Reports from DIDSON work in Karasjohka 2010
Report I Use of DIDSON to estimate spawning run of Atlantic salmon in the River Karasjohka, the tributary of the River Tana
Juha Lilja1 & Panu Orell1
1) Finnish Game and Fisheries Research Institute, Finland
Report II Evaluation of the counting system DIDSON in Karasjohka 2010
Helge Balk1, Johanna Järnegren2 & Gry Haraldsson1
1) University of Oslo, Norway 2) Norwegian Institute for Nature Research, Norway
Use of DIDSON to estimate spawning run of Atlantic salmon in the River Karasjohka, the tributary of the River Tana
Juha Lilja1 & Panu Orell1
1) Finnish Game and Fisheries Research Institute, Finland
Contents Abstract ...... 2 1 Introduction ...... 3 2 Materials and methods ...... 4 2.1 Study site ...... 4 2.2 DIDSON sounder ...... 9 2.3 DIDSON data collection and analysis ...... 10 2.3.1 On-site data processing ...... 10 2.3.2 Time expansion of the counting result ...... 10 2.3.3 Inter person calibration and variance estimation ...... 11 2.4 Auxiliary information supporting the monitoring ...... 12 2.4.1 Underwater video camera ...... 12 2.4.2 Catch data ...... 12 3 Results and discussion ...... 17 3.1 Daily counts and escapement estimate ...... 17 3.2 Length distribution of fish ...... 18 3.3 Migration route and time ...... 19 3.4 Species composition based on the video surveillance ...... 21 3.5 Precision of estimates ...... 22 4 Conclusion – fulfilment of spawner reference level ...... 23 5 References ...... 25
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Abstract
Spawning run of Atlantic salmon (Salmo salar) in to the River Karasjohka was counted with DIDSON sonar between 9th June and 31st August in 2010. Altogether 90 % of the total monitoring time was covered by soundings and there was only one longer period when the DIDSON was not an optimal position. The expanded fish escapement estimate through the counting site was 661 (±48) multi-sea-winter (MSW) salmon (length ≥ 67.5 cm) and 1016 (±51) upstream fish with a size of 50 – 67.5 cm. Thus, the total escapement estimate through that site was 1677 (±56) fish in 2010. Most of fish migrated upstream on the deepest part of the river. A sample variance estimator based on differences between counters led ±6 % and ±4 % (95 % confidence limits) for MSW salmon and grilse, respectively. According to video recordings, the proportion of salmon was 94 % in size category 50-65 cm and all fish longer than 65 cm were judged to be salmon. Sea-trout (Salmo trutta), whitefish (Coregonus lavaretus) and grayling (Thymallus thymallus) were other species, which were detected on site.
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1 Introduction
Reliable data on the number of salmon entering tributaries of the Tana River to spawn (escapement) is needed for developing a suitable fisheries management concerning the whole river system. Hydroacoustic methods are typically used to assess abundance in migrating fish populations when other methods are not feasible, e.g. the river is too wide for counting weirs or too turbid for visual observation. Moreover, sonar counts are usually the best choice compare to other salmonid escapement techniques (Parsons and Skalski 2010). Dual-frequency Identification Sonar (DIDSON) has been available on the market for some years and it has been proven to be a suitable equipment to observe and count migrating fish (Holmes et al. 2005, Cronkite et al. 2006, Enzenhofer et al. 2010, Lilja et al. 2010). The DIDSON sounder produces underwater video image using sound. This means that it is not dependent on light or good visibility in order to function well. The quality of the images produced can also be very good, allowing observations of size and direction as well as behavior, images that can tell what is fish and what is not. The unit is very manageable in size, easy to handle and reliable in use. However, there are also limitations to this system that needs to be considered, especially when using it out in large rivers and over long periods of time. However, the DIDSON, like other sonars and echo-sounders have a detection probability function which depends on range. This is controlled by the underlying volume and signal to noise ratio functions, the first increasing and the second decreasing with range. It is thus, important to determine the part of the beam that has the best detection probability and avoid the other areas by applying guiding nets or applying alternative assessment methods for these areas.
The River Tana is a large river, which flows between Norway and Finland. In the main stem of the Tana, the potential counting site for DIDSON was found in Tana bru, where the river bottom was quite uniform without large rocks or boulders obstructing of the acoustic beams. However, an optimal DIDSON operation in Tana bru requires at least two units and high initial costs. In 1997- 99, the split-beam echosounder was used to count ascending salmons in to the main stem of the Tana. The counting site was situated in Polmak, about 56 km from the river mouth. At the site the river is more than 130 m wide, and thereby requires also at least two DIDSON units to cover the whole river.
The salmon stock of the River Karasjohka is supposed to be rather large including significant component of multi-sea-winter (MSW) Atlantic salmon. However, in recent year concerns have arisen about the status of Karasjohka salmon, but no reliable information on the spawning escapement is available from the system. In this study, we used a DIDSON unit with guiding nets in order to cover the entire river cross section. Auxiliary information such as video camera and catch data were used to support and confirm the DIDSON counts. The escapement estimate of salmon spawning run through the counting site was also produced.
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2 Materials and methods
2.1 Study site
The subarctic River Tana flows between Norway and Finland and it is one of the largest (catchment area about 16 400 km2) and the most productive Atlantic salmon river of both countries, whereas the River Karasjohka is one of the most important tributary system of the River Tana with a catchment area of >5000 km2. In 2010, sites suitable for DIDSON monitoring were sought on the lower part of the River Karasjohka. At first, potential river sections were chosen from a map and on-site inspections were done at several places, basically almost all narrow passages were examined. The suitability of potential sites for DIDSON sounders was estimated using the criteria given by Enzenhofer and Cronkite (2000). Below the confluence of the rivers Karasjohka and Iesjohka, the river was too wide to monitor fish migrations with only one DIDSON unit. Thus, the site was sought above the confluence and a potential site was found in Heastánjarga area. This site is located approximately 5 km upstream from confluence of the rivers Karasjohka and Iesjohka (Fig. 1). The river is approximately 40 m in wetted width with a maximum depth of 1.5 m at the acoustic site (depending on water level). At the site, the bridge crosses over the river and the river bottom was quite uniform without large rocks or boulders that may interfere with the path of the acoustic beam or create turbulent flow. Generally, the success of DIDSON in counting upstream migrating salmons depends primarily on two basic prerequisites; 1) deployment of the system on a site that enables recording of representative and high-quality images, and 2) accurate and precise measurement of fish during the data post-processing.
The River Karasjohka DIDSON site is situated in northern latitudes (69° 23’ 50” N, 25° 08’ 40” E), where the sun is above the horizon all day during the summer. At the beginning of the monitoring period, the second week of June, there were not sunset or sunrise at the site (Fig. 2). Thus, it was possible to use under water video camera in parallel with DIDSON and compare counts also during the night time. The first time the sunset occurred on 25th July, whereas the end of the study period the sun was already below the horizon more than 8 h 30 min.
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Figure 1. A map of the River Tana watershed and the DIDSON site in the River Karasjohka.
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Figure 2. The time of sunrise and sunset at the River Karasjohka area in 2010. The study period between dotted lines.
The DIDSON system was deployed on an adjustable tripod on the east bank of the river approximately 10 m from shore and about 15 m upstream from a bridge across the river (Fig. 3). The sonar beams were aimed towards the middle channel and guiding nets were used on both shores to lead fish to the DIDSON view and prevent to fish swim too close to the sonar. The system was positioned so that the lens was approximately 40 cm below the water surface and the transducer was tried to aim at near -7° angle relative to the water surface and perpendicular to the shoreline and water flow. Using this aim, the upper edge of beams followed the water surface and the lower edge reached the bottom so the DIDSON beams ensonified the entire 17 m weir opening.
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24 21 18 15 12 9 6 3 0 -3 -6 -9 0
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1 Depth (m) Depth
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Distance from DIDSON (m) 2 Figure 3. DIDSON site in the River Karasjohka, about 10 m upstream from the bridge across the river. DIDSON sounder was the east side (right) of the river and the video camera in the middle of the channel. The bottom profile measured on June-10, 2010.
The bottom profile across the river was generated from DIDSON data according to protocol from Maxwell and Smith (2007). During the measurement of the bottom profile the DIDSON was deployed near shore and aimed perpendicular to the river current with the multiple beams positioned in the vertical plane so the sounder was turned 90° compared to normal data collection. The vertical beam opening was compressed from 14° to 1° using an optional concentration lens in order to receive less noise and accurate signal from the bottom. The bottom of the counting site was also inspected by diving (Fig. 4). The vertical boundaries of the beams were confirmed by observing the image from the substrate and also from images where a salmon size target was lifted from bottom to the surface, at various ranges from the DIDSON system (Fig. 5).
Topside equipment such as laptop computers controlling the acoustic systems and the video camera were housed in a trailer, which was placed on the east shore of the river. All electronic components and the acoustic systems were powered by 220 V mains current and all valuable and sensitive equipment were secured against overvoltage using an uninterruptible power supply (UPS).
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Figure 4. DIDSON tripod and guiding nets in the river Karasjohka. The bottom of the counting site was inspected by diving.
Figure 5. An artificial target that was lifted from bottom to the surface in order to confirm vertical boundaries of the DIDSON beams.
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2.2 DIDSON sounder
Long range (LR) DIDSON acoustic imaging system was used at the counting site. As well as a standard version, the long range DIDSON is capable of utilizing two different frequencies (modes) for data collection. When operated at high frequency mode (HF = 1200 kHz), the maximum window length setting permitted is 20 m, although the start length can be set at up to 13 m which provides viewing out to a maximum of 33 m. If this distance is inadequate, switching to low frequency mode (LF = 700 kHz) will be necessary. When operated at LF, the window length setting can be increased to 40 or 80 m. In the River Karasjohka, DIDSON acoustic imaging system was used in high frequency mode (1.2 MHz) for data collection. In this mode the system utilises multiple sound beams focused through a moveable lens to produce near video quality images comprised of frames produced by 48 beams (Fig. 6). A frame (image) is constructed in sequence and consists of 4 sets of 12 beams fired simultaneously (Sound Metrics Corporation 2010). Each beam is 0.6° wide and together produce a nominal field of view 29° horizontally and 14° vertically. In order to build up a digital image, each beam was divided in 512 segments (sample) in longitudinal direction, and the image is constructed by echo-intensity values in the matrix of 48 by 512 (Fig. 5).
Figure 6. A schematic picture (from above) of a DIDSON frame (image) and a snapshot of the DIDSON screen where two salmon were swimming from right to left.
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2.3 DIDSON data collection and analysis
2.3.1 On-site data processing
In 2010, DIDSON acoustic data were collected between 9th June to 31st August and total coverage was 90% of available sample time. There was only one longer period when the DIDSON was not an optimal position. The rainy weather on 22nd July caused a floodwater and the DIDSON unit was fallen over. It took about 5 days before the system was on the original position again. Otherwise, there were only a few short periods when the DIDSON did not operate caused by the problems in electricity supply.
The DIDSON sounder was programmed to create new files (time and date stamped) beginning at the top of the hour. All data were recorded and post-processing of fish counts was made using Version 5.25 of the DIDSON operating system software (Sound Metrics Corporation 2009). DIDSON data was saved to external hard drives, creating two identical copies that were adequate for archiving and storage purposes.
The display images used for upstream and downstream counts were analyzed using background subtraction. This subtraction removed the static portion of the acoustic image, showing only objects in motion. Removing the background allowed for easier fish detection. The following procedure was used to compile fish count and length measurements from DIDSON files: • Files were played back with the background subtraction. The play back frame rate depended on the original data collection frame rate but was usually 10 times faster than the original frame rate. • Once a fish was detected the file was paused (freeze-frame) and a box was drawn around the image to allow magnification of the image. • Frames which contained the fish image were stepped through one at a time until the clearest image was attained. • The Mark Fish option was enabled to provide a cursor with which the fish length could be measured, its range marked and then entered to a fish count file. • Play back was continued and the next fish was sought.
Once the DIDSON-files were screened and fish were measured, two data sets were constructed; 1) all measured fish were collected into the same file (RAW-fish file), and 2) hourly passages for fish larger than 67.5 cm (MSW) as well as fish in length class 50 – 67.5 cm (grilse) were summed up (Hourly-fish file).
2.3.2 Time expansion of the counting result
Daily estimates were counted by summing the 24 hourly counts starting from midnight. Moreover, the daily numbers were summed up over the study period resulting the estimate of the total escapement. Salmon counts for unsampled time periods were expanded into the hourly counts. The following strategies were used for expanding counts across the unsampled time periods. First, when the sounder was not operating a whole hour but more than 6 min (10%) per hour, the hourly passage estimate was obtained by expanding the results over the unsampled time. Second, when one or more hours per day were missing, the estimate for a given hour ( ) was averaged from previous and next day counts made during the same hour. This method took into account a diurnal pattern of salmon
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run through the counting site. Three, when the data of the whole day or days were missed, the estimate for given day ( ) was calculated as weighted mean from daily counts of a few days before and after the interpolated day.
2.3.3 Inter person calibration and variance estimation
Comparing DIDSON counts between observers is necessary for estimating observer error and is maintained as part of the standard approach to quality control (precision). In all 93 hours (files) were counted by two observers in 2010. Selected data set was picked up using a random sampling design by weighting the days when fish were observed (Appendix 1). Both Finnish and Norwegian observers analysed the data set and the fish numbers were compared.
Three quantifiable sources of error were recognized in this monitoring design. First, the variance caused by interpolated hourly counts (Var( )), and second, the variance for counts that were estimated in situation when whole day was interpolated (Var( )). Third, the variance caused by counters (Var( ̂)). Owing to large amount of data compare to interpolated values, the variance estimators for Var( ) and Var( ) could be calculated using a measured variation between given counts (population variance). Var( ̂) was estimated (sample variance) from double-checked data (Wolter 1985). The estimate of variance for the total escapement estimate Var( ) was the sum of those variance components.