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A geospatially resolved wetland vulnerability index: Synthesis of physical drivers
Assessing wetland vulnerability to chronic and episodic physical drivers is fundamental for establishing restoration priorities. We synthesized multiple data sets from E.B. Forsythe National Wildlife Refuge, New Jersey, to establish a wetland vulnerability metric that integrates a range of physical...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6992177/ https://www.ncbi.nlm.nih.gov/pubmed/31999806 http://dx.doi.org/10.1371/journal.pone.0228504 |
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author | Defne, Zafer Aretxabaleta, Alfredo L. Ganju, Neil K. Kalra, Tarandeep S. Jones, Daniel K. Smith, Kathryn E. L. |
author_facet | Defne, Zafer Aretxabaleta, Alfredo L. Ganju, Neil K. Kalra, Tarandeep S. Jones, Daniel K. Smith, Kathryn E. L. |
author_sort | Defne, Zafer |
collection | PubMed |
description | Assessing wetland vulnerability to chronic and episodic physical drivers is fundamental for establishing restoration priorities. We synthesized multiple data sets from E.B. Forsythe National Wildlife Refuge, New Jersey, to establish a wetland vulnerability metric that integrates a range of physical processes, anthropogenic impact and physical/biophysical features. The geospatial data are based on aerial imagery, remote sensing, regulatory information, and hydrodynamic modeling; and include elevation, tidal range, unvegetated to vegetated marsh ratio (UVVR), shoreline erosion, potential exposure to contaminants, residence time, marsh condition change, change in salinity, salinity exposure and sediment concentration. First, we delineated the wetland complex into individual marsh units based on surface contours, and then defined a wetland vulnerability index that combined contributions from all parameters. We applied principal component and cluster analyses to explore the interrelations between the data layers, and separate regions that exhibited common characteristics. Our analysis shows that the spatial variation of vulnerability in this domain cannot be explained satisfactorily by a smaller subset of the variables. The most influential factor on the vulnerability index was the combined effect of elevation, tide range, residence time, and UVVR. Tide range and residence time had the highest correlation, and similar bay-wide spatial variation. Some variables (e.g., shoreline erosion) had no significant correlation with the rest of the variables. The aggregated index based on the complete dataset allows us to assess the overall state of a given marsh unit and quickly locate the most vulnerable units in a larger marsh complex. The application of geospatially complete datasets and consideration of chronic and episodic physical drivers represents an advance over traditional point-based methods for wetland assessment. |
format | Online Article Text |
id | pubmed-6992177 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-69921772020-02-20 A geospatially resolved wetland vulnerability index: Synthesis of physical drivers Defne, Zafer Aretxabaleta, Alfredo L. Ganju, Neil K. Kalra, Tarandeep S. Jones, Daniel K. Smith, Kathryn E. L. PLoS One Research Article Assessing wetland vulnerability to chronic and episodic physical drivers is fundamental for establishing restoration priorities. We synthesized multiple data sets from E.B. Forsythe National Wildlife Refuge, New Jersey, to establish a wetland vulnerability metric that integrates a range of physical processes, anthropogenic impact and physical/biophysical features. The geospatial data are based on aerial imagery, remote sensing, regulatory information, and hydrodynamic modeling; and include elevation, tidal range, unvegetated to vegetated marsh ratio (UVVR), shoreline erosion, potential exposure to contaminants, residence time, marsh condition change, change in salinity, salinity exposure and sediment concentration. First, we delineated the wetland complex into individual marsh units based on surface contours, and then defined a wetland vulnerability index that combined contributions from all parameters. We applied principal component and cluster analyses to explore the interrelations between the data layers, and separate regions that exhibited common characteristics. Our analysis shows that the spatial variation of vulnerability in this domain cannot be explained satisfactorily by a smaller subset of the variables. The most influential factor on the vulnerability index was the combined effect of elevation, tide range, residence time, and UVVR. Tide range and residence time had the highest correlation, and similar bay-wide spatial variation. Some variables (e.g., shoreline erosion) had no significant correlation with the rest of the variables. The aggregated index based on the complete dataset allows us to assess the overall state of a given marsh unit and quickly locate the most vulnerable units in a larger marsh complex. The application of geospatially complete datasets and consideration of chronic and episodic physical drivers represents an advance over traditional point-based methods for wetland assessment. Public Library of Science 2020-01-30 /pmc/articles/PMC6992177/ /pubmed/31999806 http://dx.doi.org/10.1371/journal.pone.0228504 Text en https://creativecommons.org/publicdomain/zero/1.0/ This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 (https://creativecommons.org/publicdomain/zero/1.0/) public domain dedication. |
spellingShingle | Research Article Defne, Zafer Aretxabaleta, Alfredo L. Ganju, Neil K. Kalra, Tarandeep S. Jones, Daniel K. Smith, Kathryn E. L. A geospatially resolved wetland vulnerability index: Synthesis of physical drivers |
title | A geospatially resolved wetland vulnerability index: Synthesis of physical drivers |
title_full | A geospatially resolved wetland vulnerability index: Synthesis of physical drivers |
title_fullStr | A geospatially resolved wetland vulnerability index: Synthesis of physical drivers |
title_full_unstemmed | A geospatially resolved wetland vulnerability index: Synthesis of physical drivers |
title_short | A geospatially resolved wetland vulnerability index: Synthesis of physical drivers |
title_sort | geospatially resolved wetland vulnerability index: synthesis of physical drivers |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6992177/ https://www.ncbi.nlm.nih.gov/pubmed/31999806 http://dx.doi.org/10.1371/journal.pone.0228504 |
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