Summary

Description

This project facilitated a partnership between USFWS efforts to document the botanical resources of Chisik Island and establish an analytical chemistry baseline in local lichenmoss communities for future reference and BEST Program efforts to identify potential methods for monitoring the presence and effects of airborne contaminants. In addition, a comprehensive soil and vegetation inventory of Chisik Island was performed in cooperation with the USDAs Natural Resources Conservation Service, U.S. Geological Survey and USFWS. Semipermeable membrane device data demonstrate their utility to sequester airborne anthropogenic contaminants. Further, the SPMDs were successfully used to define the absence of detectable airborne contaminants on Chisik Island and the presence of typical anthropogenic contaminants in the air at the Anchorage site. Thus, the SPMD technique can be employed in ambient air monitoring activities. Further research is required to develop algorithms necessary to estimate actual air concentrations. This research would involve controlling laboratory studies to define the kinetics of uptake of contaminants by SPMDs; additional field deployment of the SPMDs. The lichenmoss analytical data and soil chemistry profiles provide a valuable baseline for future comparisons. When sufficient data is available, this baseline data can be compared with more current data to determine whether correlations exist between data patterns and nonpollution physical and biological factors. Such correlations may provide a basis for determining to what extent these factors i.e. elemental content and soil chemistry influence lichen species diversity, distribution and abundance. Regression analyses might be used for studying trends over time and space. If the appropriate experimental design is used and the statistical assumptions are met, various parametric or nonparametric univariate approaches may be useful as well. The ultimate challenge for the BEST Program in establishing an air quality monitoring component is developing the capability to economically collect and interpret site characterization data and distinguish data patterns that can be attributed to airborne contaminants.