Pelagic Fish Distribution and Dynamics in Coastal Areas in the Baltic Sea Proper
by Thomas Axenrot
Department of Systems Ecology Stockholm University S-106 91 Stockholm Sweden 2005
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Doctoral Dissertation Thomas Axenrot Department of Systems Ecology Stockholm University SE-106 91 Stockholm Sweden
[email protected]
© 2005 Thomas Axenrot ISBN 91-7155-037-2 Printed by Intellecta DocuSys AB Cover by Thomas Axenrot
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Abstract Pelagic fish distribution and diel behaviour patterns were studied in coastal areas in the north-western Baltic Sea Proper to understand more about how fish distribution and behaviour might affect planning and analyses of results of hydroacoustic surveys (Papers I and II). The vertical distribution of fish at night from spring to autumn showed seasonal and annual trends that could be explained by predictable and consistent seasonal changes, e.g., in temperature and stratification. Horizontal fish distributions did not show any trends probably owing to a lack of such seasonal characteristics. The observed vertical fish distribution over the diel cycle showed that hydroacoustic surveys at night were to be preferred over daytime surveys. At night, fish did not school and were generally less aggregated resulting in less variable hydroacoustic backscattering values and a higher percentage of single echo detections. By starting the surveys one hour after sunset and stopping one hour before sunrise, confusion between day- and nighttime behaviour in fish could be avoided. At night, fish occupied midwater layers to a higher extent than surface and bottom layers, which was beneficial for the quality of the hydroacoustic data, particularly with respect to the hydroacoustic blind and dead zones (i.e. surface and bottom, respectively). To quantify seasonal changes in pelagic fish abundance, densities and size distributions, nighttime hydroacoustic surveys were done every second week from spring through autumn in 2000 and 2001 (Paper III). There was a drastic increase in fish abundance and densities that started in early July and peaked in mid-August in both years. Analyses of the hydroacoustic data in relation to gillnet and trawl catches showed that the increase was caused mainly by young-of-the-year (YOY) herring. This age class is commonly not well represented in catches using traditional sampling methods like gillnets and trawling. Consequently, hydroacoustic data that have high precision and accuracy may improve quantitative estimates and our understanding of the biology in coastal nursery areas. Baltic herring spawn in coastal areas and the density of metamorphosed YOY individuals may provide an early estimate of year-class strength. By analysing the relationship between parameters known to affect recruitment success and year-class strength in age 2 herring (YCS) a model that predicted herring recruitment was developed (Paper IV). The model explained 93 % of the variation in the number of age 2 herring over the period 19852000 and included the parameters YOY densities, climate (North Atlantic Oscillation index) and spawning stock biomass (SSB). Thus YCS could be predicted two years earlier than today and three years before entering the fishery. Up to the present, three new years (2001-2003) have become available for testing the model. For one of these years the predicted YCS was notably different from the assessed YCS. The reason for this is not fully understood, but for all three years SSB was outside the range used in the original model. Including the three new years into the data series resulted in a poorer explanation of the observed recruitment variation (55 %). A comparison of the standardized regression coefficients of both models showed increased significance for the parameter YOY (from 0.47 to 0.61).
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Table of contents
ABSTRACT ............................................................................................................................................................... 3 LIST OF PAPERS ...................................................................................................................................................... 5 1. INTRODUCTION.................................................................................................................................................. 7 2. THE PELAGIC FISH COMMUNITY IN THE BALTIC SEA............................................................................ 7 3. BALTIC HERRING BIOLOGY............................................................................................................................ 8 4. HYDROACOUSTICS............................................................................................................................................ 9 5. PELAGIC FISH DISTRIBUTION AND BEHAVIOUR ................................................................................... 11 6. SEASONAL DYNAMICS AND ABUNDANCE ESTIMATES ....................................................................... 14 7. RECRUITMENT PREDICTIONS FOR BALTIC HERRING........................................................................... 15 8. ACKNOWLEDGEMENTS ................................................................................................................................. 16 9. REFERENCES ..................................................................................................................................................... 17 SVENSK SAMMANFATTNING ........................................................................................................................... 23
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List of papers I
Didrikas, T., Axenrot, T., and Hansson, S. Pelagic fish distribution in relation to water temperature and wind direction; a study in a Baltic Sea coastal bay. Manuscript.
II
Axenrot, T., Didrikas, T., Danielsson, C., and Hansson, S. 2004. Diel patterns in pelagic fish behaviour and distribution observed from a stationary, bottommounted and upward-facing transducer. ICES Journal of Marine Science, 61: 1100-1104. © 2004 International Council for the Exploration of the Sea
III
Axenrot, T., and Hansson, S. 2004. Seasonal dynamics in pelagic fish abundance in a Baltic Sea coastal area. Estuarine, Coastal and Shelf Science, 60: 541-547. © 2004 Elsevier Science
IV
Axenrot, T., and Hansson, S. 2003. Predicting herring recruitment from youngof-the-year fish densities, spawning stock biomass, and climate. Limnology and Oceanography, 48: 1716-1720. © 2003 American Society of Limnology and Oceanography
The published articles are reprinted with the kind permission of the copyright holders.
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1. Introduction This thesis involves two rather different, but in this context intimately linked, fields of science. Hydroacoustic technology is pure physics whereas fish distribution, governed by abiotic and biotic factors, is biology. Hydroacoustic technology has experienced a rapid development over the last decades (e.g. MacLennan & Simmonds 1992, MacLennan & Holliday 1996, Ona 1999), and lately it has been suggested that the bottleneck in interpreting acoustics data now lies in our understanding of fish behaviour (Fréon & Misund 1999). The main focus for my work is on fish and understanding the underlying causes of fish behaviour and distribution. At any given time a fish will be found in a certain position (including depth) which, of course, is not random. To understand more about fish distribution and population dynamics it is necessary to know how the individual fish responds to different ecological factors (Wootton 1998). The total world catch of marine fish for 2002 was 70 million tonnes, of which almost 50 % (34 million tonnes) was represented by small pelagic species, e.g. herrings, anchovies, sardines and mackerels (FAO 2002). FAO (2002) further reports that 75% of the assessed marine fish stocks were fully exploited, overexploited, depleted or recovering from depletion. With overfishing as the most serious human impact on marine ecosystems (e.g. Pauly et al. 1998, Jackson et al. 2001), it becomes increasingly clear that improved methods for stock assessment are needed as well as better understanding of basic fish biology and the variability in fish recruitment (e.g. Ricker 1954, Beverton & Holt 1957, Houde 1989, Bradford 1992, Cushing 1996). Hydroacoustics is today one of the most powerful and commonly used tools worldwide for abundance estimations of pelagic fish, especially in marine environments. It is also independent of information from the fisheries, in contrast to for example landings statistics. Recent advances in hydroacoustic technology and post-processing software have opened up for a wider field of applications, e.g., monitoring of discrete populations or specific environments, studies of fish behaviour and fish migration (e.g. Fréon et al. 1996, Huse & Ona 1996, Kubecka & Wittingerova 1998, Ransom et al. 1998, Torgersen & Kaartvedt 2001, Fabi & Sala 2002, Gauthier & Rose 2002, Axenrot et al. 2004). In Papers I and II, I discuss pelagic fish behaviour and distribution in coastal areas in the Baltic Sea with respect to diel, seasonal and annual patterns to understand how these factors may affect results from hydroacoustic surveys and analyses of data. Paper III makes use of the increased knowledge about the fish in these areas to explore and quantify the seasonal dynamics of herring, reproduction, and larval and juvenile behaviour and distribution. Taken together, this information is used to analyse a long-term data series from hydroacoustic surveys in a coastal region (Paper IV). Here, young-of-the-year (YOY) herring, the size of the adult population (spawning stock), and climate are used to develop a model for early recruitment prediction, making it possible to produce multi-annual quotas as requested by, e.g., the European Commission (Anon. 2001).
2. The pelagic fish community in the Baltic Sea The generally low number of species in the brackish Baltic Sea simplifies the problem of species recognition in the hydroacoustic data. The dominating marine pelagic species in the Baltic Sea are the clupeids herring (Clupea harengus membras L.) and sprat (Sprattus sprattus balticus (Schneider)). Both species have been subjected to intensive fishing, with – at least in herring – far-reaching consequences for spawning stock biomass and recruitment (Fig. 1). However, in the nearest future we might expect a decrease in fishing mortality due to the limited commercial market for Baltic herring and sprat caused by new EU rules on dioxin limits in both human and animal food (fishmeal).
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Herring undertake extensive feeding and spawning migrations and congregate in large numbers close to their spawning grounds prior to spawning, possibly showing natal homing behaviour that separate different stocks (Rajasilta et al. 1993, Parmanne et al. 1994, Fréon & Misund 1999, Kääriä 1999). In the Baltic Sea, the spring-spawning herring has dominated since the late 1960s (Parmanne et al. 1994). Archipelago areas on the Swedish east coast have been shown to house dense populations of YOY herring, with peak densities in late August (Rudstam et al. 1992, Hansson 1993, Axenrot & Hansson 2004). However, information from local fishermen that I have cooperated with over the last 3-4 years, together with personal observations, imply a possible shift back to autumn-spawner dominance. In contrast to herring, sprat are pelagic spawners with eggs and larvae drifting in the offshore pelagic environment. Sprat also occur in bays and estuaries, essentially from one year of age and older. In the coastal waters a few other pelagic species can occasionally and locally be numerous. The most common of these are the European smelt (Osmerus eperlanus (L.)), three-spined stickleback (Gasterosteus aculeatus L.) and vendace (Coregonus albula (L.)). SSB
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Fig. 1. Changes in catch (tonnes), recruitment (millions), size of spawning stock biomass (SSB, tonnes) and fishing mortality (F) for the Central Baltic herring during 1974 – 2004 (ICES 2005).
3. Baltic herring biology The target species for this thesis is herring (Clupea harengus L.; Fig. 2). Herring is a marine species with a wide distribution in the North Atlantic. The whole stock is divided into many different populations depending on geographical distribution, migratory behaviour and spawning periods. Their occurrence throughout the brackish Baltic Sea shows a wide capability of adaptation both physiologically, e.g. to different salinities, and behaviourally, 8
e.g. by timing of spawning or choice of spawning grounds. In the Baltic Sea, herring are also divided into different populations; the Northern and Southern Bothnian, Central Baltic, and Western Baltic spring-spawning herring. Sometimes herring in the Riga Bay and Gulf of Finland are also treated as separate populations. For practical reasons my work has concentrated on the Central Baltic herring, which includes both spring- and autumn-spawners as well as possible local populations with differing migratory behaviour (e.g. Aneer 1989, Parmanne et al. 1994).
Fig. 2. Herring (Clupea harengus L.). Original by W. von Wright, photographed by Carl Erdmann.
Herring are zooplanktivores although large, adult fish may include mysids, amphipods and small fish in their diet (Rudstam et al. 1992, Arrhenius & Hansson 1993, Arrhenius 1996). In the Baltic Sea Proper, which includes the Central Baltic herring, adults are found mainly in offshore areas during most of the year, but spawn in sheltered, shallow coastal areas. Some weeks, or even months, before spawning herring congregate close to their spawning grounds. In the northern Baltic Sea Proper, spawning has been reported from early spring all through summer (e.g. Aneer 1989, Rajasilta et al. 1993, 1996), although the main part of the spawning occurs from May to early June, at a temperature of about 8-12 º C. Eggs are deposited over benthic vegetation down to about 10 m depth and hatch after 7-12 days, depending on temperature (Aneer 1989, Rajasilta et al. 1993, Arrhenius & Hansson 1996, Kääriä 1999) and, possibly, the level of oxygen (Aneer 1989). After spawning the adult fish migrate back to the open sea (Parmanne et al. 1994). When hatching, the larvae are 7-9 mm long (Arrhenius & Hansson 1996). Young larvae have been observed to migrate to the littoral zone, possibly to benefit from higher temperature and food concentrations (Urho & Hildén 1990, Kääriä 1999). The larvae stay in the littoral, shallow areas until they reach a length of about 30 mm, after which they move to the pelagic zone in nearby mid-waters (Urho & Hildén, 1990). The larvae feed during daylight hours in the upper layer of the water column, and are believed not to undertake vertical diel migrations like the older fish (Sjöblom & Parmanne 1978, Arrhenius & Hansson 1996; but see also Batty 1987). At a length of about 35 mm, i.e. late larval/early metamorphosed stages, the larvae also develop schooling behaviour (Gallego & Heath 1994). At the end of August the juveniles are believed to migrate from the coastal nursery areas, probably to nearby offshore areas (e.g. Costa et al., 2002). There are, however, few studies that document and discuss the decline in the number of YOY herring in late summer (Aneer 1979, Rudstam et al. 1988, Urho & Hildén 1990).
4. Hydroacoustics Today, pelagic fish abundance estimations are conducted worldwide using hydroacoustic technology in combination with biological sampling, mainly trawling. Hydroacoustic data also provide information about the size distribution of the fish and can
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identify and characterise schools and layers (MacLennan & Simmonds 1992, Fréon & Misund 1999, Ona 1999). Surveys usually aim at estimating fish stock biomass and numbers, or determining spatial distributions (mapping). The study area must be sufficiently covered with transects to get a proper description of the true conditions. Since fish are not randomly distributed, the survey design must consider the biology of the fish in the area (MacLennan & Simmonds 1992, Rivoirard et al. 2000). Fish life history, behaviour and distribution must be taken into account to decide on appropriate timing (day or night, season) and distribution of acoustic transects (MacLennan & Simmonds 1992, Fréon & Misund 1999). The travelling speed for sound in water is about 1500 ms-1, i.e. more than four times faster than in air. In contrast to light, sound can travel long distances in water. Technically, hydroacoustics is based on generating short sound pulses (pings) with a specific frequency, which for fish detection is usually between 38-400 kHz, and receiving the returning echoes. These functions are performed by a transducer which is the submerged unit of an echo sounder. The backscattered sound is processed in two different ways. All backscattered sound energy is integrated to derive a total fish abundance estimate and a size distribution is produced from echoes of various strengths that were accepted as single echo detections, i.e. accepted as coming from one fish. Additionally, split beam transducers determine the threedimensional position of a fish in the sound beam (MacLennan & Simmonds 1992). With the transducer in a fixed position, in situ studies and measurements of individual fish behaviour are made possible (e.g. Torgersen & Kaartvedt 2001, Cech & Kubecka 2002). For backscattering of sound the most significant part of the fish is the swim bladder, which account for 90-95 % of the total backscattering (Foote 1980, Misund 1997). A swim bladder, however, is not a perfect sphere but differs in shape and size with species and individual fish size which result in differences in the backscattering properties. Thus, in vertical echo sounding the tilt angle of the fish relative to the transducer face is very important for the backscattering (MacLennan & Simmonds 1992, Aglen 1994, McClatchie et al. 1996, Fréon & Misund 1999). It is generally assumed that the tilt angle of fish has a normal distribution which gives an average tilt angle based on all single echo detections (Foote 1987, Aglen 1994). However, an increased tilt angle has been observed in fish when swimming at slow speed, e.g. at night for overwintering herring (Huse & Ona 1996), which resulted in a bimodal tilt angle distribution over 24 hours for the same congregation of fish. Increased tilt angle has also been observed in connection with diel vertical migration (McQuinn & Winger 2003). The swim bladder size is also affected by other factors like for example fat content, gonad size and depth (Ona 1990, Aglen 1994). The influence of fat content on fish buoyancy and thus on swim bladder size is important in the case of the Baltic herring. In comparison with Atlantic and North Sea herring, the Baltic herring is less fatty and occupies a habitat with lower salinity. A larger swim bladder compensates for the resulting lower buoyancy. Consequently, a Baltic Sea herring will give a stronger echo than a North Sea herring of equal size. There are several reports on fish avoiding boats, including research vessels of course, which may jeopardize the quality of the hydroacoustic data. There is quite a lot of variation in the reports about the eliciting distance between the vessel and the fish as well as different reactions depending on boats, species, bottom depth, day and night, spawning period etc. (thoroughly summarised in Fréon & Misund 1999), but avoidance has been observed down to 150 m depth (Vabö et al. 2002). When avoiding a vessel the fish can try to escape either horizontally or vertically. In the first case, fish will not be acoustically registered at all and thus will not be included in, e.g., abundance estimates. In the second case the tilt angle of the diving fish will bias results and fish abundance will be underestimated (e.g. Olsen et al. 1983, Misund et al. 1996). There are also reports of herring and sprat schools being herded in front of the vessel. The presence of a thermocline affects sound propagation and may accordingly
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affect fish reactions. Several studies report no or only limited fish reactions to small boats (Fréon & Misund, 1999). However, avoidance reactions should generally be considered for surveys aiming for abundance estimations or fish distribution, especially in relatively shallow waters like coastal areas or the Baltic Sea. It has been suggested that the difference in catchbased and hydroacoustic estimations on the herring stock in the Baltic Sea can be assigned to avoidance behaviour during the hydroacoustic surveys (Ona, pers. comm.). As described in Paper II, fish abundance, distribution, behaviour etc. were studied using stationary hydroacoustics with the aim of not causing any disturbance that could affect fish behaviour, like avoidance reactions. In July/August and mid-August 2001 mobile vertical “downwardfacing” surveys were performed in the bay of Himmerfjärden, passing an area where a bottom-mounted stationary “upward-facing” transducer was positioned. A comparison of abundance, densities, size distribution, and the vertical distribution of these parameters, indicated the possibility of avoidance reactions in the mobile surveys (Fig. 3). If so, and if the capability of avoiding an approaching vessel develops over the summer in YOY fish, this might also affect the perception of the vertical distribution of fish, as discussed in Paper I. Another explanation, although not yet thoroughly studied, might be that fish avoided being close to the bottom-mounted transducer because of the regularly emitted sound pulses (pings). The hydroacoustic equipment used in my studies is an EY500 portable echo sounder with a 70 kHz split beam transducer (Simrad AS, Norway). The surveys have been performed with two boats, 8 and 12 m long. Data from before 1997, used for the long-term time series in Paper IV, were collected using a 70 kHz single beam transducer (Simrad EY/M). The Institute of Marine Research (Swedish Board of Fisheries) has kindly provided data from their annual surveys covering the offshore areas of the Baltic Sea. Fish abundance
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Fig. 3. Similarities and differences in fish abundance, densities and vertical distribution between stationary and mobile hydroacoustics at night in the same area. sA (nautical area backscattering coefficient) is an index for fish abundance.
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5. Pelagic fish behaviour and distribution Pelagic fish behaviour plays a major role in hydroacoustic fish stock assessment surveys (e.g. Fernö & Olsen 1994), and may be the bottleneck in interpreting acoustics data (Fréon & Misund 1999). To learn more about fish behaviour, distribution and population dynamics it is necessary to know how the individual fish responds to different ecological factors (Wootton, 1998). This knowledge is needed when hydroacoustic surveys are planned and performed as well as when results are being analysed and interpreted (MacLennan & Simmonds 1992, Fréon & Misund 1999, Rivoirard et al. 2000). Modern hydroacoustic technology and postprocessing software make studies of fish behaviour in their natural environment possible, as individuals, in shoals or schools. Some environmental data, like e.g. bottom depth and topography and the depth of the fish, are included in the hydroacoustic data. Additional environmental data may be needed depending on the aim of the study, like water temperatures, light intensities and food availability etc. Fish distribution is governed by habitat selection and migration. These topics are of primary interest in stock assessment and fisheries management (Kramer et al. 1997, Fréon & Misund 1999), but also crucial in understanding fish distribution and ecology at individual, species and community levels. Contrary to its appearance the pelagic environment is not homogenous. It can be characterised by differences in abiotic and biotic factors such as temperature, oxygen, salinity, transparency, light intensity, presence of conspecifics, prey or predators (Fréon & Misund, 1999). The choice of habitat (habitat selection) often differs among species, and sometimes even between populations of the same species, as for example with herring. Life history also affects habitat selection, e.g., by separating adults and juveniles (Fréon & Misund, 1999). Factors that influence habitat selection are divided into ultimate (long-term, functional) and proximate (short-term, immediate response, causation) cues (Noakes 1992). Here, the focus is mainly on the latter. There are several abiotic and biotic factors that are believed to influence fish behaviour and distribution, discretely or in combination. For example, the timing or synchronisation - zeitgeber – of diel vertical migrations can be caused by changes in light intensity, with possible physiological connection to the pineal organ, or be indirectly related to the behaviour and distribution of prey or predators (Neilson & Perry 1990, Ali 1992, Fréon & Misund 1999). In tidal areas, both adult fish and larvae are known for vertical migrations to the rhythm of the tides (24.8 hours), which is slightly different to the circadian rhythm (24 hours; Gibson 1992 and 1993, Kramer et al. 1997). Diel patterns also vary due to other circumstances, such as reproduction period, habitat or latitude (Helfman 1993). In high latitudes, as in the Baltic Sea, many behavioural patterns are seasonally dependent (Helfman 1993, Wootton 1998). Migration can be studied on different time and space scales. Circadian, ultradian and tidal rhythms include migrations within short time intervals, for example diel (daily) vertical migration. Lunar and semi-lunar cycles occur within months, seasonal or annual rhythms within years (Ali 1992, Gibson 1992 and 1993, Leatherland et al. 1992, Noakes 1992, Helfman 1993). Many anadromous and catadromous semelparous species have cycles covering several years, as for example the European eel, Anguilla anguilla (Fréon & Misund, 1999). Cushing (1996) has suggested even longer time-scales, like climatic changes over hundreds of years, affecting patterns of fish migration, distribution and numbers. Fisheries, or maybe more accurately failures in fisheries management, have shown to affect migration patterns probably as a result of drastically changing the population size, exemplified by the Norwegian spring-spawning herring after the 1960s (Dragesund et al. 1997, Fréon & Misund 1999, Toresen & Östvedt 2001). Such a potential link between the overfished and declining stock of the Central Baltic herring (Fig.1) and the decreasing Swedish coastal fishery for herring is often discussed but has so far not been well investigated. A similar, nearby example is the alleged effect of the Finnish trawl fishery on the Swedish coastal herring fishery in the
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Bothnian Sea. Furthermore, if a migratory population is heavily fished in contrast to a more sedentary population in the same region this might be selective for the sedentary population (Fréon & Misund, 1999), which would be a complicating element in the case of herring that are separated in discrete populations. Fish naturally live their lives in a three dimensional environment. This means that their distribution needs to be analyzed from both a horizontal and a vertical perspective. Horizontal fish distribution studies usually compare abundance or densities between areas or along transects (e.g. Jurvelius et al. 1996, Maravelias et al. 1996). The temporal and spatial scales for such observations may affect the results (Boudreau 1992, Maravelias & Haralabous 1995). Horizontal distributional patterns and migration have been observed in relation to, e.g., food concentrations, high primary production, and temperature fronts (Moser & Smith 1993, Maravelias & Reid 1995, Fréon & Misund 1999, Helle & Pennington 1999, Nöttestad et al. 1999). The effect of wind stress on fish distribution is usually restricted to larvae and juveniles (Pepin et al. 1995, Margonski 2000), often in relation to larval survival and recruitment (e.g. MacKenzie et al. 1994, Cushing 1996). There is also the question of whether larvae are just transported “passive particles” or actively choose their habitat (e.g. Lazzari et al. 1993, Smith et al. 2001, Hindell et al. 2003). There are, however, observations of larvae moving out from vegetation to open water at night (Romare & Bergman 1999) or migrating from the littoral to the pelagic zone at a given stage in the metamorphosis (Urho & Hildén 1990), as well as differences in the number of migrating larvae depending on moon phase (Gaudreau & Boisclair 2000). Vertical fish distributions have been studied from many abiotic and biotic aspects, like light, temperature, oxygen, salinity, bottom depth and topography, food availability, predators and life stages. Temperature has been considered one of the most important factors since body temperature in fish is governed by the surrounding water temperature. Fish are very sensitive to temperature differences and can detect temperature variations smaller than 0.1º C (Hoar & Randall 1979). This allows them to orientate towards areas favourable to their metabolic needs (Batty 1994), or detect remote frontal areas where prey may be more abundant (Fernö et al. 1998, Misund et al. 1998, Fréon & Misund 1999). The thermocline is quite often referred to as a boundary for fish habitat selection (Perry & Neilson 1988, Swartzman et al. 1994, 1995), although a variety of factors may be involved in the process of habitat selection related to the thermocline (e.g. Ciannelli et al. 2002, Swartzman et al. 2002, Gray & Kingsford 2003). Horizontal and vertical fish distributions were studied in relation to wind conditions and water temperatures in the bay of Himmerfjärden from spring through autumn for two consecutive years (Paper I). Relating horizontal distribution to wind direction showed no seasonal or inter-annual trends. Restricting the analysis spatially to the upper layer and temporally to the larvae/juvenile period gave contradictory results for the two years separately and showed no trend for the two years combined. In contrast, the vertical fish distribution showed an annual trend that was much the same for both 2000 and 2001. Fish biomass generally moved towards greater depths through the season, staying in the relatively warmer surface water in spring and in the colder part below the thermocline in summer. In the period July to August, this gradual change towards greater depths might also reflect a developing capability in YOY fish of avoiding an approaching vessel, as discussed above in section 4. When small and large fish were studied separately, results showed – after a thermocline had established - that the small ones stayed in and above the thermocline, i.e. in the zone with warmer water and higher primary production, while large fish preferred staying in the cold water below the thermocline. It should be noted that all surveys in this study were done at night when there is little or no feeding activity of the pelagic fish in the area (Arrhenius & Hansson 1994). Metabolic benefits may be the cause of habitat choice for both the small and the large fishes. Small fish, like larvae and YOY juveniles, benefit from rapid growth and
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development which make them less vulnerable to predation (Houde 1994, Cushing 1996). Large fish are favoured by a slow metabolic rate at night when they are not feeding (e.g. Levy 1990). The horizontal and vertical fish distributions observed over seasons and between years suggest some fundamental difference in the mechanisms that determine habitat choice. Seasonal cycles in water temperatures, the establishing and breaking up of a thermocline, and food production are characteristic for coastal areas and lakes at these latitudes (55°-69° N; e.g. Horne & Goldman 1994). Such predictable features can explain much of the spatial distribution and temporal changes in the fish community. Some of these features, like for example the thermocline, are present for months and likely provide the basis for the annually repeated distribution patterns that were observed (e.g. Fernö et al., 1998). The horizontal fish distribution did not show any seasonal or interannual trends and a possible explanation might be a lack of corresponding long-term, stable environmental conditions that direct the fish to some specific distribution or distributional trend over the season. The main objective in Paper II was to study possible effects of diel behaviour in pelagic fish on hydroacoustic survey results. To perform this study without causing fish avoidance reactions or attraction to floating equipment the transducer was placed on the bottom facing upwards and connected to a land based echo sounder. The results provided information that was valuable for survey planning, analyses and interpretation of the hydroacoustic data. The observed vertical fish distribution over the diel cycle showed that hydroacoustic surveys at night were to be preferred over daytime surveys. At night, fish did not school and were generally less aggregated resulting in less variable hydroacoustic backscattering values and a higher percentage of single echo detections. By starting the surveys one hour after sunset and stopping one hour before sunrise, confusion between day- and nighttime behaviour in fish could be avoided. At night, fish occupied mid-water layers to a higher extent than surface and bottom layers, which was beneficial for the quality of the hydroacoustic data particularly with respect to the hydroacoustic blind and dead zones (i.e. surface and bottom, respectively).
6. Seasonal dynamics and abundance estimates In Paper III the aim was to follow and quantify pelagic fish abundance, densities and size distributions from spring to autumn in a typical herring spawning and nursery area. In the first year (2000), the surveys started in late May and continued until November. In 2001 the surveys started in early May, to pick up any patterns that might have been missed the previous year, and the last survey was done in September since fish abundance and densities in year 2000 did not seem to experience any significant changes in late autumn. Based on knowledge on fish behaviour, distribution (Papers I and II), the fish community and life histories in this area (e.g. Rudstam et al. 1988, 1989 and 1992, Aneer 1989, Hansson 1993, Hansson & Rudstam 1995, Arrhenius & Hansson 1996 and 1999), the surveys were all done at night, planned to start at least one hour after sunset and ending one hour before sunrise. Around midsummer the surveys had to be performed during the darkest possible period as they lasted for about three hours. Results showed a similar trend both years with a drastic increase in abundance and densities from mid-July. The variation (geostatistical coefficient of variation) of the mean abundance (nautical area scattering coefficient, sA) of the surveys was rather low and similar both years. To understand more about the ecological consequences of the observed seasonal dynamics, fish size distribution and the proportion of small YOY juveniles needed to be analysed further. Gillnet catches, trawling and the hydroacoustic data all gave somewhat different results, although trawling results and hydroacoustic data were more similar than
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gillnet catches. For different reasons, that are discussed in Paper III, small YOY larvae and juveniles are typically not well represented in traditional sampling gears like gillnets or trawls. It is suggested in Paper III that hydroacoustics in this and similar situations and areas might help to improve estimates of small juvenile fish densities in order to get a better understanding of the biological processes. A reasonably reliable estimate of annual recruitment may be valuable for different reasons like, for example, early assessments of yearclass strength (e.g. Cushing 1996) or identifying possible reproductive disturbances of importance for environmental monitoring.
7. Recruitment prediction for Baltic herring The strength of a year-class (YCS) is often first assessed when it enters the fishery. Catch quotas for Baltic Sea herring are presently based on estimated abundance of age groups that are already recruited to the fishable stock, i.e. usually from age 3. Naturally, it would improve management substantially if YCS could be determined from densities of younger fish, not yet significantly affected by the fishery (Paper IV). This would also make a longer time perspective possible with multi-annual quotas as requested by the European Commission (Anon. 2001). Estimates of YCS should be derived at the earliest when the young fish have passed larval and early metamorphosed stages (Bradford 1992, Cushing 1996). Previous studies in the north-western Baltic Sea Proper have shown that mid-August is a suitable time to assess YCS from hydroacoustic densities of YOY herring (Axenrot & Hansson 2004). The most important factors that affect recruitment success are spawning stock biomass (SSB), food availability, temperature and other climatic factors. Owing to a lack of relevant data, food availability was not included in this study other than indirectly through the North Atlantic Oscillation index (NAO). Over the last years, the Baltic herring SSB has been at very low levels (Fig. 1). The steady decline right up to year 2002 introduced a complication when testing the model (Paper IV). Initially, ten years of data were available for the model from a period of sixteen years (1985-2000). This is rather few data to develop a model on fish recruitment. As a consequence, there were no years left to test the model. Years 2001-2003 have provided new data to test the model, i.e. to compare predicted YCS with observed YCS of age 2 herring two years later. Only in 2002 the predicted YCS was within the confidence limits (95%) of the model. In 2003 the predicted YCS was notably different from assessed YCS. However, the SSB for 2001-2003 (41.1, 42.8 and 68.4, respectively) were all outside the data range for SSB when the prediction model was developed (90.5-208.6). Including the three new years into the data series, thus creating a new model, resulted in a poorer explanation of the observed recruitment variation (93 and 55 %, respectively). A comparison of the standardized regression coefficients of both models showed that the parameters SSB and NAO decreased in significance (0.36 to 0.10 and 0.58 to 0.44, respectively) while YOY increased (from 0.47 to 0.61). There is a fundamental difference between the parameters. YOY is a direct, although regional, measure of recruitment success while both SSB and NAO describe conditions that are believed to be important for this process. There may well be other conditions, as e.g. food availability, local variability or things yet to be described, that are equally or even more important than SSB and NAO for recruitment success. For two of the added years (2001 and 2003), YCS were very high despite the lowest SSB in the time series (Fig 4). In the original model SSB had the weakest effect of the three parameters which might seem surprising, but pelagic species have high fecundity with a stock–recruitment relationship that is generally weak because of high and variable egg and larval mortality (Houde 1994, Cushing 1996). However, very low SSB is supposed to have a
15
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3500 YCS2 (millions in SD 27)
YCS2 (millions in SD 27)
restraining effect on the incidence of strong year classes, even if climatic conditions are favourable. This did not seem to be the case in our study for YCS in 2001 and 2003. A possible explanation could be that a substantial part of the adult fishes, constituting the SSB, migrated out of subdivision 27 after spawning and were thus not registered as part of the SSB for this subdivision. However, SSB was low in the whole Central Baltic for this period (Fig. 1). Another – at least theoretical – possibility is that intense fishing had reduced the stock after spawning but before the Board of Fishery assessment surveys in October, although fishing mortality has been decreasing after year 2000 (Fig. 1). When NAO and YCS are compared, one year (2003) had a high YSC although NAO was among the lowest (Fig. 4). Influence from neighbouring subdivisions should not matter in this case as climate factors associated with the NAO index generally affect the whole region. However, NAO effects on local or regional scales that might affect recruitment success in herring have not been studied. The correlation between YOY and YCS (r2=0.48; Fig. 4) was strengthened when the three years were added, supporting the suggested link between year-class strength in metamorphosed juveniles and recruitment (Bradford 1992, Cushing 1996). It is quite possible that YOY alone might provide better precision in predicting recruitment if information from more coastal areas was included.
3000 2500
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2001-2003 R2 = 0.094
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Fig. 4. Correlations between year-class strength of age 2 herring (YCS2) and spawning stock biomass (SSB) from subdivision 27 (SD 27) in the Baltic Sea, climate (North Atlantic Oscillation index, NAO) and young-of-the-year (YOY) densities of metamorphosed herring in the AsköHimmerfjärden area in the Baltic Sea. Filled dots represent data from the ten years that were used in the initial recruitment prediction model. Open dots represent data from the following three years. Grey dots represent data from 1987-2000 that could not be used in the original prediction model (see further in Axenrot & Hansson 2003).
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8. Acknowledgements/Erkännanden Ett stort tack till min handledare Sture Hansson som har en enastående entusiasm för allt som rör fisk och liv i vatten. Din tilltro till mig och min forskning kan inte överskattas. Dessutom har Du alltid med entusiasm och ofta överraskande snabbt givit mig respons på funderingar, problem och manuskript. Jag vill även tacka Tomas Didrikas som jag haft ett nära samarbete med under flera år. Speciellt under fältarbeten, ofta med arbete både dag och natt, har vårt samarbete varit smidigt och effektivt. Dessutom har det varit roligt! Börje Larsson i Grönvik har ställt upp med båtar, utrustning och inte minst sina stora kunskaper om 16
fisk och fiske från sitt liv som yrkesfiskare. Tack även till skeppare Nicki Bagger på Askö. På Systemekologiska Institutionen vill jag tacka rumskamraterna under åren – Olle Hjerne, Jason van Tassel, Gustaf Almqvist och Martin Ogonowski - för trevlig samvaro och givande diskussioner. Därutöver tack även till de på institutionen som hjälp mig under åren med synpunkter, manuskript, material, datorer mm – Ragnar Elmgren, Gunilla Ejdung, Calle Rolff, Ulf Larsson, Elena Gorokhova, Charlotte Danielsson, Lars Gustavsson, Berndt Abrahamsson, Svante Nyberg, Anders Sjösten och Leif Lundgren. Fredrik Arrhenius, Nils Håkansson och Niklas Larson på Havsforskningslaboratoriet i Lysekil har vänligen bistått med data från Fiskeriverket. Olle Enderlein och Peter Ahlander på Fiskeriverket har ställt upp med båt och trålning i Himmerfjärden.
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Svensk sammanfattning Denna avhandling handlar huvudsakligen om att förstå förändringar i beteende och utbredning hos pelagiska fiskar, i synnerhet strömming. Pelagiska fiskars beteende spelar en avgörande roll för hydroakustiska undersökningar som bl. a. syftar till att bestämma beståndsstorlek. För att förstå mer om fiskars utbredning och populationsförändringar är det nödvändigt att känna till hur enskilda fiskar reagerar på olika ekologiska faktorer. Hydroakustisk teknik erbjuder de bästa möjligheterna att studera pelagisk fisk i deras naturliga omgivning. Pelagiska fiskars utbredning och variationer i beteende över dygnet studerades i kustområden i nordvästra Egentliga Östersjön för att bättre förstå hur utbredning och beteende kan påverka planering och efterföljande analyser av resultat för undersökningar som genomförs med hjälp av ekolodning (Papers I och II). Fiskars vertikala fördelning nattetid från vår till höst visade på såväl säsongs- som årsvis likartad variation. Dessa variationer kunde förklaras av förutsägbara och stabila karaktärsdrag i omgivningen som t ex temperaturdynamiken under säsongen eller temperaturstratifiering på sommaren. Den horisontella utbredningen uppvisade inte några liknande trender vilket sannolikt hänger samman med att stabila strukturerande förhållanden saknas. Den vertikala fördelningen över dygnet visade att undersökningar nattetid är att föredra framför dagtid. På natten upphör stimbildning och fiskarna är allmänt mer utspridda vilket resulterar i lägre variation i resultaten samt högre andel enskilda ekosvar. Genom att påbörja undersökningarna en timme efter solnedgången samt avsluta dessa en timme före soluppgången undviks en blandning av dag- och nattbeteenden hos fisk. Nattetid uppehåller sig fisk i högre grad i mellanlagren, dvs i mindre omfattning nära yta och botten. Detta är positivt för kvaliteten på hydroakustiska data eftersom fisk nära ytan och botten är osynliga för ekolodet. För att kvantifiera förändringar i fiskmängd, tätheter och storlekar över säsongen genomfördes hydroakustiska undersökningar varannan vecka från vår till höst under år 2000 och 2001 (Paper III). I början av juli inleddes en kraftig tillväxt av både fiskmängd och täthet, och som nådde sin högsta nivå i mitten av augusti båda åren. Analyser och jämförelser av ekolodningsdata med resultat från nätprovfisken och trålning visade att ökningen till största delen bestod av årsungar av strömming. Denna åldersgrupp är vanligen dåligt representerad vid nätprovfisken och trålning. Följaktligen kan hydroakustiska data av hög kvalitet och precision förbättra kvantitativa skattningar och därmed förståelsen av biologin i lek- och uppväxtområden i kustområdena. Strömming leker vid kusten och mängden strömmingsungar som passerat larvstadiet kan ge en tidig skattning av storleken hos en årsklass. Analyser av förhållanden mellan olika parametrar som påverkar lekframgång och storleken på årsklassen 2-årig strömming resulterade i en modell som förutspår rekrytering till strömmingsbeståndet (Paper IV). Modellen förklarade 93 % av variationen hos årsklassen 2-årig strömming under perioden 1985-2000 och beräknades med hjälp av parametrarna yngeltäthet (hydroakustiska data från kustområden), klimat (North Atlantic Oscillation index) och lekbiomassan (strömming ≥ 3 år). Med denna modell kunde storleken på årsklassen 2-årig strömming förutspås två år tidigare än idag och tre år innan man börjar fiska på denna årsklass. Fram till nu har tre nya år (2001-2003) blivit tillgängliga för att testa modellen. För ett av dessa år blev den förutspådda årsklasstyrkan anmärkningsvärt annorlunda än den två år senare skattade mängden. Orsaken till detta är inte helt klarlagd, men för de tre nya åren var lekbiomassan i samtliga fall lägre än vad som ingick i den ursprungliga modellen. Av de tre parametrarna var det endast yngeltäthet i kustområden som stärktes av att inkludera de tre nya åren i modellen, och denna parameter uppvisar enskilt den starkaste korrelationen med skattad årsklasstyrka.
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