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  • 1
    Publication Date: 2022-10-27
    Description: © The Author(s), 2019. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Farris, A. S., Defne, Z., & Ganju, N. K. Identifying salt marsh shorelines from remotely sensed elevation data and imagery. Remote Sensing, 11(15), (2019): 1795, doi: 10.3390/rs11151795.
    Description: Salt marshes are valuable ecosystems that are vulnerable to lateral erosion, submergence, and internal disintegration due to sea level rise, storms, and sediment deficits. Because many salt marshes are losing area in response to these factors, it is important to monitor their lateral extent at high resolution over multiple timescales. In this study we describe two methods to calculate the location of the salt marsh shoreline. The marsh edge from elevation data (MEED) method uses remotely sensed elevation data to calculate an objective proxy for the shoreline of a salt marsh. This proxy is the abrupt change in elevation that usually characterizes the seaward edge of a salt marsh, designated the “marsh scarp.” It is detected as the maximum slope along a cross-shore transect between mean high water and mean tide level. The method was tested using lidar topobathymetric and photogrammetric elevation data from Massachusetts, USA. The other method to calculate the salt marsh shoreline is the marsh edge by image processing (MEIP) method which finds the unvegetated/vegetated line. This method applies image classification techniques to multispectral imagery and elevation datasets for edge detection. The method was tested using aerial imagery and coastal elevation data from the Plum Island Estuary in Massachusetts, USA. Both methods calculate a line that closely follows the edge of vegetation seen in imagery. The two methods were compared to each other using high resolution unmanned aircraft systems (UAS) data, and to a heads-up digitized shoreline. The root-mean-square deviation was 0.6 meters between the two methods, and less than 0.43 meters from the digitized shoreline. The MEIP method was also applied to a lower resolution dataset to investigate the effect of horizontal resolution on the results. Both methods provide an accurate, efficient, and objective way to track salt marsh shorelines with spatially intensive data over large spatial scales, which is necessary to evaluate geomorphic change and wetland vulnerability.
    Description: This project was supported by the U.S. Geological Survey (USGS) Coastal/Marine Natural Hazards and Resources Program as well as the Massachusetts O ce of Coastal Zone Management under interagency agreement 16ENMALQ006000.
    Keywords: Marsh edge ; Marsh shoreline ; Unmanned aircraft system ; UAS ; UAV ; Drone ; Lidar ; Salt marsh ; Coastal wetlands ; Plum Island
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 2
    Publication Date: 2022-10-27
    Description: © The Author(s), 2019. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Goodwin, J. D., Munroe, D. M., Defne, Z., Ganju, N. K., & Vasslides, J. Estimating connectivity of hard clam (Mercenaria mercenaria) and eastern oyster (Crassostrea virginica) larvae in Barnegat Bay. Journal of Marine Science and Engineering, 7(6), (2019): 167, doi:10.3390/jmse7060167.
    Description: Many marine organisms have a well-known adult sessile stage. Unfortunately, our lack of knowledge regarding their larval transient stage hinders our understanding of their basic ecology and connectivity. Larvae can have swimming behavior that influences their transport within the marine environment. Understanding the larval stage provides insight into population connectivity that can help strategically identify areas for restoration. Current techniques for understanding the larval stage include modeling that combines particle attributes (e.g., larval behavior) with physical processes of water movement to contribute to our understanding of connectivity trends. This study builds on those methods by using a previously developed retention clock matrix (RCM) to illustrate time dependent connectivity of two species of shellfish between areas and over a range of larval durations. The RCM was previously used on physical parameters but we expand the concept by applying it to biology. A new metric, difference RCM (DRCM), is introduced to quantify changes in connectivity under different scenarios. Broad spatial trends were similar for all behavior types with a general south to north progression of particles. The DRCMs illustrate differences between neutral particles and those with behavior in northern regions where stratification was higher, indicating that larval behavior influenced transport. Based on these findings, particle behavior led to small differences (north to south movement) in transport patterns in areas with higher salinity gradients (the northern part of the system) compared to neutral particles. Overall, the dominant direction for particle movement was from south to north, which at times was enhanced by winds from the south. Clam and oyster restoration in the southern portion of Barnegat Bay could serve as a larval supply for populations in the north. These model results show that coupled hydrodynamic and particle tracking models have implications for fisheries management and restoration activities.
    Description: This work is supported by the Barnegat Bay Partnership EPA grants CE98212311, CE98212312. We extend our deep thanks to anonymous reviewers and Lisa Lucas who provided thoughtful input that improved the manuscript. We thank Matthew Kozak and Ian Mitchell for technical advice and Elizabeth North for LTRANS guidance. Joe Caracapa and Jennifer Gius provided help running remote simulations. COAST model source code is available at https://code.usgs.gov/coawstmodel/COAWST [50]. The hydrodynamic model outoput is available at: http://geoport.whoi.edu/thredds/catalog/clay/usgs/users/zdefne/GRL/catalog.html [21] and particle tracking model outputs are available from the corresponding author upon request.
    Keywords: Bivalve connectivity ; Larval transport ; Modeling ; Retention clock ; RCM ; ROMS ; LTRANS ; Barnegat Bay ; Hard clam ; Eastern oyster
    Repository Name: Woods Hole Open Access Server
    Type: Article
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