensively) managed sites and remnant (extensively managed) grassland sites in southwest Missouri using multinomial logit discrete choice models in a Bayesian framework. We captured 158 bobwhite from 67 unique coveys and attached transmitters to 119 individuals. We created 671 choice sets comprised of 1 used location and 3 available locations. Bobwhite selected for locations which were closer to trees during the winter; the relative probability of selection decreased from 0.45 (85% Credible Interval [CRI]: 0.17-0.74) to 0.00 (85% CRI: 0.00-0.002) as distance to trees ranged from 0-313 m. The relative probability of selection increased from near 0 (85% CRI: 0.00-0.01) to 0.33 (85% CRI: 0.09-0.56) and from near 0 (85% CRI: 0.00-0.00) to 0.51 (85% CRI: 0.36-0.71) as visual obstruction increased from 0 to 100% during fall and winter, respectively. Bobwhite also selected locations with more woody stems; the relative probability of selection increased from near 0.00 (85% CRI: 0.00-0.002) to 0.30 (85% CRI: 0.17-0.46) and near 0.00 (85% CRI: 0.00-0.001) to 0.35 (85% CRI: 0.22-0.55) as stem count ranged from 0 to 1000 stems in fall and winter, respectively. The relative probability of selection also decreased from 0.35 (85% CRI: 0.20-0.54) to nearly 0 (85% CRI: 0.00-0.001) as percent grass varied from 0 to 100% in fall. We suggest that dense shrub cover in close proximity to native grasslands is an important component of fall and winter cover given bobwhite selection of shrub cover and previously reported survival benefits in fall and winter.

Resource selection and movement by northern bobwhite broods varies with age and explains survival.

Resource selection is a dynamic process driven by habitat valuation and risk avoidance in heterogeneous landscapes. Resource selection and movement decisions of individuals may be sensitive to intrinsic factors, such as body condition, and variation in these choices may have consequences on subsequent survival. We evaluated northern bobwhite (Colinus virginianus) brood resource selection patterns to quantify utility of different cover types during the development period using integrated step-selection analysis in a Bayesian hierarchical modeling framework with three brood stages: flightless broods ≤ 14 days old, dependent broods 15-35 days old, and independent broods over 35 days old. Broods showed strongest selection for native grasslands that were burned and grazed at least once in the previous two years, and agricultural fields. Brood mobility improved with age; broods > 35 days old travelled farther on average and took daily steps > 200 m more frequently than younger broods. Young broods ≤ 14 days old did not select for idle native grasslands, while broods > 35 days old did select for that cover type. Young broods also selected areas farther from trees compared to older broods. We evaluated the survival consequences of resource selection by comparing patterns in choices of broods that succeeded to choices of broods that failed to survive to 35 days. Successful broods chose habitats with more shrub cover and areas farther from trees compared to failed broods. Our results suggest that conservation planning should consider age-specific patterns in habitat use and demographic consequences of habitat choice for greatest effectiveness.

Winter fidelity, movements, and energy expenditure of Midcontinent Greater White-fronted Geese.

BACKGROUND: Animal movement patterns are the result of both environmental and physiological effects, and the rates of movement and energy expenditure of given movement strategies are influenced by the physical environment an animal inhabits. Greater white-fronted geese in North America winter in ecologically distinct regions and have undergone a large-scale shift in wintering distribution over the past 20 years. White-fronts continue to winter in historical wintering areas in addition to contemporary areas, but the rates of movement among regions, and energetic consequences of those decisions, are unknown. Additionally, linkages between wintering and breeding regions are generally unknown, and may influence within-winter movement rates. METHODS: We used Global Positioning System and acceleration data from 97 white-fronts during two winters to elucidate movement characteristics, model regional transition probabilities using a multistate model in a Bayesian framework, estimate regional energy expenditure, and determine behavior time-allocation influences on energy expenditure using overall dynamic body acceleration and linear mixed-effects models. We assess the linkages between wintering and breeding regions by evaluating the winter distributions for each breeding region. RESULTS: White-fronts exhibited greater daily movement early in the winter period, and decreased movements as winter progressed. Transition probabilities were greatest towards contemporary winter regions and away from historical wintering regions. Energy expenditure was up to 55% greater, and white-fronts spent more time feeding and flying, in contemporary wintering regions compared to historical regions. White-fronts subsequently summered across their entire previously known breeding distribution, indicating substantial mixing of individuals of varying breeding provenance during winter. CONCLUSIONS: White-fronts revealed extreme plasticity in their wintering strategy, including high immigration probability to contemporary wintering regions, high emigration from historical wintering regions, and high regional fidelity to western regions, but frequent movements among eastern regions. Given that movements of white-fronts trended toward contemporary wintering regions, we anticipate that a wintering distribution shift eastward will continue. Unexpectedly, greater energy expenditure in contemporary wintering regions revealed variable energetic consequences of choice in wintering region and shifting distribution. Because geese spent more time feeding in contemporary regions than historical regions, increased energy expenditure is likely balanced by increased energy acquisition in contemporary wintering areas.

Partial and complete dependency among data sets has minimal consequence on estimates from integrated population models.

Integrated population models (IPMs) are widely used to combine disparate data sets in joint analysis to better understand population dynamics and provide guidance for conservation activities. An often-cited assumption of IPMs is independence among component data sets within the combined likelihood. Dependency among data sets should lead to underestimation of variance and bias because individuals contribute data to more than one data set. In practice, studied individuals often occur in multiple data sets in IPMs (i.e., overlap), which is one way for the independence assumption to be violated. Such cases have the potential to dissuade practitioners and limit application of IPMs to solve emerging ecological problems. We assessed precision and bias of demographic rates estimated from IPMs using a complete gradient (0-100%) of overlap among data sets, wide ranges in demographic rates (e.g., survival 0.1-0.8) and sample sizes (100-1,200 individuals) and variable data sources. We compared results from our simulations with those from IPMs constructed using empirical data on tree swallows (Tachycineta bicolor) where data sets either had complete overlap or included different individuals. Contrary to previous investigators, we found no substantive bias or uncertainty in any demographic rate from IPMs derived from data sets with complete overlap. While variability in demographic rates was greater at low sample sizes (i.e., low capture, recapture, and survey probabilities), there were negligible differences in the posterior mean or root mean square error of demographic rates among IPMs with strong dependence vs. complete independence among data sets. Our simulations suggest IPMs can be designed using only capture-recapture data or harvest and capture-recovery data where population estimates are obtained from the same data as survival and productivity data. While we encourage researchers to carefully consider the modeling approach best suited for their data sets, our results suggest that dependence among data sets does not generally compromise IPM estimates. Thus, violation of the independence assumption should not dissuade researchers from the application of IPMs in ecological research.

Assessing bias in demographic estimates from joint live and dead encounter models.

Joint encounter (JE) models estimate demographic rates using live recapture and dead recovery data. The extent to which limited recapture or recovery data can hinder estimation in JE models is not completely understood. Yet limited data are common in ecological research. We designed a series of simulations using Bayesian multistate JE models that spanned a large range of potential recapture probabilities (0.01-0.90) and two reported mortality probabilities (0.10, 0.19). We calculated bias by comparing estimates against known probabilities of survival, fidelity and reported mortality. We explored whether sparse data (i.e., recapture probabilities <0.02) compromised inference about survival by comparing estimates from dead recovery (DR) and JE models using an 18-year data set from a migratory bird, the lesser snow goose (Anser caerulescens caerulescens). Our simulations showed that bias in probabilities of survival, fidelity and reported mortality was relatively low across a large range of recapture probabilities, except when recapture and reported mortality probabilities were both lowest. While bias in fidelity probability was similar across all recapture probabilities, the root mean square error declined substantially with increased recapture probabilities for reported mortality probabilities of 0.10 or 0.19, as expected. In our case study, annual survival probabilities for adult female snow geese were similar whether estimated with JE or DR models, but more precise from JE models than those from DR models. Thus, our simulated and empirical data suggest acceptably minimal bias in survival, fidelity or reported mortality probabilities estimated from JE models. Even a small amount of recapture information provided adequate structure for JE models, except when reported mortality probabilities were <0.10. Thus, practitioners with limited recapture data should not be discouraged from use of JE models. We recommend that ecologists incorporate other data types as frequently as analytically possible, since precision of focal parameters is improved, and additional parameters of interest can be estimated.

Land-use change increases climatic vulnerability of migratory birds: Insights from integrated population modelling.

Knowledge of land-use patterns that could affect animal population resiliency or vulnerability to environmental threats such as climate change is essential, yet the interactive effects of land use and climate on demography across space and time can be difficult to study. This is particularly true for migratory species, which rely on different landscapes throughout the year. Unlike most North American migratory waterfowl, populations of northern pintails (Anas acuta; hereafter pintails) have not recovered since the 1980s despite extended periods of abundant flooded wetlands (i.e. ponds). The mechanisms and drivers involved in this discrepancy remain poorly understood. While pintails are similar to other ducks in their dependence on ponds throughout their annual cycle, their extensive use of croplands for nesting differentiates them and makes them particularly vulnerable to changes in agricultural land use on prairie breeding grounds. Our intent was to quantify how changes in land use and ponds on breeding grounds have influenced pintail population dynamics by developing an integrated population model to analyse over five decades (1961-2014) of band-recovery, breeding population survey, land-use and pond count data. We focused especially on the interactive effects of pond counts and land use on pintail productivity, while accounting for density-dependent processes. Pintail populations responded more strongly to annual variation in productivity than survival. Productivity was positively correlated with pond count and negatively correlated with agricultural intensification. Further, a positive interaction between pond count and agricultural intensification was insufficient to overcome the strong negative effect of agricultural intensification on pintail productivity across nearly all pond counts. The interaction also indicated that pintail populations were more negatively impacted by the decrease in ponds associated with climate change under higher agricultural intensification. Our results indicate that pintail populations have become more vulnerable to climate change under intensified land use, which suggests that future conservation strategies must adapt to these altered relationships. The interactive effects of land use and climate on demography should be considered more frequently in animal ecology, and integrated population models provide an adaptable framework to understand vital rates and their drivers simultaneously.

Integrated population models reveal local weather conditions are the key drivers of population dynamics in an aerial insectivore.

Changes to weather patterns under a warming climate are complex: while warmer temperatures are expected virtually worldwide, decreased mean precipitation is expected at mid-latitudes. Migratory birds depend on broad-scale weather patterns to inform timing of movements, but may be more susceptible to local weather patterns during sedentary periods. We constructed Bayesian integrated population models (IPMs) to assess whether continental or local weather effects best explained population dynamics in an environmentally sensitive aerial insectivorous bird, the tree swallow (Tachycineta bicolor), along a transcontinental gradient from British Columbia to Saskatchewan to New York, and tested whether population dynamics were synchronous among sites. Little consistency existed among sites in the demographic rates most affecting population growth rate or in correlations among rates. Juvenile apparent survival at all sites was stable over time and greatest in New York, whereas adult apparent survival was more variable among years and sites, and greatest in British Columbia and Saskatchewan. Fledging success was greatest in Saskatchewan. Local weather conditions explained significant variation in adult survival in Saskatchewan and fledging success in New York, corroborating the hypothesis that local more than continental weather drives the population dynamics of this species and, therefore, demographic synchrony measured at three sites was limited. Nonetheless, multi-population IPMs can be a powerful tool for identifying correlated population trajectories caused by synchronous demographic rates, and can pinpoint the scale at which environmental drivers are responsible for changes. We caution against applying uniform conservation actions for populations where synchrony does not occur or is not fully understood.

Using accelerometry to compare costs of extended migration in an arctic herbivore.

Understanding how individuals manage costs during the migration period is challenging because individuals are difficult to follow between sites; the advent of hybrid Global Positioning System-acceleration (ACC) tracking devices enables researchers to link spatial and temporal attributes of avian migration with behavior for the first time ever. We fitted these devices on male Greenland white-fronted geese Anser albifrons flavirostris wintering at 2 sites (Loch Ken, Scotland and Wexford, Ireland) to understand whether birds migrating further during spring fed more on wintering and staging areas in advance of migration episodes. Although Irish birds flew significantly further (ca. 300 km) than Scottish birds during spring, their cumulative hours of migratory flight, flight speed during migration, and overall dynamic body ACC (i.e., a proxy for energy expenditure) were not significantly different. Further, Irish birds did not feed significantly more or expend significantly more energy in advance of migration episodes. These results suggest broad individual plasticity in this species, although Scottish birds arriving on breeding areas in Greenland with greater energy stores (because they migrated less) may be better prepared for food scarcity, which might increase their reproductive success.

Conditions during adulthood affect cohort-specific reproductive success in an Arctic-nesting goose population.

Variation in fitness between individuals in populations may be attributed to differing environmental conditions experienced among birth (or hatch) years (i.e., between cohorts). In this study, we tested whether cohort fitness could also be explained by environmental conditions experienced in years post-hatch, using 736 lifelong resighting histories of Greenland white-fronted geese (Anser albifrons flavirostris) marked in their first winter. Specifically, we tested whether variation in age at first successful reproduction, the size of the first successful brood and the proportion of successful breeders by cohort was explained by environmental conditions experienced on breeding areas in west Greenland during hatch year, those in adulthood prior to successful reproduction and those in the year of successful reproduction, using North Atlantic Oscillation indices as proxies for environmental conditions during these periods. Fifty-nine (8%) of all marked birds reproduced successfully (i.e., were observed on wintering areas with young) only once in their lifetime and 15 (2%) reproduced successfully twice or thrice. Variation in age at first successful reproduction was explained by the environmental conditions experienced during adulthood in the years prior to successful reproduction. Birds bred earliest (mean age 4) when environmental conditions were 'good' prior to the year of successful reproduction. Conversely, birds successfully reproduced at older ages (mean age 7) if they experienced adverse conditions prior to the year of successful reproduction. Hatch year conditions and an interaction between those experienced prior to and during the year of successful reproduction explained less (marginally significant) variation in age at first successful reproduction. Environmental conditions did not explain variation in the size of the first successful brood or the proportion of successful breeders. These findings show that conditions during adulthood prior to the year of successful reproduction are most important in determining the age at first successful reproduction in Greenland white-fronted geese. Very few birds bred successfully at all (most only once), which suggests that May environmental conditions on breeding areas have cohort effects that influence lifetime (and not just annual) reproductive success.