Use of chemical tracers in assessing the diet and foraging regions of eastern North Pacific killer whales

Top predators in the marine environment integrate chemical signals acquired from their prey that reflect both the species consumed and the regions from which the prey were taken. These chemical tracers—stable isotope ratios of carbon and nitrogen; persistent organic pollutant (POP) concentrations, patterns and ratios; and fatty acid profiles—were measured in blubber biopsy samples from North Pacific killer whales (Orcinus orca) (n = 84) and were used to provide further insight into their diet, particularly for the offshore group, about which little dietary information is available. The offshore killer whales were shown to consume prey species that were distinctly different from those of sympatric resident and transient killer whales. In addition, it was confirmed that the offshores forage as far south as California. Thus, these results provide evidence that the offshores belong to a third killer whale ecotype. Resident killer whale populations showed a gradient in stable isotope profiles from west (central Aleutians) to east (Gulf of Alaska) that, in part, can be attributed to a shift from off-shelf to continental shelf-based prey. Finally, stable isotope ratio results, supported by field observations, showed that the diet in spring and summer of eastern Aleutian Island transient killer whales is apparently not composed exclusively of Steller sea lions.

Use of chemical tracers in assessing the diet and foraging regions of eastern North Pacific killer whales

Top predators in the marine environment integrate chemical signals acquired from their prey that reflect both the species consumed and the regions from which the prey were taken. These chemical tracers—stable isotope ratios of carbon and nitrogen; persistent organic pollutant (POP) concentrations, patterns and ratios; and fatty acid profiles—were measured in blubber biopsy samples from North Pacific killer whales (Orcinus orca) (n = 84) and were used to provide further insight into their diet, particularly for the offshore group, about which little dietary information is available. The offshore killer whales were shown to consume prey species that were distinctly different from those of sympatric resident and transient killer whales. In addition, it was confirmed that the offshores forage as far south as California. Thus, these results provide evidence that the offshores belong to a third killer whale ecotype. Resident killer whale populations showed a gradient in stable isotope profiles from west (central Aleutians) to east (Gulf of Alaska) that, in part, can be attributed to a shift from off-shelf to continental shelf-based prey. Finally, stable isotope ratio results, supported by field observations, showed that the diet in spring and summer of eastern Aleutian Island transient killer whales is apparently not composed exclusively of Steller sea lions.

Antler Size of Alaskan Moose Alces alces gigas: Effects of Population Density, Hunter Harvest and Use of Guides

Moose Alces alces gigas in Alaska, USA, exhibit extreme sexual dimorphism, with adult males possessing large, elaborate antlers. Antler size and conformation are influenced by age, nutrition and genetics, and these bony structures serve to establish social rank and affect mating success. Population density, combined with anthropogenic effects such as harvest, is thought to influence antler size. Antler size increased as densities of moose decreased, ostensibly a density-dependent response related to enhanced nutrition at low densities. The vegetation type where moose were harvested also affected antler size, with the largest-antlered males occupying more open habitats. Hunts with guides occurred in areas with low moose density, minimized hunter interference and increased rates of success. Such hunts harvested moose with larger antler spreads than did non-guided hunts. Knowledge and abilities allowed guides to satisfy demands of trophy hunters, who are an integral part of the Alaskan economy. Heavy harvest by humans was also associated with decreased antler size of moose, probably via a downward shift in the age structure of the population resulting in younger males with smaller antlers. Nevertheless, density-dependence was more influential than effects of harvest on age structure in determining antler size of male moose. Indeed, antlers are likely under strong sexual selection, but we demonstrate that resource availability influenced the distribution of these sexually selected characters across the landscape. We argue that understanding population density in relation to carrying capacity (K) and the age structure of males is necessary to interpret potential consequences of harvest on the genetics of moose and other large herbivores. Our results provide researchers and managers with a better understanding of variables that affect the physical condition, antler size, and perhaps the genetic composition of populations, which may be useful in managing and modeling moose populations.

Spatial modelling and prediction on river networks: up model, down model or hybrid?

Preservation of rivers and water resources is crucial in most environmental policies and many efforts are made to assess water quality. Environmental monitoring of large river networks are based on measurement stations. Compared to the total length of river networks, their number is often limited and there is a need to extend environmental variables that are measured locally to the whole river network. The objective of this paper is to propose several relevant geostatistical models for river modeling. These models use river distance and are based on two contrasting assumptions about dependency along a river network. Inference using maximum likelihood, model selection criterion and prediction by kriging are then developed. We illustrate our approach on two variables that differ by their distributional and spatial characteristics: summer water temperature and nitrate concentration. The data come from 141 to 187 monitoring stations in a network on a large river located in the Northeast of France that is more than 5000 km long and includes Meuse and Moselle basins. We first evaluated different spatial models and then gave prediction maps and error variance maps for the whole stream network.

An animal movement model incorporating home range and habitat selection

Wildlife biologists are often interested in how an animal uses space and the habitat resources within that space. We propose a single model that estimates an animal’s home range and habitat selection parameters within that range while accounting for the inherent autocorrelation in frequently sampled telemetry data. The model is applied to brown bear telemetry data in southeast Alaska.

Spatial statistical models that use flow and stream distance

We develop spatial statistical models for stream networks that can estimate relationships between a response variable and other covariates, make predictions at unsampled locations, and predict an average or total for a stream or a stream segment. There have been very few attempts to develop valid spatial covariance models that incorporate flow, stream distance, or both. The application of typical spatial autocovariance functions based on Euclidean distance, such as the spherical covariance model, are not valid when using stream distance. In this paper we develop a large class of valid models that incorporate flow and stream distance by using spatial moving averages. These methods integrate a moving average function, or kernel, against a white noise process. By running the moving average function upstream from a location, we develop models that use flow, and by construction they are valid models based on stream distance. We show that with proper weighting, many of the usual spatial models based on Euclidean distance have a counterpart for stream networks. Using sulfate concentrations from an example data set, the Maryland Biological Stream Survey (MBSS), we show that models using flow may be more appropriate than models that only use stream distance. For the MBSS data set, we use restricted maximum likelihood to fit a valid covariance matrix that uses flow and stream distance, and then we use this covariance matrix to estimate fixed effects and make kriging and block kriging predictions.

Review of Applied Spatial Data Analysis with R by R. S. Bivand, E. J. Pebesma, and V. Gomez-Rubio

Most authors struggle to pick a title that adequately conveys all of the material covered in a book. When I first saw Applied Spatial Data Analysis with R, I expected a review of spatial statistical models and their applications in packages (libraries) from the CRAN site of R. The authors’ title is not misleading, but I was very pleasantly surprised by how deep the word “applied” is here. The first half of the book essentially covers how R handles spatial data. To some statisticians this may be boring. Do you want, or need, to know the difference between S3 and S4 classes, how spatial objects in R are organized, and how various methods work on the spatial objects? A few years ago I would have said “no,” especially to the “want” part. Just let me slap my EXCEL spreadsheet into R and run some spatial functions on it. Unfortunately, the world is not so simple, and ultimately we want to minimize effort to get all of our spatial analyses accomplished. The first half of this book certainly convinced me that some extra effort in organizing my data into certain spatial class structures makes the analysis easier and less subject to mistakes. I also admit that I found it very interesting and I learned a lot.

Accounting for uncertainty in ecological analysis: the strengths and limitations of hierarchical statistical modeling

Analyses of ecological data should account for the uncertainty in the process(es) that generated the data. However, accounting for these uncertainties is a difficult task, since ecology is known for its complexity. Measurement and/or process errors are often the only sources of uncertainty modeled when addressing complex ecological problems, yet analyses should also account for uncertainty in sampling design, in model specification, in parameters governing the specified model, and in initial and boundary conditions. Only then can we be confident in the scientific inferences and forecasts made from an analysis. Probability and statistics provide a framework that accounts for multiple sources of uncertainty. Given the complexities of ecological studies, the hierarchical statistical model is an invaluable tool. This approach is not new in ecology, and there are many examples (both Bayesian and non-Bayesian) in the literature illustrating the benefits of this approach. In this article, we provide a baseline for concepts, notation, and methods, from which discussion on hierarchical statistical modeling in ecology can proceed. We have also planted some seeds for discussion and tried to show where the practical difficulties lie. Our thesis is that hierarchical statistical modeling is a powerful way of approaching ecological analysis in the presence of inevitable but quantifiable uncertainties, even if practical issues sometimes require pragmatic compromises.

Regional differences in the spatial and temporal heterogeneity of oceanographic habitat used by Steller sea lions

Over the past three decades, the decline and altered spatial distribution of the western stock of Steller sea lions (Eumetopias jubatus) in Alaska have been attributed to changes in the distribution or abundance of their prey due to the cumulative effects of fisheries and environmental perturbations. During this period, dietary prey occurrence and diet diversity were related to population decline within metapopulation regions of the western stock of Steller sea lions, suggesting that environmental conditions may be variable among regions. The objective of this study, therefore, was to examine regional differences in the spatial and temporal heterogeneity of oceanographic habitat used by Steller sea lions within the context of recent measures of diet diversity and population trajectories. Habitat use was assessed by deploying satellite-depth recorders and satellite relay data loggers on juvenile Steller sea lions (n = 45) over a five-year period (2000–2004) within four regions of the western stock, including the western, central, and eastern Aleutian Islands, and central Gulf of Alaska. Areas used by sea lions during summer months (June, July, and August) were demarcated using satellite telemetry data and characterized by environmental variables (sea surface temperature [SST] and chlorophyll a [chl a]), which possibly serve as proxies for environmental processes or prey. Spatial patterns of SST diversity and Steller sea lion population trends among regions were fairly consistent with trends reported for diet studies, possibly indicating a link between environmental diversity, prey diversity, and distribution or abundance of Steller sea lions. Overall, maximum spatial heterogeneity coupled with minimal temporal variability of SST appeared to be beneficial for Steller sea lions. In contrast, these patterns were not consistent for chl a, and there appeared to be an ecological threshold. Understanding how Steller sea lions respond to measures of environmental heterogeneity will ultimately be useful for implementing ecosystem management approaches and developing additional conservation strategies.

Distance software: design and analysis of distance sampling surveys for estimating population size

1. Distance sampling is a widely used technique for estimating the size or density of biological populations. Many distance sampling designs and most analyses use the software Distance. 2. We briefly review distance sampling and its assumptions, outline the history, structure and capabilities of Distance, and provide hints on its use. 3. Good survey design is a crucial prerequisite for obtaining reliable results. Distance has a survey design engine, with a built-in geographic information system, that allows properties of different proposed designs to be examined via simulation, and survey plans to be generated. 4. A first step in analysis of distance sampling data is modeling the probability of detection. Distance contains three increasingly sophisticated analysis engines for this: conventional distance sampling, which models detection probability as a function of distance from the transect and assumes all objects at zero distance are detected; multiple-covariate distance sampling, which allows covariates in addition to distance; and mark–recapture distance sampling, which relaxes the assumption of certain detection at zero distance. 5. All three engines allow estimation of density or abundance, stratified if required, with associated measures of precision calculated either analytically or via the bootstrap. 6. Advanced analysis topics covered include the use of multipliers to allow analysis of indirect surveys (such as dung or nest surveys), the density surface modeling analysis engine for spatial and habitat-modeling, and information about accessing the analysis engines directly from other software. 7. Synthesis and applications. Distance sampling is a key method for producing abundance and density estimates in challenging field conditions. The theory underlying the methods continues to expand to cope with realistic estimation situations. In step with theoretical developments, state-of- the-art software that implements these methods is described that makes the methods accessible to practicing ecologists.

Demography and population viability of polar bears in the Gulf of Boothia, Nunavut

We estimated demographic parameters and harvest risks for polar bears (Ursus maritimus) inhabiting the Gulf of Boothia, Nunavut, from 1976 to 2000. We computed survival and abundance from capture–recapture and recovery data (630 marks) using a Burnham joint live–dead model implemented in program MARK. Annual mean total survival (including harvest) was 0.889 ± 0.179 ( x ± 1 SE) for cubs, 0.883 ± 0.087 for subadults (ages 1–4), 0.919 ± 0.044 for adult females, and 0.917 ± 0.041 for adult males. Abundance in the last 3 yr of study was 1,592 ± 361 bears. Mean size of newborn litters was 1.648 ± 0.098 cubs. By age 7, 0.97 ± 0.30 of available females were producing litters. Harvest averaged 38.4 ± 4.2 bears/year in the last 5 yr of study; however, the 2002–2007 kill averaged 56.4 bears/yr. We used a harvested Population Viability Analysis (PVA) to examine impacts of increasing rates of harvest. We estimated the current population growth rate, λH, to be 1.025 ± 0.032. Although this suggests the population is growing, progressive environmental changes may require more frequent population inventory studies to maintain the same levels of harvest risk.

Development and application of DNA techniques for validating and improving pinniped diet estimates

Polymerase chain reaction techniques were developed and applied to identify DNA from .40 species of prey contained in fecal (scat) soft-part matrix collected at terrestrial sites used by Steller sea lions (Eumetopias jubatus) in British Columbia and the eastern Aleutian Islands, Alaska. Sixty percent more fish and cephalopod prey were identified by morphological analyses of hard parts compared with DNA analysis of soft parts (hard parts identified higher relative proportions of Ammodytes sp., Cottidae, and certain Gadidae). DNA identified 213 prey occurrences, of which 75 (35%) were undetected by hard parts (mainly Salmonidae, Pleuronectidae, Elasmobranchii, and Cephalopoda), and thereby increased species occurrences by 22% overall and species richness in 44% of cases (when comparing 110 scats that amplified prey DNA). Prey composition was identical within only 20% of scats. Overall, diet composition derived from both identification techniques combined did not differ significantly from hard-part identification alone, suggesting that past scat-based diet studies have not missed major dietary components. However, significant differences in relative diet contributions across scats (as identified using the two techniques separately) reflect passage rate differences between hard and soft digesta material and highlight certain hypothesized limitations in conventional morphological-based methods (e.g., differences in resistance to digestion, hard part regurgitation, partial and secondary prey consumption), as well as potential technical issues (e.g., resolution of primer efficiency and sensitivity and scat subsampling protocols). DNA analysis of salmon occurrence (from scat soft-part matrix and 238 archived salmon hard parts) provided species-level taxonomic resolution that could not be obtained by morphological identification and showed that Steller sea lions were primarily consuming pink (Oncorhynchus gorbuscha) and chum (Oncorhynchus keta) salmon. Notably, DNA from Atlantic salmon (Salmo salar) that likely originated from a distant fish farm was also detected in two scats from one site in the eastern Aleutian Islands. Overall, molecular techniques are valuable for identifying prey in the fecal remains of marine predators. Combining DNA and hard-part identification will effectively alleviate certain predicted biases and will ultimately enhance measures of diet richness, fisheries interactions (especially salmon-related ones), and the ecological role of pinnipeds and other marine predators, to the benefit of marine wildlife conservationists and fisheries managers.

History and fate of a small isolated population of Weddell seals at White Island, Antarctica

Weddell seals (Leptonychotes weddellii Lesson) at White Island, Antarctica form a small, completely enclosed, natural population hypothesized to be of recent origin, likely founded by individuals from nearby Erebus Bay. This population constitutes an ideal model to document a founder event and ensuing genetic drift, with implications for conservation. Here we combined historical accounts, census and tagging data since the late 1960s, and genetic data (41 microsatellite loci and mitochondrial DNA sequences) from 84 individuals representing nearly all individuals present between 1990 and 2000 to investigate the history of the founding of the White Island population, document its population dynamics and evaluate possible future threats. We fully resolved parental relationships over three overlapping generations. Cytonuclear disequilibrium among the first generation suggested that it comprised the direct descendants of a founding group. We estimated that the White Island population was founded by a small group of individuals that accessed the island during a brief break in the surrounding sea ice in the mid-1950s, consistent with historical accounts. Direct and indirect methods of calculating effective population size were highly congruent and suggested a minimum founding group consisting of three females and two males. The White Island population showed altered reproductive dynamics compared to Erebus Bay, including highly skewed sex ratio, documented inbred mating events, and the oldest known reproducing Weddell seals. A comparison with the putative source population showed that the White Island population has an effective inbreeding coefficient (Fe) of 0.29. Based on a pedigree analysis including the hypothesized founding group, 86% of the individuals for whom parents were known had inbreeding coefficients ranging 0.09–0.31. This high level of inbreeding was correlated with reduced pup survival. Seals at White Island therefore face the combined effects of low genetic variability, lack of immigration, and inbreeding depression. Ultimately, this study provides evidence of the effects of natural isolation on a large, long-lived vertebrate and can provide clues to the potential effects of anthropogenic- caused isolation of similar taxa.

Psychological and Support Characteristics of Parents of Child Sexual Abuse Victims: Relationship with Child Functioning and Treatment

Child sexual abuse continues to be a prevalent and complex problem in today’s society as it poses serious and pervasive mental health risks to child victims and their non-offending parents. The main objectives of this study were (a) to elucidate the psychological symptoms and support needs of parents of child sexual abuse victims as they present to group treatment, (b) to examine changes in psychological symptoms and support needs and their relationship with child functioning over the course of a parallel group treatment, and (c) to examine the impact of these factors on completion of group treatment. Participants included 104 sexually abused youth and their non-offending parent presenting to Project SAFE Group Intervention, a 12-session cognitive-behavioral group treatment for sexually abused children and their non-offending parents. This project had a unique advantage of utilizing a variety of demographic, parent-, and child-report measures, allowing for a more comprehensive examination of change in symptomatology and needs over the course of treatment. Several significant findings were noted, including the identification of four clusters of youth at pre-treatment, which were maintained at post-treatment; elevations on the CTQ Sexual Abuse scale; parents of youth sexually abused by a non-family member had significantly higher PSI-Restriction of Role subscale scores; parental expectations of a negative impact on their child were worse for older children; several parent characteristics predicted client treatment retention (e.g., older parents, lower SCL-90-R GSI scores); and an early age of onset of abuse also increased treatment retention. Future directions, recommendations, and limitations were discussed.

Vanishing of Ext and Tor over complete intersections

Let (R,m) be a local complete intersection, that is, a local ring whose m-adic completion is the quotient of a complete regular local ring by a regular sequence. Let M and N be finitely generated R-modules. This dissertation concerns the vanishing of Tor(M, N) and Ext(M, N). In this context, M satisfies Serre's condition (S_{n}) if and only if M is an nth syzygy. The complexity of M is the least nonnegative integer r such that the nth Betti number of M is bounded by a polynomial of degree r-1 for all sufficiently large n. We use this notion of Serre's condition and complexity to study the vanishing of Tor_{i}(M, N). In particular, building on results of C. Huneke, D. Jorgensen and R. Wiegand [32], and H. Dao [21], we obtain new results showing that good depth properties on the R-modules M, N and MtensorN force the vanishing of Tor_{i}(M, N) for all i>0. We give examples showing that our results are sharp. We also show that if R is a one-dimensional domain and M and MtensorHom(M,R) are torsion-free, then M is free if and only if M has complexity at most one. If R is a hypersurface and Ext^{i}(M, N) has finite length for all i>>0, then the Herbrand difference [18] is defined as length(Ext^{2n}(M, N))-(Ext^{2n-1}(M, N)) for some (equivalently, every) sufficiently large integer n. In joint work with Hailong Dao, we generalize and study the Herbrand difference. Using the Grothendieck group of finitely generated R-modules, we also examined the number of consecutive vanishing of Ext^{i}(M, N) needed to ensure that Ext^{i}(M, N) = 0 for all i>>0. Our results recover and improve on most of the known bounds in the literature, especially when R has dimension two.