Project Details
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Adopting mangrove vegetation zonation patterns to gain information on subsurface aquifer structures and advance belowground plant competition concepts in individual-based modelling – MARZIPAN

Subject Area Ecology and Biodiversity of Plants and Ecosystems
Term from 2018 to 2021
Project identifier Deutsche Forschungsgemeinschaft (DFG) - Project number 398759560
 
Final Report Year 2022

Final Report Abstract

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 project, the process- and individual-based mangrove population dynamics model MANGA was developed. 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.

Publications

  • (2020). The interplay between vegetation and water in mangroves: new perspectives for mangrove stand modelling and ecological research. Wetlands Ecology and Management
    Peters, R., Walther, M., Lovelock, C., Jiang, J., and Berger, U.
    (See online at https://doi.org/10.1007/s11273-020-09733-0)
  • (2020). The MANgrove–GroundwAter feedback model (MANGA) – Describing belowground competition based on first principles. Ecological Modelling, 420:108973
    Bathmann, J., Peters, R., Naumov, D., Fischer, T., Berger, U., and Walther, M.
    (See online at https://doi.org/10.1016/j.ecolmodel.2020.108973)
  • (2021). Flows form forests the mangrove groundwater feedback model MANGA. Dresden
    Bathmann, Jasper, Kolditz, O., Berger, U., Grimm, V., and Krauss, K.
  • (2021). Modelling mangrove forest structure and species composition over tidal inundation gradients: The feedback between plant water use and porewater salinity in an arid mangrove ecosystem. Agricultural and Forest Meteorology, 308-309:108547
    Bathmann, J., Peters, R., Reef, R., Berger, U., Walther, M., and Lovelock, C. E.
    (See online at https://doi.org/10.1016/j.agrformet.2021.108547)
  • (2021). Partial canopy loss of mangrove trees: Mitigating water scarcity by physical adaptation and feedback on porewater salinity. Estuarine, Coastal and Shelf Science, page 106797
    Peters, R., Lovelock, C., López-Portillo, J., Bathmann, J., Wimmler, M. C., Jiang, J., Walther, M., and Berger, U.
    (See online at https://doi.org/10.1016/j.ecss.2020.106797)
  • (2021). Plant–soil feedbacks in mangrove ecosystems: establishing links between empirical and modelling studies. Trees
    Wimmler, M.-C., Bathmann, J., Peters, R., Jiang, J., Walther, M., Lovelock, C. E., and Berger, U.
    (See online at https://doi.org/10.1007/s00468-021-02182-z)
 
 

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