Geology topics

Jeffrey F. Bromaghin

Publications and source records attributed to Jeffrey F. Bromaghin.

32 records · Page 2Linked to original sources

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

Diet of yellow-billed loons ( Gavia adamsii ) in Arctic lakes during the nesting season inferred from fatty acid analysis

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.

Alaska↗

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↗

USGS2015

Simulating realistic predator signatures in quantitative fatty acid signature analysis

Diet estimation is an important field within quantitative ecology, providing critical insights into many aspects of ecology and community dynamics. Quantitative fatty acid signature analysis (QFASA) is a prominent method of diet estimation, particularly for marine mammal and bird species. Investigators using QFASA commonly use computer simulation to evaluate statistical characteristics of diet estimators for the populations they study. Similar computer simulations have been used to explore and compare the performance of different variations of the original QFASA diet estimator. In both cases, computer simulations involve bootstrap sampling prey signature data to construct pseudo-predator signatures with known properties. However, bootstrap sample sizes have been selected arbitrarily and pseudo-predator signatures therefore may not have realistic properties. I develop an algorithm to objectively establish bootstrap sample sizes that generates pseudo-predator signatures with realistic properties, thereby enhancing the utility of computer simulation for assessing QFASA estimator performance. The algorithm also appears to be computationally efficient, resulting in bootstrap sample sizes that are smaller than those commonly used. I illustrate the algorithm with an example using data from Chukchi Sea polar bears ( Ursus maritimus ) and their marine mammal prey. The concepts underlying the approach may have value in other areas of quantitative ecology in which bootstrap samples are post-processed prior to their use.

Ecological Informatics↗

USGS2015

Polar bear population dynamics in the southern Beaufort Sea during a period of sea ice decline

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.

Alaska↗

USGS2015

Validation of mercury tip-switch and accelerometer activity sensors for identifying resting and active behavior in bears

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 accelerometers more accurately identified resting and active behaviors at time intervals ranging from 1 minute to 1 hour (≥91.1% accuracy) compared with the mercury tip-switch (range = 75.5–86.3%). However, mercury tip-switch accuracy improved when sampled at longer intervals (e.g., 30–60 min). Data from the lower resolution accelerometer, but not the mercury tip-switch, accurately predicted the percentage of time spent resting during an hour. Although the number of bears available for this study was small, our results suggest that these activity sensors can remotely identify resting versus active behaviors across most time intervals. We recommend that investigators consider both study objectives and the variation in accuracy of classifying resting and active behaviors reported here when determining sampling interval.

Ursus↗

USGS2015

Evaluating and ranking threats to the long-term persistence of polar bears

The polar bear ( Ursus maritimus ) was listed as a globally threatened species under the U.S. Endangered Species Act (ESA) in 2008, mostly due to the significant threat to their future population viability from rapidly declining Arctic sea ice. A core mandate of the ESA is the development of a recovery plan that identifies steps to maintain viable populations of a listed species. A substantive evaluation of the relative influence of putative threats to population persistence is helpful to recovery planning. Because management actions must often be taken in the face of substantial information gaps, a formalized evaluation hypothesizing potential stressors and their relationships with population persistence can improve identification of relevant conservation actions. To this end, we updated a Bayesian network model previously used to forecast the future status of polar bears worldwide. We used new information on actual and predicted sea ice loss and polar bear responses to evaluate the relative influence of plausible threats and their mitigation through management actions on the persistence of polar bears in four ecoregions. We found that polar bear outcomes worsened over time through the end of the century under both stabilized and unabated greenhouse gas (GHG) emission pathways. Under the unabated pathway (i.e., RCP 8.5), the time it took for polar bear populations in two of four ecoregions to reach a dominant probability of greatly decreased was hastened by about 25 years. Under the stabilized GHG emission pathway (i.e., RCP 4.5), where GHG emissions peak around the year 2040, the polar bear population in the Archipelago Ecoregion of High Arctic Canada never reached a dominant probability of greatly decreased, reinforcing earlier suggestions of this ecoregion’s potential to serve as a long-term refugium. The most influential drivers of adverse polar bear outcomes were declines to overall sea ice conditions and to the marine prey base. Improved sea ice conditions substantively lowered the probability of a decreased or greatly decreased outcome, while an elevated marine prey base was slightly less influential in lowering the probability of a decreased or greatly decreased outcome. Stressors associated with in situ human activities exerted considerably less influence on population outcomes. Reduced mortality from hunting and defense of life and property interactions resulted inmodest 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 point-source pollution had negligible effects on polar bear outcomes, but that could be attributed to uncertainties in the ecological relevance of those specific stressors. Our findings suggest adverse consequences of loss of sea ice habitat become more pronounced as the summer ice-free period lengthens beyond 4 months, which could occur in portions of the Arctic by the middle of this century under the unabated pathway. The long-term persistence of polar bears may be achieved through ameliorating the loss of sea ice habitat, which will likely require stabilizing CO 2 emissions at or below the ceiling represented by RCP 4.5. Management of other stressors may serve to slow the transition of polar bear populations to progressively worsened outcomes, and improve the prospects of persistence, pending GHG mitigation.

Open-File Report↗

USGS2014

Use of genetic data to infer population-specific ecological and phenotypic traits from mixed aggregations

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.

PLoS ONE↗

USGS2014

Effects of capturing and collaring on polar bears: findings from long-term research on the southern Beaufort Sea population

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.

Wildlife Research↗

USGS2013

Plausible combinations: An improved method to evaluate the covariate structure of Cormack-Jolly-Seber mark-recapture models

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.

Open Journal Of Ecology↗

USGS2013

New insights into the diets of harbor seals in the Salish Sea revealed by quantitative fatty acid signature analysis

Harbor seals ( Phoca vitulina ) 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 information on 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.

British Columbia, Washington↗

USGS2011

Using a genetic mixture model to study phenotypic traits: Differential fecundity among Yukon river Chinook Salmon

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 is commonly used to estimate the composition of multipopulation mixtures based on genetic data. The new model facilitates maximum likelihood estimation of stock‐specific fecundity parameters without first using individual assignment to a putative population of origin, thus avoiding potential biases caused by assignment error. The hypothesis that fecundity of Chinook salmon has declined was not supported; this result implies that fecundity exhibits high interannual variability. However, length‐adjusted fecundity estimates decreased as migratory distance increased, and fecundity was more strongly dependent on fish size for populations spawning in the middle and upper portions of the drainage. These findings provide insights into potential constraints on reproductive investment imposed by long migrations and warrant consideration in fisheries management and conservation. The new mixture model extends the utility of genetic markers to new applications and can be easily adapted to study any observable trait or condition that may vary among populations.

Transactions of the American Fisheries Society↗

USGS2010

A likelihood framework for joint estimation of salmon abundance and migratory timing using telemetric mark-recapture

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 the assumption of homogeneous capture probabilities. A common analytical strategy is to test the hypothesis that mark rates are homogeneous and combine all recapture data if the test is not significant. However, mark rates are often low, and a test of homogeneity may lack sufficient power to detect meaningful differences among populations. In addition, differences among mark rates may provide information that could be exploited during parameter estimation. We present a temporally stratified mark—recapture model that permits capture probabilities and migratory timing through the capture area to vary among strata. Abundance information obtained from a subset of populations after the populations have segregated for spawning is jointly modeled with telemetry distribution data by use of a likelihood function. Maximization of the likelihood produces estimates of the abundance and timing of individual populations migrating through the capture area, thus yielding substantially more information than the total abundance estimate provided by the conventional approach. The utility of the model is illustrated with data for coho salmon O. kisutch from the Kasilof River in south-central Alaska.

North American Journal of Fisheries Management↗