Statistical models of fecal coliform levels in Pacific Northwest estuaries for improved shellfish harvest area closure decision making.

ABSTRACT: There is a substantial need for tools that effectively predict spatial and temporal fecal pollution patterns in estuarine waters. In this study, statistical models of exceedances of shellfish fecal coliform (FC) water quality criteria were developed using a 10-year dataset of FC levels and environmental data. Performance (sensitivity, specificity, and predictive capacity) of five different types of models was tested (MLR regression, Tobit (censored) regression, Firth's binary logistic regression (BLR), classification trees, and mixed-effects regression) for each of three conditionally managed shellfish-harvesting areas in Tillamook Bay, Oregon (USA). The most influential variables were related to precipitation and river stage height in the wet season and wind and tidal-stage in the dry sea

SUBMITTER: Zimmer-Faust AG 

PROVIDER: S-EPMC6290359 | biostudies-literature | 2018 Dec

REPOSITORIES: biostudies-literature