Plant Species Responses to an Elevational Gradient in German North Sea Salt Marshes

Suchrow, Sigrid; Jensen, Kai

doi:10.1007/s13157-010-0073-3

Cited by 62 publications

(48 citation statements)

References 48 publications

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“…Salt marshes are an obvious environment for the further application of the dynamic plant community model presented in this study. Several authors have related the zonation of marsh communities to elevation above mean sea level and hence tidal range (Cutini et al, 2010;Moffett et al, 2010;Suchrow & Jensen, 2010;Moffett et al, 2012). However, tidal ranges vary greatly, so any plant community model would likely be valid only for areas with similar tidal regimes.…”

Section: Discussionmentioning

confidence: 99%

Improved modelling of the impacts of sea level rise on coastal wetland plant communities

et al. 2015

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Section: Discussionmentioning

confidence: 99%

Improved modelling of the impacts of sea level rise on coastal wetland plant communities

et al. 2015

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“…However, marshes are intertidal areas often located at low elevation with very little topographic relief. Even a small topographic change can cause major impacts on wetland ecosystems such as water flow, sediment deposition, and the amplitude and frequency of inundation [6][7][8]. Elevation changes of less than a few cm have a significant effect on plant distribution and productivity [6][7][8].…”

Section: Introductionmentioning

confidence: 99%

Unsupervised Clustering Method for Complexity Reduction of Terrestrial Lidar Data in Marshes

et al. 2018

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Accurate characterization of marsh elevation and landcover evolution is important for coastal management and conservation. This research proposes a novel unsupervised clustering method specifically developed for segmenting dense terrestrial laser scanning (TLS) data in coastal marsh environments. The framework implements unsupervised clustering with the well-known K-means algorithm by applying an optimization to determine the "k" clusters. The fundamental idea behind this novel framework is the application of multi-scale voxel representation of 3D space to create a set of features that characterizes the local complexity and geometry of the terrain. A combination of point-and voxel-generated features are utilized to segment 3D point clouds into homogenous groups in order to study surface changes and vegetation cover. Results suggest that the combination of point and voxel features represent the dataset well. The developed method compresses millions of 3D points representing the complex marsh environment into eight distinct clusters representing different landcover: tidal flat, mangrove, low marsh to high marsh, upland, and power lines. A quantitative assessment of the automated delineation of the tidal flat areas shows acceptable results considering the proposed method is unsupervised with no training data. Clustering results based on K-means are also compared to results based on the Self Organizing Map (SOM) clustering algorithm. Results demonstrate that the developed multi-scale voxelization approach and representative feature set are transferrable to other clustering algorithms, thereby providing an unsupervised framework for intelligent scene segmentation of TLS point cloud data in marshes.

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“…During progressive succession, bare tidal flats are colonized by pioneer species of the low marsh, which are later replaced by high marsh species. Progressive succession results from sediment deposition and an associated increase in surface elevation (for salt marshes see, e.g., Olff et al 1997;Suchrow and Jensen 2010;Wang and Temmerman 2013). Contrastingly, regressive succession or a shift from vegetated marsh to bare tidal flat can occur if erosion leads to a decrease in surface elevation (van Proosdij et al 2006).…”

Section: Introductionmentioning

confidence: 99%

Vegetation succession of low estuarine marshes is affected by distance to navigation channel and changes in water level

et al. 2016

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Climate change and engineering activities have modified the hydrology and morphology of estuaries. However, the potential effects of these modifications on vegetation succession in estuarine marshes are still poorly understood. Therefore, we studied temporal changes in tidal habitats of the Elbe estuary over a period of 30 years. We compared vegetation maps from 1980 to 2010 and calculated the change in area of habitats with respect to three salinity and three elevational zones. To analyze the direction of the temporal change, we differentiated between progressive and regressive succession. By using regression tree models (conditional inference trees), we identified the most influential factors determining progressive or regressive succession of low marshes. The total area of the estuarine tidal marshes at the Elbe increased by 2 % from 1980 to 2010, but changes were unequal among the salinity zones. In the salt and brackish zones, the area covered by high marshes increased substantially but decreased in the tidal freshwater zone, while that covered by low marshes decreased in all the salinity zones. Additionally, we determined high persistence of tidal flats and high marshes, whereas only 19 to 28 % of the low marshes found in 1980 remained in 2010. In salt and brackish marshes, more than two-thirds of the area that had been identified as low marshes in 1980 had progressively developed into high marshes. In contrast, 44 % of the area of low marshes in tidal freshwater marshes showed regressive succession back into tidal flats. The distance to the navigation channel was the main factor determining successional direction in salt and brackish marshes. Here, greater proximity to the channel was correlated with higher risk of regressive succession. In tidal freshwater marshes, we identified both the distance to the navigation channel and the situation on the river shore (i.e. inner bank, outer bank or straight bank) as the main factors for marsh succession. Here, considerable engineering activities in the channel had simultaneously decreased the mean low water level and increased the mean high water level between 1980 and 2010, which led to an increase in tidal amplitude. It is quite likely that these changes negatively modified marsh distribution, increased regressive succession and, thus, lowered the quality of tidal freshwater marshes.

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Plant Species Responses to an Elevational Gradient in German North Sea Salt Marshes

Cited by 62 publications

References 48 publications

Improved modelling of the impacts of sea level rise on coastal wetland plant communities

Improved modelling of the impacts of sea level rise on coastal wetland plant communities

Unsupervised Clustering Method for Complexity Reduction of Terrestrial Lidar Data in Marshes

Vegetation succession of low estuarine marshes is affected by distance to navigation channel and changes in water level

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