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Het OWA, het open archief van het Waterbouwkundig Laboratorium heeft tot doel alle vrij toegankelijke onderzoeksresultaten van dit instituut in digitale vorm aan te bieden. Op die manier wil het de zichtbaarheid, verspreiding en gebruik van deze onderzoeksresultaten, alsook de wetenschappelijke communicatie maximaal bevorderen.
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| one publication added to basket [307974] |
Spatial and temporal distribution of submerged aquatic vegetation in a tropical coastal lagoon habitat in Viet Nam
Phan, T.T.H.; Stiers, I.; Nguyen, T.T.H.; Pham, T.T.; Ton, T.P.; Luong, Q.D.; Triest, L. (2018). Spatial and temporal distribution of submerged aquatic vegetation in a tropical coastal lagoon habitat in Viet Nam. Bot. Mar. 61(3): 213-224. https://dx.doi.org/10.1515/bot-2017-0107
In: Botanica Marina. Walter de Gruyter & Co: Berlin; New York. ISSN 0006-8055; e-ISSN 1437-4323, meer
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| Author keywords |
grain sizes; hydrophytes; salinity; seagrasses; Tam Giang - Cau Hai |
| Auteurs | | Top |
- Phan, T.T.H., meer
- Stiers, I., meer
- Nguyen, T.T.H.
- Pham, T.T.
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- Ton, T.P.
- Luong, Q.D.
- Triest, L., meer
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| Abstract |
Submerged aquatic vegetation (SAV) is considered as a keystone habitat, contributing significantly to structure and function of coastal lagoons. However, limited understanding of the factors driving SAV distribution and abundance across a wide range of salinity in tropical coastal lagoons has restricted the effectiveness of managing and preserving the ecosystem services in coastal lagoon habitats. This study examined the distribution and abundance of SAV species in the growing season in relation to water physico-chemical variables and grain sizes of sediment types in a tropical lagoon in Viet Nam. The results revealed that Najas indica and Halophila beccarii were the dominant species in the community of 7 SAV species, accounting for 70% of the total cover and 55% of the total biomass sampled. Variation partitioning showed that both water and sediment variables were important in explaining spatial distribution and abundance of SAV species across the coastal lagoon. Salinity was the most significant predictor variable that accounted for the variation of SAV species data. The study implied that changes of salinity and silt (versus sand) particles can lead to different SAV assemblages in the lagoon. |
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