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Marine Biology

, Volume 144, Issue 4, pp 653–664 | Cite as

Factors affecting macroalgal distribution in a eutrophic tropical lagoon in Taiwan

  • Hsing-Juh LinEmail author
  • Jia-Jang Hung
Research Article

Abstract

Factors affecting distribution of macroalgal periphyton were examined during a complete seasonal cycle in Tapong Bay, a eutrophic tropical lagoon in southern Taiwan. Water residence time varied from a few days to weeks. Total biomass and species richness declined with increasing residence time. However, they appeared to exhibit a unimodal seasonal pattern across all study sites, with blooms and greater richness in winter and spring and lower values in summer and fall. Nonmetric multidimensional scaling ordination of macroalgal communities reveals a clear gradual continuum of changes in species composition along the flushing gradient, suggesting the communities were primarily structured by site, and secondarily by season. The fast-flushing region was dominated by the chlorophycean genus Ulva, which was replaced by Enteromorpha intestinalis at mid-flushing levels, while the cyanobacterium Lyngbya majuscula was the dominant species in the slow-flushing region. Tissue nitrogen, but not tissue phosphorus, of these dominant species increased with increasing nutrient availability as a result of slow flushing. Our results suggest that water motion was an important selective factor for the spatial dominance of macroalgal species in Tapong Bay. This study demonstrates that species-dependent ordination is more sensitive in discriminating between sites than are species-independent measures such as total biomass and nutrient content when monitoring coastal eutrophication in the tropics. However, more-sensitive ordination provides only an ‘early warning’ that a community is changing; less-sensitive measures are also required to indicate the magnitude and type of these environmental changes.

Keywords

Phytoplankton Macroalgae Dissolve Organic Nitrogen Water Residence Time Herbivorous Fish 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements

This study was supported by the National Science Council under grant number NSC89-2621-2-056A-001. We are grateful to Miss Hui-Ying Wang and Miss Pei-Chen Wen for field and laboratory assistance. Comments by two anonymous reviewers were particularly helpful in revising the manuscript.

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Copyright information

© Springer-Verlag 2003

Authors and Affiliations

  1. 1.Department of Life SciencesNational Chung Hsing UniversityTaichungTaiwan, R.O.C.
  2. 2.Institute of Marine Geology and ChemistryNational Sun Yat-sen UniversityKaohsiungTaiwan, R.O.C.

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