Modeling nonlinear seagrass clonal growth: Assessing the efficiency of space occupation across the seagrass flora

The clonal growth of 9 seagrass species was modeled using a simulation model based on observed clonal growth rules (i.e., spacer length, rhizome elongation rates, branching rates, branching angle) and shoot mortality rates for seagrass species. The results of the model confirmed the occurrence of complex, nonlinear growth of seagrass clones derived from internal dynamics of space occupation. The modeled clones progressed from a diffuse-limited aggregation (DLA), dendritic growth, identified with a guerrilla strategy of space occupation, to a compact (Eden) growth, comparable to the phalanx strategy of space occupation, once internal recolonization of gaps, left by dead shoots within the clone, begins. The time at which seagrass clones shifted from diffuse limited to compact growth was predictable from the branching angle and frequency of the species and varied from 1 yr to several decades among species. As a consequence the growth behavior and the apparent growth strategy of the species changes with the development of the clones. The results of the model demonstrate that the emergent complexity of seagrass clonal growth is contained within the simple set of growth rules that can be used to represent clonal growth.     

Classifying coastal waters: Current necessity and historical perspective

Coastal ecosystems are ecologically and commercially valuable, productive habitats that are experiencing escalating compromises of their structural and functional integrity. The Clean Water Act (USC 1972) requires identification of impaired water bodies and determination of the causes of impairment. Classification simplifies these determinations, because estuaries within a class are more likely to respond similarly to particular stressors. We reviewed existing classification systems for their applicability to grouping coastal marine and Great Lakes water bodies based on their responses to aquatic stressors, including nutrients, toxic substances, suspended sediments, habitat alteration, and combinations of stressors. Classification research historically addressed terrestrial and freshwater habitats rather than coastal habitats. Few efforts focused on stressor response, although many well-researched classification frameworks provide information pertinent to stressor response. Early coastal classifications relied on physical and hydrological properties, including geomorphology, general circulation patterns, and salinity. More recent classifications sort ecosystems into a few broad types and may integrate physical and biological factors. Among current efforts are those designed for conservation of sensitive habitats based on ecological processes that support patterns of biological diversity. Physical factors, including freshwater inflow, residence time, and flushing rates, affect sensitivity to stressors. Biological factors, such as primary production, grazing rates, and mineral cycling, also need to be considered in classification. We evaluate each existing classification system with respect to objectives, defining factors, extent of spatial and temporal applicability, existing sources of data, and relevance to aquatic stressors. We also consider classification methods in a generic sense and discuss their strengths and weaknesses for our purposes. Although few existing classifications are based on responses to stressors, may well-researched paradigms provide important information for improving our capabilities for classification, as an investigative and predictive management tool.