The mutual influence of biotic and abiotic components on the long-term ecomorphodynamic evolution of salt-marsh ecosystems

D’Alpaos, Andrea

doi:10.1016/j.geomorph.2010.04.027

Cited by 85 publications

(66 citation statements)

References 60 publications

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“…In a hypothetical nonvegetated setting k NV = α T , whereas with vegetation we have k = α T + γ 0 > k NV ; therefore larger k values allow marshes to keep pace with larger R values. Vegetation growth increases marsh accretion to such an extent that it allows existing marshes to keep pace with R values and SSCs that would preclude salt marsh surfaces from developing in the first place, consistent with the numerical results of D'Alpaos [2011] and Kirwan et al [2011].…”

Section: Discussionsupporting

confidence: 82%

“…In contrast, to analyze the effects of a sinusoidal rate of RSLR, Allen [1995] carried out more than 110 numerical simulations which allowed him to explore the role of sediment supply, vegetation productivity, oscillation period of the rate of RSLR and amplitude of the oscillation, without considering the role of the tidal range. Numerical models can be computationally expensive; owing to computational expense a full exploration of marsh response to changing sea level rise and sediment supply, or to variations in the quantities representative of the processes involved, has been difficult [e.g., Allen , 1995; Kirwan and Murray , 2008; D'Alpaos , 2011].…”

Section: Discussionmentioning

confidence: 99%

“…Managers should, however, be aware of the limitations of the approach as the model only addresses the average elevation of a marsh platform. Because sediment concentrations vary as a function of position on the marsh [e.g., Christiansen et al , 2000] its response to changing RSLR will also be spatially varied [e.g., D'Alpaos , 2011]. Moreover, we have considered a marsh populated by a single vegetation species, namely Spartina alterniflora , and have condensed in the parameters α T and γ O the characteristics of such species [ Morris and Haskin , 1990].…”

Section: Discussionmentioning

confidence: 99%

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Dynamic response of marshes to perturbations in suspended sediment concentrations and rates of relative sea level rise

2011

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[1] We have developed an analytical model of salt marsh evolution that captures the dynamic response of marshes to perturbations in suspended sediment concentrations, plant productivity, and the rate of relative sea level rise (RSLR). Sediment-rich and highly productive marshes will approach a new equilibrium state in response to a step change in the rate of RSLR faster than sediment-poor or less productive marshes. Microtidal marshes will respond more quickly to a step change in the rate of RSLR than mesotidal or macrotidal marshes. Marshes are more resilient to a decrease rather than to an increase in the rate of RSLR, and they are more resilient to a decrease rather than to an increase in sediment availability. Moreover, macrotidal marshes are more resilient to changes in the rate of RSLR than their microtidal counterparts. Finally, we find that a marsh's ability to record sea level fluctuations in its stratigraphy is fundamentally related to a timescale we call T FT , or filling timescale, which is equal to the tidal amplitude divided by the maximum possible accretion rate on the marsh (a function of plant productivity, sediment properties, and availability). Marshes with a short-filling timescale (i.e., marshes with rapid sedimentation or small tidal amplitudes) are best suited to recording high-frequency fluctuations in RSLR, but our model suggests it is unlikely that marshes will be able to record fluctuations occurring over timescales that are shorter than decadal.

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Section: Discussionsupporting

confidence: 82%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Dynamic response of marshes to perturbations in suspended sediment concentrations and rates of relative sea level rise

2011

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“…As sea level rises, plants at lower elevations are the first to be lost because they drown. This results in less overall organic accumulation on the marsh plain and less trapping of sediment, which ultimately accelerates drowning in other areas of the marsh (Kirwan and others 2008;D'Alpaos 2011). In the worst-case scenario, as sea level continues to rise, the entire marsh drowns and converts to open water habitat.…”

Section: Vegetation Feedback Loopsmentioning

confidence: 99%

Conceptual Model of Sedimentation in the Sacramento–San Joaquin Delta

Schoellhamer¹,

Wright²,

Drexler³

2012

SFEWS

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Sedimentation in the Sacramento-San Joaquin River Delta builds the Delta landscape, creates benthic and pelagic habitat, and transports sediment-associated contaminants. Here we present a conceptual model of sedimentation that includes submodels for river supply from the watershed to the Delta, regional transport within the Delta and seaward exchange, and local sedimentation in open water and marsh habitats. The model demonstrates feedback loops that affect the Delta ecosystem. Submerged and emergent marsh vegetation act as ecosystem engineers that can create a positive feedback loop by decreasing suspended sediment, increasing water column light, which in turn enables more vegetation. Sea-level rise in open water is partially countered by a negative feedback loop that increases deposition if there is a net decrease in hydrodynamic energy. Manipulation of regional sediment transport is probably the most feasible method to control suspended sediment and thus turbidity. The conceptual model is used to identify information gaps that need to be filled to develop an accurate sediment transport model.

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“…mountainous, fluvial or tidal) exhibit a variety of morphologies and their shape and functioning has attracted considerable attention in the research sphere (Montgomery et al, 1997;Rinaldo et al, 1998Rinaldo et al, , 1999a. A comprehensive understanding of channel networks' morphologies as well as their long-term evolutions is fundamental to address their response to environmental variations under increasing climate change and human pressure (French, 2006;D'Alpaos, 2011;Coco et al, 2013). Branching tidal networks are typical landscapes in back-barrier tidal basins such as the Wadden Sea (Wang et al, 2012) and the Venice Lagoon (D'Alpaos et al, 2007a).…”

Section: Introductionmentioning

confidence: 99%

Analysis of the drainage density of experimental and modelled tidal networks

et al. 2014

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Abstract. Based on controlled laboratory experiments, we numerically simulate the initiation and long-term evolution of back-barrier tidal networks in micro-tidal and meso-tidal conditions. The simulated pattern formation is comparable to the morphological growth observed in the laboratory, which is characterised by relatively rapid initiation and slower adjustment towards an equilibrium state. The simulated velocity field is in agreement with natural reference systems such as the micro-tidal Venice Lagoon and the meso-tidal Wadden Sea. Special attention is given to the concept of drainage density, which is measured on the basis of the exceedance probability distribution of the unchannelled flow lengths. Model results indicate that the exceedance probability distribution is characterised by an approximately exponential trend, similar to the results of laboratory experiments and observations in natural systems. The drainage density increases greatly during the initial phase of tidal network development, while it slows down when the system approaches equilibrium. Due to the larger tidal prism, the tidal basin has a larger drainage density for the meso-tidal condition (after the same amount of time) than the micro-tidal case. In both micro-tidal and meso-tidal simulations, it is found that there is an initial rapid increase of the tidal prism which soon reaches a relatively steady value (after approximately 40 yr), while the drainage density adjusts more slowly. In agreement with the laboratory experiments, the initial bottom perturbations play an important role in determining the morphological development and hence the exceedance probability distribution of the unchannelled flow lengths. Overall, our study indicates an agreement of the geometric characteristics between the numerical and experimental tidal networks.

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The mutual influence of biotic and abiotic components on the long-term ecomorphodynamic evolution of salt-marsh ecosystems

Cited by 85 publications

References 60 publications

Dynamic response of marshes to perturbations in suspended sediment concentrations and rates of relative sea level rise

Dynamic response of marshes to perturbations in suspended sediment concentrations and rates of relative sea level rise

Conceptual Model of Sedimentation in the Sacramento–San Joaquin Delta

Analysis of the drainage density of experimental and modelled tidal networks

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