Limnology and Oceanography · 1995 · 340 citations · 30 references
SeagrassBiogeochemistryEutrophicationEngineeringAlgal BiomassBotanyMesocosm ExperimentsMarine PollutionZostera MarinaMarine EcologyOutdoor Mesocosm ExperimentsMarine BiologyAlgal BiologyExcess Nutrient LoadingPhotosynthesisEelgrass CommunitiesEstuaryHealth Sciences
Outdoor mesocosm experiments were used to examine the response of eelgrass communities to excess nutrient loading and reduced light that simulated coastal eutrophication. A series of replicated manipulations conducted between 1988 and 1990 demonstrated the effects of reduced available light and increased loading of nitrogen plus phosphorus on habitats dominated by eelgrass Zostera marina L. Shade and nutrients each significantly affected eelgrass growth, morphology, density, and biomass. We found no significant interactions between the effects of shade and the effects of nutrients on any plant characteristics except leaf length. The growth rate of individual eelgrass shoots was linearly related to light, increasing throughout the range of available light. Biomass and daily biomass increase, or areal growth, were also linearly related to light, but specific growth showed no response to light. Shoot density increased with the log of light. Excess nutrient loading was shown to significantly reduce eelgrass growth and bed structure through stimulation of various forms of algae that effectively competed with eelgrass for light. The absence of significant interactions between the effects of shade and nutrients on eelgrass density, growth, and biomass suggests that the negative effect of algae on eelgrass occurs primarily through the reduction of light (i.e. shading). The outcome of nutrient enrichment was a shift in plant dominance from eelgrass to three algal forms: phytoplankton, epiphytic algae, and macroalgae. We quantified the effects of eutrophication and demonstrated that increased nutrient loading results in less light for eelgrass and that eelgrass growth linearly decreases with reduced light.
30
Applied Linear Statistical Models
Eric R. Ziegel, John Neter, William Wasserman et al. · Technometrics · 1992 · 10K citations
Statistical Foundation, Regression Analysis, Statistical Inference +3
Applied Linear Statistical Models
Ralph C. St. John · Journal of Quality Technology · 1986 · 1.3K citations
Assessing Water Quality with Submersed Aquatic Vegetation
William C. Dennison, Robert J. Orth, Kenneth A. Moore et al. · BioScience · 1993 · 899 citations
Carlos M. Duarte · Aquatic Botany · 1991 · 810 citations