Using wildlife activity and antibiotic resistance analysis to model bacterial water quality in coastal ponds

Models that help predict fecal coliform bacteria (FCB) levels in environmental waters can be important tools for resource managers. In this study, we used animal activity along with antibiotic resistance analysis (ARA), land cover, and other variables to build models that predict bacteria levels in coastal ponds that discharge into an estuary. Photographic wildlife monitoring was used to estimate terrestrial and aquatic wildlife activity prior to sampling. Increased duck activity was an important predictor of increased FCB in coastal ponds. Terrestrial animals like deer and raccoon, although abundant, were not significant in our model. Various land cover types, rainfall, tide, solar irradiation, air temperature, and season parameters, in combination with duck activity, were significant predictors of increased FCB. It appears that tidal ponds allow for settling of bacteria under most conditions. We propose that these models can be used to test different development styles and wildlife management techniques to reduce bacterial loading into downstream shellfish harvesting and contact recreation areas.

Chemical contaminants in the coral Porites astreoides from southwest Puerto Rico

This report presents an initial characterization of chemical contamination in coral tissues (Porites astreoides) from southwest Puerto Rico. It is the second technical report from a project to characterize chemical contaminants and assess linkages between contamination and coral condition. The first report quantified chemical contaminants in sediments from southwest Puerto Rico. This document summarizes the analysis of nearly 150 chemical contaminants in coral tissues. Although only eight coral samples were collected, some observations can be made on the correlations between observed tissue and sediment contaminant concentrations. The concentrations of polycyclic aromatic hydrocarbons (PAHs), typically associated with petroleum spills and the combustion of fossil fuels, and polychlorinated biphenyls (PCBs) in the coral tissues were comparable to concentrations found in adjacent sediments. However, the concentration of a chemical contaminant (e.g., PAHs) in the coral tissues at a particular site was not a good predictor of what was in the adjacent sediments. In addition, the types of PAHs found in the coral tissues were somewhat different (higher ratios of alkylated PAHs) than in sediments. The levels of PCBs and DDT in coral tissues appeared higher just outside of Guanica Bay, and there was evidence of a downstream concentration gradient for these two contaminant classes. The trace elements copper, zinc and nickel were frequently detected in coral tissues, and the concentration in the corals was usually comparable to that found in adjacent sediments. Chromium was an exception in that it was not detected in any of the coral tissues analyzed. Additional work is needed to assess how spatial patterns in chemical contamination affect coral condition, abundance and distribution.

A statistical model of climates in the southwestern United States

EXTRACT (SEE PDF FOR FULL ABSTRACT): We describe an empirical-statistical model of climates of the southwestern United States. Boundary conditions include sea surface temperatures, atmospheric transmissivity, and topography. Independent variables are derived from the boundary conditions along 1000-km paths of atmospheric circulation. ... Predictor equations are derived over a larger region than the application area to allow for the increased range of paleoclimate. This larger region is delimited by the autocorrelation properties of climatic data.

The influence of seasonal precipitation and temperature variations on runoff in California and southwestern Oregon

EXTRACT (SEE PDF FOR FULL ABSTRACT): There is considerable seasonal-to-interannual variability in the runoff of major watersheds in the Sierra Nevada, Coastal, and Cascade ranges of California and southwestern Oregon. This variability is reflected in both the amount and timing of runoff. This study examines that variability using long historical streamflow records and seasonal mean temperature and precipitation. ... Precipitation is the only significant predictor for both amount and timing of runoff in the low elevation basins. As elevation increases, the models rely more and more on temperature to explain amount and timing of runoff.