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Gregory W. Thiemann

Publications and source records attributed to Gregory W. Thiemann.

11 recordsLinked to original sources
USGS2023

A body composition model with multiple storage compartments for polar bears (Ursus maritimus)

Climate warming is rapidly altering Arctic ecosystems. Polar bears ( Ursus maritimus ) need sea ice as a platform from which to hunt seals, but increased sea-ice loss is lengthening periods when bears are without access to primary hunting habitat. During periods of food scarcity, survival depends on the energy that a bear has stored in body reserves, termed storage energy, making this a key metric in predictive models assessing climate change impacts on polar bears. Here, we developed a body composition model for polar bears that estimates storage energy while accounting for changes in storage tissue composition. We used data of dissected polar bears ( n = 31) to link routinely collected field measures of total body mass and straight-line body length to the body composition of individual bears, described in terms of structural mass and two storage compartments, adipose and muscle. We then estimated the masses of metabolizable proteins and lipids within these storage compartments, giving total storage energy. We tested this multi-storage model by using it to predict changes in the lipid stores from an independent dataset of wild polar bears ( n = 36) that were recaptured 8–200 days later. Using length and mass measurements, our model successfully predicted direct measurements of lipid changes via isotopic dilutions (root mean squared error of 14.5 kg). Separating storage into two compartments, and allowing the molecular composition of storage to vary, provides new avenues for quantifying energy stores of individuals across their life cycle. The multi-storage body composition model thus provides a basis for further exploring energetic costs of physiological processes that contribute to individual survival and reproductive success. Given bioenergetic models are increasingly used as a tool to predict individual fitness and population dynamics, our approach for estimating individual energy stores could be applicable to a wide range of species.

Article↗
USGS2021

Fatty acid profiles of feeding and fasting bears: Estimating calibration coefficients, the timeframe of diet estimates, and selective mobilization during hibernation

Accurate information on diet composition is central to understanding and conserving carnivore populations. Quantitative fatty acid signature analysis (QFASA) has emerged as a powerful tool for estimating the diets of predators, but ambiguities remain about the timeframe of QFASA estimates and the need to account for species-specific patterns of metabolism. We conducted a series of feeding experiments with four juvenile male brown bears ( Ursus arctos ) to (1) track the timing of changes in adipose tissue composition and QFASA diet estimates in response to a change in diet and (2) quantify the relationship between consumer and diet FA composition (i.e., determine “calibration coefficients”). Bears were fed three compositionally distinct diets for 90–120 days each. Two marine-based diets were intended to approximate the lipid content and composition of the wild diet of polar bears ( U. maritimus ). Bear adipose tissue composition changed quickly in the direction of the diet and showed evidence of stabilization after 60 days. During hibernation, FA profiles were initially stable but diet estimates after 10 weeks were sensitive to calibration coefficients. Calibration coefficients derived from the marine-based diets were broadly similar to each other and to published values from marine-fed mink ( Mustela vison ), which have been used as a model for free-ranging polar bears. For growing bears on a high-fat diet, the temporal window for QFASA estimates was 30–90 days. Although our results reinforce the importance of accurate calibration, the similarities across taxa and diets suggest it may be feasible to develop a generalized QFASA approach for mammalian carnivores.

Journal of Comparative Physiology B: Biochemical, ↗
USGS2021

Diet composition and body condition of polar bears (Ursus maritimus) in relation to sea ice habitat in the Canadian High Arctic

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.

Canadian High Arctic↗
USGS2020

Drivers and consequences of apex predator diet composition in the Canadian Beaufort Sea

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.

Northwest Territories, Yukon↗
USGS2017

Detect and exploit hidden structure in fatty acid signature data

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.

Ecosphere↗
USGS2017

Simultaneous estimation of diet composition and calibration coefficients with fatty acid signature data

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.

Ecology and Evolution↗
USGS2016

Should fatty acid signature proportions sum to 1 for diet estimation?

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.

Ecological Research↗
USGS2015

Assessing the robustness of quantitative fatty acid signature analysis to assumption violations

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.

Methods in Ecology and Evolution↗
USGS2015

Distance measures and optimization spaces in quantitative fatty acid signature analysis

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.

Ecology and Evolution↗
USGS2013

Variation in the response of an Arctic top predator experiencing habitat loss: Feeding and reproductive ecology of two polar bear populations

Polar bears ( Ursus maritimus ) have experienced substantial changes in the seasonal availability of sea ice habitat in parts of their range, including the Beaufort, Chukchi, and Bering Seas. In this study, we compared the body size, condition, and recruitment of polar bears captured in the Chukchi and Bering Seas (CS) between two periods (1986–1994 and 2008–2011) when declines in sea ice habitat occurred. In addition, we compared metrics for the CS population 2008–2011 with those of the adjacent southern Beaufort Sea (SB) population where loss in sea ice habitat has been associated with declines in body condition, size, recruitment, and survival. We evaluated how variation in body condition and recruitment were related to feeding ecology. Comparing habitat conditions between populations, there were twice as many reduced ice days over continental shelf waters per year during 2008–2011 in the SB than in the CS. CS polar bears were larger and in better condition, and appeared to have higher reproduction than SB bears. Although SB and CS bears had similar diets, twice as many bears were fasting in spring in the SB than in the CS. Between 1986–1994 and 2008–2011, body size, condition, and recruitment indices in the CS were not reduced despite a 44-day increase in the number of reduced ice days. Bears in the CS exhibited large body size, good body condition, and high indices of recruitment compared to most other populations measured to date. Higher biological productivity and prey availability in the CS relative to the SB, and a shorter recent history of reduced sea ice habitat, may explain the maintenance of condition and recruitment of CS bears. Geographic differences in the response of polar bears to climate change are relevant to range-wide forecasts for this and other ice-dependent species.

Beaufort Sea; Bering Sea; Chukchi Sea↗