Aquat Ecol (2009) 43:1121–1131 DOI 10.1007/s10452-008-9215-6
Hydroacoustic fish biomass assessment in man-made lakes in Tunisia: horizontal beaming importance and diel effect Imed Djemali Æ Rachid Toujani Æ Jean Guillard
Received: 1 February 2008 / Accepted: 5 September 2008 / Published online: 25 September 2008 Ó Springer Science+Business Media B.V. 2008
Abstract We used a Simrad EK60 echosounder equipped with two split-beam transducers to develop a sampling strategy for assessing fish resources in Tunisian man-made lakes. Day and night surveys, using vertical and horizontal beaming, were carried out between December 2006 and February 2007, a period when fish catchability is high. Four reservoirs with differing surface areas and bathymetries were selected. Echogram analysis revealed that fish communities were mainly composed of individual targets. A few schools were detected near the surface during daylight, but these schools dispersed slightly at night. In these multispecies reservoirs, considerable day and night differences in density existed, but with no clear trend. Target strength (TS) distribution mode values detected at night were always lower or equal to daytime values. Biomass estimates were significantly higher during daytime in three reservoirs,
corresponding with higher TS modal values. In the other reservoir, the biomass estimate was significantly higher during nighttime corresponding with higher mean density during this period. Using only a vertically aimed transducer in our study reservoirs would have led to an underestimate of density and biomass by 5–100% and 20–100%, respectively, depending on the man-made lake. We conclude that acoustic sampling in our reservoirs must be done during day and night and that both vertical and horizontal beaming must be used to obtain the best possible picture of the fish stocks. Keywords Echosounder Day and night Reservoir Water column Horizontal beaming
Introduction
I. Djemali (&) R. Toujani Institut National des Sciences et Technologies de la Mer, 28 rue du 2 Mars 1934 Centre de Salammboˆ, 2025 Tunis, Tunisia e-mail:
[email protected] J. Guillard Institut National de la Recherche Agronomique, Station d’Hydrobiologie Lacustre, UMR CARRTEL, BP 511, 74203 Thonon les Bains, France
The exploitation of freshwater fish resources in Tunisia is more recent than sea fishing. It constitutes only 1% of the national catch (Anonymous 2006). Because of the semi-arid climate of North Africa, freshwater is a rare and unevenly distributed resource in Tunisia. Storage of the surface water resources of a large part of the Tunisian territory was made possible by building 27 dams. The large scale introduction of freshwater fish in the early 1990 created fisheries that must be managed. The main species exploited in the reservoirs are carp
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(Cyprinus carpio), roach (Rutilus rubilio), and rudd (Scardinius erythrophthalmus), as well as species with higher commercial value, such as mullet (Mugil cephalus and Liza ramada) and pikeperch (Sander lucioperca) (Djemali 2005). This fisheries activity can only be maintained in the long term by monitoring fish stocks, which are still rarely assessed in Tunisia (Toujani 1998; Djemali 2005). Fish population monitoring by acoustic methods is recognized by the scientific community as a viable tool (Lyons 1998; Swierzowski et al. 2000; Guillard et al. 2004; Stetter et al. 2006), but the method is limited by the low volume of water sampled near the vertically aimed transducer (Burczynski and Johnson 1986), which can be problematic when trying to detect fish located near a surface. Thus, to sample the upper layers of the water column, horizontal beaming has been employed in freshwater lakes and reservoirs (Hughes 1998; Kubecka and Wittingerova 1998; Yule 2000; Drastik and Kubecka 2005). Other studies have used only vertical beaming (Brandt et al. 1991; Nyberg et al. 2001; Cyterski et al. 2003; Schimdt et al. 2005). The choice between these two ways of sampling is due to the knowledge of the fish vertical distributions. Some fish species occupy different layers from the surface to bottom on a diel basis (Fre´on et al. 1993; Guillard et al. 2006), which can impact biomass assessment (Appenzeller and Leggett 1992; Schael et al. 1995; Taylor et al. 2005; Winfield et al. 2007). The presence of (1) fish in surface layers and (2) day and night migrations must be taken into account when choosing the best sampling strategy. Djemali et al. (2003) carried out the only acoustic study in a Tunisian man-made lake, so understanding of the spatial distribution of freshwater fish in these ecosystems is limited. These first results, obtained in spring 2000, showed that fish did not have gregarious behaviour (Djemali et al. 2003), but that study was carried out only during daytime using vertical beaming which may have significantly biased the density data (Knudsen and Sægrov 2002). The objectives of this study were to (1) determine how acoustic size structure, density and biomass vary by photoperiod and (2) how density and biomass vary according to water layer. Results will allow us to define a preliminary acoustic sampling strategy for biomass assessment in Tunisian reservoirs.
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Material and methods Study area Four reservoirs characterized by different depths and surface areas (Table 1) were selected for study. The selection also took into account the presence or absence of carnivorous fish (i.e. pikeperch) that can impact both prey fish population dynamics and distribution patterns. Masri Reservoir is located in the area of the Cap Bon in the northeast Tunisia (36°310 9500 N, 10°290 2700 E). It was filled in 1968 and is used exclusively for irrigation. The main species are mullet, pikeperch and barbel (Barbus callensis). The reservoir has a surface area of 66 ha and is 4.4 m deep. Joumine Reservoir, located in the northern portion of the country (36°580 4800 N, 9°350 3200 E), was filled in 1983 and provides irrigation for 1500 ha of farm land in the Mateur area. It has an area of 660 ha and a mean depth of 11.7 m. The indigenous Tunisian species, barbel (Kraiem 1989), and mullet are the only fish species in Joumine reservoir. Siliana Reservoir, filled in 1987, is located in northwest Tunisia (36°080 0500 N, 9°210 3500 E) with water used to irrigate a large surrounding area. It has a similar surface area as Joumine, but is much shallower. The fish species present are mullet, carp, pikeperch and rudd. Sidi-el-Barak Reservoir, located in the extreme northwest of the country (37°000 4700 N, 9°010 3100 E), has been used since 1999 for irrigation and to improve the water quality of the Medjerda canal used to supply drinking water to Tunis. The species fished are mullet, pikeperch, herbivorous carp (Ctenopharyngodon idella), eel (Anguilla anguilla) and barbel. It has a much larger surface area (2734 ha) than the other three reservoirs. Surveys were carried out between December 2006 and February 2007 (Table 1), when fish yield was the highest (Djemali 2005). In each survey, the temperature and oxygen profiles were measured, using a Wissenschaftlich Technische Werksta¨tten (WTW) depth probe, model oxi 197i, provided with a 50 m cable (Nova Analytics Company, Weilheim, Germany). Acoustic sampling The day and night acoustic surveys were carried out by zigzagging at a constant speed of 3 knots (Fig. 1). The degree of coverage values calculated for each
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Table 1 Hydraulic characteristics and degree of acoustic coverage for the studied reservoirs Reservoir Sampling period
Area Volume (million m3) (ha)
7
Average depth (m)
66
Maximum depth (m)
Vertical average temperature surface/ bottom (°C)
Vertical average oxygen concentration surface/ bottom (mg/l)
Degree of coverage day/night 7.1/6.8
Masri
21/02/2007
4.4
10.6
13.8/13.7
6.5/6.4
Joumine
15/01/2007 130
660 11.7
29.3
13.2/13.0
7.2/7.0
6.3/6.1
Siliana
05/12/2006
70
600
3.8
9.5
14.5/14.3
8.5/8.2
6.5/6.7
Sidi-elBarak
14/02/2007 264
2734
8.3
22.5
13.4/13.2
6.2/6.0
6.7/6.5
Fig 1 Maps of the four Tunisian reservoirs with the sampling design and the three strata defined (U = upstream; M = middle; and D = downstream)
D
U
M
Sidi-el-Barak 1
0
Scale in Kilometers
D
M U
Masri 0
D
1
Scale in Kilometers
M
D U
M U 0
1
Joumine 0
1
Scale in Kilometers Scale in Kilometers
survey using the formula of Aglen (1983) ranged from 6.1 to 7.1 (Table 1). These coverage values exceeded the level recommended by Aglen (1983). Each man-made reservoir was divided into three zones with similar surface areas (upstream, middle and downstream). We used a portable sounder (SIMRAD EK60), equipped with two 120 kHz split-beam transducers connected by a multiplexer to the ‘‘General Purpose Transceiver’’ (GPT). One transducer was circular with half power beam width of 7° and was aimed vertically. The other transducer
Siliana
had an elliptic beam of 4 9 10 and was used for horizontal beaming. Both transducers were mounted on a stainless steel stand, to fix them at 0.5 m below the surface. The 0–3 m layer was sampled using horizontal beaming and the deeper layer using vertical beaming. Surface sampling is very sensitive to bad weather (Mouse and Kemper 1996; Knudsen and Sægrov 2002; Gangl and Whaley 2004) and to transducer aiming angle (Balk 2001), so surveys were always carried out when there was little wind (no waves on the reservoirs) with the horizontal
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transducer always tilted 2° below horizontal. Night surveys began one hour after sunset. The echosounder was connected to a portable computer, which provided a real-time display and data storage. A global positioning system (GPS) was used to determine the geographical coordinates. The pulse length was fixed at 0.256 ms, with a repetition rate of 10 pings per second with transducers beaming alternately (i.e. fast multiplexing at 5 pings per second per channel). Data analysis The hydroacoustic data were analysed using Sonar5pro software (Balk and Lindem 2006), based on image analysis which greatly improves fish detections in noisy environments (Balk 2001), such as surface water reservoirs. The filters used were those recommended by the software manufacturer, and we varied the foreground filter width only from 1 to 3, depending on the noise level in the echograms. The extraction criteria for the single targets were as follows: minimum value = -70 dB; minimum echo length = 0.8; maximum echo length = 1.2; maximum gain compensation = 3 dB and maximum phase deviation = 0.8. The equipment was calibrated before the four surveys using a 23 mm diameter copper sphere, following the protocol of Foote et al. (1987). The acoustic data was processed for the individual targets by echo counting (Balk and Lindem 2006), using a maximum range of 50 m for horizontal beaming. The algorithm selection criterion for tracking was set to at least 4 echo detections; no more than 2 lost echoes were permitted, with a maximum allowable depth difference of 0.3 m for consecutive echoes. The noise threshold was fixed at -70 dB for both target strength (TS) in 40 log R and volume backscattering in 20 log R time varied gain (TVG). By convention, the nominal transducer beam width, measured on a one-way polar plot, is defined as -3 dB down from the acoustic axis. Therefore, targets as small as -64 dB (two-way spreading loss) were detectable throughout the nominal beam width (Yule 2000). The species size–TS relationships of our fish populations have not been studied, so we decided to apply a general size–TS relationship for fish sampled with a vertically aimed transducer (Love 1977). Because we had no individual length and weight measurements, we estimated mean weight from TS predicted mean lengths using the cube law
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whereby a fish’s weight is proportional to the cube of its length. For horizontal beaming, we used a TS–weight equation of freshwater fish species developed by Kubecka and Duncan (1998) at all aspects. We felt application of this equation to our 120 kHz data was appropriate because Horne and Clay (1998) concluded TS of fish should be comparable when using transducers with operating frequencies exceeding 100 kHz. TSmean = 5.66 log W-53.2 where W = fish weight in grams The applied thresholds allowed detection of fish targets more than 0.98 cm in total length (L) in downlooking aspect (Love 1977), and 1.05 cm in standard length (SL) in side-looking aspect (Kubecka and Duncan 1998). Combining image analysis and target tracking allowed us to distinguish fish from noise using our applied thresholds. Because the reservoirs have different depths and fish occupied the entire water column, we choose to express density estimates on a volumetric basis. Whole transects were used as elementary sampling distance unit (ESDU) as recommended by Jolly and Hampton (1990). For each ESDU, we obtained from tracked fish the acoustic size distribution in decibel (dB), the mean TS, fish density (fish/1000 m3) and fish biomass estimates (g/1000 m3). The water column was divided into two layers: surface to 3 m depth sampled by the horizontal beaming and 3 m depth to the bottom sampled by the vertically aimed transducer. The average density and biomass obtained for each zone of the reservoirs corresponded to the weighted average of the ESDU densities (Sokal and Rohlf 1981): iP ¼n
ðAi Vsi Þ x ¼ i¼1 i¼n p P Vsi i¼1
where xp is the weighted average biomass (or density), n is the number of transects per area, Ai is the biomass (or density) along transect i and Vsi is the sampled volume of transect i. Statistical data analysis First, we compared the day and night acoustic TS distributions using one of the most powerful
Aquat Ecol (2009) 43:1121–1131
nonparametric test of Mann–Whitney (Zar 1999). In order to test the influence of the photoperiod (day and night), strata (upstream, middle and downstream) and the beaming method (vertical and horizontal) on fish biomass, a multifactor analysis of variance (MANOVA) was performed. Statistical tests were performed with ‘‘Statistica’’ Software (version 5.5) with a set at 0.05. To compare biomass according to strata, MANOVA was followed by Tukey HDS post hoc test when significant differences were found. The dependant variable for the MANOVA was biomass (g/1000 m3) with the ESDU values serving as sample units. The data were log10 transformed to stabilize the variance.
Results
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sufficient for comparison. Differences in TS distribution observed across photoperiods in the upper surface waters (top 3 m) were also significant (P \ 0.01) at all four reservoirs. Fish per unit volume was not systematically more in either photoperiod in both surface and deeper layers (Fig. 3). For the biomass estimates, the trend was the same as the TS distribution modal values. For Siliana Reservoir, the biomass was significantly higher in nighttime than in daytime (F = 25.29, P \ 0.000, Error df = 90) contrary to the other three man-made reservoirs where the biomass were statistically higher during daytime (Masri: F = 103.65, P \ 0.000, Error df = 52; Sidi-el-Barak: F = 42.57, P \ 0.000, Error df = 84; Joumine: F = 803.33, P \ 0.000, Error df = 78). Interactions between photoperiod, layers and strata were also highly significant (P \ 0.000).
Fish behaviour During the study period, the vertical oxygen and temperature profiles in the four reservoirs were homogeneous (Table 1), and fish were observed throughout the water column. Marked degasification phenomena were observed in the reservoirs, but fish densities in these waters were not noticeably lower compared with areas without gas bubbles. In the reservoirs sampled, fish seldom displayed gregarious behaviour during the day or at night. In one case, the downstream sector of Sidi-el-Barak Reservoir, schools were detected near the surface during daylight: large schools and smaller ones often found close together. At nighttime, we observed a scattering of the large schools leading to an increase in smaller schools. Influence of photoperiod The mode values of the TS distribution between day and night were higher (between -6 and -9 dB) during daytime in both layers at Joumine, Masri and Sidi-el-Barak reservoirs (Fig. 2) indicating that the largest fish (i.e. fish targeted by fishers) were more accessible during day. In contrast, at Siliana Reservoir mode values of the TS distribution did not vary across photoperiods. Mann–Whitney tests showed TS distributions gathered by vertical beaming varied across photoperiods (P \ 0.01) at three lakes (Joumine, Masri and Siliana) where sample sizes were
Influence of strata For Siliana Reservoir, biomass in different strata differed significantly (P \ 0.000), increasing from upstream to downstream (differences between two strata with Tukey test were always significant P \ 0.00). For Joumine, Masri and Sidi-el-Barak Lakes, differences between the three strata were significant (P \ 0.000 with MANOVA); however, differences were not systematic compared with other in these three man-made lakes. Usefulness of horizontal beaming For Siliana Reservoir, biomass estimate (g/1000 m3) did not significantly (P [ 0.05) differ between surface (0–3 m) and underlying (3 m to bottom) layers. But for the other three reservoirs, biomass did significantly (P \ 0.000) differ between layers. It was higher in the superficial layer (0–3 m) for Sidiel-Barak and Masri and in the deep water (more than 3 m) for Joumine Reservoir. According to day data, only in Sidi-el-Barak Reservoir were both densities and biomass detected in surface layer were always higher than the deeper layer (Table 2). The fish density in the 0–3 m layer varied between 5 and 100% (compared with the density of the entire water column in day data), while biomass estimates varied between 20 and 100%.
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1126 m = - 49 dB m' = - 55 dB n = 1486 n' = 614
Joumine (V)
40
%
40
m = - 46 dB m' = - 52 dB n = 1723 n' = 711
Joumine (H)
20
20
0
0 m = - 58 dB m' = -64 dB n = 32 n' = 167
Masri (V)
40
%
40
m = - 52 dB m' = -58 dB n = 3613 n' = 2118
Masri (H)
20
20
0
0 m = not enough data m' = - 52 dB n = not enough data n' = 84
Sidi-el-Barak (V) 40
m = - 55 dB m' = - 64 dB n = 930 n' = 2581
Sidi-el-Barak (H) 40
%
Fig. 2 TS frequency distribution of the fish sampled in the four reservoirs. The white bars correspond to the daytime data, and the black bars represent the night-time data (3 dB width for day and night). (V) and (H) indicate vertical and horizontal beaming, respectively. m and m0 represent, respectively, day and night mode. n and n0 represent, respectively, day and night number of tracked fish. When the TS distribution is bimodal we presented the higher mode value. Predicted total fish length (L) was obtained with the formula of Love (1977) in vertical beaming and standard length (SL) with the all aspects and all species equation of Kubecka and Duncan (1998) in horizontal beaming
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20
20
0
0 m = - 46 dB m' = - 46 dB n = 2732 n' = 3956
Siliana (V)
40
%
40
m = - 43 dB m' = - 43 dB n = 20 711 n' = 29 936
Siliana (H)
20
20 0
0 -70
-64
-58
-52
-46
-40
Target strength (in dB) L ≤ 6 cm
Discussion Tunisian dams are essential for good management of the country’s water resources, but can also be an important contribution to fish yield in areas far from the coasts. We have shown that it is necessary to sample fish during both day and night because TS distribution mode values were not always higher in daytime for the four reservoirs. For Siliana Reservoir, mode values of the TS distribution were the same during day and night, but biomass estimates were higher at night. A gradient in fish biomass according to geographic strata was only apparent in Siliana Reservoir where fish biomass was higher downstream compared with upstream. We have shown the need to sample the Tunisian reservoirs with horizontal beaming because there was not always statistically more
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6 < L ≤ 17,8
L > 17,8 cm
-70
-64
-58
-52
-46
-40
Target strength (in dB) SL ≤ 7,1 cm
7,1 < SL ≤ 22,3
SL > 22,3 cm
fish biomass in the deep-water layer ([3 m depth) compared with the surface layer. Densities varied considerably between surface and deeper layers because of spatial and temporal mobility of the fish populations that showed no clear behavioural tendencies. There was no water column structuring related to temperature or oxygen levels, which could organize the spatial distribution of fish. During this study, fish were detected using single echo detection (SED) methods after applying a -70 dB threshold. Traces from targets were detected with image analysis (Balk and Lindem 2000). Using the same technique with Sonar6-pro, Jurvelius et al. (2007) stated that fish and noise due to invertebrates could be successfully discriminated at a single frequency by thresholding and cross filtering. For this study, if we have used a threshold of -55 dB in
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1127 V 10000
Biomass (g/1000 m 3)
Density (Fish/1000 m 3)
100000
10000
1000
100
10
100000
100
10
10000
H Biomass (g/1000 m 3)
Density (Fish/1000 m 3 )
1000
1
1
10000 1000
100 10
1
V
u
m Siliana
d
u m d Joumine
u m d Sidi-el-Barak
u
m
d
Masri
H
1000
100
10
1
u
m d Siliana
u
m d Joumine
u m d Sidi-el-Barak
u
m d Masri
Fig. 3 Mean fish density and biomass in vertical (V) and horizontal (H) beaming (u = upstream; m = middle; and d = downstream). The white bars correspond to the daytime
data, and the grey bars represent the night-time data (error bars show standard deviation)
Table 2 Percentage of fish densities (P1) and biomass (P2) per strata located in the 0–3 m layer versus the total value from surface to the bottom for surveys of four Tunisian reservoirs
threshold would have likely precluded detection of 20 mm mullet fingerlings in side-looking aspect that are regularly stocked in Tunisian man-made lakes during autumn (Kraiem et al. 2001). Both at sea and in lakes, fish tend to form schools during the day and disperse at night (Fre´on and Misund 1999). This schooling behaviour identified for species such as herring Clupea harengus (Skaret et al. 2003; Cardinale et al. 2003) and young perch Perca fluviatilis (Guillard et al. 2006), arises from night-time feeding and predator avoidance strategies. In our study reservoirs, we detected schools only in the downstream stratum of Sidi-el-Barak Reservoir; presumably the fish were mullets, which are known to display gregarious behaviour (McFarland and Okubo 1997) while other main species in this reservoir (pikeperch and the herbivorous carp) do not. These schools displayed a different behaviour from that described for mullets by Fre´on et al. (1993) with schools still present at night, but smaller and nearer the surface possibly to optimize plankton filtration (Cardona pers. comm., International University Study Center, Barcelona, Spain). It is possible that gregarious behaviour in our reservoirs may be limited to a
Reservoirs Siliana
Joumine
Sidi-el-Barak
P1 (%) Upstream
28.38
74.14
Middle
23.99
24.07
Downstream
83.34
26.99
Upstream
4.83
48.91
Middle
8.40
25.99
18.91 78.80
20.27 98.57
100.00
100.00
90.46
99.57
Downstream Upstream Middle Downstream
Masri
P2 (%)
Upstream
15.59
66.65
Middle
23.00
80.71
Downstream
70.17
61.01
SED (Yule 2000; Jurvelius et al. 2005) instead of -70 dB after filtering, small echoes with fish-like characteristics would have been removed. In fact, some targets with few detections would have been eliminated altogether with the selected tracking parameters used (Fig. 4). Further, a -55 dB
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Fig. 4 Echograms in vertical beaming (Joumine) showing fish before and after image analysis and with two thresholds ((a) threshold: -70 dB in SED before filters; (b) threshold: -70 dB in SED after image analysis; (c) threshold: -55 dB in SED after image analysis). Yellow lines represent bottom, while black circles (b) represent some fish removed in the -55 dB threshold echogram
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short time period. In any case, fish schools in our study reservoirs were positioned far from the reservoir bed but deep enough below the surface to allow acoustic detection during both day and night by horizontal beaming. This is opposite to what Knudsen and Sægrov (2002) observed for European whitefish Coregonus lavaretus schools near the lakebed that could not be effectively sampled by vertical beaming. Higher biomass estimate during day than at night was linked to having larger modal TS values during this photoperiod. Where TS mode values were higher during day (Joumine, Masri and Sidi-el-Barak), biomass estimate of the entire water column was also significantly greater during the day, evidence that fish biomass should be assessed during this period because it corresponds to the highest number of large fish targeted by fishers. Where the TS modal values during day and night were similar (Siliana reservoir), the biomass was significantly higher at night because mean density was higher during this period. We conclude that the acoustic sampling on Siliana Reservoir is best done at night. The measured TS of a fish depends on the fish behaviour at the time the boat passes overhead, since this affects the angle by which they are detected (Gauthier and Rose 2001; Lilja et al. 2004; Frouzova et al. 2005; Simmonds and MacLennan 2005). Day and night difference in TS mode values were observed for herring in the Baltic Sea and these differences were attributed to changes in fish behaviour between the two photoperiods (Axenrot et al. 2004). Cadic (2002) found that in reservoirs that are not vertically structured, as those of our study, there is a tendency for fish to gather close to the banks at night for trophic reasons, resulting in a higher individual tilt, and therefore a lower TS than in the open water. The number of targets detected in the day and night often differed, so it is possible we may have dealt with species that do not move in the daytime and so are seen only at night, or vice versa. By studying the variability of the day and night transects in the population estimate of threadfin shad (Dorodoma petense) in Lake Texoma (Texas, United States), Vondracek and Degan (1995) recommended night sampling. Yule (2000) recommended day sampling for trout because at night they move close to surface so that they are obscured even with horizontal
Aquat Ecol (2009) 43:1121–1131
beaming. Other authors have recommended monitoring fish populations at night to account for the scattering of the fish schools in the darkness (Appenzeller and Legget 1992; Schael et al. 1995), but in our reservoirs this problem did not arise because schools were rare and individual fish were mostly dispersed during both night and day. We conclude the choice of day and night sampling in Tunisian reservoirs should be made when TS intensity is maximum because (1) it corresponds to the best accessibility to the resource and (2) the bigger fish are the fish most vulnerable to passive fishing gears like gillnets used by fishers. Upstream, middle and downstream densities during both day and night showed no clear trends in the four reservoirs we studied. According to day vertical beaming data, downstream fish density in Siliana Reservoir was lower than the middle and upstream strata, while biomass was higher, consistent with big fish occupying deep water and small fish occupying shallower upstream areas. These results are in accordance with the study of Dekar and Magoulick (2007), where fish density was negatively related to maximum depth, and with the study of Power (1987), who asserts that increasing maximum depth can result in greater predation risk from larger aquatic predators. In Masri, Joumine and Sidi-el-Barak reservoirs, statistical analyses indicated no biomass gradient existed across strata; nevertheless, assessment could be improved with specific species size–weight relationships of fish from Tunisian reservoirs. We conclude that there does not appear to be a real benefit to stratifying our reservoirs. Finally, concerning the beaming orientation, our study has shown that acoustic sampling without horizontal beaming can result in conservative estimates of both density and biomass. In Joumine Reservoir, such estimates were always higher (more than 50%) in vertical beaming than in horizontal, while in the Sidi-el-Barak Reservoir both fish density and biomass were greatest in the 0–3 m layer compared with deeper water (Table 2). At Masri Reservoir, more than 50% of fish biomass was estimated to be present in the surface layer. These results are in accordance with many acoustic studies (Johnston 1981; Tarbox and Thorne 1996; Kubecka and Wittingerova 1998; Knudsen and Sægrov 2002). In terms of density, the percentage of fish detected in the surface layer relative to the entire water column
1129
(surface to reservoir bed) varied between 5 (upstream Joumine during daytime) and 100% (middle Sidi-elBarak in daytime). For areal densities, Knudsen and Sægrov 2002 found that between 20 and 100% occurred in the upper layer. Kubecka and Wittingerova (1998) showed that densities detected by vertical beaming alone could be 2–50 times lower because of fish escapes. This could be an important factor in the upstream stretches of our study reservoirs where the water was quite shallow and the entire fish biomass was near the surface. Mouse and Kemper (1996) claimed that the uppermost 4 and 5 m depths are often devoid of fish for this reason. Our study shows that even in deeper waters horizontal sampling is necessary, because we found that in downstream areas of Siliana, Sidi-el-Barak and Masri reservoirs more than 70% of fish occupied surface waters (Table 2). If fish spatial distribution is confined to a clearly identified depth layer, far from the surface, it might be possible to sample without horizontal beaming (Linlokken 1995). When climatic conditions are satisfactory (i.e. no wind) and transducer tilt in water is appropriate, we obtained good quality data by horizontal beaming, thanks to image analysis provided by Sonar5-pro.
Conclusions In our study reservoirs, schools were rare and fish were, for the most part, dispersed during both night and day. Normally, assessment biologists choose a photoperiod based upon when fish behaviour is conducive to maximum detectability. We found no clear advantage for day or night sampling, so we recommend sampling when TS intensity is maximized. By using this approach, we will obtain the highest number of large fish targets that represent the sizes being harvested. In order to estimate fish biomass, it is necessary to sample using both vertical and horizontal beaming because both the surface layer (0–3 m) and deeper layer ([3 m) had high fish biomass. According to day data, exclusive use of a vertical transducer would have underestimated density and biomass by 5–100% and 20–100%, respectively, depending on the reservoir studied. Future work must pair acoustic methods with other sampling gears in order to have complementary informations about fish population.
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1130 Acknowledgements The study was financed by the Tunisian Ministry for Higher Education and Scientific Research, and was carried out as part of the research project ‘‘GRAVID’’. We would like to thank Dr. F.R. Knudsen from Simrad Horten in Norway for his kindness and advice, and also Dr. H. Balk from the University of Oslo for his kind assistance. We would like also to thank Dr. L. Cardona from the University of Barcelona for providing information about the behaviour of mullet. We express our gratitude to the people in charge of regional fishing in the districts of Be´ja, Nabeul, Siliana and Bizerte for their assistance. Special thanks to the two anonymous referees for improving the manuscript and to Daniel Yule for his great help and advice.
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