Projects

Determining localized impacts of predicted sea level rise to engineered versus natural landscapes, and how risk perception may alter response

End Date: 5/31/15

Abstract

The primary goal of this proposed project is to use a regional approach to refine the NOAA SLR Visualization Tool for local implementation in areas experiencing two different driving mechanisms of habitat change (subsidence and erosion).  This collaborative project involves researchers from USM and UNO who will determine the different ways in which two different stakeholder groups (traditional ecosystem users and resource managers) evaluate risk and plan mitigation strategies associated with habitat change due to predicted SLR.

To achieve this goal, we will determine: (1) a method for producing localized vulnerability/sustainability maps based on predicted inundation and redistribution of coastal wetlands under accelerated SLR for two regionally representative systems; the first is an ecosystem-dependent coastal Louisiana indigenous Native American community, and the second is a Mississippi natural coastal preserve.  Results from physical information derived from data and modeling of subsidence, erosion, engineered restoration and coastal protection features, historical land loss, and future land prediction under SLR that are complemented with traditional ecological knowledge (TEK) offered by the collaborating local ecosystem users will be integrated for these assessments; and (2) how and whether the results of such an approach can provide more useful information for assessing localized impacts of SLR and associated risk that may later be applied across the Gulf Coast by Seagrant and NOAA CSC among others.

The methods developed for this case study will enhance the development of the SLR Visualization Tool with new information to produce an accurate and comprehensive blueprint for evaluating local effects of predicted SLR that can benefit both human community and ecosystem mitigation planning.  This will be accomplished by bringing together physical science and TEK and potentially differing perspectives of risk in two different coastal stakeholder groups (ecosystem-dependent community residents versus resource managers).

Objectives

The primary goal of this proposed project is to use a regional approach to refine the NOAA SLR Visualization Tool for local implementation in areas experiencing two different driving mechanisms of habitat change (subsidence versus erosion). This collaborative project involves researchers from USM and UNO who will determine the different ways in which two different stakeholder groups (traditional ecosystem users versus resource managers) evaluate risk and plan mitigation strategies associated with habitat change due to predicted sea level rise (SLR). 

To achieve this goal, we will determine: (1) a method for producing localized vulnerability/sustainability maps based on predicted inundation and redistribution of coastal wetlands under accelerated SLR for two regionally representative systems; the first is an ecosystem-dependent coastal Louisiana indigenous Native American community, and the second is a Mississippi natural coastal preserve. Results from physical information derived from data and modeling of subsidence, erosion, engineered restoration and coastal protection features, historical land loss, and future land prediction under SLR that are complemented with traditional ecological knowledge (TEK) offered by the collaborating local ecosystem users will be integrated for these assessments; and (2) how and whether the results of such an approach can provide more useful information for assessing localized impacts of SLR and associated risk that may later be applied across the Gulf Coast by Seagrant and NOAA CSC among others.

Methodology

This proposed project will assemble an interdisciplinary team that includes physical and social scientists, community outreach and engagement specialists, agency managers, modelers, and ecosystem users.  The team’s specific skills include the following:  coastal inundation mapping and modeling; marsh vegetation biophysical characteristics; GIS and remote sensing applications in marsh health mapping, land loss assessments, and TEK-based social/cultural datasets; and community vulnerability and risk assessments.  With this interdisciplinary team, the proposed project will consider both ecological and social/cultural aspects of predicted SLR risk to produce integrated mapping products suitable to inform local mitigation strategies for two very different stakeholder groups.

We will study two representative coastal marsh systems; (1) the livelihood base of the Pointe-au-Chien tribe in Pointe Aux Chenes, LA with anthropogenic disturbances and high subsidence rates affecting its marshes, and (2) the more natural marshes of the Grand Bay National Estuarine Research Reserve in MS (GNDNERR) with low subsidence rates and little anthropogenic disturbances.  The proposed work will include three phases: Phase I – Data Collection that includes both (A) biophysical scientific information and (B) TEK about the study sites that produce mapping products that can be included as inputs in modeling predicted local SLR impacts; Phase II – Spatial modeling of a range of predicted SLR and storm surge scenarios; and Phase III – Risk Assessment and communication that results from the integrated mapping products of both the biophysical modeling and TEK.

Rationale

Marshes are essential buffer zones between land and water in estuaries and coastal zones, they are disappearing rapidly, and those that remain are often in poor health. The most dramatic coastal marsh losses in the U.S. are in the northern Gulf of Mexico (Turner, 1997). These disappearing marshes serve as a vital habitat for a diverse and unique range of flora and fauna, a cushion between coastal waterfront-dependent communities and the open waters of the Gulf, and an integral resource for the economic and social viability of these communities. Therefore, coastal community leaders, government officials, and natural resource managers must be able to accurately assess and predict a given coastal landscape’s sustainability and/or vulnerability, especially as this coastal habitat continues to undergo rapid and dramatic changes associated with natural and anthropogenic activities such as accelerated relative SLR.

This proposed project will develop new data to characterize local vulnerabilities and impacts of sea-level rise at two sites representative of highly vulnerable coastal marshes Gulf-wide. GIS and remote-sensing data, scientifically-derived biophysical data, anthropologically obtained Traditional Ecological Knowledge, and mechanistic modeling will all be combined to simulate and forecast site vulnerability to SLR and the associated risks to natural and built resources. The information obtained will be compared with the NOAA SLR Visualization Tool and missing elements will be communicated to Seagrant and the NOAA Coastal Services Center for further improvement of this tool region-wide.

Results

Local knowledge informs restoration