Riffle fish populations in Blue River were sampled using a strip transect removal (Zippin) method. Secondly, we performed rapid bioassessment analyses on stream habitat and riffle macroinvertebrates. Lastly, we gathered background information on water quality, riparian vegetation, stream discharge and numbers of fecal coliform bacteria per 100 ml.
One underlying purpose of this study was to continue use of permanent monitoring sites organized in 1999. The sites selected this year were White Cloud (Site 3), Rothrock’s Dam (Site 6) and Milltown Dam (Site 7). Since Dr. Baker was present on the trips, he was able to point out specific sample sites where he had collected the species.
Latitude, longitude and elevation information were either determined in the field using a GPS device or by calculating with a grid using the appropriate 7.5 minute USGS topographic map. Elevation, range, township and section numbers were also recorded from the topographic maps.
Upon arrival at a sampling location, we photographed each site from the upstream and downstream perspective and recorded the data in field notebooks. These notebooks were later used as a reference source for preparing this report.
The Zippin method collection procedure, also referred to as the constant
probability of capture or the maximum likelihood method of Zippin, involves
multiple, repeated stripping or removal of fish from the same selected riffle.
It was accomplished at each location in the following manner.
1. A 20-foot small mesh, common sense purse seine was set in a preselected area
of primary habitat. In most areas, we were familiar with locations where the
darters have been previously taken.
2. Kickers formed a line about twenty feet in front of the seine opening and
began turning over rocks, and stirring the water column while gradually
advancing toward the seine.
3. After the fish were driven into the net, the seine was lifted and carried to
the bank where the fish were identified, counted, and returned to the stream
(away from the sampling area).
4. The process was then repeated in the same location until relatively few or no
fish were taken. At each sampling location, about 100+ to 400+ square feet of
riffle area was sampled.
5. Software programs for the Zippin method were used to make the following
estimates and calculations for each riffle sampled: (a) Population estimates for
total number of species collected and individual species where appropriate, (b)
Population standard error, (c) and 95% confidence intervals.
For the macroinvertebrate analysis, we used a very efficient Pollution Tolerance Index (PTI) and a more definitive rapid bioassessment protocol technique (RBP). The PTI is based on indicator organisms and is being used widely by volunteer river monitors across the nation. The observer simply identifies the organisms and places them into one of three categories—pollution intolerant, able to survive in a wide range of conditions and pollution tolerant organisms. Using this approach, a cumulative index value is obtained allowing the assessment of excellent, good, fair or poor.
The EPA-based RBP focuses on the invertebrates in the riffle/run habitat, one of the most productive in a stream ecosystem. This analysis is based upon the original RBPs that emphasized the sampling of a single habitat, in particular riffles or runs, as a means to standardize assessments among streams having those habitats. This approach is still valid, because macroinvertebrate diversity and abundance are usually highest in cobble substrate (riffle/run) habitats.
With our analysis, we obtained three triangular kick- net method samples in the riffles at each site. These samples, known as TKM, were taken with a triangular kick-net with a small mesh. The net was placed on the substrate and moved upstream for a distance of 10 feet while the area in front of the net was agitated for a width of 1 foot. Samples taken using TKM’s were preserved in 40% isopropanol and taken to the laboratory where they were sorted and identified to the family taxonomic level, and counted.
Following counting, the numbers were placed on taxonomic sheets so that the following metric analyses could be calculated.
Taxa Richness --This metric measures the total number of families present and collected at the site. Generally, as habitat diversity, habitat suitability, and water quality increase, the number of families present and collected will increase./p>
Family Biotic Index--For this analysis, each taxonomic group is assigned a tolerance value of 0 to 10. The computed values increase as a water quality decreases. This index is designed to detect organic pollution.
Ratio of Scraper and Filtering Collector Functional Feeding Groups --This metric focuses on the community food base. Scrapers are present in numbers when the rocks are covered with diatoms and other attached algae. They tend to decrease when filamentous algae and aquatic mosses increase. The algae and mosses provide good attachment sites for filtering collectors. Excessive nutrient input and organic enrichment provide the fertilizer for an overabundance of algae.
The EPT to Chironomid ratio is an indication of community balance. Mayflies (Ephemeroptera), Stoneflies (Plecoptera), and Caddisflies (Tricoptera) are organisms often associated with high quality habitats. Very high numbers of midge larvae (Chironomidae) relative to the more sensitive EPT taxa may indicate environmental stress.
Percent Contribution of Dominant Family --This metric uses the dominant taxon as an indication of community balance at the family level. A community dominated by relatively few families would indicate environmental stress.
EPT Index --Scientists have determined that the EPT Index normally increases with increasing water quality. The EPT summarizes the taxa richness within the insect groups that are considered pollution sensitive.
Community Loss Index--This index measures the loss of benthic species between a Blue River reference site and the Milltown site. Values increase as the degree of dissimilarity increases.
Shredders (CPOM Sample)--Shredder macroinvertebrates are those that utilize coarse particulate organic matter (COPM). Shredders are known to be a particularly good indicator of toxic effects since toxins are absorbed by the CPOM. Some toxins such as herbicides and insecticides often are already on the CPOM when they enter the water.
Values obtained using the above metrics are then compared to a pristine river system and given numerical scores of 0, 2, 4 or 6. The cumulative scores from each metric are then summed and the overall score referenced against the cumulative score for the pristine stream as a percent of reference. Percentages above 79% are considered non-impaired while those from 29% to 72% are considered moderately impaired. Percentages below 21% are in the severely impaired group. Based on previous experience with Blue River, we did not expect these sites to fall into the severe impairment area.
Jaccard’s Coefficient of Similarity , % Similarity and Shannon’s Species Diversity Index were determined using available software programs. The Shannon index is one of a number of diversity indexes. It measures the degree of uncertainity. If diversity is low, then the certainty of picking up a particular species is high. High diversity means high uncertainty. We compared our samples with the information obtained in 1995.
The three sites were evaluated using two habitat assessment methods: The Habitat Assessment for High Gradient Streams developed by the EPA and the Qualitative Habitat Evaluation Index developed by the Ohio EPA (QHEI).
Habitat Assessment is a rapid visual assessment developed using the available field data sheet for High Gradient Streams from the EPA. Physical characterization includes an evaluation of general land use, description of the stream origin and type, summary of the riparian vegetation features, and measurements of instream parameters such as width, depth, flow, and substrate. The Habitat Assessment Matrix supports the biosurvey analysis and is weighted to emphasize the most biologically significant parameters. The actual habitat assessment involves rating the nine parameters as excellent, good, fair, or poor. Within each group, there opportunity for further discrimination using a numerical ranking. The assessment, once completed, is then compared as a percent of reference to the best attainable situation to provide a final habitat ranking.
In our analysis, we used an upper control limit of 88% to separate comparable to a high quality reference from those habitats that could be considered as supporting of a variety of aquatic life. We used a value of 75% to separate supporting from partially supporting habitats.
The second method used was the qualitative habitat evaluation index (QHEI) developed by the Ohio EPA. QHEI provides a measure of the qualitative habitat corresponding to the physical features that affect fish and invertebrate communities. The QHEI data sheets are divided into metrics and each metric is broken down into individual components. Metrics for the QHEI include substrate, in-stream cover, channel morphology, riparian zone and bank erosion, pool/glide and riffle/run quality, and gradient. For each component the status of the river is assessed and a score is assigned based on that status.
The scores are added together to give an aggregate QHEI. The score is interpreted using a scale that corresponds to suitability of a warm water habitat for aquatic organisms. QHEI scores greater than 60 are suitable for warmwater habitat without use impairment. Scores between 45 and 60 may meet warmwater habitat in some circumstances, but it may show a level of impairment that requires classification as a modified warmwater habitat. A QHEI score between 32 and 45 meets modified warmwater habitat. A score of less than 32 may be suitable for modified warmwater habitat only if the watershed is greater than three square miles. Even then, this may not be possible. Where modified warmwater habitat is not possible, the stream segment is classified as a limited resource water.
Riparian trees and emergent vegetation were analyzed along a transect line by identifying the larger trees and riparian vegetation. Plant specimens were identified using available field keys or from specimens and leaves returned to the laboratory.
Water quality was evaluated using instrumentation available at Indiana
University Southeast. The data obtained were tabulated and compared with
available water quality data. The following is an expanded treatment of the
water quality methods.
1. Air temperatures were recorded by using the HACH conductivity-temperature
meter. This was accomplished by letting the probe rest in the shade to get an
approximate temperature reading.
· The water temperature was recorded by using the same HACH
conductivity-temperature meter. This was accomplished by submerging the probe
rest in the river.
1. Conductivity is an estimate of total dissolved salts, or the total amount of
dissolved ions in the water. It is controlled by the geology, size of watershed
into the river, pollutants, evaporation of water, and bacterial metabolism.
Pollutants can come from wastewater, from water sewage plants, septic tanks,
runoff from roads, and agricultural runoff. Conductivity was measured with the
HACH conductivity meter. It is measured in microSiemens per centimeter (m S/cm).
· The pH test is a measure of the hydrogen ion concentration in the water. This
test allows one to identify the water as acidic, neutral or alkaline. A reading
of seven is neutral, less than seven is acidic, and greater than seven is
alkaline. Most natural waters have a pH range between 5.0 to 8.5.
· Alkalinity is the ability to neutralize acids. Total alkalinity is the total
concentration of bases in water. It is measured in grains per gallon or parts
per million (ppm), milligrams per liter (mg/L) of calcium carbonate.
4. Hardness of water is due to the presence of multivalent metal ions from
dissolved minerals in water. The primary ions in freshwater are calcium and
magnesium. Hardness is expressed in gr per gal or mg/L of calcium carbonate. The
harder the water the lower the toxicity of other metals to aquatic life.
4. Nitrogen and phosphates are important nutrients for aquatic plants. Too much
of these ions can cause enrichment or eutrophication. This makes the water
favorable for algae to grow profusely. Then when the algae cells die, oxygen is
used in the decomposition, and fish death can result. Measurements of these ions
were done on filtered water using a HACH spectrophotometer and prepared
reagents.
· Turbidity refers to how clear the water is. The greater the total suspended
solids in the water, the murkier the water will appear. High concentrations of
silt and clay can sink to the bottom and suffocate larvae and it can take up
space that could have been used for aquatic life. These measurements were made
using a HACH turbidimeter with a readout in nephelometric turbidity units (NTU).
· Fecal coliform is bacteria that live in the intestines of humans and animals.
The presence of fecal coliform in water indicates that it has been contaminated
with fecal material of either human or other animals. This can be caused by
overflow of sewage systems and could be a possible health risk. To evaluate the
numbers of fecal coliform bacteria, we first collected 100 ml whirlpack or
dilution blank water samples around the areas we were studying. We then filtered
this water through Millipore filters. Following the filtering, we placed the
filters into prepared petri dishes with the appropriate media on an absorbent
pad. After 24 hours of incubation at 44.5o C, we counted the colonies and
recorded the colonies of fecal coliform as numbers per 100 ml.
· Discharge refers to the quantity of water in cubic feet per second passing a
particular site. Silt and muddy water are associated with high discharge and
storm events that wash topsoil and nutrients from unprotected agricultural land.
To determine discharge, we measured the width of the stream and measured the
depth at selected intervals (usually one foot). These data were later converted
into square feet of cross sectional area (CSA). Then, we used a Global water
current meter and measured the water velocity at one-foot intervals by moving
the current meter up and down within the water column. The average water
velocity was then computed by the current meter, and these data were used in
calculating the discharge. Discharge in cubic feet per second was computed using
the formula: Discharge (Q) = average velocity (V) x the Cross Sectional Area
(CSA).