Estonian coastal wetlands are of international importance as they support characteristic biological diversity. Their limited extent and distribution mean that these wetlands are of high conservation concern, and as such have been identified as a priority in the European Union Habitats Directive. These wetlands are typified by a flat, extensive landscape, situated between the micro-tidal «0.02m), brackish Baltic Sea and a forest interior. Due to the low relief these wetlands may be under threat from sea level rise. This research consisted of four studies: (i) to determine and quantify the relationship between a range of coastal wetland plant community types, elevation and edaphic conditions. Results demonstrated that plant community distribution was significantly affected by micro-topography and edaphic variability. The majority of the plant communities were discernible in the field by elevation alone and elevation was found to be the factor that could distinguish the greatest number of plant communities. (ii) to determine an appropriate method of interpolating LiDAR elevation data and assess the use of LiDAR data in creating a static correlative model to determine plant community type based on elevation. Results showed that with dGPS calibration the model could accurately predict plant community location. Validation of the model in two further sites showed that the correlative model was able to predict plant community with almost perfect (K 0.81) and moderate agreement (K 0.53) dependent on the site. (iii) to determine sediment accretion rates to complete the dynamic model by analysing the level of radionuclides, 137CS and 210Pb, in discrete core sections. Results showed that during periods of greater storminess sediment accretion increased almost threefold. These sensitivity data were included in the dynamic correlative model. (iv) to assess the effects of sea level rise on plant communities in Estonian coastal wetlands under five sea level scenarios, two accretion rate scenarios and factoring in isostatic uplift rates. Results showed that local sea level will rise in some sites and decrease in others dependent on location and SLR scenario. This study has indicated that in many instances Estonian coastal wetlands will increase in extent in the future due to high rates of sediment accretion, particularly in a scenario with more frequent storms, and isostatic uplift. The study has shown that following validation, calibration and sensitivity analysis LiDAR data can be used to accurately predict plant community type in microtopographical ecosystems. The model developed in this study of Estonian coastal wetlands is likely to be transferable to other appropriate habitats such as tidal, estuarine, and floodplains wetlands.
Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:589774 |
Date | January 2012 |
Creators | Ward, Raymond |
Publisher | University of Brighton |
Source Sets | Ethos UK |
Detected Language | English |
Type | Electronic Thesis or Dissertation |
Source | https://research.brighton.ac.uk/en/studentTheses/37b928df-19dc-48f5-aad8-08398383fb95 |
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