Spatial and Temporal Dynamics of Larval Atlantic Menhaden on the East Coast of the United States

Atlantic Menhaden Brevoortia tyrannus is a commercially and ecologically important forage fish abundant on the Atlantic Coast of the United States. We conducted spatial and temporal analyses of larval Atlantic Menhaden using data collected from two large-scale ichthyoplankton programs during 1977-1987 and 1999-2013 to construct indices of larval abundance and survival over time, evaluate how environmental factors affect early life survival, and examine how larvae are distributed in space to gain knowledge on spawning and larval dispersal. Over time, we found larval abundance to increase, while early life survival declined. Coastal temperature, wind speed, and Atlantic Multidecadal Oscillation were found to potentially explain some of this decline in survival. Over both periods, we found evidence spawning predominantly occurs near shore, from New York to North Carolina, increasing in intensity southwards. While the general spatial patterns were consistent, we observed some localized variation and overall expansion of occupied area by larvae.

Defining the Resolution of a Network for Transportation Analyses: a New Method to Improve Transportation Planning Decisions

Travel demand models are important tools used in the analysis of transportation plans, projects, and policies. The modeling results are useful for transportation planners making transportation decisions and for policy makers developing transportation policies. Defining the level of detail (i.e., the number of roads) of the transport network in consistency with the travel demand model’s zone system is crucial to the accuracy of modeling results. However, travel demand modelers have not had tools to determine how much detail is needed in a transport network for a travel demand model. This dissertation seeks to fill this knowledge gap by (1) providing methodology to define an appropriate level of detail for a transport network in a given travel demand model; (2) implementing this methodology in a travel demand model in the Baltimore area; and (3) identifying how this methodology improves the modeling accuracy. All analyses identify the spatial resolution of the transport network has great impacts on the modeling results. For example, when compared to the observed traffic data, a very detailed network underestimates traffic congestion in the Baltimore area, while a network developed by this dissertation provides a more accurate modeling result of the traffic conditions. Through the evaluation of the impacts a new transportation project has on both networks, the differences in their analysis results point out the importance of having an appropriate level of network detail for making improved planning decisions. The results corroborate a suggested guideline concerning the development of a transport network in consistency with the travel demand model’s zone system. To conclude this dissertation, limitations are identified in data sources and methodology, based on which a plan of future studies is laid out.