Responses of eastern Chinese coastal salt marshes to sea-level rise combined with vegetative and sedimentary processes.
ABSTRACT: The impacts of sea-level rise (SLR) on coastal ecosystems have attracted worldwide attention in relation to global change. In this study, the salt marsh model for the Yangtze Estuary (SMM-YE, developed in China) and the Sea Level Affecting Marshes Model (SLAMM, developed in the U.S.) were used to simulate the effects of SLR on the coastal salt marshes in eastern China. The changes in the dominant species in the plant community were also considered. Predictions based on the SLAMM indicated a trend of habitat degradation up to 2100; total salt marsh habitat area continued to decline (4-16%) based on the low-level scenario, with greater losses (6-25%) predicted under the high-level scenario. The SMM-YE showed that the salt marshes could be resilient to threats of SLR through the processes of accretion of mudflats, vegetation expansion and sediment trapping by plants. This model predicted that salt marsh areas increased (3-6%) under the low-level scenario. The decrease in the total habitat area with the SMM-YE under the high-level scenario was much lower than the SLAMM prediction. Nevertheless, SLR might negatively affect the salt marsh species that are not adapted to prolonged inundation. An adaptive strategy for responding to changes in sediment resources is necessary in the Yangtze Estuary.
Project description:Storm surge and sea level rise (SLR) are affecting coastal communities, properties, and ecosystems. While coastal ecosystems, such as wetlands and marshes, have the capacity to reduce the impacts of storm surge and coastal flooding, the increasing rate of SLR can induce the transformation and migration of these natural habitats. In this study, we combined coastal storm surge modeling and economic analysis to evaluate the role of natural habitats in coastal flood protection. We focused on a selected cross-section of three coastal counties in New Jersey adjacent to the Jacques Cousteau National Estuarine Research Reserve (JCNERR) that is protected by wetlands and marshes. The coupled coastal hydrodynamic and wave models, ADCIRC+SWAN, were applied to simulate flooding from historical and synthetic storms in the Mid-Atlantic US for current and future SLR scenarios. The Sea Level Affecting Marshes Model (SLAMM) was used to project the potential migration and habitat transformation in coastal marshes due to SLR in the year 2050. Furthermore, a counterfactual land cover approach, in which marshes are converted to open water in the model, was implemented for each storm scenario in the present and the future to estimate the amount of flooding that is avoided due to the presence of natural habitats and the subsequent reduction in residential property damage. The results indicate that this salt marshes can reduce up to 14% of both the flood depth and property damage during relatively low intensity storm events, demonstrating the efficacy of natural flood protection for recurrent storm events. Monetarily, this translates to the avoidance of up to $13.1 and $32.1 million in residential property damage in the selected coastal counties during the '50-year storm' simulation and hurricane Sandy under current sea level conditions, and in the year '2050 SLR scenario', respectively. This research suggests that protecting and preserving natural habitats can contribute to enhance coastal resilience.
Project description:Sea Level Rise (SLR) caused by climate change is impacting coastal wetlands around the globe. Due to their distinctive biophysical characteristics and unique plant communities, freshwater tidal wetlands are expected to exhibit a different response to SLR as compared with the better studied salt marshes. In this study we employed the Sea Level Affecting Marshes Model (SLAMM), which simulates regional- or local-scale changes in tidal wetland habitats in response to SLR, and adapted it for application in a freshwater-dominated tidal river system, the Hudson River Estuary. Using regionally-specific estimated ranges of SLR and accretion rates, we produced simulations for a spectrum of possible future wetland distributions and quantified the projected wetland resilience, migration or loss in the HRE through the end of the 21st century. Projections of total wetland extent and migration were more strongly determined by the rate of SLR than the rate of accretion. Surprisingly, an increase in net tidal wetland area was projected under all scenarios, with newly-formed tidal wetlands expected to comprise at least 33% of the HRE's wetland area by year 2100. Model simulations with high rates of SLR and/or low rates of accretion resulted in broad shifts in wetland composition with widespread conversion of high marsh habitat to low marsh, tidal flat or permanent inundation. Wetland expansion and resilience were not equally distributed through the estuary, with just three of 48 primary wetland areas encompassing >50% of projected new wetland by the year 2100. Our results open an avenue for improving predictive models of the response of freshwater tidal wetlands to sea level rise, and broadly inform the planning of conservation measures of this critical resource in the Hudson River Estuary.
Project description:Salt marshes provide a bulwark against sea-level rise (SLR), an interface between aquatic and terrestrial habitats, important nursery grounds for many species, a buffer against extreme storm impacts, and vast blue carbon repositories. However, salt marshes are at risk of loss from a variety of stressors such as SLR, nutrient enrichment, sediment deficits, herbivory, and anthropogenic disturbances. Determining the dynamics of salt marsh change with remote sensing requires high temporal resolution due to the spectral variability caused by disturbance, tides, and seasonality. Time series analysis of salt marshes can broaden our understanding of these changing environments. This study analyzed aboveground green biomass (AGB) in seven mid-Atlantic Hydrological Unit Code 8 (HUC-8) watersheds. The study revealed that the Eastern Lower Delmarva watershed had the highest average loss and the largest net reduction in salt marsh AGB from 1999-2018. The study developed a method that used Google Earth Engine (GEE) enabled time series of the Landsat archive for regional analysis of salt marsh change and identified at-risk watersheds and salt marshes providing insight into the resilience and management of these ecosystems. The time series were filtered by cloud cover and the Tidal Marsh Inundation Index (TMII). The combination of GEE enabled Landsat time series, and TMII filtering demonstrated a promising method for historic assessment and continued monitoring of salt marsh dynamics.
Project description:The Sea Level Affecting Marshes Model (SLAMM) was applied at six major estuaries along Florida's Gulf Coast (Pensacola Bay, St. Andrews/Choctawhatchee Bays, Apalachicola Bay, Southern Big Bend, Tampa Bay and Charlotte Harbor) to provide quantitative and spatial information on how coastal ecosystems may change with sea level rise (SLR) and to identify how this information can be used to inform adaption planning. High resolution LiDAR-derived elevation data was utilized under three SLR scenarios: 0.7 m, 1 m and 2 m through the year 2100 and uncertainty analyses were conducted on selected input parameters at three sites. Results indicate that the extent, spatial orientation and relative composition of coastal ecosystems at the study areas may substantially change with SLR. Under the 1 m SLR scenario, total predicted impacts for all study areas indicate that coastal forest (-69,308 ha; -18%), undeveloped dry land (-28,444 ha; -2%) and tidal flat (-25,556 ha; -47%) will likely face the greatest loss in cover by the year 2100. The largest potential gains in cover were predicted for saltmarsh (+32,922 ha; +88%), transitional saltmarsh (+23,645 ha; na) and mangrove forest (+12,583 ha; +40%). The Charlotte Harbor and Tampa Bay study areas were predicted to experience the greatest net loss in coastal wetlands The uncertainty analyses revealed low to moderate changes in results when some numerical SLAMM input parameters were varied highlighting the value of collecting long-term sedimentation, accretion and erosion data to improve SLAMM precision. The changes predicted by SLAMM will affect exposure of adjacent human communities to coastal hazards and ecosystem functions potentially resulting in impacts to property values, infrastructure investment and insurance rates. The results and process presented here can be used as a guide for communities vulnerable to SLR to identify and prioritize adaptation strategies that slow and/or accommodate the changes underway.
Project description:Tidal marshes will be threatened by increasing rates of sea-level rise (SLR) over the next century. Managers seek guidance on whether existing and restored marshes will be resilient under a range of potential future conditions, and on prioritizing marsh restoration and conservation activities.Building upon established models, we developed a hybrid approach that involves a mechanistic treatment of marsh accretion dynamics and incorporates spatial variation at a scale relevant for conservation and restoration decision-making. We applied this model to San Francisco Bay, using best-available elevation data and estimates of sediment supply and organic matter accumulation developed for 15 Bay subregions. Accretion models were run over 100 years for 70 combinations of starting elevation, mineral sediment, organic matter, and SLR assumptions. Results were applied spatially to evaluate eight Bay-wide climate change scenarios.Model results indicated that under a high rate of SLR (1.65 m/century), short-term restoration of diked subtidal baylands to mid marsh elevations (-0.2 m MHHW) could be achieved over the next century with sediment concentrations greater than 200 mg/L. However, suspended sediment concentrations greater than 300 mg/L would be required for 100-year mid marsh sustainability (i.e., no elevation loss). Organic matter accumulation had minimal impacts on this threshold. Bay-wide projections of marsh habitat area varied substantially, depending primarily on SLR and sediment assumptions. Across all scenarios, however, the model projected a shift in the mix of intertidal habitats, with a loss of high marsh and gains in low marsh and mudflats.Results suggest a bleak prognosis for long-term natural tidal marsh sustainability under a high-SLR scenario. To minimize marsh loss, we recommend conserving adjacent uplands for marsh migration, redistributing dredged sediment to raise elevations, and concentrating restoration efforts in sediment-rich areas. To assist land managers, we developed a web-based decision support tool (www.prbo.org/sfbayslr).
Project description:Prioritization of marsh-management strategies is a difficult task as it requires a manager to evaluate the relative benefits of each strategy given uncertainty in future sea-level rise and in dynamic marsh response. A modeling framework to evaluate the costs and benefits of management strategies while accounting for both of these uncertainties has been developed. The base data for the tool are high-resolution uncertainty-analysis results from the SLAMM (Sea-Level Affecting Marshes Model) under different adaptive-management strategies. These results are combined with an ecosystem-valuation assessment from stakeholders. The SLAMM results and stakeholder values are linked together using "utility functions" that characterize the relationship between stakeholder values and geometric metrics such as "marsh area," marsh edge," or "marsh width." The expected-value of each site's ecosystem benefits can then be calculated and compared using estimated costs for each strategy. Estimates of optimal marsh-management strategies may then be produced, maximizing the "ecosystem benefits per estimated costs" ratio.
Project description:Ria de Aveiro is a mesotidal coastal lagoon with one of the largest continuous salt marshes in Europe. The objective of this work was to assess C, N and P stocks of Spartina maritima (low marsh pioneer halophyte) and Juncus maritimus (representative of mid-high marsh halophytes) combined with the contribution of Halimione portulacoides, Sarcocornia perennis, and Bolbochenous maritimus to the lagoon ?4400?ha marsh area. A multivariate analysis (PCO), taking into account environmental variables and the annual biomass and nutrient dynamics, showed that there are no clear seasonal or spatial differences within low or mid-high marshes, but clearly separates J. maritimus and S. maritima marshes. Calculations of C, N and P stocks in the biomass of the five most representative halophytes plus the respective rhizosediment (25?cm depth), and taking into account their relative coverage, represents 252053?Mg C, 38100?Mg N and 7563?Mg P. Over 90% of the stocks are found within mid-high marshes. This work shows the importance of this lagoon's salt marshes on climate and nutrients regulation, and defines the current condition concerning the 'blue carbon' and nutrient stocks, as a basis for prospective future scenarios of salt marsh degradation or loss, namely under SLR context.
Project description:Sea-level rise (SLR) impacts on intertidal habitat depend on coastal topology, accretion, and constraints from surrounding development. Such habitat changes might affect species like Belding's savannah sparrows (Passerculus sandwichensis beldingi; BSSP), which live in high-elevation salt marsh in the Southern California Bight. To predict how BSSP habitat might change under various SLR scenarios, we first constructed a suitability model by matching bird observations with elevation. We then mapped current BSSP breeding and foraging habitat at six estuarine sites by applying the elevation-suitability model to digital elevation models. To estimate changes in digital elevation models under different SLR scenarios, we used a site-specific, one-dimensional elevation model (wetland accretion rate model of ecosystem resilience). We then applied our elevation-suitability model to the projected digital elevation models. The resulting maps suggest that suitable breeding and foraging habitat could decline as increased inundation converts middle- and high-elevation suitable habitat to mudflat and subtidal zones. As a result, the highest SLR scenario predicted that no suitable breeding or foraging habitat would remain at any site by 2100 and 2110. Removing development constraints to facilitate landward migration of high salt marsh, or redistributing dredge spoils to replace submerged habitat, might create future high salt marsh habitat, thereby reducing extirpation risk for BSSP in southern California.
Project description:Climate change shuffles species ranges and creates novel interactions that may either buffer communities against climate change or exacerbate its effect. For instance, facilitation can become more prevalent in salt marshes under stressful conditions while competition is stronger in benign environments. Sea-level rise (SLR) is a consequence of climate change that affects the distribution of stress from inundation and salinity. To determine how interactions early in SLR are affected by changes in these two stressors in Mediterranean-climate marshes, we transplanted marsh turfs to lower elevations to simulate SLR and manipulated cover of the dominant plant species, Salicornia pacifica (formerly Salicornia virginica). We found that both S. pacifica and the subordinate species were affected by inundation treatments, and that subordinate species cover and diversity were lower at low elevations in the presence of S. pacifica than when it was removed. These results suggest that the competitive effect of S. pacifica on other plants is stronger at lower tidal elevations where we also found that salinity is reduced. As sea levels rise, stronger competition by the dominant plant will likely reduce diversity and cover of subordinate species, suggesting that stronger species interactions will exacerbate the effects of climate change on the plant community.
Project description:Many studies have explored the value of using more sophisticated coastal impact models and higher resolution elevation data in sea-level rise (SLR) adaptation planning. However, we know little about to what extent the improved models and data could actually lead to better conservation outcomes under SLR. This is important to know because high-resolution data are likely to not be available in some data-poor coastal areas in the world and running more complicated coastal impact models is relatively time-consuming, expensive, and requires assistance by qualified experts and technicians. We address this research question in the context of identifying conservation priorities in response to SLR. Specifically, we investigated the conservation value of using more accurate light detection and ranging (Lidar)-based digital elevation data and process-based coastal land-cover change models (Sea Level Affecting Marshes Model, SLAMM) to identify conservation priorities versus simple "bathtub" models based on the relatively coarse National Elevation Dataset (NED) in a coastal region of northeast Florida. We compared conservation outcomes identified by reserve design software (Zonation) using three different model dataset combinations (Bathtub-NED, Bathtub-Lidar, and SLAMM-Lidar). The comparisons show that the conservation priorities are significantly different with different combinations of coastal impact models and elevation dataset inputs. The research suggests that it is valuable to invest in more accurate coastal impact models and elevation datasets in SLR adaptive conservation planning because this model-dataset combination could improve conservation outcomes under SLR. Less accurate coastal impact models, including ones created using coarser Digital Elevation Model (DEM) data can still be useful when better data and models are not available or feasible, but results need to be appropriately assessed and communicated. A future research priority is to investigate how conservation priorities may vary among different SLR scenarios when different combinations of model-data inputs are used.