Environmental Effects and Aquatic Organisms: Investigations of Molecular Mechanisms of Carcinogenesis

Cancers of the reproductive system are among the leading causes of mortality in women in the United States. While both genetic and environmental factors have been implicated in their etiology, the extent of the contribution of environmental factors to human diseases remains controversial. To better address the role of environmental exposures in cancer etiology, there has been an increasing focus on the development of nontraditional, environmentally relevant models. Our research involves the development of one such model, Gonadal tumors have been described in the softshell clam (Mya arenaria) in Maine and the hardshell clam (Mercenaria spp.) from Florida. Prevalence of these tumors is as high as 40% in some populations in eastern Maine and 60% in Some areas along the Indian River in Florida. The average tumor prevalence in Maine and Florida is approximately 20 and 11%, respectively. An association has been suggested between the use of herbicides and the incidence of gonadal tumors in the softshell clam in Maine. The role of environmental exposures in the development of the tumors in Mercenaria in Florida is unknown, however, there is evidence that genetic factors may contribute to its etiology. Epidemiologic studies of human populations in these same areas show a higher than average mortality rate due to cancers of the reproductive system in women, including both ovarian and breast career. The relationship, if any, among these observations is unknown, Our studies on the molecular basis of this disease in clams may provide additional information on environmental exposures and their possible link to cancer in clams and other organisms, including humans.

Assessment of Skill and Portability in Regional Marine Biogeochemical Models: Role of Multiple Planktonic Groups

Application of biogeochemical models to the study of marine ecosystems is pervasive, yet objective quantification of these models' performance is rare. Here, 12 lower trophic level models of varying complexity are objectively assessed in two distinct regions (equatorial Pacific and Arabian Sea). Each model was run within an identical one-dimensional physical framework. A consistent variational adjoint implementation assimilating chlorophyll-a, nitrate, export, and primary productivity was applied and the same metrics were used to assess model skill. Experiments were performed in which data were assimilated from each site individually and from both sites simultaneously. A cross-validation experiment was also conducted whereby data were assimilated from one site and the resulting optimal parameters were used to generate a simulation for the second site. When a single pelagic regime is considered, the simplest models fit the data as well as those with multiple phytoplankton functional groups. However, those with multiple phytoplankton functional groups produced lower misfits when the models are required to simulate both regimes using identical parameter values. The cross-validation experiments revealed that as long as only a few key biogeochemical parameters were optimized, the models with greater phytoplankton complexity were generally more portable. Furthermore, models with multiple zooplankton compartments did not necessarily outperform models with single zooplankton compartments, even when zooplankton biomass data are assimilated. Finally, even when different models produced similar least squares model-data misfits, they often did so via very different element flow pathways, highlighting the need for more comprehensive data sets that uniquely constrain these pathways.