The blue crab (Callinectes sapidus) is a commercially and ecologically importantspecies found along the Atlantic coast of North and South America. These crustaceans play a critical role in coastal ecosystems, serving as both predators and prey in the food web. The blue crab supports a major fishery in Chesapeake Bay, where the species is a cultural icon. Juvenile blue crabs, the smallest and most vulnerable size classes of individuals, are reliant upon structurally complex habitats. Population dynamics of this species are therefore influenced by spatiotemporally fluctuating environmental variables, such as habitat availability. Understanding blue crab ecology is essential for managing their populations sustainably and maintaining the health of their habitats. The primary aim of this dissertation was to quantitatively evaluate the contributions of several widely distributed habitats to blue crab population dynamics in Chesapeake Bay. Empirical valuation of nursery habitat effects on blue crab population dynamics can (i) estimate the optimal extent of habitat required for the long-term sustainability of blue crab fisheries, (ii) quantify how changes in habitat extent will affect blue crab populations, such as alterations due to climate change, and (iii) inform ecosystem-based fisheries management (EBFM) decisions, as a complement to stock assessments. Here, I present four separate but interrelated studies examining habitat-specific demographic rates at multiple spatial and temporal scales. These studies involved a combination of survey data, mensurative and manipulative field experiments, and complex population dynamics models. Chapter 1 evaluates nursery habitat contributions to blue crab population dynamics by examining relationships between juvenile blue crab distributions and multiple environmental variables in three tributaries—the York, James, and Rappahannock rivers—at broad spatial (regional) and temporal (decadal) scales using fisheries-independent survey data and digitized GIS maps of habitat distributions. Chapter 2 examines fine-scale spatiotemporal (i.e., 10s of km2 over biweekly intervals) variation and ontogenetic shifts in juvenile blue crab densities in salt marsh edge, seagrass, shallow detrital habitat, and unstructured habitat under a suite of physical and biological parameters in the York River. Chapter 3 expands on these findings to examine the mechanistic basis for ontogenetic habitat shifts by evaluating differential abundance and survival of juvenile blue crabs across three size classes in salt marsh edge, seagrass, and unstructured sand habitat, with specific attention to effects of refuge, turbidity, and postlarval supply. Finally, Chapter 4 integrates population-scale indices of abundance from two major fisheries-independent surveys with time-series of habitat data to assess the influence of seagrass species on blue crab population dynamics at the scale of Chesapeake Bay.

<p>Heterocyst-forming Cyanobacterial species encompass the orders <em>Nostocales</em> and <em>Stigonematales</em>. These orders are currently differentiated based solely upon morphological characteristics (such as the formation of true or false branches), which may be unrelated to phylogeny. Thus, these bacteria do not form distinct monophyletic groups in the 16S rRNA tree, and as yet, no reliable molecular markers have yet been identified that allow species of these two orders to be distinguished from each other or from other organisms. Using published genome sequences for these species, we have investigated the relationship of species from these two orders. We describe here detailed phylogenetic analyses based on concatenated protein sequences for 45 proteins from 48 Cyanobacterial species/strains whose genomes are now available. In addition, we have performed comprehensive comparative genomic analyses on eight available <em>Nostocales</em> and <em>Stigonematales</em> genomes to identify conserved signature indels (CSIs) and conserved signature proteins (CSPs) that are specifically present in all <em>Nostocales/Stigonematales</em> or any of their subclades. These analyses have yielded >100 CSIs and CSPs that are specific for distinct coherent clades of <em>Nostocales/Stigonematales</em>. Seventeen of these CSIs and twelve CSPs are present in all sequenced <em>Nostocales</em> and <em>Stigonematales</em>, supporting a distinct relationship of the species from these two orders of heterocyst-forming bacteria. Fifty-four CSIs and forty-one CSPs are specific for different subclades of <em>Nostocales</em> and many others are diagnostic of individual species/strains. The newly-identified CSIs and CSPs, which are specific for different subclades of <em>Nostocales/Stigonematales,</em> may provide novel means for identifying previously unknown members of these orders, for assignment of unsequenced members of heterocystous Cyanobacteria into different identified subclades, and for detecting individual strains from environmental samples by employing CSIs/CSPs as diagnostic tools.</p> / Master of Science (MSc)

One of the main challenges still confronting biologists is unravelling the mechanismsunderlying the evolution of evolvability — the ability to produce heritable and adaptive phenotypic variation. The impact of ecological factors on evolvability remains largely unstudied. Ecological interactions among populations are a relevant ecological factor shaping biodiversity through coevolution, i.e. the reciprocal adaptation resulting from these interactions. This study adopts a community-wide approach to investigate how the complexity of interaction networks and degree (the number of interacting partners of each species) affect evolvability. Quantifying these metrics represents a monumental practical challenge, which is overcome by harnessing a digital life platform that simulates the coevolutionary process of hosts and their parasites. I found that more evolvable communities are those embedded in a more complex network of interactions. However, within each community, a wide range of evolvability values coexist; an observation not related to specific differences in degree. These results emphasise the role of ecological networks of interaction in shaping evolvability.

In recent decades we have learned that cooperation is an important and pervasive feature of microbial life. This revelation raises exciting possibilities. On the one hand, we can now augment our understanding of how social phenomena evolve by using microbial model systems to test our theories. On the other hand, we can use concepts from social evolution to gain insight into the biology of the microbes we hope to control or kill. In this thesis I explore both possibilities. First, I consider the theoretical problem of how and when microbial cooperation might be subject to frequency- and densitydependence. Formerly, vague theory and a scant, sometimes contradictory empirical literature made it unclear when such patterns could be expected. Here, I develop theory tailored to a microbial context, and in each case, I test key predictions from the theory in laboratory experiments, using as my model trait the production of siderophores by the bacterium Pseudomonas aeruginosa. Secondly, I consider the ecological consequences of cooperator-cheat dynamics in the context of an infection. Specifically, I use experimental infections of diverse host models to investigate the role of two cooperative traits, siderophore production and quorum sensing, in the pathogenesis of P. aeruginosa. When a successful infection requires cooperation among pathogens, theory predicts that conflict among coinfecting strains can undermine cooperation and hence decrease virulence; whereas, in the absence of cooperation, conflict could lead to heightened exploitation and hence increased virulence. This exciting idea has received little empirical attention to date but here I address this using multiple pathogen strains, multiple social traits, and multiple model hosts.

Currently three systems are used to categorize honey production regions in the United States, one from the United States Department of Agriculture, one from the American Bee Journal used for its monthly U.S. Honey Crop and Markets report, and one from Bee Culture’s monthly regional honey price report. These systems follow political state boundaries and are based upon climate, bee forage, and regional beekeeping practices. While these systems are popular with the general beekeeping community, to our knowledge, their accuracy has not been studied. Although differing geographic regions can vary in bee forage species availability, states with similar geography and flora should have similar honey production. This is not the case because states within the same honey production region vary in honey production, possibly due to smaller ecotype divisions within the larger honey production regions. Due to this ecotype gradient, some models divide the United States into far more regions based upon ecotypes and disregard political boundaries. While a model based on ecotypes that disregard state political boundaries may be more accurate, it is not currently possible to statistically evaluate them due to how honey production data are collected. This study developed nine novel regional honey production models that regard political boundaries while attempting to satisfy ecotype similarity. The first four alternative models are based solely on Level II ecoregions and were developed by a best fit manual approach that minimized the number of ecoregions per honey production region. The five remaining models were created using statistical k-means partitioning cluster analysis and are purely data based. Also discussed is a linear regression model produced by Page et al. Differences within and between the models were analyzed using descriptive statistics and ANOVA in order to determine an improved model that describes regional honey production in the United States. Many of the models, both preexisting and those developed for this study, had insignificant means and are not viable. Of those that had significant means, a k-means cluster based model was determined to be the statistically superior model and can be considered an improved regional honey production model for the United States.

Microbes rely on collective behaviours, such as communication and cooperation to survive and form communities. The majority of these social behaviours are mediated by the secretion of public good molecules into a shared environment such that they can be utilized by neighbouring cells. Therefore, individuals that engage in costly cooperative behaviour are susceptible to exploitation by selfish cheats that gain the benefit of cooperation without investing their share of the public good cost. Understanding such bacterial social interactions and the underlying molecular mechanisms gives insight into their complex social life in natural environments and can be used to develop alternative treatments for pathogenic bacteria that rely on such social interactions for virulence and to infect hosts. In this thesis I examine social behaviours expressed by the opportunistic pathogen, Pseudomonas aeruginosa. I develop an understanding of bacterial social dynamics, particularly competitive dynamics between cooperator and cheat strains and strains that engage in bacteriocin-mediated chemical warfare. I investigate bacterial cheat-cooperator systems in several ways: 1) I begin with a review describing the evolution of and response to cheating across a range of organisms and discuss the confusion that arises in identifying cheats particularly in microbial studies and therefore propose a key to identify cheating behaviour. 2) I empirically test whether cheating behaviour is context dependent in bacterial populations and reveal that the ability to cheat varies with the abiotic and social environment, which are two fluctuating conditions in natural environments. 3) I take an experimental approach to investigate why cheat invasion is not commonly observed in natural bacterial populations by testing the effect of cooperative bacterial growth dynamics on cheating ability. I find that secretion of public goods varies with bacterial growth dynamics and physiological growth stages which may explain why cheat invasion is more commonly observed in lab cultures and not in established natural populations. 4) In the final chapter I experimentally use natural isolates to examine the role of bacteriocins in mediating competition in pathogenic populations and find that contrary to empirical and theoretical work, bacteriocins do not play a significant role in strain competitive success and dominance. The thesis has laid groundwork for studying and understanding the role of social behaviours in bacterial systems and for further exploring social dynamics in natural bacterial populations.

<p>The concept of biological fitness is foundational for our understanding of both ecology and evolution. Fitness is often described vaguely as an organism’s contribution to the next generation. The reason this is vague is because researchers define and measure fitness differently across fields. I suggest that the myriad definitions and ways to measure fitness commonly employed have led to debates and, seemingly contradictory results. In order to investigate the use of the concept of fitness, I performed a literature review and asked, (1) How is biological fitness defined and used by researchers? (2) How is fitness actually measured by researchers? To address these questions, I surveyed 478 papers published between 2012 and 2016, that included the word ‘fitness’ in the title, and were in the Web of Science categories of ‘ecology’ and ‘evolutionary biology’. In my analysis of the journal articles fitness was only defined 33% of the time. Among studies that did explicitly define fitness, I categorized 18 different definitions, though only 7 were found in more than 5% of papers. I also found differences in how fitness was measured. I found 87 measurements that I grouped into 13 categories. In addition to my survey of the literature, I performed an experiment to explore the relationship between different measures of fitness. Vegetative biomass and reproductive biomass are often both used as metrics of fitness by plant ecologists. In this experiment I determined the relationship between two popular measures of plant fitness vegetative biomass and reproductive yield. I found that these two proxies for plant fitness, vegetative biomass and reproduction, were unimodally related, meaning: 1) intermediate sized plants have the greatest reproductive output, and; 2) for any unique amount of reproduction there is both a small and a large plant with identical reproductive output. Two things emerge from the literature review and the experiment: first, given the many definitions that exist, researchers should be clear about which one they are using. Second, one must be clear about the expected relationship between proxy measurements and fitness, as it may be complex, or non-existent.</p><p></p>

In a heterogeneous environment where temperature influences fitness, individuals must navigate to a thermal optimum to maximize reproductive output and minimize physiological stress. However, the optimal temperature varies among individuals due to genetic and environmental contributions. The neural and genetic basis to such natural variation in behavior has remained elusive in most cases, as the high-throughput genomic, neurodevelopmental, and behavioral techniques were not developed. Using the nematode / 10000-01-01

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This study concurrently quantified blue crab feeding habits and preference, and examined the inter-relationships between diet, predator preference, and predator and prey abundance and distribution in three subestuaries of lower Chesapeake Bay--the James, York and Rappahannock Rivers, Virginia. Complementary laboratory investigations estimated the combined effect of the functional, aggregative and interference responses upon prey and predator survival and predator foraging rates for blue crabs and a common bivalve prey, Macoma balthica, in this system. Crab abundance, prey abundance and diet were correlated such that blue crabs aggregated in areas of highest preferred (i.e., bivalve) prey abundance, as determined through electivity analyses. Spatial and size-related differences in diet selection occurred. at least two trophic groups were distinguished, based on their relative consumption of bivalves and crabs, including conspecifics (i.e., older juveniles and adults) or polychaetes and small crustaceans (i.e., younger juveniles and new recruits). Spatial differences were reflected by proportional bivalve consumption: crabs always preferred bivalves, but in areas of relatively lower bivalve abundance, opportunistically expanded their diets to include other prey taxa. Cannibalism was common, but the frequency of occurrence varied with crab size, season, river, new juvenile recruit abundance, and the density of alternative preferred prey. Laboratory experiments assessed the joint effects of varying predator and prey densities upon predator foraging rates and prey survival. A full-factorial experimental design involved 2 prey and 3 predator densities with 6 trials per treatment combination. Blue crabs exhibited density-dependent foraging under all conditions: proportionally more clams were consumed at higher clam density. Furthermore, at the higher crab densities, mutual interference was evident in the incidence of wounds and deaths to crabs resulting from cannibalism or intraspecific aggression. The collective results indicate that both predator and prey densities must be examined experimentally for their joint impact upon predator-prey dynamics in marine systems.