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Throughout the salt marshes of the US Atlantic Coast, ribbed mussels (Geukensia demissa, Dillwyn, 1817) and smooth cordgrass (Spartina alterniflora Loisel) form an important mutualistic relationship. Spartina provides habitat and promotes settling of ribbed mussels, which, in turn, stabilize and fertilize the Spartina and sediment. This relationship, however, is at risk of interruption due to sea level rise, erosion, and coastal development. Among the most at-risk segments of the marsh, the front (waterward) edge of the marsh is also where ribbed mussels and their ecosystem services are concentrated. Despite their importance of ribbed mussels to the salt marsh ecosystem, very little is known about the spatial distribution. in order to address these questions, we had the following objectives: 1) to identify spatial factors influencing mussel distribution across the landscape, 2) to quantify the contribution of ribbed mussels to nitrogen removal in the presence of Spartina, and 3) to assess how the distribution of the population and its ecosystem services are likely to change by the year 2050. We conducted field work in the summers of 2015 and 2016 to survey ribbed mussel populations in 30 marshes around the Chesapeake Bay. Ribbed mussel population density and distribution was positively related to the number of Spartina stems, the exposure of the site, and to a minor degree, the amount of agriculture within 300 m. The amount of forested land cover within 60 m was negatively related to ribbed mussel density. With these factors, we built a model to estimate ribbed mussel populations in the first two meters (edge) of the marsh, and estimated the presence of 805 million mussels along the edges of Virginia's marshes. Sediment core incubations revealed that when ribbed mussels are integrated with Spartina, the ammonium and particulate removal is enhanced, relative to when mussels occur separately, but that the overall rates vary dramatically by the location of the marsh whence the cores were collected. Spatial application of a 0.62 m sea level rise scenario and local erosion rates altered the distribution of both marshes and ribbed mussels. Overall, ribbed mussel abundance declined by 3.6% between 2018 and 2050; however, most locations saw moderate to large declines, while a very few locations saw very large increases (> 100%). Declines in abundance were greatest in urban areas dominated by fringing marsh and extensive shoreline armoring, while gains were greatest in agricultural areas with extensive marshes. The projected redistribution of mussels by 2050 will have important implications for water quality improvement goals that will need to be addressed by local and state authorities. This dissertation has focused on the seascape ecology and management of ribbed mussels in the Chesapeake Bay. The work has demonstrated the importance of applying spatial techniques to study and understand organisms and ecosystems at the interface between land and water. Only through further study and proactive planning will we be able to plan for and address the coming impacts of anthropogenic climate change and sea level rise.

The incidence of tick-borne diseases is on the rise in the US and around the world, due in part to emerging pathogens. However, the environmental drivers affecting these pathogens remain unclear. Most research on the topic in the US has focused on Borrelia burgdorferi, which causes Lyme, but it is unknown if the same conditions that affect B. burgdorferi also affect other pathogens, which may be carried by other ticks or reservoirs. The answer will help determine generalizable principles in tick-borne pathogen ecology, if they exist, as well as better manage for tick-borne pathogen risk in areas at risk from new and often unfamiliar pathogens. One such pathogen in the eastern US is Ehrlichia chaffeensis, which is transmitted by the lone star tick (Amblyomma americanum) and is the causative agent of monocytic ehrlichiosis, a potentially fatal illness. Here, I examine spatial and temporal variation in E. chaffeensis prevalence in southeastern Virginia and how this is influenced by the environment. in Chapter 1, I used four years of data to ask how E. chaffeensis prevalence changed between years and how this was affected by seasonal weather patterns. Using mixed-effect models, I related E. chaffeensis occurrence to temperature, humidity, vapor-pressure deficit, and precipitation up to 21 months prior to sampling. Annual prevalence varied significantly from 0.9% - 3.7%, and was positively affected by temperatures during the previous winter (i.e. before the current cohort of nymphs hatched). I hypothesize this is because winter temperature affects reservoir host mortality or natality, which would in turn affect the availability of naïve reservoir hosts in the spring. Regardless of mechanism, my findings have implications for the future because winters in this region are predicted to grow warmer, which could increase E. chaffeensis prevalence. in Chapter 2, I used five years of field data to ask how landscape context affects spatial variation in the prevalence of E. chaffeensis and interannual occupancy dynamics of its vector, A. americanum. Under a Bayesian framework, I created a metric- and scale-optimized model to relate E. chaffeensis prevalence and A. americanum turnover to the availability, quality, and fragmentation of habitat. Prevalence was highest and turnover was lowest in areas of low forest cover and low edge density, dominated by deciduous trees. Thus, highest disease risk is predicted in areas of forested areas that are either isolated or abutted against impermeable boundaries, both characteristic of many parks. Many of my results highlight the complexity of tick-borne disease dynamics and the challenges inherent to the subject; some results ran counter to my predictions and E. chaffeensis prevalence remains rare, which makes it challenging to model. That said, my work also represents important progress in an often-neglected area of tick-borne disease ecology. to my knowledge, this is the first study to address temporal variation in E. chaffeensis prevalence, and is one of few studies to relate E. chaffeensis prevalence to landscape context at a scale relevant to the pathogen's hosts and to disease-risk management.

As sea levels rise, coastal salt marshes, and the organisms for which they provision, face existential threats. A first step in understanding how projected marsh loss and reconfiguration may impact obligate species is to define their contemporary distribution and temporal shifts in structure using dynamic occupancy models. While occupancy models have commonly been applied to multi-annual butterfly studies, few have investigated population dynamics within a single-season. Here, we used Bayesian dynamic use models to define within-flight-period trends in adult salt-marsh skipper (Panoquina panoquin) use and state change probability. In doing so, we developed and validated a fully-Bayesian test for closure, and documented the ecology, behavior and detectability of this previously unstudied marsh-specialist butterfly. We found evidence that transects in our study system were open to changes in state across the field season, and, consequently, that transect use probability varied considerably by month from 0.35 to 0.84. Latent salt-marsh skipper phenology and transect quality were better predictors of within-flight-period dynamics than marsh area or isolation. This research highlights how variable population dynamics can be within a period of time commonly assumed to be static.