Multiple Stable States and Catastrophic Shifts in Coastal Wetlands: Progress, Challenges, and Opportunities in Validating Theory Using Remote Sensing and Other Methods
Multiple stable states are established in coastal tidal wetlands (marshes, mangroves, deltas, seagrasses) by ecological, hydrological, and geomorphological feedbacks. Catastrophic shifts between states can be induced by gradual environmental change or by disturbance events. These feedbacks and outco...
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doaj-768fa380152d43a3a477601c51c149282020-11-24T23:58:10ZengMDPI AGRemote Sensing2072-42922015-08-0178101841022610.3390/rs70810184rs70810184Multiple Stable States and Catastrophic Shifts in Coastal Wetlands: Progress, Challenges, and Opportunities in Validating Theory Using Remote Sensing and Other MethodsKevan B. Moffett0William Nardin1Sonia Silvestri2Chen Wang3Stijn Temmerman4School of the Environment, Washington State University, Vancouver, WA 98686, USADepartment of Earth & Environment, Boston University, Boston, MA 02215, USANicholas School of the Environment, Duke University, Durham, NC 27708, USADepartment of Biology, University of Antwerp, Antwerpen 2000, BelgiumDepartment of Biology, University of Antwerp, Antwerpen 2000, BelgiumMultiple stable states are established in coastal tidal wetlands (marshes, mangroves, deltas, seagrasses) by ecological, hydrological, and geomorphological feedbacks. Catastrophic shifts between states can be induced by gradual environmental change or by disturbance events. These feedbacks and outcomes are key to the sustainability and resilience of vegetated coastlines, especially as modulated by human activity, sea level rise, and climate change. Whereas multiple stable state theory has been invoked to model salt marsh responses to sediment supply and sea level change, there has been comparatively little empirical verification of the theory for salt marshes or other coastal wetlands. Especially lacking is long-term evidence documenting if or how stable states are established and maintained at ecosystem scales. Laboratory and field-plot studies are informative, but of necessarily limited spatial and temporal scope. For the purposes of long-term, coastal-scale monitoring, remote sensing is the best viable option. This review summarizes the above topics and highlights the emerging promise and challenges of using remote sensing-based analyses to validate coastal wetland dynamic state theories. This significant opportunity is further framed by a proposed list of scientific advances needed to more thoroughly develop the field.http://www.mdpi.com/2072-4292/7/8/10184multiple stable statesalternative stable statesequilibriaremote sensingwetlandmarshdeltamangroveseagrasscoast |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Kevan B. Moffett William Nardin Sonia Silvestri Chen Wang Stijn Temmerman |
spellingShingle |
Kevan B. Moffett William Nardin Sonia Silvestri Chen Wang Stijn Temmerman Multiple Stable States and Catastrophic Shifts in Coastal Wetlands: Progress, Challenges, and Opportunities in Validating Theory Using Remote Sensing and Other Methods Remote Sensing multiple stable states alternative stable states equilibria remote sensing wetland marsh delta mangrove seagrass coast |
author_facet |
Kevan B. Moffett William Nardin Sonia Silvestri Chen Wang Stijn Temmerman |
author_sort |
Kevan B. Moffett |
title |
Multiple Stable States and Catastrophic Shifts in Coastal Wetlands: Progress, Challenges, and Opportunities in Validating Theory Using Remote Sensing and Other Methods |
title_short |
Multiple Stable States and Catastrophic Shifts in Coastal Wetlands: Progress, Challenges, and Opportunities in Validating Theory Using Remote Sensing and Other Methods |
title_full |
Multiple Stable States and Catastrophic Shifts in Coastal Wetlands: Progress, Challenges, and Opportunities in Validating Theory Using Remote Sensing and Other Methods |
title_fullStr |
Multiple Stable States and Catastrophic Shifts in Coastal Wetlands: Progress, Challenges, and Opportunities in Validating Theory Using Remote Sensing and Other Methods |
title_full_unstemmed |
Multiple Stable States and Catastrophic Shifts in Coastal Wetlands: Progress, Challenges, and Opportunities in Validating Theory Using Remote Sensing and Other Methods |
title_sort |
multiple stable states and catastrophic shifts in coastal wetlands: progress, challenges, and opportunities in validating theory using remote sensing and other methods |
publisher |
MDPI AG |
series |
Remote Sensing |
issn |
2072-4292 |
publishDate |
2015-08-01 |
description |
Multiple stable states are established in coastal tidal wetlands (marshes, mangroves, deltas, seagrasses) by ecological, hydrological, and geomorphological feedbacks. Catastrophic shifts between states can be induced by gradual environmental change or by disturbance events. These feedbacks and outcomes are key to the sustainability and resilience of vegetated coastlines, especially as modulated by human activity, sea level rise, and climate change. Whereas multiple stable state theory has been invoked to model salt marsh responses to sediment supply and sea level change, there has been comparatively little empirical verification of the theory for salt marshes or other coastal wetlands. Especially lacking is long-term evidence documenting if or how stable states are established and maintained at ecosystem scales. Laboratory and field-plot studies are informative, but of necessarily limited spatial and temporal scope. For the purposes of long-term, coastal-scale monitoring, remote sensing is the best viable option. This review summarizes the above topics and highlights the emerging promise and challenges of using remote sensing-based analyses to validate coastal wetland dynamic state theories. This significant opportunity is further framed by a proposed list of scientific advances needed to more thoroughly develop the field. |
topic |
multiple stable states alternative stable states equilibria remote sensing wetland marsh delta mangrove seagrass coast |
url |
http://www.mdpi.com/2072-4292/7/8/10184 |
work_keys_str_mv |
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