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Publication - Progress report

Technical, Logistical, and Economic Considerations for the Development and Implementation of a Scottish Salmon Counter Network: Scottish Marine and Freshwater Science Vol 7 No 2

Published
22 March 2016
Part of
Marine and fisheries
ISBN
9781785449642

This report provides an extensive review of electronic counter technologies and their potential for implementation in Scotland’s rivers. We consider all major types of proven counter technologies and software implemented by companies and government agenci

View supporting documents Supporting documents

List of Figures

Figure 2.1. Sonar unit mounted on the bottom of a tripod at Spius Creek, held to the substrate by sandbags. This installation allows adjustment with a winch above water surface. Photo courtesy of H. Olynyk - DFO..

Figure 2.2. A simple stepladder mount for a DIDSON sensor. Photo courtesy of H. Enzenhofer.

Figure 2.3. Logie resistivity counter setup with battery bank. Photo courtesy of InStream Fisheries Research.

Figure 2.4. Example signal traces from graphics programs operated by the Logie 2100C resistivity fish counter with a flat pad sensor. The top plot shows the trace of a fish moving upstream over the counter and the bottom plot show the trace of a fish moving downstream over the counter.

Figure 2.5. Virtual illustration of Vaki Riverwatcher's migration corridor. Photo courtesy of Vaki.

Figure 2.6. Virtual illustration of fish migrating through Vaki Riverwatcher. The left illustrates a side profile view of the counter. The right illustrates how a fish disrupts the optical beams. Photo courtesy of Vaki.

Figure 2.7. Vaki optical beam counter with double light box video recorder. Photo courtesy of Vaki.

Figure 2.8. Screenshot of Vaki's proprietary software for the Riverwatcher counter, Winari, with corresponding fish shadow from a specific fish event. Photo courtesy of Vaki.

Figure 2.9. Alaskan floating fence used on the Stanislaus River, United States. Panels are 20 ft. long and incorporate a Vaki counter unit. Photo courtesy of Vaki.

Figure 2.10. A single panel 10ft high picket fence with mounting tripod and three rails. Photo courtesy of InStream Fisheries Research.

Figure 2.11. Seton River picket fence with trap box. River width approximately 30 m, discharge 30 m 3/s, depth 1 m. Photo courtesy of InStream Fisheries Research.

Figure 2.12. Keogh River Alaskan floating fence with 3 m long panels and trap box located on the far riverbank. Photo courtesy of InStream Fisheries Research.

Figure 2.13. A four channel Crump weir with resistivity counter sensors installed. Photo courtesy of InStream Fisheries Research.

Figure 2.14. Helmsdale resistivity fish counter weir with four channels at low flow. Photo courtesy of InStream Fisheries Research.

Figure 2.15. Glendale spawning channel British Columbia, Canada with a hybrid Crump weir and diversion fence. Photo courtesy of InStream Fisheries Research.

Figure 2.16. Chilcotin River flat pad sensor prior to (left) and after installation (right). River width approximately 24 m. Photo courtesy of InStream Fisheries Research.

Figure 2.17. Crawford Creek flat pad counter. Channel width approximately 10 m. Photo courtesy of InStream Fisheries Research.

Figure 2.18. Box sensor unit awaiting deployment. Photo courtesy of InStream Fisheries Research.

Figure 2.19. Seton Dam fish pass counter with eight sensor units. Note that only the top four tubes are visible. Photo courtesy of InStream Fisheries Research.

Figure 2.20. Seton Dam fish pass sensor units prior to installation in a separation grid. Photo courtesy of InStream Fisheries Research.

Figure 3.1. DIDSON DCS interface depicting the sonar's ensonification region.

Figure 3.2. Echoview's data manipulation flowchart used in Case Study 1. (a) A single echogram ping of DIDSON data, with an image of Fish #1 ensonified. (b) Same image as (a) but with the background removed and beam dilation filters applied. Fish #1 is the only object remaining after the variables are applied. (c) Virtual echogram converted into a time series of single beam data, with each ping displayed next to one another. Ping 1250 from (a) and (b) are displayed within the thin rectangular box. The fish tracking setting is applied, showing a trace of Fish #1 in the water column in relation to time (blue line). (d) Time series of single beam data, displaying the length of each ensonified object in relation to time. The same coloration indicates objects with similar lengths. Fish #1 is shown as the purple line, and ping 1250 is displayed within the thin rectangular box. (e) Time series of single beam data, displaying the angle of each ensonified object in relation to the sonar head through time. The full rainbow coloration indicates a track of movement from one edge of the ensonified region to the next. Fish #1 is shown as the rainbow line, and ping 1250 is displayed within the thin rectangular box.

Figure 3.3. Flowchart illustrating budget and effectiveness trade-off in manual analysis

Figure 3.4. Estimated fish lengths using Echoview in relation to distance from sonar. The variance in Echoview measured fish sizes decrease as the distance from the sonar increases. Blue points are fish detected by Echoview and identified as the target species (steelhead, > 83 cm) by manual analysis. Note the high number of blue points measured to be < 83 cm by Echoview, suggesting manual estimate of size differ in comparison to estimate of size by Echoview. Orange points are all other fish detected by Echoview, they represent fish that are either missed by manual counts, or assumed to be < 83 cm during manual analysis and therefore not tracked. The hashed area illustrates an area not ensonified by the DIDSON, located between 0-0.83 m from the sonar head. A 1.5 m diversion fence diverts fish at a minimum of 1 meter to ensure migration is within the field of view. Only fish > 40 cm determined by Echoview are plotted, as fish < 40 cm were purposely not tracked in the manual method since they were not the target species.

Figure 3.5. Signal strength in relation to fish length as determined by Echoview. Blue points are fish detected by Echoview and identified as the target species (steelhead, > 83 cm) by manual analysis. Orange points are all other fish detected by Echoview, they represent fish that are either missed by manual counts, or assumed to be < 83 cm during manual analysis and therefore not tracked. The dotted line illustrates the established 83 cm fish size cut-off for manual analysis, note the high number of blue points measured to be < 83 cm by Echoview, suggesting manual estimate of size differ in comparison to estimate of size by Echoview. Only fish > 40 cm determined by Echoview are plotted, as fish < 40 cm were purposely not tracked in the manual method since they were not the target species.

Figure 3.6. Signal strength in relation to estimated length as determined by Echoview. The variance in Echoview measured fish sizes decrease as the distance from the sonar increases. Blue points are fish detected by Echoview and identified as the target species (steelhead > 83 cm) by manual analysis. Note the high number of blue points measured as < 83 cm by Echoview, suggesting manual estimate of size differ greatly in comparison to estimate of size by Echoview. Orange points are all other fish detected by Echoview, they represent fish that are either missed by manual counts, or assumed to be < 83 cm during manual analysis and therefore not tracked. Only fish > 40 cm determined by Echoview are plotted, as fish < 40 cm were purposely not tracked in the manual method since they were not the target species.

Figure 3.7. Proportions of counts detected in manual analysis increase relative to signal strengths, as determined by Echoview. Only fish > 40 cm determined by Echoview are plotted, as fish < 40 cm were purposely not tracked in the manual method since they were not the target species.

Figure 3.8. Proportion of counts detected in manual analysis decrease relative to an increase in distance from sonar. The hashed area illustrates an area not ensonified by the DIDSON, located between 0-0.83 m from the sonar head. A 1.5 m diversion fence diverts fish at a minimum of 1 meter to ensure migration is within the field of view. Only fish > 40 cm determined by Echoview are plotted, as fish < 40 cm were purposely not tracked in the manual method since they were not the target species.

Figure 3.9. Sequential frames showing a fish migrating through the DIDSON imaging region at an average of 25 m away from the sonar head. Plots illustrate the difficulty of identifying fish manually at greater distances from equipment.

Figure 3.10. Proportion of counts detected in manual analysis increase relative to greater fish length, as determined by Echoview. The dotted line illustrates the established 83 cm fish size cut-off for manual analysis in enumerating Steelhead. Only fish > 40 cm determined by Echoview are plotted, as fish < 40 cm were purposely not tracked in the manual method since they were not the target species.

Figure 3.11. Comparison of up count fish between Echoview and manual analysis. Each point represents a separate analysis file.

Figure 3.12. Comparison of down count fish between Echoview and manual analysis. Each point represents a separate analysis file.

Figure 3.13. Raw DIDSON data during high migration periods, where sockeye salmon moved in a cluster formation. Both images show the difficulty in determining exact numbers of fish within the cluster.

Figure 3.14. Winari's interface displaying data. An .ARV file (fish physical data) is paired with . IMG (fish silhouette) and photo data (digital image) to provide an overview of each object detected. Photo courtesy of Vaki.

Figure 3.15. Screen shot of example folder containing individual files (e.g., 050813.txt) and master data file produced by the bind_counter_data function (e.g., ExampleData2015.csv).

Figure 3.16. Screen shot of sample R code that demonstrates how to install the FishCounter package and use the bind_counter_data function.

Figure 3.17. Screen shot of sample R code that demonstrates how to read in the new master dataset produced by the bind_counter_data function. It also shows how to set the first_day parameter, which determines the day the dataset should begin.

Figure 3.18. Screen shot of sample R code that demonstrates how to create .pdf files of output from two plotting functions.

Figure 3.19. Plots of histograms of up count PSS values for Channels 1 to 3.

Figure 3.20. Plots showing the number of events per hour by date. Each plot represents the events for a given channel. Black lines are the number of events per hour, blue lines are the number of up counts per hour, and the horizontal dashed red line is the mean number of events per hour for all channels. This provides a baseline for the typical number of events per hour and can be used as a benchmark for when there may be counter problems.

Figure 3.21. Plot produced by plot_pss_date function. Grey points show the raw up count peak signal size values and the red points indicate the daily mean up count PSS values. PSS is an indicator of fish size. Note the declining PSS values from mid March to early April, depicting the switch from anadromous to resident Oncorhynchus mykiss.

Figure 3.22. The top plot shows the number of up counts by time of day, and bottom plot shows the peak signal size by time of day.

Figure 3.23. Plot produced by plot_abundance function. The top plot shows the daily number of fish passing through the counter. The bottom plot shows the cumulative abundance by day. This function plots the raw number of up counts and should not be used as a definitive count but as a minimum count.

Figure 3.24. Map of the Gala Watershed. The red dot indicates the location of the Skinworks Cauld fish pass and the Vaki fish counter at Gala. Grid reference: NT 487 367. Map courtesy of James Hunt.

Figure 3.25. Photo of the Skinworks Cauld fish pass and counter site. Photo courtesy of James Hunt.

Figure 3.26. Photo of the Vaki counter and colour video camera installation at the Skinworks Cauld fish pass. Fish enter the counter at the top of the photo and exit at the bottom. The triangular section of the counter box on the right side of the photo is the colour camera and viewing window. Photo courtesy of James Hunt.

Figure 3.27. Screen shot of A) salmon and B) trout swimming through the Vaki counter. Photo courtesy of James Hunt.

Figure 3.28. Length distributions for salmon (blue) and trout (grey) by month and year.

Figure 3.29. Estimated abundance for salmon (blue) and trout (grey) for 2014 using the historical and current models. The dots represent the mean estimate and the bars are the 95% confidence intervals surrounding the mean estimates.

Figure 3.30. Plots showing predicted probabilities of being a salmon (blue) and trout (grey) by month using the current model ( GLM, family: binomial). Length and month are the explanatory variables. The solid line is the mean predicted probability for a given fish length and shaded areas are the 95% confidence limits on the predicted probabilities.

Figure 3.31. Predicted probabilities of being a salmon (blue) and trout (grey) by month using the historical model ( GLMM, family: binomial). Length and month are explanatory variables, and year has been set as a random effect. The solid line is the mean predicted probability for a given fish length and shaded areas are the 95% confidence limits on the predicted probabilities. Note, the 95% confidence intervals are only for the fixed-effects and underestimate the total uncertainty (fixed-effects + random effects).

Figure 4.1. Plots showing the trade-off between validation effort (the number of fish validated) and error in abundance estimates for a single species at a constant accuracy (70 - grey, 80 - blue, 90% - dark blue). Error in abundance estimates are reported as the percent relative error in a) accuracy, b) precision and c) bias. Accuracy is a measure of how close an estimate is to the true abundance (i.e., a combination of precision and bias). Precision is a measure of how repeatable an estimate is. Bias is a measure of whether or not estimates are consistently higher or lower than the true abundance. Points indicate mean values and vertical bars represent the standard deviation.

Figure 4.2. Plots showing the trade-off between validation effort (the number of fish validated) and error in abundance estimates for a single species - variable accuracy (80% - grey) and variable accuracy (50-80% - blue). Error in abundance estimates are reported as the percent relative error in a) accuracy, b) precision, and c) bias. Accuracy is a measure of how close an estimate is to the true abundance (i.e., a combination of precision and bias). Precision is a measure of how repeatable an estimate is. Bias is a measure of whether or not estimates are consistently higher or lower than the true abundance. Points indicate mean values and vertical bars represent the standard deviation.

Figure 4.3. Plots showing the trade-off between validation effort (the number of fish validated) and error in abundance estimates for a two species - constant accuracy (80% - grey) and variable accuracy (50-80% - blue) scenario. Error in abundance estimates is reported as the percent relative error in a) accuracy, b) precision, and c) bias. Accuracy is a measure of how close an estimate is to the true abundance (i.e., a combination of precision and bias). Precision is a measure of how repeatable an estimate is. Bias is a measure of whether or not estimates are consistently higher or lower than the true abundance. Points indicate mean values and vertical bars represent 1 standard deviation.

Figure 4.4. Posterior distributions of A) counter up and B) down accuracy, C) species proportions moving up stream and d) downstream, and E) estimated spawner abundance. Uniform prior distributions were used for A-D. The estimated spawner escapement represents the number of fish that passed over the counter while accounting for uncertainty in counter accuracy and the proportion of fish that were identified as the target species. The red line is the true abundance and the solid black line is the mean estimated spawner abundance. The broken black lines indicate the upper and lower bounds of the 2.5 and 97.5% credible interval.

Figure 5.1. Flow diagram of the decision and cost model.

Figure 5.2. Map of Scottish rivers visited by IFR, October 2014.

Figure 5.3. Potential counter site visited by IFR on River Avon, a major tributary of the River Spey.

Figure 5.4. A potential counter site on the River Avon, October 2014. Photo courtesy of InStream Fisheries Research.

Figure 5.5. Potential counter sites visited by IFR on River Ness.

Figure 5.6. A potential counter site on the River Ness, October 2014. Photo courtesy of InStream Fisheries Research.

Figure 5.7. Potential counter sites visited by IFR on Little Gruinard River.

Figure 5.8. A potential counter site on the Little Gruinard River (Site 1), October 2014. Photo courtesy of InStream Fisheries Research.

Figure 5.9. A potential counter site on the Little Gruinard River (Site 2), October 2014. Photo courtesy of InStream Fisheries Research.

Figure 5.10. Potential counter sites visited by IFR on River South Esk.

Figure 5.11. Clova Bridge, a potential counter site on River South Esk. This picture shows river upstream of bridge. Photo courtesy of InStream Fisheries Research.

Figure 5.12. Clova Bridge, a potential counter site on River South Esk. This picture shows river downstream of bridge. Photo courtesy of InStream Fisheries Research.

Figure 5.13. Prosen Bridge, a higher gradient section of the Prosen Water, a potential counter site for River South Esk. This picture shows upstream of the bridge. Photo courtesy of InStream Fisheries Research.

Figure 5.14. Prosen Bridge, a higher gradient section of the Prosen Water. A potential counter site for River South Esk. This picture shows downstream of the bridge. Photo courtesy of InStream Fisheries Research.

Figure 5.15. South Esk weir, a potential counter site for River South Esk. A small fish pass exists in the middle of the fish weir. Photo courtesy of InStream Fisheries Research.

Figure 5.16. South Esk footbridge, a potential counter site for River South Esk. A footbridge downstream of the South Esk weir site. Photo courtesy of InStream Fisheries Research.

Figure 5.17. Potential counter sites visited by IFR on River Lochy.

Figure 5.18. River Lochy canal pool, a potential counter site for River Lochy. Photo courtesy of InStream Fisheries Research.

Figure 5.19. Potential counter site visited by IFR on River Dee.

Figure 5.20. River Dee at Portarch Bridge, a potential counter site for River Dee. Photo courtesy of InStream Fisheries Research.

Figure 5.21. Potential counter site visited by IFR on River Polla.

Figure 5.22. River Polla, upstream of the stone bridge near the ocean confluence. Photo courtesy of InStream Fisheries Research.

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