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Towards a better characterization of morphological plasticity and biomass partitioning of trees in structural dynamics of mangrove forests

Changing environmental conditions often impose stressful growing conditions in plant communities. Until now, morphological plasticity, i.e. polymorphic growth physiognomies of plants, has not been sufficiently studied as a pivotal strategy for the whole ecosystem adaptation to environmental stress. We consider mangrove ecosystems as suitable models to provide insights on this subject.

In the thesis, I investigate the ecological significance of tree morphological plasticity in the structural development and the dynamics of mangrove forests. I conducted field experiments in two regions located on both sides of the Amazon River mouths i.e. in French Guiana and North Brazil. Forest inventories were carried out in contrasting mangrove stands in both regions. The thesis combines empirical analysis of field data, terrestrial laser scanning (TLS), and mechanistic, individual-based computer simulations.

We published results that proved the TLS-based analysis of individual tree structure useful for a better knowledge on biomass allocation between trunk and branches in tall and large Avicennia germinans mangrove trees reaching 45 m high and 125 cm of trunk diameter. Combining structural descriptions of A. germinans trees found in both sites, I highlighted the site-specific differences in tree allometries. The study suggests that regional differences in mangrove tree structure and function could be captured through better description of crown metrics, and that selected indicators of local morphological plasticity and consequent stand structure could generate a plus-value in the understanding of mangrove stand dynamics across contrasting coastal environments. Beyond the extension of allometric models to large Avicennia trees, we proposed new biomass equations with improved predictive power when crown metrics is taken into account. Additionally, we developed a novel software tool, named Lollymangrove, based on the AMAPStudio suite of software, with the objective of maximizing the potential of further field descriptions and modeling works. Lollymangrove allows standardized forest data capture, 3D visualization of structural data, aboveground biomass computations from a configurable module and export formats for forest dynamics and remote sensing models.

Simulation experiments were conducted by means of the spatially explicit, individual-based stand model BETTINA_IBM. This model describes the important mechanism of water uptake limited by salt stress, and revealed insights into the relation between environmental conditions, allometric variations and biomass partitioning of mangrove trees, and stand characteristics. The simulation results suggest close matches with observed ecological patterns (e.g., tree allometries, mortality distributions, and self-thinning trajectories) under higher salinity. In low salinity conditions, however, the current parameterization underestimates the maximum tree height and diameter, and consequently, aboveground biomass and self-thinning trajectories of forest stands. This suggests that the morphology of trees under low levels of salinity are explained by further regulation mechanism(s) that still need to be addressed in a subsequent model improvement.

Overall, this work has essentially pointed out the need to elucidate how morphological plasticity relates with structural development of forest stands. It establishes that TLS measurements and structural data analysis associated to efforts for integrative software and mechanistic modelling works could link mangrove dynamics to fast-changing coastal processes.

Identiferoai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:30214
Date09 December 2016
CreatorsOlagoke, Adewole
ContributorsBerger, Uta, Proisy, Christophe, Zimmer, Martin, Imbert, Daniel, Technische Universität Dresden
Source SetsHochschulschriftenserver (HSSS) der SLUB Dresden
LanguageEnglish
Detected LanguageEnglish
Typedoc-type:doctoralThesis, info:eu-repo/semantics/doctoralThesis, doc-type:Text
Rightsinfo:eu-repo/semantics/openAccess

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