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.
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.
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.
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.
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.
Summary1. Knowledge of predator diets provides essential insights into their ecology, yet diet estimation is challenging and remains an active area of research. 2. 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. 3. 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. 4. 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.
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.
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