AN EVALUATION OF HEAVY METAL CONCENTRATIONS IN POND SEDIMENTS ON THE OZARK – ST. FRANCIS NATIONAL FORESTS

Federal land managers face a variety of challenges while managing the environmental impacts of various land uses. Informed decision-making requires empirically based, locally relevant resource information set in the context of natural background conditions and regulatory limitations. Monitoring is often a component of adaptive management used to evaluate decision results, define impacts, measure progress, provide accountability, and feeds into new decisions.

This study is an investigation into the heavy metal concentrations found in pond sediments on the Ozark-St. Francis National Forests. Sediment from 14 sites was sampled and analyzed for 27 constituents, which included 18 elemental heavy metals. Ten pond sites (with controls) and four unique environmental settings were chosen to provide a representation of sediment chemistry in wildlife ponds, natural gas well developments and background conditions. Heavy metal analysis utilized accepted standard methodology, a total digestion of the sample was followed with measurements conducted using an ICP-AES protocol (SM 3120 B). The results from this analysis are summarized and compared to local values derived from the National Geochemical Survey conducted by the USGS (USGS Open-File Report 2004-1001).

Two statistical tests were conducted to evaluate the results. The sample sites were compared to control samples using a paired t-test. This resulted in the identification of four statistically significant constituents for distinguishing between pond sediments and their terrestrial controls (No3, Co, Cu, and Zn). A second analysis compared the constituents found in ponds that were classified by land use. This analysis identified four statistically significant constituents for distinguishing between sites where gas development activities occurred and sites where it did not (No3, CA, Cr, and Na).

This investigation will provide the empirically based, locally relevant information decision makers need to make informed land management decisions. This investigation also fills a data gap in the understanding of heavy metal background concentrations at the local level. The results will be used to develop decision support systems