Estimating Demographic Parameters for Bearded Seals, , in Alaska Using Close-Kin Mark-Recapture Methods.

Reliable estimates of population abundance and demographics are essential for managing harvested species. Ice-associated phocids, "ice seals," are a vital resource for subsistence-dependent coastal Native communities in western and northern Alaska, USA. In 2012, the Beringia distinct population segment of the bearded seal, , was listed as "threatened" under the US Endangered Species Act requiring greater scrutiny for management assessments.

Marginal inference for hierarchical generalized linear mixed models with patterned covariance matrices using the Laplace approximation.

We develop hierarchical models and methods in a fully parametric approach to generalized linear mixed models for any patterned covariance matrix. The Laplace approximation is used to marginally estimate covariance parameters by integrating over all fixed and latent random effects. The Laplace approximation relies on Newton-Raphson updates, which also leads to predictions for the latent random effects.

Aerial survey estimates of polar bears and their tracks in the Chukchi Sea.

Polar bears are of international conservation concern due to climate change but are difficult to study because of low densities and an expansive, circumpolar distribution. In a collaborative U.S.

Developing and assessing a density surface model in a Bayesian hierarchical framework with a focus on uncertainty: insights from simulations and an application to fin whales ().

Density surface models (DSMs) are an important tool in the conservation and management of cetaceans. Most previous applications of DSMs have adopted a two-step approach to model fitting (hereafter referred to as the Two-Stage Method), whereby detection probabilities are first estimated using distance sampling detection functions and subsequently used as an offset when fitting a density-habitat model. Although variance propagation techniques have recently become available for the Two-Stage Method, most previous applications have not propagated detection probability uncertainty into final density estimates.

Taxonomy-based hierarchical analysis of natural mortality: polar and subpolar phocid seals.

Knowledge of life-history parameters is frequently lacking in many species and populations, often because they are cryptic or logistically challenging to study, but also because life-history parameters can be difficult to estimate with adequate precision. We suggest using hierarchical Bayesian analysis (HBA) to analyze variation in life-history parameters among related species, with prior variance components representing shared taxonomy, phenotypic plasticity, and observation error. We develop such a framework to analyze U-shaped natural mortality patterns typical of mammalian life history from a variety of sparse datasets.

On Extrapolating Past the Range of Observed Data When Making Statistical Predictions in Ecology.

Ecologists are increasingly using statistical models to predict animal abundance and occurrence in unsampled locations. The reliability of such predictions depends on a number of factors, including sample size, how far prediction locations are from the observed data, and similarity of predictive covariates in locations where data are gathered to locations where predictions are desired. In this paper, we propose extending Cook's notion of an independent variable hull (IVH), developed originally for application with linear regression models, to generalized regression models as a way to help assess the potential reliability of predictions in unsampled areas.

Accommodating species identification errors in transect surveys.

Ecologists often use transect surveys to estimate the density and abundance of animal populations. Errors in species classification are often evident in such surveys, yet few statistical methods exist to properly account for them. In this paper, we examine biases that result from species misidentification when ignored, and we develop statistical models to provide unbiased estimates of density in the face of such errors.

Integrated modeling of bilateral photo-identification data in mark-recapture analyses.

When natural marks provide sufficient resolution to identify individual animals, noninvasive sampling using cameras has a number of distinct advantages relative to "traditional" mark-recapture methods. However, analyses from photo-identification records often pose additional challenges. For example, it is often unclear how to link left- and right-side photos to the same individual, and previous studies have primarily used data from just one side for statistical inference.

A hierarchical modeling framework for multiple observer transect surveys.

Ecologists often use multiple observer transect surveys to census animal populations. In addition to animal counts, these surveys produce sequences of detections and non-detections for each observer. When combined with additional data (i.

Laparoscopic resection of an epidermoid cyst within an intrapancreatic accessory spleen: a case report and review article.

Case Report: We report a case of an epidermoid cyst within an intrapancreatic accessory spleen that was treated by laparoscopic excision. A 39-year-old man with no abdominal symptoms was incidentally found to have a cystic pancreatic lesion on computed tomography scan undertaken for suspected deep vein thrombosis. Further computed tomography and magnetic resonance imaging confirmed similar findings and the laparoscopic resection of the distal pancreas and spleen was undertaken as malignancy could not be excluded.

Integrated population modeling of black bears in Minnesota: implications for monitoring and management.

Background: Wildlife populations are difficult to monitor directly because of costs and logistical challenges associated with collecting informative abundance data from live animals. By contrast, data on harvested individuals (e.g.

Bayesian analysis of wildlife age-at-harvest data.

State and federal natural resource management agencies often collect age-structured harvest data. These data represent finite realizations of stochastic demographic and sampling processes and have long been used by biologists to infer population trends. However, different sources of data have been combined in ad hoc ways and these methods usually failed to incorporate sampling error.

Adjusting age and stage distributions for misclassification errors.

Ecologists often use samples from the age or stage structure of a population to make inferences about population-level processes and to parameterize matrix models. Typically, researchers make a simplifying assumption that age and stage classes are determined without error, when in fact some level of misclassification often can be expected. If unaccounted for, misclassification will lead to overly optimistic levels of precision and can cause biased estimates of age or stage structure.

Estimating the abundance of mouse populations of known size: promises and pitfalls of new methods.

Knowledge of animal abundance is fundamental to many ecological studies. Frequently, researchers cannot determine true abundance, and so must estimate it using a method such as mark-recapture or distance sampling. Recent advances in abundance estimation allow one to model heterogeneity with individual covariates or mixture distributions and to derive multimodel abundance estimators that explicitly address uncertainty about which model parameterization best represents truth.

A general model for the analysis of mark-resight, mark-recapture, and band-recovery data under tag loss.

Estimates of waterfowl demographic parameters often come from resighting studies where birds fit with individually identifiable neck collars are resighted at a distance. Concerns have been raised about the effects of collar loss on parameter estimates, and the reliability of extrapolating from collared individuals to the population. Models previously proposed to account for collar loss do not allow survival or harvest parameters to depend on neck collar presence or absence.

Determinants of antileukemia effects of allogeneic NK cells.

In HLA-nonidentical bone marrow transplantation, we studied the characteristics of donor NK cells, recipient leukemia cells, and the cytokine environment that predict the antileukemia effects of allogeneic NK cells. We found that the risk of relapse in pediatric patients with hematologic malignancies was best predicted by a model taking into consideration the presence of inhibitory killer cell Ig-like receptors (KIRs) on the donor's NK cells and the absence of corresponding KIR ligand in the recipient's HLA repertoire (a receptor-ligand model). The risk of relapse was prognosticated less precisely by the Perugia donor-recipient KIR ligand-ligand mismatch model or by a natural cytotoxicity model.