Bioenergetic and ecological consequences of diet variability in Atlantic croaker Micropogonias undulatus

Atlantic croaker Micropogonias undulatus is a commercially and ecologically important bottom-associated fish that occurs in marine and estuarine systems from Cape Cod, MA to Mexico. I documented the temporal and spatial variability in the diet of Atlantic croaker in Chesapeake Bay and found that in the summer fish, particularly bay anchovies Anchoa mitchilli, make up at least 20% of the diet of croaker by weight. The use of a pelagic food source seems unusual for a bottom-associated fish such as croaker, but appears to be a crepuscular feeding habit that has not been previously detected. Thus, I investigated the bioenergetic consequences of secondary piscivory to the distribution of croaker, to the condition of individuals within the population and to the ecosystem. Generalized additive models revealed that the biomass of anchovy explained some of the variability in croaker occurrence and abundance in Chesapeake Bay. However, physical factors, specifically temperature, salinity, and seasonal dynamics were stronger determinants of croaker distribution than potential prey availability. To better understand the bioenergetic consequences of diet variability at the individual level, I tested the hypothesis that croaker feeding on anchovies would be in better condition than those feeding on polychaetes using a variety of condition measures that operate on multiple time scales, including RNA:DNA, Fulton's condition factor (K), relative weight (Wr), energy density, hepatosomatic index (HSI), and gonadosomatic index (GSI). Of these condition measures, several morphometric measures were significantly positively correlated with each other and with the percentage (by weight) of anchovy in croaker diets, suggesting that the type of prey eaten is important in improving the overall condition of individual croaker. To estimate the bioenergetic consequences of diet variability on growth and consumption in croaker, I developed and validated a bioenergetic model for Atlantic croaker in the laboratory. The application of this model suggested that croaker could be an important competitor with weakfish and striped bass for food resources during the spring and summer when population abundances of these three fishes are high in Chesapeake Bay. Even though anchovies made up a relatively small portion of croaker diet and only at certain times of the year, croaker consumed more anchovy at the population level than striped bass in all simulated years and nearly as much anchovy as weakfish. This indicates that weak trophic interactions between species are important in understanding ecosystem processes and should be considered in ecosystem-based management.

Development and Application of Predictive Models for Survival, Growth, and Death of Enteric Pathogens in Leafy Greens Supply Chain

Leafy greens are essential part of a healthy diet. Because of their health benefits, production and consumption of leafy greens has increased considerably in the U.S. in the last few decades. However, leafy greens are also associated with a large number of foodborne disease outbreaks in the last few years. The overall goal of this dissertation was to use the current knowledge of predictive models and available data to understand the growth, survival, and death of enteric pathogens in leafy greens at pre- and post-harvest levels. Temperature plays a major role in the growth and death of bacteria in foods. A growth-death model was developed for Salmonella and Listeria monocytogenes in leafy greens for varying temperature conditions typically encountered during supply chain. The developed growth-death models were validated using experimental dynamic time-temperature profiles available in the literature. Furthermore, these growth-death models for Salmonella and Listeria monocytogenes and a similar model for E. coli O157:H7 were used to predict the growth of these pathogens in leafy greens during transportation without temperature control. Refrigeration of leafy greens meets the purposes of increasing their shelf-life and mitigating the bacterial growth, but at the same time, storage of foods at lower temperature increases the storage cost. Nonlinear programming was used to optimize the storage temperature of leafy greens during supply chain while minimizing the storage cost and maintaining the desired levels of sensory quality and microbial safety. Most of the outbreaks associated with consumption of leafy greens contaminated with E. coli O157:H7 have occurred during July-November in the U.S. A dynamic system model consisting of subsystems and inputs (soil, irrigation, cattle, wildlife, and rainfall) simulating a farm in a major leafy greens producing area in California was developed. The model was simulated incorporating the events of planting, irrigation, harvesting, ground preparation for the new crop, contamination of soil and plants, and survival of E. coli O157:H7. The predictions of this system model are in agreement with the seasonality of outbreaks. This dissertation utilized the growth, survival, and death models of enteric pathogens in leafy greens during production and supply chain.