A Comparison of Bacterial Indicators and Methods in Rural Surface Waters

The United States Environmental Protection Agency (USEPA) recommends the use of Escherichia coli (E. coli) and enterococci as indicators of enteric pathogens in fresh waters; however, fecal coliform analyses will remain important by virtue of the large amount of historic data collected in prior years. In this study, we attempted, in a real-world situation (i.e., a rural inland watershed in the Piedmont of South Carolina) to compare different bacterial indicators and methods to one another. We compared fecal coliforms, enumerated by membrane filtration with E. coli, enumerated by a commercialized enzyme substrate method and observed E. coli/fecal coliform ratios of 1.63 and 1.2 for two separate tests. In the same watershed, we observed an E. coli/fecal coliform ratio of 0.84 when we used the commercialized enzyme substrate method for both enumerations. Given these results, users of such data should exercise care when they make comparisons between historic membrane filtration data and data acquired through the use of the more modern enzymatic methods. Some sampling and side-by-side testing between methods in a specific watershed may be prudent before any conversion factors between old and new datasets are applied.     

Mapping the Spatial Variability of Plant Diversity in a Tropical Forest: Comparison of Spatial Interpolation Methods

Knowledge of the spatial distribution of plant species is essential to conservation and forest managers in order to identify high priority areas such as vulnerable species and habitats, and designate areas for reserves, refuges and other protected areas. A reliable map of the diversity of plant species over the landscape is an invaluable tool for such purposes. In this study, the number of species, the exponent Shannon and the reciprocal Simpson indices, calculated from 141 quadrat sites sampled in a tropical forest were used to compare the performance of several spatial interpolation techniques used to prepare a map of plant diversity, starting from sample (point) data over the landscape. Means of mapped classes, inverse distance functions, kriging and co-kriging, both, applied over the entire studied landscape and also applied within vegetation classes, were the procedures compared. Significant differences in plant diversity indices between classes demonstrated the usefulness of boundaries between vegetation types, mapped through satellite image classification, in stratifying the variability of plant diversity over the landscape. These mapped classes, improved the accuracy of the interpolation methods when they were used as prior information for stratification of the area. Spatial interpolation by co-kriging performed among the poorest interpolators due to the poor correlation between the plant diversity variables and vegetation indices computed by remote sensing and used as covariables. This indicated that the latter are not suitable covariates of plant diversity indices. Finally, a within-class kriging interpolator yielded the most accurate estimates of plant diversity values. This interpolator not only provided the most accurate estimates by accounting for the indices' intra-class variability, but also provided additional useful interpretations of the structure of spatial variability of diversity values through the interpretation of their semi-variograms. This additional role was found very useful in aiding decisions in conservation planning.