Evaluating the Response of Mediterranean-Atlantic Saltmarshes to Sea-Level Rise

Abstract

Saltmarshes provide high-value ecological services and play an important role in coastal ecosystems and populations. As the rate of sea level rise accelerates in response to climate change, saltmarshes and tidal environments and the ecosystem services that they provide could be lost in those areas that lack sediment supply for vertical accretion or space for landward migration. Predictive models could play an important role in foreseeing those impacts, and to guide the implementation of suitable management plans that increase the adaptive capacity of these valuable ecosystems. The SLAMM (sea-level affecting marshes model) has been extensively used to evaluate coastal wetland habitat response to sea-level rise. However, uncertainties in predicted response will also reflect the accuracy and quality of primary inputs such as elevation and habitat coverage. Here, we assessed the potential of SLAMM for investigating the response of Atlantic-Mediterranean saltmarshes to future sea-level rise and its application in managerial schemes. Our findings show that SLAMM is sensitive to elevation and habitat maps resolution and that historical sea-level trend and saltmarsh accretion rates are the predominant input parameters that influence uncertainty in predictions of change in saltmarsh habitats. The understanding of the past evolution of the system, as well as the contemporary situation, is crucial to providing accurate uncertainty distributions and thus to set a robust baseline for future predictions.

A Methodology to Assess Land Use Development, Flooding, and Wetland Change as Indicators of Coastal Vulnerability

“…For example, future analysis could incorporate the Lidar elevation data (DSM and DEM) along with the wetland maps (which were mapped using NAIP aerial photography and Lidar) and change results to further identify areas at risk to wetland loss [54]. The most popular model to assess potential changes to coastal marshes due to SLR is SLAMM (sea-level affecting marshes model) [55]; however, there is an increasing amount of evidence that the output from this model is directly related to the accuracy (horizontal and vertical) of elevation and habitat mapping data [56]. Therefore, another potential future analysis with data derived from this project will be to test the accuracy of the SLAMM model in this study area.…”

“…Now that we have documented areas at risk, it will be interesting and potentially useful to see if SLAMM also identifies these same areas at risk. Considering the reliance on elevation data (which can be inaccurate ), many researches have questioned the validity of the SLAMM output [54,56]. For example, one major drawback of SLAMM is that it does not incorporate urban development, or other land use conversions, into the model and since this is a driver of change in this study area, another modeling option is the use of ST-SIM (state-and-transition simulation model) [78].…”

Coastal Salt Marshes

“…Human interventions such as settlings and channel redirection or other mechanical works further maximize the effect of wave action on coastlines that host wetland networks (Adam 2002). Fernandez-Nunez et al (2019) report that although a coastal salt marsh could potentially accrete vertically following a possible sea level rise, lateral erosion caused by either anthropogenic or natural factors can significantly affect the pioneer zone and may induce loss rates higher than the accretion rates, resulting in the total loss of the marsh.…”

A climate adaptation strategy for Mai Po Inner Deep Bay Ramsar site: Steppingstone to climate proofing the East Asian-Australasian Flyway

“…This model has been widely used for coastal resource management across the world, including for selected wetlands in the Yellow Sea estuary of China [16,27] and Korea [28] in the EAAF region. But we note that the lack of data on historic wetland conversion, especially outside North America [29] hinders retrospective analysis, which could be used to calibrate and validate the model. Analyses have shown that elevation data is the most important factor for output accuracy since conversion among habitat classes is mainly governed by elevation [29][30][31].…”

“…But we note that the lack of data on historic wetland conversion, especially outside North America [29] hinders retrospective analysis, which could be used to calibrate and validate the model. Analyses have shown that elevation data is the most important factor for output accuracy since conversion among habitat classes is mainly governed by elevation [29][30][31]. Therefore, a high-resolution DEM is important for generating consistent results.…”