Modeled Tradeoffs between Developed Land Protection and Tidal Habitat Maintenance during Rising Sea Levels.

Tidal habitats host a diversity of species and provide hydrological services such as shoreline protection and nutrient attenuation. Accretion of sediment and biomass enables tidal marshes and swamps to grow vertically, providing a degree of resilience to rising sea levels. Even if accelerating sea level rise overcomes this vertical resilience, tidal habitats have the potential to migrate inland as they continue to occupy land that falls within the new tide range elevations. The existence of developed land inland of tidal habitats, however, may prevent this migration as efforts are often made to dyke and protect developments. To test the importance of inland migration to maintaining tidal habitat abundance under a range of potential rates of sea level rise, we developed a spatially explicit elevation tracking and habitat switching model, dubbed the Marsh Accretion and Inundation Model (MAIM), which incorporates elevation-dependent net land surface elevation gain functions. We applied the model to the metropolitan Washington, DC region, finding that the abundance of small National Park Service units and other public open space along the tidal Potomac River system provides a refuge to which tidal habitats may retreat to maintain total habitat area even under moderate sea level rise scenarios (0.7 m and 1.1 m rise by 2100). Under a severe sea level rise scenario associated with ice sheet collapse (1.7 m by 2100) habitat area is maintained only if no development is protected from rising water. If all existing development is protected, then 5%, 10%, and 40% of the total tidal habitat area is lost by 2100 for the three sea level rise scenarios tested.

Multilevel space-time aggregation for bright field cell microscopy segmentation and tracking.

A multilevel aggregation method is applied to the problem of segmenting live cell bright field microscope images. The method employed is a variant of the so-called "Segmentation by Weighted Aggregation" technique, which itself is based on Algebraic Multigrid methods. The variant of the method used is described in detail, and it is explained how it is tailored to the application at hand. In particular, a new scale-invariant "saliency measure" is proposed for deciding when aggregates of pixels constitute salient segments that should not be grouped further. It is shown how segmentation based on multilevel intensity similarity alone does not lead to satisfactory results for bright field cells. However, the addition of multilevel intensity variance (as a measure of texture) to the feature vector of each aggregate leads to correct cell segmentation. Preliminary results are presented for applying the multilevel aggregation algorithm in space time to temporal sequences of microscope images, with the goal of obtaining space-time segments ("object tunnels") that track individual cells. The advantages and drawbacks of the space-time aggregation approach for segmentation and tracking of live cells in sequences of bright field microscope images are presented, along with a discussion on how this approach may be used in the future work as a building block in a complete and robust segmentation and tracking system.