1. 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. 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. CCA variable scores Axis 2 Axis 1 Acentrella Acroneuria Agapetus Ameletus Amphinemura Baetis Bezzia/Palpomyia Cambarus Capniidae Ceratopogonidae Chaetocladius Chelifera Cheumatopsyche Chimarra Chloroperlidae Cinygmula Clinocera Constempellina Cricotopus Diamesa Diplectrona Diploperla Dolichopodidae Dolophilodes Drunella Ectopria Empididae Epeorus Ephemerella Eukiefferiella Gomphidae Haploperla Helichus Hemerodromia Hydropsyche Hydroptila Isoperla Leptophlebiidae Leuctra Micropsectra Neophylax Neozavrelia Oligochaeta Optioservus Orthocladius Oulimnius Parakiefferiella Paraleptophlebia Parametriocnemus Peltoperla Perlidae Perlodidae Plauditus Polycentropus Polypedilum Psephenus Pseudolimnophila Pteronarcys Remenus Rheotanytarsus Rhyacophila Simulium Stempellinella Stilocladius Taeniopteryx Tanytarsus Thienemanniella Thienemannimyia Tipula Tvetenia Yugus Zavrelimyia Epifaunal Substrate Embeddedness Sediment Deposition Total RBP Score ALKALINITY Conductivity pH HARDNESS IRON MANGANESE, DISSOLVED NITRATE+NITRITE POTASSIUM SELENIUM SODIUM SULFATE ZINC Vector scaling: 1.73 CCA case scores Unmined Filled Mined Axis 2 Axis 1 MT02 MT03 MT13 MT39 MT42 MT50 MT51 MT91 MT95 MT103 MT104 MT14 MT15 MT18 MT25B MT32 MT34B MT52 MT60 MT64 MT86 MT87 MT98 MT45 MT79 MT81 Epifaunal Substrate Embeddedness Sediment Deposition Total RBP Score ALKALINITY Conductivity pH HARDNESS IRON MANGANESE, DISSOLVED NITRATE+NITRITE POTASSIUM SELENIUM SODIUM SULFATE ZINC Vector scaling: 2.74 Partial PCA of EPA MTM/VF EIS DATA Unmined Filled Mined Axis 2 Axis 1 -0.03-0.06-0.090.030.060.090.120.15 ALKALINITY CONDUCTIVITY pHHARDNESS, TOTAL IRON, TOTAL MANGANESE, DISS. NITRATE+NITRITE POTASSIUM, TOTAL SELENIUM, TOTAL SODIUM, TOTAL SULFATE ZINC, TOTAL Vector scaling: 0.19 67_69Sp 0102030405060708090100 WVSCI 0 10 20 30 40 50 60 70 80 90 100 GLIMPSS 2030405060708090100 WVSCI 20 30 40 50 60 70 80 90 Unmined Mined Filled 5 th %ile COMPARISON OF GLIMPSS AND WVSCI ASSESSMENTS Although the WVSCI and the GLIMPSS are highly correlated, the WVSCI often fails to detect impairment that the GLIMPSS can detect. The graph on the left indicates all data in WV dataset from the spring/mountain season/region. The graph on the right indicates the EIS Spring 2000 data from the southern coal fields. Sites in the lower right quadrant are rated as not impaired by the WVSCI but impaired by the GLIMPSS. Most of the filled sites that the WVSCI indicated as not impaired were impaired using the GLIMPSS. FilledMinedUnmined 15 20 25 30 35 40 45 # TOTAL TAXA FilledMinedUnmined 0 5 10 15 20 25 # INTOLERANT FilledMinedUnmined 0 2 4 6 8 10 12 # MAYFLY FilledMinedUnmined 0 5 10 15 # STONEFLY FilledMinedUnmined 0 5 10 15 20 # CLINGER FilledMinedUnmined 2 3 4 5 6 7 HBI FilledMinedUnmined 0 10 20 30 40 50 60 70 % ORTHOCLAD FilledMinedUnmined 20 30 40 50 60 70 % 5 DOMINANT FilledMinedUnmined 0 10 20 30 40 50 % MAYFLIES-Baetis COMPONENT METRICS OF THE GLIMPSS FOR THE MTM/VF REGION The genus-level data allows much better resolution of tolerant and intolerant taxa and habit designations (e.g. % clinger) than the family level data. At the family level, several genera may be present, and if those genera vary in terms of tolerance or habit, the family level tolerance ratings may not represent the true tolerance of the actual taxa that are present. The genus level data also offer more range in the taxa richness measures than the family level data. Some of the metrics don’t change from family to genus level (e.g. % mayflies). The graphs below indicate the values of the component metrics of the GLIMPSS for the Spring 2000 EIS data. Note that there is excellent discrimination between the filled and unmined sites for all metrics except the # of stonefly taxa. Stonefly taxa appear to be more tolerant to the alkaline mine drainage. CONCLUSIONS The genus level index (GLIMPSS) indicates similar patterns to the family level index (WVSCI), except that the more sensitive and accurate genus-level index indicates more of the filled sites are impaired. Note that during the EIS, one of the criticisms was that the family level index may not give an accurate protrayal of the condition of filled sites. This analysis indicates the WVSCI painted a more optimistic picture of ecological conditions in filled streams. The multivariate analysis indicates that the patterns in the raw taxa data are best explained by a subset of the water quality and habitat parameters. The water quality parameters are all associated with coal mining. This analysis supports further research on the effects of total dissolved solids (conductivity and associated ions) and selenium. Selenium was the only parameter in the EIS to exceed numeric water quality criteria. The other parameters of concern do not have numeric water quality criteria for aquatic life. 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). 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). ABIOTIC CHARACTERISTICS AND CORRELATIONS WITH GLIMPSS FilledMinedUnmined 130 140 150 160 170 TOTAL RBP SCORE FilledMinedUnmined 0 500 1000 1500 SP COND FilledMinedUnmined 0 10 2020 30 40 50 60 70 % Mining FilledMinedUnmined 20 30 40 50 60 70 80 90 GLIMPSS 050010001500 SP COND 20 30 40 50 60 70 80 90 GLIMPSS Unmined Mined Filled 010203040506070 % Mining 20 30 40 50 60 70 80 90 GLIMPSS These box and whisker plots indicate the distribution of total RBP habitat scores, conductivity, % mining in the watershed and GLIMPSS scores. The mined and unmined sites tended to have better physical habitat and better water quality than the filled sites. The mined sites (some surface mining but no valley fills) tended to have very small amounts of mining in their watersheds. Most large scale surface mining is associated with valley fills in this region. 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