Response of Fish and Macroinvertebrate [PDF]

Jason G. Freund Æ J. Todd Petty ... J. T. Petty. West Virginia University, Division of Forestry and Natural ... drainag

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Environ Manage (2007) 39:707-720 DOI 10.1007/s00267-005-0116-3

E NV I R O N M E N T A L A S S E S S M E N T

Response of Fish and Macroinvertebrate Bioassessment Indices to Water Chemistry in a Mined Appalachian Watershed Jason G. Freund Æ J. Todd Petty

Received: 18 April 2005 / Accepted: 24 October 2006  Springer Science+Business Media, LLC 2007

Abstract Multimetric indices based on fish and benthic macroinvertebrate assemblages are commonly used to assess the biological integrity of aquatic ecosystems. However, their response to specific stressors is rarely known. We quantified the response of a fish-based index (Mid-Atlantic Highlands Index of Biotic Integrity, MAH-IBI) and a benthic invertebratebased index (West Virginia Stream Condition Index, WV-SCI) to acid mine drainage (AMD)-related stressors in 46 stream sites within the Cheat River watershed, West Virginia. We also identified specific stressor concentrations at which biological impairment was always or never observed. Water chemistry was extremely variable among tributaries of the Cheat River, and the WV-SCI was highly responsive across a range of AMD stressor levels. Furthermore, impairment to macroinvertebrate communities was observed at relatively low stressor concentrations, especially when compared to state water quality standards. In contrast to the WV-SCI, we found that the MAH-IBI was significantly less responsive to local water quality conditions. Low fish diversity was observed in several streams that possessed relatively good water quality. This pattern was especially pronounced in highly degraded subwatersheds, suggesting that regional conditions may have a strong influence on fish assemblages J. G. Freund (&)  J. T. Petty West Virginia University, Division of Forestry and Natural Resources, Morgantown, WV 26506-6125, USA e-mail: [email protected] Present Address: J. G. Freund Carroll College, Environmental Science Program, 100 N. East Ave., Waukesha, WI 53186, USA

in this system. Our results indicate that biomonitoring programs in mined watersheds should include both benthic invertebrates, which are consistent indicators of local conditions, and fishes, which may be indicators of regional conditions. In addition, remediation programs must address the full suite of chemical constituents in AMD and focus on improving linkages among streams within drainage networks to ensure recovery of invertebrate and fish assemblages. Future research should identify the precise chemical conditions necessary to maintain biological integrity in mined Appalachian watersheds. Keywords Acid Mine Drainage (AMD)  Appalachian streams  Bioassessment  Index of Biotic Integrity (IBI)  Local vs. regional impacts  Mining impacts  Stream Condition Index (SCI)

Introduction Both benthic macroinvertebrate and fish assemblages are commonly used as bioindicators in state and federal aquatic monitoring programs (Barbour and others 1999). Multimetric indices are widely used by regulatory agencies to estimate current biotic conditions, to determine biotic assemblage response to environmental stressors, to assist in regulatory decision making, and for the long-term monitoring of aquatic ecosystems. These indices have several important values. They can be refined to meet local conditions and stressors (e.g., Shields and others 1995; Lyons and others 1996), their protocols provide standardized data collection and analysis (Barbour and others 1999; Yoder and Smith 1999), and they are easily adapted

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to meet regulatory and monitoring program needs (Yoder and Smith 1999). Both macroinvertebrate and fish assemblages have been shown to be responsive to variability in physical habitat (Shields and others 1995; Snyder and others 2003; Pirhalla 2004) and water chemistry (Wallace and others 1996; Snyder and others 2003). The ability of benthic macroinvertebrate and fish multimetric indices to respond to physical and chemical conditions is paramount to their utility as diagnostic and regulatory tools (Karr 1981). It is often argued that macroinvertebrates are good indicators of local conditions because they are diverse and display a wide range of tolerance to physical and chemical stressors (Hilsenhoff 1982; Barbour and others 1999; Sloane and Norris 2003). Also, benthic macroinvertebrates are represented by a great diversity of species within functional feeding groups (Barbour and others 1999; Mebane 2001). Because most fishes are highly mobile and tend to be longer lived than most macroinvertebrates, they may be better indicators of historic and chronic stressors, the effects of aquatic habitat fragmentation, and stressors that have regional and local impacts (Karr 1981; Barbour and others 1999; Townsend and others 2003). The West Virginia Stream Condition Index (WVSCI) and the Mid-Atlantic Highland Index of Biotic Integrity (MAH-IBI) were developed to assess biotic conditions in West Virginia watersheds. The West Virginia Division of Environmental Protection (WVDEP) uses the West Virginia Stream Condition Index (Tetra Tech 2000) based on macroinvertebrate assemblages in the agency’s Clean Water Act mandated watershed assessments (e.g., WVDEP 1996). The United States Environmental Protection Agency (US EPA) developed a fish-based index of biotic integrity as part of the Mid-Atlantic Highlands Assessment (MAHA) that included the entire state of West Virginia (McCormick and others 2001). Although multiple anthropogenic stressors impact most watersheds (Karr 1981; Barbour and others 1996), mining-related discharge can overwhelm other impacts (WVDEP 1996; Sloane and Norris 2003; Petty and Barker 2004). Pyrite-rich coal fields in the Appalachians produce acid mine drainage (AMD), a chemical mixture that is typified by elevated heavy metal and sulfate concentrations and low pH, alkalinity, and hardness (WVDEP 1996; Williams and others 1999; Petty and Barker 2004). Elevated trace metal concentrations can greatly affect macroinvertebrate (WVDEP 1996; Sloane and Norris 2003) and fish (Woodward and others 1997; Maret and MacCoy 2002) assemblages. Streams that are moderately

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impacted by AMD are defined herein as streams where water chemistry is temporally variable and receives pulses of trace metals (Petty and Barker 2004). Acid mine drainage also reduces stream acid neutralizing capacity thereby increasing the stream’s susceptibility to acid deposition (Pinder and Morgan 1995; Welsh and Perry 1997). Despite a basic understanding of the chemical characteristics of AMD impacted streams, fish and invertebrate response to AMD impairment is less certain. Specific levels of AMD that cause ecological impairment in streams also are unknown. To address these shortcomings we: (1) quantified the response of multimetric scores to water and habitat quality in an intensively mined watershed, (2) determined the extent to which fish- and macroinvertebrate-based indices and a combined index differ in their response to AMD-related stressors, and (3) identified specific AMD stressor levels related to ecological impairment in streams of the Cheat River watershed. To meet these objectives, we followed bioassessment procedures as developed and implemented by WVDEP and USEPA.

Methods The Cheat River watershed is a major tributary to the Monongahela River and drains an area of 3,678 km2 in northeastern West Virginia (WVDEP 1996) (Fig. 1). The Cheat River is formed by the confluence of the Black and Shavers Forks and flows approximately 100 km until the river is impounded by the Lake Lynn dam near the West Virginia–Pennsylvania border. Tributaries to the Cheat River vary greatly in water and habitat quality, predominantly as a result of acidic drainage from underground and surface mines (Petty and Barker 2004). Approximately 43 km downstream of the river’s origin, the Cheat River receives several important sources of acid mine drainage. This point effectively separates the upper and lower Cheat River basins. Both upper and lower basins are dominated by sandstone and shale geology with limited outcrops of Greenbrier limestone. The lower basin, however, possesses extensive coal deposits. Principal mined seams include the Upper and Lower Freeport and Bakerstown, all of which have high pyrite coal. In contrast, the upper basin possesses few coal deposits and none of them have been mined extensively (Cardwell and others 1968). Forty-six sites within the Cheat River watershed were selected across a range of stream size, geology, position within a drainage network, and mining inten-

Environ Manage (2007) 39:707–720

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Fig. 1 The position of the Cheat River watershed relative to West Virginia, including sample site locations included in analysis and known water quality impairment prior to the initiation of our study from water quality data collected by the WVDEP

sity. Water quality impairment in the Cheat River basin is dominated by AMD (WVDEP 1996; Petty and Barker 2004), but potentially includes other anthropogenic stressors such as acid precipitation, agriculture, and urban and residential development. Studied streams ranged in size from 3 to 141 km2 drainage area. Levels of mining activity affecting study streams ranged from no mining within the basin to more than half of the drainage basin area having been mined (Petty et al., unpublished data). At a subset of the study sites (n = 39), we sampled water chemistry monthly over the period of March 31, 2002–April 24, 2003. Water quality from all 46 study locations was quantified from a single visit in April 2003. Depending on the objective being addressed, we used either the mean water chemistry from the 39 intensively sampled sites or the water chemistry observed in the April 2003 site visit. Previous analyses of these data (Petty and Barker 2004) indicated that the Spring 2003 sample provided a good relative measure of water quality at each of the sites for two reasons: (1) most streams in this watershed experienced their worst conditions during baseflow conditions in early spring, and (2) despite significant seasonal variability in water chemistry, general water quality conditions were remarkably constant from year to year, especially when comparing early spring samples. For example, specific conductance among the 39 study sites sampled in spring 2002 and 2003 had a correlation coefficient (r) equal to 0.97. Similarly, high correlations for other chemical constituents were

observed as well. Consequently, we are confident that the spring 2003 sample is indicative of variation in water quality conditions among the 46 study locations over the period of Spring 2002–2003. During site visits temperature (C), pH, specific conductance (lS/cm3), dissolved oxygen (mg/l), and total dissolved solids (mg/l) were measured instream using a YSI 650 with a 600 XL sonde (Yellow Springs, OH). A 500-ml water sample was filtered (mixed cellulose ester membrane with 0.45-lm pore size) immediately and treated with 5 ml 1:1 nitric acid. Filtered samples were used for quantifying concentrations of total dissolved aluminum, iron, manganese, nickel, cadmium, chromium, and calcium and total hardness (all in units of mg/l). A 1-liter grab sample also was collected for analysis of alkalinity (mg/l CaCO3 equivalents), acidity (mg/l CaCO3), and sulfate concentration (mg/l SO4). Unfiltered samples were kept on ice after collection and stored in the laboratory at 4C until analyses could be completed. All laboratory analyses were conducted at Black Rock Test Lab in Morgantown, WV, and followed USEPA standard analysis protocols (Clesceri and others 1992). Rapid visual habitat assessment (RVHA) data were collected at each site following USEPA protocols (Barbour and others 1999) and used to quantify relative habitat quality. Two observers trained in RVHA estimated these parameters to maximize repeatability and reduce errors in the data (Roper and Scharnecchia 1995). RVHA percent score was used for all statistical analyses.

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To quantify ecological condition at each site on the basis of macroinvertebrate assemblages, we used the WV-SCI. We used our own data (39 sites) collected in spring 2003 immediately after water chemistry sampling along with unpublished WV-SCI scores obtained from the WVDEP samples collected in 2001 and 2002. As with the water chemistry data, the correlation between WV-SCI estimates obtained in 2002 and 2003 at the same sites was extremely high (r = 0.85), indicating that benthic assemblages were relatively constant from year to year over the study period. Consequently, data collected across the 2001–2003 period were combined for analysis unless otherwise noted. All sampling of benthic invertebrate communities used a modified version of the USEPA Rapid Bioassessment protocols (Barbour and others 1999). Macroinvertebrates were collected from three riffle habitats using a rectangular dipnet with an opening of 0.5 m in larger streams or a D-frame dipnet with an opening of 0.33 m in smaller streams; both nets have 500-lm mesh netting. In larger streams, samples from four representative riffles were collected. In each case, the total sample area = 1.0 m2 and samples from representative riffles were combined into a single sample to represent the site. Two hundred macroinvertebrates were selected from each composite sample by picking macroinvertebrates from randomly selected grid cells (WVDEP 2003). Macroinvertebrates were identified by trained biologists to family or the lowest practical taxomonic level (WVDEP 2003). The WV-SCI (Tetra Tech 2000) is a composite of six individual metrics, including macroinvertebrate taxon richness; Ephemeroptera (E), Plecoptera (P), and Trichoptera (T) richness; percent of all individuals members of EPT; percent tolerant (of all individuals); percent dominance; and a modified Hilsenhoff biotic index (HBI, Hilsenhoff 1988). The final WV-SCI score is scaled to vary from 0 to 100, where streams with a score of 100 are 100% similar to the highest quality reference streams in the state (Tetra Tech 2000). We used the MAH-IBI to quantify fish assemblage structure (McCormick and others 2001). All fish sampling was conducted by our lab members in late summer 2002 and 2003, and sampling protocols were similar to those outlined by McCormick and others (2001). A subset of the 46 sites (n = 9) was sampled in both years to assess year-to-year variability in fish assemblage structure. Analyses of these data indicated that MAH-IBI scores were consistent (r = 0.95) over time, and thus all sites were combined for analysis. Study reaches for fish sampling were 40 times the mean stream width (MSW) or a minimum of 150 m and

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a maximum of 300 m in length (Lyons 1992; Yoder and Smith 1999). This distance has been found to be sufficient for comparing relative biological conditions through IBI scores or estimating relative species richness (Ohio EPA 1989; Maret and Ott 2004; Freund, unpublished data). Prior to sampling, upstream and downstream reach boundaries were blocked with a large net if a natural barrier did not exist. To capture fishes, we used one to three backpack electrofishing units (Smith Root models 12-B, 15-D, and/or LR-24), depending on the size of the stream, along with a seine and dip nets. We identified all captured individuals to species and returned non-vouchered fishes to the stream after completion of the sample site. Voucher specimens of each species were collected and preserved in a 10% buffered formalin solution or 95% ethyl alcohol. Specimens were verified by biologist at West Virginia University and the West Virginia Division of Natural Resources. We calculated an MAH-IBI score for each site according to McCormick and others (2001) with metric scoring equations provided by the United States Environmental Protection Agency (Alan Herlihy, personal communication). Important metrics in the MAHIBI include: number of native cyprinid species, number of native benthic species, proportion of individuals in the family Cottidae, sensitive species richness, proportion of tolerant individuals, proportion of non-indigenous individuals, proportion of invertivore-piscivore individuals, proportion of macro-omnivores, and proportion of (clean) gravel spawning species (McCormick and others 2001). Statistical Analysis WV-SCI and MAH-IBI scores were scaled relative to the highest scores observed in the watershed (henceforth WV-SCI* and MAH-IBI*, respectively). Scaling constrained both scores (WV-SCI and MAH-IBI) to a similar range of values (0–100) that facilitated direct statistical comparisons between the two indices. Analyses that were conducted independently or referred to WVDEP and USEPA condition categories used unscaled data. We then constructed an additional condition index that combined the WV-SCI* and MAHIBI* scores into a single index (henceforth referred to as SCI*+IBI*) by taking the average of the WV-SCI* and MAH-IBI* scores. Proportion data were arc sine square root transformed, and water chemistry values other than pH were natural log transformed to approximate normality before inclusion in statistical analyses (Zar 1999). In addition, both WV-SCI and MAH-IBI scores were

Environ Manage (2007) 39:707–720

used to classify all streams into ecological condition categories (Excellent, Good, Fair, and Poor) as defined by the WVDEP (1996), and McCormick and others (2001), respectively. Following WV-DEP procedures, excellent and good were considered unimpaired whereas fair and poor were considered impaired (WV-SCI score dv – 0.045 >dv – 0.074 0.01 – 58.6 >dv – 7.38 0.001 – 0.25 2.7 – 8.4 31 – 2390

59.6 27.0

212 229

5.9 – 670.0 0 – 348

41.7

144

7.3 – 379

76 N/A N/A 50 72 61

19 N/A N/A 55 26 36

38 – 98 –0.73 – 4.16 –1.87 – 2.98 0 – 84 14 – 93 7 – 85

Values below detection values are designated as ‘‘>dv’’. Mean and CV are not given for standardized principle component factor scores, which by definition mean = 0, standard deviation = 1. Sample size (n) = 46 for all measures except RVHA % Score where n = 41

ing concentrations of AMD constituents, and negative scores characterized streams with higher pH and alkalinity (Table 2). The second principal component (PC 2) represented a hardness and alkalinity gradient: positive factor scores represented sites with relatively high pH, alkalinity, calcium, and total hardness, whereas negative scores characterized areas of decreasing alkalinity and pH (Table 2). The third axis represented a gradient in cadmium and chromium, which were two trace metals that did not load significantly in PC 1 (i.e., factor loading scores |0.4| are presented. Units of measurement are presented in Table 1. Factor loadings of

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