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PARTIAL LEAST SQUARE ANALYSES FOR ASSOCIATION OF LANDSCAPE METRICS WITH WATER BIOLOGICAL AND CHEMICAL PROPERTIES IN THE SAVANNAH RIVER BASIN
Citation:
Nash, M S. AND D J. Chaloud. PARTIAL LEAST SQUARE ANALYSES FOR ASSOCIATION OF LANDSCAPE METRICS WITH WATER BIOLOGICAL AND CHEMICAL PROPERTIES IN THE SAVANNAH RIVER BASIN. Presented at 14th EPA Conference on Statistics and Information, Philadelphia, PA, May 14-17, 2001.
Impact/Purpose:
The primary objectives of this research are to:
Develop methodologies so that landscape indicator values generated from different sensors on different dates (but in the same areas) are comparable; differences in metric values result from landscape changes and not differences in the sensors;
Quantify relationships between landscape metrics generated from wall-to-wall spatial data and (1) specific parameters related to water resource conditions in different environmental settings across the US, including but not limited to nutrients, sediment, and benthic communities, and (2) multi-species habitat suitability;
Develop and validate multivariate models based on quantification studies;
Develop GIS/model assessment protocols and tools to characterize risk of nutrient and sediment TMDL exceedence;
Complete an initial draft (potentially web based) of a national landscape condition assessment.
This research directly supports long-term goals established in ORDs multiyear plans related to GPRA Goal 2 (Water) and GPRA Goal 4 (Healthy Communities and Ecosystems), although funding for this task comes from Goal 4. Relative to the GRPA Goal 2 multiyear plan, this research is intended to "provide tools to assess and diagnose impairment in aquatic systems and the sources of associated stressors." Relative to the Goal 4 Multiyear Plan this research is intended to (1) provide states and tribes with an ability to assess the condition of waterbodies in a scientifically defensible and representative way, while allowing for aggregation and assessment of trends at multiple scales, (2) assist Federal, State and Local managers in diagnosing the probable cause and forecasting future conditions in a scientifically defensible manner to protect and restore ecosystems, and (3) provide Federal, State and Local managers with a scientifically defensible way to assess current and future ecological conditions, and probable causes of impairments, and a way to evaluate alternative future management scenarios.
Description:
Surface water quality is related to conditions in the surrounding geophysical environment, including soils, landcover, and anthropogenic activities. A number of statistical methods may be used to analyze and explore relationships among variables. Single-, multiple- and multivariate regression analyses have been used to relate water nutrient concentrations to selected landscape metries. Partial Least Square (PLS) is a multivariate analysis used to explore relations between two data sets and predict variability for each data set. PLS is a predictive model that can be used for prediction of dependent variables in new locations when the independent variables are measured and especially if they are highly correlated.
In this study, three distinct data sets were used: water chemistry (Chem) from point sites, water biology (Bio) from stream reaches centered around the point sites, and landscape metrics (LS) generated for the drainage areas to the point sites. The landscape-biota model indicated three major contributing variables: the LS variable Slope greater than 3 percent (Slope3), the Bio variable EPT (an indicator of three microinvertebrate genera), and the Bio variable NE-richness (an index of microinvertebrate species richness). Within this model, the LS variable percent of erodible soil was the second highest LS contributor, with a negative relationship to the Bio variables.
The analysis indicated increased slope (indicating complex topography, generally occurring in the mountainous areas of the Savannah River Basin) is associated with increased microinvertebrate quality, while the percentage of watershed with highly erodible soils is associated with declines in aquatic biota quality.