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Project 1
Graduate Thesis
2024
Eelgrass (Zostera marina) is a critical component of coastal ecosystems, providing essential services such as habitat for marine species, nutrient cycling, and shoreline stabilization. Understanding the spatial and temporal distribution of eelgrass is vital for conservation and management efforts, particularly in the face of environmental changes. This study employs spatiotemporal modeling techniques to predict the distribution of eelgrass habitats in Casco Bay, Maine. Using MaxEnt, a species distribution modeling tool, I incorporate variables such as temperature, salinity, dissolved oxygen, total nitrogen, turbidity, and bathymetry to generate a presence-only predictive model of the region.
Spatial statistics, including Local Moran's I and Emerging Hotspot Analysis (EHSA), are utilized to identify and analyze patterns of eelgrass presence and distribution across different temporal periods. This research contributes to the understanding of eelgrass ecology and provides a framework for predicting presence under varying environmental conditions. The findings can inform conservation strategies and management practices aimed at preserving and restoring eelgrass habitats in coastal Maine, ensuring their resilience in the face of climate change and anthropogenic pressures.
Thesis: Link
Slide deck: (upon request)
This independent project is ongoing in collaboration with the Maine Department of Environmental Protection and Casco Bay Estuary Partnership.