Table of Contents

• Coverage
• Dataset Description
  • Methods & Sampling
  • Data Processing Description
• Parameters
• Project Information
• Funding

Dataset Includes a shapefile. Data uses EPSG 4326 projected to WGS 1984 Web Mercator (auxiliary sphere). Attribute table includes seven columns:

FID, Id, and gridcode are identical and identify objects in the dataframe

Shape: Data type
Shape_Leng: Aggregated perimeter length of all polygons that share given Class_name in meters
Shape_Area: Aggregated area of all polygons that share given Class_name in square meters
Class_name: name of the habitat class. Habitat classes defined as follows:

•  Water: Open water areas
• Mangrove: Land covered in mangrove vegetation
• Saltmarsh: Land covered in Saltmarsh vegetation
• Manmade: Artificial structures like houses, port facilities, and dredge berms
• Mud Flat: Regions of water that appear to be particularly shallow based on satellite imagery. This class was merged with water in the final analysis.

Satellite images taken in 2022 of the entire port were selected from google earth, georeferenced and clipped to the study area. The satellite image had a resolution of 2.8 x 3.3 meters per pixel.

We estimated habitat cover by classifying satellite imagery in ArcGIS Pro (3.3.0). We used ArcGIS Pro’s  Image Classification Tool to segment the satellite image into habitat types based on supervised training data.

Training data was provided by drawing polygons around regions dominated by Spartina marsh and mangrove trees. We trained the model to classify regions water and artificial structures in the same manner. We used a support vector machine algorithm to classify the satellite image and made manual corrections where necessary.

NSF Award Abstract:
Coastal marshes provide a suite of vital functions that support natural and human communities. Humans frequently take for granted and exploit these ecosystem services without fully understanding the ecological feedbacks, linkages, and interdependencies of these processes to the wider ecosystem. As demands on coastal ecosystem services have risen, marshes have experienced substantial loss due to direct and indirect impacts from human activity. The rapidly changing coastal ecosystems of Louisiana provide a natural experiment for understanding how coastal change alters ecosystem function. This project is developing new metrics and tools to assess food web variability and test hypotheses on biodiversity and ecosystem function in coastal Louisiana. The research is determining how changing habitat configuration alters the distribution of energy across the seascape in a multitrophic system. This work is engaging students from the University of Louisiana Lafayette and Dillard University in placed-based learning by immersing them in the research and local restoration efforts to address land loss and preserve critical ecosystem services. Students are developing a deeper understanding of the complex issues facing coastal regions through formal course work, directed field work, and outreach. Students are interacting with stakeholders and managers who are currently battling coastal change. Their directed research projects are documenting changes in coastal habitat and coupling this knowledge with the consequences to ecosystems and the people who depend on them. By participating in the project students are emerging with knowledge and training that is making them into informed citizens and capable stewards of the future of our coastal ecosystems, while also preparing them for careers in STEM. The project is supporting two graduate students and a post-doc.

The transformation and movement of energy through a food web are key links between biodiversity and ecosystem function. A major hurdle to testing biodiversity ecosystem function theory is a limited ability to assess food web variability in space and time. This research is quantifying changing seascape structure, species diversity, and food web structure to better understand the relationship between biodiversity and energy flow through ecosystems. The project uses cutting edge tools and metrics to test hypotheses on how the distribution, abundance, and diversity of key species are altered by ecosystem change and how this affects function. The hypotheses driving the research are: 1) habitat is a more important indirect driver of trophic structure than a direct change to primary trophic pathways; and 2) horizontal and vertical diversity increases with habitat resource index. Stable isotope analysis is characterizing energy flow through the food web. Changes in horizontal and vertical diversity in a multitrophic system are being quantified using aerial surveys and field sampling. To assess the spatial and temporal change in food web resources, the project is combining results from stable isotope analysis and drone-based remote sensing technology to generate consumer specific energetic seascape maps (E-scapes) and trophic niche metrics. In combination these new metrics are providing insight into species’ responses to changing food web function across the seascape and through time.

This project is jointly funded by Biological Oceanography and the Established Program to Stimulate Competitive Research (EPSCoR).

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.