Evolution of allometries in the worker caste of Dorylus army ants

We investigated the effect of local environment on the demography and population dynamics of arctic ground squirrels ( Spermophilus parryii plesius ) by comparing reproduction, survival, and population trends of squirrels living in low elevation boreal forest and high elevation alpine tundra sites in southwestern Yukon Territory, Canada. Contrary to the trend for most birds and mammals, reproduction was significantly lower at the lower elevation and females living at higher elevation did not delay the age at which they first reproduced. Even though survival in the boreal forest was lower in summer than in the alpine, it was higher over winter so annual adult female survival was similar between sites.
Sensitivity analysis of model parameters revealed that in the forest, population growth rate (λ) was most sensitive to small changes in adult active season survival whereas for the alpine population, λ was most sensitive to changes in juvenile winter survival. In their respective habitats, these parameters also showed high year to year variation and thus contributed greatly to the population trends observed. Even though ground squirrels persisted in the boreal forest, the measured demographic rates indicate the forest was sink habitat (λ<1) and may have relied on nearby grassy meadows for immigrants. In contrast, the alpine habitat maintained a ground squirrel population in the absence of immigration (λ=1).
The variation in demographic rates between ground squirrels living at high and low elevation may arise from phenotypic responses of squirrels to different habitat structure. Arctic ground squirrels rely on sight to detect predators from a safe distance, and the boreal forest, with its lower visibility and higher predator density, appears to be suboptimal habitat.     

The joint evolution of seed dormancy and flowering time in annual plants living in variable environments

In annual plants, both seed germination (as opposed to dormancy) and delayed flowering are assumed to confer both greater and more variable reproduction. With this assumption, a simple model of these two characters, together with a reparameterization of survival and reproductive rates and a general approximation, leads to several predictions based on maximizing geometric growth rates. Each character optimum is a ratio of mean to variance of future reproduction, and the two optimums are interdependent, with compensation by one favored if the other changes. Optimal character variances, possible with prediction of future reproduction, are roughly squared correlations of characters with future reproduction, divided by variances of future reproduction. The optimal mean of each character is more sensitive to the other character's variance than to its own variance, and the optimal variance of each character is more sensitive to the other character's mean than to its own mean. Optimal germination is increased with better correlation between flowering time and future reproduction. A diffusion approximation for the single locus, single character genetic analog of the phenotypic model showed fluctuating natural selection to favor, in expectation and under suitable conditions, the allele frequency maximizing the geometric population growth rate. Conditions for a protected polymorphism at a second locus, controlling the other character, show genetic variation at the first locus favors alleles at the second locus adapted to greater environmental variability. Computer simulations check some results, and the general predictions should be relevant for studies of correlated life history characters.     

Survival and population growth of a long-lived threatened snake species, Drymarchon couperi (Eastern Indigo Snake)

Demographic data provide a basis for understanding the life history and ecology of species, factors which are vital for informing conservation efforts; however, little is known regarding the population ecology of most snake species, including the threatened Eastern Indigo Snake (Drymarchon couperi). We used 11 years (1999–2009) of capture-mark-recapture (CMR) and 2.5 years (2003–2005) of radiotelemetry data from southeastern Georgia, USA, in a CMR modeling framework to estimate apparent survival, capture and transition probabilities, and evaluate factors influencing these parameters. The model-averaged estimate of overall apparent annual survival probability was 0.700 (±0.030 SE) and is comparable to that obtained from known fate analysis (radiotelemetry) at the same site. Body size positively influenced survival, regardless of sex. Capture probability differed seasonally by sex, suggesting lower capture probability for females in fall and males in winter. There was no evidence for effect of precipitation or site-specific differences in survival. Model averaged estimate of annual adult survival estimated using multistate CMR models was 0.738 ± 0.030 and 0.515 ± 0.189 for subadults. We estimated population growth rate (λ) and elasticity (proportional sensitivity) of λ to vital rates using a stage-structured matrix population model. Population growth rate ranged from 0.96 to 1.03 depending on the value of the probability of transitioning from subadult to adult stage. The λ was proportionally most sensitive to changes in adult survival rate, followed by subadult survival. Our results suggest that protecting adult snakes and their habitats would result in the highest likelihood of long-term population stability and growth.     

Local population dynamics and the impact of scale and isolation: a study on different little owl populations

The understanding of how variation of demographic rates translates into variation of population growth is a central aim in population ecology. Besides stochastic and deterministic factors, the spatial extent and the isolation of a local population may have an impact on the contribution of the different demographic components. Using long-term demographic data we performed retrospective population analyses of four little owl ( Athene noctua ) populations with differential spatial extent and degree of isolation to assess the contribution of demographic rates to the variation of the growth rate (λ) of each local population and to the difference of λ among populations. In all populations variation of fecundity contributed least to variation of λ, and variation of adult survival contributed most to variation of λ in three of four populations. Between population comparisons revealed that differences mainly stem from differences of immigration and juvenile local survival. The relative importance of immigration to λ tended to decrease with increasing spatial extent and isolation of the local populations. None of the four local populations was self-sustainable. Because the local populations export and import individuals, they can be considered as open recruitment systems in which part of the recruited breeding birds are not produced locally. The spatial extent and the degree of isolation of a local population have an impact on local population dynamics; hence these factors need to be considered in studies about local population dynamics and for deriving conservation measures.     

Spatiotemporal variation in reproductive parameters of yellow-bellied marmots

Spatiotemporal variation in reproductive rates is a common phenomenon in many wildlife populations, but the population dynamic consequences of spatial and temporal variability in different components of reproduction remain poorly understood. We used 43 years (1962–2004) of data from 17 locations and a capture–mark–recapture (CMR) modeling framework to investigate the spatiotemporal variation in reproductive parameters of yellow-bellied marmots (Marmota flaviventris), and its influence on the realized population growth rate. Specifically, we estimated and modeled breeding probabilities of two-year-old females (earliest age of first reproduction), >2-year-old females that have not reproduced before (subadults), and >2-year-old females that have reproduced before (adults), as well as the litter sizes of two-year old and >2-year-old females. Most reproductive parameters exhibited spatial and/or temporal variation. However, reproductive parameters differed with respect to their relative influence on the realized population growth rate (λ). Litter size had a stronger influence than did breeding probabilities on both spatial and temporal variations in λ. Our analysis indicated that λ was proportionately more sensitive to survival than recruitment. However, the annual fluctuation in litter size, abetted by the breeding probabilities, accounted for most of the temporal variation in λ. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Identifying key factors using λ contribution analysis

1. Key factor analysis is widely used as the first step in analysing census data to identify factors responsible for population change, but is generally considered to be flawed. The conceptual problems can be overcome by assessing the effects of variation in the life-history parameters on population growth rate, λ. We refer to this as λ-contribution analysis. The difference from key factor analysis is that now each life history parameter is weighted by the sensitivity of λ to that parameter. The rationale for this modification is that population growth rate is the best available measure of population change.
2. The advantages of the new method are: that it correctly assesses the effects of life history parameters on population growth rate; that birth rates are included in the analysis in a natural way without making arbitrary assumptions about birth rate mortalities; that post-reproductive individuals who do not contribute to population growth rate are zero-weighted; and that the analysis can be applied to populations with overlapping generations.
3. It is proposed that λ-contribution analysis should replace conventional key-factor analysis as the first step in a wider analysis of population change and density dependence. λ-contribution analysis also links census studies of natural populations with the use of life-table response experiments.     

Population dynamics of the rare plant Kosteletzkya pentacarpos (Malvaceae): a nine-year study

Rare plant species have extremely narrow distributions that can be reduced to a single or few populations. The rare long-lived plant Kosteletzkya pentacarpos is one such species because only two extant localities are known in the western Mediterranean. In this study, we analyse the population dynamics over nine years of the only population known in north-east Spain, which is located at the Llobregat delta (Barcelona). We collected basic demographic data to build a transition matrix model. We computed population growth rates λ and their confidence intervals for each year of study. We conducted elasticity and variance decomposition analyses to determine the relative importance of vital rates to overall population dynamics. On average, the K. pentacarpos population exhibited an increasing dynamics. Survivorship of adult plants contributed the most to each λ, whereas temporal variance in fecundity and juvenile fate explained the observed variation in λ. Despite the increasing dynamics of K. pentacarpos , important reductions in fecundity resulting from biotic agents and recruitment owing to habitat limitations are constraints for population growth. We conclude that the knowledge generated in this long-term study should be used to create new K. pentacarpos populations at the Llobregat delta in order to minimize the risk of extinction following catastrophic events that are nearly impossible to predict.  © 2007 The Linnean Society of London, Botanical Journal of the Linnean Society , 2007, 153 , 455–462.     

Population size and survival of the Brazilian Torrent Frog Hylodes heyeri (Anura,Hylodidae)

Population dynamics are influenced by environmental variability and understanding the abundance and persistence of individuals and populations is a fundamental goal of population ecology. Thus, estimating demographic parameters to identify the factors important for population variability is required to understand temporal and spatial dynamics. The stream-living diurnal frog Hylodes heyeri is endemic to the Atlantic Forest of Brazil in the states of Paraná, São Paulo and Santa Catarina. Here we use capture-mark-recapture methods to estimate survival rates and population size of this Brazilian Torrent Frog in Pico do Marumbi State Park, Paraná. We used CJS models for an open population to estimate apparent survival, capturability and population size in two streams. The number of captures during each session was positively correlated with the minimum weekly temperature. Despite that correlation, the most parsimonious model of survival and capturability was the constant model for both parameters, resulting in a monthly survival rate of 0.38 (95% CI = 0.30–0.46). Thus, only the abundance of the frog differed in the two streams (79 vs. 36), with the population size estimate of 187 individuals. Reproduction is seasonal in the Brazilian Torrent Frog and so the low monthly survival rate suggests that animals move over time rather than die, because 38% month⁻¹ survival should result in <1% of the population remaining after 5 months. Thus, researchers must recognize that populations are labile and individuals often move or are washed downstream during heavy rainfall, generating apparently rapid local turnover that is unlikely to reflect true mortality.     

Contrasting age-specific recruitment and survival at different spatial scales: a case study with the European storm petrel

Evolutionary studies on optimal decisions or conservation guidelines are often derived by generalising patterns from a single population, while inter‐population variability in life‐history traits is seldom considered. We investigated here how survival and recruitment probabilities changed with age at different geographical scales using the encounter histories of 5523 European storm petrels from three Mediterranean colonies, and also how our estimates of these parameters might be expected to affect population growth rates using population matrix models. We recorded similar patterns among colonies, but also important biological differences. Local survival, recruitment and breeding success increased with age at all colonies; the most distant of three colonies (Marettimo Is.) showed the largest differences. Strikingly, differences in recruitment were also found between two adjacent colonies (two caves from Benidorm Is.). Birds marked as adults from Marettimo and Benidorm colonies had a different survival, whereas we found no differences within Benidorm. Differences in survival were no longer apparent between the two islands at the end of the study following a reduction in predation by specialist gulls at Benidorm. Since birds marked as fledglings mostly recruited near the end of the study, their overall survival was high and in turn similar among colonies. Results from our population matrix models suggested that different age‐dependent patterns of demographic parameters can lead to similar population growth rates. Variability appeared to be greater for recruitment and the most sensitive parameter was adult survival. Thus conservation actions targeting this vulnerable species should focus on factors influencing adult survival. Differences in survival and recruitment among colonies could reflect the spatial heterogeneity in mortality due to predation and colony‐specific density dependent processes. Results highlight the importance of taking into account the potential spatio‐temporal heterogeneity among populations in vital rates, even in those traits that life‐history theory considers less important in driving population dynamics.     

Cumulative weather effects can impact across the whole life cycle

Predicting how species will be affected by future climatic change requires the underlying environmental drivers to be identified. As vital rates vary over the lifecycle, structured population models derived from statistical environment–demography relationships are often used to inform such predictions. Environmental drivers are typically identified independently for different vital rates and demographic classes. However, these rates often exhibit positive temporal covariance, suggesting that vital rates respond to common environmental drivers. Additionally, models often only incorporate average weather conditions during a single, a priori chosen time window (e.g. monthly means). Mismatches between these windows and the period when the vital rates are sensitive to variation in climate decrease the predictive performance of such approaches. We used a demographic structural equation model (SEM) to demonstrate that a single axis of environmental variation drives the majority of the (co)variation in survival, reproduction, and twinning across six age–sex classes in a Soay sheep population. This axis provides a simple target for the complex task of identifying the drivers of vital rate variation. We used functional linear models (FLMs) to determine the critical windows of three local climatic drivers, allowing the magnitude and direction of the climate effects to differ over time. Previously unidentified lagged climatic effects were detected in this well‐studied population. The FLMs had a better predictive performance than selecting a critical window a priori, but not than a large‐scale climate index. Positive covariance amongst vital rates and temporal variation in the effects of environmental drivers are common, suggesting our SEM–FLM approach is a widely applicable tool for exploring the joint responses of vital rates to environmental change.     

Characterising demographic contributions to observed population change in a declining migrant bird

Populations of Afro‐Palearctic migrant birds have shown severe declines in recent decades. To identify the causes of these declines, accurate measures of both demographic rates (seasonal productivity, apparent survival, immigration) and environmental parameters will allow conservation and research actions to be targeted effectively. We used detailed observations of marked breeding birds from a ‘stronghold’ population of whinchats Saxicola rubetra in England (stable against the declining European trend) to reveal both on‐site and external mechanisms that contribute to population change. From field data, a population model was developed based on demographic rates from 2011 to 2014. Observed population trends were compared to the predicted population trends to assess model‐accuracy and the influence of outside factors, such as immigration. The sensitivity of the projected population growth rate to relative change in each demographic rate was also explored. Against expectations of high productivity, we identified low seasonal breeding success due to nocturnal predation and low apparent first‐year survival, which led to a projected population growth rate (λ) of 0.818, indicating a declining trend. However, this trend was not reflected in the census counts, suggesting that high immigration was probably responsible for buffering against this decline. Elasticity analysis indicated λ was most sensitive to changes in adult survival but with covariance between demographic rates accounted for, most temporal variation in λ was due to variation in productivity. Our study demonstrates that high quality breeding habitat can buffer against population decline but high immigration and low productivity will expose even such stronghold populations to potential decline or abandonment if either factor is unsustainable. First‐year survival also appeared low, however this result is potentially confounded by high natal dispersal. First‐year survival and/or dispersal remains a significant knowledge gap that potentially undermines local solutions aimed at counteracting low productivity.     

Long-term trends in survival of a declining population: the case of the little owl (<Emphasis Type="Italic">Athene noctua</Emphasis>) in the Netherlands

The little owl (Athene noctua) has declined significantly in many parts of Europe, including the Netherlands. To understand the demographic mechanisms underlying their decline, we analysed all available Dutch little owl ringing data. The data set spanned 35 years, and included more than 24,000 ringed owls, allowing detailed estimation of survival rates through multi-state capture–recapture modelling taking dispersal into account. We investigated geographical and temporal variation in age-specific survival rates and linked annual survival estimates to population growth rate in corresponding years, as well as to environmental covariates. The best model for estimating survival assumed time effects on both juvenile and adult survival rates, with average annual survival estimated at 0.258 (SE = 0.047) and 0.753 (SE = 0.019), respectively. Juvenile survival rates decreased with time whereas adult survival rates fluctuated regularly among years, low survival occurring about every 4 years. Years when the population declined were associated with low juvenile survival. More than 60% of the variation in juvenile survival was explained by the increase in road traffic intensity or in average temperature in spring, but these correlations rather reflect a gradual decrease in juvenile survival coinciding with long-term global change than direct causal effects. Surprisingly, vole dynamics did not explain the cyclic dynamics of adult survival rate. Instead, dry and cold years led to low adult survival rates. Low juvenile survival rates, that limit recruitment of first-year breeders, and the regular occurrence of years with poor adult survival, were the most important determinants of the population decline of the little owl.     

On using integral projection models to generate demographically driven predictions of species' distributions: development and validation using sparse data

Knowledge of species' geographic distributions is critical for understanding and forecasting population dynamics, responses to environmental change, biodiversity patterns, and conservation planning. While many suggestive correlative occurrence models have been used to these ends, progress lies in understanding the underlying population biology that generates patterns of range dynamics. Here, we show how to use a limited quantity of demographic data to produce demographic distribution models (DDMs) using integral projection models for size‐structured populations. By modeling survival, growth, and fecundity using regression, integral projection models can interpolate across missing size data and environmental conditions to compensate for limited data. To accommodate the uncertainty associated with limited data and model assumptions, we use Bayesian models to propagate uncertainty through all stages of model development to predictions. DDMs have a number of strengths: 1) DDMs allow a mechanistic understanding of spatial occurrence patterns; 2) DDMs can predict spatial and temporal variation in local population dynamics; 3) DDMs can facilitate extrapolation under altered environmental conditions because one can evaluate the consequences for individual vital rates. To illustrate these features, we construct DDMs for an overstory perennial shrub in the Proteaceae family in the Cape Floristic Region of South Africa. We find that the species' population growth rate is limited most strongly by adult survival throughout the range and by individual growth in higher rainfall regions. While the models predict higher population growth rates in the core of the range under projected climates for 2050, they also suggest that the species faces a threat along arid range margins from the interaction of more frequent fire and drying climate. The results (and uncertainties) are helpful for prioritizing additional sampling of particular demographic parameters along these gradients to iteratively refine projections. In the appendices, we provide fully functional R code to perform all analyses.     

Importance of adult survival, local recruitment and immigration in a declining boreal forest passerine, the willow tit Parus montanus

Population growth rate (λ) and its components (adult survival, local recruitment, immigration and their relative contributions to λ) were studied in the declining willow tit Parus montanus in Northern Finland. Capture–recapture models for open populations were used to estimate the population parameters and their process variation. Adult survival was fairly high with low variation (0.593, CV=0.067). As expected, local recruitment was lower and more variable (0.063, CV=0.610). During the 12-year study, the population growth rate averaged to one (0.988, CV=0.197; calculated as However, if the present processes continue, population projections show that the population is likely to decline. There was considerable temporal variation in the relative contributions of demographic parameters to λ. In all years, adult survival had the highest relative contribution (mean 64%) to the population growth rate and it was the least variable trait. Immigration had a higher relative contribution (22%) to λ than local recruitment (14%). Based on the results for the contributions to λ, the main conservation concern for willow tits is adult survival. Due to low variation, adult survival may be difficult to enhance, but at least it should be prevented from declining. High stochasticity in local recruitment and immigration is probably an inherent characteristic of highly seasonal environments, making these traits difficult to address for conservation practices.     

A STAGE-BASED MODEL OF MANATEE POPULATION DYNAMICS

A stage-structured population model for the Florida manatee ( Trichechus manatus latirostris ) was developed that explicitly incorporates uncertainty in parameter estimates. The growth rates calculated with this model reflect the status of the regional populations over the most recent 10-yr period. The Northwest and Upper St. Johns River regions have growth rates (λ) of 1.037 (95% interval, 1.016–1.056) and 1.062 (1.037–1.081), respectively. The Southwest region has a growth rate of 0.989 (0.946–1.024), suggesting this population has been declining at about 1.1% per year. The estimated growth rate in the Atlantic region is 1.010 (0.988–1.029), but there is some uncertainty about whether adult survival rates have been constant over the last 10 yr; using the mean survival rates from the most recent 5-yr period, the estimated growth rate in this region is 0.970 (0.938–0.998). Elasticity analysis indicates that the most effective management actions should seek to increase adult survival rates. Decomposition of the uncertainty in the growth rates indicates that uncertainty about population status can best be reduced through increased monitoring of adult survival rate.     

Estimating the growth of a newly established moose population using reproductive value

Estimating the population growth rate and environmental stochasticity of long-lived species is difficult because annual variation in population size is influenced by temporal autocorrelations caused by fluctuations in the age-structure. Here we use the dynamics of the reproductive value to estimate the long-term growth rate s and the environmental variance of a moose population that recently colonized the island of Vega in northern Norway. We show that the population growth rate was high (ŝ=0.26). The major stochastic influences on the population dynamics were due to demographic stochasticity, whereas the environmental variance was not significantly different from 0. This supports the suggestion that population growth rates of polytocous ungulates are high, and that demographic stochasticity must be assessed when estimating the growth of small ungulate populations.     

Sources of variability in spotted owl population growth rate: testing predictions using long-term mark–recapture data

For long-lived iteroparous vertebrates that annually produce few young, life history theory predicts that reproductive output (R) and juvenile survival should influence temporal variation in population growth rate (λ) more than adult survival does. We examined this general prediction using 15 years of mark–recapture data from a population of California spotted owls (Strix occidentalis occidentalis). We found that survival of individuals ≥1 year old (ϕ) exhibited much less temporal variability , where CV is coefficient of variation, than R and that R was strongly influenced by environmental stochasticity. Although λ was most sensitive ( ; log-transformed sensitivity) to ϕ and much less sensitive to either R or juvenile survival (survival rate of owls from fledging to 1 year old; ), we estimated that R contributed as much as ϕ to the observed annual variability in λ. The contribution of juvenile survival to variability in λ was proportional to its These results are consistent with the hypothesis that natural selection may have favored the evolution of longevity in spotted owls as a strategy to increase the probability of experiencing favorable years for reproduction. Our finding that annual weather patterns that most affected R (temperature and precipitation during incubation) and ϕ (conditions during winter related to the Southern Oscillation Index) were equally good at explaining temporal variability in λ supports the conclusion that R and ϕ were equally responsible for variability in λ. Although currently accepted conservation measures for spotted owl populations attempt to enhance survival, our results indicated that conservation measures that target R may be as successful, as long as actions do not reduce ϕ.     

Inferences about population dynamics from count data using multistate models: a comparison to capture–recapture approaches

Wildlife populations consist of individuals that contribute disproportionately to growth and viability. Understanding a population's spatial and temporal dynamics requires estimates of abundance and demographic rates that account for this heterogeneity. Estimating these quantities can be difficult, requiring years of intensive data collection. Often, this is accomplished through the capture and recapture of individual animals, which is generally only feasible at a limited number of locations. In contrast, N‐mixture models allow for the estimation of abundance, and spatial variation in abundance, from count data alone. We extend recently developed multistate, open population N‐mixture models, which can additionally estimate demographic rates based on an organism's life history characteristics. In our extension, we develop an approach to account for the case where not all individuals can be assigned to a state during sampling. Using only state‐specific count data, we show how our model can be used to estimate local population abundance, as well as density‐dependent recruitment rates and state‐specific survival. We apply our model to a population of black‐throated blue warblers (Setophaga caerulescens) that have been surveyed for 25 years on their breeding grounds at the Hubbard Brook Experimental Forest in New Hampshire, USA. The intensive data collection efforts allow us to compare our estimates to estimates derived from capture–recapture data. Our model performed well in estimating population abundance and density‐dependent rates of annual recruitment/immigration. Estimates of local carrying capacity and per capita recruitment of yearlings were consistent with those published in other studies. However, our model moderately underestimated annual survival probability of yearling and adult females and severely underestimates survival probabilities for both of these male stages. The most accurate and precise estimates will necessarily require some amount of intensive data collection efforts (such as capture–recapture). Integrated population models that combine data from both intensive and extensive sources are likely to be the most efficient approach for estimating demographic rates at large spatial and temporal scales.     

Continental Survival and Recovery Rates of Northern Pintails Using Band-Recovery Data

Abstract: Unlike other North American prairie-nesting dabbling ducks, northern pintail (Anas acuta) populations have not increased since the early 1990s and remain well below the long-term average for traditional survey areas. Previously reported estimates of annual survival and recovery rates for pintails did not investigate any spatial or temporal factors to explain annual variation of these rates. We used band-recovery data from 1970 to 2003 to test the influence of temporal periods defined by differing harvest regulations and habitat conditions of breeding grounds with spatially delineated regions on survival and recovery rates of northern pintails in North America. We separated regions based on a multiresponse permutation procedure to identify banding blocks with dissimilar recovery distributions based on a cluster analysis. We categorized time by grouping years into temporal periods based on bag limits, season lengths, or overflight versus nonoverflight years. We used the Brownie approach in Program MARK to evaluate 46 a priori models estimating survival and recovery rates. The best approximating model indicated that survival varied with age, sex, and region with additive time and interactive time-by-age and time-by-region effects. Recovery rate was best represented by a fully interactive term comprised of age, sex, region, and year. There were no statistical differences among average annual survival point estimates between age and sex classes within each region, and our estimates were similar to previous unpublished studies. We found the eastern region had decreased survival and increased recovery rates compared to other regions. Trends in pintail survival suggest that variation in annual survival was not the cause of the initial decrease in the northern pintail population and is unlikely the dominant factor preventing the population from increasing. The influence of other population parameters, such as recruitment rate, should be investigated to further evaluate other causes for the population status of northern pintails. Use of the top-ranked model to estimate annual survival and recovery rates for northern pintails in North America, which indicated that annually varying estimates of survival rates were better supported by the data than grouping years into temporal classes (i.e., based on bag limits, season lengths, and overflight yr) can be used by managers and policy makers when considering annual harvest regulations and effects of conservation efforts. Managers should incorporate these estimates into future demographic studies of pintails as well as consider using the top-ranked model for future analyses of band-recovery data.     

Emigration effects on estimates of age‐ and sex‐specific survival of two sciurids

Age‐ and sex‐specific survival estimates are crucial to understanding important life history characteristics, and variation in these estimates can be a key driver of population dynamics. When estimating survival using Cormack–Jolly–Seber (CJS) models, emigration is typically unknown but confounded with apparent survival. Consequently, especially for populations or age classes with high dispersal rates, apparent survival estimates are often biased low and temporal patterns in survival might be masked when site fidelity varies temporally. We used 9 years of annual mark–recapture data to estimate age‐, sex‐, and time‐specific apparent survival of Humboldt''s flying squirrels (Glaucomys oregonensis) and Townsend''s chipmunks (Neotamias townsendii). For Humboldt''s flying squirrels, these estimates support a small body of research investigating potential variation in survival among age and sex classes, but age‐ and sex‐specific survival has not been evaluated for Townsend''s chipmunks. We also quantified the effects of age‐ and sex‐specific emigration on confounded estimates of apparent survival. Our estimates of juvenile flying squirrel survival were high relative to other small mammal species and estimates for both species were variable among years. We found survival differed moderately among age and sex classes for Humboldt''s flying squirrels, but little among age and sex classes for Townsend''s chipmunks, and that the degree to which emigration confounded apparent survival estimates varied substantially among years. Our results demonstrate that emigration can influence commonly used estimates of apparent survival. Unadjusted estimates confounded the interpretation of differences in survival between age and sex classes and masked potential temporal patterns in survival because the magnitude of adjustment varied among years. We conclude that apparent survival estimators are robust during some time periods; however, when emigration rates vary in time, the effects of emigration should be carefully considered and accounted for.