A Biotic Index for the Southeastern United States: Derivation and List of Tolerance Values, with Criteria for Assigning Water-Quality Ratings Author(s): David

A Biotic Index for the Southeastern United States: Derivation and List of Tolerance Values,with Criteria for Assigning Water-Quality RatingsAuthor(s): David R. LenatSource: Journal of the North American Benthological Society, Vol. 12, No. 3 (Sep., 1993), pp.279-290Published by: Society for Freshwater ScienceStable URL: http://www.jstor.org/stable/1467463 .

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J. N. Am. Benthol. Soc., 1993, 12(3):279-290 ? 1993 by The North American Benthological Society

A biotic index for the southeastern United States: derivation and list of tolerance values, with criteria for assigning

water-quality ratings

DAVID R. LENAT

North Carolina Division of Environmental Management, Water Quality Section, 4401 Reedy Creek Road, Raleigh, North Carolina 27607 USA

Abstract. North Carolina's Division of Environmental Management has a large number of semiquantitative stream macroinvertebrate collections that have been assigned water-quality ratings. These semiquantitative data use abundance values of Rare = 1, Common = 3, and Abundant = 10, allowing the calculation of mean abundance (range = 0-10) for each taxon across five water-quality classes. This information was used to derive tolerance values and classification criteria for a southeastern biotic index. Classification criteria were adjusted for both season and ecoregion, but no corrections were required for stream size. Tolerance values are listed for >500 North Carolina taxa, and are compared with a similar Wisconsin data base.

Key words: biotic index, benthic macroinvertebrates, streams, water quality, pollution, biological monitoring, North Carolina.

Benthic macroinvertebrates are often collected to help evaluate water quality and/or habitat

quality. This task involves collection of repre- sentative samples, accurate taxonomy, and some

system to convert invertebrate data into water-

quality ratings. North American stream ecolo-

gists have struggled to establish such ratings for over 50 years, and a bewildering array of methods have been proposed (Cairns and Pratt

1993). Currently, more than one type of data

summary (metric) is often used to summarize invertebrate data, with a final evaluation of water quality based on several independent methods. Many of the proposed metrics, however, are applicable only to a particular type of collection, a single habitat, or a single geographic area.

The most widely used metrics are taxa richness and "biotic indices". Taxa richness is as- sumed to be inversely related to the degree of stress, whereas biotic indices attempt to summarize information on the tolerance of the macroinvertebrate community. The North Carolina

(NC) Division of Environmental Management (DEM) uses taxa richness of the most intolerant invertebrate groups (Ephemeroptera + Plecop- tera + Trichoptera, or "EPT") and a biotic index similar to that of Hilsenhoff (1987). Both metrics are weighted equally in assigning water-quality ratings (NC DEM 1992). We have invested substantial efforts in testing and evaluating both methods, both in deriving criteria and in making adjustments for the effects of ecoregions,

stream size, and season. The EPT taxa richness criteria have been in use for many years, but we have only recently derived biotic index criteria. This paper describes the method used to

produce the North Carolina Biotic Index (NCBI) and gives tolerance values for taxa in southeastern USA. The emphasis was on the objective derivation of tolerance values, because other

investigators have already demonstrated the

utility and accuracy of a biotic index (Chutter 1972, Hilsenhoff 1982, 1987, 1988, Narf et al. 1984, Jones et al. 1981).

The first North Carolina biotic index was es- tablished in 1980, using "expert opinions" to

assign tolerance values for each taxon. Trial values were assigned by NC DEM biologists, and

adjusted following discussion at a meeting of benthic ecologists from North Carolina, South Carolina and Georgia. This index (with poten- tial values ranging from 0-5) was modeled on that of Hilsenhoff (1977), which was, in turn, derived from Chutter's (1972) index:

Sum TV,N, Total N

where TV, is the tolerance value of the ith taxa, N, is the abundance of the ith taxa, and Total N is the number of individuals in the sample. Total N may be based on either actual densities (No./m2, etc.) or abundance categories (see Methods).

Ideally, such an index would be used to target specific kinds of stress. For example, a species

279



D. R. LENAT

might be sensitive to metal toxicity, but tolerant of low dissolved oxygen. Rather than a single index, an array of indices would be used to assess water quality and/or habitat quality. Un-

fortunately, this level of information for species tolerance is not available. Dr. Hilsenhoff tar-

geted his index at organic pollution, although it is used by other investigators to look at many other kinds of stress. The NCBI is intended for examination of the general level of pollution, regardless of source.

The utility and accuracy of such an index is

only as good as the system used to derive the tolerance values. The use of expert opinion values proved to be unreliable in North Carolina, as biotic index ratings frequently conflicted with

ratings from EPT taxa richness values or ratings based on professional judgment. Unbiased as-

signment of tolerance values requires a large number of invertebrate collections that have

already received some kind of water-quality rat-

ing. To my knowledge, only Hilsenhoff (1987) has used such a method to derive tolerance values. Other lists of invertebrate tolerance in use within the United States are modifications of Hilsenhoff's list with "expert opinion" modifications for taxa not found in Wisconsin. North Carolina biologists saw a need for indepen- dently deriving tolerance values for southeastern species, as well as deriving criteria for biotic index values that could be adjusted for differences in ecoregion, season, and stream size.

Methods

The NC DEM has a data set of >2000 macroinvertebrate stream samples collected during water-quality surveys between 1983 and 1992. These samples have been assigned to five water-

quality categories (bioclassifications): Poor (n =

299), Fair (n = 392), Good-Fair (n = 481), Good

(n = 492), and Excellent (n = 424); they include both standardized qualitative samples (Lenat 1988) and collections limited to Ephemeroptera, Plecoptera, and Trichoptera (Eaton and Lenat 1991). Classification is based on EPT taxa richness and an earlier version of the NCBI.

A variety of information is associated with each sample, including ecoregion, date, and stream size. The abundance information for each taxon is semiquantitative, being tabulated as either Rare (1-2/sample), Common (3-9/sample) or Abundant (>10/sample), and it is coded in

the computer system, respectively, as 1, 3 or 10. Calculations of mean abundance for this study also included zero values, since I used all samples in a particular water-quality category, not just samples where this taxon occurred. Similar abundance categories are used with the Chan- dler Score, a European biotic index (Chandler 1970).

The primary measurement used to compute the tolerance value for any taxon was the av-

erage abundance (range = 0-10) in each water-

quality category. I computed how far each taxon

(starting from Excellent) extended into the areas of poorer water quality. The abundance values (by water-quality category) were converted into cumulative percentiles and graphed vs. the wa-

ter-quality score (1 = Excellent, 2 = Good, 3 = Good-Fair, 4 = Fair, 5 = Poor). I tried a 50th percentile, a 75th percentile, and a 90th percentile value; the 75th percentile produced the

greatest separation of intolerant and tolerant species (Table 1), while still leaving the facultative species with values near the midrange. Calculations of such percentiles usually re-

quired the use of simple linear interpolation between categories. For example, the mean abundance data (number per sample, by water-

quality class) for Cricotopus bicinctus in Table 1 is: Excellent (1): 1.0, Good (2): 2.4, Good-Fair (3): 3.1, Fair (4): 4.0, and Poor (5): 3.7. Convert- ing these abundance values to a cumulative per- centage produces: 7.0, 23.9, 45.8, 73.9, 100.0. This indicates that the 75th percentile for the water-

quality score lies between Fair (4) and Poor (5) and yields by interpolation a value of 4.04.

This procedure produced a range of preliminary tolerance values generally between 1.0 and 4.5, but the desired range (to be comparable with Hilsenhoff 1987) was 0-10. If the 1-4.5

range is graphed vs. the 0-10 range (with 1 and 4.5 being the x and y intercepts), a conversion formula for tolerance value (TV) is derived:

Final TV = 2(1.43 x Preliminary TV - 1.43).

The 75th percentile technique was best suited for taxa with substantial amounts of data. If only a few data points were available, then the 75th percentile value often was too high. Review of our data base suggested that the 75th percentile was suitable for taxa with at least 25 observa- tions (out of the 2000 samples). For taxa with

only 10-24 collections, a 50th percentile was used, and the old "expert opinion" values were

280 [Volume 12



A BIOTIC INDEX FOR SOUTHEASTERN USA

TABLE 1. Average abundance values (range = 0-10) by water-quality rating (five categories) of represen- tative taxa, and North Carolina tolerance values (TV) calculated from this information. "+" = <0.1, N = No. of records for taxon.

Water quality and score

Excel- lent Good G-F Fair Poor

1 2 3 4 5 N NC TV

Group 1: Intolerant

Drunella wayah Rhithrogena spp. Chimarra spp. Micrasema wataga Goera spp. Brachycentrus spinae Pteronarcys dorsata Acroneuria abnormis

Mean TV (?1 SD)

Group 2: Facultative

Stenonema modestum

Ephemerella catawba gr. Eurylophella temporalis Cheumatopsyche spp. Hydropsyche venularis Perlesta placida Ancyronyx variegata Polypedilum convictum

Mean TV (?1 SD)

Group 3: Tolerant

Cricotopus bicinctus C. tremulus gr. Chironomus spp. Polypedilum illinoense

Physella spp. Argia spp. Limnodrilus hoffmeisteri Asellus spp.

Mean TV (?1 SD)

0.4 0.7 2.7 0.8 0.6 0.8 0.8 6.2

6.6 3.8 1.6 5.5 1.8 1.5 1.2 2.3

1.0 0.3 0.6 1.4 0.8 1.7 0.6 0.5

0.1 0.2 2.9 0.8 0.2 0.1 0.7 4.6

8.1 1.9 1.5 6.9 2.7 1.9 2.3 3.1

2.4 0.6 1.0 2.8 2.0 2.7 0.9 0.6

+ 0.1 1.4 0.5 + +

0.1 1.7

8.2 1.7 1.2 7.1 2.4 1.8 2.8 3.0

3.1 1.1 1.5 2.9 2.3 3.3 1.3 1.2

+

0.4 0.1 + + +

0.4

6.9 0.7 0.6 6.6 1.5 1.1 2.5 1.8

4.0 1.3 3.1 3.9 3.5 4.0 2.3 1.4

- 51 - 155

+ 650 + 280

- 172 + 73

186 + 1031

1.1 0.4 0.2 2.5 0.3 + 1.0 0.4

3.7 1.4 5.0 5.2 3.8 4.1 4.0 2.0

1660 550 518

1680 656 524 726 622

744 279 711 932 825 914 561 390

0.0 0.4 2.8 3.2 0.4 0.0 1.8 2.2

1.4 (+1.3)

5.8 4.0 4.6 6.6 5.4 5.0 7.0 5.2

5.4 (?1.0)

8.8 9.0 9.8 9.2 9.0 8.6 9.8 9.4

9.2 (?0.4)

used for taxa with <10 records. This system is designed to be compatible with existing biotic indices currently in use for the southeastern United States.

Average biotic index values were calculated for all standardized qualitative samples, and analysis of variance methods (two-way and three-way ANOVA) were used to examine the effects of three ecoregions (Mountain, Pied- mont, Coastal Plain), four seasons, four stream width categories (1-2 m, 3-7 m, 8-20 m, >20 m) and five water-quality ratings (Excellent, Good, Good-Fair, Fair, Poor). Seasons were de- fined as Summer: June-August; Fall: Septem-

ber-November; Winter: December-February; and Spring: March-May.

For the ANOVA calculations, the water-quality rating again used a score from 1-5. There were few differences between biotic index values for flowing streams in the Piedmont and Coastal Plain ecoregions, so these two areas were combined in subsequent calculations. After making seasonal corrections (see Results), the prior water-quality ratings were then used to derive classification criteria for the NCBI. For initial tests of tolerance values, 24 taxa were chosen that could be roughly divided into In- tolerant, Facultative, or Tolerant categories.

1993] 281



D. R. LENAT

TABLE 2. Seasonally correcteda average NCBI by ecoregion and water-quality rating, with ANOVA results.

Water-quality rating

Excel- Good- Ecoregion lent Good Fair Fair Poor

Mountain 3.78 4.58 5.52 6.32 7.80 Piedmont/Coastal 5.02 5.65 6.26 7.09 8.32

Two-way ANOVA Mean

Source df square F-value

Ecoregion 2 88.5 307.8

Water-quality score 4 265.8 924.0

Ecoregion x score 8 2.4 8.5 Residual 1467 0.2 -

a For mountain streams: 0.5 added to winter/spring collections, 0.4 added to fall collections. For Pied- mont/Coastal streams: 0.2 added to winter/spring collections.

These a priori choices were based on professional judgment and were intended to be non- controversial, but I included taxa known to be tolerant of both organic and toxic materials.

Results

For the 24 taxa chosen for initial testing, the distribution of average abundance values across five water-quality categories always produced unimodal patterns, and confirmed the initial

assignment of these taxa as intolerant, facultative, and tolerant (Table 1). The calculation of tolerance values (using the 75th percentile) produced low values for the intolerant group (mean = 1.4), high values for tolerant taxa (mean =

9.2), and intermediate values for the facultative

group (mean = 5.4). Appendix 1 is a complete list of tolerance

values for North Carolina stream invertebrates. Nomenclature generally follows that of Brig- ham et al. (1982). Comparable values from a Wisconsin data base (Hilsenhoff 1987) also have been listed. Some taxa have not been included in this list, either because we have insufficient data to calculate a tolerance value (<10 collections), or because a taxon can only be identified with unpublished keys for particular North Carolina taxa.

Two-way ANOVA showed that differences in season significantly affected biotic index values

for each ecoregion in North Carolina. I made tables for biotic index values vs. season for each of the ecoregions, and attempted simple additive corrections that would equalize the average NCBI values for all seasons. Fall, winter, and spring values were corrected to the average summer value. The following system proved satisfactory. For the Mountain ecoregion, 0.4 was added to the fall (September-November) biotic index, and 0.5 was added to the spring/ winter (December-May) biotic index. For the Piedmont/Coastal Plain ecoregions, 0.2 was added to the spring/winter biotic index. After making these corrections to the NCBI, season could be eliminated as a significant variable when the effects of season and water-quality class were examined within specific ecoregions (p = 0.29 for Mountain ecoregion, p = 0.36 for Piedmont/Coastal Plain).

Three-way ANOVA examining the effects of stream width, ecoregion, and water-quality class on NCBI values (seasonally corrected) indicated that all three factors significantly affected biotic index values (p = 0.001), but that width effects were very small (F = 6.8), relative to Ecoregion (F = 228.4) and Water-quality Score (F = 831.4). Criteria for each water-quality class were then derived using mean values (Table 2) as the mid- point for each class. This procedure showed that NCBI values for Piedmont/Coastal streams were almost one unit higher than for Mountain streams of comparable water quality (Table 3).

Discussion

North Carolina had a data set of 2000+ stream macroinvertebrate samples which were divided into five water-quality ratings. This data set was used to derive preliminary tolerance values for over 500 taxa. A regression equation then was

TABLE 3. Criteria for North Carolina Biotic Index after seasonal corrections.

Water Ecoregion quality Piedmont/

class Mountain Coastal

Excellent <4.18 <5.24 Good 4.17-5.09 5.25-5.95 Good-Fair 5.10-5.91 5.96-6.67 Fair 5.92-7.05 6.68-7.70 Poor >7.05 >7.71

282 [Volume 12




used to stretch the initial range of water-quality scores (1-4.5) to a 0-10 range (NCBI). I then tested for the effects of season, stream size, and

ecoregion on NCBI. Simple additive seasonal corrections were derived, correcting spring, fall and winter values to the mean summer NCBI values. Stream size did not have a large effect on NCBI values (relative to ecoregion and water

quality), but Piedmont/Coastal streams had NCBI values about one unit higher than Moun- tain streams (Table 2).

Hilsenhoff (1987) used similar procedures to derive tolerance values for Wisconsin streams from a data set of 2000+ invertebrate collections. His initial tolerance values were based on

expert opinion, but were later modified based on the mean biotic index value for sites where

any given taxon was collected. This procedure produced a range of values from 1.4-3.9 on a

possible scale of 0-5 (W. L. Hilsenhoff, Univer-

sity of Wisconsin, personal communication). These numbers were then "stretched" to cover the entire range of a 0-10 scale. Dr. Hilsenhoff's values, however, were based on means, while the NC values used a 75th percentile figure. Furthermore, the Hilsenhoff Biotic Index (HBI) was only intended to monitor organic pollution, while the NCBI measures any stress that either lowers EPT taxa richness or promotes the

development of tolerant species. The North Carolina tolerance values func-

tioned well to separate examples of intolerant, facultative, and tolerant taxa (24 taxa: Table 1). Comparisons of these tolerance values with Hil- senhoff's (1987) data were complicated by a number of problems. Sometimes no comparable values could be found (3 taxa), sometimes com-

parisons could only be made by using different

species in the same genus (2 taxa), and sometimes tolerance values were listed at a species level in one data set, but at the generic level in the other data set (9 taxa). Using the most com-

parable information from the Wisconsin data set, mean tolerance values for the Intolerant, Facultative and Tolerant groups in Table 1 were 0.6, 4.1, and 6.1. Although the trend for the mean tolerance values is similar to the North Carolina data (Table 1), the values for the Tol- erant examples showed considerable difference: 6.1 vs. 9.2.

Some species had North Carolina populations that were rated as more tolerant than comparable Wisconsin populations. For example, the

mayfly flies Stenonema modestum and species in the Ephemerella catawba group are fairly tolerant, abundant, and widespread in North Carolina. Wisconsin data, however, had suggested that these are very intolerant species. It is possible that these "populations" actually are different

species that are not separable with current taxonomic keys. These problems illustrate the per- ils of using a biotic index outside its intended

geographic range. Mean tolerance values for the major taxonom-

ic groups were similar for the North Carolina and Wisconsin data sets (Table 4). In particular, both the tolerance values and the rankings for

Ephemeroptera, Plecoptera and Trichoptera were very close. Chironomidae (as a group) were ranked somewhat differently for the two data sets, but comparable taxa were often similar in their tolerance values. The greatest between-

region differences occurred for Megaloptera and Odonata.

Some of the differences between North Car- olina and Wisconsin tolerance values may re- flect differences in collection methods. The Wis- consin samples were limited to riffle samples, whereas North Carolina uses multiple-habitat collection methods. More slow-water species (especially Odonata) would occur in the multiple-habitat collections, and possibly affect the

assignment of tolerance values. Both our data and Hilsenhoff's data showed

that biotic index values vary with season. Hil- senhoff's values are standardized for spring and fall collections, with a subtraction of 0.5 during summer months (Hilsenhoff 1988). North Car- olina data, however, are standardized for summer collections, with some corrections for other periods of the year. For mountain streams, I have suggested adding 0.4-0.5 during non- summer months, similar to the corrections proposed for Wisconsin streams. During periods of expected change (late spring, fall), stream ratings should be made with caution.

Biotic index values also appear to vary with ecoregion. This may be related to differences in stream temperature, although other variables also may affect between-ecoregion differences. North Carolina mountain streams and Hilsen- hoff's Wisconsin streams had similar criteria ranges; both areas support cold-water fish species (especially trout). If the Wisconsin data are seasonally corrected for summer collections (subtract 0.5, Hilsenhoff 1988), then the NC

1993] 283



D. R. LENAT

TABLE 4. Comparisons of tolerance values (TV), by taxonomic group (ranked by Mean TV), for North Carolina and Wisconsin (Hilsenhoff 1987). N = No. of records/group.

North Carolina Wisconsin Differencea

Mean Mean Group Rank N TV Rank N TV N Mean

Plecoptera 1 62 1.8 1 39 1.3 20 +1.1

Trichoptera 2 102 2.3 2 87 2.9 48 <0.1

Ephemeroptera 3 94 2.7 3 72 3.3 49 +0.5

Diptera: Chironomidae 4 150 5.7 8 71 6.3 71 +0.3

Coleoptera 4 29 5.7 6 28 4.8 9 -0.2 Mollusca 6 17 6.1 Not included - -

Megaloptera 7 4 6.2 4 5 3.6 3 +2.9

Diptera: miscellaneous 8 30 6.4 5 48 4.3 19 +1.6 Odonata 9 33 6.9 7 35 5.4 18 +2.2 Crustacea 10 11 7.5 9 6 7.3 Not comparable Oligochaeta 11 23 8.2 Not included

a North Carolina TV minus Wisconsin TV, applied only to comparable taxa and not derived from Mean TV values.

mountain criteria and the Wisconsin criteria be- come even more similar, rarely differing by > 0.1. NC Piedmont and Coastal Plain streams are limited to warm-water fisheries, and NCBI values for these ecoregions (for streams with similar

water-quality ratings) were much higher relative to the mountain ecoregion.

Biotic index values were not strongly affected

by stream width, a pattern very different from EPT taxa richness values (NC DEM, unpublished data). For this reason, biotic indices are more reliable than taxa richness when ratings are assigned to smaller streams.

North Carolina streams have been rated by the Division of Environmental Management us-

ing EPT taxa richness. The development of a biotic index allows for a second method of rat-

ing. Our current system produces a final rating that receives equal weight from both methods.

Acknowledgements

The data used to derive this biotic index are based on the work of many ecologists in the NC DEM, including Trish MacPherson, David Penrose, Larry Eaton, Neil Medlin, and Ferne Winborne. I am grateful to these individuals for constructive comments during the devel-

opment of the North Carolina biotic index. I thank Ken Eagleson for developing computer programs that generated the tolerance values.

Literature Cited

BRIGHAM, A. R., W. R. BRIGHAM AND A. GNILKA. 1982.

Aquatic insects and oligochaetes of North and South Carolina. Midwest Aquatic Enterprises, Mahomet, Illinois.

CAIRNS, J., AND J. R. PRATT. 1993. A history of bio-

logical monitoring using benthic macroinvertebrates. Pages 10-27 in D. M. Rosenberg and V. H. Resh (editors). Freshwater biomonitoring and benthic macroinvertebrates. Chapman & Hall, New York.

CHANDLER, J. R. 1970. A biological approach to water

quality management. Water Pollution Control 69: 415-421.

CHUTTER, F. M. 1972. An empirical biotic index of the quality of water in South African streams and rivers. Water Research 6:19-30.

EATON, L. E., AND D. R. LENAT. 1991. Comparison of a rapid bioassessment method with North Car- olina's macroinvertebrate collection method. Journal of the North American Benthological So-

ciety 10:335-338. HILSENHOFF, W. L. 1977. Use of arthropods to eval-

uate water quality in streams. Wisconsin De-

partment of Natural Resources, Technical Bul- letin No. 100.

HILSENHOFF, W. L. 1982. Using a biotic index to evaluate water quality in streams. Wisconsin De-

partment of Natural Resources, Technical Bul- letin No. 132.

HILSENHOFF, W. L. 1987. An improved biotic index of organic stream pollution. Great Lakes Ento-

mologist 20:31-39. HILSENHOFF, W. L. 1988. Seasonal correction factors

284 [Volume 12




for the biotic index. Great Lakes Entomologist 21: 9-13.

JONES, J. R., B. H. TRACY, J. L. SEBAUGH, D. H. HAZELWOOD, AND M. M. SMART. 1981. Biotic index tested for ability to assess water quality of Missouri Ozark Streams. Transactions of the American Fisheries Society 110:627-637.

LENAT, D. R. 1988. Water quality assessment of streams using a qualitative collection method for benthic macroinvertebrates. Journal of the North American Benthological Society 7:222-233.

NARF, R. P., E. L. LANGE, AND R. C. WILDMAN. 1984.

Statistical procedures for applying Hilsenhoff's Biotic Index. Journal of Freshwater Ecology 2:441- 448.

NC DIVISION OF ENVIRONMENTAL MANAGEMENT. 1992. Standard operating procedures, biological mon-

itoring. Raleigh, North Carolina.

Received: 4 November 1992

Accepted: 4 May 1993

APPENDIX 1. Tolerance values for North Carolina stream macroinvertebrates, with comparable values for Wisconsin taxa (Hilsenhoff 1987). * = based on less than 25 collections for North Carolina data or less than 5 collections for Wisconsin data. ** = comparisons based on differing levels of taxonomy. NC taxonomy according to Brigham et al. (1982).

Taxon NCBI WIBI Taxon NCBI WIBI

Ephemeroptera Acentrella amplus Acerpenna pygmaeus Ameletus lineatus Attenella attenuata Baetis ephippiatus Baetis flavistriga Baetis frondalis Baetis intercalaris Baetis pluto Baetis propinquus Baetis tricaudatus Baetisca berneri Baetisca carolina Baetisca gibbera Brachycercus spp. Caenis spp. Callibaetis spp. Centroptilum spp. Cinygmula subaequalis Cloeon spp. Dannella lita Dannella simplex Drunella allegheniensis Drunella conestee Drunella cornutella Drunella lata Drunella tuberculata Drunella walkeri Drunella wayah Epeorus dispar Epeorus pleuralis Epeorus rubidus

Epeorus spp. Ephemera guttalata Ephemera spp.

3.6 3.7 2.1 2.6 3.9 7.2 8.0 5.8 4.8 6.2 1.8 0.6* 3.6 1.4 3.5 7.6 9.3 6.3 0.0 7.4 0.0* 3.9 1.3 0.0 0.0 0.1 0.2 1.0 0.0 1.0 2.0 1.4 1.2 0.0 2.2

4 0* 3*

4 5* 6

6*

5**

3* 7 9 2*

4* 4* 2*

0

0**

1**

Ephemerella berneri

Ephemerella catawba (gr) Ephemerella hispida Ephemerella invaria (gr) Ephemerella needhami

Ephemerella rotunda

Ephemerella septentrionalis Ephoron leukon

Eurylophella bicolor

Eurylophella coxalis

Eurylophella funeralis Eurylophella temporalis Eurylophella verisimilis

Habrophlebia vibrans

Heptagenia julia Heptagenia marginalis Heptagenia pulla Heptagenia spp. Heterocloeon spp. Hexagenia spp. Isonychia spp. Leptohyphes spp. Leptophlebia spp. Leucrocuta aphrodite Leucrocuta spp. Litobrancha recurvata

Neoephemera purpurea Paracleodes spp. Paraleptophlebia spp. Potamanthus spp. Pseudocloeon spp. Rhithrogena amica

Rhithrogena exilis

Rhithrogena fuscifrons Rhithrogena spp. Serratella carolina

0.0* 4.0 0.6 2.2 0.0* 2.8 2.0 1.5 5.1 2.6 2.3 4.6 0.3* 0.0 0.5* 2.5 2.3 2.8 3.6 4.7 3.8 2.0* 6.4 2.5 0.0 0.0* 2.1 8.7 1.2 1.6 4.4 0.0* 0.0* 0.0* 0.4 0.0*

1*

1 2

2* 1

0* 5

3** 2* 6 2

4 1** 1** 6*

1 4 4**

0

1993] 285



D. R. LENAT

APPENDIX 1. Continued.


Serratella deficiens Serratella serrata Serratella serratoides

Siphlonurus spp. Siphloplecton spp. Stenacron carolina Stenacron interpunctatum Stenacron pallidum Stenonema carlsoni Stenonema femoratum Stenonema integrum Stenonema ithaca Stenonema lenati Stenonema mediopunctatum Stenonema meririvulanum Stenonema modestum Stenonema pudicum Stenonema terminatum Stenonema vicarium

Tricorythodes spp.

Plecoptera Acroneuria abnormis Acroneuria arenosa Acroneuria carolinensis Acroneuria lycorias Acroneuria mela

Agnetina annulipes Agnetina flavescens Allocapnia spp. Alloperla spp. Amphinemura spp. Beloneuria spp. Clioperla clio Cultus decisus

Diploperla spp. Diploperla duplicata Diploperla morgani Eccoptura xanthenes

Haploperla brevis

Helopicus bogaloosa Helopicus subvarians

Isogenoides hansoni

Isoperla bilineata Isoperla dicala

Isoperla holochlora

Isoperla namata (gr) Isoperla nr holochlora

Isoperla nr slossonae

Isoperla orata

Isoperla similis

Isoperla slossonae

Isoperla transmarina (gr) Leuctra spp.

2.7 2 2.7 1.5 2.6 7 3.1 2* 1.7 7.1 7 2.9 2.1 7.5 5 5.5 4* 4.1 2.3 1.7* 3 0.3 5.8 1 2.1 4.5 4 1.0 2 5.4 4

2.2 2.2 0.0 1.5 0.9 0.0* 0.0* 2.8 1.4 3.4 0.0 4.8 1.6 2.0* 2.7 1.5 4.1 1.3 0.0* 0.8 0.0* 5.5 2.2 0.0 1.8 0.0 1.3 0.0 0.7 2.6 5.6 0.7

0**

3 0*

3**

1

1

2

0 0

Malirekus hastatus

Neoperla spp. Paracapnia angulata Paragnetina fumosa Paragnetina ichusa

Paragnetina immarginata Paragnetina kansensis Perlesta placida Perlesta spp. (not perlesta) Perlinella drymo Prostoia spp. Pteronarcys dorsata

Pteronarcys spp. Remenus bilobatus

Shipsa rotunda

Strophopteryx spp. Suwallia spp. Sweltsa spp. Taeniopteryx burksi

Taeniopteryx metequi Taeniopteryx spp. Talloperla spp. Yugus arinus

Yugus bulbosus

Trichoptera

Agapetus spp. Agarodes libalis

Anisocentropus pyraloides Apatania spp. Arctopsyche irrorata

Brachycentrus appalachia Brachycentrus chelatus

Brachycentrus lateralis

Brachycentrus nigrosoma Brachycentrus numerosus

Brachycentrus spinae Brachycentrus spp. Ceraclea ancylus Ceraclea nr excisa Ceraclea flava Ceraclea maculata Ceraclea transversa

Ceratopsyche alhedra

Ceratopsyche bifida Ceratopsyche bronta

Ceratopsyche macleodi

Ceratopsyche morosa

Ceratopsyche slossonae

Ceratopsyche sparna Ceratopsyche ventura

Cheumatopsyche spp. Chimarra spp.

1.4 1.6 0.2 3.5 0.0 1.7 2.0 4.9 0.0 0.0 6.1 1.8 1.7 0.3 0.3* 2.5 0.0* 0.0 5.8 1.4 6.3 1.4 0.0* 0.0

0.0 0.0* 0.8 0.6 0.0 1.1 0.0* 0.4 2.2 1.8 0.0 2.2 2.5 0.0* 0.0* 6.4 2.7 0.0* 1.0 2.7 0.9 3.2 0.0 3.2 0.0 6.6 2.8

1*

1

1*

0

2**

0

2 3**

2

0 3*

1*

1

3*

3

5

2 4 1

5 4**

286 [Volume 12






Cyrnellus fraternus Diplectrona modesta

Dolophilodes spp. Fattigia pele Glossosoma spp. Goera spp. Helicopsyche borealis

Heteroplectron americanum

Hydatophylax argus Hydropsyche betteni

Hydropsyche decalda

Hydropsyche demora

Hydropsyche hageni Hydropsyche incommoda

Hydropsyche phalerata Hydropsyche rossi

Hydropsyche scalaris

Hydropsyche venularis

Hydroptila spp. Ironoquia punctatissima Lepidostoma spp. Leucotrichia pictipes Lype diversa Macrostemum spp. Matrioptila jeanae Micrasema bennetti Micrasema burksi Micrasema charonis Micrasema rickeri Micrasema rusticum Micrasema wataga Molanna blenda

Mystacides sepulchralus Nectopsyche candida

Nectopsyche exquisita Nectopsyche pavida Neophylax concinnus

Neophylax mitchelli

Neophylax oligius Neophylax ornatus

Neophylax spp. Neureclipsis spp. Nyctiophylax moestus

Nyctiophylax spp. Oecetis spl (stick case) Oecetis sp2 (stick case) Oecetis spp. Orthotrichia spp. Parapsyche cardis

Phylocentropus spp. Polycentropus spp. Protoptila spp. Psilotreta spp.

7.4 2.2 1.0 1.1 1.5 0.3 0.0 2.9 2.3 8.1 4.1 1.8 0.0* 5.0 3.7 4.9 3.0 5.3 6.2 7.3 1.0 4.3 4.3 3.6 0.0* 0.0 0.0* 0.3 0.0 0.0* 3.2 3.9 3.5 3.8 4.2 4.2 1.2 0.0 2.6 1.6* 1.6 4.4 2.6 0.9 4.7 4.1 5.7 7.2 0.0 5.6 3.5 2.8 0.0

8*

0* 0**

0 0

0**

3

2 6

7 1*

2

6 3* 1 2 2 3**

2 6** 4

3**

3 7

5

8

4 6 1 0*

Psychomyia flavida Psychomyia nomada Ptilostomis spp. Pycnopsyche gentilis Pycnopsyche guttifer Pycnopsyche lepida Pycnopsyche scabripennis Pycnopsyche spp. Rhyacophila acutiloba

Rhyacophila atrata Rhyacophila carolina Rhyacophila fuscula Rhyacophila ledra

Rhyacophila minor

Rhyacophila nigrita Rhyacophila torva

Rhyacophila vuphipes Setodes spp. Triaenodes abus Triaenodes injusta Triaenodes tardus Wormaldia spp.

Coleoptera

Anchytarsus bicolor

Ancyronyx variegatus Berosus spp. Copelatus spp. Coptotomus spp. Dineutes spp. Dubiraphia spp. Ectopria nervosa Enochrus spp. Falloporus spp. Gyrinus spp. Helichus spp. Helophorus spp. Hydrocanthus spp. Hydroporus mellitus Hydroporus spp. Laccobius spp. Laccophilus spp. Macronychus glabratus Microcylloepus pusillus Optioservus spp. Oulimnius latiusculus Peltodytes spp. Promoresia elegans Promoresia tardella Psephenus herricki Sperchopsis tessellatus Stenelmis spp. Tropisternus spp.

3.3 2.0 6.7 0.8 2.7 2.5 4.0 2.3 0.0 0.0 0.0 2.0 3.4 0.0* 0.0 1.8 0.0 0.9 4.3 2.2 4.7 0.4

2

4

0* O*

2

6**

0"*

6

6 5

5

4 3* 4

4

5

3.8 6.9 8.6 9.1* 9.0 5.5 6.4 4.3 8.5 2.8 6.3 5.4 7.9 6.9* 1.8 8.9 8.0

10.0 4.7 2.1 2.7 1.8 8.5 2.2 0.0 2.5 6.5 5.4 9.8

1993] 287



D. R. LENAT



Megaloptera

Corydalus cornutus

Nigronia fasciatus Nigronia serricornis Sialis spp.

5.6 6.2 5.5 7.5

Odonata

Argis spp. Basiaeschna janata Boyeria grafiana Boyeria vinosa

Calopteryx spp. Cordulegaster spp. Dromogomphus spp. Enallagma spp. Epicordulia spp. Erythemis simplicicollis Gomphus spiniceps Gomphus spp. Hagenius brevistylus Hetaerina spp. Ischnura spp. Lanthus spp. Libellula spp. Macromia spp. Nasiaeschna pentacantha Neurocordulia molesta Neurocordulia obsoleta Neurocordulia spp. Neurocordulia virginiensis Ophiogomphus spp. Pachydiplax longipennis Perithemis spp. Plathemis lydia Progomphus obscurus Somatochlora spp. Stylogomphus albistylus Sympetrum spp. Tetragoneuria spp.

Diptera: Chironomidae

Ablabesmyia mallochi

Ablabesmyia parajanta/janta Ablabesmyia peleensis Apsectrotanypus johnsoni Brillia spp. Brundiniella eumorpha Cardiocladius spp. Chironomus spp. Cladopelma spp. Cladotanytarsus spp. Clinotanypus pinguis Coelotanypus concinnus

6

0 4

8.7 8** 7.7 6 6.3 6.3 2 8.3 5** 6.1 3** 6.3 9.0 9** 5.6 7.7* 4.9 6.2 5* 4.0 1* 6.2 6 9.4 9** 2.7 9.8 9** 6.7 2** 8.0 3.3* 5* 5.4 0* 5.8 1.6 6.2 1 9.6

10.0 10.0 8* 8.7 8.9 1* 4.8 0* 7.3 10* 8.5

7.6 8** 7.1 4.6* 0.0* 5.2 5 3.8 6.2 5 9.8 10 2.5* 9* 3.7 7 9.1 8 7.7

Coelotanypus spp. Conchapelopia group Corynoneura spp. Cricotopus spp. Cricotopus bicinctus (C/O spl) Cricotopus infuscatus gr

(CIO sp5) Cricotopus vieriensis gr

(CIO sp46) Cricotopus varipes gr (C/O sp6) Cricotopus sylvestris gr

(C/O sp9) Orthocladius obumbratus gr

(C/O splO) Orthocladius robacki

(C/O spl2) Orthocladius spp. Orthocladius (Euorthocladius)

type III (C/O spl3) Orthocladius (E.) sp (C/O sp3) Orthocladius nigritus gr

(C/O sp47) Orthocladius clarkei gr

(C/O sp54) Orthocladius dorenus gr

(C/O sp7) Cryptochironomus blarina gr Cryptochironomus fulvus gr Cryptotendipes spp. Demicryptochironomus spp. Diamesa spp. Dicrotendipes modestus

Dicrotendipes neomodestus

Dicrotendipes nervosus

Dicrotendipes simpsoni Dicrotendipes spp. Diplocladius cultriger Endochironomus nigricans Eukiefferiella spp. Eukiefferiella claripennis gr

(E. spll) Eukiefferiella brehmi gr

(E. spl2) Eukiefferiella gracei gr

(E. spl4) Eukiefferiella devonica gr

(E. sp2) Eukiefferiella brevicalcar gr

(E. sp6) Genus nr Nanocladius B

Glyptotendipes spp. Goeldichironomus holoprasinatus Harnischia spp. Heleniella spp.

6.2 8.7 6 6.2 7

7 8.7

9.0

4.8 8.1

10.0

8.8

7.2 6

6.3 9.2

0.9*

5.8

6.7 8.0 6.7 6.1 2.1

*

8** 8**

6

7.7 8* 9.2 5 8.3

10.0 10.0 7.9 7.7 8 7.5* 8*

8 5.7

3.7

2.7*

2.6

1.7 6.7 8.5 10

10.0 7.5 8 0.0

288

I I

[Volume 12






Heterotrissocladius spp. Hydrobaenus spp. Keifferulus dux Labrundinia pilosella Labrundinia virescens Larsia spp. Lopescladius spp. Micropsectra spp. Microtendipes spp. Nanocladius downesi Nanocladius spp. Natarsia spp. Nilotanypus spp. Nilothauma spp. Odontomesa fulva Pagastia sp. Pagastiella ostansa Parachaetocladius spp. Parachironomus monochromus Parachironomus spp. Paracladopelma spp. Paracladopelma nereis

Paracladopelma undine

Parakiefferiella cf. triqueta Parakiefferiella spp. Paralauterborniella nigrohalteralis Paramerina spp. Parametriocnemus lundbecki

Paratanytarsus spp. Paratendipes spp. Pentaneura spp. Phaenopsectra flavipes Phaenopsectra sp2 Phaenopsectra fuscicorne

(P. sp3) Phaenopsectra spp. Polypedilum angulum Polypedilum aviceps Polypedilum convictum

Polypedilum fallax Polypedilum halterale

Polypedilum illinoense

Polypedilum scalaenum Potthastia gaedi Potthastia longimanus Procladius spp. Prodiamesa olivacea Psectrocladius spp. Psectrotanypus dyari Pseudochironomus spp. Pseudorthocladius spp. Rheocricotopus robacki (R. spl) Rheocricotopus tuberculatus

(R. sp2)

5.4 0* 9.6 8

10.0 10* 6.0 7** 4.5* 8.3 6 2.2 4* 1.4 7 6.2 7 2.6 7.2 3*

10.0 8 4.0 6 5.5 2 5.9 4 2.2 1 2.6* -

0.0 7.9 9.2 10 6.4 7* 1.8* 5.2 5.6 5.9 4.8 8 2.8 3.7 5** 7.7 6 5.3 8 4.6 6 8.5 6.2 7

6.0 6.8 5.6 4.0 5.3 6.7 7.2 9.2 8.7 2.0 7.4 9.3 7.9 3.8

10.0

7

9 3** 8*

10

Rheosmittia nr delicatula

Rheotanytarsus spp. Robackia claviger Robackia demeijerei Saetheria tylus Stelechomyia perpulchra Stempellina spp. Stempellinella spp. Stenochironomus spp. Stictochironomus spp. Sublettea coffmani Symposiocladius lignicola Sympotthastia spp. Synorthocladius spp. Tanypus spp. Tanytarsus spp. Thienemaniella spp. Tribelos spp. Tvetenia spp. Tvetenia bavarica gr (E. spl) Tvetenia discoloripes gr (E. sp3) Unniella multivirga Xenochironomus xenolabis

Xylotopus par Zavrelia spp. Zavrelimyia spp.

Diptera: Miscellaneous

Anopheles spp. Antocha spp. Atherix lantha

Atrichopogon spp. Blepharicera spp. Chaoborus punctipennis Chrysops spp. Cnephia mutata Culex spp. Culicoides spp. Dicranota spp. Dixa spp. Dolichopodidae Empididae Eristalis spp. Hexatoma spp. Limnophora spp. Limonia spp. Palpomyia (complex) Polymeda / ormosia spp. Prosimulium mixtum

4.2 5 Prosimulium spp. 0.0 O* Protoplasa fitchii 7.7 6** Pseudolimnophila spp.

Psychoda spp. 6.8 * Simulium spp.

7.1 6.4 6 2.4 4.3 8.1 4** 4.6 2.0* 2 5.3 4 6.4 5 6.7 9 1.7 5.4 5.7 2 4.7 2* 9.6 10 6.7 6 6.0 6 6.6 5

5 4.0 3.9 0.0* 7.0 0** 6.6 2* 2.7* 9.3 8

9.1 4.6 3 2.1 2 6.8 0.2 0** 8.5 8** 7.3 6 4.0* 5

10.0 6.5 10 0.0 3 2.8 9.7 4 8.1 6

10.0 10 4.7 2 7.0*

10.0 6 6.9 6 6.5 3.3 3 2.6 5.0 7.3 2 9.9* 4.4

1993] 289





Simulium venustum Simulium vittatum Tabanus spp. Tipula spp.

Oligochaeta Aulodrilus limnobius Aulodrilus pigueti Branchiura sowerbyi Cambarincolidae Dero spp. Enchytraeidae Haber speciosus Ilyodrilus templetoni Isochaetides curvisetosus Isochaetides freyi Limnodrilus cervix Limnodrilus hoffmeisteri Limnodrilus spp. Limnodrilus udekemianus Lumbriculidae Nais spp. Opisthopora (earthworm gr) Peloscolex spp. Pristina spp. Slavina appendiculata Spirosperma nikolskyi Stylaria lacustris

Tubifex tubifex

Hirudinea

Batracobdella phalera Erpobdella / mooreobdella spp. Helobdella elongata Helobdella stagnalis Helobdella triserialis Mooreobdella tetragon Placobdella papillifera Placobdella parasitica

Crustacea

Asellus spp. Astacidae

7.4 5 8.7 7 9.7 5* 7.7 4

5.2* 4.7* 8.4 6.2

10.0 10.0 2.8 9.4 7.18 7.6

10.0 9.8 9.6 9.7* 7.3 9.1 9.1 8.8 9.9 7.1 7.7 8.5

10.0

7.1 7.8 9.9 6.7 8.9 9.7 9.0 6.6

Cambarus spp. Crangonyx serratus

Crangonyx spp. Gammarus fasciatus Hyallela azteca Lirceus spp. Orconectes spp. Palaemonetes paludosus Procambarus spp.

Mollusca

Amnicola spp. Campeloma decisum Elimia spp. Ferrissia spp. Helisoma anceps Laevapex fuscus Leptoxis spp. Menetus dilatus

Physella spp. Pseudosuccinea columella

Somatogyrus spp. Stagnicola spp. Corbicula fluminea Elliptio complanata Elliptio lanceolata Pisidium spp. Sphaerium spp.

Other

Belastoma spp. Ranatra spp. Corixidae Climacia areolaris Cura foremanii Dugesia tigrina Hydracarina Petrophila sp. Prostoma graecens

9.4 8 7.2

8.1 8.1* 8.0 6.9 7.9 8 7.7 2.7 6.7 9.5

4.8 6.7 2.5 6.9 6.5 7.3 1.6 8.4 9.1 7.2 6.5 8.0 6.3 5.4 1.9* 6.8 7.7

9.8 7.5 9.0 6.5 5.1 7.5 5.7 1.8 5 6.6

D. R. LENAT [Volume 12 290



A Biotic Index for the Southeastern United States: Derivation and List of Tolerance Values, with Criteria for Assigning Water-Quality Ratings Author(s): David

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