Geology topics

William A. Link

Publications and source records attributed to William A. Link.

At least 19 recordsLinked to original sources

USGS2024

Identifying Pareto-efficient eradication strategies for invasive populations

Invasive species are a major cause of biodiversity loss and are notoriously expensive and challenging to manage. We developed a decision-analytic framework for evaluating invasive species removal strategies, given objectives of maximizing eradication probability and minimizing costs. The framework uses an existing estimation model for spatially referenced removal data—one of the most accessible types of invasive species data—to obtain estimates of population growth rate, movement probability, and detection probability. We use these estimates in simulations to identify Pareto-efficient strategies—strategies where increases in eradication probability cannot be obtained without increases in cost—from a set of proposed strategies. We applied the framework post hoc to a successful eradication of veiled chameleons ( Chamaeleo calyptratus ) and identified the potential for substantial improvements in efficiency. Our approach provides managers and policymakers with tools to identify cost-effective strategies for a range of invasive species using only prior knowledge or data from initial physical removals.

Hawaii↗

USGS2020

Sources of variation in maternal allocation in a long-lived mammal

1. Life history theory predicts allocation of energy to reproduction varies with maternal age, but additional maternal features may be important to the allocation of energy to reproduction. We aimed to characterize age‐specific variation in maternal allocation and assess the relationship between maternal allocation and other static and dynamic maternal features. Mass measurements of 531 mothers and pups were used with Bayesian hierarchical models to explain the relationship between diverse maternal attributes and both the proportion of mass allocated by Weddell seal mothers, and the efficiency of mass transfer from mother to pup during lactation as well as the weaning mass of pups. Our results demonstrated that maternal mass was strongly and positively associated with the relative reserves allocated by a mother and a pup's weaning mass but that the efficiency of mass transfer declines with maternal parturition mass. Birthdate was positively associated with proportion mass allocation and pup weaning mass, but mass transfer efficiency was predicted to be highest at the mean birthdate. The relative allocation of maternal reserves declined with maternal age but the efficiency of mass transfer to pups increases, suggestive of selective disappearance of poor‐quality mothers. These findings highlight the importance of considering multiple maternal features when assessing variation in maternal allocation.

Journal of Animal Ecology↗

USGS2020

Model selection for the North American Breeding Bird Survey

The North American Breeding Bird Survey (BBS) provides data that can be used in complex, multiscale analyses of population change, while controlling for scale‐specific nuisance factors. Many alternative models can be fit to the data, but most model selection procedures are not appropriate for hierarchical models. Leave‐one‐out cross‐validation (LOOCV), in which relative model fit is assessed by omitting an observation and assessing the prediction of a model fit using the remainder of the data, provides a reasonable approach for assessing models, but is time consuming and not feasible to apply for all observations in large data sets. We report the first large‐scale formal model selection for BBS data, applying LOOCV to stratified random samples of observations from BBS data. Our results are for 548 species of North American birds, comparing the fit of four alternative models that differ in year effect structures and in descriptions of extra‐Poisson overdispersion. We use a hierarchical model among species to evaluate posterior probabilities that models are best for individual species. Models in which differences in year effects are conditionally independent (D models) were generally favored over models in which year effects are modeled by a slope parameter and a random year effect (S models), and models in which extra‐Poisson overdispersion effects are independent and t ‐distributed (H models) tended to be favored over models where overdispersion was independent and normally distributed. Our conclusions lead us to recommend a change from the conventional S model to D and H models for the vast majority of species (544/548). Comparison of estimated population trends based on the favored model relative to the S model currently used for BBS summaries indicates no consistent differences in estimated trends. Of the 18 species that showed large differences in estimated trends between models, estimated trends from the default S model were more extreme, reflecting the influence of the slope parameter in that model for species that are undergoing large population changes. WAIC, a computationally simpler alternative to LOOCV, does not appear to be a reliable alternative to LOOCV.

Ecological Applications↗

USGS2019

Consistency counts: Modeling the effects of a change in protocol on Breeding Bird Survey counts

Analysis of North American Breeding Bird Survey (BBS) data requires controls for factors that influence detectability of birds along survey routes. Identifying factors that influence the counting process and incorporating them into analyses is a primary means of limiting bias in estimates of population change. Twedt (2015) implemented an alternative counting protocol on operational and non-random BBS survey routes in the southeastern United States. Observers on selected routes employed a time-distance protocol in which they recorded birds in 1-minute intervals and in 2 distance categories. We hypothesized that processing and recording observations using this time-distance protocol could cause observers to count fewer birds relative to observers using the standard protocol. We used a hierarchical log-linear model with a categorical covariate associated with protocol (standard vs time-distance) to assess whether use of the time-distance protocol had a measurable effect on counting birds along BBS routes. We applied this model to BBS data from portions of eight states in which the time-distance protocol was implemented and estimated a protocol effect for 167 bird species. We documented a significant overall effect of the time-distance protocol on observers’ counts of birds. On average, the effect of the time-distance protocol was a 10% decline in count, and 80% of species had lower counts when the time-distance protocol was used on a survey route. However, because the time-distance protocol was only used on a small portion of the operational BBS routes and for a limited time, including the covariate for the time-distance protocol data had insignificant effects on analysis of population change. Although the covariate controlled for the effects of the time-distance protocol in BBS data, the results emphasize the importance of standardization as well as a need to track and, if necessary, control in analyses for changes in counting procedures along BBS routes.

The Condor↗

USGS2018

Analysis of population change and movement using robust design removal data

In capture-mark-reencounter studies, Pollock’s robust design combines methods for open populations with methods for closed populations. Open population features of the robust design allow for estimation of rates of death or permanent emigration, and closed population features enhance estimation of population sizes. We describe a similar design, but for use with removal data. Data collection occurs on secondary sampling occasions clustered within primary sampling periods. Primary sampling periods are intervals of brief enough duration that it can be safely assumed that the population is unchanged by births, deaths, immigration or emigration during them; all population change and movement occurs between primary sampling periods. Our model provides a basis for inference about population size, changes in population size, and movement rates among sample locations between primary sampling periods. Movement rates are modeled as functions of distance and time. Capture probabilities are modeled as a function of effort. We apply the model to data obtained in attempting to eradicate an introduced population of veiled chameleons ( Chamaeleo calyptratus ) on the island of Maui in Hawaii.

Journal of Agricultural, Biological, and Environme↗

USGS2018

Variation in the vital rates of an Antarctic marine predator: the role of individual heterogeneity

Variation in life‐history traits such as lifespan and lifetime reproductive output is thought to arise, in part, due to among‐individual differences in the underlying probabilities of survival and reproduction. However, the stochastic nature of demographic processes can also generate considerable variation in fitness‐related traits among otherwise‐identical individuals. An improved understanding of life‐history evolution and population dynamics therefore depends on evaluating the relative role of each of these processes. Here, we used a 33‐yr data set with reproductive histories for 1,274 female Weddell seals from Erebus Bay, Antarctica, to assess the strength of evidence for among‐individual heterogeneity in the probabilities of survival and reproduction, while accounting for multiple other sources of variation in vital rates. Our analysis used recent advances in Bayesian model selection techniques and diagnostics to directly compare model fit and predictive power between models that included individual effects on survival and reproduction to those that did not. We found strong evidence for costs of reproduction to both survival and future reproduction, with breeders having rates of survival and subsequent reproduction that were 3% and 6% lower than rates for non‐breeders. We detected age‐related changes in the rates of survival and reproduction, but the patterns differed for the two rates. Survival rates steadily declined from 0.92 at age 7 to 0.56 at the maximal age of 31 yr. In contrast, reproductive rates increased from 0.68 at age 7 to 0.79 at age 16 and then steadily declined to 0.37 for the oldest females. Models that included individual effects explained more variation in observed life histories and had better estimated predictive power than those that did not, indicating their importance in understanding sources of variation among individuals in life‐history traits. We found that among‐individual heterogeneity in survival was small relative to that for reproduction. Our study, which found patterns of variation in vital rates that are consistent with a series of predictions from life‐history theory, is the first to provide a thorough assessment of variation in important vital rates for a long‐lived, high‐latitude marine mammal while taking full advantage of recent developments in model evaluation.

Ecology↗

USGS2018

On the robustness of N‐mixture models

N ‐mixture models provide an appealing alternative to mark–recapture models, in that they allow for estimation of detection probability and population size from count data, without requiring that individual animals be identified. There is, however, a cost to using the N ‐mixture models: inference is very sensitive to the model's assumptions. We consider the effects of three violations of assumptions that might reasonably be expected in practice: double counting, unmodeled variation in population size over time, and unmodeled variation in detection probability over time. These three examples show that small violations of assumptions can lead to large biases in estimation. The violations of assumptions we consider are not only small qualitatively, but are also small in the sense that they are unlikely to be detected using goodness‐of‐fit tests. In cases where reliable estimates of population size are needed, we encourage investigators to allocate resources to acquiring additional data, such as recaptures of marked individuals, for estimation of detection probabilities.

Ecology↗

USGS2017

On the reliability of N‐mixture models for count data

N‐mixture models describe count data replicated in time and across sites in terms of abundance N and detectability p . They are popular because they allow inference about N while controlling for factors that influence p without the need for marking animals. Using a capture–recapture perspective, we show that the loss of information that results from not marking animals is critical, making reliable statistical modeling of N and p problematic using just count data. One cannot reliably fit a model in which the detection probabilities are distinct among repeat visits as this model is overspecified. This makes uncontrolled variation in p problematic. By counter example, we show that even if p is constant after adjusting for covariate effects (the “constant p ” assumption) scientifically plausible alternative models in which N (or its expectation) is non‐identifiable or does not even exist as a parameter, lead to data that are practically indistinguishable from data generated under an N‐mixture model. This is particularly the case for sparse data as is commonly seen in applications. We conclude that under the constant p assumption reliable inference is only possible for relative abundance in the absence of questionable and/or untestable assumptions or with better quality data than seen in typical applications. Relative abundance models for counts can be readily fitted using Poisson regression in standard software such as R and are sufficiently flexible to allow controlling for p through the use covariates while simultaneously modeling variation in relative abundance. If users require estimates of absolute abundance, they should collect auxiliary data that help with estimation of p .

Biometrics↗

USGS2017

Expanding the North American Breeding Bird Survey analysis to include additional species and regions

The North American Breeding Bird Survey (BBS) contains data for >700 bird species, but analyses often focus on a core group of ∼420 species. We analyzed data for 122 species of North American birds for which data exist in the North American Breeding Bird Survey (BBS) database but are not routinely analyzed on the BBS Summary and Analysis Website. Many of these species occur in the northern part of the continent, on routes that fall outside the core survey area presently analyzed in the United States and southern Canada. Other species not historically analyzed occur in the core survey area with very limited data but have large portions of their ranges in Mexico and south. A third group of species not historically analyzed included species thought to be poorly surveyed by the BBS, such as rare, coastal, or nocturnal species. For 56 species found primarily in regions north of the core survey area, we expanded the scope of the analysis, using data from 1993 to 2014 during which ≥3 survey routes had been sampled in 6 northern strata (Bird Conservation regions in Alaska, Yukon, and Newfoundland and Labrador) and fitting log-linear hierarchical models for an augmented BBS survey area that included both the new northern strata and the core survey area. We also applied this model to 168 species historically analyzed in the BBS that had data from these additional northern strata. For both groups of species we calculated survey-wide trends for the both core and augmented survey areas from 1993 to 2014; for species that did not occur in the newly defined strata, we computed trends from 1966 to 2014. We evaluated trend estimates in terms of established credibility criteria for BBS results, screening for imprecise trends, small samples, and low relative abundance. Inclusion of data from the northern strata permitted estimation of trend for 56 species not historically analyzed, but only 4 of these were reasonably monitored and an additional 13 were questionably monitored; 39 of these species were likely poorly monitored because of small numbers of samples or very imprecisely estimated trends. Only 4 of 66 “new” species found in the core survey area were reasonably monitored by the BBS; 20 were questionably monitored; and 42 were likely poorly monitored by the BBS because of inefficiency in precision, abundance, or sample size. The hierarchical analyses we present provide a means for reasonable inclusion of the additional species and strata in a common analysis with data from the core area, a critical step in the evolution of the BBS as a continent-scale survey. We recommend that results be presented both 1) from 1993 to the present using the expanded survey area, and 2) from 1966 to the present for the core survey area. Although most of the “new” species we analyzed were poorly monitored by the BBS during 1993–2014, continued expansion of the BBS will improve the quality of information in future analyses for these species and for the many other species presently monitored by the BBS.

Journal of Fish and Wildlife Management↗

USGS2017

Model selection for the North American Breeding Bird Survey: A comparison of methods

The North American Breeding Bird Survey (BBS) provides data for >420 bird species at multiple geographic scales over 5 decades. Modern computational methods have facilitated the fitting of complex hierarchical models to these data. It is easy to propose and fit new models, but little attention has been given to model selection. Here, we discuss and illustrate model selection using leave-one-out cross validation, and the Bayesian Predictive Information Criterion (BPIC). Cross-validation is enormously computationally intensive; we thus evaluate the performance of the Watanabe-Akaike Information Criterion (WAIC) as a computationally efficient approximation to the BPIC. Our evaluation is based on analyses of 4 models as applied to 20 species covered by the BBS. Model selection based on BPIC provided no strong evidence of one model being consistently superior to the others; for 14/20 species, none of the models emerged as superior. For the remaining 6 species, a first-difference model of population trajectory was always among the best fitting. Our results show that WAIC is not reliable as a surrogate for BPIC. Development of appropriate model sets and their evaluation using BPIC is an important innovation for the analysis of BBS data.

Condor↗

USGS2017

The first 50 years of the North American Breeding Bird Survey

The vision of Chandler (Chan) S. Robbins for a continental-scale omnibus survey of breeding birds led to the development of the North American Breeding Bird Survey (BBS). Chan was uniquely suited to develop the BBS. His position as a government scientist had given him experience with designing and implementing continental-scale surveys, his research background made him an effective advocate of the need for a survey to monitor pesticide effects on birds, and his prominence in the birding community gave him connections to infrastructure—a network of qualified volunteer birders who could conduct roadside surveys with standardized point counts. Having started in the eastern United States and the Atlantic provinces of Canada in 1966, the BBS now provides population change information for ∼546 species in the continental United States and Canada, and recently initiated routes in Mexico promise to greatly expand the areas and species covered by the survey. Although survey protocols have remained unchanged for 50 years, the BBS remains relevant in a changing world. Several papers that follow in this Special Section of The Condor: Ornithological Advances review how the BBS has been applied to conservation assessments, especially in combination with other large-scale survey data. A critical feature of the BBS program is an active research program into field and analytical methods to enhance the quality of the count data and to control for factors that influence detectability. Papers in the Special Section also present advances in BBS analyses that improve the utility of this expanding and sometimes controversial survey. In this Perspective, we introduce the Special Section by reviewing the history of the BBS, describing current analyses, and providing summary trend results for all species, highlighting 3 groups of conservation concern: grassland-breeding birds, aridland-breeding birds, and aerial insectivorous birds.

The Condor↗

USGS2016

Tarangire revisited: Consequences of declining connectivity in a tropical ungulate population

The hyper-abundance of migratory wildlife in many ecosystems depends on maintaining access to seasonally available resources. In Eastern and Southern Africa, land-use change and a loss of connectivity have coincided with widespread declines in the abundance and geographic range of ungulate populations. Using photographic capture-mark-recapture, we examine the historical pattern of loss of connectivity and its impact on population trends in a partially migratory wildebeest population in northern Tanzania. To estimate abundance, we use a novel modeling approach that overcomes bias associated with photo misidentifications. Our data indicate (1) diminished connectivity within and between seasonal areas as a result of human activities, (2) a reduction in the overall population size compared to historical numbers, with high variability over time, (3) the continued use of highly constrained movement corridors between the three main seasonal ranges, (4) higher recruitment in the non-migratory subpopulation (Lake Manyara National Park) than in other areas of the ecosystem, and (5) an increase in the relative abundance of resident to migrant wildebeest. Recent conservation efforts to protect seasonal habitat and to enforce anti-poaching policies outside protected areas have likely helped stabilize the population, at least temporarily, but we caution that several key vulnerabilities remain.

Tarangire-Manyara Ecosystem↗

USGS2016

Bayesian cross-validation for model evaluation and selection, with application to the North American Breeding Bird Survey

The analysis of ecological data has changed in two important ways over the last 15 years. The development and easy availability of Bayesian computational methods has allowed and encouraged the fitting of complex hierarchical models. At the same time, there has been increasing emphasis on acknowledging and accounting for model uncertainty. Unfortunately, the ability to fit complex models has outstripped the development of tools for model selection and model evaluation: familiar model selection tools such as Akaike's information criterion and the deviance information criterion are widely known to be inadequate for hierarchical models. In addition, little attention has been paid to the evaluation of model adequacy in context of hierarchical modeling, i.e., to the evaluation of fit for a single model. In this paper, we describe Bayesian cross-validation, which provides tools for model selection and evaluation. We describe the Bayesian predictive information criterion and a Bayesian approximation to the BPIC known as the Watanabe-Akaike information criterion. We illustrate the use of these tools for model selection, and the use of Bayesian cross-validation as a tool for model evaluation, using three large data sets from the North American Breeding Bird Survey.

Ecology↗

USGS2015

Combining waterfowl and breeding bird survey data to estimate wood duck breeding population size in the Atlantic Flyway

We combined data from the Atlantic Flyway Breeding Waterfowl Survey (AFBWS) and the North American Breeding Bird Survey (BBS) to estimate the number of wood ducks ( Aix sponsa ) in the United States portion of the Atlantic Flyway from 1993 to 2013. The AFBWS is a plot-based survey that covers most of the northern and central portions of the Flyway; when analyzed with adjustments for survey time of day effects, these data can be used to estimate population size. The BBS provides an index of wood duck abundance along roadside routes. Although factors influencing change in BBS counts over time can be controlled in BBS analysis, BBS indices alone cannot be used to derive population size estimates. We used AFBWS data to scale BBS indices for Bird Conservation Regions (BCR), basing the scaling factors on the ratio of estimated AFBWS population sizes to regional BBS indices for portions of BCRs that were common to both surveys. We summed scaled BBS results for portions of the Flyway not covered by the AFBWS with AFBWS population estimates to estimate a mean yearly total of 1,295,875 (mean 95% CI: 1,013,940–1,727,922) wood ducks. Scaling factors varied among BCRs from 16.7 to 148.0; the mean scaling factor was 68.9 (mean 95% CI: 53.5–90.9). Flyway-wide, population estimates from the combined analysis were consistent with alternative estimates derived from harvest data, and also provide population estimates within states and BCRs. We recommend their use in harvest and habitat management within the Atlantic Flyway.

Connecticut, Delaware, Maryland, Massachusetts, Ne↗

USGS2015

Individual heterogeneity in growth and age at sexual maturity: A gamma process analysis of capture–mark–recapture data

Knowledge of organisms’ growth rates and ages at sexual maturity is important for conservation efforts and a wide variety of studies in ecology and evolutionary biology. However, these life history parameters may be difficult to obtain from natural populations: individuals encountered may be of unknown age, information on age at sexual maturity may be uncertain and interval-censored, and growth data may include both individual heterogeneity and measurement errors. We analyzed mark–recapture data for Red-backed Salamanders ( Plethodon cinereus ) to compare sex-specific growth rates and ages at sexual maturity. Aging of individuals was made possible by the use of a von Bertalanffy model of growth, complemented with models for interval-censored and imperfect observations at sexual maturation. Individual heterogeneity in growth was modeled through the use of Gamma processes. Our analysis indicates that female P. cinereus mature earlier and grow more quickly than males, growing to nearly identical asymptotic size distributions as males.

Journal of Agricultural, Biological, and Environme↗

USGS2015

Truth, models, model sets, AIC, and multimodel inference: a Bayesian perspective

Statistical inference begins with viewing data as realizations of stochastic processes. Mathematical models provide partial descriptions of these processes; inference is the process of using the data to obtain a more complete description of the stochastic processes. Wildlife and ecological scientists have become increasingly concerned with the conditional nature of model-based inference: what if the model is wrong? Over the last 2 decades, Akaike's Information Criterion (AIC) has been widely and increasingly used in wildlife statistics for 2 related purposes, first for model choice and second to quantify model uncertainty. We argue that for the second of these purposes, the Bayesian paradigm provides the natural framework for describing uncertainty associated with model choice and provides the most easily communicated basis for model weighting. Moreover, Bayesian arguments provide the sole justification for interpreting model weights (including AIC weights) as coherent (mathematically self consistent) model probabilities. This interpretation requires treating the model as an exact description of the data-generating mechanism. We discuss the implications of this assumption, and conclude that more emphasis is needed on model checking to provide confidence in the quality of inference.

Journal of Wildlife Management↗

USGS2014

Modeling participation duration, with application to the North American Breeding Bird Survey

We consider “participation histories,” binary sequences consisting of alternating finite sequences of 1s and 0s, ending with an infinite sequence of 0s. Our work is motivated by a study of observer tenure in the North American Breeding Bird Survey (BBS). In our analysis, j indexes an observer’s years of service and X j is an indicator of participation in the survey; 0s interspersed among 1s correspond to years when observers did not participate, but subsequently returned to service. Of interest is the observer’s duration D = max { j : X j = 1}. Because observed records X = ( X 1 , X 2 ,..., X n ) 1 are of finite length, all that we can directly infer about duration is that D ⩾ max { j ⩽ n : X j = 1}; model-based analysis is required for inference about D . We propose models in which lengths of 0s and 1s sequences have distributions determined by the index j at which they begin; 0s sequences are infinite with positive probability, an estimable parameter. We found that BBS observers’ lengths of service vary greatly, with 25.3% participating for only a single year, 49.5% serving for 4 or fewer years, and an average duration of 8.7 years, producing an average of 7.7 counts.

Communications in Statistics - Theory and Methods↗

USGS2014

Hierarchical model analysis of the Atlantic Flyway Breeding Waterfowl Survey

We used log-linear hierarchical models to analyze data from the Atlantic Flyway Breeding Waterfowl Survey. The survey has been conducted by state biologists each year since 1989 in the northeastern United States from Virginia north to New Hampshire and Vermont. Although yearly population estimates from the survey are used by the United States Fish and Wildlife Service for estimating regional waterfowl population status for mallards (Anas platyrhynchos), black ducks (Anas rubripes), wood ducks (Aix sponsa), and Canada geese (Branta canadensis), they are not routinely adjusted to control for time of day effects and other survey design issues. The hierarchical model analysis permits estimation of year effects and population change while accommodating the repeated sampling of plots and controlling for time of day effects in counting. We compared population estimates from the current stratified random sample analysis to population estimates from hierarchical models with alternative model structures that describe year to year changes as random year effects, a trend with random year effects, or year effects modeled as 1-year differences. Patterns of population change from the hierarchical model results generally were similar to the patterns described by stratified random sample estimates, but significant visibility differences occurred between twilight to midday counts in all species. Controlling for the effects of time of day resulted in larger population estimates for all species in the hierarchical model analysis relative to the stratified random sample analysis. The hierarchical models also provided a convenient means of estimating population trend as derived statistics from the analysis. We detected significant declines in mallard and American black ducks and significant increases in wood ducks and Canada geese, a trend that had not been significant for 3 of these 4 species in the prior analysis. We recommend using hierarchical models for analysis of the Atlantic Flyway Breeding Waterfowl Survey.

Journal of Wildlife Management↗