Item talk:Q271299
From geokb
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"abstract": "Assessing wetland vulnerability to chronic and episodic physical drivers is fundamental\nfor establishing restoration priorities. We synthesized multiple data sets from E.B\nForsythe National Wildlife Refuge, New Jersey, to establish a wetland vulnerability\nmetric that integrates a range of physical processes, regulatory information and\nphysical/biophysical features. The geospatial data are based on aerial imagery, remote\nsensing, regulatory information, and hydrodynamic modeling, and include elevation,\ntidal range, unvegetated to vegetated marsh ratio (UVVR), shoreline erosion, potential\nexposure to contaminants, residence time, marsh condition change, change in salinity\nand salinity exposure, and sediment concentration. First, we delineated the wetland\ncomplex into individual marsh units based on surface contours and then defined a\nwetland vulnerability index that combined contributions from all parameters. We\napplied principal component and cluster analyses to explore the interrelations between\nthe data layers and separate regions that exhibited common characteristics. Our\nanalysis shows that the spatial variation of vulnerability in this domain cannot be\nexplained satisfactorily by a smaller subset of the variables. The most influential factor\non the vulnerability index was the combined effect of elevation, tide range, residence\ntime, and UVVR. Tide range and residence time had the highest correlation, and\nsimilar bay-wide spatial variation. Some variables (e.g., shoreline erosion) had no\nsignificant correlation with the rest of the variables. The aggregated index based on the\ncomplete dataset allows us to assess the overall state of a given marsh unit and quickly\nlocate the most vulnerable units in a larger marsh complex. The application of\ngeospatially complete datasets and consideration of chronic and episodic physical drivers\nrepresents an advance over traditional point-based methods for wetland assessment.",
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