MODELLING, SIMULATION AND VISUALIZATION OF A MULTISPECIFIC PHILIPPINE SEAGRASS MEADOW
Seagrass meadows are constantly under threat from natural and man-made stresses due to its shallow existence in the coastal environment. Restoration and preservation of seagrasses by means of rehabilitation or transplanting strategies is possible, but the studies have been limited. An agent-based mo...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2019-12-01
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| Series: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Online Access: | https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-4-W19/77/2019/isprs-archives-XLII-4-W19-77-2019.pdf |
| Summary: | Seagrass meadows are constantly under threat from natural and man-made stresses due to its shallow existence in the coastal environment. Restoration and preservation of seagrasses by means of rehabilitation or transplanting strategies is possible, but the studies have been limited. An agent-based model of a mixed Philippine seagrass meadow is presented. Three species were used for testing: <i>Enhalus acoroides</i>, <i>Thalassia hemprichii</i>, and <i>Cymodocea rotundata</i>. The model features parameter-based clonal growth of seagrass species, recruitment of new seagrass apices through basic flowering/seeding, and a crowding logic for multiple coexisting species in a single meadow. Seagrass clonal growth is modeled using a modified Diffusion-Limited Aggregation (DLA) model. Each species has a preconfigured set of parameters for clonal growth including rhizome elongation, branching rate, vertical elongation rate, rhizome branching angle and shoot age. Seed recruitment is applied through occasional flowering/seeding events configurable per species. We developed a simple three-species competition model which controls the growth and direct competition effects based on a configurable population size and comparison radius. Upon further calibration and validation, the model would enable more accurate long-term predictions for different rehabilitation and transplanting strategies of mixed seagrass meadows. Further improvements can also be implemented, particularly taking into account the environmental variables within the meadows such as light attenuation and salinity, among other factors. |
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| ISSN: | 1682-1750 2194-9034 |