An agent-based model approach to assessing the role of vegetative fragments in seagrass connectivity

Samantha Lai, Theophilus Zhi En Teo, Arief Rullyanto, Jeffery Low, Karenne Tun, Peter A. Todd and Siti Maryam Yaakub

Ecological Modelling, 2024, vol. 487, issue C

Abstract: Understanding how populations in the marine environment exchange genetic material is vital for the implementation of suitable conservation measures. However, dispersal can be challenging to empirically assess as it can occur over huge distances. Increasingly, agent-based models (ABMs) are being used to predict the dispersal pathways of populations of many taxa, including seagrasses. Most seagrass ABMs have been based on sexual propagules (i.e. fruits, seeds, spathes), and overlook the potential role of asexual vegetative fragments in long-distance dispersal. In this study, we developed two contrasting ABMs, one for vegetative fragments and another for fruits and seeds using Halophila ovalis and Thalassia hemprichii respectively as model species, to evaluate (i) the dispersal potential of these two dispersal strategies, and (ii) the local and regional seagrass connectivity around Singapore. Our models demonstrate that vegetative fragments could be an effective mode of dispersal for H. ovalis, having similar establishment patterns to T. hemprichii fruits/seeds and establishing at greater distances on average. The models also show that most meadows are well connected locally and regionally, regardless of the mode of dispersal. The ABMs identified possible source and sink meadows that should be conserved to provide a repository of genetic material, as well as a supply of propagules for recruitment. We highlight the need to include vegetative fragments alongside sexual propagules when evaluating seagrass connectivity in future modeling efforts.

Keywords: Individual-based model; Thalassia hemprichii; Halophila ovalis; Asexual; Sexual; Dispersal (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecomod:v:487:y:2024:i:c:s0304380023002582

DOI: 10.1016/j.ecolmodel.2023.110528

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