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Landscape metrics as predictors of hydrologic connectivity between Coastal Plain forested wetlands and streams

Geographically isolated wetlands, those entirely surrounded by uplands, provide numerous landscape‐scale ecological functions, many of which are dependent on the degree to which they are hydrologically connected to nearby waters. There is a growing need for field‐validated, landscape‐scale approache...

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Autores principales: Epting, Steven M., Hosen, Jacob D., Alexander, Laurie C., Lang, Megan W., Armstrong, Alec W., Palmer, Margaret A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5856080/
https://www.ncbi.nlm.nih.gov/pubmed/29576682
http://dx.doi.org/10.1002/hyp.11433
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author Epting, Steven M.
Hosen, Jacob D.
Alexander, Laurie C.
Lang, Megan W.
Armstrong, Alec W.
Palmer, Margaret A.
author_facet Epting, Steven M.
Hosen, Jacob D.
Alexander, Laurie C.
Lang, Megan W.
Armstrong, Alec W.
Palmer, Margaret A.
author_sort Epting, Steven M.
collection PubMed
description Geographically isolated wetlands, those entirely surrounded by uplands, provide numerous landscape‐scale ecological functions, many of which are dependent on the degree to which they are hydrologically connected to nearby waters. There is a growing need for field‐validated, landscape‐scale approaches for classifying wetlands on the basis of their expected degree of hydrologic connectivity with stream networks. This study quantified seasonal variability in surface hydrologic connectivity (SHC) patterns between forested Delmarva bay wetland complexes and perennial/intermittent streams at 23 sites over a full‐water year (2014–2015). Field data were used to develop metrics to predict SHC using hypothesized landscape drivers of connectivity duration and timing. Connection duration was most strongly related to the number and area of wetlands within wetland complexes as well as the channel width of the temporary stream connecting the wetland complex to a perennial/intermittent stream. Timing of SHC onset was related to the topographic wetness index and drainage density within the catchment. Stepwise regression modelling found that landscape metrics could be used to predict SHC duration as a function of wetland complex catchment area, wetland area, wetland number, and soil available water storage (adj‐R (2) = 0.74, p < .0001). Results may be applicable to assessments of forested depressional wetlands elsewhere in the U.S. Mid‐Atlantic and Southeastern Coastal Plain, where climate, landscapes, and hydrological inputs and losses are expected to be similar to the study area.
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spelling pubmed-58560802018-03-21 Landscape metrics as predictors of hydrologic connectivity between Coastal Plain forested wetlands and streams Epting, Steven M. Hosen, Jacob D. Alexander, Laurie C. Lang, Megan W. Armstrong, Alec W. Palmer, Margaret A. Hydrol Process Research Articles Geographically isolated wetlands, those entirely surrounded by uplands, provide numerous landscape‐scale ecological functions, many of which are dependent on the degree to which they are hydrologically connected to nearby waters. There is a growing need for field‐validated, landscape‐scale approaches for classifying wetlands on the basis of their expected degree of hydrologic connectivity with stream networks. This study quantified seasonal variability in surface hydrologic connectivity (SHC) patterns between forested Delmarva bay wetland complexes and perennial/intermittent streams at 23 sites over a full‐water year (2014–2015). Field data were used to develop metrics to predict SHC using hypothesized landscape drivers of connectivity duration and timing. Connection duration was most strongly related to the number and area of wetlands within wetland complexes as well as the channel width of the temporary stream connecting the wetland complex to a perennial/intermittent stream. Timing of SHC onset was related to the topographic wetness index and drainage density within the catchment. Stepwise regression modelling found that landscape metrics could be used to predict SHC duration as a function of wetland complex catchment area, wetland area, wetland number, and soil available water storage (adj‐R (2) = 0.74, p < .0001). Results may be applicable to assessments of forested depressional wetlands elsewhere in the U.S. Mid‐Atlantic and Southeastern Coastal Plain, where climate, landscapes, and hydrological inputs and losses are expected to be similar to the study area. John Wiley and Sons Inc. 2018-02-20 2018-02-15 /pmc/articles/PMC5856080/ /pubmed/29576682 http://dx.doi.org/10.1002/hyp.11433 Text en © 2018 The Authors. Hydrological Processes Published by John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution (http://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Articles
Epting, Steven M.
Hosen, Jacob D.
Alexander, Laurie C.
Lang, Megan W.
Armstrong, Alec W.
Palmer, Margaret A.
Landscape metrics as predictors of hydrologic connectivity between Coastal Plain forested wetlands and streams
title Landscape metrics as predictors of hydrologic connectivity between Coastal Plain forested wetlands and streams
title_full Landscape metrics as predictors of hydrologic connectivity between Coastal Plain forested wetlands and streams
title_fullStr Landscape metrics as predictors of hydrologic connectivity between Coastal Plain forested wetlands and streams
title_full_unstemmed Landscape metrics as predictors of hydrologic connectivity between Coastal Plain forested wetlands and streams
title_short Landscape metrics as predictors of hydrologic connectivity between Coastal Plain forested wetlands and streams
title_sort landscape metrics as predictors of hydrologic connectivity between coastal plain forested wetlands and streams
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5856080/
https://www.ncbi.nlm.nih.gov/pubmed/29576682
http://dx.doi.org/10.1002/hyp.11433
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