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William A. Link

Publications and source records attributed to William A. Link.

At least 37 records · Page 2Linked to original sources
USGS2013

Insights into the latent multinomial model through mark-resight data on female grizzly bears with cubs-of-the-year

Mark-resight designs for estimation of population abundance are common and attractive to researchers. However, inference from such designs is very limited when faced with sparse data, either from a low number of marked animals, a low probability of detection, or both. In the Greater Yellowstone Ecosystem, yearly mark-resight data are collected for female grizzly bears with cubs-of-the-year (FCOY), and inference suffers from both limitations. To overcome difficulties due to sparseness, we assume homogeneity in sighting probabilities over 16 years of bi-annual aerial surveys. We model counts of marked and unmarked animals as multinomial random variables, using the capture frequencies of marked animals for inference about the latent multinomial frequencies for unmarked animals. We discuss undesirable behavior of the commonly used discrete uniform prior distribution on the population size parameter and provide OpenBUGS code for fitting such models. The application provides valuable insights into subtleties of implementing Bayesian inference for latent multinomial models. We tie the discussion to our application, though the insights are broadly useful for applications of the latent multinomial model.

Journal of Agricultural, Biological, and Environme↗
USGS2013

Population size, survival, growth, and movements of Rana sierrae

Based on 2431 captures of 757 individual frogs over a 9-yr period, we found that the population of R. sierrae in one meadow–stream complex in Yosemite National Park ranged from an estimated 45 to 115 adult frogs. Rana sierrae at our relatively low elevation site (2200 m) grew at a fast rate (K = 0.73–0.78), had high overwintering survival rates (44.6–95%), lived a long time (up to 16 yr), and tended to be fairly sedentary during the summer (100% minimum convex polygon annual home ranges of 139 m2) but had low year-to-year site fidelity. Even though the amphibian chytrid fungus (Batrachochytrium dendrobatidis, Bd) has been present in the population for at least 13 yr, there was no clear downward trend as might be expected from reports of R. sierrae population declines associated with Bd or from reports of widespread population decline of R. sierrae throughout its range.

Herpetologica↗
USGS2013

The North American Breeding Bird Survey 1966–2011: Summary analysis and species accounts

The North American Breeding Bird Survey is a roadside, count-based survey conducted by volunteer observers. Begun in 1966, it now is a primary source of information on spatial and temporal patterns of population change for North American birds. We analyze population change for states, provinces, Bird Conservation Regions, and the entire survey within the contiguous United States and southern Canada for 426 species using a hierarchical log-linear model that controls for observer effects in counting. We also map relative abundance and population change for each species using a spatial smoothing of data at the scale of survey routes. We present results in accounts that describe major breeding habitats, migratory status, conservation status, and population trends for each species at several geographic scales. We also present composite results for groups of species categorized by habitats and migratory status. The survey varies greatly among species in percentage of species' range covered and precision of results, but consistent patterns of decline occur among eastern forest, grassland, and aridland obligate birds while generalist bird species are increasing.

North American Fauna↗
USGS2011

Evaluating the demographic buffering hypothesis with vital rates estimated for Weddell seals from 30years of mark-recapture data

1. Life‐history theory predicts that those vital rates that make larger contributions to population growth rate ought to be more strongly buffered against environmental variability than are those that are less important. Despite the importance of the theory for predicting demographic responses to changes in the environment, it is not yet known how pervasive demographic buffering is in animal populations because the validity of most existing studies has been called into question because of methodological deficiencies. 2. We tested for demographic buffering in the southern‐most breeding mammal population in the world using data collected from 5558 known‐age female Weddell seals over 30 years. We first estimated all vital rates simultaneously with mark–recapture analysis and then estimated process variance and covariance in those rates using a hierarchical Bayesian approach. We next calculated the population growth rate’s sensitivity to changes in each of the vital rates and tested for evidence of demographic buffering by comparing properly scaled values of sensitivity and process variance in vital rates. 3. We found evidence of positive process covariance between vital rates, which indicates that all vital rates are affected in the same direction by changes in annual environment. Despite the positive correlations, we found strong evidence that demographic buffering occurred through reductions in variation in the vital rates to which population growth rate was most sensitive. Process variation in vital rates was inversely related to sensitivity measures such that variation was greatest in breeding probabilities, intermediate for survival rates of young animals and lowest for survival rates of older animals. 4. Our work contributes to a small but growing set of studies that have used rigorous methods on long‐term, detailed data to investigate demographic responses to environmental variation. The information from these studies improves our understanding of life‐history evolution in stochastic environments and provides useful information for predicting population responses to future environmental change. Our results for an Antarctic apex predator also provide useful baselines from a marine ecosystem when its top‐ and middle‐trophic levels were not substantially impacted by human activity.

Journal of Animal Ecology↗
USGS2011

On thinning of chains in MCMC

1. Markov chain Monte Carlo (MCMC) is a simulation technique that has revolutionised the analysis of ecological data, allowing the fitting of complex models in a Bayesian framework. Since 2001, there have been nearly 200 papers using MCMC in publications of the Ecological Society of America and the British Ecological Society, including more than 75 in the journal Ecology and 35 in the Journal of Applied Ecology . 2. We have noted that many authors routinely 'thin' their simulations, discarding all but every k th sampled value; of the studies we surveyed with details on MCMC implementation, 40% reported thinning. 3. Thinning is often unnecessary and always inefficient, reducing the precision with which features of the Markov chain are summarised. The inefficiency of thinning MCMC output has been known since the early 1990's, long before MCMC appeared in ecological publications. 4. We discuss the background and prevalence of thinning, illustrate its consequences, discuss circumstances when it might be regarded as a reasonable option and recommend against routine thinning of chains unless necessitated by computer memory limitations.

Methods in Ecology and Evolution↗
USGS2011

Decision analysis for conservation breeding: Maximizing production for reintroduction of whooping cranes

Captive breeding is key to management of severely endangered species, but maximizing captive production can be challenging because of poor knowledge of species breeding biology and the complexity of evaluating different management options. In the face of uncertainty and complexity, decision-analytic approaches can be used to identify optimal management options for maximizing captive production. Building decision-analytic models requires iterations of model conception, data analysis, model building and evaluation, identification of remaining uncertainty, further research and monitoring to reduce uncertainty, and integration of new data into the model. We initiated such a process to maximize captive production of the whooping crane ( Grus americana ), the world's most endangered crane, which is managed through captive breeding and reintroduction. We collected 15 years of captive breeding data from 3 institutions and used Bayesian analysis and model selection to identify predictors of whooping crane hatching success. The strongest predictor, and that with clear management relevance, was incubation environment. The incubation period of whooping crane eggs is split across two environments: crane nests and artificial incubators. Although artificial incubators are useful for allowing breeding pairs to produce multiple clutches, our results indicate that crane incubation is most effective at promoting hatching success. Hatching probability increased the longer an egg spent in a crane nest, from 40% hatching probability for eggs receiving 1 day of crane incubation to 95% for those receiving 30 days (time incubated in each environment varied independently of total incubation period). Because birds will lay fewer eggs when they are incubating longer, a tradeoff exists between the number of clutches produced and egg hatching probability. We developed a decision-analytic model that estimated 16 to be the optimal number of days of crane incubation needed to maximize the number of offspring produced. These results show that using decision-analytic tools to account for uncertainty in captive breeding can improve the rate at which such programs contribute to wildlife reintroductions.

Journal of Wildlife Management↗
USGS2011

Book review: Bayesian analysis for population ecology

Brian Dennis described the field of ecology as “fertile, uncolonized ground for Bayesian ideas.” He continued: “The Bayesian propagule has arrived at the shore. Ecologists need to think long and hard about the consequences of a Bayesian ecology. The Bayesian outlook is a successful competitor, but is it a weed? I think so.” (Dennis 2004) Review info: Bayesian Analysis for Population Ecology. By Ruth King, Byron J. T. Morgan, Olivier Gimenez, and Stephen P. Brooks, 2010. ISBN: 978-1439811870, xvii, 442 pp.

American Statistician↗
USGS2011

Estimating age from recapture data: Integrating incremental growth measures with ancillary data to infer age-at-length

Estimating the age of individuals in wild populations can be of fundamental importance for answering ecological questions, modeling population demographics, and managing exploited or threatened species. Significant effort has been devoted to determining age through the use of growth annuli, secondary physical characteristics related to age, and growth models. Many species, however, either do not exhibit physical characteristics useful for independent age validation or are too rare to justify sacrificing a large number of individuals to establish the relationship between size and age. Length‐at‐age models are well represented in the fisheries and other wildlife management literature. Many of these models overlook variation in growth rates of individuals and consider growth parameters as population parameters. More recent models have taken advantage of hierarchical structuring of parameters and Bayesian inference methods to allow for variation among individuals as functions of environmental covariates or individual‐specific random effects. Here, we describe hierarchical models in which growth curves vary as individual‐specific stochastic processes, and we show how these models can be fit using capture–recapture data for animals of unknown age along with data for animals of known age. We combine these independent data sources in a Bayesian analysis, distinguishing natural variation (among and within individuals) from measurement error. We illustrate using data for African dwarf crocodiles, comparing von Bertalanffy and logistic growth models. The analysis provides the means of predicting crocodile age, given a single measurement of head length. The von Bertalanffy was much better supported than the logistic growth model and predicted that dwarf crocodiles grow from 19.4 cm total length at birth to 32.9 cm in the first year and 45.3 cm by the end of their second year. Based on the minimum size of females observed with hatchlings, reproductive maturity was estimated to be at nine years. These size benchmarks are believed to represent thresholds for important demographic parameters; improved estimates of age, therefore, will increase the precision of population projection models. The modeling approach that we present can be applied to other species and offers significant advantages when multiple sources of data are available and traditional aging techniques are not practical.

Loango National Park↗
USGS2010

Comparative analysis of Mourning Dove population change in North America

Mourning doves (Zenaida macroura) are surveyed in North America with a Call-Count Survey (CCS) and the North American Breeding Bird Survey (BBS). Analyses in recent years have identified inconsistencies in results between surveys, and a need exists to analyze the surveys using modern methods and examine possible causes of differences in survey results. Call-Count Survey observers collect separate information on number of doves heard and number of doves seen during counting, whereas BBS observers record one index containing all doves observed. We used hierarchical log-linear models to estimate trend and annual indices of abundance for 1966–2007 from BBS data, CCS-heard data, and CCS-seen data. Trend estimates from analyses provided inconsistent results for several states and for eastern and central dovemanagement units. We examined differential effects of change in land use and noise-related disturbance on the CCS indices. Changes in noiserelated disturbance along CCS routes had a larger influence on the heard index than on the seen index, but association analyses among states of changes in temperature and of amounts of developed land suggest that CCS indices are differentially influenced by changes in these environmental features. Our hierarchical model should be used to estimate population change from dove surveys, because it provides an efficient framework for estimating population trends from dove indices while controlling for environmental features that differentially influence the indices.

Journal of Wildlife Management↗
USGS2010

Model-based estimation of individual fitness

Fitness is the currency of natural selection, a measure of the propagation rate of genotypes into future generations. Its various definitions have the common feature that they are functions of survival and fertility rates. At the individual level, the operative level for natural selection, these rates must be understood as latent features, genetically determined propensities existing at birth. This conception of rates requires that individual fitness be defined and estimated by consideration of the individual in a modelled relation to a group of similar individuals; the only alternative is to consider a sample of size one, unless a clone of identical individuals is available. We present hierarchical models describing individual heterogeneity in survival and fertility rates and allowing for associations between these rates at the individual level. We apply these models to an analysis of life histories of Kittiwakes ( Rissa tridactyla ) observed at several colonies on the Brittany coast of France. We compare Bayesian estimation of the population distribution of individual fitness with estimation based on treating individual life histories in isolation, as samples of size one (e.g. McGraw & Caswell, 1996).

Brittany Coast↗
USGS2010

Bayesian estimation of weak material dispersion: Theory and experiment

This work considers the estimation of dispersion in materials via an interferometric technique. At its core, the problem involves extracting the quadratic variation in phase over a range of wavelengths based on measured optical intensity. The estimation problem becomes extremely difficult for weakly dispersive materials where the quadratic nonlinearity is very small relative to the uncertainty inherent in experiment. This work provides a means of estimating dispersion in the face of such uncertainty. Specifically, we use a Markov Chain Monte Carlo implementation of Bayesian analysis to provide both the dispersion estimate and the associated confidence interval. The interplay between various system parameters and the size of the resulting confidence interval is discussed. The approach is then applied to several different experimental samples.

Optics Express↗
USGS2010

Bayesian Inference: with ecological applications

This text provides a mathematically rigorous yet accessible and engaging introduction to Bayesian inference with relevant examples that will be of interest to biologists working in the fields of ecology, wildlife management and environmental studies as well as students in advanced undergraduate statistics.. This text opens the door to Bayesian inference, taking advantage of modern computational efficiencies and easily accessible software to evaluate complex hierarchical models.

Book↗
USGS2007

Toxicity and hazard of vanadium to mallard ducks (Anas platyrhynchos) and Canada geese (Branta canadensis)

A recent Canada goose ( Branta canadensis ) die-off at a petroleum refinery fly ash pond in Delaware was attributed to vanadium (V) toxicity. Because of the paucity of V toxicity data for wild birds, a series of studies was undertaken using the forms of V believed to have resulted in this incident. In 7-d single oral dose trials with mallard drakes ( Anas platyrhynchos ), the estimated median lethal dose (LD50) for vanadium pentoxide was 113 mg/kg body weight, while the LD50 for sodium metavanadate was 75.5 mg/kg. Sodium metavanadate was found to be even more potent (LD50 = 37.2 mg/kg) in male Canada geese. The most distinctive histopathological lesion of both forms of V was lympho-granulocytic enteritis with hemorrhage into the intestinal lumen. Vanadium accumulation in liver and kidney was proportional to the administered dose, and predictive analyses based on these data suggest that V concentrations of 10 μg/g dry weight (dw) in liver and 25 μg/g dw in kidney are associated with mortality (>90% confidence that exposure is >LD50) in mallards acutely exposed to sodium metavanadate. Chronic exposure to increasing dietary concentrations of sodium metavanadate (38.5 to 2651 ppm) over 67 d resulted in V accumulation in liver and kidney (25.2 and 13.6 μg/g dw, respectively), mild intestinal hemorrhage, blood chemistry changes, and evidence of hepatic oxidative stress in mallards, although some of these responses may have been confounded by food avoidance and weight loss. Dietary exposure of mallards to 250 ppm sodium metavanadate for 4 wk resulted in modest accumulation of V in liver and kidney (<5 μg/g dw) and mild intestinal hemorrhage. Based on these data and other observations, it is unlikely that chronic low-level dietary exposure to V poses a direct lethal hazard to wildlife. However, point sources, such as the V-laden fly ash pond encountered by geese at the petroleum refinery in Delaware, may pose a significant hazard to water birds.

Journal of Toxicology and Environmental Health, Pa↗
USGS2005

Quantifying production of salmon fry in an unscreened irrigation system: A case study on the Rangitata River, New Zealand

Diversion of out-migrant juvenile salmon into unscreened irrigation and hydroelectric canals is thought to have contributed significantly to declining populations of anadromous salmonids in the Pacific Northwest but is seldom studied in detail. Here we describe a program to study the fate of Chinook salmon Oncorhynchus tshawytscha fry diverted into the unscreened Rangitata Diversion Race (RDR) on the Rangitata River, New Zealand, by trapping fish in a random sample of on-farm canals in irrigation schemes (systems) served by the RDR. The catch rate at a site 9 km below the intake was strongly related to Rangitata River flow, but catches further downstream were unrelated to flow. Most fish entering the RDR were fry or early postfry (<70 mm fork length (FL)), but up to 92% of the fish trapped in on-farm canals were fingerlings (>70 mm FL), suggesting that many such fish became resident in the RDR for up to 3 months. Consequently, our estimate of the total number of fish leaving the RDR via on-farm canals (204,200 fish; 95% confidence limits = 127,100 and 326,700) is a conservative measure of the number lost from the Rangitata River because it does not allow for mortality within the RDR. We did not quantify the proportion of Rangitata River out-migrants that entered the RDR, but our results suggest that this figure was at least 5% and that it may have been as high as 25%, depending on mortality rates within the Rangitata River main stem and the RDR itself.

Rangitata River↗
USGS2005

Modeling association among demographic parameters in analysis of open population capture-recapture data

We present a hierarchical extension of the Cormack–Jolly–Seber (CJS) model for open population capture–recapture data. In addition to recaptures of marked animals, we model first captures of animals and losses on capture. The parameter set includes capture probabilities, survival rates, and birth rates. The survival rates and birth rates are treated as a random sample from a bivariate distribution, thus the model explicitly incorporates correlation in these demographic rates. A key feature of the model is that the likelihood function, which includes a CJS model factor, is expressed entirely in terms of identifiable parameters; losses on capture can be factored out of the model. Since the computational complexity of classical likelihood methods is prohibitive, we use Markov chain Monte Carlo in a Bayesian analysis. We describe an efficient candidate-generation scheme for Metropolis–Hastings sampling of CJS models and extensions. The procedure is illustrated using mark-recapture data for the moth Gonodontis bidentata .

Biometrics↗
USGS2005

A general class of multinomial mixture models for anuran calling survey data

We propose a general framework for modeling anuran abundance using data collected from commonly used calling surveys. The data generated from calling surveys are indices of calling intensity (vocalization of males) that do not have a precise link to actual population size and are sensitive to factors that influence anuran behavior. We formulate a model for calling-index data in terms of the maximum potential calling index that could be observed at a site (the “latent abundance class”), given its underlying breeding population, and we focus attention on estimating the distribution of this latent abundance class. A critical consideration in estimating the latent structure is imperfect detection, which causes the observed abundance index to be less than or equal to the latent abundance class. We specify a multinomial sampling model for the observed abundance index that is conditional on the latent abundance class. Estimation of the latent abundance class distribution is based on the marginal likelihood of the index data, having integrated over the latent class distribution. We apply the proposed modeling framework to data collected as part of the North American Amphibian Monitoring Program (NAAMP).

Ecology↗
USGS2005

Nonlinearity and seasonal bias in an index of brushtail possum abundance

Introduced brushtail possums ( Trichosurus vulpecula ) are a widespread pest of conservation and agriculture in New Zealand, and considerable effort has been expended controlling populations to low densities. A national protocol for monitoring the abundance of possums, termed trap catch index (TCI), was adopted in 1996. The TCI requires that lines of leghold traps set at 20-m spacing are randomly located in a management area. The traps are set for 3 fine nights and checked daily, and possums are killed and traps reset. The TCI is the mean percentage of trap nights that possums were caught, corrected for sprung traps and nontarget captures, with trap line as the sampling unit. We studied 1 forest and 1 farmland area in the North Island, New Zealand, to address concerns that TCI estimates may not be readily comparable because of seasonal changes in the capture probability of possums. We located blocks of 6 trap lines at each area and randomly trapped 1 line in each block in 3 seasons (summer, winter, and spring) in 2000 and 2001. We developed a model to allow for variation in local population size and nightly capture probability, and fitted the model using the Bayesian analysis software BUGS . Capture probability declined with increasing abundance of possums, generating a nonlinear TCI. Capture probability in farmland was lower during spring relative to winter and summer, and to forest during summer. In the absence of a proven and cost-effective alternative, our results support the continued use of the TCI for monitoring the abundance of possums in New Zealand. Seasonal biases in the TCI should be minimized by conducting repeat sampling in the same season.

Journal of Wildlife Management↗