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Brown Trout Spawning Migration in Fragmented Central European Headwaters: Effect of Isolation by Artificial Obstacles and the Moon Phase a
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Ondřej Slavík , Pavel Horký , Tomáš Randák , Pavel Balvín & Michal Bílý
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Water Research Institute Tomáš Garrigue Masaryk, Department of Applied Ecology, Podbabska 30, 160 00, Prague 6, Czech Republic b
Faculty of Fisheries and Protection of Waters, South Bohemian Research Centre of Aquaculture and Biodiversity of Hydrocenoses, University of South Bohemia, České Budějovice, Czech Republic c
Water Research Institute Tomáš Garrigue Masaryk, Department of Hydrology, Podbabska 30, 160 00, Prague 6, Czech Republic Available online: 17 May 2012
To cite this article: Ondřej Slavík, Pavel Horký, Tomáš Randák, Pavel Balvín & Michal Bílý (2012): Brown Trout Spawning Migration in Fragmented Central European Headwaters: Effect of Isolation by Artificial Obstacles and the Moon Phase, Transactions of the American Fisheries Society, 141:3, 673-680 To link to this article: http://dx.doi.org/10.1080/00028487.2012.675897
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Transactions of the American Fisheries Society 141:673–680, 2012 C American Fisheries Society 2012 ISSN: 0002-8487 print / 1548-8659 online DOI: 10.1080/00028487.2012.675897
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Brown Trout Spawning Migration in Fragmented Central European Headwaters: Effect of Isolation by Artificial Obstacles and the Moon Phase Ondˇrej Slav´ık* and Pavel Hork´y Water Research Institute Tom´asˇ Garrigue Masaryk, Department of Applied Ecology, Podbabska 30, 160 00, Prague 6, Czech Republic
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Tom´asˇ Rand´ak Faculty of Fisheries and Protection of Waters, South Bohemian Research Centre of Aquaculture and Biodiversity of Hydrocenoses, ˇ e Budˇejovice, Czech Republic University of South Bohemia, Cesk´
Pavel Balv´ın Water Research Institute Tom´asˇ Garrigue Masaryk, Department of Hydrology, Podbabska 30, 160 00, Prague 6, Czech Republic
Michal B´ıl´y Water Research Institute Tom´asˇ Garrigue Masaryk, Department of Applied Ecology, Podbabska 30, 160 00, Prague 6, Czech Republic
Abstract The spawning migrations of 123 brown trout Salmo trutta were studied in six highland streams in the Elbe River catchment area, Czech Republic, in central Europe. Trout were observed by using radiotelemetry from August to November in headwater stretches isolated by artificial obstacles without fish ladders. The length of isolated headwater stretches ranged between 5.7 and 16.1 km. Migration distance per day and total migration length over the study period (total migration) were analyzed. In total, 1,957 individual fish positions were recorded. In general, the brown trout spawning migration reflected the seasonality with respect to temperature. Migration distance per day was low in August, reached a maximum in October, and then decreased in November. In isolated headwaters, trout adapted their migrations to the length of available free migration stretches, as both migration descriptors (migration distance per day and total migration) increased according to this variable. Moon phase appeared to be the key factor that influenced the timing of brown trout migration activity on a daily basis. High migration distance per day occurred during the eclipse of the moon, whereas the lowest migration distance per day occurred during the full moon. Furthermore, migration distance per day decreased with increasing river slope. The other variables tested (sex and physicochemical parameters, such as flow, pH, conductivity,
and dissolved oxygen) did not affect brown trout migration activity. The results indicated that despite the restrictions of upstream migrations by lateral obstacles without fish ladders, brown trout migration activity in artificially isolated headwaters with pristine morphology is preserved. Furthermore, the analyses revealed a significant impact of the moon phase on brown trout migration that has not been previously described for this species. Although the observed migration occurred over a short period of time, brown trout did not adopt sedentary behavior, as has been described in the river stretches upstream from natural obstacles, such as waterfalls.
Migrations of landlocked brown trout Salmo trutta in lotic environments and between lotic and lentic environments have been described across large areas of the species’ range. Although migratory behavior is genetically determined (Northcote 1981, 1992; Jonsson 1982; Elliott 1989), local conditions can influence an individual trout’s decision about whether to migrate, thereby forming residential and migratory phenotypes in the populations (Jonsson 1985; Hindar et al. 1991; Jonsson and Jonsson 1993; Hendry et al. 2004). However, the response to environmental variability varies within the entire population (Solomon and Templeton 1976; Heggenes et al. 1991; Gowan
*Corresponding author: ondrej
[email protected] Received March 30, 2011; accepted December 3, 2011
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et al. 1994); for example, larger individuals often move longer distances (Hesthagen 1988; Young 1994) and are able to pass over larger obstacles (Aass et al. 1989). In general, migration is influenced by food availability (Wysujack et al. 2009; O’Neal and Stanford 2011), growth rate (Jonsson 1985; Hindar et al. 1991), population density (Jonsson and Jonsson 1993; Olsson and Greenberg 2004), and social hierarchy (H¨ojesj¨o et al. 2007). Spawning migrations of landlocked brown trout populations are usually the longest movements for this species within an annual period (Young 1994; Ovidio et al. 1998; Rustadbakken et al. 2004; Zimmer et al. 2010). Some populations, or portions of populations, also undertake extensive migrations in the spring and summer to reach feeding habitats (Clapp et al. 1990; Gowan and Fausch 1996; Carlsson et al. 2004). Salmonids occupying headwaters isolated by natural obstacles, such as waterfalls and rapids, or river stretches isolated by artificial dams often show unique population characteristics (Northcote 2010). Fish from isolated areas are smaller (Jonsson and Sandlund 1979; Northcote and Hartman 1988; Carlsson et al. 2004), grow more slowly (Northcote 1981; Carlsson et al. 2004), and may have lower population densities (Jonsson and Sandlund 1979; Northcote and Hartman 1988) and fecundities (Northcote and Hartman 1988), shorter life spans (Jonsson and Sandlund 1979), and different spawning periods (Jonsson 1982; Northcote and Hartman 1988) compared with those of conspecifics from typically downstream, nonisolated stretches. In addition, their spawning migrations may be weak, similar to postspawning downstream migrations (Jonsson and Sandlund 1979; Northcote and Hartman 1988; Northcote 1992). Although spawning migrations of brown trout have been widely documented (e.g., Young 1994; Ovidio et al. 1998; Zimmer et al. 2010), only limited information is available about salmonid migrations in isolated and fragmented headwaters. We analyzed the length and timing of brown trout spawning migrations in six highland streams. The study sites were located in headwater stretches in the Elbe River catchment area, Czech Republic, in central Europe. The stretches were isolated by artificial migratory obstacles without fish ladders. Thus, the maximal theoretical upstream migration distances corresponded with the length of these headwater stretches delineated by a river source and the first lateral obstacle without fish ladders situated downstream from the river source. We assumed that the length of migration would increase according to the length of available stretch studied. Furthermore, the timing of reproductive activities (including spatial changes in fish distribution) in many fish species is synchronized with the moon phase (see Takemura et al. 2010 for a review); hence, we analyzed the relationship between the moon phase cycle and the brown trout spawning migration. The effects of additional variables (e.g., slope, flow, temperature, pH, conductivity, dissolved oxygen, and sex) on brown trout migration were also tested.
TABLE 1. Total length of streams and study sites and the number of migration obstacles, including coordinates of the first migration obstacle limiting the study site.
Stream Blanice Zlat´y potok Luˇzn´ı potok Volsbach Vltava Otava
Stream Study site Number length length of (km) (km) obstacles 94.7 36.7 8.5 5.7 54.3 23.7
12.3 15.7 8.5 5.7 16.1 13.8
54 8 0 0 13 2
Coordinates 48◦ 57 N, 13◦ 56 E 48◦ 55 N, 14◦ 4 E 50◦ 18 N, 12◦ 7 E 50◦ 18 N, 12◦ 6 E 49◦ 00 N, 13◦ 37 E 49◦ 10 N, 13◦ 30 E
METHODS Study site.—Brown trout migrations were observed in six highland streams located in the Elbe River catchment area, Czech Republic (Figure 1), where the pristine character of the riverbed is maintained without flow regulation. All evaluated streams contained low nutrient levels. The study sites were headwater stretches situated between the river source and the first migratory obstacle on the particular stream (Table 1). Migratory obstacles without fish ladders were impassable for upstream fish migration. Precise data on the origin of migratory obstacles and their ages are not available. However, their existence may be attributed to the construction of water-powered sawmills during the 19th and early 20th centuries, suggesting hundreds of years of impact of these obstacles on the trout populations. No stream sections had any excessive slope or other unusual conditions that would create an obstacle for fish migration in the longitudinal profile of the streams. Sampling procedures.—A total of 130 brown trout (Table 2) were caught by electrofishing (pulsed DC, 650 V, 4 A). The fish were anesthetized with 0.2 mL/L of 2-phenoxyethanol, measured (standard length [SL]; mm), and weighed (g). The fish were caught in upstream areas adjacent to the first migration obstacle in the studied stretch. Three types of radio transmitters were used throughout the study: (1) MCFT 3HM, 2 g in air, 9.2 × 20 mm, with an operational life of approximately 52 d; (2) MCFT 3D, 3.7 g in air, 10 × 29 mm, with an operational life of approximately 90 d; and (3) NTC-4–2 L, 2.1 g in air, 8.3 × 18.3 mm, with an operational life of approximately 87 d (Lotek, Newmarket, Ontario). The types of transmitters available from the manufacturer differed over the duration of our study (a 5-year period). The MCFT 3HM transmitters were programmed for a 12-h operating period (0800–2000 hours) to extend their operational life. Radio transmitters were implanted into the body cavities of brown trout through a midventral incision that was closed with three separate stitches with sterile braided absorbable sutures (Ethicon Coated Vicryl). The mass of the transmitter never exceeded 2% of the body mass of the
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NOTE TABLE 2.
Characteristics of tagged specimens (standard length [SL] and weight ranges; means in parentheses) and study periods.
Stream
SL (mm)
Weight (g)
30 30 15 15 20 20
185–255 (208) 185–258 (200) 182–230 (196) 183–215 (203) 180–272 (178) 196–307 (229)
103–200 (130) 100–261 (125) 106–179 (112) 103–147 (116) 100–300 (148) 140–231 (178)
Study period Aug 13–Nov 10, 2004 Aug 7–Nov 11, 2005 Aug 10–Nov 10, 2006 Aug 10–Nov 15, 2005 Aug 15–Nov 15, 2002 Aug 15–Nov 15, 2001
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Blanice Zlat´y potok Luˇzn´ı potok Volsbach Vltava Otava
Number of tagged specimens
FIGURE 1. Study sites in the Elbe River catchment area, Czech Republic, in central Europe: (A) Central Europe, showing the Elbe River catchment area (light gray); (B) the Czech Republic, showing the Elbe River upper catchment area (light gray) and the area in which the study sites are located (dark gray); and (C)–(D) details of the study sites indicated in (B).
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TABLE 3. Characteristics of the river stretches (ranges of values; means in parentheses).
Stream
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Blanice Zlat´y potok Luˇzn´ı potok Volsbach Vltava Otava
Temperature (◦ C)
Flow (m3/s)
Slope (m/km)
pH
5.0–16.4 (10.7) 5.9–18.3 (9.3) 5.9–8.9 (7.6) 6.2–14.7 (8.9) 2.9–10.8 (6.8) 6.8–8.3 (6.9)
0.20–11.0 (2.10) 0.01–0.20 (0.10) 0.07–0.10 (0.09) 0.09–0.30 (0.10) 1.40–8.10 (3.90) 2.20–2.60 (2.30)
0.57 0.36 0.70 1.00 1.20 2.60
7.0–7.9 (7.5) 6.6–7.2 (7.0) 6.7–7.6 (7.2) 6.4–7.5 (6.9) 5.8–6.9 (6.4) 5.7–6.2 (5.8)
fish (mean tag ratio, 1.68%; range, 0.7–2%; Winter 1983). The fish were released at or near the point of capture after they recovered and exhibited spontaneous swimming activity (∼5 min after surgery). At all the study sites, tracking series were carried out from August to November (Table 2). All of the fish were tracked twice a week during a 4-h period (1000–1400 hours) by using a radio receiver (Lotek SRX 400 receiver firmware version W31) and a three-element Yagi antenna equipped with a compass. Compass bearings were taken on the transmitter direction from locations positioned with the help of a Global Positioning System (GPS map 76S, Garmin, Olathe, Kansas). A computer program was developed to obtain fish position coordinates and plot them on a map by using the biangulation method proposed by White and Garrott (1990). Habitat measurements.—Water temperature (◦ C), dissolved oxygen (mg/L), pH, and conductivity (µS/cm) were measured by using microprocessors (Oxi 196 WTW, pH/Cond 340i SET) throughout the study during the days when fish were tracked (Table 3). Flow (m3/s) was measured at a hydrometric profile on a tracking day or at the gauging station located within the study stretch where the Vltava River Authority measures flow daily. The river slope (%) was measured by using the Pulse Total Station (Topcon GPT 2000, Itabashi, Tokyo, Japan) and was determined for the stretches delineated by fish migrations or movements. The river slope was considered to be the difference between water levels in two adjacent stream cross sections (Boiten 2000). Data analyses.—Data from 123 brown trout were included in our statistical analyses. Eurasian otters Lutra lutra caught six
Dissolved oxygen (mg/L) Conductivity (µS/cm) 6.7–11.0 (8.9) 6.7–11.0 (9.4) 7.9–9.8 (9.2) 7.3–10.2 (9.7) 6.7–11.5 (10.3) 7.3–11.0 (8.5)
85–112 60–116 72–161 87–174 35–55 22–27
(96.3) (99.3) (112.0) (125.0) (44.5) (25.0)
individuals, and one fish died during the first month of the study. These fish were excluded from further analyses. The tracking series were generally carried out every third day of each week. However, owing to technical problems, it was not possible to permanently maintain the same time period between two consecutive tracking series. Thus, some tracking series were carried out after 2 or 4 d. To assure the comparability of the data, movement was divided by the number of days between two consecutive tracking series, referred to as “migration distance per day” (see Table 4). The “total migration” of specimens was computed as the distance between the fish’s two farthest positions during the entire study period. To ensure that migration distance per day and total migration were independent of length (SL), “migration distance per day corrected by fish length” and “total migration corrected by fish length” were calculated by dividing both by the individual fishs’ SLs (Aarestrup et al. 2005). In further analyses, we used values correcting for fish length only. Statistical analyses.—Associations between the variables were tested by using a linear mixed model (LMM). Separate models were applied for the following dependent variables: migration distance per day per fish length (LMM I) and total migration per fish length (LMM II). The data were transformed for normality before LMM analysis when needed. To account for repeated measures, all analyses were performed by using a mixed model with random factors (PROC MIXED, SAS, Version 9.1; SAS Institute, www.sas.com). The random factors were individual fish, date nested within individual fish, and study site nested within individual fish. The fixed effects included the classes: month (four levels), moon phase (eight levels), and
TABLE 4. Values of computed brown trout linear ranges and movements in the streams (ranges of values; means in parentheses).
Stream Blanice Zlat´y potok Luˇzn´ı potok Volsbach Vltava Otava
Total migration (m)
Total migration per fish length (m)
Migration per day (m)
Migration per day and fish length (m)
6–1,096 (308) 93–1,236 (383) 58–330 (199) 7–64 (38) 16–4,325 (1,025) 22–502 (302)
0.1–5.8 (1.5) 0.4–5.9 (1.9) 0.3–1.7 (1.0) 0.1–0.3 (0.2) 0.1–35.2 (6.5) 0.1–2.5 (1.4)
0–555 (33) 0–183 (13) 0–46 (4) 0–10.4 (3) 0–2,100 (34) 0–247 (16)
0–2.6 (0.2) 0–0.1 (0.1) 0–0.2 (0.1) 0–0.1 (0.1) 0–14 (0.2) 0–1.2 (0.1)
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sex (two levels). Continuous variables included water temperature (2.9–18.3◦ C), flow (0.01–11 m3/s), slope (0.36–2.6 m/km), pH (5.7–7.9), dissolved oxygen (6.7–11.5 mg/L), and conductivity (22–174 µS/cm). The significance of each fixed effect (including interactions) in the LMMs was assessed by using an F-test in which we sequentially dropped the least significant effect beginning with the full model (backward selection procedure). Fixed effects and their interactions that were not statistically significant are not discussed further. Least-squares means (LSM), henceforth referred to as “adjusted means,” were computed for each class, and differences between classes were tested with a t-test. For multiple comparisons, we used a Tukey– Kramer adjustment. Associations between the dependent variables and other continuous variables were estimated by fitting a random coefficient model by using PROC MIXED as described by Tao et al. (2002). With this random coefficient model, we calculated predicted values for the dependent variables and plotted them against the continuous variables by using predicted regression lines. The degrees of freedom were calculated by using the Kenward–Roger method (Kenward and Roger 1997). RESULTS In total, we analyzed 1,957 records of brown trout positions. Migration distance per day ranged from 0 m to 2,100 m, and total migration ranged from 6 m to 4,325 m (Table 4). Final significant LLMs contained the fixed factors of month, moon phase, interaction between slope and length of available stretch for migration distance per day per SL, and length of available stretch for total migration per SL (Table 5). The brown trout spawning migration generally reflected seasonality with respect to the temperature. Migration distance per day per SL increased with decreasing temperature from August to October and then declined in November (Figure 2). Isolation by artificial migratory obstacles caused the trout to adapt their migrations to the lengths of the available free migration stretches. Total migration per SL (Figure 3) as well as migration distance per day per SL (Figure 4) increased according to this
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FIGURE 2. Differences in movement per day per fish standard length (SL) (open bars; adjusted means ± SEs of square-root-transformed [Sqrt] data) and temperature (solid triangles; means ± SEs) per month.
variable. Migration distance per day per SL (Figure 4) decreased with increasing river slope. In contrast, slope did not influence total migration per SL, suggesting that there were no excessive slope values that would prevent fish from longer migrations. Our results revealed a significant relationship between the moon phase cycle and brown trout spawning migration, as migration distance per day per SL matched up with the moon phase cycle (Figure 5). The movements varied gradually and were at their highest during the new moon and their lowest during the full moon, suggesting that lunar periodicity is the key factor influencing the timing of brown trout spawning migrations on a daily basis. Migration activity was not influenced by the other variables tested (i.e., flow, pH, conductivity, dissolved oxygen, and sex).
TABLE 5. Type 3 tests of fixed effects for final significant linear mixed models (LMMs); SL = standard length.
Effect
Numerator Denominator df df
F
P-value
LMM I (migration distance per day per SL) Month 3 1,948 10.07
