Abstract
Underwater irradiance has frequently been cited as one of the most important, if not dominant, factors that regulates the distribution and productivity of seagrasses. Here we test that hypothesis in the development of a model to predict changes in the biomass of the seagrass Halodule wrightii Aschers based on the assumption that light is the dominant factor affecting growth. The model is a time-dependent, mechanistic model developed from above- and below-ground mass-bal- ance and based on data collected in the Upper Laguna Madre, Texas, over a period of 9 yr from 1989 to 1997; the data set is ideally suited to testing the assumptions of the model. The data include regu- lar measurements of above- and below-ground biomass coupled with continuous monitoring of underwater irradiance. Although the Upper Laguna suffered from a persistent brown tide from the summer of 1990 through the spring of 1996, the model was successful in reproducing trends in the observed above- and below-ground biomass. In particular, it captured the rapid recovery of the below-ground biomass as the brown tide bloom declined during spring 1996. Since agreement between the model and data decreases over a period of about 1 yr, some simple data-assimilation techniques were incorporated to help improve model performance. Close agreement between our model and in situ biomass measurements of H. wrightii collected over a 9 yr period reflect the impor- tance of underwater light intensity as a major abiotic factor regulating seagrass productivity. In addi- tion, the success of the model in predicting both above- and below-ground biomass demonstrates the importance of including both compartments in whole-plant modeling efforts that can be applied to coastal management practices. The demonstrated validity of a predictive whole-plant model for sea- grass biomass will provide a valuable tool in the successful management of seagrass resources in coastal areas threatened by decreases in water transparency from anthropogenic impacts.
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