Due to the wide range of provided ecosystem services of mangroves, their conservation, maintenance, and restoration is of major public interest. The distribution of species and plant growth forms in mangrove ecosystems is patterned in zones. The characteristics of these zonation patterns can provide evidence on ecosystem properties. There is ongoing discussion on the drivers leading to mangrove zonation. No full mechanistic explanation to understand the complete interaction of the multiple factors that determine the mangrove zonation patterns exists.Therefore, the underlying processes require deeper evaluation.This will help to better design mangrove conservation projects, and allow more reliable projections of ecosystem development in a changing climate.
Numerical and conceptual modelling facilitates the understanding of system dynamics. In this work, I present the process- and individual-based mangrove population dynamics model MANGA. The mechanistic modelling approach is based on first principles. With the full coupling between a groundwater flow model and an individual-based mangrove growth model, MANGA provides a novel approach to study mangrove ecosystem dynamics.
MANGA describes observed mangrove stand zonation in species distribution and plant growth forms as the consequence of the apparent site conditions such as hydrologic conductivity, porewater salinity distribution and the tidal regime.
Model parameterization does not only depend on empirical evidence.Knowledge on the underlying processes can also be used for model calibration. Varying model boundary conditions and parameters provides insights to the influence of a variety of abiotic drivers on mangrove zonation. The MANGA model is capable to simulate the reaction of mangrove ecosystem to variations of environmental conditions related to climate change. According to MANGA simulations, for example, mangrove species composition depends on freshwater inputs which alter with varying precipitation regimes.
Based on the presented applications of the mechanistic modelling approach, I discuss benefits and current limitations, and outline possible future use of the MANGA model.
| Identifer | oai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:77480 |
| Date | 20 January 2022 |
| Creators | Bathmann, Jasper |
| Contributors | Kolditz, Olaf, Berger, Uta, Grimm, Volker, Krauss, Ken, Technische Universität Dresden, Umweltforschungszentrum |
| Source Sets | Hochschulschriftenserver (HSSS) der SLUB Dresden |
| Language | English |
| Detected Language | English |
| Type | info:eu-repo/semantics/publishedVersion, doc-type:doctoralThesis, info:eu-repo/semantics/doctoralThesis, doc-type:Text |
| Rights | info:eu-repo/semantics/openAccess |
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