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The Arctic Ocean is undergoing rapid transformation toward a seasonally ice‐free ecosystem. As ice‐adapted apex predators, polar bears (Ursus maritimus) are challenged to cope with ongoing habitat degradation and changes in their prey base driven by food‐web response to climate warming. Knowledge of polar bear response to environmental change is necessary to understand ecosystem dynamics and inform conservation decisions. In the southern Beaufort Sea (SBS) of Alaska and western Canada, sea ice extent has declined since satellite observations began in 1979 and available evidence suggests that the carrying capacity of the SBS for polar bears has trended lower for nearly two decades. In this study, we investigated the population dynamics of polar bears in Alaska's SBS from 2001 to 2016 using a multistate Cormack–Jolly–Seber mark–recapture model. States were defined as geographic regions, and we used location data from mark–recapture observations and satellite‐telemetered bears to model transitions between states and thereby explain heterogeneity in recapture probabilities. Our results corroborate prior findings that the SBS subpopulation experienced low survival from 2003 to 2006. Survival improved modestly from 2006 to 2008 and afterward rebounded to comparatively high levels for the remainder of the study, except in 2012. Abundance moved in concert with survival throughout the study period, declining substantially from 2003 and 2006 and afterward fluctuating with lower variation around an average of 565 bears (95% Bayesian credible interval [340, 920]) through 2015. Even though abundance was comparatively stable and without sustained trend from 2006 to 2015, polar bears in the Alaska SBS were less abundant over that period than at any time since passage of the U.S. Marine Mammal Protection Act. The potential for recovery is likely limited by the degree of habitat degradation the subpopulation has experienced, and future reductions in carrying capacity are expected given current projections for continued climate warming., As ice‐adapted apex predators, polar bears (Ursus maritimus) are challenged to cope with the ongoing habitat degradation and changes in their prey base driven by food web response to climate warming. We investigated the population dynamics of polar bears in Alaska's southern Beaufort Sea (SBS) using a multistate CJS mark–recapture model. Abundance declined during several consecutive years of poor survival and afterward fluctuated in concert with survival but without sustained trend, averaging 565 bears from 2006 to 2015, the lowest level since passage of the US Marine Mammal Protection Act.

Sea ice loss is fundamentally altering the Arctic marine environment. Yet there is a paucity of data on the adaptability of food webs to ecosystem change, including predator-prey interactions. Polar bears (Ursus maritimus) are an important subsistence resource for Indigenous people and an apex predator that relies entirely on the under-ice food web to meet its energy needs. In this study, we assessed whether polar bears maintained dietary energy density by prey switching in response to spatiotemporal variation in prey availability. We compared the macronutrient composition of diets inferred from stable carbon and nitrogen isotopes in polar bear guard hair (primarily representing summer/fall diet) during periods when bears had low and high survival (2004-2016), between bears that summered on land versus pack ice, and between bears occupying different regions of the Alaskan and Canadian Beaufort Sea. Polar bears consumed diets with lower energy density during periods of low survival, suggesting that concurrent increased dietary proportions of beluga whales (Delphinapterus leucas) did not offset reduced proportions of ringed seals (Pusa hispida). Diets with the lowest energy density and proportions from ringed seal blubber were consumed by bears in the western Beaufort Sea (Alaska) during a period when polar bear abundance declined. Intake required to meet energy requirements of an average free-ranging adult female polar bear was 2.1 kg/day on diets consumed during years with high survival but rose to 3.0 kg/day when survival was low. Although bears that summered onshore in the Alaskan Beaufort Sea had higher-fat diets than bears that summered on the pack ice, access to the remains of subsistence-harvested bowhead whales (Balaena mysticetus) contributed little to improving diet energy density. Because most bears in this region remain with the sea ice year round, prey switching and consumption of whale carcasses onshore appear insufficient to augment diets when availability of their primary prey, ringed seals, is reduced. Our results show that a strong predator-prey relationship between polar bears and ringed seals continues in the Beaufort Sea. The method of estimating dietary blubber using predator hair, demonstrated here, provides a new metric to monitor predator-prey relationships that affect individual health and population demographics.

Polar bears (Ursus maritimus) rely on sea ice for hunting marine mammal prey. Declining sea ice conditions associated with climate warming have negatively affected polar bears, especially in the southern portion of their range. At higher latitudes, the transition from multi-year ice to thinner annual ice has been hypothesized to increase biological productivity and potentially improve polar bear foraging conditions. To investigate this possibility, we used quantitative fatty acid signature analysis to characterize the diet composition of 148 polar bears in two high-latitude subpopulations from 2012 to 2014: (1) Viscount Melville Sound, where little is known about marine mammal ecology, and (2) Northern Beaufort Sea, a subpopulation considered stable with comparatively more ecological data. We used adipose tissue lipid content as an index of body condition. To characterize long-term habitat conditions, we examined trends in sea ice metrics from 1979 to 2014 in both regions. Although the diets of bears in both subpopulations were dominated by ringed seal (Pusa hispida, mean biomass consumption = 45%), bears in Viscount Melville Sound showed higher proportional consumption of beluga whale (Delphinapterus leucas; mean biomass consumption = 37%) than any other polar bear subpopulation studied to date. Although the three-year duration of our study precludes long-term insights, relatively lighter sea ice conditions in Viscount Melville Sound were associated with reduced consumption of preferred prey (i.e., ringed seal), especially among female polar bears. Further, polar bears in Viscount Melville sound were in poorer body condition than those in the Northern Beaufort Sea. Our results do not indicate that declining sea ice has had any positive effect on polar bear foraging at high-latitudes.

Polar bears (Ursus maritimus) are experiencing loss of sea ice habitats used to access their marine mammal prey. Simultaneously, ocean warming is changing ecosystems that support marine mammal populations. The interactive effects of sea ice and prey are not well understood yet may explain spatial-temporal variation in the response of polar bears to sea ice loss. Here, we examined the potential combined effects of sea ice, seal body condition, and atmospheric circulation patterns on the body condition, recruitment, diet, and feeding probability of 469 polar bears captured in the Chukchi Sea, 2008-2017. The body condition of ringed seals (Pusa hispida), the primary prey of females and subadults, was related to dietary proportions of ringed seal, feeding probability, and the body condition of females and cubs. In contrast, adult males consumed more bearded seals (Erignathus barbatus) and exhibited better condition when bearded seal body condition was higher. The litter size, number of yearlings per adult female, and the condition of dependent young were higher following winters characterized by low Arctic Oscillation conditions, consistent with a growing number of studies. Body condition, recruitment, and feeding probability were either not associated or negatively associated with sea ice conditions, suggesting that, unlike some subpopulations, Chukchi Sea bears are not currently limited by sea ice availability. However, spring sea ice cover declined 2% per year during our study reaching levels not previously observed in the satellite record and resulting in the loss of polar bear hunting and seal pupping habitat. Our study suggests that the status of ice seal populations is likely an important factor that can either compound or mitigate the response of polar bears to sea ice loss over the short term. In the long term, neither polar bears nor their prey are likely robust to limitless loss of their sea ice habitat.

A key aspect in the use of fatty acids (FA) to estimate predator diets using quantitative FA signature analysis (QFASA) is the ability to account for FA assimilation through the use of calibration coefficients (CC). Here, we tested the assumption that CC are independent of dietary fat concentrations by feeding Atlantic pollock (Pollachius virens) three formulated diets with very similar FA proportions but different fat concentrations (5–9% of diet) for 20 weeks. CC calculated using FA profiles of diet and triacylglycerols in pollock liver were significantly different for the three diets. To test the robustness of diet estimates to these differences, we used the CC set derived from feeding the diet with the lowest fat concentration, published prey FA profiles and realistic diet estimates of pollock to construct ‘pseudo-predators'. Application of QFASA to each pseudo-predator using the three sets of CC and the same prey FA profiles resulted in diet estimate biases of twofold for major prey items and approximately fivefold for minor prey items. This work illustrates the importance of incorporating diets with fat concentrations that are similar to natural prey when conducting feeding experiments to calculate CC. This article is part of the theme ‘The next horizons for lipids as ‘trophic biomarkers': evidence and significance of consumer modification of dietary fatty acids'.

In the Arctic, warming air and ocean temperatures have resulted in substantial changes to sea ice, which is primary habitat for polar bears (Ursus maritimus). Reductions in extent, duration, and thickness have altered sea ice dynamics, which influences the ability of polar bears to reliably access marine mammal prey. Because nutritional condition is closely linked to population vital rates, a progressive decline in access to prey or an increase in the energetic cost of accessing prey has the potential to adversely affect polar bear population dynamics. We examined long-term (1983–2015) patterns of spring body condition (indexed using residual body mass) and maternal investment (i.e., litter mass of cubs-of-the-year and yearlings; COY and YRL) of polar bears from Alaska’s southern Beaufort Sea to evaluate potential relationships with regional- and circumpolar-scale sea ice conditions and atmospheric patterns. The length of the summer open-water (OW) season (i.e., the period of time the sea ice is mostly absent from the continental shelf) increased at a rate of 18 days decade-1 over the study period. However, the OW season duration was not a strong determinant of spring residual body mass or litter mass. Residual body mass of independent (i.e., subadults and adults) female bears varied relative to age class, reproductive status, and the strength of the prior winter’s Arctic Oscillation (i.e., a circumpolar-scale mode of climate variability driven by long-term atmospheric patterns). Spring residual mass of independent males varied with age class and variation in wind speed (i.e., regional-scale short-term atmospheric patterns) during the winter of the year preceding capture. Over the study period, mean annual body mass of adult females unaccompanied by COY declined by 4 kg/ decade-1, while no temporal trends were evident in the mean annual body mass of adult females with COY, adult males, and subadults. Litter mass of COY varied relative to capture date, maternal age class and mass, litter size, and year of capture. Litter mass of YRL varied with capture date, maternal age class and mass, litter size, variation in winter wind speed (the year of and year preceding capture), and the strength of the prior winter’s Arctic Oscillation. Mean annual litter mass of COY decreased at a rate of 2.6 kg decade-1 and declined 0.68 kg for every 10 kg reduction in maternal mass. No trend was evident in the mean annual litter mass of yearlings. These findings suggest a nuanced response of the southern Beaufort Sea polar bears to environmental change, where some demographic groups (e.g., adult males and subadults) are presently more resilient than others to changes in the Arctic marine ecosystem.

Summary Knowledge of predator diets provides essential insights into their ecology, yet diet estimation is challenging and remains an active area of research. Quantitative fatty acid signature analysis (QFASA) is a popular method of estimating diet composition that continues to be investigated and extended. However, software to implement QFASA has only recently become publicly available. I summarize a new R package, qfasar, for diet estimation using QFASA methods. The package also provides functionality to evaluate and potentially improve the performance of a library of prey signature data, compute goodness-of-fit diagnostics, and support simulation-based research. Several procedures in the package have not previously been published. qfasar makes traditional and recently published QFASA diet estimation methods accessible to ecologists for the first time. Use of the package is illustrated with signature data from Chukchi Sea polar bears and potential prey species.

Polar bears (Ursus maritimus) rely on annual sea ice as their primary habitat for hunting marine mammal prey. Given their long lifespan, wide geographic distribution, and position at the top of the Arctic marine food web, the diet composition of polar bears can provide insights into temporal and spatial ecosystem dynamics related to climate-mediated sea ice loss. Polar bears with the greatest ecological constraints on diet composition may be most vulnerable to climate-related changes in ice conditions and prey availability. We used quantitative fatty acid signature analysis (QFASA) to estimate the diets of polar bears (n = 419) in two western Canadian Arctic subpopulations (Northern Beaufort Sea and Southern Beaufort Sea) from 1999 to 2015. Polar bear diets were dominated by ringed seal (Pusa hispida), with interannual, seasonal, age- and sex-specific variation. Foraging area and sea ice conditions also affected polar bear diet composition. Most variation in bear diet was explained by longitude, reflecting spatial variation in prey availability. Sea ice conditions (extent, thickness, and seasonal duration) declined throughout the study period, and date of sea ice break-up in the preceding spring was positively correlated with female body condition and consumption of beluga whale (Delphinapterus leucas), suggesting that bears foraged on beluga whales during entrapment events. Female body condition was positively correlated with ringed seal consumption, and negatively correlated with bearded seal consumption. This study provides insights into the complex relationships between declining sea ice habitat and the diet composition and foraging success of a wide-ranging apex predator.

Knowledge of predator diets, including how diets might change through time or differ among predators, provides essential insights into their ecology. Diet estimation therefore remains an active area of research within quantitative ecology. Quantitative fatty acid signature analysis (QFASA) is an increasingly common method of diet estimation. QFASA is based on a data library of prey signatures, which are vectors of proportions summarizing the fatty acid composition of lipids, and diet is estimated as the mixture of prey signatures that most closely approximates a predator’s signature. Diets are typically estimated using proportions from a subset of all fatty acids that are known to be solely or largely influenced by diet. Given the subset of fatty acids selected, the current practice is to scale their proportions to sum to 1.0. However, scaling signature proportions has the potential to distort the structural relationships within a prey library and between predators and prey. To investigate that possibility, we compared the practice of scaling proportions with two alternatives and found that the traditional scaling can meaningfully bias diet estimators under some conditions. Two aspects of the prey types that contributed to a predator’s diet influenced the magnitude of the bias: the degree to which the sums of unscaled proportions differed among prey types and the identifiability of prey types within the prey library. We caution investigators against the routine scaling of signature proportions in QFASA.

Understanding the diet of deep-diving predators can provide essential insight to the trophic structure of the mesopelagic ecosystem. Comprehensive population-level diet estimates are exceptionally difficult to obtain for elusive marine predators due to the logistical challenges involved in observing their feeding behavior and collecting samples for traditional stomach content or fecal analyses. We used quantitative fatty acid signature analysis (QFASA) to estimate the diet composition of a wide-ranging mesopelagic predator, the northern elephant seal (Mirounga angustirostris), across five years. To implement QFASA, we first compiled a library of prey fatty acid profiles from the mesopelagic eastern North Pacific. Given the scarcity of a priori diet data for northern elephant seals, our prey library was necessarily large to encompass the range of potential prey in their foraging habitat. However, statistical constraints limit the number of prey species that can be included in the prey library to the number of dietary fatty acids in the analysis. Exceeding that limit could produce non-unique diet estimates (i.e. multiple diet estimates fit the data equally well). Consequently, we developed a novel ad-hoc method to identify which prey were unlikely to contribute to diet and could, therefore, be excluded from the final QFASA model. The model results suggest that seals predominantly consumed small mesopelagic fishes, including myctophids (lanternfishes) and bathylagids (deep sea smelts), while non-migrating mesopelagic squids comprised a third of their diet, substantially less than suggested by previous studies. Our results revealed that mesopelagic fishes, particularly energy-rich myctophids, were a critical prey resource, refuting the long-held view that elephant seals are squid specialists.

Activity sensors are often included in wildlife transmitters and can provide information on the behavior and activity patterns of animals remotely. However, interpreting activity-sensor data relative to animal behavior can be difficult if animals cannot be continuously observed. In this study, we examined the performance of a mercury tip-switch and a tri-axial accelerometer housed in collars to determine whether sensor data can be accurately classified as resting and active behaviors and whether data are comparable for the 2 sensor types. Five captive bears (3 polar [Ursus maritimus] and 2 brown [U. arctos horribilis]) were fitted with a collar specially designed to internally house the sensors. The bears’ behaviors were recorded, classified, and then compared with sensor readings. A separate tri-axial accelerometer that sampled continuously at a higher frequency and provided raw acceleration values from 3 axes was also mounted on the collar to compare with the lower resolution sensors. Both acce...

Summary Knowledge of animal diets can provide important insights into life history and ecology, relationships among species in a community and potential response to ecosystem change or perturbation. Quantitative fatty acid signature analysis (QFASA) is a method of estimating diets from data on the composition, or signature, of fatty acids stored in adipose tissue. Given data on signatures of potential prey, a predator diet is estimated by minimizing the distance between its signature and a mixture of prey signatures. Calibration coefficients, constants derived from feeding trials, are used to account for differential metabolism of individual fatty acids. QFASA has been widely applied since its introduction and several variants of the original estimator have appeared in the literature. However, work to compare the statistical properties of QFASA estimators has been limited. One important characteristic of an estimator is its robustness to violations of model assumptions. The primary assumptions of QFASA are that prey signature data contain representatives of all prey types consumed and the calibration coefficients are known without error. We investigated the robustness of two QFASA estimators to a range of violations of these assumptions using computer simulation and recorded the resulting bias in diet estimates. We found that the Aitchison distance measure was most robust to errors in the calibration coefficients. Conversely, the Kullback–Leibler distance measure was most robust to the consumption of prey without representation in the prey signature data. In most QFASA applications, investigators will generally have some knowledge of the prey available to predators and be able to assess the completeness of prey signature data and sample additional prey as necessary. Conversely, because calibration coefficients are derived from feeding trials with captive animals and their values may be sensitive to consumer physiology and nutritional status, their applicability to free-ranging animals is difficult to establish. We therefore recommend that investigators first make any improvements to the prey signature data that seem warranted and then base estimation on the Aitchison distance measure, as it appears to minimize risk from violations of the assumption that is most difficult to verify.

Understanding the dietary habits of yellow-billed loons (Gavia adamsii) can give important insights into their ecology, however, studying the diet of loons is difficult when direct observation or specimen collection is impractical. We investigate the diet of yellow-billed loons nesting on the Arctic Coastal Plain of Alaska using quantitative fatty acid signature analysis. Tissue analysis from 26 yellow-billed loons and eleven prey groups (nine fish species and two invertebrate groups) from Arctic lakes suggests that yellow-billed loons are eating high proportions of Alaska blackfish (Dallia pectoralis), broad whitefish (Coregonus nasus) and three-spined stickleback (Gasterosteus aculeatus) during late spring and early summer. The prominence of blackfish in diets highlights the widespread availability of blackfish during the early stages of loon nesting, soon after spring thaw. The high proportions of broad whitefish and three-spined stickleback may reflect a residual signal from the coastal staging period prior to establishing nesting territories on lakes, when loons are more likely to encounter these species. Our analyses were sensitive to the choice of calibration coefficient based on data from three different species, indicating the need for development of loon-specific coefficients for future study and confirmation of our results. Regardless, fish that are coastally distributed and that successfully overwinter in lakes are likely key food items for yellow-billed loons early in the nesting season.

In the southern Beaufort Sea of the United States and Canada, prior investigations have linked declines in summer sea ice to reduced physical condition, growth, and survival of polar bears (Ursus maritimus). Combined with projections of population decline due to continued climate warming and the ensuing loss of sea ice habitat, those findings contributed to the 2008 decision to list the species as threatened under the U.S. Endangered Species Act. Here, we used mark-recapture models to investigate the population dynamics of polar bears in the southern Beaufort Sea from 2001 to 2010, years during which the spatial and temporal extent of summer sea ice generally declined. Low survival from 2004 through 2006 led to a 25-50% decline in abundance. We hypothesize that low survival during this period resulted from (1) unfavorable ice conditions that limited access to prey during multiple seasons; and possibly, (2) low prey abundance. For reasons that are not clear, survival of adults and cubs began to improve in 2007 and abundance was comparatively stable from 2008 to 2010, with ~900 bears in 2010 (90% CI 606-1212). However, survival of subadult bears declined throughout the entire period. Reduced spatial and temporal availability of sea ice is expected to increasingly force population dynamics of polar bears as the climate continues to warm. However, in the short term, our findings suggest that factors other than sea ice can influence survival. A refined understanding of the ecological mechanisms underlying polar bear population dynamics is necessary to improve projections of their future status and facilitate development of management strategies.

Quantitative fatty acid signature analysis has become an important method of diet estimation in ecology, especially marine ecology. Controlled feeding trials to validate the method and estimate the calibration coefficients necessary to account for differential metabolism of individual fatty acids have been conducted with several species from diverse taxa. However, research into potential refinements of the estimation method has been limited. We compared the performance of the original method of estimating diet composition with that of five variants based on different combinations of distance measures and calibration-coefficient transformations between prey and predator fatty acid signature spaces. Fatty acid signatures of pseudopredators were constructed using known diet mixtures of two prey data sets previously used to estimate the diets of polar bears Ursus maritimus and gray seals Halichoerus grypus, and their diets were then estimated using all six variants. In addition, previously published diets of Chukchi Sea polar bears were re-estimated using all six methods. Our findings reveal that the selection of an estimation method can meaningfully influence estimates of diet composition. Among the pseudopredator results, which allowed evaluation of bias and precision, differences in estimator performance were rarely large, and no one estimator was universally preferred, although estimators based on the Aitchison distance measure tended to have modestly superior properties compared to estimators based on the Kullback-Leibler distance measure. However, greater differences were observed among estimated polar bear diets, most likely due to differential estimator sensitivity to assumption violations. Our results, particularly the polar bear example, suggest that additional research into estimator performance and model diagnostics is warranted.

Estimates of predator diet composition are essential to our understanding of their ecology. Although several methods of estimating diet are practiced, methods based on biomarkers have become increasingly common. Quantitative fatty acid signature analysis (QFASA) is a popular method that continues to be refined and extended. Quantitative fatty acid signature analysis is based on differences in the signatures of prey types, often species, which are recognized and designated by investigators. Similarly, predator signatures may be structured by known factors such as sex or age class, and the season or region of sample collection. The recognized structure in signature data inherently influences QFASA results in important and typically beneficial ways. However, predator and prey signatures may contain additional, hidden structure that investigators either choose not to incorporate into an analysis or of which they are unaware, being caused by unknown ecological mechanisms. Hidden structure also influences QFASA results, most often negatively. We developed a new method to explore signature data for hidden structure, called divisive magnetic clustering (DIMAC). Our DIMAC approach is based on the same distance measure used in diet estimation, closely linking methods of data exploration and parameter estimation, and it does not require data transformation or distributional assumptions, as do many multivariate ordination methods in common use. We investigated the potential benefits of the DIMAC method to detect and subsequently exploit hidden structure in signature data using two prey signature libraries with quite different characteristics. We found that the existence of hidden structure in prey signatures can increase the confusion between prey types and thereby reduce the accuracy and precision of QFASA diet estimates. Conversely, the detection and exploitation of hidden structure represent a potential opportunity to improve predator diet estimates and may lead to new insights into the ecology of either predator or prey. The DIMAC algorithm is implemented in the R diet estimation package qfasar.

Knowledge of animal diets provides essential insights into their life history and ecology, although diet estimation is challenging and remains an active area of research. Quantitative fatty acid signature analysis (QFASA) has become a popular method of estimating diet composition, especially for marine species. A primary assumption of QFASA is that constants called calibration coefficients, which account for the differential metabolism of individual fatty acids, are known. In practice, however, calibration coefficients are not known, but rather have been estimated in feeding trials with captive animals of a limited number of model species. The impossibility of verifying the accuracy of feeding trial derived calibration coefficients to estimate the diets of wild animals is a foundational problem with QFASA that has generated considerable criticism. We present a new model that allows simultaneous estimation of diet composition and calibration coefficients based only on fatty acid signature samples from wild predators and potential prey. Our model performed almost flawlessly in four tests with constructed examples, estimating both diet proportions and calibration coefficients with essentially no error. We also applied the model to data from Chukchi Sea polar bears, obtaining diet estimates that were more diverse than estimates conditioned on feeding trial calibration coefficients. Our model avoids bias in diet estimates caused by conditioning on inaccurate calibration coefficients, invalidates the primary criticism of QFASA, eliminates the need to conduct feeding trials solely for diet estimation, and consequently expands the utility of fatty acid data to investigate aspects of ecology linked to animal diets.

Mark-recapture models are extensively used in quantitative population ecology, providing estimates of population vital rates, such as survival, that are difficult to obtain using other methods. Vital rates are commonly modeled as functions of explanatory covariates, adding considerable flexibility to mark-recapture models, but also increasing the subjectivity and complexity of the modeling process. Consequently, model selection and the evaluation of covariate structure remain critical aspects of mark-recapture modeling. The difficulties involved in model selection are compounded in Cormack-Jolly-Seber models because they are composed of separate sub-models for survival and recapture probabilities, which are conceptualized independently even though their parameters are not statistically independent. The construction of models as combinations of sub-models, together with multiple potential covariates, can lead to a large model set. Although desirable, estimation of the parameters of all models may not be feasible. Strategies to search a model space and base inference on a subset of all models exist and enjoy widespread use. However, even though the methods used to search a model space can be expected to influence parameter estimation, the assessment of covariate importance, and therefore the ecological interpretation of the modeling results, the performance of these strategies has received limited investigation. We present a new strategy for searching the space of a candidate set of Cormack-Jolly-Seber models and explore its performance relative to existing strategies using computer simulation. The new strategy provides an improved assessment of the importance of covariates and covariate combinations used to model survival and recapture probabilities, while requiring only a modest increase in the number of models on which inference is based in comparison to existing techniques.

Effective conservation planning requires understanding and ranking threats to wildlife populations. We developed a Bayesian network model to evaluate the relative influence of environmental and anthropogenic stressors, and their mitigation, on the persistence of polar bears (Ursus maritimus). Overall sea ice conditions, affected by rising global temperatures, were the most influential determinant of population outcomes. Accordingly, unabated rise in atmospheric greenhouse gas (GHG) concentrations was the dominant influence leading to worsened population outcomes, with polar bears in three of four ecoregions reaching a dominant probability of decreased or greatly decreased by the latter part of this century. Stabilization of atmospheric GHG concentrations by mid‐century delayed the greatly reduced state by ≈25 yr in two ecoregions. Prompt and aggressive mitigation of emissions reduced the probability of any regional population becoming greatly reduced by up to 25%. Marine prey availability, linked closely to sea ice trend, had slightly less influence on outcome state than sea ice availability itself. Reduced mortality from hunting and defense of life and property interactions resulted in modest declines in the probability of a decreased or greatly decreased population outcome. Minimizing other stressors such as trans‐Arctic shipping, oil and gas exploration, and contaminants had a negligible effect on polar bear outcomes, although the model was not well‐informed with respect to the potential influence of these stressors. Adverse consequences of loss of sea ice habitat became more pronounced as the summer ice‐free period lengthened beyond four months, which could occur in most of the Arctic basin after mid‐century if GHG emissions are not promptly reduced. Long‐term conservation of polar bears would be best supported by holding global mean temperature to ≤ 2°C above preindustrial levels. Until further sea ice loss is stopped, management of other stressors may serve to slow the transition of populations to progressively worsened outcomes, and improve the prospects for their long‐term persistence.

Understanding behavioral responses of species to environmental change is critical to forecasting population-level effects. Although climate change is significantly impacting species’ distributions, few studies have examined associated changes in behavior. Polar bear (Ursus maritimus) subpopulations have varied in their near-term responses to sea ice decline. We examined behavioral responses of two adjacent subpopulations to changes in habitat availability during the annual sea ice minimum using activity data. Location and activity sensor data collected from 1989 to 2014 for 202 adult female polar bears in the Southern Beaufort Sea (SB) and Chukchi Sea (CS) subpopulations were used to compare activity in three habitat types varying in prey availability: (1) land; (2) ice over shallow, biologically productive waters; and (3) ice over deeper, less productive waters. Bears varied activity across and within habitats with the highest activity at 50–75% sea ice concentration over shallow waters. On land, SB bears exhibited variable but relatively high activity associated with the use of subsistence-harvested bowhead whale carcasses, whereas CS bears exhibited low activity consistent with minimal feeding. Both subpopulations had fewer observations in their preferred shallow-water sea ice habitats in recent years, corresponding with declines in availability of this substrate. The substantially higher use of marginal habitats by SB bears is an additional mechanism potentially explaining why this subpopulation has experienced negative effects of sea ice loss compared to the still-productive CS subpopulation. Variability in activity among, and within, habitats suggests that bears alter their behavior in response to habitat conditions, presumably in an attempt to balance prey availability with energy costs.

Fecundity is a vital population characteristic that is directly linked to the productivity of fish populations. Historic data from Yukon River (Alaska) Chinook salmon Oncorhynchus tshawytscha suggest that length-adjusted fecundity differs among populations within the drainage and either is temporally variable or has declined. Yukon River Chinook salmon have been harvested in large-mesh gill-net fisheries for decades, and a decline in fecundity was considered a potential evolutionary response to size-selective exploitation. The implications for fishery conservation and management led us to further investigate the fecundity of Yukon River Chinook salmon populations. Matched observations of fecundity, length, and genotype were collected from a sample of adult females captured from the multipopulation spawning migration near the mouth of the Yukon River in 2008. These data were modeled by using a new mixture model, which was developed by extending the conditional maximum likelihood mixture model that...

Many fisheries for Pacific salmon Oncorhynchus spp. are actively managed to meet escapement goal objectives. In fisheries where the demand for surplus production is high, an extensive assessment program is needed to achieve the opposing objectives of allowing adequate escapement and fully exploiting the available surplus. Knowledge of abundance is a critical element of such assessment programs. Abundance estimation using mark—recapture experiments in combination with telemetry has become common in recent years, particularly within Alaskan river systems. Fish are typically captured and marked in the lower river while migrating in aggregations of individuals from multiple populations. Recapture data are obtained using telemetry receivers that are co-located with abundance assessment projects near spawning areas, which provide large sample sizes and information on population-specific mark rates. When recapture data are obtained from multiple populations, unequal mark rates may reflect a violation of...

Concern regarding the potential for selective fisheries to degrade desirable characteristics of exploited fish populations is growing worldwide. Although the occurrence of fishery-induced evolution in a wild population has not been irrefutably documented, considerable theoretical and empirical evidence for that possibility exists. Environmental conditions influence survival and growth in many species and may mask comparatively subtle trends induced by selective exploitation, especially given the evolutionarily short time series of data available from many fisheries. Modeling may be the most efficient investigative tool under such conditions. Motivated by public concern that large-mesh gillnet fisheries may be altering Chinook salmon in western Alaska, we constructed a stochastic model of the population dynamics of Chinook salmon. The model contained several individually based components and incorporated size-selective exploitation, assortative mating, size-dependent female fecundity, density-dependent survival, and the heritability of size and age. Substantial reductions in mean size and age were observed under all scenarios. Concurrently reducing directional selection and increasing spawning abundance was most effective in stimulating population recovery. Use of this model has potential to improve our ability to investigate the consequences of selective exploitation and aid development of improved management strategies to more effectively sustain fish and fisheries into the future.

Methods of evaluating loci in studies of mixture composition or individual assignment are largely based on performance characteristics of individual loci. Synergisms between loci are not exploited. Loci are often evaluated based on their ability to resolve individual populations, even though multipopulation aggregations are more commonly of interest. In addition, measures of locus performance may indirectly relate to investigative objectives. A new computer program, bels, offers an alternative that addresses these limitations and may be preferable to existing methods in some applications. The algorithm is illustrated using Yukon River chum salmon (Oncorhynchus keta) data.

Since 1996, U.S. Fish and Wildlife Service biologists have annually used fish wheels to capture migrating adult fall chum salmon Oncorhynchus keta in the main-stem Yukon River, Alaska, and estimated their abundance via mark–recapture methods. In each year of the study, the mark rate of captured fish at a site near Rampart has been substantially greater than rates observed at numerous locations upriver of that site. The factors most likely to cause the observed reduction in the mark rate are violations of mark–recapture model assumptions or the mortality of marked fish between the Rampart site and upriver locations. Results of studies conducted through 2000 were most consistent with the hypothesis of mortality. We investigate potential explanatory factors for the apparent reduction in mark rates at upriver locations using data collected during additional studies from 2001 to 2003. Results document that holding fish in submerged pens at the marking site negatively affects their ability to migrate f...

Pacific walruses (Odobenus rosmarus divergens) are harvested by subsistence hunters in Alaska as they migrate north through the Bering Strait in the spring. Harvest records and biological specimens have been collected from the Bering Strait communities of Little Diomede, Gambell, and Savoonga since the 1950s. Harvest levels in the Bering Strait region peaked in the late 1980s and declined thereafter; however, there was considerable variation in the size and composition of the harvests among communities and over time. The relationships among characteristics of the community harvests and the presence of temporal trends were investigated using generalized linear models. The proportion of females in the catch increased over time in all three communities, while the proportion pregnant among harvested females declined over the range of sample years. The ages of harvested walruses increased over time in all three communities through the 1980s, after which trends in age stabilized or began to decline. The age of first reproduction was significantly older for females sampled in 1975-1985 than for females sampled between 1952 and 1962 or 1992 and 1998. Factors thought to have influenced the size and composition of the catch over the past 50 yr include hunter preferences, harvest management regimes, environmental conditions, and changes in the population itself.

Hook-and-line gear is commonly used for monitoring the size and abundance of resident fish populations in southwest Alaska. The selectivity of the gear, however, may contribute to bias in the catch, making it difficult to detect changes in population structure over time. This study assessed the potential bias in sampling a population of rainbow trout Oncorhynchus mykiss with angling gear. A bidirectional weir was operated on Gertrude Creek from 1997 to 1999 to intercept the annual upstream spring migration of rainbow trout into the stream. Captured fish were measured and tagged to establish a population of marked individuals with a known length distribution above the weir. The marked population was then sampled with angling gear on three occasions during each of three summers. A variety of terminal tackle was used, and types were selected to maximize the catch of rainbow trout. Size selectivity was evaluated by use of an exact Kolmogorov–Smirnov (KS) test of the hypothesis that the length distrib...

Gillnet catch data from the lower Yukon River, AK, collected from 1990 to 2003 in conjunction with a sonar study to estimate the abundance of migrating fish, were assembled. The full dataset contained 92,029 records with complete species and length information. A subset of data for the eight most prevalent groups of fish was selected for the estimation of net selectivity. The reduced dataset contained 89,984 records for Chinook salmon (Oncorhynchus tshawytscha), summer and fall runs of chum salmon (O. keta), coho salmon (O. kisutch), pink salmon (O. gorbuscha), humpback whitefish (Coregonus pidschian), broad whitefish (C. nasus), and various cisco (Coregonus) species. A Pearson function was used as a net selectivity model for all eight groups of fish, though a parameter was added to accommodate the catch of fish that are relatively large for a particular mesh. Because most of these relatively large fish were probably not gilled, but rather caught by body parts other than the operculum, the extra parameter can be thought of as a tangling parameter. The parameters of the modified Pearson model were estimated using maximum likelihood, and variances were estimated through bootstrapping. Gillnets were found to be most efficient, for all eight groups of fish, when fish length is approximately twice as great as the perimeter of a mesh, and the corresponding location parameter of the Pearson model was estimated with high precision. As the Pearson function has apparently not been used previously as a net selectivity model, its suitability was compared to the normal, lognormal, gamma, inverse Gaussian, and bi-normal functions, which are commonly employed as net selectivity models. Model fit was evaluated on the basis of the value of the likelihood function obtained, Akaike's Information Criterion and scaled deviance statistics, and plots of estimated models and scaled catch data. The Pearson model was found to be quite flexible, and fit the data as well as or better than the other models for all eight groups of fish considered. Other researchers may wish to consider its use with their data.

Fishery resources are often studied when individuals from multiple stocks are aggregated. For that reason, mixed-stock analysis (MSA), i.e., estimation of the stock composition of a mixture of individuals, is an important component of many research programs. Although many characteristics can be used in MSA, DNA loci, particularly microsatellites, have become extremely common. Microsatellite loci usually have a greater number of potential expressions, or alleles, than other marker types. A high degree of polymorphism can enhance the power of MSA, but allele proportions are estimated less precisely and rare alleles are absent or observed in very small numbers in typically sized samples. The reduced precision and presence of rare alleles can degrade the performance of some analytic methods. Although the effect can be reduced by binning alleles, which is common, an objective method of doing so has not been available previously. We present a method for binning alleles that reduces the number of rare alleles, largely preserves the genetic relationships observed among stocks, and modestly improves the performance of mixed-stock and individual-assignment analyses. The method is illustrated with data from Yukon River chum salmon (Oncorhynchus keta) and western Alaska Dolly Varden (Salvelinus malma).

From 1996 to 1998, marked fish from a mark–recapture experiment were used to examine potential effects of fish wheel capture, handling, and tagging on adult chum salmon Oncorhynchus keta in the Yukon River, Alaska. Four fish wheels equipped with live holding boxes were used to capture fish, two at the marking site and two at the recapture site. During the 3 years of the study we annually marked 8,513–18,632 fish with individually numbered spaghetti tags; annual tag returns external to the mark–recapture experiment (not by project fish wheels) ranged from 594 to 1,007. Individual salmon were captured from one to four times in the four project fish wheels used in the mark–recapture experiment. Tag returns, interviews, carcass surveys, and data from other management projects indicated that the proportion of fish with marks decreased as distance from the marking site increased. Nine possible explanations for these observations were considered, but fish mortality associated with capture and handling a...

Genetic studies of fish and wildlife populations are increasingly based on highly polymorphic DNA loci. The large number of alleles, and particularly the large number of alleles that are observed in low frequency, have led many researchers to bin alleles. However, most strategies for binning alleles are subjective and may lead to loss of discriminatory power. A computer program that implements the allele-binning algorithm of Bromaghin and Crape (2005 ) is described.

Harbor seals (Phoca fvitulina) are an abundant predator along the west coast of North America, and there is considerable interest in their diet composition, especially in regard to predation on valued fish stocks. Available informationon harbor seal diets, primarily derived from scat analysis, suggests that adult salmon (Oncorhynchus spp.), Pacific Herring (Clupea pallasii), and gadids predominate. Because diet assessments based on scat analysis may be biased, we investigated diet composition through quantitative analysis of fatty acid signatures. Blubber samples from 49 harbor seals captured in western North America from haul-outs within the area of the San Juan Islands and southern Strait of Georgia in the Salish Sea were analyzed for fatty acid composition, along with 269 fish and squid specimens representing 27 potential prey classes. Diet estimates varied spatially, demographically, and among individual harbor seals. Findings confirmed the prevalence of previously identified prey species in harbor seal diets, but other species also contributed significantly. In particular, Black (Sebastes melanops) and Yellowtail (S. flavidus) Rockfish were estimated to compose up to 50% of some individual seal diets. Specialization and high predation rates on Black and Yellowtail Rockfish by a subset of harbor seals may play a role in the population dynamics of these regional rockfish stocks that is greater than previously realized.

Sample size determination is an important component of study design and can frequently be addressed using the multinomial probability model. The sample size determination procedures of Tortora and also Thompson describe two approaches to the problem based upon simultaneous interval estimation of multinomial probabilities. This article compares these procedures and highlights their differences. An alternative procedure is also developed. The new procedure employs Tortora's approach but is based upon different confidence limits and results in smaller recommended sample sizes.

Encounter-sampling designs are data-collection procedures in which population units are included in the sample as they are detected, or "encountered." Perhaps the most familiar examples of encountersampling designs are line-transect (e.g. Burnham et al. 1980) and line-intercept (e.g. De Vries 1979) procedures. One characteristic of encounter-sampling designs is that a sampling frame (e.g. Cochran 1977) of population units is not required. When individuals are mobile, elusive, or possess other characteristics that make it difficult to construct a sampling frame, encounter-sampling designs often provide the only effective means of sampling a population. A second characteristic of encounter-sampling designs is that they lack control over the subset of the population comprising the sample. As a result, data collected by these procedures often are not representative of the population of interest (i.e. a biased sample), and are best viewed as a probability sample. If variables of interest are correlated with the probability of inclusion, the data cannot be treated as a simple random sample, and estimators based upon random sampling theory are biased (Rao 1965). In these cases, designspecific estimators or bias corrections dependent on the probability structure of the data must be employed. A population of bird nests is one example of a population whose study requires the use of an encountersampling technique. In addition to the obvious lack of a sampling frame, the population is demographically open in that nests are initiated and fail through time. The usual sampling design consists of conducting searches for viable nests, including all detected nests in the sample. Data collected under such a design are biased because longer-lived nests are included in the sample with higher probability than are shorter-lived nests (Mayfield 1961). However, the method by which searches are conducted, typically, is not structured and is not helpful in deriving estimators. The parameter most often of interest is the nestsurvival rate (i.e. probability a nest survives to "success"). Success is often defined as the production of at least one offspring, though other definitions are equally appropriate. Nest-survival rates may be estimated using a number of models. Mayfield (1961, 1975), Johnson (1979), and Bart and Robson (1982) modeled nest survival after detection. Hensler and Nichols (1981), Pollock and Cornelius (1988), and Bromaghin and McDonald (1993) modeled the entire existence of nests by incorporating probabilities of inclusion and partial information of the total lifetime of detected nests in the model. While all of these models attempt to treat the probability structure of the data, only the Pollock-Cornelius and BromaghinMcDonald models do so fully and correctly. Although Heisey and Nordheim (1990) indicated that the Pollock-Cornelius model produces biased estimates of nest survival, recent information (Pollock and Cornelius unpubl. data) suggests that the bias decreases as the time between visits to nests decreases. All of the nest-survival models are designed to produce estimators of a single parameter, the probability of nest-success, while acknowledging the biased nature of the data. To some extent, they have all been successful. However, any number of additional parameters may also be of interest, and their estimation, which is also complicated by the biased nature of the data, has received little attention. We present a sampling design and estimation procedures that directly utilize the unequal probabilities with which nests are included in the sample. The method is developed from a classical sampling approach in that all characteristics of the population of nests are considered as fixed; randomness observed in the data is due solely to the sampling design. The design consists of temporally systematic searches for nests, and nests are included in the sample as they are detected. The model assumes that nests are (approximately) aged at the time of detection and monitored until they either fail or are successful. The systematic design permits probabilities of inclusion to be estimated. The estimates are employed in modified Horvitz-Thompson estimators (Horvitz and Thompson 1952) to obtain estimates of any parameter that can be expressed as a total or a ratio of totals. Such parameters include the probability a nest survives to success, the number of nests which survive to success, and the numbers of nests initiated. The sampling model.-Consider a fixed geographic area in which birds are nesting. Nests are initiated and survive for some period of time. The population of interest consists of all nests which exist within the area for any portion of a specified time frame. For example, the time frame might be constructed to contain all or some interesting portion of the nesting season of the species under consideration. Thus, a geographic area and a time frame are used to define the population. The population size is denoted N and the number of time units in the time frame of interest is denoted D. The time frame of D time units is divided into a

Bromaghin (1991) presents a systematic encounter sampling design that is appropriate for the study of biological populations that may be demographically and geographically open. The elements of the population must be approximately aged at the time of detection and monitored thereafter. The design permits two general classes of parameters to be estimated, population totals and ratios of population totals. However, the recommended estimation procedures are complex and the statistical properties of the estimators must be investigated using numerical techniques. This work presents the results of a simulation study conducted to numerically evaluate the statistical properties of the systematic encounter sampling design and the recommended estimators. The results of the study indicate the estimators possess attractive statistical properties in a variety of experimental situations.

Estimates of the median lethal dose (LD 5 0 ) [or the median lethal concentration (LC 5 0 )] are used in toxicological and hazard assessment studies to indicate the dosage of a substance that produces a 50% response (death)rate in a population. The calculation of LD 5 0 estimates is frequently accomplished through probit analysis. Probit analysis is based on certain underlying assumptions about the tolerance of the population in question to the substance being tested. The response rate is assumed to follow a cumulative normal distribution with respect to the dosage or the logarithms of the dosage. Recently we reviewed ASTM's proposed standard practice for using probit analysis (Draft No. 2). A BASIC computer program for performing probit analysis was included with the proposed standard. We evaluated this program using the PROBIT procedure in the well-known SAS Institute package as a standard of comparison. The SAS procedure offers a default option that assumes the response rate of the population follows the cumulative normal distribution. In addition, two logarithmic options are also offered (natural and base 10), whereby the response rate is assumed cumulative normal relative to the logarithm of the dose. The BASIC and SAS programs give very similar results when the appropriate logarithmic option is used with the SAS procedure. Thus, the ASTM program would be a subset of the SAS procedure in that it is comparable to one of the SAS options, employing one set of possible assumptions. We believe that the assumptions one would make about the distributional response of a population are not necessarily standard, and that careful examination of the data relative to analytical assumptions prior to analysis is recommended.

An approach is presented for estimating density from line transect data where the animals move away in response to the observer. This estimation method involves fitting the perpendicular sighting distances to the Weibull distribution. Estimates of the Weibull parameters are incorporated into the density estimate. When movement exists, even light movement, this method greatly outperforms the Fourier series estimator. It also outperforms the Fourier series estimator in some low density situations when there is no movement. The Weibull method shows promise for estimating density in the presence of movement and further development is planned.

Many applications in ecological genetics involve sampling individuals from a mixture of multiple biological populations and subsequently associating those individuals with the populations from which they arose. Analytical methods that assign individuals to their putative population of origin have utility in both basic and applied research, providing information about population-specific life history and habitat use, ecotoxins, pathogen and parasite loads, and many other non-genetic ecological, or phenotypic traits. Although the question is initially directed at the origin of individuals, in most cases the ultimate desire is to investigate the distribution of some trait among populations. Current practice is to assign individuals to a population of origin and study properties of the trait among individuals within population strata as if they constituted independent samples. It seemed that approach might bias population-specific trait inference. In this study we made trait inferences directly through modeling, bypassing individual assignment. We extended a Bayesian model for population mixture analysis to incorporate parameters for the phenotypic trait and compared its performance to that of individual assignment with a minimum probability threshold for assignment. The Bayesian mixture model outperformed individual assignment under some trait inference conditions. However, by discarding individuals whose origins are most uncertain, the individual assignment method provided a less complex analytical technique whose performance may be adequate for some common trait inference problems. Our results provide specific guidance for method selection under various genetic relationships among populations with different trait distributions.

Context The potential for research methods to affect wildlife is an increasing concern among both scientists and the public. This topic has a particular urgency for polar bears because additional research is needed to monitor and understand population responses to rapid loss of sea ice habitat. Aims This study used data collected from polar bears sampled in the Alaska portion of the southern Beaufort Sea to investigate the potential for capture to adversely affect behaviour and vital rates. We evaluated the extent to which capture, collaring and handling may influence activity and movement days to weeks post-capture, and body mass, body condition, reproduction and survival over 6 months or more. Methods We compared post-capture activity and movement rates, and relationships between prior capture history and body mass, body condition and reproductive success. We also summarised data on capture-related mortality. Key results Individual-based estimates of activity and movement rates reached near-normal levels within 2–3 days and fully normal levels within 5 days post-capture. Models of activity and movement rates among all bears had poor fit, but suggested potential for prolonged, lower-level rate reductions. Repeated captures was not related to negative effects on body condition, reproduction or cub growth or survival. Capture-related mortality was substantially reduced after 1986, when immobilisation drugs were changed, with only 3 mortalities in 2517 captures from 1987–2013. Conclusions Polar bears in the southern Beaufort Sea exhibited the greatest reductions in activity and movement rates 3.5 days post-capture. These shorter-term, post-capture effects do not appear to have translated into any long-term effects on body condition, reproduction, or cub survival. Additionally, collaring had no effect on polar bear recovery rates, body condition, reproduction or cub survival. Implications This study provides empirical evidence that current capture-based research methods do not have long-term implications, and are not contributing to observed changes in body condition, reproduction or survival in the southern Beaufort Sea. Continued refinement of capture protocols, such as the use of low-impact dart rifles and reversible drug combinations, might improve polar bear response to capture and abate short-term reductions in activity and movement post-capture.