The Abundance and Behavioral Ecology of Cape Cod Gray Seals Under Predation Risk From White Sharks

The ultimate goal of wildlife recovery is abundance growth of a species, though it must also involve the reestablishment of the species’ ecological role within ecosystems frequently modified by humans. Reestablishment and subsequent recovery may depend on the species’ degree of adaptive behavior as well as the duration of their functional absence and the extent of ecosystem alteration. In cases of long extirpations or extensive alteration, successful reestablishment may entail adjusting foraging behavior, targeting new prey species, and encountering unfamiliar predatory or competitive regimes. Recovering species must also increasingly tolerate heightened anthropogenic presence, particularly within densely inhabited coastal zones. In recent decades, gray seals (Halichoerus grypus) recovered from exploitation, depletion, and partial extirpation in the Northwest Atlantic. On Cape Cod, MA, USA, gray seals have reestablished growing breeding colonies and seasonally interact with migratory white sharks (Carcarodon carcharias). Though well-studied in portions of their range due to concerns over piscivorous impacts on valuable groundfish, there are broad knowledge gaps regarding their ecological role to US marine ecosystems. Furthermore, there are few studies that explicitly analyze gray seal behavior under direct risk of documented shark predation.

In this dissertation, I apply a behavioral and movement ecology approach to telemetry data to understand gray seal abundance and activity patterns along the coast of Cape Cod. This coastal focus complements extensive research documenting and describing offshore movement and foraging behavior and allows me to address questions about movement decisions and risk allocation. Using beach counts of seals visible in satellite imagery, I estimate the total regional abundance of gray seals using correction factors from haul out behavior and demonstrate a sizeable prey base of gray seals locally. Analyzing intra-annual space use patterns, I document small, concentrated home ranges utilizing nearshore habitats that rapidly expand with shifting activity budgets to target disperse offshore habitats following seasonal declines in white sharks. During the season of dense shark presence, seals conducted abbreviated nocturnal foraging trips structured temporally around divergent use of crepuscular periods. The timing of coastal behavior with different levels of twilight indicate risk allocation patterns with diel cycles of empirical white shark activity. The emergence of risk allocation to explain unique behavioral and spatial patterns observed in these gray seals points to the importance of the restored predator-prey dynamic in gray seal behavior along Cape Cod.

Experimental evidence that phenotypic divergence in predators drives community divergence in prey.

Studies of adaptive divergence have traditionally focused on the ecological causes of trait diversification, while the ecological consequences of phenotypic divergence remain relatively unexplored. Divergence in predator foraging traits, in particular, has the potential to impact the structure and dynamics of ecological communities. To examine the effects of predator trait divergence on prey communities, we exposed zooplankton communities in lake mesocosms to predation from either anadromous or landlocked (freshwater resident) alewives, which have undergone recent and rapid phenotypic differentiation in foraging traits (gape width, gill raker spacing, and prey size-selectivity). Anadromous alewives, which exploit large prey items, significantly reduced the mean body size, total biomass, species richness, and diversity of crustacean zooplankton relative to landlocked alewives, which exploit smaller prey. The zooplankton responses observed in this experiment are consistent with patterns observed in lakes. This study provides direct evidence that phenotypic divergence in predators, even in its early stages, can play a critical role in determining prey community structure.

Eco-evolutionary trophic dynamics: loss of top predators drives trophic evolution and ecology of prey.

Ecosystems are being altered on a global scale by the extirpation of top predators. The ecological effects of predator removal have been investigated widely; however, predator removal can also change natural selection acting on prey, resulting in contemporary evolution. Here we tested the role of predator removal on the contemporary evolution of trophic traits in prey. We utilized a historical introduction experiment where Trinidadian guppies (Poecilia reticulata) were relocated from a site with predatory fishes to a site lacking predators. To assess the trophic consequences of predator release, we linked individual morphology (cranial, jaw, and body) to foraging performance. Our results show that predator release caused an increase in guppy density and a "sharpening" of guppy trophic traits, which enhanced food consumption rates. Predator release appears to have shifted natural selection away from predator escape ability and towards resource acquisition ability. Related diet and mesocosm studies suggest that this shift enhances the impact of guppies on lower trophic levels in a fashion nuanced by the omnivorous feeding ecology of the species. We conclude that extirpation of top predators may commonly select for enhanced feeding performance in prey, with important cascading consequences for communities and ecosystems.

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.

Real-Time and Data-Driven Operation Optimization and Knowledge Discovery for an Enterprise Information System

An enterprise information system (EIS) is an integrated data-applications platform characterized by diverse, heterogeneous, and distributed data sources. For many enterprises, a number of business processes still depend heavily on static rule-based methods and extensive human expertise. Enterprises are faced with the need for optimizing operation scheduling, improving resource utilization, discovering useful knowledge, and making data-driven decisions.

This thesis research is focused on real-time optimization and knowledge discovery that addresses workflow optimization, resource allocation, as well as data-driven predictions of process-execution times, order fulfillment, and enterprise service-level performance. In contrast to prior work on data analytics techniques for enterprise performance optimization, the emphasis here is on realizing scalable and real-time enterprise intelligence based on a combination of heterogeneous system simulation, combinatorial optimization, machine-learning algorithms, and statistical methods.

On-demand digital-print service is a representative enterprise requiring a powerful EIS.We use real-life data from Reischling Press, Inc. (RPI), a digit-print-service provider (PSP), to evaluate our optimization algorithms.

In order to handle the increase in volume and diversity of demands, we first present a high-performance, scalable, and real-time production scheduling algorithm for production automation based on an incremental genetic algorithm (IGA). The objective of this algorithm is to optimize the order dispatching sequence and balance resource utilization. Compared to prior work, this solution is scalable for a high volume of orders and it provides fast scheduling solutions for orders that require complex fulfillment procedures. Experimental results highlight its potential benefit in reducing production inefficiencies and enhancing the productivity of an enterprise.

We next discuss analysis and prediction of different attributes involved in hierarchical components of an enterprise. We start from a study of the fundamental processes related to real-time prediction. Our process-execution time and process status prediction models integrate statistical methods with machine-learning algorithms. In addition to improved prediction accuracy compared to stand-alone machine-learning algorithms, it also performs a probabilistic estimation of the predicted status. An order generally consists of multiple series and parallel processes. We next introduce an order-fulfillment prediction model that combines advantages of multiple classification models by incorporating flexible decision-integration mechanisms. Experimental results show that adopting due dates recommended by the model can significantly reduce enterprise late-delivery ratio. Finally, we investigate service-level attributes that reflect the overall performance of an enterprise. We analyze and decompose time-series data into different components according to their hierarchical periodic nature, perform correlation analysis,

and develop univariate prediction models for each component as well as multivariate models for correlated components. Predictions for the original time series are aggregated from the predictions of its components. In addition to a significant increase in mid-term prediction accuracy, this distributed modeling strategy also improves short-term time-series prediction accuracy.

In summary, this thesis research has led to a set of characterization, optimization, and prediction tools for an EIS to derive insightful knowledge from data and use them as guidance for production management. It is expected to provide solutions for enterprises to increase reconfigurability, accomplish more automated procedures, and obtain data-driven recommendations or effective decisions.

Biological and Physical Factors Affecting the Natural History and Evolution of Encapsulated Development

The evolution of reproductive strategies involves a complex calculus of costs and benefits to both parents and offspring. Many marine animals produce embryos packaged in tough egg capsules or gelatinous egg masses attached to benthic surfaces. While these egg structures can protect against environmental stresses, the packaging is energetically costly for parents to produce. In this series of studies, I examined a variety of ecological factors affecting the evolution of benthic development as a life history strategy. I used marine gastropods as my model system because they are incredibly diverse and abundant worldwide, and they exhibit a variety of reproductive and developmental strategies.

The first study examines predation on benthic egg masses. I investigated: 1) behavioral mechanisms of predation when embryos are targeted (rather than the whole egg mass); 2) the specific role of gelatinous matrix in predation. I hypothesized that gelatinous matrix does not facilitate predation. One study system was the sea slug Olea hansineensis, an obligate egg mass predator, feeding on the sea slug Haminoea vesicula. Olea fed intensely and efficiently on individual Haminoea embryos inside egg masses but showed no response to live embryos removed from gel, suggesting that gelatinous matrix enables predation. This may be due to mechanical support of the feeding predator by the matrix. However, Haminoea egg masses outnumber Olea by two orders of magnitude in the field, and each egg mass can contain many tens of thousands of embryos, so predation pressure on individuals is likely not strong. The second system involved the snail Nassarius vibex, a non-obligate egg mass predator, feeding on the polychaete worm Clymenella mucosa. Gel neither inhibits nor promotes embryo predation for Nassarius, but because it cannot target individual embryos inside an egg mass, its feeding is slow and inefficient, and feeding rates in the field are quite low. However, snails that compete with Nassarius for scavenged food have not been seen to eat egg masses in the field, leaving Nassarius free to exploit the resource. Overall, egg mass predation in these two systems likely benefits the predators much more than it negatively affects the prey. Thus, selection for environmentally protective aspects of egg mass production may be much stronger than selection for defense against predation.

In the second study, I examined desiccation resistance in intertidal egg masses made by Haminoea vesicula, which preferentially attaches its flat, ribbon-shaped egg masses to submerged substrata. Egg masses occasionally detach and become stranded on exposed sand at low tide. Unlike adults, the encased embryos cannot avoid desiccation by selectively moving about the habitat, and the egg mass shape has high surface-area-to-volume ratio that should make it prone to drying out. Thus, I hypothesized that the embryos would not survive stranding. I tested this by deploying individual egg masses of two age classes on exposed sand bars for the duration of low tide. After rehydration, embryos midway through development showed higher rates of survival than newly-laid embryos, though for both stages survival rates over 25% were frequently observed. Laboratory desiccation trials showed that >75% survival is possible in an egg mass that has lost 65% of its water weight, and some survival (<25%) was observed even after 83% water weight lost. Although many surviving embryos in both experiments showed damage, these data demonstrate that egg mass stranding is not necessarily fatal to embryos. They may be able to survive a far greater range of conditions than they normally encounter, compensating for their lack of ability to move. Also, desiccation tolerance of embryos may reduce pressure on parents to find optimal laying substrata.

The third study takes a big-picture approach to investigating the evolution of different developmental strategies in cone snails, the largest genus of marine invertebrates. Cone snail species hatch out of their capsules as either swimming larvae or non-dispersing forms, and their developmental mode has direct consequences for biogeographic patterns. Variability in life history strategies among taxa may be influenced by biological, environmental, or phylogenetic factors, or a combination of these. While most prior research has examined these factors singularly, my aim was to investigate the effects of a host of intrinsic, extrinsic, and historical factors on two fundamental aspects of life history: egg size and egg number. I used phylogenetic generalized least-squares regression models to examine relationships between these two egg traits and a variety of hypothesized intrinsic and extrinsic variables. Adult shell morphology and spatial variability in productivity and salinity across a species geographic range had the strongest effects on egg diameter and number of eggs per capsule. Phylogeny had no significant influence. Developmental mode in Conus appears to be influenced mostly by species-level adaptations and niche specificity rather than phylogenetic conservatism. Patterns of egg size and egg number appear to reflect energetic tradeoffs with body size and specific morphologies as well as adaptations to variable environments. Overall, this series of studies highlights the importance of organism-scale biotic and abiotic interactions in evolutionary patterns.

Physics of Hexagonal Limit-Periodic Phases: Thermodynamics, Formation and Vibrational Modes

Limit-periodic (LP) structures exhibit a type of nonperiodic order yet to be found in a natural material. A recent result in tiling theory, however, has shown that LP order can spontaneously emerge in a two-dimensional (2D) lattice model with nearest-and next-nearest-neighbor interactions. In this dissertation, we explore the question of what types of interactions can lead to a LP state and address the issue of whether the formation of a LP structure in experiments is possible. We study emergence of LP order in three-dimensional (3D) tiling models and bring the subject into the physical realm by investigating systems with realistic Hamiltonians and low energy LP states. Finally, we present studies of the vibrational modes of a simple LP ball and spring model whose results indicate that LP materials would exhibit novel physical properties.

A 2D lattice model defined on a triangular lattice with nearest- and next-nearest-neighbor interactions based on the Taylor-Socolar (TS) monotile is known to have a LP ground state. The system reaches that state during a slow quench through an infinite sequence of phase transitions. Surprisingly, even when the strength of the next-nearest-neighbor interactions is zero, in which case there is a large degenerate class of both crystalline and LP ground states, a slow quench yields the LP state. The first study in this dissertation introduces 3D models closely related to the 2D models that exhibit LP phases. The particular 3D models were designed such that next-nearest-neighbor interactions of the TS type are implemented using only nearest-neighbor interactions. For one of the 3D models, we show that the phase transitions are first order, with equilibrium structures that can be more complex than in the 2D case.

In the second study, we investigate systems with physical Hamiltonians based on one of the 2D tiling models with the goal of stimulating attempts to create a LP structure in experiments. We explore physically realizable particle designs while being mindful of particular features that may make the assembly of a LP structure in an experimental system difficult. Through Monte Carlo (MC) simulations, we have found that one particle design in particular is a promising template for a physical particle; a 2D system of identical disks with embedded dipoles is observed to undergo the series of phase transitions which leads to the LP state.

LP structures are well ordered but nonperiodic, and hence have nontrivial vibrational modes. In the third section of this dissertation, we study a ball and spring model with a LP pattern of spring stiffnesses and identify a set of extended modes with arbitrarily low participation ratios, a situation that appears to be unique to LP systems. The balls that oscillate with large amplitude in these modes live on periodic nets with arbitrarily large lattice constants. By studying periodic approximants to the LP structure, we present numerical evidence for the existence of such modes, and we give a heuristic explanation of their structure.

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.