Calculating the 10-Metric Genus-Level B-IBI for Puget Sound Lowlands, and Interpreting the Results

(adapted from www.salmonweb.org)

A B-IBI is created by first identifying and counting all benthic macroinvertebrates found from a stream sampling event. Various metrics are then tabulated using these raw data. After the metrics are calculated, they are each converted to a score of 1, 3, or 5 in order to facilitate comparisons between areas both over time and space (i.e., between sampling site, watersheds, or regions). A value of "5" is assigned for the range of expected results (i.e., for each metric) in an UNDISTURBED SITE. A value of "3" is designated for results expected from a SOMEWHAT DEGRADED SITE, and a value of "1" is assigned for values expected in SEVERELY DEGRADED SITES.

The individual metric scores are added together for a Total B-IBI score. In the genus-level ten-metric B-IBI, a total score can range from 10 (i.e., 10 X 1) to 50 (i.e., 10 X 5). The Total B-IBI score can then be assessed using a qualitative coding system (see “grading” table near the end of this document.)

Genus-Level 10-Metric B-IBI Descriptions

Taxon means a single taxonomic group such as family, genus, or species. Taxa is plural. For genus-level scoring, aquatic insects are identified to the genus level, with the exception of chironomids, which are identified to the family level. Non-insects are identified to the order or family level:

Here is the complete taxonomic identification protocol that we use for the 10-metric genus-level B-IBI for the Puget Sound Lowlands:

  • Arthopods: to genus, except:
      • Chironomids: to family
      • Copepods, ostracods, and acarines: to order
  • Molluscs: to family
  • Hydras and relatives, flat and segmented worms: to class
  • Roundworms: to phylum
  • Early instar larvae, pupae, incomplete organisms: ID to the lowest taxon possible (or the levels specified above, whichever comes first), if that taxon can be positively distinguished from other taxa found in that replicate.

 

The following ten metrics are calculated from the sample’s taxonomic identification:

 

Total Taxa Richness

The total number of unique taxa is identified in each replicate. The numbers from the three replicates are then averaged for this metric.

 

Ephemeroptera Taxa Richness

The total number of unique mayfly (Ephemeroptera) taxa is identified in each replicate. The numbers from the three replicates are then averaged for this metric.

 

Plecoptera Taxa Richness

The total number of unique stonefly (Plecoptera) taxa is identified in each replicate. The numbers from the three replicates are then averaged for this metric.

 

Trichoptera Taxa Richness

The total number of unique caddisfly (Tricoptera) taxa is identified in each replicate. The numbers from the three replicates are then averaged for this metric.

 

Number of Long-Lived Taxa

The cumulative number of unique long-lived taxa identified across all three replicates.

 

Number of Intolerant Taxa

The cumulative number of unique intolerant taxa identified across all three replicates.

 

Percent Tolerant Individuals

The total number of tolerant individuals counted in each replicate, divided by the total number of individuals in that replicate, multiplied by 100. The percentages from the three replicates are then averaged for this metric.

 

Number of Clinger Taxa

The total number of unique clinger taxa is identified in each replicate. The numbers from the three replicates are then averaged for this metric.

 

Percent Predator Individuals

The total number of predator individuals counted in each replicate, divided by the total number of individuals in that replicate, multiplied by 100. The percentages from the three replicates are then averaged for this metric.

 

Percent Dominance

The sum of individuals in the three (3) most abundant taxa in each replicate, divided by the total number of individuals in that replicate, multiplied by 100. The percentages from the three replicates are then averaged for this metric.

 

Percent Dominance Example

Step 1

Calculate taxa totals

Step 2

Sum 3 Most numerous Taxa

Step 3

Calculate Percentage

Taxon 1 = 10 organisms
Taxon 2 = 8 organisms
Taxon 3 = 3 organisms
Taxon 4 = 1 organism

Pick Top 3:
Taxa 1 = 10
Taxa 2 = 8
Taxa 3 = 3

(# organisms in 3 dominant taxa / Total # individuals) X 100

(21 / 22) X 100

Total = 22 organisms

Total = 21 organisms

Percent Dominance = 95%

 

10 Metric Genus Level Scoring Criteria

Square braces indicate the value next to the brace is included in the range; rounded parentheses indicate the value is not included.

 

Scoring Criteria:   

1

3

5

Metrics:

Taxa richness and composition

 

Total number of taxa

[0, 14)

[14, 28]

> 28

 

Number of Ephemeroptera (mayfly) taxa

[0, 3.5)

[3.5, 7]

> 7

 

Number of Plecoptera (stonefly) taxa

[0, 2.7)

[2.7, 5.3]

> 5.3

 

Number of Trichoptera (caddisfly) taxa

[0, 2.7)

[2.7, 5.3]

>5.3

 

Number of long-lived taxa

[0, 4)

[4, 8]

> 8

Tolerance

 

Number of intolerant taxa

[0, 2)

[2, 4]

> 4

 

% of individuals in tolerant taxa

> 44

[27, 44]

< 27

Feeding ecology

 

% of predator individuals

[0, 4.5)

[4.5, 9]

> 9

 

Number of clinger taxa

[0, 8)

[8, 16]

> 16

Population attributes

 

% dominance (top 3 taxa)

> 75

[55, 75)

[0, 55)


10 Metric Genus Level B-IBI Worksheet

METRICS (averaged)

Rep 1

Rep 2

Rep 3

Replicate Average

Metric IBI Score

(1, 3, or 5)

Total number of taxa

 

 

 

 

 

Number of Ephemeroptera (mayfly) taxa

 

 

 

 

 

Number of Plecoptera (stonefly) taxa

 

 

 

 

 

Number of Tricoptera (caddisfly) taxa

 

 

 

 

 

% of individuals in tolerant taxa

 

 

 

 

 

Number of clinger taxa

 

 

 

 

 

% of predator individuals

 

 

 

 

 

% dominance (3 taxa)

 

 

 

 

 

METRICS (cumulative)

Rep 1

Rep 2

Rep 3

Cumulative Unique

Metric IBI Score

(1, 3, or 5)

Number of long-lived taxa

 

 

 

 

 

Number of intolerant taxa

 

 

 

 

 

Total B-IBI Score (Add Metric B-IBI scores for Total B-IBI score):

 

For the percentage metrics, remember to multiply the final computation by 100 for each replicate, e.g., % predator individuals = (total number predator individuals / total number individuals) X 100

 

Interpreting your IBI Score

Once you've calculated the Puget Sound B-IBI, you have a number between 10 and 50. What does that number mean?

The B-IBI is a measure of a stream's biological condition (i.e., health). Each of the individual metrics reflect the condition of important biological components. These components provide insight and clues about the types of degradation responsible for changes within the biological community of benthic macroinvertebrates.

A value close to 50 indicates that the stream's biology is equivalent to what would be found in a "natural" stream of that area. A value close to 10 indicates a poor biotic condition within the stream. Most scores will fall somewhere in between these two extremes. Listed below are cut-off values for the B-IBI scores and their qualitative interpretation.

 

“Grading” System For B-IBI For Puget Sound Lowlands:

Score

Grade

Definition

50-46

Healthy

Ecologically intact, supporting the most sensitive life-forms.

44-36

Compromised

Showing signs of ecological degradation. Impacts expected to one or more salmon life-stages.

34-28

Impaired

Healthy ecosystem functions demonstrably impaired.  Cannot support self-sustaining salmon populations.

26-18

Highly impaired

Highly adverse to salmon and various other life-forms.

16-10

Critically impaired

Unable to support a large proportion of once-native life-forms.

 

It is important to not only look at the final B-IBI score, but to look at the individual metric scores for clues to the types of impacts affecting the final score. For example: Did you have a high percentage of pollution tolerant taxa? Were long lived taxa present? Were sediment tolerant taxa present? The individual metrics, the original data set, and your notes on the land uses surrounding the site will help you understand the processes occurring within and around your sampling site.

Indices of Biological Integrity do more than generate a final score - they provide the opportunity to investigate the types of influences acting upon a watershed. However, keep in mind that human disturbances act upon stream systems in complex ways and thus the resulting IBI scores should be interpreted as a whole (Rossano, 1996). For example, a sampling site may possess high diversity (i.e., total taxa richness) and thus indicate a high biological integrity score. However, if the species contributing to a high diversity are pollution tolerant species, the overall biological integrity of the system may be poor. Knowing the stream ecology of the different taxa associated with streams in your region will aid in the interpretation of your data and the resulting IBI.

 

References

Fore, L. S., K. Paulsen, & K. O'Laughlin. (In press) Assessing the performance of volunteers in monitoring streams. Freshwater Biology.

Karr, J.R. 1996a. Ecological integrity and ecological health are not the same. Pp. 97-109 in P.C. Schulze, ed. Engineering Within Ecological Constraints. National Academy Press, Washington, DC.

Karr, J.R. 1996b. Rivers as Sentinels: Using the biology of rivers to guide landscape management. Pp in RJ. Naiman and R.E. Bilby, eds. The Ecology and Management of Streams and Rivers in the Pacific Northwest Coastal Ecoregion. Springer-Verlag, New York.

Karr, J.R., and E.W. Chu. 1997. Biological Monitoring and Assessment: Using Multimetric Indexes Effectively. EPA 235-R97-001. Seattle: University of Washington.

Karr, J.R. 1999. Defining and measuring river health. Freshwater Biology, 41:221-234.

Karr, J.R. and E.W. Chu. 1998. Restoring Life in Running Waters: Better Biological Monitoring. Island Press, Washington, DC.

Karr, J.R. and D.R. Dudley. 1981. Ecological perspective on water quality goals. Environmental Management, 5:55-68.

Karr, J.R., K.D. Fausch, P.L. Angermeier, P.R. Yant, and I.J. Schlosser. 1986. Assessing biological integrity in running waters, a method and its rational. Illinois Natural History Survey, Special Publication 5.

Morley, S.A. (2000) Effects of urbanization on the biological integity of Puget Sound lowland streams: Restoration with a biological focus, Washington, USA. Thesis, University of Washington, Seattle, WA.

Rossano, E.M. 1996. Diagnosis of Stream Environments with Index of Biological Integrity. Sankaido, Tokyo, Japan.