Geology topics

W.A. Link

Publications and source records attributed to W.A. Link.

At least 19 recordsLinked to original sources

USGS2010

Postcatastrophe population dynamics and density dependence of an endemic island duck

Laysan ducks ( Anas laysanensis ) are restricted to approximately 9 km 2 in the Northwestern Hawaiian Islands, USA. To evaluate the importance of density dependence for Laysan ducks, we conducted a Bayesian analysis to estimate the parameters of a Gompertz model and the magnitude of process variation and observation error based on the fluctuations in Laysan duck abundance on Laysan Island from 1994 to 2007. This model described a stationary distribution for the population at carrying capacity that fluctuates around a long-term mean of 456 ducks and is between 316 to 636 ducks 95% of the time. This range of expected variability can be used to identify changes in population size that warn of catastrophic events. Density-dependent population dynamics may explain the recovery of Laysan duck from catastrophic declines and allow managers to identify population monitoring thresholds.

Journal of Wildlife Management↗

USGS2010

Occam's shadow: levels of analysis in evolutionary ecology - where to next?

Evolutionary ecology is the study of evolutionary processes, and the ecological conditions that influence them. A fundamental paradigm underlying the study of evolution is natural selection. Although there are a variety of operational definitions for natural selection in the literature, perhaps the most general one is that which characterizes selection as the process whereby heritable variation in fitness associated with variation in one or more phenotypic traits leads to intergenerational change in the frequency distribution of those traits. The past 20 years have witnessed a marked increase in the precision and reliability of our ability to estimate one or more components of fitness and characterize natural selection in wild populations, owing particularly to significant advances in methods for analysis of data from marked individuals. In this paper, we focus on several issues that we believe are important considerations for the application and development of these methods in the context of addressing questions in evolutionary ecology. First, our traditional approach to estimation often rests upon analysis of aggregates of individuals, which in the wild may reflect increasingly non-random (selected) samples with respect to the trait(s) of interest. In some cases, analysis at the aggregate level, rather than the individual level, may obscure important patterns. While there are a growing number of analytical tools available to estimate parameters at the individual level, and which can cope (to varying degrees) with progressive selection of the sample, the advent of new methods does not reduce the need to consider carefully the appropriate level of analysis in the first place. Estimation should be motivated a priori by strong theoretical analysis. Doing so provides clear guidance, in terms of both (i) assisting in the identification of realistic and meaningful models to include in the candidate model set, and (ii) providing the appropriate context under which the results are interpreted. Second, while it is true that selection (as defined) operates at the level of the individual, the selection gradient is often (if not generally) conditional on the abundance of the population. As such, it may be important to consider estimating transition rates conditional on both the parameter values of the other individuals in the population (or at least their distribution), and population abundance. This will undoubtedly pose a considerable challenge, for both single- and multi-strata applications. It will also require renewed consideration of the estimation of abundance, especially for open populations. Thirdly, selection typically operates on dynamic, individually varying traits. Such estimation may require characterizing fitness in terms of individual plasticity in one or more state variables, constituting analysis of the norms of reaction of individuals to variable environments. This can be quite complex, especially for traits that are under facultative control. Recent work has indicated that the pattern of selection on such traits is conditional on the relative rates of movement among and frequency of spatially heterogeneous habitats, suggesting analyses of evolution of life histories in open populations can be misleading in some cases.

Journal of Applied Statistics↗

USGS2010

Uncovering a latent multinomial: Analysis of mark–recapture data with misidentification

Natural tags based on DNA fingerprints or natural features of animals are now becoming very widely used in wildlife population biology. However, classic capture-recapture models do not allow for misidentification of animals which is a potentially very serious problem with natural tags. Statistical analysis of misidentification processes is extremely difficult using traditional likelihood methods but is easily handled using Bayesian methods. We present a general framework for Bayesian analysis of categorical data arising from a latent multinomial distribution. Although our work is motivated by a specific model for misidentification in closed population capture-recapture analyses, with crucial assumptions which may not always be appropriate, the methods we develop extend naturally to a variety of other models with similar structure. Suppose that observed frequencies f are a known linear transformation f=A'x of a latent multinomial variable x with cell probability vector pi= pi(theta). Given that full conditional distributions [theta | x] can be sampled, implementation of Gibbs sampling requires only that we can sample from the full conditional distribution [x | f, theta], which is made possible by knowledge of the null space of A'. We illustrate the approach using two data sets with individual misidentification, one simulated, the other summarizing recapture data for salamanders based on natural marks.

Biometrics↗

USGS2010

A Bayesian approach to identifying structural nonlinearity using free-decay response: Application to damage detection in composites

This work discusses a Bayesian approach to approximating the distribution of parameters governing nonlinear structural systems. Specifically, we use a Markov Chain Monte Carlo method for sampling the posterior parameter distributions thus producing both point and interval estimates for parameters. The method is first used to identify both linear and nonlinear parameters in a multiple degree-of-freedom structural systems using free-decay vibrations. The approach is then applied to the problem of identifying the location, size, and depth of delamination in a model composite beam. The influence of additive Gaussian noise on the response data is explored with respect to the quality of the resulting parameter estimates.

Journal of Sound and Vibration↗

USGS2010

Estimating migratory game-bird productivity by integrating age ratio and banding data

Context: Reproduction is a critical component of fitness, and understanding factors that influence temporal and spatial dynamics in reproductive output is important for effective management and conservation. Although several indices of reproductive output for wide-ranging species, such as migratory birds, exist, there has been no theoretical justification for their estimators or associated measures of variance. Aims: The aims of our research were to develop statistical justification for an estimator of reproduction and associated variances on the basis of an existing national wing-collection survey and banding data, and to demonstrate the applicability of this estimator to a migratory game bird. Methods: We used a Bayesian hierarchical modelling approach to integrate wing-collection data, which provides information on population age ratios, and band-recovery data, which provides information on recovery probabilities of various age classes, for American woodcock ( Scolopax minor ) to estimate productivity and associated measures of variance. We present two models of relative vulnerability between age classes: one model assumed that adult recovery probabilities were higher, but that annual fluctuations were synchronous between the two age classes (i.e. an additive effect of age and year). The second model assumed that adults, on average, had higher recovery probabilities than did juveniles and that annual fluctuations were asynchronous through time (i.e. an interaction between age and year). Key results: Fitting our models within a hierarchical Bayesian framework efficiently incorporates the two data types into a single estimator and derives appropriate variances for the productivity estimator. Further, use of Bayesian methods enabled us to derive credible intervals that avoid the reliance on asymptotic assumptions. When applied to American woodcock data, the additive model resulted in biologically realistic and more precise age-ratio estimates each year and is adequate when the relative vulnerability to sampling only slightly varies or does not vary among components of a population (e.g. age, sex class) among years. Therefore, we recommend using woodcock indices from our analysis based on this model. Conclusions: We provide a flexible modelling framework for estimating productivity and associated variances that can incorporate ecological covariates to explore various factors that could drive annual dynamics in productivity. Applying our model to the American woodcock data indicated that assumptions about the variability in relative recovery probabilities could greatly influence the precision of our productivity estimator. Therefore, researchers should carefully consider the assumption of temporally variable relative recovery probabilities (i.e. ratio of juvenile to adults' recovery probability) for different age classes when applying this estimator. Implications: Several national and international management strategies for migratory game birds in North America rely on measures of productivity from harvest survey parts collections, without a justification of the estimator or providing estimates of precision. We derive an estimator of productivity with realistic measures of uncertainty that can be directly incorporated into management plans or ecological studies across large spatial scales.

Wildlife Research↗

USGS2009

Estimating transition probabilities in unmarked populations: Entropy revisited

The probability of surviving and moving between 'states' is of great interest to biologists. Robust estimation of these transitions using multiple observations of individually identifiable marked individuals has received considerable attention in recent years. However, in some situations, individuals are not identifiable (or have a very low recapture rate), although all individuals in a sample can be assigned to a particular state (e.g. breeding or non-breeding) without error. In such cases, only aggregate data (number of individuals in a given state at each occasion) are available. If the underlying matrix of transition probabilities does not vary through time and aggregate data are available for several time periods, then it is possible to estimate these parameters using least-squares methods. Even when such data are available, this assumption of stationarity will usually be deemed overly restrictive and, frequently, data will only be available for two time periods. In these cases, the problem reduces to estimating the most likely matrix (or matrices) leading to the observed frequency distribution of individuals in each state. An entropy maximization approach has been previously suggested. In this paper, we show that the entropy approach rests on a particular limiting assumption, and does not provide estimates of latent population parameters (the transition probabilities), but rather predictions of realized rates.

Bird Study↗

USGS2009

Bayes factors and multimodel inference

Multimodel inference has two main themes: model selection, and model averaging. Model averaging is a means of making inference conditional on a model set, rather than on a selected model, allowing formal recognition of the uncertainty associated with model choice. The Bayesian paradigm provides a natural framework for model averaging, and provides a context for evaluation of the commonly used AIC weights. We review Bayesian multimodel inference, noting the importance of Bayes factors. Noting the sensitivity of Bayes factors to the choice of priors on parameters, we define and propose nonpreferential priors as offering a reasonable standard for objective multimodel inference.

Book chapter↗

USGS2009

An evaluation of density-dependent and density-independent influences on population growth rates in Weddell seals

Much of the existing literature that evaluates the roles of density-dependent and density-independent factors on population dynamics has been called into question in recent years because measurement errors were not properly dealt with in analyses. Using state-space models to account for measurement errors, we evaluated a set of competing models for a 22-year time series of mark-resight estimates of abundance for a breeding population of female Weddell seals (Leptonychotes weddellii) studied in Erebus Bay, Antarctica. We tested for evidence of direct density dependence in growth rates and evaluated whether equilibrium population size was related to seasonal sea-ice extent and the Southern Oscillation Index (SOI). We found strong evidence of negative density dependence in annual growth rates for a population whose estimated size ranged from 438 to 623 females during the study. Based on Bayes factors, a density-dependence-only model was favored over models that also included en! vironmental covariates. According to the favored model, the population had a stationary distribution with a mean of 497 females (SD = 60.5), an expected growth rate of 1.10 (95% credible interval 1.08-1.15) when population size was 441 females, and a rate of 0.90 (95% credible interval 0.87-0.93) for a population of 553 females. A model including effects of SOI did receive some support and indicated a positive relationship between SOI and population size. However, effects of SOI were not large, and including the effect did not greatly reduce our estimate of process variation. We speculate that direct density dependence occurred because rates of adult survival, breeding, and temporary emigration were affected by limitations on per capita food resources and space for parturition and pup-rearing. To improve understanding of the relative roles of various demographic components and their associated vital rates to population growth rate, mark-recapture methods can be applied that incorporate both environmental covariates and the seal abundance estimates that were developed here. An improved understanding of why vital rates change with changing population abundance will only come as we develop a better understanding of the processes affecting marine food resources in the Southern Ocean.

Ecology↗

USGS2008

Apparent tolerance of turkey vultures (Cathartes aura) to the non-steroidal anti-inflammatory drug diclofenac

The nonsteroidal anti‐inflammatory drug diclofenac is extremely toxic to Old World Gyps vultures (median lethal dose ∼0.1–0.2 mg/kg), evoking visceral gout, renal necrosis, and mortality within a few days of exposure. Unintentional secondary poisoning of vultures that fed upon carcasses of diclofenac‐treated livestock decimated populations in the Indian subcontinent. Because of the widespread use of diclofenac and other cyclooxygenase‐2 inhibiting drugs, a toxicological study was undertaken in turkey vultures ( Cathartes aura ) as an initial step in examining sensitivity of New World scavenging birds. Two trials were conducted entailing oral gavage of diclofenac at doses ranging from 0.08 to 25 mg/kg body weight. Birds were observed for 7 d, blood samples were collected for plasma chemistry (predose and 12, 24, and 48 h and 7 d postdose), and select individuals were necropsied. Diclofenac failed to evoke overt signs of toxicity, visceral gout, renal necrosis, or elevate plasma uric acid at concentrations greater than 100 times the estimated median lethal dose reported for Gyps vultures. For turkey vultures receiving 8 or 25 mg/kg, the plasma half‐life of diclofenac was estimated to be 6 h, and it was apparently cleared after several days as no residues were detectable in liver or kidney at necropsy. Differential sensitivity among avian species is a hallmark of cyclooxygenase‐2 inhibitors, and despite the tolerance of turkey vultures to diclofenac, additional studies in related scavenging species seem warranted.

Environmental Toxicology and Chemistry↗

USGS2008

Efficient implementation of the Metropolis-Hastings algorithm, with application to the Cormack?Jolly?Seber model

Judicious choice of candidate generating distributions improves efficiency of the Metropolis-Hastings algorithm. In Bayesian applications, it is sometimes possible to identify an approximation to the target posterior distribution; this approximate posterior distribution is a good choice for candidate generation. These observations are applied to analysis of the Cormack?Jolly?Seber model and its extensions.

Environmental and Ecological Statistics↗

USGS2008

Combining Breeding Bird Survey and Christmas Bird Count data to evaluate seasonal components of population change in Northern Bobwhite

Annual surveys of wildlife populations provide information about annual rates of change in populations but provide no information about when such changes occur. However, by combining data from 2 annual surveys, conducted in different parts of the year, seasonal components of population change can be estimated. We describe a hierarchical model for simultaneous analysis of 2 continent-scale monitoring programs. The Christmas Bird Count is an early winter survey, whereas the North American Breeding Bird Survey is conducted in June. Combining information from these surveys permits estimation of seasonal population variance components and improves estimation of long-term population trends. The composite analysis also controls for survey-specific sampling effects. We applied the model to estimation of population change in northern bobwhites (Colinus virginianus). Over the interval 1969?2004, bobwhite populations declined, with trend estimate of -3.56% per year (95% CI = [-3.80%, -3.32%]) in the surveyed portion of their range. Our analysis of seasonal population variance components indicated that northern bobwhite populations changed more in the winter and spring portion of the year than in the summer and fall portion of the year.

Journal of Wildlife Management↗

USGS2008

A hierarchical model for estimating change in American Woodcock populations

The Singing-Ground Survey (SGS) is a primary source of information on population change for American woodcock (Scolopax minor). We analyzed the SGS using a hierarchical log-linear model and compared the estimates of change and annual indices of abundance to a route regression analysis of SGS data. We also grouped SGS routes into Bird Conservation Regions (BCRs) and estimated population change and annual indices using BCRs within states and provinces as strata. Based on the hierarchical model?based estimates, we concluded that woodcock populations were declining in North America between 1968 and 2006 (trend = -0.9%/yr, 95% credible interval: -1.2, -0.5). Singing-Ground Survey results are generally similar between analytical approaches, but the hierarchical model has several important advantages over the route regression. Hierarchical models better accommodate changes in survey efficiency over time and space by treating strata, years, and observers as random effects in the context of a log-linear model, providing trend estimates that are derived directly from the annual indices. We also conducted a hierarchical model analysis of woodcock data from the Christmas Bird Count and the North American Breeding Bird Survey. All surveys showed general consistency in patterns of population change, but the SGS had the shortest credible intervals. We suggest that population management and conservation planning for woodcock involving interpretation of the SGS use estimates provided by the hierarchical model.

Journal of Wildlife Management↗

USGS2007

Efficient implementation of the Metropolis-Hastings algorithm, with application to the Cormack-Jolly-Seber model

Conference Paper↗

USGS2007

Effects of methylmercury on reproduction in American kestrels

Sixty breeding pairs of captive American kestrels ( Falco sparverius ) were exposed to a range of sublethal dietary concentrations of mercury (Hg), in the form of methylmercuric chloride, and their subsequent reproduction was measured. Egg production, incubation performance, and the number and percent of eggs hatched decreased markedly between 3.3 and 4.6 mg/kg dry weight of Hg (1.2 and 1.7 mg/kg wet wt), in the diet. The number of fledglings and the percent of nestlings fledged were reduced markedly at 0.7 mg/kg dry weight (0.3 mg/kg wet wt) and declined further between 2 and 3.3 mg/kg dry weight (0.7 and 1.2 mg/kg wet wt). Dietary concentrations of ⩾ 4.6 mg/kg dry weight (1.7 mg/kg wet wt) were associated with total fledging failure. The estimated decline in fledged young per pair (24%, Bayesian regression) for kestrels consuming 0.7 mg/kg dry weight (0.3 mg/ kg wet wt) raises concerns about population maintenance in areas subject to high inputs of anthropogenic Hg. Mercury concentrations in 20 second-laid eggs collected from all groups were related to dietary concentrations of Hg, and the Hg concentrations in 19 of these eggs were related to eggs laid and young fledged. Concentrations of Hg in eggs from the highest diet group (5.9 mg/kg dry wt; 2.2 mg/kg wet wt) were higher than egg concentrations reported for either wild birds or for captive birds (nonraptors) fed dry commercial food containing 5 mg/kg methylmercury. Accumulation ratios of Hg from diets to eggs were higher than those reported for feeding studies with other species.

Environmental Toxicology and Chemistry↗

USGS2007

Bayesian multimodel inference for dose-response studies

Statistical inference in dose-response studies is model-based: The analyst posits a mathematical model of the relation between exposure and response, estimates parameters of the model, and reports conclusions conditional on the model. Such analyses rarely include any accounting for the uncertainties associated with model selection. The Bayesian inferential system provides a convenient framework for model selection and multimodel inference. In this paper we briefly describe the Bayesian paradigm and Bayesian multimodel inference. We then present a family of models for multinomial dose-response data and apply Bayesian multimodel inferential methods to the analysis of data on the reproductive success of American kestrels (Falco sparveriuss) exposed to various sublethal dietary concentrations of methylmercury.

Environmental Toxicology and Chemistry↗

USGS2007

Analysis of multinomial models with unknown index using data augmentation

Multinomial models with unknown index ('sample size') arise in many practical settings. In practice, Bayesian analysis of such models has proved difficult because the dimension of the parameter space is not fixed, being in some cases a function of the unknown index. We describe a data augmentation approach to the analysis of this class of models that provides for a generic and efficient Bayesian implementation. Under this approach, the data are augmented with all-zero detection histories. The resulting augmented dataset is modeled as a zero-inflated version of the complete-data model where an estimable zero-inflation parameter takes the place of the unknown multinomial index. Interestingly, data augmentation can be justified as being equivalent to imposing a discrete uniform prior on the multinomial index. We provide three examples involving estimating the size of an animal population, estimating the number of diabetes cases in a population using the Rasch model, and the motivating example of estimating the number of species in an animal community with latent probabilities of species occurrence and detection.

Journal of Computational and Graphical Statistics↗

USGS2006

Effects of methyl mercury on reproduction in American kestrels

Methyl mercury (MeHg) readily passes through biological membranes, accumulates in individuals, and biomagnifies in higher order predators. It is acutely toxic to some birds at 5-15 parts per million (ppm) wet weight in the diet, and it can damage the central nervous system, impair reproduction, and retard growth and development. The effects of MeHg on reproduction in wild raptors are poorly known, and experiments with captive raptors have not included measures of reproductive response. In this study, breeding pairs of captive American kestrels (Falco sparverius) were exposed to environmentally realistic concentrations of MeHg in the diet and their subsequent reproduction was measured. Egg production, incubation performance, and the number of eggs hatched markedly decreased between 3.2 and 4.6 ppm MeHg dry weight in the diet. The percent of eggs hatched declined between 0.75 and 2 ppm MeHg dry weight in the diet and further declined to almost total hatching failure between 3.2 and 4.6 ppm. The number of fledglings and the percent of nestlings fledged were greatly reduced at 0.75 ppm MeHg dry weight in the diet and began a final sharp decline between 2 and 3.2 ppm. Dietary concentrations of > 4.6 ppm MeHg dry weight were associated with total fledging failure. Mercury concentrations in a set of 19 `second-laid? eggs collected from all groups were related to dietary concentrations of MeHg and the reproductive responses of kestrels in each group. Observed percentage declines in fledgling production caused by diets containing >2 ppm MeHg dry weight would result in the production of insufficient numbers of young kestrels for maintenance of wild populations. Concentrations of total Hg in eggs from the highest diet group (5.9 ppm dry weight) were higher than egg concentrations reported for either wild birds or for captive birds fed dry commercial food containing 5 ppm MeHg wet weight.

Book chapter↗

USGS2006

A hierarchical model for regional analysis of population change using Christmas Bird Count data, with application to the American Black Duck

Analysis of Christmas Bird Count (CBC) data is complicated by the need to account for variation in effort on counts and to provide summaries over large geographic regions. We describe a hierarchical model for analysis of population change using CBC data that addresses these needs. The effect of effort is modeled parametrically, with parameter values varying among strata as identically distributed random effects. Year and site effects are modeled hierarchically, accommodating large regional variation in number of samples and precision of estimates. The resulting model is complex, but a Bayesian analysis can be conducted using Markov chain Monte Carlo techniques. We analyze CBC data for American Black Ducks (Anas rubripes), a species of considerable management interest that has historically been monitored using winter surveys. Over the interval 1966-2003, Black Duck populations showed distinct regional patterns of population change. The patterns shown by CBC data are similar to those shown by the Midwinter Waterfowl Inventory for the United States.

Condor↗