Intraspecific variation in a predator affects community structure and cascading trophic interactions.

Intraspecific phenotypic variation in ecologically important traits is widespread and important for evolutionary processes, but its effects on community and ecosystem processes are poorly understood. We use life history differences among populations of alewives, Alosa pseudoharengus, to test the effects of intraspecific phenotypic variation in a predator on pelagic zooplankton community structure and the strength of cascading trophic interactions. We focus on the effects of differences in (1) the duration of residence in fresh water (either seasonal or year-round) and (2) differences in foraging morphology, both of which may strongly influence interactions between alewives and their prey. We measured zooplankton community structure, algal biomass, and spring total phosphorus in lakes that contained landlocked, anadromous, or no alewives. Both the duration of residence and the intraspecific variation in foraging morphology strongly influenced zooplankton community structure. Lakes with landlocked alewives had small-bodied zooplankton year-round, and lakes with no alewives had large-bodied zooplankton year-round. In contrast, zooplankton communities in lakes with anadromous alewives cycled between large-bodied zooplankton in the winter and spring and small-bodied zooplankton in the summer. In summer, differences in feeding morphology of alewives caused zooplankton biomass to be lower and body size to be smaller in lakes with anadromous alewives than in lakes with landlocked alewives. Furthermore, intraspecific variation altered the strength of the trophic cascade caused by alewives. Our results demonstrate that intraspecific phenotypic variation of predators can regulate community structure and ecosystem processes by modifying the form and strength of complex trophic interactions.

Spatial Relationships among Hydroacoustic, Hydrographic and Top Predator Patterns: Cetacean Distributions in the Mid-Atlantic Bight

Effective conservation and management of top predators requires a comprehensive understanding of their distributions and of the underlying biological and physical processes that affect these distributions. The Mid-Atlantic Bight shelf break system is a dynamic and productive region where at least 32 species of cetaceans have been recorded through various systematic and opportunistic marine mammal surveys from the 1970s through 2012. My dissertation characterizes the spatial distribution and habitat of cetaceans in the Mid-Atlantic Bight shelf break system by utilizing marine mammal line-transect survey data, synoptic multi-frequency active acoustic data, and fine-scale hydrographic data collected during the 2011 summer Atlantic Marine Assessment Program for Protected Species (AMAPPS) survey. Although studies describing cetacean habitat and distributions have been previously conducted in the Mid-Atlantic Bight, my research specifically focuses on the shelf break region to elucidate both the physical and biological processes that influence cetacean distribution patterns within this cetacean hotspot.

In Chapter One I review biologically important areas for cetaceans in the Atlantic waters of the United States. I describe the study area, the shelf break region of the Mid-Atlantic Bight, in terms of the general oceanography, productivity and biodiversity. According to recent habitat-based cetacean density models, the shelf break region is an area of high cetacean abundance and density, yet little research is directed at understanding the mechanisms that establish this region as a cetacean hotspot.

In Chapter Two I present the basic physical principles of sound in water and describe the methodology used to categorize opportunistically collected multi-frequency active acoustic data using frequency responses techniques. Frequency response classification methods are usually employed in conjunction with net-tow data, but the logistics of the 2011 AMAPPS survey did not allow for appropriate net-tow data to be collected. Biologically meaningful information can be extracted from acoustic scattering regions by comparing the frequency response curves of acoustic regions to theoretical curves of known scattering models. Using the five frequencies on the EK60 system (18, 38, 70, 120, and 200 kHz), three categories of scatterers were defined: fish-like (with swim bladder), nekton-like (e.g., euphausiids), and plankton-like (e.g., copepods). I also employed a multi-frequency acoustic categorization method using three frequencies (18, 38, and 120 kHz) that has been used in the Gulf of Maine and Georges Bank which is based the presence or absence of volume backscatter above a threshold. This method is more objective than the comparison of frequency response curves because it uses an established backscatter value for the threshold. By removing all data below the threshold, only strong scattering information is retained.

In Chapter Three I analyze the distribution of the categorized acoustic regions of interest during the daytime cross shelf transects. Over all transects, plankton-like acoustic regions of interest were detected most frequently, followed by fish-like acoustic regions and then nekton-like acoustic regions. Plankton-like detections were the only significantly different acoustic detections per kilometer, although nekton-like detections were only slightly not significant. Using the threshold categorization method by Jech and Michaels (2006) provides a more conservative and discrete detection of acoustic scatterers and allows me to retrieve backscatter values along transects in areas that have been categorized. This provides continuous data values that can be integrated at discrete spatial increments for wavelet analysis. Wavelet analysis indicates significant spatial scales of interest for fish-like and nekton-like acoustic backscatter range from one to four kilometers and vary among transects.

In Chapter Four I analyze the fine scale distribution of cetaceans in the shelf break system of the Mid-Atlantic Bight using corrected sightings per trackline region, classification trees, multidimensional scaling, and random forest analysis. I describe habitat for common dolphins, Risso’s dolphins and sperm whales. From the distribution of cetacean sightings, patterns of habitat start to emerge: within the shelf break region of the Mid-Atlantic Bight, common dolphins were sighted more prevalently over the shelf while sperm whales were more frequently found in the deep waters offshore and Risso’s dolphins were most prevalent at the shelf break. Multidimensional scaling presents clear environmental separation among common dolphins and Risso’s dolphins and sperm whales. The sperm whale random forest habitat model had the lowest misclassification error (0.30) and the Risso’s dolphin random forest habitat model had the greatest misclassification error (0.37). Shallow water depth (less than 148 meters) was the primary variable selected in the classification model for common dolphin habitat. Distance to surface density fronts and surface temperature fronts were the primary variables selected in the classification models to describe Risso’s dolphin habitat and sperm whale habitat respectively. When mapped back into geographic space, these three cetacean species occupy different fine-scale habitats within the dynamic Mid-Atlantic Bight shelf break system.

In Chapter Five I present a summary of the previous chapters and present potential analytical steps to address ecological questions pertaining the dynamic shelf break region. Taken together, the results of my dissertation demonstrate the use of opportunistically collected data in ecosystem studies; emphasize the need to incorporate middle trophic level data and oceanographic features into cetacean habitat models; and emphasize the importance of developing more mechanistic understanding of dynamic ecosystems.

Food preferences and weight change during low-fat and low-carbohydrate diets.

UNLABELLED: Understanding associations between food preferences and weight loss during various effective diets could inform efforts to personalize dietary recommendations and provide insight into weight loss mechanisms. We conducted a secondary analysis of data from a clinical trial in which participants were randomized to either a 'choice' arm, in which they were allowed to select between a low-fat diet (n = 44) or low-carbohydrate diet (n = 61), or to a 'no choice' arm, in which they were randomly assigned to a low-fat diet (n = 49) or low-carbohydrate diet (n = 53). All participants were provided 48 weeks of lifestyle counseling. Food preferences were measured at baseline and every 12 weeks thereafter with the Geiselman Food Preference Questionnaire. Participants were 73% male and 51% African American, with a mean age of 55. Baseline food preferences, including congruency of food preferences with diet, were not associated with weight outcomes. In the low-fat diet group, no associations were found between changes in food preferences and weight over time. In the low-carbohydrate diet group, increased preference for low-carbohydrate diet congruent foods from baseline to 12 weeks was associated with weight loss from 12 to 24 weeks. Additionally, weight loss from baseline to 12 weeks was associated with increased preference for low-carbohydrate diet congruent foods from 12 to 24 weeks. Results suggest that basing selection of low-carbohydrate diet or low-fat diet on food preferences is unlikely to influence weight loss. Congruency of food preferences and weight loss may influence each other early during a low-carbohydrate diet but not low-fat diet, possibly due to different features of these diets. CLINICAL TRIAL REGISTRY: NCT01152359.

US-Based Food and Agricultural Value Chains and Their Relevance to Healthy Diets.

This article examines the structure and health implications of two industries, chicken and tomatoes, that play prominent roles in US food and agricultural competitiveness. Both industries have become more concentrated over time, with powerful "lead firms" driving geographical, technological, and marketing changes. Overall, a processed food revolution has taken place in agricultural products that transforms the types of food and dietary options available to consumers. The nature of contemporary food and agricultural value chains affects the strategies and policies that can be effectively employed to address major health goals such as improved nutrition, food safety, and food security.