# Presentation: 037873

## Revisiting The Analysis of the Condition Of Streams In The Primary Region Of Mountaintop Mining/Valley Fill (MTM/VF) Coal Mining

- <date/time>

**Revisiting The Analysis of the Condition Of Streams In The Primary Region Of Mountaintop Mining/Valley Fill (MTM/VF) Coal Mining**

**G. Pond and  M. Passmore (USEPA Region 3)**

**BACKGROUND**
- In 1999 and 2000, EPA R3 characterized and compared the ecological condition of unmined, valley-filled, mined, residential and filled-residential streams in the MTM/VF coal fields of southern WV for a programmatic EIS using a family-level Stream Condition Index (WVSCI).  Since that time, EPA has worked with WVDEP to develop a genus-level index (GLIMPSS).
- The vouchered EIS macroinvertebrate samples were re-identified to genus level and reanalyzed using the GLIMPSS.  Relationships between the ecological condition and various physical, chemical and watershed characteristics were examined using descriptive and multivariate statistics.  Results are shown here for the filled, mined and unmined sites.  Note that the mined sites have some mining, but no valley fills.  The amount of mining in these watersheds tends to be very small as most large scale surface mining is associated with valley fills.
- The genus-level index offers many refinements over the family-level index, which are summarized in table 1.  These refinements offer a more sensitive, and therefore accurate, characterization of stream condition and causes of impairment.

**MULTIVARIATE ANALYSIS OF TAXANOMIC DATA WITH CHEMICAL AND PHYSICAL HABITAT VARIABLES**
- Principal Components Analysis (PCA) was used to explore the multivariate character of a subset of the water chemistry  variables at the sites.  Water quality variables dominated by non-detects or with little variation were not included in this analysis.  The PCA graph indicates the sites in multidimensional space so that the longest axis (the axis with the most variance) is the first PCA axis, and the second longest axis is the second PCA axis, perpendicular to the first.  The first few PCA axes indicate the greatest amount of variation in the dataset and should contain some significant patterns.  In this case, the first axis explained 71% of the variance in the sites, and the second axis only explained an additional 12% of the variance.  In the EIS dataset, potassium, selenium, sulfate, hardness, alkalinity, conductivity, and sodium all had high positive component loadings on axis 1.  Note that the filled sites are clearly separated from the unmined sites along axis 1.  The mined sites plotted closer to the unmined sites in this multivariate space, indicating their water quality is more similar to the unmined sites.
- Canonical Correspondence Analysis (CCA) was used to relate the biotic variables (genera) to abiotic variables (RBP habitat and median water chemistry values).  This analysis is a multivariate, direct-gradient analysis method.  The axes of the final ordination are restricted to be linear combinations of the environmental variables and the taxa data. In this CCA, the first two axes accounted for 42% of the variation in the data, the first was 26% and the second was 16%.
- The results of the CCA are presented with the environmental variables plotted as arrows and the taxa (called variables) and sites (called cases) plotted as points in 2-dimensional space.  The sites are identified as mined, unmined and filled by symbol.  Each site lies at the centroid of the points for species that occur in those samples.  The arrows indicate the direction of maximum change for that environmental variable and the length of the arrow is proportional to the rate of change. The case (or site) axis scores can be correlated to the original environmental variables to further quantify the relationship between where the site is positioned and the individual variables. In the CCA case diagram, the filled sites clearly contain very different taxa from the unmined sites and the arrows indicate several chemical or habitat variables associated with those taxa differences.  Filled sites tended to have worse water quality and habitat.   In the CCA variable diagram, the taxa associated with those chemical-physical gradients are shown.  The taxa associated with the “filled” space are clearly more tolerant taxa than those occupying the “unmined” space.   This ordination also indicates the lack of mayfly taxa in the space associated with mine effluent or the ‘filled” space.  This space is dominated by tolerant caddisflies *(Hydropsyche *and* Cheumatopsyche*) and midge taxa (e.g. *Cricotopus*)*.*

- These scatter plots show the relationship between the GLIMPSS scores and % mining in the watershed  and field conductivity for the Spring of 2000.  There is a strong and positive correlation between the GLIMPSS scores and % mining and conductivity.  This is similar to what was found with the WVSCI.

- Table 1.  Refinements offered by the genus-leve GLIMPSS