- Email: [email protected]
The development, use, and misuse of biocriteria with an emphasis on the index of biotic integrity
Environmental Science & Policy 3 (2000) S51±S58
www.elsevier.com/locate/envsci
The development, use, and misuse of biocriteria with an emphasis on the index of biotic integrity Greg Seegert* EA Engineering, Science, and Technology, Inc., 444 Lake Cook Road, Suite 18, Deer®eld, IL 60015, USA
Abstract Biocriteria can provide valuable tools for determining use attainment and detecting impairment. Unfortunately, however, biocriteria are sometimes hastily developed, and the underlying metrics either not calibrated properly or not calibrated at all. In this paper, the process of developing biocriteria is reviewed and problems in three basic areas are identi®ed; ®eld collections, metric development, and data analysis. With regard to ®eld sampling, it was found that a greater degree of standardization is needed because variability increases when each investigator is left to choose what gear to sample with, when to sample, and with what intensity. To improve metric performance, several recommendations were made: (1) expectations and scoring for each metric should be based solely on ®eld data; (2) states should not take scoring criteria developed in other states and assume that they apply in their state, unless they have overlapping ecoregions; (3) the slope of the of the 95th percentile line should be determined statistically, rather than by eye; (4) the minimum data set needed to develop defensible metrics needs to be investigated; (5) metric scoring should be based only on data from `least impacted' sites; and (6) metrics that are overly redundant should be eliminated from multi-metric indices. Finally, it was found that accuracy and precision have not been adequately addressed. Round-robin testing should be used to establish the variance of each sampling method. 7 2000 Elsevier Science Ltd. All rights reserved. Keywords: Biocriteria; Bioassessment; Index of biotic integrity; Fish; Macroinvertebrates; Metrics
1. Introduction Biocriteria are criteria based on biological measures or endpoints. Broadly speaking, biocriteria can be based on any biological measure: diversity, species richness, sentinel species, as well as multi-metric indices that measure community structure and function. The multimetric approach, as exempli®ed by the index of biotic integrity (IBI) (Karr, 1981; Karr et al., 1986) and its numerous state or regional derivatives (Ohio Environmental Protection Agency, 1987; Lyons, 1992; Richard, 1996), is currently the most widely used bioassessment tool; thus the multimetric approach, particularly the IBI is the focus of this paper. Hereafter, any reference in this paper to biocriteria should * Tel.: +1-847-945-8010; fax: +1-847-945-0296. E-mail address: [email protected] (G. Seegert).
be interpreted to mean multimetric indices. Various bioassessment techniques, but particularly multimetric indices like the IBI are being considered for use nationwide to assess possible impacts caused by water intakes (Debra Nagle, USEPA, personal communication). Because many water intakes are located on large waterbodies (i.e., lakes, reservoirs, and large rivers), this paper focuses on the usefulness of the IBI and its derivatives for such areas. To date, most of the work on multi-metric indices has focused on wadeable streams (Karr, 1981; Lyons, 1992; Leonard and Orth, 1986; Barbour et al., 1999). Only recently have larger waterbodies been studied (Gerritsen et al., 1998; McDonough and Hickman, 1999); standard protocols for large rivers have yet to be developed. This paper addresses the proper methods for collection of ®eld data and the practical applications associated with developing and calibrating IBI metrics. Readers interested in the theoretical
1462-9011/00/$ - see front matter 7 2000 Elsevier Science Ltd. All rights reserved. PII: S 1 4 6 2 - 9 0 1 1 ( 0 0 ) 0 0 0 2 7 - 7
S52
G. Seegert / Environmental Science & Policy 3 (2000) S51±S58
underpinnings of the multimetric approach should see Davis and Simon (1995), Simon (1999), and Karr and Chu (1999). Wherever possible, the problems or concerns identi®ed herein are supported by appropriate literature citations. However, some of the cautions or concerns identi®ed are new. In these cases, the recommendations provided represent the professional judgement of the author based on detailed reviews of numerous state/federal/provincial guidance documents, ®eld work in 25 states, and ®eld audits of various IBI practitioners. Objectives of this paper are: . evaluate both the methods used to collect data for biocriteria development and the methods by which the biocriteria themselves are developed; . identify areas or situations where biocriteria either do not work or where further work is needed; . identify factors that might make the collection of biosurvey data more dicult or may confound or obscure interpretation of these data; . describe limitations associated with biocriteria (i.e., what they can and can not do); . recommend solutions to the problems identi®ed. Biocriteria can provide valuable tools for determining use attainment and detecting impairment. However, bioassessment techniques often do not and sometimes cannot pinpoint the cause(s) of any impairment which has been identi®ed. Furthermore, biocriteria are sometimes hastily developed, and the underlying metrics either not calibrated properly or not calibrated at all. Problems fall into three basic areas; ®eld collections, metric development, and data analysis, each of which is discussed in turn in the remainder of the paper. Although this paper focuses on the freshwater environment, many of these same issues/problems/recommendations apply in estuarine or marine environments. This paper should not be construed as a call for the abandonment of bioassessment techniques. Rather, it is a call for a more careful and standardized approach to the collection and analysis of biosurvey data. This paper is not intended to be a comprehensive review of biocriteria or biosurvey techniques. Rather it is an overview of these topics and focuses on issues or concerns that seem to be of the greatest interest or which seem to be the most troubling.
2. Field methods 2.1. Macroinvertebrates Depending on the jurisdiction in which you sample, the recommended macroinvertebrate sampling method varies by gear (e.g., Ponars vs Surbers vs Hester-Dendys, etc.), substrate (arti®cial vs natural), method
(quantitative vs qualitative), subsampling technique, and level of taxonomy (species vs genus vs family). Also, the emphasis or, in some cases, lack thereof, placed on certain taxonomic groups (e.g., worms, midges, and EPT) varies greatly among the various methodologies. Some variety in methods is needed to address dierences in substrate type (e.g., hard vs soft) or other factors. If the ®eld investigators were free to choose from the full range of macroinvertebrate methods, this variety of `recommended' methods would be reasonable. In practice, however, each jurisdiction typically allows only a subset of the methods to be used; those they believe are best for that area. An adjacent jurisdiction often recommends an entirely dierent set of methods. This is an area in which USEPA should provide de®nitive guidance regarding what methods are acceptable so as to resolve confusing and often con¯icting guidance at lower jurisdictional (e.g., state) levels. 2.2. Fish A suite of standard methods that covers the range of conditions and stream sizes likely to be encountered in the area being investigated should be established. The methods, issues, and recommendations addressed below are directed towards the IBI (Karr, 1981; Karr et al., 1986). Karr (1981) in his original description of the IBI, as well as in later papers (Karr et al., 1986, Karr and Chu, 1999), emphasizes the need for representative samples. Karr et al. (1986) state that one of the most common sampling problems is using a gear that is ``ineectual for certain species or habitats'', and that ``a basic premise of the IBI is that the entire ®sh fauna has been sampled in its true relative abundance without bias toward taxa or size of ®sh''. Adherence to the guidelines presented herein should result in the collection of consistent, scienti®cally defensible data. These guidelines were based on a thorough review of the literature as well as my own experience based on sampling ®sh in 25 states. Aspects of the sampling program that should be standardized are: . Gears Ð Electro®shing by itself is generally adequate for wadeable streams, but a second gear is often needed for large rivers in order to sample certain species or habitats (Karr et al., 1986). Ð Seining provides an excellent complement to electro®shing and is especially eective at collecting minnows and other small ®shes. In combination, electro®shing and seining collect nearly all the ®sh species present in large rivers but singly each gear only collects about two-thirds of the species present
G. Seegert / Environmental Science & Policy 3 (2000) S51±S58
(Seegert, 2000). Ð Contrary to what is sometimes thought, results from several gears can be combined. For several years, TVA biologists have successfully combined results from several electro®shing and seining techniques at a site to yield a single IBI score for that site (Saylor et al., 1993). . Sampling period Ð An index period should be established when ¯ows are low (and relatively constant) and when ®sh movement, especially movement related to spawning, is minimal. . Flow conditions Ð Flow and especially water clarity guidelines must be established. This is particularly important when dealing with streams and rivers that are relatively turbid much of the time, like many in the Midwest. In the Midwest, 20 cm is probably the minimum acceptable Secchi value. Higher values may be necessary in other regions. . Level of eort Ð The eort can be standardized according to area, time, or distance. However, the eort must be sucient to collect all the species present or at least a reasonable cross section of those species, without bias regarding size or taxa (Karr, 1981; Karr et al., 1986). Furthermore, as noted by Angermeir and Karr (1986) ``the eects of sampling eort on species-richness metrics are clearly signi®cant''. To evaluate temporal variability, it is recommended that each location be sampled at least twice during the index period. . Time of day for electro®shing Ð Catches are almost always better (2±5 higher) at night, and night electro®shing is the preferred method for medium to large rivers (EA Engineering, Science and Technology, Inc., 1987, Sanders, 1992). . At a minimum, what other parameters should be measured? Ð Habitat quality using appropriate qualitative techniques (e.g., QHEI, Rankin, 1989) Ð Water temperature and dissolved oxygen Ð Conductivity . Special considerations Ð Low (<50 mS/cm) and high (>2000 mS/cm) con-
S53
ductivity situations are occasionally encountered and investigators need to be prepared to electro®sh eectively under either situation. . Miscellaneous considerations Ð Based on ®eld audits conducted by this author, it is apparent that some biologists know very little about the principles of electro®shing or the intricacies of their equipment. Thorough knowledge of electro®shing is necessary to use it eectively and safely. Ð Other states should follow the lead of Ohio and develop rigorous certi®cation/training programs. Ð Historically, identi®cation of non-game ®shes was not a priority among resource agencies or consulting ®rms. However, identi®cation of non-game species is needed to develop accurate IBI scores. Thus, training in proper ®sh identi®cation techniques is needed. Identi®cation and veri®cation guidelines similar to those proposed by Barbour et al. (1999) should be followed.
3. IBI metric development There are two signi®cant problems regarding IBI development. One is the use of historical data. Resource agencies, utilities, and others often have reams of data available, some of it going back 30 years or more. They want to make use of what seems to be a valuable resource. It may be valuable, but often not for IBI development. These older data can oer important insights regarding the historical ®sh community and thus what the area could once again attain (assuming the habitat has not been irretrievably altered). However, based on the author's experience, most historical data are not appropriate for calibration of IBI metrics or for calculating IBI scores because the data were not collected following standardized ®eld guidelines like those described herein. A little good data are better than a lot of bad data. Thus, rigorous criteria should be established regarding the use of historical data for IBI metric calibration. The second issue is the incestuous relationships among the various IBIs. Certainly it's easier and far less expensive to use the metrics and scoring procedures developed in an adjacent state or basin but that is not scienti®cally defensible unless the adjacent area is within the same ecoregion or the faunas within the two areas are known to be nearly identical. Even then some ®ne tuning of the metrics or the scoring cutos will often be needed. Each investigator must determine what metrics work in his/her geographic area and develop appropriate scoring cutos for each metric. Scoring criteria should not be based on what
S54
G. Seegert / Environmental Science & Policy 3 (2000) S51±S58
`experts' think are the right values as has been done for some IBIs (North Carolina Department Environmental, Health and Natural Resources, 1997; Carolina Power & Light, 1993). There is no substitute for the collection and evaluation of site (basin)-speci®c data. Biological expectations should be reasonable and attainable, and therefore the limitations of each system must be taken into account. Expectations are sometimes set unreasonably high by resource/regulatory agencies, particularly in urban settings.
3.1. Minimum data set What is the minimum data set needed to develop defensible metrics? Yoder and Rankin (1995) recommend that 35±40 reference sites be sampled per ecoregion per site type (e.g., headwaters, boat sites, etc.) and note that more sites might be needed in heterogeneous ecoregions. If metrics are developed based on data from all sites, not just reference sites, a practice not endorsed here, then even more sites are necessary.
3.2. What metrics should be chosen? 1. Avoid using metrics that are highly correlated, a practice referred to herein as double dipping. This is often done for macroinvertebrates (e.g., number of may¯y spp. and % may¯ies, two metrics that obviously are strongly interrelated). This creates the illusion that the index is more robust than it actually is. 2. Do not use a metric just because Karr (1981) used it or someone in an adjacent state uses it . . . determine which metrics provide the best ®t for your data and which conform to the guidelines established for the IBI (Karr, 1981, Karr et al., 1986). 3. Consider other measures or indicators as a metric (e.g., Richard, 1996 used the index of well being (IWB) score at each site as one of his metrics).
3.3. How many metrics are needed? Some redundancy among metrics within the broad categories established by Karr et al., 1986 (i.e., species richness and composition, trophic composition, and abundance and condition) is acceptable. Within reason the more metrics the better, but the metrics should not be highly correlated with each other (i.e., do not double dip). Most IBIs contain 12 metrics as Karr's original IBI did but Nebraska uses eight metrics and Wisconsin uses 10 metrics so there is no set number.
3.4. Troublesome metrics 3.4.1. Catch per eort CPE often oers little resolving power, especially when large numbers of either highly tolerant or irruptive species are present. In fact, Karr and Chu (1999) indicate that abundance (e.g., as measured by CPE) varies too much to use in multimetric biological indices and indicate that it is ``not a reliable metric''. If an abundance metric is included, then highly tolerant species should not be included in the CPE calculation (Ohio EPA, 1987). Irruptive species may also need to be excluded. Irruptive species are de®ned here as those that occasionally (or in some years regularly) account for >50% of the catch at a station. Some common tolerant species and common irruptive species are listed in Table 1. Many regulatory and resource agencies including USEPA recommend a basin- or watershed-speci®c approach to assessing ecological health. Irruptive species should also be handled on a basin by basin basis. Depending on how much they disrupt expected results, they can be excluded from CPE calculations, and/or from calculation of proportional metrics (Rankin and Yoder, 1999). Decisions such as these were envisioned by Karr (1981) when he developed the IBI nearly 20 years ago when he noted that ``well-trained biologists exercising sound judgement'' was an important aspect of the IBI. CPE expectations can vary considerably. Guidance provided the same year by Gammon (1998) and Simon and Stahl (1998) for the same river (the Wabash in Indiana) and the same gear (boat electro®shing) diers by an order of magnitude (see Table 2). 3.4.2. Tolerance classi®cation The ®rst question regarding the tolerance/intolerance of ®sh is tolerance or intolerance to what? The fact is we know very little about either the absolute or relative tolerance of most ®shes to toxics. In most cases our estimate of a species' tolerance is based on its tolerance to habitat disturbance, e.g. channelization, dams, sedimentation, etc., and, in some cases, we know its relative tolerance to conventional pollutants (e.g., ammonia, temperature, and DO). Conversely, our knowledge regarding the sensitivity of ®shes and macroinvertebrates to most toxics (i.e., metals, pesticides, etc.) is limited to a few species. Similarly, most of the species characterized as intolerants are classi®ed as such because of their intolerance to habitat disturbance (again siltation, channelization, etc.). Rarity by itself is not a suitable criterion for considering a species to be intolerant. Many threatened and endangered ®shes are so listed because of being peripheral to the geographic area in question. Such species should not be characterized as
G. Seegert / Environmental Science & Policy 3 (2000) S51±S58
S55
Table 1 A list of some common tolerant and common irruptive species Common tolerants
Common Irruptives
Common carp White sucker Golden shiner Bluntnose minnow Green sun®sh Blacknose dace Red shiner
(Cyrinus carpio ) (Catostomus commersoni ) (Notemigonus crysoleucas ) (Pimephales notatus ) (Lepomis cyanellus ) (Rhinichthys atratulus ) (Cyprinella lutrensis )
intolerants unless they are known to be intolerant to speci®c habitat or water quality parameters. Finally, most species currently listed as intolerants are naturally rare or absent in large rivers, so lists of intolerants speci®c to large rivers need to be developed. 3.4.3. Young of the year (YOY) in¯uence Inclusion of YOY ®sh may skew IBI results, particularly for those metrics dealing with percentages (e.g., percent tolerant species) (Angermeir and Karr, 1986, Ohio Environmental Protection Agency, 1987; Rankin and Yoder, 1999). To address this problem, ®sh less than a certain size (say 20 mm) can be excluded (Ohio Environmental Protection Agency, 1987) or YOYs can be excluded (Angermeir and Karr, 1986). However, determining whether an individual is or is not a YOY can be dicult, especially for small species. Data collected from several wadeable streams in Ohio indicate that IBI scores calculated both with and without YOYs were similar (dierence typically <2 IBI points) (EA, 1999), so this may not be as large an issue as is sometimes portrayed. Given the diculty associated with determining whether or not each specimen is a YOY, a size cuto (25 mm) rather than an age cuto is recommended herein. 3.5. Scoring IBI metrics Historically, trisecting or otherwise dividing plotted data was done mainly by eye. This may be sucient in `clean' or large, robust data sets but is not appropriate for smaller data sets or those with considerable scatter. In the latter situations, methods for determining the position and slope of the 95th percentile line similar to Table 2 Catch per eort metric criteria recommended for the Wabash River No. per km Metric score
Simon and Stahl
Gammon
5 3 1
> 300 150±300 < 150
> 30 12±30 < 12
Gizzard shad Emerald shiner Bullhead minnow Silvery minnows Stonerollers Spot®n shiner Striped shiner
(Dorosoma cepedianum ) (Notropis atherinoides ) (Pimephales vigilax ) (Hybognathus spp.) (Campostoma spp.) (Cyprinella spiloptera ) (Luxilus chrysocephalus
those described by Rankin and Yoder (1999) should be used. The presence of large numbers of irruptive species (e.g., gizzard shad, emerald shiner, etc.) can `overwhelm' certain IBI metrics, particularly proportional metrics or those dealing with catch rates. The possible exclusion of irruptive species should be handled on a watershed by watershed basis. This may involve calculation of the IBI both with and without the irruptive species in question (Rankin and Yoder, 1999), and determining the degree to which that species aects proportional metrics. 3.6. IBIs for the same area can dier appreciably Described previously was an example where two investigators (Gammon, 1998; Simon and Stahl, 1998) independently developed guidelines for the same river that diered by an order of magnitude with regard to CPE scoring cutos. Other metric cutos developed by these investigators for the same waterbody also differed appreciably. Three separate groups have developed IBIs for the Pigeon River in North Carolina and Tennessee (Saylor et al., 1993, North Carolina Department of Environment, Health and Natural Resources, 1997; Carolina Power & Light, 1993). These groups all used a 12metric IBI with most of the metrics being identical. Depending on which version is used, IBI scores can dier by as much as 18 IBI units for the same data set. Using data independently collected from the Pigeon River, IBI scores using the version developed by Carolina Power & Light (1993) were found to consistently be six points lower than if the same data were scored using state of North Carolina Departmental Health and Natural Resources (NCDEHNR) (1997) scoring criteria, with scores being intermediate when the scoring cutos recommended by Saylor et al. (1993) are used. The Carolina Power & Light and NCDEHNR metric scoring cutos were based on professional judgement regarding expectations rather than on ®eld data (as recommended in this paper). The cutos used by Saylor et al. (1993) were based on ®eld collections from several Blue Ridge tributaries to the upper Ten-
S56
G. Seegert / Environmental Science & Policy 3 (2000) S51±S58
nessee River. The dierences in Pigeon River IBI scores were large enough that the classi®cation given to a site (i.e., poor, fair, good, etc.) often diered depending on which IBI was used.
wadeable streams do not accurately re¯ect the tolerance of large river ®shes. Thus, new classi®cation schemes, unique to large rivers, must be developed.
4. Issues unique or most problematic in large rivers
5. Data analysis
Assessment of large river ®sh communities is particularly important for the electric utility industry since nearly half the nation's generating capacity comes from plants located on large rivers (Electric Power Research Institute, unpublished data). Because the problems associated with bioassessment of large rivers is discussed in greater detail elsewhere in these proceedings (Seegert, 2000), only a brief listing of some of the more challenging issues or problems is provided in this paper.
Accuracy and precision have not been adequately addressed. Only one study has addressed IBI variability in any depth, and that study (Fore et al., 1994) only established what is typically referred to as single operator precision (i.e., one person, one piece of apparatus). In practice, however, many individuals (i.e., operators) will be involved in IBI data collection with great dierences in their degree of training. Furthermore, there is no such thing as a `standard' electro®sher. Variables in the electro®shing system that aect eectiveness include:
. Day vs night Ð based on personal experience, electro®shing catch rates in medium to large rivers are two to three-fold higher at night and as much as 10fold higher for some species. Species richness is also higher at night. Most other investigators have reached the same conclusion (Sanders, 1992; Paragamian, 1989). Therefore, electro®shing should be done at night in large rivers. . Gear eectiveness/overlap Ð One gear is not enough if you want/need to collect most (>80% of the species present). As described in greater detail elsewhere (Seegert, 2000), the overlap between shock and seine collections is 070±75% based on multiple collections but often only 050% for single collections. Although it is sometimes believed that results from dierent gears can not be combined, such results can be successfully combined to generate valid IBI scores (Saylor et al., 1993). . Seasonal movements Ð many riverine species (e.g., walleye and sauger) move large distances during spawning. Thus, an index period should be established that avoids such periods. . Lack of reference sites is a problem on all of our large rivers, which makes it dicult to determine expectations accurately. . Irruptive species like gizzard shad often confound the data. . Taxonomy is more of a problem in large rivers than in wadeable streams because large rivers have more species and few ichthyologists study large rivers. Some of the taxa which are most troublesome are carpsuckers (Carpiodes spp.), black bualo (Ictiobus niger ), introduced hybrids (e.g., wipers, saugeye), and cyprinids (especially the mimic/channel/Cahaba shiner group in the Midwest and East, and Gila spp. in the southwest). . The tolerant/intolerant classi®cations developed for
. The electro®sher itself (which includes not only numerous commercially available makes and models but also homemade units). . The form of the electrical output Ð AC, DC, pulsed DC, pulse width, pulse frequency, wave form, etc. . Generator size (power) . Anode/cathode size and con®guration. Round-robin, inter-laboratory testing like that used for analytical methods (American Society of Testing and Materials, 1992, Method D2777) should be used to establish the variance of each biological method. Such testing would establish what ASTM refers to as multiple operator variance. Such testing not only establishes precision limits, but also reveals whether standard electro®shing methods are described in sucient detail to allow them to be followed accurately by other investigators.
6. Broad issues There seems to be considerable debate regarding how the IBI or other biological measures can be used to measure impacts and what the limitations of these methods are. IBI values are useful not only for determining whether designated uses have or have not been attained, but also for deciding whether the designated uses are appropriate (i.e., attainable). However, despite the fact that procedures like the IBI are excellent for determining that a problem is present, they are not nearly as eective at determining the cause of the impairment, especially when multiple dischargers are present and/or the habitat has been disturbed. Yoder and Rankin (1995) suggest that biological data can be used to establish cause and eect relationships, and
G. Seegert / Environmental Science & Policy 3 (2000) S51±S58
found that toxic constituents left a diagnostic `signature'. Streams in which toxics are a problem consistently yielded very low (often <20) IBI scores, high percentages of ®sh anomalies, and high percentages of tolerant macroinvertebrates (Yoder and Rankin, 1995). However, for the six other impact types they investigated, there was a rather broad overlap in ®sh and macroinvertebrate index scores and in the values for the metrics composing these indices. That is, neither the index score nor any of the metric scores were diagnostic. Thus, except for toxics, the ability of the IBI or its metrics to establish causation is limited. 6.1. Transferability As has been shown to be the case regarding the transferability of habitat preference curves (Hanson, 1993), transferability of IBI metrics or metric scoring procedures from one state to another, or even from one watershed to another should not be done without recalibrating each metric, unless the areas are within the same ecoregion or are known to possess nearly identical faunal assemblages. Even then it would still be worthwhile to at least spot check some metrics.
S57
7. Summary For biocriteria to gain better acceptance, several problems/issues associated with their development and use need to be addressed. With regard to data collection, a greater degree of standardization is necessary. Procedures should be developed that tell an investigator when, where, and how to sample. A suite of standard methods that covers the range of conditions and stream sizes likely to be encountered in the area being investigated should be established. Round-robin testing should then be used to establish the variability and reproducibility of each method. The applicability of each metric should be established for the geographic area in question and each metric should be carefully calibrated. Multimetric techniques like the IBI are excellent for determining that impairment exists or for comparing environmental health among sites. However, the IBI is of limited use in establishing the reasons for any such impairment. When problems are identi®ed, follow-up detailed studies of the impaired area will likely be necessary to determine the cause of the impairment.
6.2. Stream size relationship
Acknowledgements
Just as you cannot transfer IBIs from one state to another, neither can you transfer them to streams (systems) decidedly dierent in size.
I would like to acknowledge constructive comments on the draft from Charles Saylor, Chris Yoder, and one anonymous reviewer.
6.3. Drainage area relationships It is often assumed that metric expectations vary according to drainage area for wadeable streams, but not for large rivers. Even though this was generally the case in Ohio (Ohio Environmental Protection Agency, 1987), it does not necessarily follow that this applies in other areas; investigators in other areas need to examine these relationships carefully. 6.4. Minimum eort Several metrics, especially those dealing with species richness, are clearly eort related (Angermeir and Karr, 1986). Thus, the practice of calculating IBIs based on a level of eort below what is otherwise recommended should be discontinued. Sampling substandard distances is sometimes done within mixing zones to reveal the presence of acutely toxic conditions. However, individual metrics within the IBI are certainly sensitive enough to reveal acutely toxic conditions. Calculation of an IBI in such situations is misleading, especially to those not familiar with the relationship between eort and certain metrics.
References American Society of Testing Materials (ASTM), 1992. Water and environmental technology. In: Annual Book of Standards: American Society of Testing and Materials, vol. 11.01. ASTM, Philadelphia, Pennsylvania. Angermeir, P.L., Karr, J.R., 1986. Applying an index of biotic integrity based on stream ®sh communities: Considerations in sampling and interpretation. North American Journal of Fisheries Management 6, 418±429. Barbour, M., Gerristen, J., Snyder, S., Stribling, J., 1999. Rapid Bioassessment Protocols for Use in Streams and Wadeable Rivers, 2nd ed. EPA, Washington, DC 841-B-99-002. Carolina Power and Light Company, 1993. Criteria for Instream Flow Releases into the Bypassed Reach of the Pigeon River at the Walters Hydroelectric Project. Walters Hydroelectric Project. App. A. FERC Proj. No. 432. Davis, W.S., Simon, T.P. (Eds.), 1995. Biological Assessment and Criteria: Tools for Water Resource Planning and Decision Making. Lewis Publishers, Boca Raton, Florida. EA Engineering Science Technology Inc., 1987. Ambient River Monitoring of the Menominee River and 316b Studies near the Water Intake for Champion International's Mill at Quinnesec, Michigan. Report submitted to Champion International. EA, Deer®eld, IL. EA Engineering Science Technology Inc., 1999. Condition of Fish and Macroinvertebrate Communities in the Leading Creek and
S58
G. Seegert / Environmental Science & Policy 3 (2000) S51±S58
Raccoon Creek Drainage near Meigs Mine 31, 1998. Report prepared for Southern Ohio Coal Company. EA, Deer®eld, IL. Fore, L.S., Karr, J.R., Conquest, L.L., 1994. Statistical properties of an index of biotic integrity used to evaluate water resources. Canadian Journal of Fisheries Aquatic Science 51, 1077±1087. Gammon, J.R., 1998. The Wabash River Ecosystem. Indiana University Press, Bloomington, IN. Gerritsen, J., Carlson, R., Dycus, D., Faulkner, C., Gibson, G., Harcum, J., Markowitz, S., 1998. Lake and Reservoir Bioassessment and Biocriteria; Technical Guidance Document. USEPA Oce of Water. EPA 841-B-98-007. Washington, DC. Hanson, D., 1993. An evaluation of habitat suitability criteria for trout of Sierra Nevada streams. Phase I: Literature review. Rpt. by EA Engineering, Science, and Technology to Paci®c Gas and Electric Company. EA, Lafayette, CA. Karr, J.R., 1981. Assessment of biotic integrity using ®sh communities. Fisheries 6, 21±27. Karr, J.R., Chu, E.W., 1999. Restoring Life in Running Waters: Better Biological Monitoring. Island Press, Washington, DC. Karr, J.R., Fausch, K.D., Angermeier, P.L., Yant, P.R., Schlosser, I.J., 1986. Assessing Biological Integrity in Running Waters: A Method and its Rationale, Illinois Natural History Survey Special Publication, 5, 28. Leonard, P.M., Orth, D.J., 1986. Application and testing of an index of biotic integrity in small, coolwater streams. Transactions of the American Fisheries Society 115, 401±414. Lyons, J., 1992. Using the index of biotic integrity (IBI) to measure environmental quality in warmwater streams of Wisconsin. General Technical Report, NC-149. US Department of Agriculture, Forest Service, St Paul, Minnesota. McDonough, T.A., Hickman, G.D., 1999. Reservoir ®shery assessment index development: a tool for assessing ecological health in Tennessee Valley Authority impoundments. In: Simon, T.P. (Ed.), Assessing the Sustainability and Biological Integrity of Water Resources Using Fish Communities. CRC Press, Boca Raton, FL. North Carolina Department of Environment, Health and Natural Resources, 1997. Standard Operating Procedures: Biological Monitoring. NCDEHNR, Raleigh, NC. Ohio Environmental Protection Agency, 1987. Biological Criteria for the Protection of Aquatic Life. Users Manual for Biological Field
Assessment of Ohio Surface Waters, vol. 2. Division of Water Quality Monitoring and Assessment, Surface Water Section, Columbus, OH. Paragamian, V.L., 1989. A comparison of day and night electro®shing: Size structure and catch per unit eort for smallmouth bass. North American Journal of Fisheries Management 9, 500±503. Rankin, E.T., 1989. The Qualitative Habitat Evaluation Index (QHEI), Rationale, Methods, and Application. Ohio Environmental Protection Agency, Division of Water Quality Planning and Assessment, Ecological Assessment Section, Columbus, OH. Rankin, E.T., Yoder, C.O., 1999. Adjustments to the index of biotic integrity: A summary of Ohio experiences and some suggested modi®cations. In: Simon, T.P. (Ed.), Assessing the Sustainability and Biological Integrity of Water Resources Using Fish Communities. CRC Press, Boca Raton, FL. Richard, Y., 1996. The Drainage Basin of the St Francois River: Ichthyological Communities and Biotic Integrity. Quebec Ministry of the Environment, Montreal, Canada. Sanders, R.E., 1992. Day versus night electro®shing catches from near-shore waters of the Ohio and Muskingum Rivers. Ohio Journal of Science 92, 51±59. Saylor, C., McKinney, A., Schacher, W., 1993. Case Study of the Pigeon River in the Tennessee River Drainage. Oak Ridge National Lab Rpt. 241, Oak Ridge, TN. Seegert, G., 2000. Considerations Regarding Development of Index of Biotic Integrity Metrics for Large Rivers. Environmental Science and Policy (in press). Simon, T.P. (Ed.), 1999. Assessing the Sustainability and Biological Integrity of Water Resources Using Fish Communities. CRC Press, Boca Raton, FL. Simon, T.P., Stahl, J.R., 1998. Development of Index of Biotic Integrity Expectations for the Wabash River. US EPA, Region V, Water Division, Watershed and Nonpoint Source Branch. Chicago, IL EPA 905/R-96. Yoder, C.O., Rankin, E.T., 1995. Biological response signatures and the area of degradation value: New tools for interpreting multimetric data. In: Davis, W., Simon, T. (Eds.), Biological Assessment and Criteria: Tools for Water Resource Planning and Decision Making. Lewis Publishers, Boca Raton, FL, pp. 263± 286.
www.elsevier.com/locate/envsci
The development, use, and misuse of biocriteria with an emphasis on the index of biotic integrity Greg Seegert* EA Engineering, Science, and Technology, Inc., 444 Lake Cook Road, Suite 18, Deer®eld, IL 60015, USA
Abstract Biocriteria can provide valuable tools for determining use attainment and detecting impairment. Unfortunately, however, biocriteria are sometimes hastily developed, and the underlying metrics either not calibrated properly or not calibrated at all. In this paper, the process of developing biocriteria is reviewed and problems in three basic areas are identi®ed; ®eld collections, metric development, and data analysis. With regard to ®eld sampling, it was found that a greater degree of standardization is needed because variability increases when each investigator is left to choose what gear to sample with, when to sample, and with what intensity. To improve metric performance, several recommendations were made: (1) expectations and scoring for each metric should be based solely on ®eld data; (2) states should not take scoring criteria developed in other states and assume that they apply in their state, unless they have overlapping ecoregions; (3) the slope of the of the 95th percentile line should be determined statistically, rather than by eye; (4) the minimum data set needed to develop defensible metrics needs to be investigated; (5) metric scoring should be based only on data from `least impacted' sites; and (6) metrics that are overly redundant should be eliminated from multi-metric indices. Finally, it was found that accuracy and precision have not been adequately addressed. Round-robin testing should be used to establish the variance of each sampling method. 7 2000 Elsevier Science Ltd. All rights reserved. Keywords: Biocriteria; Bioassessment; Index of biotic integrity; Fish; Macroinvertebrates; Metrics
1. Introduction Biocriteria are criteria based on biological measures or endpoints. Broadly speaking, biocriteria can be based on any biological measure: diversity, species richness, sentinel species, as well as multi-metric indices that measure community structure and function. The multimetric approach, as exempli®ed by the index of biotic integrity (IBI) (Karr, 1981; Karr et al., 1986) and its numerous state or regional derivatives (Ohio Environmental Protection Agency, 1987; Lyons, 1992; Richard, 1996), is currently the most widely used bioassessment tool; thus the multimetric approach, particularly the IBI is the focus of this paper. Hereafter, any reference in this paper to biocriteria should * Tel.: +1-847-945-8010; fax: +1-847-945-0296. E-mail address: [email protected] (G. Seegert).
be interpreted to mean multimetric indices. Various bioassessment techniques, but particularly multimetric indices like the IBI are being considered for use nationwide to assess possible impacts caused by water intakes (Debra Nagle, USEPA, personal communication). Because many water intakes are located on large waterbodies (i.e., lakes, reservoirs, and large rivers), this paper focuses on the usefulness of the IBI and its derivatives for such areas. To date, most of the work on multi-metric indices has focused on wadeable streams (Karr, 1981; Lyons, 1992; Leonard and Orth, 1986; Barbour et al., 1999). Only recently have larger waterbodies been studied (Gerritsen et al., 1998; McDonough and Hickman, 1999); standard protocols for large rivers have yet to be developed. This paper addresses the proper methods for collection of ®eld data and the practical applications associated with developing and calibrating IBI metrics. Readers interested in the theoretical
1462-9011/00/$ - see front matter 7 2000 Elsevier Science Ltd. All rights reserved. PII: S 1 4 6 2 - 9 0 1 1 ( 0 0 ) 0 0 0 2 7 - 7
S52
G. Seegert / Environmental Science & Policy 3 (2000) S51±S58
underpinnings of the multimetric approach should see Davis and Simon (1995), Simon (1999), and Karr and Chu (1999). Wherever possible, the problems or concerns identi®ed herein are supported by appropriate literature citations. However, some of the cautions or concerns identi®ed are new. In these cases, the recommendations provided represent the professional judgement of the author based on detailed reviews of numerous state/federal/provincial guidance documents, ®eld work in 25 states, and ®eld audits of various IBI practitioners. Objectives of this paper are: . evaluate both the methods used to collect data for biocriteria development and the methods by which the biocriteria themselves are developed; . identify areas or situations where biocriteria either do not work or where further work is needed; . identify factors that might make the collection of biosurvey data more dicult or may confound or obscure interpretation of these data; . describe limitations associated with biocriteria (i.e., what they can and can not do); . recommend solutions to the problems identi®ed. Biocriteria can provide valuable tools for determining use attainment and detecting impairment. However, bioassessment techniques often do not and sometimes cannot pinpoint the cause(s) of any impairment which has been identi®ed. Furthermore, biocriteria are sometimes hastily developed, and the underlying metrics either not calibrated properly or not calibrated at all. Problems fall into three basic areas; ®eld collections, metric development, and data analysis, each of which is discussed in turn in the remainder of the paper. Although this paper focuses on the freshwater environment, many of these same issues/problems/recommendations apply in estuarine or marine environments. This paper should not be construed as a call for the abandonment of bioassessment techniques. Rather, it is a call for a more careful and standardized approach to the collection and analysis of biosurvey data. This paper is not intended to be a comprehensive review of biocriteria or biosurvey techniques. Rather it is an overview of these topics and focuses on issues or concerns that seem to be of the greatest interest or which seem to be the most troubling.
2. Field methods 2.1. Macroinvertebrates Depending on the jurisdiction in which you sample, the recommended macroinvertebrate sampling method varies by gear (e.g., Ponars vs Surbers vs Hester-Dendys, etc.), substrate (arti®cial vs natural), method
(quantitative vs qualitative), subsampling technique, and level of taxonomy (species vs genus vs family). Also, the emphasis or, in some cases, lack thereof, placed on certain taxonomic groups (e.g., worms, midges, and EPT) varies greatly among the various methodologies. Some variety in methods is needed to address dierences in substrate type (e.g., hard vs soft) or other factors. If the ®eld investigators were free to choose from the full range of macroinvertebrate methods, this variety of `recommended' methods would be reasonable. In practice, however, each jurisdiction typically allows only a subset of the methods to be used; those they believe are best for that area. An adjacent jurisdiction often recommends an entirely dierent set of methods. This is an area in which USEPA should provide de®nitive guidance regarding what methods are acceptable so as to resolve confusing and often con¯icting guidance at lower jurisdictional (e.g., state) levels. 2.2. Fish A suite of standard methods that covers the range of conditions and stream sizes likely to be encountered in the area being investigated should be established. The methods, issues, and recommendations addressed below are directed towards the IBI (Karr, 1981; Karr et al., 1986). Karr (1981) in his original description of the IBI, as well as in later papers (Karr et al., 1986, Karr and Chu, 1999), emphasizes the need for representative samples. Karr et al. (1986) state that one of the most common sampling problems is using a gear that is ``ineectual for certain species or habitats'', and that ``a basic premise of the IBI is that the entire ®sh fauna has been sampled in its true relative abundance without bias toward taxa or size of ®sh''. Adherence to the guidelines presented herein should result in the collection of consistent, scienti®cally defensible data. These guidelines were based on a thorough review of the literature as well as my own experience based on sampling ®sh in 25 states. Aspects of the sampling program that should be standardized are: . Gears Ð Electro®shing by itself is generally adequate for wadeable streams, but a second gear is often needed for large rivers in order to sample certain species or habitats (Karr et al., 1986). Ð Seining provides an excellent complement to electro®shing and is especially eective at collecting minnows and other small ®shes. In combination, electro®shing and seining collect nearly all the ®sh species present in large rivers but singly each gear only collects about two-thirds of the species present
G. Seegert / Environmental Science & Policy 3 (2000) S51±S58
(Seegert, 2000). Ð Contrary to what is sometimes thought, results from several gears can be combined. For several years, TVA biologists have successfully combined results from several electro®shing and seining techniques at a site to yield a single IBI score for that site (Saylor et al., 1993). . Sampling period Ð An index period should be established when ¯ows are low (and relatively constant) and when ®sh movement, especially movement related to spawning, is minimal. . Flow conditions Ð Flow and especially water clarity guidelines must be established. This is particularly important when dealing with streams and rivers that are relatively turbid much of the time, like many in the Midwest. In the Midwest, 20 cm is probably the minimum acceptable Secchi value. Higher values may be necessary in other regions. . Level of eort Ð The eort can be standardized according to area, time, or distance. However, the eort must be sucient to collect all the species present or at least a reasonable cross section of those species, without bias regarding size or taxa (Karr, 1981; Karr et al., 1986). Furthermore, as noted by Angermeir and Karr (1986) ``the eects of sampling eort on species-richness metrics are clearly signi®cant''. To evaluate temporal variability, it is recommended that each location be sampled at least twice during the index period. . Time of day for electro®shing Ð Catches are almost always better (2±5 higher) at night, and night electro®shing is the preferred method for medium to large rivers (EA Engineering, Science and Technology, Inc., 1987, Sanders, 1992). . At a minimum, what other parameters should be measured? Ð Habitat quality using appropriate qualitative techniques (e.g., QHEI, Rankin, 1989) Ð Water temperature and dissolved oxygen Ð Conductivity . Special considerations Ð Low (<50 mS/cm) and high (>2000 mS/cm) con-
S53
ductivity situations are occasionally encountered and investigators need to be prepared to electro®sh eectively under either situation. . Miscellaneous considerations Ð Based on ®eld audits conducted by this author, it is apparent that some biologists know very little about the principles of electro®shing or the intricacies of their equipment. Thorough knowledge of electro®shing is necessary to use it eectively and safely. Ð Other states should follow the lead of Ohio and develop rigorous certi®cation/training programs. Ð Historically, identi®cation of non-game ®shes was not a priority among resource agencies or consulting ®rms. However, identi®cation of non-game species is needed to develop accurate IBI scores. Thus, training in proper ®sh identi®cation techniques is needed. Identi®cation and veri®cation guidelines similar to those proposed by Barbour et al. (1999) should be followed.
3. IBI metric development There are two signi®cant problems regarding IBI development. One is the use of historical data. Resource agencies, utilities, and others often have reams of data available, some of it going back 30 years or more. They want to make use of what seems to be a valuable resource. It may be valuable, but often not for IBI development. These older data can oer important insights regarding the historical ®sh community and thus what the area could once again attain (assuming the habitat has not been irretrievably altered). However, based on the author's experience, most historical data are not appropriate for calibration of IBI metrics or for calculating IBI scores because the data were not collected following standardized ®eld guidelines like those described herein. A little good data are better than a lot of bad data. Thus, rigorous criteria should be established regarding the use of historical data for IBI metric calibration. The second issue is the incestuous relationships among the various IBIs. Certainly it's easier and far less expensive to use the metrics and scoring procedures developed in an adjacent state or basin but that is not scienti®cally defensible unless the adjacent area is within the same ecoregion or the faunas within the two areas are known to be nearly identical. Even then some ®ne tuning of the metrics or the scoring cutos will often be needed. Each investigator must determine what metrics work in his/her geographic area and develop appropriate scoring cutos for each metric. Scoring criteria should not be based on what
S54
G. Seegert / Environmental Science & Policy 3 (2000) S51±S58
`experts' think are the right values as has been done for some IBIs (North Carolina Department Environmental, Health and Natural Resources, 1997; Carolina Power & Light, 1993). There is no substitute for the collection and evaluation of site (basin)-speci®c data. Biological expectations should be reasonable and attainable, and therefore the limitations of each system must be taken into account. Expectations are sometimes set unreasonably high by resource/regulatory agencies, particularly in urban settings.
3.1. Minimum data set What is the minimum data set needed to develop defensible metrics? Yoder and Rankin (1995) recommend that 35±40 reference sites be sampled per ecoregion per site type (e.g., headwaters, boat sites, etc.) and note that more sites might be needed in heterogeneous ecoregions. If metrics are developed based on data from all sites, not just reference sites, a practice not endorsed here, then even more sites are necessary.
3.2. What metrics should be chosen? 1. Avoid using metrics that are highly correlated, a practice referred to herein as double dipping. This is often done for macroinvertebrates (e.g., number of may¯y spp. and % may¯ies, two metrics that obviously are strongly interrelated). This creates the illusion that the index is more robust than it actually is. 2. Do not use a metric just because Karr (1981) used it or someone in an adjacent state uses it . . . determine which metrics provide the best ®t for your data and which conform to the guidelines established for the IBI (Karr, 1981, Karr et al., 1986). 3. Consider other measures or indicators as a metric (e.g., Richard, 1996 used the index of well being (IWB) score at each site as one of his metrics).
3.3. How many metrics are needed? Some redundancy among metrics within the broad categories established by Karr et al., 1986 (i.e., species richness and composition, trophic composition, and abundance and condition) is acceptable. Within reason the more metrics the better, but the metrics should not be highly correlated with each other (i.e., do not double dip). Most IBIs contain 12 metrics as Karr's original IBI did but Nebraska uses eight metrics and Wisconsin uses 10 metrics so there is no set number.
3.4. Troublesome metrics 3.4.1. Catch per eort CPE often oers little resolving power, especially when large numbers of either highly tolerant or irruptive species are present. In fact, Karr and Chu (1999) indicate that abundance (e.g., as measured by CPE) varies too much to use in multimetric biological indices and indicate that it is ``not a reliable metric''. If an abundance metric is included, then highly tolerant species should not be included in the CPE calculation (Ohio EPA, 1987). Irruptive species may also need to be excluded. Irruptive species are de®ned here as those that occasionally (or in some years regularly) account for >50% of the catch at a station. Some common tolerant species and common irruptive species are listed in Table 1. Many regulatory and resource agencies including USEPA recommend a basin- or watershed-speci®c approach to assessing ecological health. Irruptive species should also be handled on a basin by basin basis. Depending on how much they disrupt expected results, they can be excluded from CPE calculations, and/or from calculation of proportional metrics (Rankin and Yoder, 1999). Decisions such as these were envisioned by Karr (1981) when he developed the IBI nearly 20 years ago when he noted that ``well-trained biologists exercising sound judgement'' was an important aspect of the IBI. CPE expectations can vary considerably. Guidance provided the same year by Gammon (1998) and Simon and Stahl (1998) for the same river (the Wabash in Indiana) and the same gear (boat electro®shing) diers by an order of magnitude (see Table 2). 3.4.2. Tolerance classi®cation The ®rst question regarding the tolerance/intolerance of ®sh is tolerance or intolerance to what? The fact is we know very little about either the absolute or relative tolerance of most ®shes to toxics. In most cases our estimate of a species' tolerance is based on its tolerance to habitat disturbance, e.g. channelization, dams, sedimentation, etc., and, in some cases, we know its relative tolerance to conventional pollutants (e.g., ammonia, temperature, and DO). Conversely, our knowledge regarding the sensitivity of ®shes and macroinvertebrates to most toxics (i.e., metals, pesticides, etc.) is limited to a few species. Similarly, most of the species characterized as intolerants are classi®ed as such because of their intolerance to habitat disturbance (again siltation, channelization, etc.). Rarity by itself is not a suitable criterion for considering a species to be intolerant. Many threatened and endangered ®shes are so listed because of being peripheral to the geographic area in question. Such species should not be characterized as
G. Seegert / Environmental Science & Policy 3 (2000) S51±S58
S55
Table 1 A list of some common tolerant and common irruptive species Common tolerants
Common Irruptives
Common carp White sucker Golden shiner Bluntnose minnow Green sun®sh Blacknose dace Red shiner
(Cyrinus carpio ) (Catostomus commersoni ) (Notemigonus crysoleucas ) (Pimephales notatus ) (Lepomis cyanellus ) (Rhinichthys atratulus ) (Cyprinella lutrensis )
intolerants unless they are known to be intolerant to speci®c habitat or water quality parameters. Finally, most species currently listed as intolerants are naturally rare or absent in large rivers, so lists of intolerants speci®c to large rivers need to be developed. 3.4.3. Young of the year (YOY) in¯uence Inclusion of YOY ®sh may skew IBI results, particularly for those metrics dealing with percentages (e.g., percent tolerant species) (Angermeir and Karr, 1986, Ohio Environmental Protection Agency, 1987; Rankin and Yoder, 1999). To address this problem, ®sh less than a certain size (say 20 mm) can be excluded (Ohio Environmental Protection Agency, 1987) or YOYs can be excluded (Angermeir and Karr, 1986). However, determining whether an individual is or is not a YOY can be dicult, especially for small species. Data collected from several wadeable streams in Ohio indicate that IBI scores calculated both with and without YOYs were similar (dierence typically <2 IBI points) (EA, 1999), so this may not be as large an issue as is sometimes portrayed. Given the diculty associated with determining whether or not each specimen is a YOY, a size cuto (25 mm) rather than an age cuto is recommended herein. 3.5. Scoring IBI metrics Historically, trisecting or otherwise dividing plotted data was done mainly by eye. This may be sucient in `clean' or large, robust data sets but is not appropriate for smaller data sets or those with considerable scatter. In the latter situations, methods for determining the position and slope of the 95th percentile line similar to Table 2 Catch per eort metric criteria recommended for the Wabash River No. per km Metric score
Simon and Stahl
Gammon
5 3 1
> 300 150±300 < 150
> 30 12±30 < 12
Gizzard shad Emerald shiner Bullhead minnow Silvery minnows Stonerollers Spot®n shiner Striped shiner
(Dorosoma cepedianum ) (Notropis atherinoides ) (Pimephales vigilax ) (Hybognathus spp.) (Campostoma spp.) (Cyprinella spiloptera ) (Luxilus chrysocephalus
those described by Rankin and Yoder (1999) should be used. The presence of large numbers of irruptive species (e.g., gizzard shad, emerald shiner, etc.) can `overwhelm' certain IBI metrics, particularly proportional metrics or those dealing with catch rates. The possible exclusion of irruptive species should be handled on a watershed by watershed basis. This may involve calculation of the IBI both with and without the irruptive species in question (Rankin and Yoder, 1999), and determining the degree to which that species aects proportional metrics. 3.6. IBIs for the same area can dier appreciably Described previously was an example where two investigators (Gammon, 1998; Simon and Stahl, 1998) independently developed guidelines for the same river that diered by an order of magnitude with regard to CPE scoring cutos. Other metric cutos developed by these investigators for the same waterbody also differed appreciably. Three separate groups have developed IBIs for the Pigeon River in North Carolina and Tennessee (Saylor et al., 1993, North Carolina Department of Environment, Health and Natural Resources, 1997; Carolina Power & Light, 1993). These groups all used a 12metric IBI with most of the metrics being identical. Depending on which version is used, IBI scores can dier by as much as 18 IBI units for the same data set. Using data independently collected from the Pigeon River, IBI scores using the version developed by Carolina Power & Light (1993) were found to consistently be six points lower than if the same data were scored using state of North Carolina Departmental Health and Natural Resources (NCDEHNR) (1997) scoring criteria, with scores being intermediate when the scoring cutos recommended by Saylor et al. (1993) are used. The Carolina Power & Light and NCDEHNR metric scoring cutos were based on professional judgement regarding expectations rather than on ®eld data (as recommended in this paper). The cutos used by Saylor et al. (1993) were based on ®eld collections from several Blue Ridge tributaries to the upper Ten-
S56
G. Seegert / Environmental Science & Policy 3 (2000) S51±S58
nessee River. The dierences in Pigeon River IBI scores were large enough that the classi®cation given to a site (i.e., poor, fair, good, etc.) often diered depending on which IBI was used.
wadeable streams do not accurately re¯ect the tolerance of large river ®shes. Thus, new classi®cation schemes, unique to large rivers, must be developed.
4. Issues unique or most problematic in large rivers
5. Data analysis
Assessment of large river ®sh communities is particularly important for the electric utility industry since nearly half the nation's generating capacity comes from plants located on large rivers (Electric Power Research Institute, unpublished data). Because the problems associated with bioassessment of large rivers is discussed in greater detail elsewhere in these proceedings (Seegert, 2000), only a brief listing of some of the more challenging issues or problems is provided in this paper.
Accuracy and precision have not been adequately addressed. Only one study has addressed IBI variability in any depth, and that study (Fore et al., 1994) only established what is typically referred to as single operator precision (i.e., one person, one piece of apparatus). In practice, however, many individuals (i.e., operators) will be involved in IBI data collection with great dierences in their degree of training. Furthermore, there is no such thing as a `standard' electro®sher. Variables in the electro®shing system that aect eectiveness include:
. Day vs night Ð based on personal experience, electro®shing catch rates in medium to large rivers are two to three-fold higher at night and as much as 10fold higher for some species. Species richness is also higher at night. Most other investigators have reached the same conclusion (Sanders, 1992; Paragamian, 1989). Therefore, electro®shing should be done at night in large rivers. . Gear eectiveness/overlap Ð One gear is not enough if you want/need to collect most (>80% of the species present). As described in greater detail elsewhere (Seegert, 2000), the overlap between shock and seine collections is 070±75% based on multiple collections but often only 050% for single collections. Although it is sometimes believed that results from dierent gears can not be combined, such results can be successfully combined to generate valid IBI scores (Saylor et al., 1993). . Seasonal movements Ð many riverine species (e.g., walleye and sauger) move large distances during spawning. Thus, an index period should be established that avoids such periods. . Lack of reference sites is a problem on all of our large rivers, which makes it dicult to determine expectations accurately. . Irruptive species like gizzard shad often confound the data. . Taxonomy is more of a problem in large rivers than in wadeable streams because large rivers have more species and few ichthyologists study large rivers. Some of the taxa which are most troublesome are carpsuckers (Carpiodes spp.), black bualo (Ictiobus niger ), introduced hybrids (e.g., wipers, saugeye), and cyprinids (especially the mimic/channel/Cahaba shiner group in the Midwest and East, and Gila spp. in the southwest). . The tolerant/intolerant classi®cations developed for
. The electro®sher itself (which includes not only numerous commercially available makes and models but also homemade units). . The form of the electrical output Ð AC, DC, pulsed DC, pulse width, pulse frequency, wave form, etc. . Generator size (power) . Anode/cathode size and con®guration. Round-robin, inter-laboratory testing like that used for analytical methods (American Society of Testing and Materials, 1992, Method D2777) should be used to establish the variance of each biological method. Such testing would establish what ASTM refers to as multiple operator variance. Such testing not only establishes precision limits, but also reveals whether standard electro®shing methods are described in sucient detail to allow them to be followed accurately by other investigators.
6. Broad issues There seems to be considerable debate regarding how the IBI or other biological measures can be used to measure impacts and what the limitations of these methods are. IBI values are useful not only for determining whether designated uses have or have not been attained, but also for deciding whether the designated uses are appropriate (i.e., attainable). However, despite the fact that procedures like the IBI are excellent for determining that a problem is present, they are not nearly as eective at determining the cause of the impairment, especially when multiple dischargers are present and/or the habitat has been disturbed. Yoder and Rankin (1995) suggest that biological data can be used to establish cause and eect relationships, and
G. Seegert / Environmental Science & Policy 3 (2000) S51±S58
found that toxic constituents left a diagnostic `signature'. Streams in which toxics are a problem consistently yielded very low (often <20) IBI scores, high percentages of ®sh anomalies, and high percentages of tolerant macroinvertebrates (Yoder and Rankin, 1995). However, for the six other impact types they investigated, there was a rather broad overlap in ®sh and macroinvertebrate index scores and in the values for the metrics composing these indices. That is, neither the index score nor any of the metric scores were diagnostic. Thus, except for toxics, the ability of the IBI or its metrics to establish causation is limited. 6.1. Transferability As has been shown to be the case regarding the transferability of habitat preference curves (Hanson, 1993), transferability of IBI metrics or metric scoring procedures from one state to another, or even from one watershed to another should not be done without recalibrating each metric, unless the areas are within the same ecoregion or are known to possess nearly identical faunal assemblages. Even then it would still be worthwhile to at least spot check some metrics.
S57
7. Summary For biocriteria to gain better acceptance, several problems/issues associated with their development and use need to be addressed. With regard to data collection, a greater degree of standardization is necessary. Procedures should be developed that tell an investigator when, where, and how to sample. A suite of standard methods that covers the range of conditions and stream sizes likely to be encountered in the area being investigated should be established. Round-robin testing should then be used to establish the variability and reproducibility of each method. The applicability of each metric should be established for the geographic area in question and each metric should be carefully calibrated. Multimetric techniques like the IBI are excellent for determining that impairment exists or for comparing environmental health among sites. However, the IBI is of limited use in establishing the reasons for any such impairment. When problems are identi®ed, follow-up detailed studies of the impaired area will likely be necessary to determine the cause of the impairment.
6.2. Stream size relationship
Acknowledgements
Just as you cannot transfer IBIs from one state to another, neither can you transfer them to streams (systems) decidedly dierent in size.
I would like to acknowledge constructive comments on the draft from Charles Saylor, Chris Yoder, and one anonymous reviewer.
6.3. Drainage area relationships It is often assumed that metric expectations vary according to drainage area for wadeable streams, but not for large rivers. Even though this was generally the case in Ohio (Ohio Environmental Protection Agency, 1987), it does not necessarily follow that this applies in other areas; investigators in other areas need to examine these relationships carefully. 6.4. Minimum eort Several metrics, especially those dealing with species richness, are clearly eort related (Angermeir and Karr, 1986). Thus, the practice of calculating IBIs based on a level of eort below what is otherwise recommended should be discontinued. Sampling substandard distances is sometimes done within mixing zones to reveal the presence of acutely toxic conditions. However, individual metrics within the IBI are certainly sensitive enough to reveal acutely toxic conditions. Calculation of an IBI in such situations is misleading, especially to those not familiar with the relationship between eort and certain metrics.
References American Society of Testing Materials (ASTM), 1992. Water and environmental technology. In: Annual Book of Standards: American Society of Testing and Materials, vol. 11.01. ASTM, Philadelphia, Pennsylvania. Angermeir, P.L., Karr, J.R., 1986. Applying an index of biotic integrity based on stream ®sh communities: Considerations in sampling and interpretation. North American Journal of Fisheries Management 6, 418±429. Barbour, M., Gerristen, J., Snyder, S., Stribling, J., 1999. Rapid Bioassessment Protocols for Use in Streams and Wadeable Rivers, 2nd ed. EPA, Washington, DC 841-B-99-002. Carolina Power and Light Company, 1993. Criteria for Instream Flow Releases into the Bypassed Reach of the Pigeon River at the Walters Hydroelectric Project. Walters Hydroelectric Project. App. A. FERC Proj. No. 432. Davis, W.S., Simon, T.P. (Eds.), 1995. Biological Assessment and Criteria: Tools for Water Resource Planning and Decision Making. Lewis Publishers, Boca Raton, Florida. EA Engineering Science Technology Inc., 1987. Ambient River Monitoring of the Menominee River and 316b Studies near the Water Intake for Champion International's Mill at Quinnesec, Michigan. Report submitted to Champion International. EA, Deer®eld, IL. EA Engineering Science Technology Inc., 1999. Condition of Fish and Macroinvertebrate Communities in the Leading Creek and
S58
G. Seegert / Environmental Science & Policy 3 (2000) S51±S58
Raccoon Creek Drainage near Meigs Mine 31, 1998. Report prepared for Southern Ohio Coal Company. EA, Deer®eld, IL. Fore, L.S., Karr, J.R., Conquest, L.L., 1994. Statistical properties of an index of biotic integrity used to evaluate water resources. Canadian Journal of Fisheries Aquatic Science 51, 1077±1087. Gammon, J.R., 1998. The Wabash River Ecosystem. Indiana University Press, Bloomington, IN. Gerritsen, J., Carlson, R., Dycus, D., Faulkner, C., Gibson, G., Harcum, J., Markowitz, S., 1998. Lake and Reservoir Bioassessment and Biocriteria; Technical Guidance Document. USEPA Oce of Water. EPA 841-B-98-007. Washington, DC. Hanson, D., 1993. An evaluation of habitat suitability criteria for trout of Sierra Nevada streams. Phase I: Literature review. Rpt. by EA Engineering, Science, and Technology to Paci®c Gas and Electric Company. EA, Lafayette, CA. Karr, J.R., 1981. Assessment of biotic integrity using ®sh communities. Fisheries 6, 21±27. Karr, J.R., Chu, E.W., 1999. Restoring Life in Running Waters: Better Biological Monitoring. Island Press, Washington, DC. Karr, J.R., Fausch, K.D., Angermeier, P.L., Yant, P.R., Schlosser, I.J., 1986. Assessing Biological Integrity in Running Waters: A Method and its Rationale, Illinois Natural History Survey Special Publication, 5, 28. Leonard, P.M., Orth, D.J., 1986. Application and testing of an index of biotic integrity in small, coolwater streams. Transactions of the American Fisheries Society 115, 401±414. Lyons, J., 1992. Using the index of biotic integrity (IBI) to measure environmental quality in warmwater streams of Wisconsin. General Technical Report, NC-149. US Department of Agriculture, Forest Service, St Paul, Minnesota. McDonough, T.A., Hickman, G.D., 1999. Reservoir ®shery assessment index development: a tool for assessing ecological health in Tennessee Valley Authority impoundments. In: Simon, T.P. (Ed.), Assessing the Sustainability and Biological Integrity of Water Resources Using Fish Communities. CRC Press, Boca Raton, FL. North Carolina Department of Environment, Health and Natural Resources, 1997. Standard Operating Procedures: Biological Monitoring. NCDEHNR, Raleigh, NC. Ohio Environmental Protection Agency, 1987. Biological Criteria for the Protection of Aquatic Life. Users Manual for Biological Field
Assessment of Ohio Surface Waters, vol. 2. Division of Water Quality Monitoring and Assessment, Surface Water Section, Columbus, OH. Paragamian, V.L., 1989. A comparison of day and night electro®shing: Size structure and catch per unit eort for smallmouth bass. North American Journal of Fisheries Management 9, 500±503. Rankin, E.T., 1989. The Qualitative Habitat Evaluation Index (QHEI), Rationale, Methods, and Application. Ohio Environmental Protection Agency, Division of Water Quality Planning and Assessment, Ecological Assessment Section, Columbus, OH. Rankin, E.T., Yoder, C.O., 1999. Adjustments to the index of biotic integrity: A summary of Ohio experiences and some suggested modi®cations. In: Simon, T.P. (Ed.), Assessing the Sustainability and Biological Integrity of Water Resources Using Fish Communities. CRC Press, Boca Raton, FL. Richard, Y., 1996. The Drainage Basin of the St Francois River: Ichthyological Communities and Biotic Integrity. Quebec Ministry of the Environment, Montreal, Canada. Sanders, R.E., 1992. Day versus night electro®shing catches from near-shore waters of the Ohio and Muskingum Rivers. Ohio Journal of Science 92, 51±59. Saylor, C., McKinney, A., Schacher, W., 1993. Case Study of the Pigeon River in the Tennessee River Drainage. Oak Ridge National Lab Rpt. 241, Oak Ridge, TN. Seegert, G., 2000. Considerations Regarding Development of Index of Biotic Integrity Metrics for Large Rivers. Environmental Science and Policy (in press). Simon, T.P. (Ed.), 1999. Assessing the Sustainability and Biological Integrity of Water Resources Using Fish Communities. CRC Press, Boca Raton, FL. Simon, T.P., Stahl, J.R., 1998. Development of Index of Biotic Integrity Expectations for the Wabash River. US EPA, Region V, Water Division, Watershed and Nonpoint Source Branch. Chicago, IL EPA 905/R-96. Yoder, C.O., Rankin, E.T., 1995. Biological response signatures and the area of degradation value: New tools for interpreting multimetric data. In: Davis, W., Simon, T. (Eds.), Biological Assessment and Criteria: Tools for Water Resource Planning and Decision Making. Lewis Publishers, Boca Raton, FL, pp. 263± 286.