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Behavioural variation in cultivated juvenile Atlantic cod (Gadus morhua L.) in relation to stocking density and size disparity
Applied Animal Behaviour Science 117 (2009) 201–209
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Applied Animal Behaviour Science journal homepage: www.elsevier.com/locate/applanim
Behavioural variation in cultivated juvenile Atlantic cod (Gadus morhua L.) in relation to stocking density and size disparity Ingebrigt Uglem a,*, Elin Kjørsvik a, Ka˚re Gruven b, Anders Lamberg c a
Norwegian University of Science and Technology, Department of Biology, N-7491 Trondheim, Norway AKVAgroup ASA, Ladebekken 17, N-7048 Trondheim, Norway c Lamberg Bio-Marin Service, Ranheimsveien 281, N-7054 Ranheim, Norway b
A R T I C L E I N F O
A B S T R A C T
Article history: Accepted 19 January 2009 Available online 13 February 2009
The aim of this study was to examine the behaviour and activity of Atlantic cod (Gadus morhua) juveniles (65–120 mm total length) in relation to varying stocking density (500–2000 fish per m3) and size disparity under both experimental and commercial hatchery conditions. This was done by using stereovideography to measure fish size and to quantify fish behaviour in situ. The swim pattern was more synchronized at higher fish densities (both experimental and commercial conditions), indicating a more pronounced schooling behaviour and possibly also indirectly reduced activity costs and stress levels with increasing fish density. Furthermore, the swim pattern became less synchronized and the relative swim speed increased as fish size disparity increased. This might indicate both elevated energetic activity costs and an augmented stress level with increasing size disparity. However, overt agonistic behaviour was nearly absent at the examined fish densities and size disparities, and negative social interactions are thus unlikely to represent a major cost under such conditions. The general absence of overt agonistic behaviour and the lack of behavioural variation indicative for extreme levels of stress or activity might suggest that the welfare status of the juveniles was not compromised under the examined conditions. ß 2009 Elsevier B.V. All rights reserved.
Keywords: Atlantic cod Gadus morhua Aquaculture Activity costs Welfare Behaviour
1. Introduction Technology for the cultivation of Atlantic cod (Gadus morhua) is constantly developing, and commercial cod farming is increasing in countries such as Norway, Scotland, Ireland and Canada (Brooking et al., 2006; Moe et al., 2007). About 11,000 metric tonnes of farmed cod was produced in Norway in 2007 (statistics from the Norwegian Fisheries Directorate). The rearing of juveniles to a size that could be transferred to marine net pens in landbased tanks is still a critical part of cod culture.
* Corresponding author. Present address: Norwegian Institute for Nature Research, Tungasletta 2, No-7485 Trondheim, Norway. Tel.: +47 73901400; fax: +47 73801401. E-mail address: [email protected] (I. Uglem). 0168-1591/$ – see front matter ß 2009 Elsevier B.V. All rights reserved. doi:10.1016/j.applanim.2009.01.006
Optimisation of growth and survival during this phase is of major importance in order to reduce costs and to shorten the remaining period until the cod reaches market size. Increased knowledge about how behaviour and activity of cultured cod juveniles varies according to social conditions could contribute to the improvement of fish welfare and production efficiency; as such variations might correlate with individual stress level and energy consumption (e.g. Sayer, 1998; Morgan et al., 1999; Øverli et al., 2002; McFarlane et al., 2004; Salvanes and Braithwaite, 2006). It is well documented that both acute and chronic stress reduces individual growth and survival in fish culture (e.g. Handeland et al., 1996; Pickering, 1998; Ellis et al., 2002). Behavioural variation might also indicate impaired fish welfare (Sneddon, 2003), as were shown for Atlantic halibut (Kristiansen et al., 2004) and rainbow trout (Chandroo et al., 2004). Finally, behavioural variation is
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often associated with variation in fish growth rate, for instance through increased energetic expenditure during high activity levels as documented in rainbow trout (Li and Brocksen, 1977; Lefranqois et al., 2001) or because behavioural variation correlates with foraging intensity (Boisclair, 1992; Kristiansen et al., 2004). The variation in individual behaviour in fish culture is related to a range of factors, of which stocking density and individual size variations within a culture unit (size disparity) are two of the most important factors. Variation in stocking density might affect the efficiency of fish farming in several ways. An elevated stocking density may be preferable if it maximizes production capacity per culture volume. However, high densities have resulted in reduced growth rates in several fish species such as rainbow trout (e.g. Holm et al., 1990; Boujard et al., 2002; Ellis et al., 2002), Atlantic halibut (Bjoˆrnsson, 1994; Kristiansen et al., 2004), sea bass (Saillant et al., 2003), as well as in Atlantic cod (Lambert and Dutil, 2001). This trend is not unequivocal though, and studies of Atlantic salmon (Kjartansson et al., 1988), winter flounder (Fairchild and Howell, 2001), and European sea bass (Paspatis et al., 2003) have reported unaffected or even increasing growth rate (Arctic charr, as shown by Baker and Ayles, 1990; Siikavuopio and Jobling, 1995) with increased fish density. Increased stocking density may also reduce fish survival in aquaculture due to cannibalism (Baras and Jobling, 2002), as shown for winter flounder (Fairchild and Howell, 2001) and grouper (Hseu, 2002). The relationships between stocking density, foraging behaviour, growth and survival might be attributed to varying levels of dominance and agonistic behaviour (Lambert and Dutil, 2001). Variation in fish size within a population (size disparity) is another important decisive factor for growth and survival, and thus for production efficiency. In commercial farming, grading and sorting of fish according to size is routinely carried out. It is widely believed that size grading results in increased biomass gain, which might be explained by larger individuals being dominant and aggressive towards the smaller individuals, which in turn might lead to suppressed feed intake and/or reduced growth of the smaller fish (Efthimiou et al., 1994; Dou et al., 2004). However, several studies have reported that size grading in fact might lead to unchanged or decreased growth in adult Atlantic cod (Lambert and Dutil, 2001), Arctic charr (Jobling and Reinsnes, 1987; Baardvik and Jobling, 1990), perch (Melard et al., 1996) and turbot (Strand and Øiestad, 1997; Sunde et al., 1998). A large size disparity in a culture unit might under some circumstances also lead to increased mortality due to cannibalism (Baras and Jobling, 2002; Hseu, 2002; Stuart and Smith, 2003). The relationship between the behaviour of cultured fish, stocking density and size disparity is therefore not straightforward, even though it is thoroughly demonstrated that both stocking density and size variation are crucial factors, which through influencing the individual behaviour, might affect production efficiency in most types of fish farming. Little is known about behaviour of juvenile cod under commercial and large-scale culture conditions per se, or how behavioural variation relates to fish welfare
and stress level (Salvanes and Braithwaite, 2006). Experimental and small-scale studies with low stocking densities have, however, shown that early experiences during culture might affect shoaling, antipredator, foraging and agonistic behaviour of juvenile cod (Braithwaite and Salvanes, 2005; Salvanes and Braithwaite, 2005; Salvanes et al., 2007). Moreover, cod have been shown to be aggressive and cannibalistic during the early juvenile phase (Blom and Folkvord, 1997; Hoglund et al., 2005). The scope of this study was to investigate if variation in realistic stocking densities and size disparities for commercial culture of Atlantic cod juveniles were associated with behavioural variation indicative for fish welfare, stress level or energetic costs. In order to control for artefacts caused by experimental conditions we examined the behaviour and activity of cod juveniles both experimentally with stocking densities and size disparities similar to commercial production of cod juveniles and in a commercial cod hatchery. 2. Materials and methods Effects of size disparity and stocking density were examined in controlled small-scale experiments carried out at the NTNU Brattøra Research Center in Trondheim, Norway during two periods (03.05–07.06.2003 and 24.11– 12.12.2003). The studies at a commercial cod hatchery were carried out at Cod Culture Norway AS (then owned by Nutreco), situated on the Norwegian West Coast, during two periods (04.10–08.10.2002 and 30.09–3.10.2003). 2.1. Setup and design of the experimental study Cod juveniles were obtained from a local commercial hatchery (Fosen Aquasenter). The cod juveniles (total length: 90–120 mm, weight: 5–12 g) were allowed to acclimatise for 3–4 weeks before the trials were initiated. The experiments were carried out in six circular tanks (diameter: 0.95 m, height: 0.9 m, water depth: 0.55 m, volume: 390 l) with constant water circulation. Fish behaviour was recorded by video cameras through a transparent window in the tank wall (Lexan1 polycarbonate: 5 mm thickness, height: 0.5 m, width: 0.6 m). The video cameras were mounted within a non-transparent box that covered the window such that the light conditions in the tanks did not change during recording. The recordings were initiated 4–5 h after introduction of the cameras to give the fish time to recover after the disturbance caused by the positioning of the cameras. Each tank was constantly illuminated by a 25-W fluorescent tube positioned 1 m above the centre of the tanks. This created a light intensity of about 500 lx at the water surface, which was similar to light conditions at a commercial hatchery. The water temperature varied between 8.5 and 9.5 8C during the first period and between 9.5 and 10 8C during the second period. The salinity was 35–36 ppt, and the oxygen concentration ranged from 8.1 to 9.4 mg l1 (oxygen saturation: 92–102%). The water inlet consisted of a vertical pipe with several holes that created a circulating and even current (water flow: 8–9 l min1). The water current at the surface at the edge of the tanks was maintained at a mean velocity at 0.058 m s1 (S.D.: 0.004 m s1).
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Table 1 Group design, mean fish lengths (mm), size disparity (coefficient of variation for length within each tank) and stocking densities (number per m3) for different tanks and periods in the experimental study. The estimated biomass is calculated on basis of the mean fish lengths in each tank from the stereovideo measurements and length–weight regressions calculated from measuring length and weight in a sample of fish (n = 50) from each study period. Tank no.
Experiment 1
Experiment 2
Mean length (mm)
S.D.
Size disparity (CV)
Initial density (per m3)
Size disparity 1 Mixed 2 Mixed 3 Medium 4 Mixed 5 Small 6 Large
102.6 102.9 103.4 102.8 94.0 109.5
11.3 11.6 9.2 10.6 8.5 8.0
0.110 0.113 0.089 0.103 0.090 0.073
705 705 705 705 705 705
Stocking density 1 Low 2 High 3 Medium 4 Low 5 High 6 Medium
120.7 120.2 115.2 114.5 118.1 120.1
11.5 9.9 10.5 12.4 9.7 9.4
0.095 0.082 0.091 0.108 0.082 0.078
321 962 641 321 641 962
Group
Group
Mean length (mm)
S.D.
Size disparity (CV)
Initial density (per m3)
Biomass (kg m3)
6.1 6.1 6.3 6.1 4.5 7.6
Mixed Small Mixed Large Medium Mixed
123.2 99.7 120.9 131.0 118.7 127.8
12.2 6.0 13.9 6.9 6.6 10.2
0.099 0.060 0.115 0.053 0.056 0.080
705 705 705 705 705 705
11.4 5.5 10.7 14.1 10.1 12.9
4.8 14.3 8.3 4.0 9.0 14.3
Low Low Medium High High Medium
122.0 118.9 118.3 125.9 120.5 121.9
12.8 12.7 10.6 11.5 11.2 13.8
0.105 0.107 0.090 0.091 0.093 0.113
321 321 641 962 962 641
5.0 4.6 9.0 16.8 14.4 10.0
Biomass (kg m3)
Variation in size disparity was constructed by sorting the fish into three size groups. The smallest group consisted of fish belonging to the smallest third of the fish, and the largest group of the largest third (Table 1). Three of the tanks were stocked with similar numbers of small, medium and large fish (mixed size), while the other three tanks were stocked with small, medium or large fish only (fish number in each tank = 275, Table 1). When the size disparity trials were finished, the fish were transferred to the same holding tank and allowed to mix for 24 h. Thereafter, the fish were divided randomly into the six experimental tanks. Two of the tanks were stocked with 125 fish, two with 250 fish and the last two tanks with 375 fish (Table 1). The groups were constructed in the same manner for both experimental periods, and the assignment of the groups to different tanks was randomized. The behavioural observations were initiated after a brief acclimatisation period (2–3 days). Each tank was observed over two whole days separated by a 4-day interval. Within each of these 2 days a 10-min bout was recorded every sixth hour by using an external timer. In each 10 min period 15 fish were observed, resulting in a total of 120 fish per tank being observed (60 fish per day). The fish were feed in the same manner as in a commercial cod hatchery (automatic feeders, Biomar cod pellets, daily ration: 3–4% of body weight corrected for weight increase). The mortality was less than 1% during the experiments.
2.2. Setup and design of the hatchery study The cod juveniles were reared in large circular tanks in the hatchery (volume: 20 m3, diameter: 5.1 m, depth: 1.4 m). Altogether 15 tanks were examined (Table 2). The stocking density was higher (Mann–Whitney U-test, Z = 3.01, P = 0.003) and the fish longer (Mann–Whitney U-test, Z = 2.32, P = 0.021) in 2002 compared to 2003 (Table 2). There was no difference in size disparity between the 2 years (Mann–Whitney U-test, Z = 1.16, P = 0.247). Stocking density was not correlated with size disparity (Pearson correlations; density as fish number vs. size disparity: r = 0.08, P = 0.78; density as fish mass vs. size disparity: r = 0.09, P = 0.76). Fish length was not associated with neither the number of fish in the tanks (Pearson correlation, r = 0.180, P = 0.521) nor size disparity (Pearson correlation, r = 0.173, P = 0.538). Both the O2 concentration (Mann–Whitney U-test, Z = 3.13, P = 0.002) and the water flow (Mann–Whitney U-test, Z = 3.28, P = 0.001) were higher in 2003 compared to 2002, whereas the temperature was slightly higher in 2002 compared to 2003 (Mann–Whitney U-test, Z = 2.08, P = 0.037) (Table 2). Fish behaviour was observed using a stereovideo camera positioned in the water column at the tank wall pointing towards the middle of the tank. Each tank was observed over 24 h and a 10-min tape was recorded every fourth hour. In each 10 min period the behaviour and activity of 20 randomly selected fish were analysed, resulting in a total sample size of 120 fish per tank. The video analyses were scored blind by one observer to avoid
Table 2 Group design, mean fish lengths (mm), size disparity (coefficient of variation for length within each tank) and stocking densities (number per m3) in the hatchery study. The mean fish lengths are based on stereovideo measurements, while estimated biomass is calculated on basis of the mean fish lengths in each tank and length–weight regressions calculated from measuring length and weight in a sample of fish (n = 150) from each study period. Period
No. tanks
Fish length (mm)
Size disparity (CV)
Fish no.
Density (no. m3)
Biomass (kg m3)
O2 (mg l1)
Temp-erature (8C)
Flow (l min1)
2002 2003
8 7
83.5–107.3 65.6–97.4
0.075–0.137 0.074–0.122
12,450–40,908 8695–13,313
623–2045 435–666
5.7–17.6 1.0–3.6
7.0–7.4 7.5–7.8
11.5–11.9 10.9–11.1
380–436 420–437
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biases due to observer related differences in interpretation of behaviour. 2.3. Quantification of fish size and behaviour by stereovideography Fish length and behaviour were quantified by the use of a stereovideographic method (e.g. Hughes and Kelly, 1996; Petrell et al., 1997; Harvey and Shortis, 1996), where the position of the fish is determined in an x, y, z Cartesian coordinate system. The two visual perspectives of a given fish required to estimate 3D positions were provided by two Monocrome Watec WAT-127LH cameras (f = 2.8 mm) arranged in parallel 30 cm apart. The cameras were calibrated before the observations according to Hughes and Kelly (1996). An object with known dimensions was measured to confirm the validity of the calibration. A quad splitter (QS-MX II) was used to combine and simultaneously present images from two sets of stereo cameras in adjacent quadrants on a monitor. A time code generator (Horita TG 50) was used to print time and frame number on the recordings. The final images were recorded by a Sony GV1000 digital tape recorder. Still images of a given fish were grabbed using the image analysis software ImageProPlus (v. 4.5). Basic algorithms for calculation of 3D coordinates from the recorded 2D coordinates were based on calibration matrices, provided by Nick Hughes (Univ. Alaska Fairbanks, School of Fisheries & Ocean Science, USA) and 3D coordinates of fish were calculated using the mathematical software Mathematica (Wolfram Research). Three parameters were determined from the 3D coordinates. Total length were defined as the length (mm) from the snout to the visible end of the tail of the fish and was estimated as
total length ðTLÞ qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ½ðxh1 xt1 Þ2 þ ðyh1 yt1 Þ2 þ ðzh1 zt1 Þ2 qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi þ ½ðxh2 xt2 Þ2 þ ðyh2 yt2 Þ2 þ ðzh2 zt2 Þ2 ¼ (1) 2 where h1 and h2 are, respectively, the x-, y-, and zcoordinates of the head for two images separated with a given time interval (DT = interval between Image 1 and Image 2; mean = 0.6 s, S.D. = 0.16) and t1 and t2 correspond to the x-, y-, and z-coordinates of the tail for the same two images. The measured total length was thus an average for two length estimates per fish. The repeatability of the two length measures was high with R2 = 0.89 (linear regression) for the pooled dataset from 2002 to 2003. The absolute swim speed (not corrected for water velocity) was defined as the average speed (m s1) of the head and tail of a fish during a given time interval (DT):
swim speed ðVÞ qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ½ðxh1 xh2 Þ2 þ ðyh1 yh2 Þ2 þ ðzh1 zh2 Þ2 =DT qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi þ ½ðxt1 xt2 Þ2 þ ðyt1 yt2 Þ2 þ ðzt1 zt2 Þ2 =DT (2) ¼ 2
Turning rates (degrees per second) were defined as the angle between the projections of the two lines joining the head and the tail of the fish in the two images and was estimated as turning rate ðDÞ Arccosf½ðxh1 xt1 Þ ðxh2 xt2 Þ þ ½ðyh1 yt1 Þ ¼
ðyh2 yt2 Þ þ ½ðzh1 zt1 Þ ðzh2 zt2 Þg=ðTL1 TL2 Þ (3) DT
where TL1 and TL2 are, respectively, the total lengths of the fish measured in Images 1 and 2 (Boisclair, 1992). In the first period of the experimental study the cod juveniles staying close to the bottom of the tanks appeared to be smaller than the juveniles staying above the bottom (Gruven, personal communication). Thus, the total length of the fish that stayed close to the bottom (<10 cm from the tank floor) and above the bottom (>10 from the tank floor) was measured in each of the 12 trials in experiment 2 (N = 10 in each of the trials and for each of the two groups). The distance from the fish to the bottom was also verified using the same procedure as for measurement of fish length, apart from that the distance from the fish snout to the tank floor was measured. 2.4. Other behavioural parameters The tailbeat rate for each observed fish was determined to the nearest half tailbeat by counting the number of tailbeats between two grabbed images. The data from Eqs. (1) and (2), and the estimated tailbeat rate, were used for calculating swim speed per body length and distance swum per tailbeat. In addition, the number of visible fish swimming 1808 against the predominating swim direction was counted over a 5-min period for each tank. The number of fish showing a behaviour termed as ‘‘flash’’ was also counted during the same 5-min period. Flash was defined as when a fish suddenly and rapidly swerved away from steady and directional swimming behaviour. Both these behaviours represented striking deviations from the predominating behavioural pattern in the tanks and were thus defined as anomalous or possible stress related. The numbers of fish swimming against the predominating swim direction and flash were divided by the total number of fish in the tank to correct for stocking density. 2.5. Data analysis The fish where not individually tagged or recognizable and the same fish might therefore have been observed twice or more in each tank. Also, the behaviour of individual fish in one tank could have been influenced by the other fish in the same tank. Thus, to reduce dependency problems, the average values for each tank were used in the statistical analyses, i.e. the resulting sample size equals the number of tanks examined. In the experimental study the averages of the two observation days were used in the further analyse and swim speeds were corrected for the current speed in the tank. In the hatchery study, partial correlations with the average water flow in each tank as a control variable were
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used to compensate for varying water currents. Density was measured as number of fish per volume or as the estimated biomass in kg per tank. The biomass per tank was estimated by developing linear regressions for a subsample of fish (N = 50 in the experimental study and N = 150 in the hatchery study each study period) that were killed with a blow to the head before being measured. The number of fish and the average fish length per tank were used to estimate the biomass for each tank (Tables 1 and 2). There was no behavioural variation among the different observation periods during the day neither in the experimental or in the hatchery study (experimental: GLM, univariate ANOVA with period and time of day as fixed factors; test statistics for time of day: 0.03 < F < 1.19, 0.34 < P < 0.99, hatchery: GLM, univariate ANOVA with period and time of day as fixed factors; test statistics for period: 0.07 < F < 2.27, 0.06 < P < 0.99). Hence, the observations within the same day was pooled for further analyses. Some of the measured parameters varied between the two study periods. In the experimental size disparity trials, flash (Mann–Whitney U-test, Z = 0.32, P = 0.82) and occurrence of swimming against the predominating swim direction (Mann–Whitney U-test, Z = 0.41, P = 0.70) did not vary between periods, while the remaining parameters varied (Mann–Whitney U-tests, 2.82 < Z < 1.92, 0.002 < P < 0.06). In the experimental density trials there was no difference between periods in flash (Mann– Whitney U-test, Z < 0.01, P = 1.00), absolute distance swam per tailbeat (Mann–Whitney U-test, Z = 0.96, P = 0.34) and distance swam per tailbeat per body length (Mann–Whitney U-test, Z = 1.60, P = 0.13), while the other parameters varied (Mann–Whitney U-tests, 2.82 < Z < 2.08, 0.002 < P < 0.04). In the hatchery study there was no variation in the behavioural parameters between the two periods (Mann–Whitney U-tests, 1.852 < Z < 0.23, 0.72 < P < 0.82), apart from for flash and swimming against the predominating swim direction. Parameters that differed between the two periods were thus standardised (Z-transformation) within each period. After Z-transformation, there were no significant differences between the periods for any of these parameters (Mann–Whitney U-tests, 0.16 < Z < 0.32, 0.82 < P < 1.00). All parameters that were analysed using parametric tests were normally distributed either untransformed or after log-transformation (Shapiro–Wilks test, P > 0.05). The statistical analyses were performed using SPSS v. 12.0.
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up in the water column, and were sporadically observed to feed on pellets lying on the tank bottom (Fig. 1), Wilcoxon Signed Ranks test, Z = 3.06, P = 0.002). Tailbeat rate increased with increasing fish density, both when stocking density was expressed as biomass (rs = 0.71, P = 0.009) and as number of fish per volume (Fig. 2A, rs = 0.68, P = 0.015). Furthermore, stocking density was negatively correlated with the frequency of flash (density as fish number: Fig. 2B, rs = 0.92, P < 0.001, density as biomass: rs = 0.90, P < 0.001) and with the proportion of fish swimming against the predominating swim direction (density as fish number: Fig. 2C, rs = 0.89, P < 0.001, density as biomass: rs = 0.79, P = 0.002). No significant associations were found between any of the other observed behavioural parameters and stocking density under experimental conditions (0.47 < rs < 0.39, 0.39, 0.012 < P < 0.72). Turning rate was significantly negatively correlated to biomass per volume (Fig. 2D, rp = 0.58, P = 0.028), while number of fish per volume (log-transformed) tended to be negatively correlated with turning rate (rp = 0.53, P = 0.051). No other correlations were found between any of the behavioural parameters and stocking density under hatchery conditions (0.045 < rp < 0.48, 0.081 < P < 0.95). Size disparity was positively correlated with turning rate (Fig. 3A, rs = 0.64, P = 0.026). Moreover, there was a tendency towards size disparity being positively correlated with the proportion of fish swimming against the predominating swim direction (Fig. 3B, rs = 0.54, P = 0.071). There were no significant associations between size disparity and the other parameters measured (0.19 < rs < 0.16, 0.56 < P < 0.98). Size disparity was positively correlated with turning rate (Fig. 3C, rp = 0.59, P = 0.025) and relative swim speed
3. Results Apart from sporadic events, the cod juveniles showed no signs of negative social interactions such as overt aggression, contest competition or cannibalism, neither under experimental conditions, nor in the hatchery. Due to the low frequencies of such behaviours (less than 10 observations of overt aggression during the entire study), analyses of relationships between negative social interactions and density or size disparity were not feasible. The fish that resided close to the bottom of the tank during the second experimental period were shorter than fish further
Fig. 1. Length (mm) of cod juveniles that stayed more than 10 cm above the bottom of the tanks (mid water: black bar) and fish that stayed closer than 10 cm to the tank bottom (bottom: white bar) under experimental conditions.
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Fig. 2. (A) Standardised (z-score) tailbeat rate, (B) average number of observed ‘‘flash’’ per juvenile within a 5-min period, (C) standardised (z-score) proportions of fish swimming against the predominating swim direction and (D) turning rate in relation to fish density as number or biomass of juveniles per m3 under experimental conditions.
(Fig. 3D, rp = 0.57, P = 0.035) and t. There were no significant associations between size disparity and the other parameters measured (0.26 < rp < 0.45, 0.11 < P < 0.99). 4. Discussion Our results indicate that both stocking density and size disparity were associated with variation in behaviours indicative for energetic costs and stress level. However, agonistic interactions and behaviours indicating extreme levels of stress or activity were rarely observed within the size ranges and densities examined. 4.1. Stocking density Under experimental conditions the occurrence of flash and swimming against the predominating swim direction decreased with stocking density, while turning rate decreased with stocking density in the hatchery study. These results show that the swim pattern at higher stocking densities was more synchronized compared to lower densities, as also have been found for rainbow trout cultured at different densities (Be´gout Anras and Lagarde´re, 2004). The swim pattern of the cod juveniles could be characterised as varying from dense shoaling at low densities to schooling at higher densities. In nature, cod juveniles change from a pelagic life style to a more benthic life style at sizes of 2–7 cm, probably because of increased predation pressure (Fahay, 1983; Fahay et al., 1999). After
this descent the coloration of the juveniles mimics the substrate and they are believed to remain on the bottom most of the time (Lough et al., 1989). Settled cod juveniles might be site-attached and defend territories around a shelter (Tupper and Boutilier, 1995), but they may also form loose shoals when shelters are lacking (Salvanes et al., 2007). Thus, the behaviour of the cod juveniles in the current study differed from the behaviour of wild cod juveniles, probably because the extreme fish densities in a culture situation inhibit the natural behaviour due to space and environmental constraints. Whether or not the synchronized swim pattern of cod juveniles in a culture situation is beneficial in terms of increased survival and growth depends on how natural constraints (e.g. predation) shape the behaviour of cod under natural conditions. If the natural swim behaviour of cod is an adaptation to maximize fitness by avoiding predation, schooling behaviour might actually be less costly than the natural swim behaviour of cod juveniles, due to possible energetic advantages of schooling/shoaling (e.g. Pitcher, 1992; Liao et al., 2003; Svendsen et al., 2003). Consequently, the more synchronized swim pattern at higher densities might reflect lower activity costs compared to lower densities. On the contrary, the finding that the tailbeat rate increased with stocking density under experimental conditions might indicate increased costs since tailbeat rate is regarded as a reliable indicator of energy use in fish (Videler, 1993; Webber et al., 2001). An increase in tailbeat rate without a corresponding increase in swim speed might be a sign of augmented costs to
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Fig. 3. (A) Standardised turning rate (z-score of the change in body angle per time) and (B) standardised proportion of fish swimming against the predominating swim direction (z-score) in relation to size disparity (coefficient of variation for body length within each tank) under experimental conditions. (C) Turning rate and (D) swim velocity as body lengths per second in relation to size disparity in each tank and under commercial hatchery conditions.
maintain a constant cruising speed with increasing fish density. However, an increase in tailbeat rate to maintain a constant cruising speed would implicitly involve a decrease in the distance swum per tailbeat, but this was not found. The swim speed in juvenile cod is determined by both tailbeat rate and amplitude (Webb, 2002) and the observed increase in tailbeat rate might also be a consequence of reduced amplitude as response to a higher fish density. In this case the increase in tailbeat rate with increasing density would not represent an increase in activity costs. The possibility that increased density do not involve significantly increased activity costs is supported by the lack of relationships between behaviours indicative for energy consumption or stress level and stocking density in the hatchery study. The decreased frequencies of flash behaviour and swimming against the predominating swim direction with increasing stocking density might also indicate that the level of stress decreased with increasing stocking density. The possibility that increasing stocking density not necessarily involve increased behavioural costs or stress level is supported by the findings of Lefranqois et al. (2001) and Boujard et al. (2002) that stocking density alone is not stressful or costly for the fish, but that increasing density rather might be costly due to decreased individual feed intake. 4.2. Size disparity The turning rate increased with increasing size disparity both under experimental and hatchery condi-
tions. In addition, the relative swim speed increased with size disparity in the hatchery study and there was a tendency towards increased occurrence of swimming against the predominating swim direction with increasing size disparity under experimental conditions. Together, these results indicate that the swim pattern was more irregular with increasing size disparity. This finding concurs with studies on other cultured fishes showing that increasing size disparity result in reduced schooling and increased occurrence of agonistic interactions, which in turn might reduce survival, feed intake and in some cases also growth (e.g. Efthimiou et al., 1994; Sogard and Olla, 2000; Baras and Jobling, 2002; Dou et al., 2004). It has also been shown that feed intake is reduced for smaller fish in mixed sized shoals (Ward and Krause, 2001). As opposed to the behavioural variation in relation to stocking density, it is thus reasonable to suggest that the more irregular swim pattern found at higher size disparities in the current study represent increased activity costs and elevated stress levels (Jobling and Reinsnes, 1986). 4.3. Agonistic behaviour Overt agonistic behaviour was nearly absent and cannibalism was not observed. However, cod juveniles of approximately similar size show higher frequencies of agonistic behaviour at very low stocking densities (Salvanes and Braithwaite, 2005). The absence of such behaviours in the current study may be a consequence of the stocking densities being too high to allow territorially
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or dominance hierarchies, and implicitly also agonistic interactions (Metcalfe, 1990; Brown et al., 1992; Juell et al., 1994). Also, at high stocking densities the behavioural pattern might resemble schooling in nature; a behavioural pattern that usually involve low levels of agonistic interactions (Pitcher, 1992). In addition, the size differences between individuals could have so small that overt conflicts would be too costly because escalated conflicts would result in physical injury or high energy expenditure (Huntingford and Turner, 1987). The absence of overt aggressive and competitive behaviours does not necessarily imply that competition was non-existent. It is possible that competition occurs through more subtle behaviours, e.g. through inexpensive displays or by evaluation of the competitive ability of an opponent on the basis of morphological features or other cues like sounds (Huntingford and Turner, 1987; Pitcher, 1992). The existence of subtle competition is supported by cod juveniles staying close to the bottom of the experimental tanks being smaller than the fish found in mid water. These fish were also observed to feed on pellets lying on the tank bottom. Smaller cod juveniles, with presumably inferior competitive capabilities, may therefore adopt an alternative feeding strategy.
(reviewed in Ellis et al., 2002). The absence of agonistic behaviour in the current study suggests that the welfare status of the cod juveniles was not inferior, at least not when compared to fish farming in general. To what extent the observed behavioural variation affected welfare status is difficult to assess. For instance, the more irregular swim pattern observed at higher size disparities could be interpreted as a weak stress response, which again could indicate reduced welfare. Nevertheless, the lack of physical injuries typically caused by aggressive behaviour and also a general low mortality, indicate that fish welfare was not seriously affected under the specific hatchery conditions for the examined size ranges and stocking densities. Acknowledgements A great thanks to Nick Hughes and Lon Kelly for providing the algorithms for the stereovideo-calculations. We would also like to thank the staff at NTNU Brattøra Research Station and Cod Culture Norway for valuable help during the course of the study. The study was funded by the Norwegian Research Council and Torstein Erboes Foundation. References
4.4. Activity costs and welfare This study indicates that activity costs and stress levels of cultured cod juveniles are associated with stocking density and size disparity within the size ranges and densities examined. The fact that overt agonistic behaviours were nearly absent and that the observed behavioural variation did not reflect considerably elevated levels of stress or activity costs do, however, indicate that the examined densities and size disparities not involve major variations in activity costs. Nevertheless, the size of equally aged cod juveniles differed considerably within and among tanks in the hatchery. This indicates the existence of some sort of mechanism regulating individual fish growth, even under standardised culture conditions. In addition to intrinsic factors like genetic variation or individual health status, the growth differences could be caused by dominant individuals obtaining more resources than sub-dominants through using subtle and inexpensive behavioural signals that were not observable in the current study. It has been suggested that variation in energetic costs associated with varying fish size disparity in a culture situation might be compensated with an increase in feed intake when food availability is not restricted (Folkvord and Ottera, 1993; Sogard and Olla, 2000). This emphasise the importance of using a feeding schedule that ensure equal and sufficient access to food for all fish in a culture unit and that reduce the competition for food. One alternative might for instance be to introduce the food at different levels and positions in the tank. Assessment of behavioural variation might be useful for evaluation the welfare of cultured fishes (Mork and Gulbrandsen, 1994; Heinen, 1998; Pickering, 1998; Chandroo, 2000; FSBI, 2002). For instance, biting and fighting might cause wounds, while intense competition for food might lead to starvation in sub-dominant individuals
Baardvik, B.M., Jobling, M., 1990. Effect of size-sorting on biomass gain and individual growth rates in Arctic charr, Salvelinus alpinus L. Aquaculture 90, 11–16. Baker, R.F., Ayles, G.B., 1990. The effects of varying density and loading level on the growth of Arctic charr (Salvelinus alpinus L.) and rainbow trout (Oncorhynchus mykiss). World Aquacult. 21, 58–62. Baras, E., Jobling, M., 2002. Dynamics of intracohort cannibalism in cultured fish. Aquacult. Res. 33, 461–479. Be´gout Anras, M.-A., Lagarde´re, J.P., 2004. Measuring cultured fish swimming behaviour: first results on rainbow trout using acoustic telemetry in tanks. Aquaculture 240, 175–186. Bjoˆrnsson, B., 1994. Effects on stocking density on growth rate of halibut (Hippoglossus hippoglossus L.) reared in large circular tanks for three years. Aquaculture 123, 259–270. Blom, G., Folkvord, A., 1997. A snapshot of cannibalism in 0-group Atlantic cod (Gadus morhua) in a marine pond. J. Appl. Ichthyol. 13, 177–181. Boisclair, D., 1992. An evaluation of the stereocinematographic method to estimate fish swimming speed. Can. J. Fish. Aquat. Sci. 49, 523–531. Boujard, T., Labbe, L., Auperin, B., 2002. Feeding behaviour, energy expenditure and growth of rainbow trout in relation to stocking density and food accessibility. Aquacult. Res. 33, 1233–1242. Braithwaite, V.A., Salvanes, A.G.V., 2005. Environmental variability in the early rearing environment generates behaviourally flexible cod: implications for rehabilitating wild populations. Proc. Roy. Soc. Lond., Ser. B: Biol. Sci. 272, 1107–1113. Brooking, P., Doucette, G., Tinker, S., Whoriskey, F.G., 2006. Sonic tracking of wild cod, Gadus morhua, in an inshore region of the Bay of Fundy: a contribution to understanding the impact of cod farming for wild cod and endangered salmon populations. ICES J. Mar. Sci. 63, 1364–1371. Brown, G.E., Brown, J.A., Srivastava, R.K., 1992. The effect of stocking density on the behaviour of Arctic charr (Salvelinus alpinus L.). J. Fish Biol. 41, 955–963. Chandroo, K.P., 2000. Assessing the welfare status of farmed rainbow trout (Onchorhynchus mykiss) with electromyogram telemetry. MSc Thesis. Department of Animal and Poultry Science, University of Guelph Guelph, ON. Chandroo, K.P., Duncan, I.J.H., Moccia, R.D., 2004. Can fish suffer? Perspectives on sentience, pain, fear and stress. Appl. Anim. Behav. Sci. 86, 225–250. Dou, S., Masuda, R., Tanaka, M., Tsukamoto, K., 2004. Size hierarchies affecting the social interactions and growth of juvenile Japanese flounder, Paralichthys olivaceus. Aquaculture 233, 237–249. Efthimiou, S., Divanach, P., Rosenthal, H., 1994. Growth, food conversion and agonistic behaviour in common dentex (Dentex dentex) juveniles fed on pelleted moist and dry diets. Aquat. Living Resour. 7, 267–275.
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Contents lists available at ScienceDirect
Applied Animal Behaviour Science journal homepage: www.elsevier.com/locate/applanim
Behavioural variation in cultivated juvenile Atlantic cod (Gadus morhua L.) in relation to stocking density and size disparity Ingebrigt Uglem a,*, Elin Kjørsvik a, Ka˚re Gruven b, Anders Lamberg c a
Norwegian University of Science and Technology, Department of Biology, N-7491 Trondheim, Norway AKVAgroup ASA, Ladebekken 17, N-7048 Trondheim, Norway c Lamberg Bio-Marin Service, Ranheimsveien 281, N-7054 Ranheim, Norway b
A R T I C L E I N F O
A B S T R A C T
Article history: Accepted 19 January 2009 Available online 13 February 2009
The aim of this study was to examine the behaviour and activity of Atlantic cod (Gadus morhua) juveniles (65–120 mm total length) in relation to varying stocking density (500–2000 fish per m3) and size disparity under both experimental and commercial hatchery conditions. This was done by using stereovideography to measure fish size and to quantify fish behaviour in situ. The swim pattern was more synchronized at higher fish densities (both experimental and commercial conditions), indicating a more pronounced schooling behaviour and possibly also indirectly reduced activity costs and stress levels with increasing fish density. Furthermore, the swim pattern became less synchronized and the relative swim speed increased as fish size disparity increased. This might indicate both elevated energetic activity costs and an augmented stress level with increasing size disparity. However, overt agonistic behaviour was nearly absent at the examined fish densities and size disparities, and negative social interactions are thus unlikely to represent a major cost under such conditions. The general absence of overt agonistic behaviour and the lack of behavioural variation indicative for extreme levels of stress or activity might suggest that the welfare status of the juveniles was not compromised under the examined conditions. ß 2009 Elsevier B.V. All rights reserved.
Keywords: Atlantic cod Gadus morhua Aquaculture Activity costs Welfare Behaviour
1. Introduction Technology for the cultivation of Atlantic cod (Gadus morhua) is constantly developing, and commercial cod farming is increasing in countries such as Norway, Scotland, Ireland and Canada (Brooking et al., 2006; Moe et al., 2007). About 11,000 metric tonnes of farmed cod was produced in Norway in 2007 (statistics from the Norwegian Fisheries Directorate). The rearing of juveniles to a size that could be transferred to marine net pens in landbased tanks is still a critical part of cod culture.
* Corresponding author. Present address: Norwegian Institute for Nature Research, Tungasletta 2, No-7485 Trondheim, Norway. Tel.: +47 73901400; fax: +47 73801401. E-mail address: [email protected] (I. Uglem). 0168-1591/$ – see front matter ß 2009 Elsevier B.V. All rights reserved. doi:10.1016/j.applanim.2009.01.006
Optimisation of growth and survival during this phase is of major importance in order to reduce costs and to shorten the remaining period until the cod reaches market size. Increased knowledge about how behaviour and activity of cultured cod juveniles varies according to social conditions could contribute to the improvement of fish welfare and production efficiency; as such variations might correlate with individual stress level and energy consumption (e.g. Sayer, 1998; Morgan et al., 1999; Øverli et al., 2002; McFarlane et al., 2004; Salvanes and Braithwaite, 2006). It is well documented that both acute and chronic stress reduces individual growth and survival in fish culture (e.g. Handeland et al., 1996; Pickering, 1998; Ellis et al., 2002). Behavioural variation might also indicate impaired fish welfare (Sneddon, 2003), as were shown for Atlantic halibut (Kristiansen et al., 2004) and rainbow trout (Chandroo et al., 2004). Finally, behavioural variation is
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often associated with variation in fish growth rate, for instance through increased energetic expenditure during high activity levels as documented in rainbow trout (Li and Brocksen, 1977; Lefranqois et al., 2001) or because behavioural variation correlates with foraging intensity (Boisclair, 1992; Kristiansen et al., 2004). The variation in individual behaviour in fish culture is related to a range of factors, of which stocking density and individual size variations within a culture unit (size disparity) are two of the most important factors. Variation in stocking density might affect the efficiency of fish farming in several ways. An elevated stocking density may be preferable if it maximizes production capacity per culture volume. However, high densities have resulted in reduced growth rates in several fish species such as rainbow trout (e.g. Holm et al., 1990; Boujard et al., 2002; Ellis et al., 2002), Atlantic halibut (Bjoˆrnsson, 1994; Kristiansen et al., 2004), sea bass (Saillant et al., 2003), as well as in Atlantic cod (Lambert and Dutil, 2001). This trend is not unequivocal though, and studies of Atlantic salmon (Kjartansson et al., 1988), winter flounder (Fairchild and Howell, 2001), and European sea bass (Paspatis et al., 2003) have reported unaffected or even increasing growth rate (Arctic charr, as shown by Baker and Ayles, 1990; Siikavuopio and Jobling, 1995) with increased fish density. Increased stocking density may also reduce fish survival in aquaculture due to cannibalism (Baras and Jobling, 2002), as shown for winter flounder (Fairchild and Howell, 2001) and grouper (Hseu, 2002). The relationships between stocking density, foraging behaviour, growth and survival might be attributed to varying levels of dominance and agonistic behaviour (Lambert and Dutil, 2001). Variation in fish size within a population (size disparity) is another important decisive factor for growth and survival, and thus for production efficiency. In commercial farming, grading and sorting of fish according to size is routinely carried out. It is widely believed that size grading results in increased biomass gain, which might be explained by larger individuals being dominant and aggressive towards the smaller individuals, which in turn might lead to suppressed feed intake and/or reduced growth of the smaller fish (Efthimiou et al., 1994; Dou et al., 2004). However, several studies have reported that size grading in fact might lead to unchanged or decreased growth in adult Atlantic cod (Lambert and Dutil, 2001), Arctic charr (Jobling and Reinsnes, 1987; Baardvik and Jobling, 1990), perch (Melard et al., 1996) and turbot (Strand and Øiestad, 1997; Sunde et al., 1998). A large size disparity in a culture unit might under some circumstances also lead to increased mortality due to cannibalism (Baras and Jobling, 2002; Hseu, 2002; Stuart and Smith, 2003). The relationship between the behaviour of cultured fish, stocking density and size disparity is therefore not straightforward, even though it is thoroughly demonstrated that both stocking density and size variation are crucial factors, which through influencing the individual behaviour, might affect production efficiency in most types of fish farming. Little is known about behaviour of juvenile cod under commercial and large-scale culture conditions per se, or how behavioural variation relates to fish welfare
and stress level (Salvanes and Braithwaite, 2006). Experimental and small-scale studies with low stocking densities have, however, shown that early experiences during culture might affect shoaling, antipredator, foraging and agonistic behaviour of juvenile cod (Braithwaite and Salvanes, 2005; Salvanes and Braithwaite, 2005; Salvanes et al., 2007). Moreover, cod have been shown to be aggressive and cannibalistic during the early juvenile phase (Blom and Folkvord, 1997; Hoglund et al., 2005). The scope of this study was to investigate if variation in realistic stocking densities and size disparities for commercial culture of Atlantic cod juveniles were associated with behavioural variation indicative for fish welfare, stress level or energetic costs. In order to control for artefacts caused by experimental conditions we examined the behaviour and activity of cod juveniles both experimentally with stocking densities and size disparities similar to commercial production of cod juveniles and in a commercial cod hatchery. 2. Materials and methods Effects of size disparity and stocking density were examined in controlled small-scale experiments carried out at the NTNU Brattøra Research Center in Trondheim, Norway during two periods (03.05–07.06.2003 and 24.11– 12.12.2003). The studies at a commercial cod hatchery were carried out at Cod Culture Norway AS (then owned by Nutreco), situated on the Norwegian West Coast, during two periods (04.10–08.10.2002 and 30.09–3.10.2003). 2.1. Setup and design of the experimental study Cod juveniles were obtained from a local commercial hatchery (Fosen Aquasenter). The cod juveniles (total length: 90–120 mm, weight: 5–12 g) were allowed to acclimatise for 3–4 weeks before the trials were initiated. The experiments were carried out in six circular tanks (diameter: 0.95 m, height: 0.9 m, water depth: 0.55 m, volume: 390 l) with constant water circulation. Fish behaviour was recorded by video cameras through a transparent window in the tank wall (Lexan1 polycarbonate: 5 mm thickness, height: 0.5 m, width: 0.6 m). The video cameras were mounted within a non-transparent box that covered the window such that the light conditions in the tanks did not change during recording. The recordings were initiated 4–5 h after introduction of the cameras to give the fish time to recover after the disturbance caused by the positioning of the cameras. Each tank was constantly illuminated by a 25-W fluorescent tube positioned 1 m above the centre of the tanks. This created a light intensity of about 500 lx at the water surface, which was similar to light conditions at a commercial hatchery. The water temperature varied between 8.5 and 9.5 8C during the first period and between 9.5 and 10 8C during the second period. The salinity was 35–36 ppt, and the oxygen concentration ranged from 8.1 to 9.4 mg l1 (oxygen saturation: 92–102%). The water inlet consisted of a vertical pipe with several holes that created a circulating and even current (water flow: 8–9 l min1). The water current at the surface at the edge of the tanks was maintained at a mean velocity at 0.058 m s1 (S.D.: 0.004 m s1).
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Table 1 Group design, mean fish lengths (mm), size disparity (coefficient of variation for length within each tank) and stocking densities (number per m3) for different tanks and periods in the experimental study. The estimated biomass is calculated on basis of the mean fish lengths in each tank from the stereovideo measurements and length–weight regressions calculated from measuring length and weight in a sample of fish (n = 50) from each study period. Tank no.
Experiment 1
Experiment 2
Mean length (mm)
S.D.
Size disparity (CV)
Initial density (per m3)
Size disparity 1 Mixed 2 Mixed 3 Medium 4 Mixed 5 Small 6 Large
102.6 102.9 103.4 102.8 94.0 109.5
11.3 11.6 9.2 10.6 8.5 8.0
0.110 0.113 0.089 0.103 0.090 0.073
705 705 705 705 705 705
Stocking density 1 Low 2 High 3 Medium 4 Low 5 High 6 Medium
120.7 120.2 115.2 114.5 118.1 120.1
11.5 9.9 10.5 12.4 9.7 9.4
0.095 0.082 0.091 0.108 0.082 0.078
321 962 641 321 641 962
Group
Group
Mean length (mm)
S.D.
Size disparity (CV)
Initial density (per m3)
Biomass (kg m3)
6.1 6.1 6.3 6.1 4.5 7.6
Mixed Small Mixed Large Medium Mixed
123.2 99.7 120.9 131.0 118.7 127.8
12.2 6.0 13.9 6.9 6.6 10.2
0.099 0.060 0.115 0.053 0.056 0.080
705 705 705 705 705 705
11.4 5.5 10.7 14.1 10.1 12.9
4.8 14.3 8.3 4.0 9.0 14.3
Low Low Medium High High Medium
122.0 118.9 118.3 125.9 120.5 121.9
12.8 12.7 10.6 11.5 11.2 13.8
0.105 0.107 0.090 0.091 0.093 0.113
321 321 641 962 962 641
5.0 4.6 9.0 16.8 14.4 10.0
Biomass (kg m3)
Variation in size disparity was constructed by sorting the fish into three size groups. The smallest group consisted of fish belonging to the smallest third of the fish, and the largest group of the largest third (Table 1). Three of the tanks were stocked with similar numbers of small, medium and large fish (mixed size), while the other three tanks were stocked with small, medium or large fish only (fish number in each tank = 275, Table 1). When the size disparity trials were finished, the fish were transferred to the same holding tank and allowed to mix for 24 h. Thereafter, the fish were divided randomly into the six experimental tanks. Two of the tanks were stocked with 125 fish, two with 250 fish and the last two tanks with 375 fish (Table 1). The groups were constructed in the same manner for both experimental periods, and the assignment of the groups to different tanks was randomized. The behavioural observations were initiated after a brief acclimatisation period (2–3 days). Each tank was observed over two whole days separated by a 4-day interval. Within each of these 2 days a 10-min bout was recorded every sixth hour by using an external timer. In each 10 min period 15 fish were observed, resulting in a total of 120 fish per tank being observed (60 fish per day). The fish were feed in the same manner as in a commercial cod hatchery (automatic feeders, Biomar cod pellets, daily ration: 3–4% of body weight corrected for weight increase). The mortality was less than 1% during the experiments.
2.2. Setup and design of the hatchery study The cod juveniles were reared in large circular tanks in the hatchery (volume: 20 m3, diameter: 5.1 m, depth: 1.4 m). Altogether 15 tanks were examined (Table 2). The stocking density was higher (Mann–Whitney U-test, Z = 3.01, P = 0.003) and the fish longer (Mann–Whitney U-test, Z = 2.32, P = 0.021) in 2002 compared to 2003 (Table 2). There was no difference in size disparity between the 2 years (Mann–Whitney U-test, Z = 1.16, P = 0.247). Stocking density was not correlated with size disparity (Pearson correlations; density as fish number vs. size disparity: r = 0.08, P = 0.78; density as fish mass vs. size disparity: r = 0.09, P = 0.76). Fish length was not associated with neither the number of fish in the tanks (Pearson correlation, r = 0.180, P = 0.521) nor size disparity (Pearson correlation, r = 0.173, P = 0.538). Both the O2 concentration (Mann–Whitney U-test, Z = 3.13, P = 0.002) and the water flow (Mann–Whitney U-test, Z = 3.28, P = 0.001) were higher in 2003 compared to 2002, whereas the temperature was slightly higher in 2002 compared to 2003 (Mann–Whitney U-test, Z = 2.08, P = 0.037) (Table 2). Fish behaviour was observed using a stereovideo camera positioned in the water column at the tank wall pointing towards the middle of the tank. Each tank was observed over 24 h and a 10-min tape was recorded every fourth hour. In each 10 min period the behaviour and activity of 20 randomly selected fish were analysed, resulting in a total sample size of 120 fish per tank. The video analyses were scored blind by one observer to avoid
Table 2 Group design, mean fish lengths (mm), size disparity (coefficient of variation for length within each tank) and stocking densities (number per m3) in the hatchery study. The mean fish lengths are based on stereovideo measurements, while estimated biomass is calculated on basis of the mean fish lengths in each tank and length–weight regressions calculated from measuring length and weight in a sample of fish (n = 150) from each study period. Period
No. tanks
Fish length (mm)
Size disparity (CV)
Fish no.
Density (no. m3)
Biomass (kg m3)
O2 (mg l1)
Temp-erature (8C)
Flow (l min1)
2002 2003
8 7
83.5–107.3 65.6–97.4
0.075–0.137 0.074–0.122
12,450–40,908 8695–13,313
623–2045 435–666
5.7–17.6 1.0–3.6
7.0–7.4 7.5–7.8
11.5–11.9 10.9–11.1
380–436 420–437
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biases due to observer related differences in interpretation of behaviour. 2.3. Quantification of fish size and behaviour by stereovideography Fish length and behaviour were quantified by the use of a stereovideographic method (e.g. Hughes and Kelly, 1996; Petrell et al., 1997; Harvey and Shortis, 1996), where the position of the fish is determined in an x, y, z Cartesian coordinate system. The two visual perspectives of a given fish required to estimate 3D positions were provided by two Monocrome Watec WAT-127LH cameras (f = 2.8 mm) arranged in parallel 30 cm apart. The cameras were calibrated before the observations according to Hughes and Kelly (1996). An object with known dimensions was measured to confirm the validity of the calibration. A quad splitter (QS-MX II) was used to combine and simultaneously present images from two sets of stereo cameras in adjacent quadrants on a monitor. A time code generator (Horita TG 50) was used to print time and frame number on the recordings. The final images were recorded by a Sony GV1000 digital tape recorder. Still images of a given fish were grabbed using the image analysis software ImageProPlus (v. 4.5). Basic algorithms for calculation of 3D coordinates from the recorded 2D coordinates were based on calibration matrices, provided by Nick Hughes (Univ. Alaska Fairbanks, School of Fisheries & Ocean Science, USA) and 3D coordinates of fish were calculated using the mathematical software Mathematica (Wolfram Research). Three parameters were determined from the 3D coordinates. Total length were defined as the length (mm) from the snout to the visible end of the tail of the fish and was estimated as
total length ðTLÞ qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ½ðxh1 xt1 Þ2 þ ðyh1 yt1 Þ2 þ ðzh1 zt1 Þ2 qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi þ ½ðxh2 xt2 Þ2 þ ðyh2 yt2 Þ2 þ ðzh2 zt2 Þ2 ¼ (1) 2 where h1 and h2 are, respectively, the x-, y-, and zcoordinates of the head for two images separated with a given time interval (DT = interval between Image 1 and Image 2; mean = 0.6 s, S.D. = 0.16) and t1 and t2 correspond to the x-, y-, and z-coordinates of the tail for the same two images. The measured total length was thus an average for two length estimates per fish. The repeatability of the two length measures was high with R2 = 0.89 (linear regression) for the pooled dataset from 2002 to 2003. The absolute swim speed (not corrected for water velocity) was defined as the average speed (m s1) of the head and tail of a fish during a given time interval (DT):
swim speed ðVÞ qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ½ðxh1 xh2 Þ2 þ ðyh1 yh2 Þ2 þ ðzh1 zh2 Þ2 =DT qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi þ ½ðxt1 xt2 Þ2 þ ðyt1 yt2 Þ2 þ ðzt1 zt2 Þ2 =DT (2) ¼ 2
Turning rates (degrees per second) were defined as the angle between the projections of the two lines joining the head and the tail of the fish in the two images and was estimated as turning rate ðDÞ Arccosf½ðxh1 xt1 Þ ðxh2 xt2 Þ þ ½ðyh1 yt1 Þ ¼
ðyh2 yt2 Þ þ ½ðzh1 zt1 Þ ðzh2 zt2 Þg=ðTL1 TL2 Þ (3) DT
where TL1 and TL2 are, respectively, the total lengths of the fish measured in Images 1 and 2 (Boisclair, 1992). In the first period of the experimental study the cod juveniles staying close to the bottom of the tanks appeared to be smaller than the juveniles staying above the bottom (Gruven, personal communication). Thus, the total length of the fish that stayed close to the bottom (<10 cm from the tank floor) and above the bottom (>10 from the tank floor) was measured in each of the 12 trials in experiment 2 (N = 10 in each of the trials and for each of the two groups). The distance from the fish to the bottom was also verified using the same procedure as for measurement of fish length, apart from that the distance from the fish snout to the tank floor was measured. 2.4. Other behavioural parameters The tailbeat rate for each observed fish was determined to the nearest half tailbeat by counting the number of tailbeats between two grabbed images. The data from Eqs. (1) and (2), and the estimated tailbeat rate, were used for calculating swim speed per body length and distance swum per tailbeat. In addition, the number of visible fish swimming 1808 against the predominating swim direction was counted over a 5-min period for each tank. The number of fish showing a behaviour termed as ‘‘flash’’ was also counted during the same 5-min period. Flash was defined as when a fish suddenly and rapidly swerved away from steady and directional swimming behaviour. Both these behaviours represented striking deviations from the predominating behavioural pattern in the tanks and were thus defined as anomalous or possible stress related. The numbers of fish swimming against the predominating swim direction and flash were divided by the total number of fish in the tank to correct for stocking density. 2.5. Data analysis The fish where not individually tagged or recognizable and the same fish might therefore have been observed twice or more in each tank. Also, the behaviour of individual fish in one tank could have been influenced by the other fish in the same tank. Thus, to reduce dependency problems, the average values for each tank were used in the statistical analyses, i.e. the resulting sample size equals the number of tanks examined. In the experimental study the averages of the two observation days were used in the further analyse and swim speeds were corrected for the current speed in the tank. In the hatchery study, partial correlations with the average water flow in each tank as a control variable were
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used to compensate for varying water currents. Density was measured as number of fish per volume or as the estimated biomass in kg per tank. The biomass per tank was estimated by developing linear regressions for a subsample of fish (N = 50 in the experimental study and N = 150 in the hatchery study each study period) that were killed with a blow to the head before being measured. The number of fish and the average fish length per tank were used to estimate the biomass for each tank (Tables 1 and 2). There was no behavioural variation among the different observation periods during the day neither in the experimental or in the hatchery study (experimental: GLM, univariate ANOVA with period and time of day as fixed factors; test statistics for time of day: 0.03 < F < 1.19, 0.34 < P < 0.99, hatchery: GLM, univariate ANOVA with period and time of day as fixed factors; test statistics for period: 0.07 < F < 2.27, 0.06 < P < 0.99). Hence, the observations within the same day was pooled for further analyses. Some of the measured parameters varied between the two study periods. In the experimental size disparity trials, flash (Mann–Whitney U-test, Z = 0.32, P = 0.82) and occurrence of swimming against the predominating swim direction (Mann–Whitney U-test, Z = 0.41, P = 0.70) did not vary between periods, while the remaining parameters varied (Mann–Whitney U-tests, 2.82 < Z < 1.92, 0.002 < P < 0.06). In the experimental density trials there was no difference between periods in flash (Mann– Whitney U-test, Z < 0.01, P = 1.00), absolute distance swam per tailbeat (Mann–Whitney U-test, Z = 0.96, P = 0.34) and distance swam per tailbeat per body length (Mann–Whitney U-test, Z = 1.60, P = 0.13), while the other parameters varied (Mann–Whitney U-tests, 2.82 < Z < 2.08, 0.002 < P < 0.04). In the hatchery study there was no variation in the behavioural parameters between the two periods (Mann–Whitney U-tests, 1.852 < Z < 0.23, 0.72 < P < 0.82), apart from for flash and swimming against the predominating swim direction. Parameters that differed between the two periods were thus standardised (Z-transformation) within each period. After Z-transformation, there were no significant differences between the periods for any of these parameters (Mann–Whitney U-tests, 0.16 < Z < 0.32, 0.82 < P < 1.00). All parameters that were analysed using parametric tests were normally distributed either untransformed or after log-transformation (Shapiro–Wilks test, P > 0.05). The statistical analyses were performed using SPSS v. 12.0.
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up in the water column, and were sporadically observed to feed on pellets lying on the tank bottom (Fig. 1), Wilcoxon Signed Ranks test, Z = 3.06, P = 0.002). Tailbeat rate increased with increasing fish density, both when stocking density was expressed as biomass (rs = 0.71, P = 0.009) and as number of fish per volume (Fig. 2A, rs = 0.68, P = 0.015). Furthermore, stocking density was negatively correlated with the frequency of flash (density as fish number: Fig. 2B, rs = 0.92, P < 0.001, density as biomass: rs = 0.90, P < 0.001) and with the proportion of fish swimming against the predominating swim direction (density as fish number: Fig. 2C, rs = 0.89, P < 0.001, density as biomass: rs = 0.79, P = 0.002). No significant associations were found between any of the other observed behavioural parameters and stocking density under experimental conditions (0.47 < rs < 0.39, 0.39, 0.012 < P < 0.72). Turning rate was significantly negatively correlated to biomass per volume (Fig. 2D, rp = 0.58, P = 0.028), while number of fish per volume (log-transformed) tended to be negatively correlated with turning rate (rp = 0.53, P = 0.051). No other correlations were found between any of the behavioural parameters and stocking density under hatchery conditions (0.045 < rp < 0.48, 0.081 < P < 0.95). Size disparity was positively correlated with turning rate (Fig. 3A, rs = 0.64, P = 0.026). Moreover, there was a tendency towards size disparity being positively correlated with the proportion of fish swimming against the predominating swim direction (Fig. 3B, rs = 0.54, P = 0.071). There were no significant associations between size disparity and the other parameters measured (0.19 < rs < 0.16, 0.56 < P < 0.98). Size disparity was positively correlated with turning rate (Fig. 3C, rp = 0.59, P = 0.025) and relative swim speed
3. Results Apart from sporadic events, the cod juveniles showed no signs of negative social interactions such as overt aggression, contest competition or cannibalism, neither under experimental conditions, nor in the hatchery. Due to the low frequencies of such behaviours (less than 10 observations of overt aggression during the entire study), analyses of relationships between negative social interactions and density or size disparity were not feasible. The fish that resided close to the bottom of the tank during the second experimental period were shorter than fish further
Fig. 1. Length (mm) of cod juveniles that stayed more than 10 cm above the bottom of the tanks (mid water: black bar) and fish that stayed closer than 10 cm to the tank bottom (bottom: white bar) under experimental conditions.
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Fig. 2. (A) Standardised (z-score) tailbeat rate, (B) average number of observed ‘‘flash’’ per juvenile within a 5-min period, (C) standardised (z-score) proportions of fish swimming against the predominating swim direction and (D) turning rate in relation to fish density as number or biomass of juveniles per m3 under experimental conditions.
(Fig. 3D, rp = 0.57, P = 0.035) and t. There were no significant associations between size disparity and the other parameters measured (0.26 < rp < 0.45, 0.11 < P < 0.99). 4. Discussion Our results indicate that both stocking density and size disparity were associated with variation in behaviours indicative for energetic costs and stress level. However, agonistic interactions and behaviours indicating extreme levels of stress or activity were rarely observed within the size ranges and densities examined. 4.1. Stocking density Under experimental conditions the occurrence of flash and swimming against the predominating swim direction decreased with stocking density, while turning rate decreased with stocking density in the hatchery study. These results show that the swim pattern at higher stocking densities was more synchronized compared to lower densities, as also have been found for rainbow trout cultured at different densities (Be´gout Anras and Lagarde´re, 2004). The swim pattern of the cod juveniles could be characterised as varying from dense shoaling at low densities to schooling at higher densities. In nature, cod juveniles change from a pelagic life style to a more benthic life style at sizes of 2–7 cm, probably because of increased predation pressure (Fahay, 1983; Fahay et al., 1999). After
this descent the coloration of the juveniles mimics the substrate and they are believed to remain on the bottom most of the time (Lough et al., 1989). Settled cod juveniles might be site-attached and defend territories around a shelter (Tupper and Boutilier, 1995), but they may also form loose shoals when shelters are lacking (Salvanes et al., 2007). Thus, the behaviour of the cod juveniles in the current study differed from the behaviour of wild cod juveniles, probably because the extreme fish densities in a culture situation inhibit the natural behaviour due to space and environmental constraints. Whether or not the synchronized swim pattern of cod juveniles in a culture situation is beneficial in terms of increased survival and growth depends on how natural constraints (e.g. predation) shape the behaviour of cod under natural conditions. If the natural swim behaviour of cod is an adaptation to maximize fitness by avoiding predation, schooling behaviour might actually be less costly than the natural swim behaviour of cod juveniles, due to possible energetic advantages of schooling/shoaling (e.g. Pitcher, 1992; Liao et al., 2003; Svendsen et al., 2003). Consequently, the more synchronized swim pattern at higher densities might reflect lower activity costs compared to lower densities. On the contrary, the finding that the tailbeat rate increased with stocking density under experimental conditions might indicate increased costs since tailbeat rate is regarded as a reliable indicator of energy use in fish (Videler, 1993; Webber et al., 2001). An increase in tailbeat rate without a corresponding increase in swim speed might be a sign of augmented costs to
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Fig. 3. (A) Standardised turning rate (z-score of the change in body angle per time) and (B) standardised proportion of fish swimming against the predominating swim direction (z-score) in relation to size disparity (coefficient of variation for body length within each tank) under experimental conditions. (C) Turning rate and (D) swim velocity as body lengths per second in relation to size disparity in each tank and under commercial hatchery conditions.
maintain a constant cruising speed with increasing fish density. However, an increase in tailbeat rate to maintain a constant cruising speed would implicitly involve a decrease in the distance swum per tailbeat, but this was not found. The swim speed in juvenile cod is determined by both tailbeat rate and amplitude (Webb, 2002) and the observed increase in tailbeat rate might also be a consequence of reduced amplitude as response to a higher fish density. In this case the increase in tailbeat rate with increasing density would not represent an increase in activity costs. The possibility that increased density do not involve significantly increased activity costs is supported by the lack of relationships between behaviours indicative for energy consumption or stress level and stocking density in the hatchery study. The decreased frequencies of flash behaviour and swimming against the predominating swim direction with increasing stocking density might also indicate that the level of stress decreased with increasing stocking density. The possibility that increasing stocking density not necessarily involve increased behavioural costs or stress level is supported by the findings of Lefranqois et al. (2001) and Boujard et al. (2002) that stocking density alone is not stressful or costly for the fish, but that increasing density rather might be costly due to decreased individual feed intake. 4.2. Size disparity The turning rate increased with increasing size disparity both under experimental and hatchery condi-
tions. In addition, the relative swim speed increased with size disparity in the hatchery study and there was a tendency towards increased occurrence of swimming against the predominating swim direction with increasing size disparity under experimental conditions. Together, these results indicate that the swim pattern was more irregular with increasing size disparity. This finding concurs with studies on other cultured fishes showing that increasing size disparity result in reduced schooling and increased occurrence of agonistic interactions, which in turn might reduce survival, feed intake and in some cases also growth (e.g. Efthimiou et al., 1994; Sogard and Olla, 2000; Baras and Jobling, 2002; Dou et al., 2004). It has also been shown that feed intake is reduced for smaller fish in mixed sized shoals (Ward and Krause, 2001). As opposed to the behavioural variation in relation to stocking density, it is thus reasonable to suggest that the more irregular swim pattern found at higher size disparities in the current study represent increased activity costs and elevated stress levels (Jobling and Reinsnes, 1986). 4.3. Agonistic behaviour Overt agonistic behaviour was nearly absent and cannibalism was not observed. However, cod juveniles of approximately similar size show higher frequencies of agonistic behaviour at very low stocking densities (Salvanes and Braithwaite, 2005). The absence of such behaviours in the current study may be a consequence of the stocking densities being too high to allow territorially
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or dominance hierarchies, and implicitly also agonistic interactions (Metcalfe, 1990; Brown et al., 1992; Juell et al., 1994). Also, at high stocking densities the behavioural pattern might resemble schooling in nature; a behavioural pattern that usually involve low levels of agonistic interactions (Pitcher, 1992). In addition, the size differences between individuals could have so small that overt conflicts would be too costly because escalated conflicts would result in physical injury or high energy expenditure (Huntingford and Turner, 1987). The absence of overt aggressive and competitive behaviours does not necessarily imply that competition was non-existent. It is possible that competition occurs through more subtle behaviours, e.g. through inexpensive displays or by evaluation of the competitive ability of an opponent on the basis of morphological features or other cues like sounds (Huntingford and Turner, 1987; Pitcher, 1992). The existence of subtle competition is supported by cod juveniles staying close to the bottom of the experimental tanks being smaller than the fish found in mid water. These fish were also observed to feed on pellets lying on the tank bottom. Smaller cod juveniles, with presumably inferior competitive capabilities, may therefore adopt an alternative feeding strategy.
(reviewed in Ellis et al., 2002). The absence of agonistic behaviour in the current study suggests that the welfare status of the cod juveniles was not inferior, at least not when compared to fish farming in general. To what extent the observed behavioural variation affected welfare status is difficult to assess. For instance, the more irregular swim pattern observed at higher size disparities could be interpreted as a weak stress response, which again could indicate reduced welfare. Nevertheless, the lack of physical injuries typically caused by aggressive behaviour and also a general low mortality, indicate that fish welfare was not seriously affected under the specific hatchery conditions for the examined size ranges and stocking densities. Acknowledgements A great thanks to Nick Hughes and Lon Kelly for providing the algorithms for the stereovideo-calculations. We would also like to thank the staff at NTNU Brattøra Research Station and Cod Culture Norway for valuable help during the course of the study. The study was funded by the Norwegian Research Council and Torstein Erboes Foundation. References
4.4. Activity costs and welfare This study indicates that activity costs and stress levels of cultured cod juveniles are associated with stocking density and size disparity within the size ranges and densities examined. The fact that overt agonistic behaviours were nearly absent and that the observed behavioural variation did not reflect considerably elevated levels of stress or activity costs do, however, indicate that the examined densities and size disparities not involve major variations in activity costs. Nevertheless, the size of equally aged cod juveniles differed considerably within and among tanks in the hatchery. This indicates the existence of some sort of mechanism regulating individual fish growth, even under standardised culture conditions. In addition to intrinsic factors like genetic variation or individual health status, the growth differences could be caused by dominant individuals obtaining more resources than sub-dominants through using subtle and inexpensive behavioural signals that were not observable in the current study. It has been suggested that variation in energetic costs associated with varying fish size disparity in a culture situation might be compensated with an increase in feed intake when food availability is not restricted (Folkvord and Ottera, 1993; Sogard and Olla, 2000). This emphasise the importance of using a feeding schedule that ensure equal and sufficient access to food for all fish in a culture unit and that reduce the competition for food. One alternative might for instance be to introduce the food at different levels and positions in the tank. Assessment of behavioural variation might be useful for evaluation the welfare of cultured fishes (Mork and Gulbrandsen, 1994; Heinen, 1998; Pickering, 1998; Chandroo, 2000; FSBI, 2002). For instance, biting and fighting might cause wounds, while intense competition for food might lead to starvation in sub-dominant individuals
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