20 Years of the German Small-Scale Bottom Trawl Survey (GSBTS): a Review

Senckenbergiana maritima 37 (1) 13 – 82 Frankfurt am Main 30.03.2007

20 years of the German Small-Scale Bottom Trawl Survey (GSBTS): A review

Siegfried Ehrich, Sara Adlerstein, Uwe Brockmann, Jens Floeter, Stefan Garthe, Hilmar Hinz, Ingrid Kröncke, Hermann Neumann, Henning Reiss, Anne F. Sell, Manfred Stein, Vanessa Stelzenmüller, Christoph Stransky, Axel Temming, Gerd Wegner & Gerd-Peter Zauke

With 50 Figures, 18 Tables, and 1 Appendix

Keywords: fish assemblages, predator-prey interactions, geostatistics, benthos, seabirds, nutrients, hydrography, temporal variation, sampling method, scale, survey design, IBTS, North Sea

Abstract

[Ehrich. S. et al. (2007): 20 years of the German Small-Scale Bottom Trawl Survey (GSBTS): A review. – Senckenbergiana maritima, 37 (1): 13 – 82, 50 Figs., 18 Tabs., 1 App., Frankfurt a. M.]

The German Small-scale Bottom Trawl Survey (GSBTS) was initiated in 1987 in order to provide complementary investigations to the International Bottom Trawl Survey (IBTS) in the North Sea, using the same methodology but focussing high-intensity sampling on selected survey areas. Over the last 20 years,

the initial number of 4 survey areas (10 ×eschweizerbartxxx 10 sng- nautical miles; “Boxes”) has been increased to 12, which are distributed over the entire North Sea. This paper describes the survey methods of the GSBTS, summarizes the scientific outcome of the first 20 years, and suggests that international fisheries research institutions would join the GSBTS. The major outcomes of the survey include to date: – Documentation changes in the distribution of fish species and in species assemblages (e.g. changes in species richness, shifts in the southern species component). – Geostatistical evaluation of GSBTS data. – Analysis of spatial scale effects: the relevance of GSBTS survey results for interpreting large-scaled abundance and distribution data from the IBTS. – Description of benthic habitats, composition of invertebrate fauna and its variability. – Process studies, especially investigation of predator-prey interactions between fish through analyses of stomach contents. – Characterization of the typical hydrographic conditions in the survey areas and their variability, and description of the nutrient supply. – Observations of seabirds and their feeding habits.

Authors’ addresses: Siegfried Ehrich [corresponding author: [email protected]],Anne F. Sell, Manfred Stein, Christoph Stransky, Gerd Wegner, Federal Research Centre for Fisheries, Institute for Sea Fisheries, Palmaille 9, D-22767 Hamburg, Germany Sara Adlerstein, University of Michigan, School of Natural Resources and Environment, 3010 Dana Building, Ann Arbor, MI 48109 – 1041, USA Uwe Brockmann, University of Hamburg; Institute of Biogeochemistry and Marine Chemistry, Martin-Luther-King-Platz 6, D-20146 Hamburg, Germany Jens Floeter, Axel Temming, Institute of Hydrobiology and Fisheries Science, University Hamburg, Center for Marine and Atmosphaeric Sciences, Olbersweg 24, D-22767 Hamburg, Germany Stefan Garthe, Research & Technology Centre (FTZ), University of Kiel, Hafentörn 1, D-25761 Büsum, Germany Hilmar Hinz, Ingrid Kröncke, Henning Reiss, Hermann Neumann, Senckenberg Institute, Department of Marine Research, Südstrand 40, D-26382 Wilhelmshaven, Germany Vanessa Stelzenmüller, Institute of Marine Science (ICM-CSIC); Passeig Marítim de la Barceloneta, 37 – 49; 08003 Barcelona, Spain Gerd-Peter Zauke, Carl von Ossietzky Universität Oldenburg, Institut für Chemie und Biologie des Meeres (ICBM); Postfach 2503, D-26111 Oldenburg, Germany

– Analysis of the effects of different parameters on catch rates for bottom fish and on the estimates of abundance indices (e.g. vessel and gear effects, towing time, hydrographic conditions, time of day, number of hauls per area). In continuing this interdisciplinary survey with simultaneous sampling of all faunal and environmental compartments and especially in making it an international effort, we see the possibility of contributing data for the implementation of the ecosystems approach to fisheries management. Particularly, the following aspects can be addressed and would further increase the scientific value of the GSBTS: – Combining the survey data with highly resolved data from the commercial fishery to separate the effects of fishing from natural variability. – Further interdisciplinary analyses of the entire data set. Main aspects include benthos-fish-bird-community changes over time and their relation to historic fisheries impacts, and the coupling of biological and physical habitat characterisation. – Collection of accompanying data (phyto-, zoo- and ichthyoplankton data) in order to make the GS- BTS a true ecosystem survey in detecting temporal changes in nearly all major levels of the food web.

Contents

Introduction...... 14 The importance of spatial scales ...... 66 Survey description...... 15 Spatial scales: the relevance of GSBTS survey results Boxes...... 15 for interpreting large-scaled abundance and distribution Sampling methods...... 15 data from the IBTS ...... 66 Statistical precision of the survey data...... 18 Analysing predator-prey interactions at large and small scales... 67 Topical studies...... 19 Scientific value of the GSBTS and applications Hydrography...... 19 in management...... 75 Nutrients...... 28 Future perspectives...... 76 Fish fauna...... 33 Acknowledgements...... 77 Sediments and benthos...... 57 References...... 77 Seabirds...... 61 Appendix...... 82

Introduction rectangle. With these highly resolved catch data, information is gained to address several specific issues: The event that triggered the “German Small-Scale Bot- 1. spatio-temporal characteristics of fish assemblages, tom Trawl Survey” (GSBTS) was a 2-ship comparative fish- 2. calculation of abundance indices of recruiting year-classes ing experiment carried out for 10 days in June 1986.eschweizerbartxxx sng- Fishing of commercially important species and comparison with hauls within a 15 × 16 nm area in the northern North Sea were those of the IBTS, carried out by both ships in parallel, when the FRV ANTON 3. small-scale variability in the distribution of age-groups of DOHRN was to be taken out of commission and replaced by commercially important fish species, the FRV WALTHER HERWIG, which took over the German 4. the generation of long-time data sets of fish assemblages demersal fish surveys in the North Sea. To compare the cap- to quantify the influence of climatic change or of anthro- ture efficiencies of the vessels using the same “GOV trawl”, pogenic impact, e.g. through fisheries, installation of wind to investigate the effect of changing from the previously used parks or establishment of Marine Protected Areas, “180-feet herring trawl” and to adapt the GOV trawl and its 5. quantification of the response of ground fish tohydro- rigging to “International Young Fish Survey” standards (later graphic conditions (e.g. water mass distribution, stratifica- the “International Bottom Trawl Survey”, IBTS), 179 hauls tion, weather events), were made by both vessels within the ten days and the rela- 6. association of ground fish species to benthic habitats and tively small area (Ehrich 1991). The observed high variability benthos communities, of catch data even for relatively evenly distributed species like 7. quantification of the effects of biological processes such as haddock and between hauls located close to each other raised food availability and predation and uncertainties about the validity of conclusions from the coarse 8. quantification of changes in fishing gear (e.g. sweep length) scale surveys like IBTS in relation to specific questions. and haul parameters (e.g. time of day, towing duration). In the following year the GSBTS was introduced with the Apart from the initial four Boxes, in order to expand the goal of providing highly resolved information on the bottom survey over the entire North Sea, further Boxes were added fish fauna of the North Sea. Initially, four survey areas of 10 and a second vessel, the FRC SOLEA has joined the survey in by 10 nautical miles each, the so-called “Boxes”, were selected. 1989. By now, both vessels jointly conduct the GSBTS and However, in the meantime the survey has been extended to 12 simultaneously visit six Boxes each during every summer and investigation areas, distributed over the entire North Sea. The selected Boxes more than once per year. The allocation of indi- GSBTS now includes a subset of the areas covered by the IBTS vidual Boxes to the two ships remains the same. (International Bottom Trawl Survey) and follows a comple- From the start of the survey, hydrographic measurements mentary sampling approach. Compared to the two IBTS hauls (CTD profiles) and nutrient analyses have accompanied the per ICES rectangle (30 × 30 nautical miles), around 20 – 30 sampling in the Boxes aboard the WALTHER HERWIG. Since hauls are made in each Box, covering one ninth of an ICES 1999, the epibenthos communities have also been regularly 15 analysed in the six W. HERWIG-Boxes. Aboard SOLEA, the N and P) and the North Sea Task Force Area (7d; Box H). survey considers the fishing and hydrographic sampling only. The remaining two Boxes, L and M were set up in order to During the survey each Box is typically sampled during provide a more even coverage of the North Sea as a whole. In three consecutive days with up to 10 hauls made in day-light general, selection criteria were the location on relatively clean per day as far as the regular survey was concerned. Occasional and smooth fishing grounds and the absence of oil and gas rigs process studies accompanied the regular survey: originally and pipelines. However, in the meantime rigs and pipelines not planned such as the determination of the influence of a have been moved into some of the Boxes. strong gale on the vertical distribution of fish (section “Effects In Tab. 1, the exact positions of the Boxes and the number of hydrographical, weather and light …”, p. 37), or partly of hauls until the end of 2005 are listed, in Tab. 2 the first year planned such as the investigations on feeding hot spots (sec- of survey in each Box. In total, 4323 hauls were conducted tion predator-prey interactions …”, p. 49), or planned such since 1986 within the Boxes, with a focus on Box A, the cen- as the comparison of fishing power for the two vessels used tral Box within the German Bight. 3965 hauls (92%) were car- (section “Effects of technical changes”, p. 33). Additional days ried out under standard conditions (see sampling methods). were included for special purposes such as the investigation of day-night differences in the catches or for the evaluation of technical details in the ground gear or its rigging, e.g. the Sampling methods sweep length. The large international surveys in the North Sea, such as Normally, each Box is allocated to one survey vessel. How- the International Bottom Trawl Survey (IBTS) and the Inter- ever, Boxes A and N are an exception for logistical reasons: national Beam Trawl Survey (BTS) primarily pursue the goal from 1991 to 1998 SOLEA also fished in Box A during the of gaining information on the condition of commercially im- summer while W. HERWIG III works in Box N in January. portant fish stocks in the North Sea. They provide the basis for Within the period of the GSBTS no changes in type of gear stock assessment by obtaining indices of population structure took place. However, both vessels were replaced; in January and recruitment or growth rates and thereby provide a status 1994 WALTHER HERWIG by WALTHER HERWIG III and analysis of the stocks, which forms the basis of recommenda- in June 2004 old SOLEA by the new SOLEA (Tab. 3). In both tions for fisheries management. The primary goal of the -GS cases, comparative fishing with the respective old and new BTS on the other hand is the analysis of small-scale ecological vessels were conducted to evaluate the effect of vessel change function, as it is tailored to investigate small-scale patterns and (section “Effects of technical changes”, p. 33). When theWAL - ecological processes. The GSBTS provides information on the THER HERWIG was substituted by the WALTHER HERWIG effects of spatial scales, on the interactions of bottom fish with III a calibration experiment was undertaken. The results of this their physical environment, and biological interactions with study indicated that the performance in terms of catch rates of benthic organisms or within the fish community. The survey is the vessels was similar (Ehrich et al. 1994). in essence a process-oriented complement to the status analysis Both FRVs SOLEA are smaller than the WALTHER HER- provided by the large-scale surveys. We are not awareeschweizerbartxxx sng- of any WIG and WALTHER HERWIG III and have weaker engines, comparable effort in any other extended region of the Euro- therefore requiring different fishing gears (Tab. 3). The Grande pean seas. Ouverture Verticale (GOV) gear used aboard WALTHER This review describes the survey methods and summarizes HERWIG and WALTHER HERWIG III has been extensively the most important outcomes of the GSBTS by presenting described in the IBTS manual (ICES 2006a). The height of the the individual publications that are based on survey data, by gear’s vertical opening is around 4.5 to 5 m with a wingspread adding new analyses, and by suggesting focus topics for future of around 20 m. The net is equipped with 20 cm diameter studies based on the GSBTS. rubber disk ground gear in the bosom, 10 cm rubber disks in the net wings with iron disks fixed between them to give extra weight. The cod end has a fine mesh liner of20mm Survey description mesh opening. The gear used during RV SOLEA surveys (the cod hopper “KJH”; see Appendix 1) is a net which was com- Boxes monly used by the German commercial fisheries in the early seventies for catching cod and is now the standard SOLEA gear The locations of the twelve 10 × 10 nm GSBTS survey ar- for the North Sea. The opening height is somewhat smaller eas (“Boxes”) shows Fig. 1 and indicates the allocation of the than that of the GOV, i.e. 3.5 m, the wingspread of 23 m is vessels to the Boxes. Table 2 indicates the year of first sampling larger (Dahm et al. 1996). Further, the KJH ground rope has for each. The Boxes of the GSBTS are distributed over the spaces between the 20 cm rubber disks, whereas in the GOV entire North Sea, four in the Exclusive Economic Zone (EEZ) ground gear the disks are fixed without intermediate space. To of the UK, three in German waters, two in Norwegian waters, get a close contact to the bottom, the KJH is fitted with 22 kg one in the EEZ of the Netherlands, one in Danish waters and weights at the wing tips. The cod end liner is similar (20mm one on the border between Denmark and Norway. On the mesh opening) to that of the GOV. basis of previous surveys, the first Boxes (A-D) were selected Since 1991 the part of the GSBTS carried out by W. HER- due to the high probability of good catches of gadoid species, WIG is embedded in the ICES co-ordinated “International especially cod. The north-western part (100 nm²) of the com- Bottom Trawl Survey (IBTS)”. Therefore, time shifts from parison fishing area from 1986 became Box D (Fig. 1). Some the third to the second quarter of the year became necessary additional Boxes were installed because of the special respon- when Germany took part in the Quarter 2 IBTS from 1991to sibility of Germany for these areas: the German EEZ (Boxes 1996. From 1997 onwards the GSBTS moved back into the 16

eschweizerbartxxx sng-

Fig. 1: Positions of the Boxes and the borders of the EEZs in the North Sea. third quarter, when the IBTS Q2 survey stopped and all avail- ning of the additional benthic investigations aboard W. HER- able ship time had to be concentrated into quarter 3. In recent WIG III, a standard procedure most commonly used during years, both vessels of the GSBTS operate from mid July un- the 3 days in a Box has been established: til the end of August. However, there are additional activities 1. trawling (GOV) at 21 stations, within the frame of the GSBTS which take place during other 2. CTD at 15 of these stations and times of the year. During one week in January, Boxes A and N 3. nutrients, epibenthos, and sediment analyses at 9 of these are sampled to investigate seasonal changes in fish and epiben- stations. thos assemblages. Therefore, for 9 stations per Box, data for all the above Normally, a vessel stays for 3 successive days in one Box. listed parameters are available. The total number of haul varies between 20 and 30 due to fur- In some years and Boxes, the program was extended be- ther programs accompanying fishing. Since 1998, the begin- yond the standard to investigate changes in fishing parameters 17

Table 1: Positions of the Boxes, depth range, total number of hauls until summer 2005, and number of standard hauls (hauls carried out under standard conditions, compare Tab. 4).

BOX latitude longitude depth [m] hauls standard hauls from to from to from – to up to 2005 up to 2005 BOX A 54°17' N 54°27' N 006°58' E 007°15' E 36 – 45 1047 915 (281) BOX B 55°16' N 55°26' N 000°18' W 000°00' W 68 – 81 392 378 BOX C 56°33' N 56°43' N 005°10' E 005°28' E 55 – 65 399 397 BOX D 57°48' N 57°58' N 000°44' W 001°04' W 90 – 115 667 547 BOX E 53°50' N 54°00' N 004°40' E 004°57' E 36 – 44 302 298 BOX F 52°23' N 52°33' N 002°25' E 002°41' E 42 – 53 366 363 BOX H 56°20' N 56°30' N 002°20' E 002°38' E 69 – 78 340 322 BOX K 55°25' N 55°35' N 006°18' E 006°36' E 37 – 44 315 313 BOX L 58°40' N 58°50' N 002°23' E 002°43' E 105 – 119 126 125 BOX M 60°17' N 60°27' N 002°22' E 002°42' E 83 – 112 132 132 BOX N 54°43' N 54°53' N 007°30' E 007°48' E 17 – 26 162 120 (60) BOX P 55°10' N 55°20' N 004°40' E 004°58' E 43 – 50 75 55 total 4323 3965

Table 2: Years when different activities in the Boxes started on a regular basis (bold) or were carried out on individual occasions.

BOX fish assemblage CTD nutrients epibenthos infauna sediment fish stomachs bird observations since since since since BOX A 1987 1987 1987 1998 1999, 2003, 2004 1996, 1999 1999, 2000 1994, 1995, 2005 BOX B 1987 1987 1987 1998 1999, 2003, 2004 1996, 1999 1996, 99, 00 1994, 1995, 2005 BOX C 1987 1987 1987 1998 1999, 2003, 2004 1996, 1999 1999, 2000 1994, 1995, 2005 BOX D 1986 1986 1986 1998 1999, 2003, 2004 1996, 1999 92, 96, 99, 00 1994, 1995, 2005

eschweizerbartxxx sng- BOX E 1989 1989 – – – – – – BOX F 1989 1989 – – – – – – BOX H 1991 1991 – – – – – – BOX K 1991 1991 – – – – – – BOX L 1999 1999 1999 1999 1999, 2003, 2004 1999 1999, 2000 1994, 1995, 2005 BOX M 1999 1999 1999 1999 1999, 2003, 2004 1999 1999, 2000 1994, 1995, 2005 BOX N 2000 2000 2000 2002 – 2002 – – BOX P 2003 2003 – – – – – –

Table 3: Details on vessels conducting the survey.

vessels type length GRT speed, max. towing speed [m] [tons] [kn] [kn] Walther Herwig stern trawler 81 2251 14 4 Walther Herwig III stern trawler 64.5 1596 13.5 4 Solea (old) cutter 35 337 10 3.5 Solea (new) cutter 41 638 12.5 3.5 such as haul duration, sweep length or time of day (day-night on a total number of 81 possible pre-selected positions within effect) on the catch. Table 4 gives an overview of additional a Box: the distances between these positions in latitude as well sampling for specific purposes. as in longitude are one nautical mile. The selection of towing The position and direction of hauls are randomly selected directions is based on a total of 72 possible directions (in steps for each Box and survey year. The choice of stations is based of 5 degrees) to avoid personal preference of the captain for 18

Table 4: Standard and additional investigations in the Boxes.

BOX vessel gear season light towing duration sweep length warp length [min] [m] [m] BOX A 1; 2; 3 GOV; KJH; 7m BT summer; winter daylight 30; 60 60 300 BOX B 1; 2 GOV summer daylight 30 110 450 (400 since 2005) BOX C 1; 2 GOV summer daylight 30 60 400 BOX D 1; 2; 4 GOV; 180'HT summer daylight; darkness 30; 60 110; 60 550 (500 since 2005) BOX E 3 KJH summer daylight 30 53 200 BOX F 3 KJH (30cm) summer daylight 30 53 225 – 250 BOX H 3 KJH summer daylight 30; 15; 60 53 350 – 375 BOX K 3 KJH summer daylight 30 53 200 BOX L 2 GOV summer daylight 30 60 550 BOX M 2 GOV summer daylight 30 60 500 BOX N 2; 3 KJH; GOV; 7m BT summer; winter daylight 30 53 100 – 150 BOX P 3 KJH; 7m BT summer daylight 30 53 225 – 250

1: Walter Herwig, 2: Walter Herwig III, 3: Solea, 4: Anton Dohrn, bold: standards

specific towing directions in relation to wind and current and taken for length measurements. For age determination of the in general to account for the potential effects of currents and commercially important species age-length-keys are used from tides on the catches. In practice, the captain is constrained to IBTS surveys of the same Standard Roundfish Areas (ICES fulfil these prerequisites as precisely as possible. In the case of 2006a) in which GSBTS Boxes are located. difficulties in the track or deviations from the given course by In addition to the catch, other relevant information on the strong currents, the captain selects the least different possible station such as water depth, haul starting and hauling time etc. option together with the chief scientist. In all cases,eschweizerbartxxx sng-the towing and on sea and weather conditions such as wind speed and track should be in a straight line to avoid mistakes in calcu- wave height are also recorded. Haul starting time is defined as lating the towing distance and speed only from shooting and the moment when the winch is stopped at a predefined warp hauling positions. The standard towing time is 30 minutes. length, the hauling back process beginning 30 minutes later. Aboard each vessel, normally the entire catch is sorted according to species, which are weighed, counted and measured. Aboard the old vessels, if catches were large (more than ap- Statistical precision of the survey data prox. 10 baskets), sub-samples of at least 5 baskets (300 kg; W. HERWIG) or 2 baskets (SOLEA) were taken. Aboard the Reliable estimate of biomass new vessels, sub-samples are only taken of the abundant species. The entire catch is sorted using a conveyor belt in order Stransky (1998) investigated the number of hauls needed not to miss rare species, of which all individuals are counted for a reliable estimate of biomass within the Boxes for the GS- and measured. BTS, using data from 1986 – 1997 for the Boxes A-D. From all From the abundant species representative sub-samples of hauls in each Box, one haul from each year was chosen at ran- at least 100 individuals depending on variability in size are dom, and the biomass values in that haul being correlated with the mean biomass calculated for all hauls in each year using the Pearson correlation coefficient. This process was repeated for Table 5: Minimum number of hauls needed to provide precise 1000 times in a bootstrap routine. The procedure was repeated biomass estimates for cod, haddock and whiting in Box A, B, C, and with a sampling size of 2, 3, ... n hauls (randomly selected D, as defined by a Pearson correlation coefficient of r > 0.9 and 95% lim without replacement), where n represents the maximum num- confidence limits inside r -0.1 to r + 0.05. lim lim ber of hauls taken in all years. The number of hauls deemed to Box Cod Haddock Whiting give a reliable estimate of the mean biomass for all hauls in a Box was defined as the lowest one providing a Pearson correla- A 10 – 6 tion coefficient of > 0.9. B >13 3 5 The number of hauls varied between species and areas C >11 >11 7 (Tab. 5). For cod in Box B for example, the minimum number of hauls which was taken in all survey years, 13 hauls, is not D 7 2 4 sufficient to meet the reliability criteria, whereas haddock bio- 19

Fig. 2: Relationship between number of hauls and number of fish species caught [%] in a Box.

eschweizerbartxxx sng- mass in Box B and D is estimated with sufficient precision by carried out by the two vessels using two different sets of gear taking 3 and 2 hauls, respectively. Where relatively low within- within the area of 100 nm² in Box D. In total 34 species were year variance occurred, e.g. haddock in Box B and D, a sam- caught. pling effort of a few hauls was found to provide high estimate Using the methods of bootstrapping in average 12 species precision. In areas which showed high within-year variation in were caught in one haul and the calculation shows an increase biomass of a particular species, e.g. cod in Box B and C, con- in species even after 90 hauls. Based on such calculations only siderably higher sampling effort was required to achieve similar 77% of the total number of species are caught in 20 hauls and precision. In the case of haddock in Box B and D, the level of 84% in 30 hauls, this being the limits between which the total between-year variation in fish distribution could, therefore, be numbers of hauls normally vary after 3 days of investigation in due to real changes in biomass, whereas between-year differ- a Box. From the first to the tenth haul in a Box the coefficient ences observed for cod in Box B and C could be subject to ran- of variation sharply decreased from 18% to 8%; with addi- dom sampling effects. The analysis of biomass trends should, tional hauls the gain in precision is only small (Fig. 2). therefore, take account for the underlying area-specific within- Between 2003 and 2005, 30 to 35 species were caught in year variation in biomass estimates for a particular species. 21 hauls each. During the entire period of investigation in Box D (20 years) 63 different fish species were taken in 498 hauls.

Representative species composition Topical studies For investigations aimed at species composition (e.g. changes in biodiversity) two questions beyond the problem Hydrography of gear catchability related to the different species are of great importance: General hydrographical patterns in the Boxes 1. How many species are caught in one haul? 2. Is the number of hauls sufficient to collect a certain num- The North Sea water masses cover a broad salinity range: ber or proportion of the species’ individuals inhabiting the from Atlantic water of 35.4 psu in the north to freshwater in survey area? the estuaries. Atlantic Water and North Sea Water with salini- In 1986, in the course of the comparison fishing experi- ties of 34.8 up to 35.4 psu dominate. In these areas of high ment (see “Effects of technical changes”, p. 33), 90 hauls were salinities, only small vertical salinity differences occur tempo- 20 rarily due to circulation differences in the single water layers In addition to Dietrich’s classification (bold letters), dif- with dissimilar horizontal advection. ferent situations or exceptions usually lasting for shorter me- The main influence of freshwater in the North Sea is lim- teorologically induced periods are given in Tab. 1 by regular ited to the coastal areas which are bordered by more or less letters. expressed frontal or transition zones against the more central waters with higher salinities. The freshwater runoff has its max- The single Boxes can be characterised as follows: imum in spring. While increasingly mixed with the underlying Box A: water, this surface water is transported from the coasts towards Box A lies in an area which is generally classified by Diet- the central regions of the North Sea (Schott 1966). Thus, a rich (1950) as well mixed region (A2). However, the vertically salinity minimum proceeds wave-like from the coastal regions homogeneous situation of the Continental Coastal Water in into the centre of the North Sea during spring to summer Box A is modified into at least two salinity layers if winds from (compare e.g. Fig. 3). On its way offshore, the amplitude of easterly or southerly directions blow for a few days or up to the annual cycle diminishes by permanent mixing from more weeks. These winds transport near-coastal low salinity water than 0.5 psu in the eastern coastal areas to less than 0.05 psu masses in a surface layer offshore. In compensation, higher in the central North Sea. In comparison, evaporation and pre- salinity bottom water from more central areas is transported cipitation are of smaller influence, while the year to year runoff towards the coastal areas as a bottom layer. Thereby, vertical changes are of greater influence on the amplitude of the annual salinity differences are temporarily induced in Box A. cycle (Schott 1966). During calm high pressure weather periods in summer, Due to short time insolation, air temperature, and wind high insolation heats the surface layer and stratifies the - wa situation, the North Sea surface temperatures vary during the ter mass of Box A in contrast to the general classification A2. course of a year between ice formation in winter and tempera- The depth of the thermocline depends on the wind mixing tures of over 20 °C in summer in the German Bight which is meanwhile. With increasing winds in the area, the vertical tur- the most continentally influenced part of the North Sea. In the bulence deepens the surface layer and reaches the permanent Shetland Island area which is the transition area to the North tide-mixed bottom layer, creating a vertically well mixed water Atlantic, the temperature variation lies approximately between column. The heat content of the original surface layer is then 6 °C and 13 °C. In all areas of the North Sea, maximum tem- distributed over the whole vertical water column with temper- peratures occur during the end of August, minimum values atures decreasing at the surface and increasing at the bottom. being found during the beginning of March (e.g. Figs. 3 – 5). Continuous strong winds mix the water masses down to the During the warming season (April to August) heated surface bottom even during strong insolation periods. layers prevent vertical exchanges with the colder intermediate Box B: or bottom layers in regions deeper than 50 m. Compared with other Boxes, this area reveals a relatively During autumn and winter, cooling at the surface leads stable water mass distribution of Atlantic origin all year-round, to thermohaline vertical convection finally down to the bot- including thermoclines from spring to autumn (A1). While tom in all areas of the North Sea, except in theeschweizerbartxxx Norwegian sng- proceeding off the British coasts from north to south, the sa- Deep. During every winter season, this vertical convection to- linity of the predominantly vertical homogeneous inflow water tally mixes the North Sea even if winds and currents start new decreases slightly by mixing with British Coastal Water masses. salinity stratifications during the convective period. - Thean With intensive westerly winds, coastal water is transported off- nual thermohaline convection is of extraordinary importance shore for greater distances: Temporarily, lower salinity near- for the North Sea life cycle, as it renews the oxygen content of surface water then creates stratification in the Box B area. the bottom water as well as the nutrients in the surface layer to During the winter season, such coastal water may be colder optimum values as a basis for the biogeochemical cycle. than the homotherm Atlantic Water beneath. During the sum- Depending on the rapid weather alternations, the hy- mer season the coastal water may initiate another near-surface drographical conditions of the North Sea are in permanent temperature stratification besides the seasonal one in greater change. Thus, a “mean hydrographical situation” only exists depths. theoretically by averaging momentary measurements. Box C: In spite of the strong variations, a general classification of Generally, the North Sea Water mass of this area is verti- hydrographical regions of the North Sea is given by Dietrich cally homohaline. A thermocline exists from spring to autumn (1950) based on seasonal stratifications. A second classifica- (B1). In the near bottom layer of Box C, Norwegian Deep tion of the regions of the North Sea depending primarily on Water with temperatures and salinities originating from the the salinities of the prevailing water masses was introduced by Atlantic Inflow along the western flank of the trench moves Laevastu (1963; Fig. 6). Table 6 combines both these clas- temporarily in a south-westerly direction. Due to longer last- sifications. ing winds from a northern to eastern direction, Baltic Outflow According to Dietrich (1950) the abbreviations stand Water generates a thin surface layer of low salinity and differ- for: ent temperatures in the Box C area (near surface halocline plus A1: homohaline throughout the year; temperature stratifica- thermocline). tion at least during summer; During very cold winters, cold bottom water with lower A2: homohaline throughout the year; homothermal through- salinity from the Juetland Bank area (Danish Coastal Water) out the year; flows into deeper regions towards the west-northwest crossing B1: salinity stratification temporarily or throughout the year; the Box C area. surface layer with slight salinity variation, bottom layer Box D: with regular seasonal changes in salinity. The Atlantic Water in the Box D area is predominantly 21

Table 6: Hydrographic regions and water masses of the North Sea. Bold letters: General classification according to Dietrich (1950) and Laevastu (1963), standard letters: temporary situations.

Box hydrographic region water masses (Dietrich 1950) (Laevastu 1963) Box A mixed (A2), S-differences due to special wind periods, continental water thermocline due to intensive irradiation periods Germ. B. coastal water Box B thermocline during summer, homohaline (A1) modified Atlantical w. S-differences depending on off-shore winds Engl. coastal water Box C thermocline during summer (B1) Northern North Sea water S-differences due to winds and deep currents Norw. coast. w., Atl. w. Box D thermocline during summer, homohaline (A1) Atlantical w. S-differences due to stronger westerly winds Scot. coastal water Box E mixed (A2), S-differences due to special wind periods, Central North Sea water, thermocline due to intensive irradiation periods Channel water Box F mixed (A2), S-differences due to special wind periods, Engl. coastal water, thermocline due to intensive irradiation periods and wind periods Channel water Box H thermocline during summer, homohaline (A1) Northern North Sea water nearly no S-differences throughout the whole year Box K thermocline during summer, homohaline (A1) Central North Sea water S-differences due to special wind periods Box L thermocline during summer (B1) Northern North Sea water, S-differences due to deep current and winds Atl. w., Norw. coast. w Box M thermocline during summer (B1) Northern North Sea water, S-differences due to deep current and winds Atl. w., Norw. coast. w Box N mixed (A2), S-differences due to special wind periods, Continental water thermocline due to intensive irradiation periods Germ. B. coastal water Box P thermocline during summer, homohaline (A1) Central North Sea water S-differences due to deep current Northern North Sea water

eschweizerbartxxx sng-

homohaline throughout the year while a thermocline develops Box H: during the summer season (A1). However, with stable westerly Box H has the least short-term variability of all Boxes. It is wind surface-near Scottish Coastal Water with lower salinity characterized by homohaline Northern North Sea Water with and different temperature is driven far towards the east, pro- temperature stratification during summer (A 1). Thermohaline ducing stratification in the upper water column. vertical convection leads to a complete homogeneity during Box E: winter. Due to the quite similar water masses in the surround- In Box E Central North Sea Water, English Channel Wa- ing and minimum advective transport of these water masses ter, or even Continental Coastal Water may be found. Due through the Box area, only small vertical salinity differences to the preceding meteorological situation, a well mixed water occur in the seasonal cycle. mass of only one origin may be found or water from up to all Depending on the changing wind and heating phases, three types may be mixed in the area. Although generally clas- the seasonal temperature stratification shows a staircase like sified as vertically homogeneous throughout the whole year by vertical temperature profiles. During summer, the nearly un- Dietrich (1950, A2), the water masses mixed from the dif- changed bottom water mass in Box H conserves the lowest ferent sources may be divided into horizontal layers lasting for North Sea bottom water temperatures. These originate from variable periods of time. the last vertical convection of cooled surface water down to the Box F: bottom at the end of the preceding winter, and will stay nearly Due to the dependence on wind fields, the variability es- unchanged until turbulent mixing reaches the tide-mixed bot- pecially of the surface water masses occurring in Box F is com- tom water layer in autumn. parably higher than that of Box E: Coastal Water with varying Box K: parts of Thames water or Wash Bay water may overlay Channel The Central North Sea Water of Box K is thermally strati- Water as the third water mass in this area. Thus, contrary to fied during the summer months and shows in general no ver- Dietrich’s general classification “mixed the whole year (A2)”, tical salinity differences (A1). However, easterly winds may salinity as well as temperature stratifications can be found transport German Bight Coastal Water further into the west temporarily in Box F and may change rapidly throughout the and displace the near-surface part of the Danish Frontal Zone year. into the Box K area. Thus, vertical salinity differences may 22 occur. A second origin for vertical salinity differences is the Typical features of the summer temperature and salinity near bottom current in the case of transport of water of higher time series of the Boxes A, B, C and D salinity from the Norwegian Deep in south-westerly directions. Data and Methods Box L: The Northern North Sea Water of Box L shows thermal Completing the biological programme, oceanographic stratification during summer months and seasonal changes in data – vertical profiles of temperature and salinity – were salinity (B1). Furthermore, the variable salinity stratification sampled inside the selected Box areas since 1986 (Fig. 1, Tab. depends on the amount of intermediate water from the Nor- 7). In addition to the observations taken during “Box-cruises” wegian Trench that crosses the banks on the edge of the trench mainly during the third quarter of a year, further available towards the central North Sea. Additionally, the amount of data were extracted from the oceanographic data base of the Norwegian Coastal Water mixed into the surface layer of Box Institute for Sea Fisheries, Hamburg. Due to the historic di- L originates from transports by easterly winds, or from block- mension considered in this analysis, the data consist of Nansen ing of the northern flow of the coastal current due to stronger bottle data and CTD data. For the more recent part of the northerly winds. CTD data salinity readings of the CTD (Kiel-Multisonde and Box M: SeaBird 911+) profiles were adjusted to water samples derived The hydrographic features of Box M are similar to those of by Rosette water sampler. The precision of the derived salini- Box L: The Northern North Sea Water shows thermal stratifi- ties allows water mass analysis to distinguish between different cation during summer and a salinity cycle (B1). Owing to the water masses of the areas. The isopleth diagrams presenting the smaller distance of Box M to the origin of the Atlantic Water, variability of the yearly averaged temperature and salinity mea- the Box M salinities are generally higher than those in Box surements in the Boxes A, B ,C, and D (Figs. 7 – 10) originate L. Bottom and surface-near layering originate from the same from the most recent version of Ocean Data View (Version processes as those of Box L. 3.1.0; Schlitzer 2006). Box N: To reveal seasonal variations in temperatures (surface, bot- Generally well mixed (A2), the Continental Coastal Water tom) and salinities (surface) of the Boxes A, C, and D, a har- in Box N may be changed into stratification with low salinity monic model (1) was applied to the mean data of areas. coastal surface water and relatively high salinity bottom water (1) ζ(t)=A × sin(2π/τ + ϕ) + lin trend due to winds from eastern directions. Long insolation periods lead to thermal layering. If such a The derived model was used to demonstrate seasonal varia- period last undisturbed for some weeks, the oxygen content of tions of periods and amplitudes of temperature and salinity in the bottom layer may be reduced to critical values, especially the areas of the selected Boxes (Figs. 3 – 5). after preceding high nutrient inputs (Rachor 1985). While some of the time series in individual Boxes started Box P: much later or have larger gaps due to different reasons, nearly eschweizerbartxxx sng- The Central North Sea Water of Box P reveals summer continuous oceanographic data exist for Box D since 1986 stratification and practically no vertical salinity differences, in and since 1987 for Boxes A, B and C (Tab. 7). They include general (A1). However, a high salinity bottom layer may exist variable numbers of profiles (between 2 and 50) per Box and due to the bottom current flowing from the Norwegian Trench year mostly taken during the months May to September. As to to the area southeast of the Dogger Bank. Intensive wind-in- comparability, this is a rather broad period which includes the duced turbulences may interrupt the seasonal layering in this most variable phase of North Sea surface temperature develop- lateral-area south-east of the Dogger Bank. ment. However, in the Boxes B and C even the measurements

Table 7: Number of t/S-profiles taken in each Box, mean and range of bottom water temperatures (summer, quarter 3), and time period covered.

Box mean profile t, bottom mean t, bottom range distance from shore no. of period depth [m] [°C] [°C] [km] t/S-profiles min max A 36 16.4 11.4 18.6 65 346 1987 – 2005 B 70 7.7 6.0 8.5 50 221 1987 – 2005 C 55 7.8 4.1 9.7 160 226 1987 – 2005 D 98 8.8 7.0 10.9 16 545 1986 – 2005 E 50 15.7 14.9 16.5 50 55 1991 – 2005 F 45 16.7 15.8 17.2 43 62 1995 – 2005 H 70 7.1 6.2 7.8 290 76 1991 – 2005 K 38 12.5 11.0 14.4 81 49 1991 – 2005 L 107 7.2 6.6 7.6 162 101 1996 – 2005 M 95 8.0 7.0 8.9 135 103 1986 – 2005 N 20 17.8 15.4 20.1 20 44 1986 – 2005 P 46 9.6 8.4 15.9 148 10 2000 – 2005 23 from May were taken into account. During these years of temperatures were measured during 1994. The water masses early measurements, incidentally late and low spring warming beneath the thermocline show the late winter temperatures of kept the summer surface temperatures below the mean values. April 1994. Parts of these April North Sea surface tempera- Thus, some of the cold years are indicated only by “trend tures were up to 1.5 K below the mean values. These lowest values and not by the real “summer” temperatures in Figs. 8 surface layer temperatures as well as the thermoclines closest to and 9. the surface in Figs. 7 – 10 originate from the retarded warming phases and from the early times of investigations within the season (May). Features in all time series Between 1995 and 2005, a nearly continuous warming The Boxes A, C, as well as B and D exemplify the main of all water masses in the Boxes occurred (Figs. 7 – 10) with hydrographical region types of the North Sea explained above. the highest temperatures being measured in 2003. From June The four time series show temperature and stratification con- to September 2003 continuously high insolation heated the ditions corresponding more or less to the long term means North Sea. Thus, the surface temperatures, averaged over the during the late 1980s: Nearly homogenous profiles in Box A whole North Sea area, were the second highest during each (Fig. 7), thermal and haline stratification of different strength month relative to the climatic mean from 1971 to 1993 in Box B, C, and D (Figs. 8 – 10). Besides the general charac- (Loewe 2003). Regionally, the anomalies surmounted 3 K in teristics given above, these time series reveal some remarkable August. features during the period 1987 – 2005. An impression of cooling as well as the heating phase through the period 1987 to 2005 is given by the time series of Temperatures the temperatures at 10 m depth of Box B (Fig. 11): The regres- Between 1991 and 1994, characteristic shifts in the paths of sion line indicates an apparent temperature increase of about cyclone families during the spring of nearly every year brought 4 K. However, the lowest surface temperatures of the first half larger quantities of cold polar air especially into the northern of the 1990s shown in Fig. 11 are no real “summer” values as parts of the North Sea, retarding the seasonal warming of discussed above. The North Sea SST anomalies Loewe( 2003) the water masses (Wegner 1994). Hence, even the Boxes A revealed an increase of 2 to 3 K due to the increased insola- and C – generally classified as mixed regions – showed strong tion during that period. At the same time, the winter cooling thermal stratification due to the initial seasonal warming. The generally decreased. Thus, the seasonal stratification started to temperatures were below the mean values not only in the bot- develop on the basis of increased spring temperatures, the bottom water, but also in the surface layer. In all areas, the lowest tom layer temperatures were increased by more than 1.5 K. In

Table 8: Characteristics of annualeschweizerbartxxx temperature sng- [°C] and salinity [psu] cycles.

Box A (surface) mean temperature temp. amplitude time of temp.-MAX. Dietrich et al. (1975) 10.0 6.4 mid-August 1987 – 2005 10.8 6.2 mid-August mean salinity salinity amplitude time of sal.-MIN Schott (1966) 33.2 0.6 mid-June 1987 – 2005 33.5 0.5 mid-June

Box C (surface) mean temperature temp. amplitude time of temp.-MAX. Dietrich et al. (1975) 9.4 5.2 mid-August 1987 – 2005 9.8 6.0 mid-August mean salinity salinity amplitude time of sal.-MIN Schott (1966) 34.5 0.4 mid-august 1987 – 2005 34.6 0.3 mid-June

Box D (surface) mean temperature temp. amplitude time of temp.-MAX. Dietrich et al. (1975) 9.2 3.3 mid-August 1987 – 2005 10.4 3.2 mid-August mean salinity salinity amplitude time of sal.-MIN Schott (1966) 34.9 0.1 end of June 1987 – 2005 35.0 0.1 begin. of June 24

Fig. 3: Averaged monthly bottom water salinities [psu] of Box A, C Fig. 4: Averaged monthly sea surface temperatures [°C] of Box A, C and D (top to bottom panel) and modelled best fit; r² = 0.84 (A), 0.61 and D (top to bottom panel) and modelled best fit; r² = 0.98 (A), 0.90 (C), 0.16 (D). (C), 0.85 (D).

eschweizerbartxxx sng-

the areas deeper than 50 m, this higher temperature level was ed to the general classification of Box A The insolated heat preserved during the following season. reached the bottom layer through vertical turbulences with the exception of only a few years. In 2001, e.g., a less haline S a l i n i t i e s surface layer was generated through winds blowing offshore in Within the usual range, salinities generally varied around that near coast water masses of the inner German Bight were the long-term means of the different regions throughout the transported into the outer regions. whole of the period under discussion. The cold phase at the The Box A salinity series (Fig. 7) is the only one of the four beginning of the 1990s was combined with higher salinities, which shows a regular alternation with a periodicity of about 6 except in Box D (Fig. 10). The less haline water between sur- years. In all other series, the times of high and low salinities oc- face and bottom in this area indicates the influence of the mix- cur at different intervals during the period from 1987 to 2005. ing of larger amount of northern British coastal waters into the They do not fit into any wave like transport of a higher haline water masses originating from the Atlantic Ocean. This mixing water mass coming in from the Atlantic and passing through resulted from the cyclone families which passed that region the North Sea due to the general circulation. as mentioned above. Due to the vertical homogeneity during In Box B (Fig. 8) the seasonal temperature stratification the winter seasons, the upper and lower water masses gener- was permanent through the years 1987 to 2005. Vertical salin- ally show year-to-year salinity alternations in the same manner. ity differences were small. Water from the British coastal zone Of course, the meteorological induced advection of water with in the surface layer led to salinity stratification only between originally different salinity enlarges the vertical differences. 2000 and 2003. During the cold period of the early 1990s, waters of higher In Box C (Fig. 9), the stratification by the yearly thermo- salinity originating from more central North Sea waters came cline was enforced by the transports of higher haline water into into the Box A area (Fig. 7) year by year. The highest salinities the lower layer from 1989 to 1994 and during 1999 and 2005. occurred near to the bottom. A halocline as well as a thermo- The bottom water could have originated from the Norwegian cline existed in this area, which is typically mixed. Trench area. The lower haline surface water masses in 1987 Especially during the much warmer period from 1996 to and 2000 contained parts of the Baltic Outflow Water. 2005, the vertical temperature and salinity profiles correspond- Besides the year by year seasonal thermal stratification in 25

1. North Atlantic water 2. Channel water 3. Skagerrak water 4. Scottish Coastal water 5. English Coastal water 6. Continental Coastal water 7. Northern North Sea water 8. Central North Sea water

Fig. 5: Averaged monthly bottom water temperature [°C] of Box A, Fig. 6: Distribution of water masses during summer (after Laevastu C and D (top to bottom panel) and modelled best fit; r² = 0.96 (A), 1963) and position of Boxes. The northern border of the Channel 0.74 (C), 0.91 (D). water oscillates and so does the association of Box E with either this or eschweizerbartxxx sng- one of the neighbouring water masses (see p. 21).

Box D (Fig. 10), larger vertical salinity differences occurred values, amplitudes and start times as taken from graphs “cor- twice. From 1993 to 1995, the high precipitation, coastal wa- rected” by eye is included in Tab. 8. Although very roughly ter transport and mixing due to the cyclone families mentioned estimated, they do not differ too much from those of Schott above, led to a low salinity surface layer. In 2001, the influence (1966). With lesser disturbances, the bottom salinity cycles of of the coastal water was of a quite lower magnitude. the Boxes A and B reveal plausible values (Fig. 3). In Box A, the salinity minimum occurred in August and varied with an Yearly cycles of temperatures and salinities amplitude of 0.50 psu around the mean value of 33.82 psu; in By the method given above, the averaged yearly surface as Box C, the amplitude was 0.11 psu on a mean value of 34.85 well as bottom temperatures and salinities of the Boxes A, C, psu, the beginning of the bottom salinity minimum was in and D were calculated. The surfacetemperature values largely September due to the larger distance to the coast as compared correspond to those estimated for this layer by Dietrich et al. to Box A (Tab. 7). A different situation was found for the salin- (1975) and Schott (1966), respectively (Fig. 4; Tab. 8), the ity cycle in the bottom water of Box D. While the amplitude small differences being due to the different data sets and meth- of 0.07 psu and the mean salinity of 35.13 psu correspond to ods used. The maxima of the bottom temperature cycles in the the values normally found in the area, the minimum occurred Boxes A and C occurred in August (Fig. 5), as expected from in April. Although the distance to shore is relatively small, the the relatively small water depths of the Boxes (A: 36 m, C: 55 minimum should occur in early summer, caused by the main m; Tab. 7) and the vertical mixing even in summer. However, period of precipitation in northern British waters which occurs the bottom maximum temperature of Box D occurred in Oc- in winter and spring. The rather early start of reduction could tober, due to the autumnal mixing of the still warmer surface be an artefact due to the large scattering of the annual mean waters through the increasing winds. bottom salinities (Fig. 3). The best fitting cycles of the surface and bottom salini- While the comparison with Dietrich et al. (1975) and ties partly do not show the annual alternations as expected. Schott (1966) appears to indicate the general surface warm- Due to the severe disturbances of the temporary transports of ing of the North Sea, the differences of the salinity parameters different water masses into the areas of the Boxes (see above), are within the local variation ranges and do not indicate long- the surface salinity cycles were omitted. The data set of mean term changes. 26

Fig. 7: Isopleth diagrams of temperature and salinity of Box A during summer (JUN-SEP); insert map shows location of stations in Box A.

eschweizerbartxxx sng-

Fig. 8: Isopleth diagrams of temperature and salinity of Box B during summer (MAY-SEP); insert map shows location of stations in Box B. 27

Fig. 9: Isopleth diagrams of temperature and salinity of Box C during summer (MAY-SEP); insert map shows location of stations in Box C.

eschweizerbartxxx sng-

Fig. 10: Isopleth diagrams of temperature and salinity of Box D during summer (JUN-SEP); insert map shows location of stations in Box D. 28

Fig. 11: Average temperatures of Box B at 10m depth and linear trend.

Nutrients Analyzer-II system from sub-samples taken by pipette. Estima- tion of nitrate and nitrite was based on the methods of Arm- Introduction strong et al. (1967), phosphate analyses being deduced from methods by Murphy & Riley (1962), modified by Eberlein Nutrient data are, apart from salinity and eschweizerbartxxx temperature sng- & Kattner (1987). For ammonium the phenol-hydrochloride data, a valuable tool to differentiate water masses. Addition- method (Koroleff 1969) was applied and silicate was quanti- ally, nutrients provide information on the recent state of bio- fied as described by Grasshoff et al. (1999). Results did not geochemical turnover processes, such as the degree of nutrient show significant differences from data obtained from filtered depletion in the mixed layer and remineralisation in the bot- samples taken on a parallel running RV. Isolines have been tom layer. If opportunities are given, fishery research should be plotted, using SURFER 7 (Golden Software), x/y diagrams supplemented by chemical analyses of the ecosystem, at least with GRAPHER (Golden Software). to characterise roughly the state of the ecosystem in the dif- Nutrient samples are only taken during summer from 7 of ferent water layers hosting the fish stocks. Nutrient concen- the 12 Boxes (see Tab. 2). Within the Boxes up to 9 stations trations reflect the state of the ecosystem, e.g. in the mixed were sampled, in order to estimate the extent of short time layer low concentrations may indicate the local limitation of variability or, if possible to detect short time changes. In sum- primary production. In the bottom layer, increased concentra- mer 2004 Box A was investigated twice, in the beginning (A1) tions, especially of ammonium, indicate the progressing rem- and at the end (A2) of the survey with 3 weeks in between. ineralisation. Through these integrated indicators the nutrient During that time at least one period of strong winds had dis- supply to the food chain succession can be evaluated and the persed the relatively weak thermal stratification of the water present state of ecosystem within the Boxes biogeochemically masses in the relatively shallow Box. characterised which is one explanation for the different abundances of fish crops in the Boxes. Results

Material and methods For an overview of the nutrient profiles in the different Boxes the data from 2004 are presented as means for the indi- Water samples for nutrient analyses were taken with Niskin vidual depths with standard deviations (Fig. 12). Temperature bottles. The unfiltered samples were immediately fixed with and salinity are given for identification of stratification by den- mercury chlorid (0.01% W/W). 150 µL of a 3.5% (W/W) sity gradients. The mixed layer in all Boxes is characterised by solution are given to 50 ml samples in polyethylene bottles and high summer temperatures (>10 °C). Often also salinity gradi- stored refrigerated and in the dark. Nutrients were analysed ents contributed to the stratification. within the following 6 – 10 months with a Technicon Auto- Normally the water column in the shallow Box A (mean 29

eschweizerbartxxx sng-

Fig. 12: Vertical profiles of salinity [psu], temperature [°C] and nutrients [µM] in all Boxes during summer 2004. Means of 3 – 9 samples per Box. Standard deviations [SD] are indicated by horizontal bars. 30 depth ca. 40m) is permanently well mixed, except in periods of in 40 m depth, coupled with a slight decrease in temperature. warm weather with slight breezes such as in 2004 at the begin- Apart from these variations no major changes were observed. ning of the survey (station A1). In the Boxes B, C, D, L and M significant vertical differences of nutrient concentrations were measured. At the shallow stations A1 and A2 in the German Discussion Bight, high concentrations of phosphate, silicate and ammonium were also found near the surface. Apart from ammonium The small standard deviations along the vertical profiles of the nutrients were depleted within the upper mixed layer of the mean nutrient concentrations within the Boxes indicate the other Boxes and increased in the bottom layer mostly to 3 –12 homogeneity within selected Boxes. The high variabilities at µM nitrate, 3.5 – 5.5 µM silicate and 0.4 – 0.8 µM phosphate. mid depths are caused by vertical fluctuations of the pycno- Significant increases by 1 – 3 µM of ammonium in the bottom cline, separating waters masses with very different qualities. layer were detected in the Boxes A (station A1), B and C. Presumably, internal waves frequently shifted the depth of the Time series of nutrient concentrations are shown for the pycnocline (Sellshop 1982). Boxes A and D since 1987 (Figs. 13, 14). In Box A, temper- At the pycnoclines sufficient nutrients were available to ature increased since 1995 as well as silicate and phosphate support primary production, which was probably limited by concentrations, in contrast to nitrate. Nutrients were generally light at 40 m depth. During a parallel cruise in 2004 of RV lower at the surface, apart from nitrate in some years. Nutrient “Gauss” (Loewe et al., unpublished data) covering the whole ratios showed especially in 1994 and 1995 high Si/phosphate North Sea, chlorophyll maxima were recorded at the pycno- values (M/M), NOx/phosphate and NOx/Si values, caused by cline and low C/N ratios of particulate matter indicated posi- high NOx values and low phosphate concentrations at that tive net primary production. time (throughout the text, NOx = nitrate + nitrite). In Box D The high nutrient loads in the bottom layer reflect the the greater water depths always cause significant vertical differ- winter concentrations, partly enriched by imports from the ences, with the exception of the Si/phosphate ratios. Nitrate Atlantic and by remineralisation of sedimented material from was depleted in the mixed layer at all times. Nutrient variabil- the mixed layer. The remineralisation is especially indicated by ity was especially high in 1993 and 2003. There were no sig- high ammonium concentrations in the bottom water of Boxes nificant changes during the years. For the period 1991 – 1995 A, B and C (Fig. 12). High concentrations of phosphate and the ratios of Si/phosphate and NOx/phosphate in the bottom silicate, combined with high ammonium which is the most layer increased consistently. significant indicator for remineralisation, indicate remobilisa- The inter-annual variability of vertical profiles is shown for tion from the sediment or decomposition in the bottom water, the Boxes A and D for the years 2001 to 2004) in (Fig. 15). whereas nitrate is utilised as oxygen donator and lost by deni- In Box D vertical profiles for temperature, salinity and silicate trification. were very similar. For nitrate and ammonium great changes The reason for the apparent increases of temperature, sili- in the bottom water were observed, for nitrate between 4 and cate and phosphate concentrations in Box A since 1995 (Fig. 10 µM and for ammonium between 1 and 4 µM.eschweizerbartxxx Around sng- the 13) is the shift of cruise dates from June to August when rem- pycnocline high variability for salinity and most of the nutri- ineralisation in the shallow area has already taken place and ents were observed as indicated by bars. In the bottom layer nutrients are released from the sediment. This is not the case in 2004 very high nitrate concentrations were observed. Phos- for nitrate which is utilised by denitrification. For Box D the phate remained very low (< 1 µM) throughout the water col- time shift of the sampling period had no great effects on the umn during the years before 2005. nutrient concentrations. In Box D all nutrient concentrations In the shallow Box A no significant stratification was ob- were higher in the bottom layer due to nutrient fixation in served in 2001 and 2004 – 2 (2nd sampling), neither for tem- the mixed layer and stable stratification. High (> 3 µM) am- perature, nor for salinity, causing homogeneous vertical nu- monium concentrations in the bottom layer indicate remin- trient profiles. High concentrations of phosphate, silicate and eralisation of sedimented biomass. Nitrogen was probably the ammonium in 2003 near the bottom indicate remobilisation limiting factor for phytoplankton growth, as indicated by low from the sediment. Variability between different stations was N/Si and N/P ratios in the mixed layer, the ratios remaining high for phosphate, but the concentrations always remained always far below 16 for N/P and mostly also below 1 for N/Si, below 0.45 µM. the Redfield ratios, which are assumed to reflect the uptake In order to show the short time variability, example data ratios by phytoplankton (Redfield et al. 1963). from 2003 have been plotted against depth and sampling time It can be assumed that the high nitrate concentrations in within the Boxes A and D (Figs. 16, 17). In Box A, a weak the bottom water of Box D in 2004 have been caused by an stratification was observed with decreasing temperature and inflow of Atlantic water, because the ammonium values are salinity within the three consecutive days of investigation. At lowest during that year, indicating no present remineralisation the same time while nitrate decreased in the mixed layer by (Fig. 14). Additionally, salinity was as high as at the northern about 0.4 µM, ammonium increased in the bottom water by stations L and M. The high ammonium concentrations in the about 1 µM. Near the surface (5 m depth) silicate and phos- bottom layer during other years reflect long lasting stagnation phate concentrations increased during the few days of observa- of bottom water, as especially at station B, allowing the decom- tion. In Box D thermal stratification, separating nutrient poor position of sedimented biomass. surface and nutrient rich bottom water, became stronger dur- The water column in the Box A was during some years ing the observation period (Fig. 17). Combined with this pro- (2001, 2004 2nd sampling) completely mixed, as shown by cess, silicate decreased in the mixed layer. On August 8, higher straight profiles of salinity, temperature and nearly all nutrients nutrient concentrations were observed below the pycnocline (Fig. 15). The increase in ammonium concentrations near the 31

Walther Herwig, Box A, summer, means and std.deviation 1987 – 2004

20 8

16 6 surface 4 12 bottom 2

8 ammonium[µM]

temperature [°C] temperature 0 8 100

[µM] 6 80 4 60 40

2 [M/M] Si/PO4

silicate silicate 20 0 0 0.8 300 0.6 [µM] 200 0.4 100 0.2 NOx/PO4 [M/M] NOx/PO4

phosphate phosphate 0.0 0 12 16 12 8 8 4 4 NOx/Si [M/M] NOx/Si nitrate [µM] nitrate 0 0 1987 1989 1991 1993 1995 1997 1999 2001 2003 1987 1989 1991 1993 1995 1997 1999 2001 2003 year year 8 7 7 7 6 6 6 6 6 8 9 8 8 - 8 8 8 8 8 7 7 7 6 6 6 6 6 8 9 8 8 - 8 8 8 8 month month

C2 Fig. 13: Mean temperature [°C], nutrients [µM] and nutrient ratios [M/M] at the surface (red) and near the bottom (blue) in Box A during summer from 1987 – 2004 (means of 6 to 9 samples each). – Standard deviations are given as vertical bars.

Walther Herwig, Box D, Summer, means and std.deviation 1987 – 2004

eschweizerbartxxx sng-

16 surface layer ] ] M C 6 ° bottom layer 14 [ [ e r m u u

t 12 4 i n a r o e 10 p 2 mm m

8 a e t 6 0 6 20 ] ] M M / 15 [

4 M [ e t 4 10 a O c li P i 2 / i s

S 5 0 0 1.2 25 ] ] M M / 20 [ M e 0.8 [ t 4 15 a O h p P /

s 10 0.4 x o O h 5 p N 0.0 0 12 3 ] ] M M /

8 M [ 2 [ i e t S / a r x t

i 4 O 1 n N

0 0 1987 1989 1991 1993 1995 1997 1999 2001 2003 1987 1989 1991 1993 1995 1997 1999 2001 2003 year year 7 7 7 6 6 6 6 6 6 - 9 7 7 - 8 8 8 8 7 7 7 6 6 6 6 6 6 - 9 7 7 - 8 8 8 8 month month

Fig. 14: Mean temperature [°C], nutrients [µM] and nutrient ratios [M/M] at the surface (red) and near the bottom (blue) in Box D during summer from 1987 – 2004 (means of 6 to 9 samples each). – Standard deviations are given as vertical bars. 32 1 2 - - 4 4 1 2 3 5 4 0 0 0 0 0 0 0 0 0 0 4 2 2 2 2 2 ] ] C 4 M M [ [ 3 m m u u i i n n o o 1 2 3 mm mm a a 0 0 1 2 0 0 0 0 0 0 0 0 0 0 0 0

-2 -4 -6 -8 -1 -2 -3 -4

-10 -12 ] [m iefe T ] m [ efe i T 6 8 ] ] 4 M M [ [ e t ca i icate l l i 2 4 6 si s 2004. Means of 6 to 9 samples each. Standard Standard each. samples 9 to 6 of Means 2004. – 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0

-2 -8 -4 -6 -2 -3 -4 -1

-12 -10 ] [m e f Tie ] m [ Tiefe 5 8 . 0. 0 4 ] ] 6 . 0. M M 0 [ [ 3 . 0 4 ate 0. 2 h phate 0. s 2 osp . 1 h . 0 p pho 0 0 0

0 0 0 0 0 0 0 ] m [ efe i T 0 0 0 0

-2 -4 -8 -1 -2 -3 -4

-10 -12 0 ] [m iefe T -6 2 1 1 0 8 1 0. ] ] 8 M M 6 . 0 [ [ 6 4 ate r 0. t 4 nitrate ni 2 . 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

-2 -4 -6 -8 -2 -3 -4 -1

-10 -12 ] [m e f Tie ] [m iefe T 4 4 3 eschweizerbartxxx sng- 35. 5 2 33. 3 y y 35. t 3 init l 5 North Sea, summers 2001 – 2004, vertical profiles in Box D, mean values of all stations in the box alini s sa 5 North Sea, summers 2001 – 2004, vertical profiles in Box A, mean values of all stations in the box 32. 3 2 3 8 5 . 34 31. 0 0 0 0 0 0 0 0 0 0 0 0

-2 -3 -4 -6 -1 -8 -2 -4

-10 -12 ] [m e f Tie ] [m iefe T 0 8 2 1 4 1 2 3 0 0 0 0 6 ] ] 20 20 20 20 1 C C ° ° 8 4 [ [ 1 1 2 ure t 1 a r 6 0 erature e 1 1 p p m e 8 t tem Vertical profiles of salinity [psu], temperature [°C] and nutrients [µM] in Box D and A during summers 2001 summers during A and D Box in [µM] nutrients and [°C] temperature [psu], salinity of profiles Vertical 4 6 1 0 0 0 0 0 0 0 0 0 0 0 0

-1 -2 -3 -4 -6 -2 -8 -4

-10 -12 ] [m e f e i T ] m [ efe i T Fig. 15: Fig. at the beginning and end of cruise (2004 – 1 and 2004 2). A during 2004 sampling was repeated Box bars. In horizontal indicated by deviations [SD] are

bottom during the 2nd sampling was probably caused by remo- to transient mixing. These concentrations are in the range of bilisation from the sediment shortly before the sampling. limitation for fast growing phytoplankton species. This means The concentration levels were especially different for the that in spite of frequent remobilisation from the sediment and two selected Boxes A and D. In the mixed layer of Box D the river discharges the potential of nitrate was limited for the on- nutrients were exhausted (nitrate < 0.2 µM) during the sum- going primary production. In Box D nutrients may permeate mer and in the bottom layer still high nutrient concentrations the pycnocline by vertical mixing allowing permanent primary were trapped below a stable pycnocline. In contrast, in the production just above the nutricline in spite of limiting light German Bight (Box A) nitrate concentrations throughout the conditions. This was indicated by chlorophyll maxima just whole water column were in the same range (< 0.7 µM) due above the pycnocline (Loewe et al. 2003, 2005). The high 33

Vertical distribution of different parameters at WH254 Box A, 2003

Temperature [°C] Salinity Nitrate [ M] 0m

-20m

-40m 14.7. 15.7. 16.7. 14.7. 15.7. 16.7. 14.7. 15.7. 16.7.

17 18 21 32 33 33.4 33.6 0 0.2 0.5 0.6

Silicate [ M] Phosphate [ M] Ammonium [ M] 0m

-20m

-40m 14.7. 15.7. 16.7. 14.7. 15.7. 16.7. 14.7. 15.7. 16.7.

1 2 3 4 5 6 7 8 0.1 0.2 0.3 0.4 0.5 0.5 1 2 3 4 4.3

eschweizerbartxxx sng- Fig. 16: Vertical distribution of temperature [°C], salinity [psu] and nutrients [µM] in Box A during 2003. The data are plotted as isolines to indicate the vertical changes during the time of observation (July 14 – 16).

variability of nutrients near the pycnocline indicated vertical a more extended interpretation of the basic biogeochemical movement of this layer caused by internal waves (Sellshop processes in the water column and would allow a closer bridg- 1982), combined with erosion of stratification. ing to the interpretation of food supply for lower trophic levels In July 2003 a period of low winds in the German Bight and remineralisation. Especially at the pycnocline particulate allowed weak temperature stratification in Box A and the de- matter accumulates, providing a specific biotope with high velopment of vertical nutrient profiles (Fig. 16). The sampling biomasses and specific chemical composition Ittekkot( 1981, only two times a day did not allow for the discrimination of Ittekkot et al. 1982). diurnal changes. However, fluctuations within the same depth indicate high turnover or advection, the latter being reflected by decreasing salinities. For this reason it makes no sense to Fish fauna calculate turnover rates from nutrient changes during the few days. Effects of different parameters on the catch The stable stratification in Box D separated the nutrient exhausted mixed layer form the nutrient rich bottom layer Effects of technical changes (Fig. 17). Apart from a slight decrease of silicate, caused probably by advection, no significant changes of nutrient concen- The quality of historic data sets depends on numerous trations were observed. The changes of nutrient concentrations factors, such as consistency and comparability within the re- at 40 m, just below the pycnocline, were probably caused by corded time series with respect to gear modifications or the internal waves which caused a partial up- and down-welling. replacement of vessels. To a certain degree, conversion factors There were no significant diurnal differences. derived by direct (Ehrich 1991; Pelletier 1998) or indirect The supplementation of nutrient analyses by estimation of methods (Sparholt 1990; Cotter 2001) can compensate chlorophyll concentrations and particulate matter would allow these differences. 34

Vertical distribution of different parameters at WH254 Box D, 2003

Temperature [°C] Salinity Nitrate [ M] 0m 0m 0m

-20m -20m -20m

-40m -40m -40m

-60m -60m -60m

-80m -80m -80m

-100m -100m -100m

7.8. 8.8. 9.8. 7.8. 8.8. 9.8. 7.8. 8.8. 9.8.

9 10 11 12 13 14 15 16 17.3 34.5 34.75 35 35.2 35.3 0 0.5 1 2 3 5 7 8

Silicate [ M] Phosphate [ M] Ammonium [ M] 0m 0m 0m

-20m -20m -20m

eschweizerbartxxx sng-

-40m -40m -40m

-60m -60m -60m

-80m -80m -80m

-100m -100m -100m

7.8. 8.8. 9.8. 7.8. 8.8. 9.8. 7.8. 8.8. 9.8.

0.3 1 2 3 4 5.2 0.05 0.1 0.2 0.3 0.4 0.5 0.61 0.4 0.7 1 2 2.2

C6 Fig. 17: Vertical distribution of temperature [°C], salinity [psu] and nutrients [µM] in Box D during 2003. The data are plotted as isolines to indicate the vertical changes during the time of observation (August 7–9). 35

Changes in catch processing methods over the years are both vessels in an area of 15 × 16nm. A significant differ- also sources of variance. It was shown that these changes have ence in the capture efficiency for haddock was only found a significant impact on species abundance estimates and the between the different nets. Higher catches were made with total number of species in the sampled catch (Hughes 1976). the “180-foot herring trawl”, which has a more forward- Naturally, in large trawl catches, the occurrence of small or rare extending square than the GOV and therefore produced species tends to be underestimated (Westrheim 1967, 1976). a significant lower rate of escape over the headline of the Therefore, the calculations of species diversity, based on these trawl. In contrast to haddock, the capture efficiency for catch data, is likely to be subject to a considerable error. Con- small cod was highly dependent on the ground gear, for sidering the increased interest in the description of the fish 85% of cod smaller than 32cm could escape under the fish- community structure in the North Sea using univariate species ing line between the heavy bobbins. For bigger cod (>32 diversity indices and multivariate species similarity measures, cm), the capture efficiency of the “GOV trawl” is signifi- the consistency in long-time data series is essential to the cor- cantly higher than that of the “180-foot herring trawl”. A rect interpretation of these descriptors. possible significant difference in the fishing power between both vessels could not be detected. Vessel and gear effects Experiment 2: A second comparative fishing experiment be- Normally the lifespan of a research vessel is not longer than came necessary when the old WALTHER HERWIG was 20 – 30 years while a gear is already antiquated after 10 years. to be replaced by WALTHER HERWIG III in January Within the political/commercial discussion with fishermen 1994. Both vessels were equipped with the standard GOV and managers it becomes more and more difficult for scientist and the standard ground gear as used in the IBTS (ICES firstly to cling on a standard gear if modern gears are more ef- 2006a). In Boxes A and D both vessels independently fective and secondly to get the financial support for a compara- made two sample series of hauls. Due to technical prob- tive fishing experiment between an old and a new vessel. lems, the number of hauls performed by the new vessel An evaluation of the capture efficiencies of vessels, of the was only half of that of the old one, which was less than the catchabilities between different gears and of the effects of required 25 hauls given as statistically necessary from the changes in the rigging of the same gear becomes necessary if first experiment. No significant differences were found in – an old fishery research vessel has to be taken out of com- the catch in number for whiting and haddock age-groups mission and a new vessel has to continue the existing sur- 1 – 4 or for dab. Despite the uncertainty it was decided to veys series, use the catch data of the new vessel in the series without – the vessel effect in a multi vessels survey on the catches has conversion (Ehrich et al. 1994). to be estimated, Experiments 3 and 4: It was shown by two further comparative – a change in the type of gear becomes necessary due to stan- experiments with independent hauls in Box A in 1992 and dardisation and if 1996 that different research vessels which fished with dif- – a quantitative estimate of the differences in the rigging of ferent gears and operating at slightly different target speeds the standard gear is essential to locate and minimizeeschweizerbartxxx sng- the have a similar performance (Adlerstein & Ehrich, un- variances of the estimated abundance indices. published data). Age specific catch rates of cod, whiting The common direct method of comparing two vessels is and herring, were not significantly different at haul lev- fishing side by side. A disadvantage of this method is the in- els of 27 and 28 (WALTHER HERWIG and SOLEA old) terdependence of both vessels just in comparison experiments respectively 23 and 18 (WALTHER HERWIG III and with new vessels, which are normally susceptible to technical SOLEA old) respectively, when compared using negative defects. The number of comparison hauls is often very limited binomial Generalized Linear Models (GLMs) introducing and not sufficient for significant and reliable results. vessel as a two level-factor. Although average catch rates of A higher number of comparison hauls and normally lower cod, whiting and herring of selected ages were in most cas- variances in the catch data can be obtained by fishing indepen- es lower in SOLEA hauls than in WALTHER HERWIG or dently within a limited area, where the target species are more WALTHER HERWIG III, differences were not significant. evenly distributed. The possibility to compare simultaneously Within reasonable bounds, such as those displayed during more than 2 vessels is a further advantage. the fishing experiments in this study differences in trawling Within the past 20 years we had the opportunity to carry speed and gear (see Tab. 3) can be compensated resulting out several experiments to quantify the effects of technical in similar fishing performance. These results increase the changes. value of GSBTS data for developing model based abun- Experiment 1: To adapt the “GOV trawl” and its rigging to dance indices for the North Sea. The results of this study “International Young Fish Survey” standards and based on also show that the use of negative binomial GLMs provides previous survey results such an area off the Scottish coast an appropriate tool to compare catch rates between vessels was chosen for a comparison fishing experiment in 1986 that allows the incorporation of zero catches and skewed (Ehrich 1991). The aims were to compare (1) the pro- distribution without transformation of the data. spective combination of the WALTHER HERWIG with Experiment 5 and 6: During 5 days in June 1994 and 3 days the standard “GOV trawl”, (2) the ANTON DOHRN with in June 1995 aboard WALTHER HERWIG III two experi- a “GOV trawl” and a heavy bobbin ground rope and (3) ments were carried out in Box D to estimate the differences the ANTON DOHRN with the “180-foot herring trawl” in the catch using 60m and 110m sweep lengths (the steel and a heavy bobbin ground rope. The latter two were used cable between the doors and the bridles of the net). For in previous years. the first quarter of the year the manual of the IBTS survey Within 10 days in June 1986 178 hauls were made by provides sweep lengths of 60m for fishing in shallow areas 36

Fig. 18: Hill N2 diversity index in relation to the total catch and catch handling. Abbreviations: 30 – 1: 30 minutes haul duration and catch handling method 1. – 30 – 2: 30 minutes haul duration and catch handling method 2. – 30 – 3: 30 minutes haul duration and catch handling method 3. – 60 – 1: 60 minutes haul duration and catch handling method 1. – 60 – 2: 60 minutes haul duration and catch handling method 2. – 60 – 3: 60 minutes haul duration and catch handling method 3.

and 110m at stations deeper than 70m to avoideschweizerbartxxx sng- possible diversity estimates under groundfish survey conditions was in- changes in gear parameters due to depth and to the length vestigated. The study also evaluates the impact of large catch of the warp. For the other 3 quarters only sweep lengths of sizes on the number of species detected in the sub-samples, 60m should be used. For standardizing the fishing method quantifies the effect on univariate diversity indices and gives for all quarters it was recommended to investigate the in- an indication of the size of the error involved. fluence of different sweep lengths on the catch. In 1994 Catch data were collected during experimental fishing to 20 hauls were carried out using sweep lengths of 60m and compare 30 and 60 minutes catches by W. HERWIG within 19 hauls with lengths of 110m and in 1995 12 and 11 Box D during five days in July 1988. The large catches with up hauls respectively. For the 4 species cod, haddock, whiting to 5000kg/h were dominated by herring and fish other than and herring the analysis of the catch data shows differences herring were relatively stable. in the mean catch, especially for herring. Using the more Aboard the vessel, only a short conveyor belt was used for extensive data set for 1994 and the nonparametric Mann- sorting the catch. Three different catch treatment methods Whitney U-test for comparing the frequency distributions were used depending on the amount of the total catch: of the catch in weight data for each species the differences – Less than 800kg: The whole catch was taken and all species are not statistically significant at a 5% level (ICES 1996). were sorted out. The IBTS Working Group decided that the number of – Between 800 and 2200 kg: Five baskets of 60 kg each hauls seems to be not sufficient to consider the high vari- were taken as a sub-sample. Noticeable or big specimens ability of the catches even in such a small area and that of other species (like rays and sharks) were selected from the results of these experiments are not clear enough to the remaining unsorted catch when passing outboard on change the procedure for the first quarter, for Norwegian the conveyor belt. colleagues could demonstrate a herding effect of longer – More than 2200 kg: Five baskets were taken as a sub-sam- sweeps especially for large cod in the Barents Sea. ple, with no notice being taken of the remaining catch. The increase in haul duration from 30 to 60 minutes led Effects of changes in catch treatment and tow - to an average increase in the mean number of species of about ing time on the number of identified species three (20%). In contrast, a change in sample treatment by tak- In a study by Ehrich & Stransky (2001) the influence of ing a sub-sample instead of sorting the total catch decreased towing time and different catch processing methods on species the number of species by the same order. Species diversity es- 37 timates are subject to the same trends. With increasing total catch, species diversity in a constant sub-sample volume decreased (Fig. 18). In order to detect trends in species diversity, using data series like the IBTS in the North Sea, only completely sorted hauls and hauls of the same towing duration should be taken into account.

Day-night effect and differences during day light hours

Effects of water column stratification and time of day on catch rates Several fish species are known to perform vertical movements within the 24 hour period of a day (Pitt et al. 1981, Ehrich & Gröger 1989, Engås & Soldal 1992, Adlerstein & Trumble 1993, Michalsen et al. 1996, Wieland et al. 1998, Aglen et al. 1999, Stensholt et al. 2000, Petrakis et al. 2001, Wieland & Rivoirard 2001). The International Bottom Trawl Surveys (IBTSs) are mainly conducted during day light to avoid bias in abundance indices due to differences between day and night hauls (ICES 2006), but variation in catch rates can also occur during day time hours. We investigated differences between day and night catch rates and also fluctuations within the hours of day light of the most abundant species in the surveys. 1. For comparison of day and night catch rates of herring (Clupea harengus), cod (Gadus morhua), haddock (Mela- nogrammus aeglefinus) and whiting (Merlangius merlangus) data were used from 81 hauls from 24 hr fishing experiments conducted in Box D during 1987 (Ehrich & Gröger 1989). Results using analysis of variance showed significant differences in catch rates of herring, cod and haddock between day and night hauls but no differenceseschweizerbartxxx sng- for whiting. 2. For a study of catch rates variation within 24 hours of Norway pout (Trisopterus ermarki), haddock, grey gurnard (Eutrigla gurnardus), whiting and dab data (Liman- da limanda) were used from 30 hauls conducted around the clock between 22 and 27 November 1997 in Box D (Adlerstein & Ehrich 2002). Generalized Additive Mod- els (GAMs) (Hastie & Tibshirani 1990) in combination with Generalized Linear Models GLMs (McCullagh & Nelder 1989) were used to analyse the effects of trawling ground speed, speed through water, swept area and swept volume on the catch. Analyses were implemented using routines contained in the S-Plus computing environment (Becker et al. 1988) and contributed by Venables & Ripley (1999). Results showed significant fluctuations of catch rates occurring within daytime hours for Norway pout, haddock, grey gurnard, and dab (Fig. 19) but not Fig. 19: Fitted time-of-day effects and approximate 95% confidence bands (dotted lines) from GAM for species/sizes exhibiting significant for whiting, whereas significant differences between day non-linear variation in catch rates. Marks on the x-axis represent and night rates were found for whiting smaller than 20 individual observations; y-axis scaled such that zero corresponds to cm (Adlerstein & Ehrich 2002). Catch rates of Norway the mean. – Figure from Adlerstein & Ehrich (2002). Details on pout and juvenile and adult haddock tended to be higher methods: dito. during daytime hours between 9.00 and 15.00 hrs than at other times, while those of dab, grey gurnard were higher between 20.00 and 4.00 hrs. The largest diurnal variation was observed in dab catch rates at night being more than double as high as during the day. 38

Combined effects of water column stratifi - Age-0 cation and time of day on the catch For a specific study on North Sea cod, data from 226 hauls (a) carried out in 1999 between 06.40 and 18.15 h (UTC + 2) in all Boxes except N and P were analysed. To complete the analysis with data collected around the clock, catch data were added from 66 hauls from fishing experiments in Boxes B and D conducted in 1996 (Adlerstein & Ehrich 2003). In the analysis the age of the fish and the effect of water stratifica- n.-s. tion on diurnal movement that could alter fish behaviour were considered. The definition of a stratified water body was based (b) on the difference between bottom and surface temperature of more than 5 °C. We classified Boxes A, E, F and K as non- stratified, and Boxes B, C, D, H, L and M as stratified during summer. The stratification was related to depth, and was detected in Boxes where depth was greater than 52 m. For this analysis we used GLMs, which were implemented using routines contained in S-Plus. Results showed significant variation s. of North Sea cod catch rates within daytime and between day and night hours. In areas where the water column was not stratified, catch rates of ages 1 to 4+fish were relatively low in the early morning, increased to a peak at around 14.00 h and Age 1 to 4+ returned to low levels thereafter (Fig. 20c). In deep stratified areas, rates for ages 1 to 4+ steadily decreased during day hours (c) (Fig. 20d). The pattern in the catch rate variation of age-0 fish with time of day in non-stratified stations was similar to that of fish age 1 and older (Fig. 20a), but rates in stratified stations peaked in the morning at around 10.00 h (Fig. 20b). Results from analysis of data collected around the clock indicated diurnal rate fluctuations with a peak at around 8.00 h and low night rates. In deep waters, catch rates of cod before 12:00 h n.-s. were double of those after 12:00 h, while the opposite was found in shallow areas. Overall results from both studies of the variationeschweizerbartxxx sng- of catch (d) rates from several species within day light hours indicate that it is likely that restricting catches to daytime is not sufficient to avoid bias in fish abundance indices. Our results warn that several abundance indicators in the North Sea can be biased if surveys are not randomized with respect to time of day. This can be corrected with modelling if necessary information is s. collected. Information required can only be obtained during fine-scale fishing experiments when other factors affecting catch rates, such as geographic location and date when surveys Fig. 20: are conducted, are kept constant. Fitted effects for catch rates of cod age 0 and ages1 – 4+ during 1999 GSBTS from negative binomial GLMs. Ticks along the x-axis represent the amount data used for the analysis. Results are for Effects of current and wind direction cod (a) and (c) different age classes at non-stratified stations and (b) It is customary to standardize effort in trawl surveys and (d) at stratified stations. For detailed methods see Adlerstein & through the use of a common gear and fixed haul duration Ehrich (2003). and vessel speed, which should result in a fairly constant area or volume swept by the gear. IBTS hauls are conducted with a standard GOV trawl for 30 minutes and at a target speed of 4 knots over ground. Nevertheless, wind and currents can affect catch rates, as is well known to fishermen, by causing varia- tain information on near-bottom water current characteristics tions in the effective trawling speed through water. This can and to measure gear geometry. Current speed and direction affect species differently, depending on their distribution in the were constantly measured with a current metre set a few me- water column and their swimming behaviour. tres above the sea bottom in the centre of the Box. Trawling In Adlerstein & Ehrich (2002), the effect of current speed through water was calculated as a function of vessel and characteristics on vessel trawling speed and on catch rates of current speed and direction. Results confirmed that current small and large whiting, of haddock, Norway pout, grey gur- characteristics affect effective trawling speed through the -wa nard and dab was investigated using data from 27 hauls con- ter. During the study, bottom currents did flow in a northerly ducted in 1997 in Box D. A special effort was allocated to ob- direction with speeds varying from 3 to 32 cm s-1 with the tide 39

1200 5 12000 5 Catch of mackerel Total catch Wave-height (m) Wave-height (m) 1000 10000 4 4

800 8000 3 3 600 6000

2 2 Wave-height (m) Catch (numbers) Wave-height (m) Catch (numbers) 4000 400

1 1 2000 200

0 0 0 0 0 12 24 36 48 60 72 84 96 0 12 24 36 48 60 72 84 96 5 July 1990 6 July 1990 7 July 1990 8 July 1990 5 July 1990 6 July 1990 7 July 1990 8 July 1990 Time (h) Time (h)

7000 5 160 5 Catch of scad Catch of cod Wave-height (m) 6000 140 Wave-height 4 4 120 5000

100 3 3 4000 80 3000 2 2 60 Wave-height (m) Wave-height (m) Catch (numbers) Catch [numbers] 2000 40 1 1 1000 20

0 0 0 0 0 12 24 36 48 60 72 84 96 0 12 24 36 48 60 72 84 96 5 July 1990 6 July 1990 8 July 1990 7 July 1990 5 July 1990 6 July 1990 7 July 1990 8 July 1990 Time (h) Time (h)

7000 5 600 5 Catch of dab Catch of plaice Wave-height (m) Wave-height (m) 6000 500 4 4

5000 400 3 3 4000 300 3000 2 2 Wave-height (m) Wave-height (m) Catch (numbers) Catch (numbers) 200 eschweizerbartxxx sng- 2000

1 1 100 1000

0 0 0 0 0 12 24 36 48 60 72 84 96 0 12 24 36 48 60 72 84 96 5 July 1990 6 July 1990 7 July 1990 8 July 1990 5 July 1990 6 July 1990 7 July 1990 8 July 1990 Time (h) Time (h)

80 5 25 5 Catch of solenette Catch of hooknose Wave-height (m) Wave-height (m)

4 20 4 60

3 15 3

2 10 2 Wave-height (m) Wave-height (m) Catch (numbers) Catch (numbers)

20 1 5 1

0 0 0 0 0 12 24 36 48 60 72 84 96 0 12 24 36 48 60 72 84 96 5 July 1990 6 July 1990 7 July 1990 8 July 1990 5 July 1990 6 July 1990 7 July 1990 8 July 1990 Time (h) Time (h) Fig. 21: The relationship between total catch and catches of mackerel, scad, cod, dab, plaice, solenette and hooknoose and wave- height in July 1990. and caused variations between 3.5 and 5.5 knots in trawling Maintaining a constant vessel speed over the ground does speed through the water. Fluctuations in speed caused signifi- not guarantee that survey data will be unbiased given the po- cant variations of catch rates of pelagic Norway pout and had- tential effect of water currents. While maintaining constant dock and whiting smaller than 20 cm but did not affect the speed over ground and through water is impractical, thoughts near bottom living species grey gurnard and dab and haddock should nevertheless be given to defining tow direction with and whiting larger than 20 cm. respect to bottom currents. 40

Fig. 22: Changes in the diversity indices Hill N1 and Hill N2 (means for Hill N1 in brackets) during the passage of a gale.

Effects of a gale event ity and possibly oscillating bottom currents during increased Wind-induced waves and the associated turbulence and wave-action in shallower waters. oscillatory currents are expected to affect the distribution of These results have far-reaching implications for the analy- fish in shallow waters because the fish are directly exposed to sis and interpretation of fish abundance data collected during these water movements. Nevertheless, fish assessment surveys groundfish surveys. Our study shows that gales of more than are routinely conducted also in rough weather conditions. Eh- eight Beaufort wind force (ca. 40 kn) are responsible for ex- rich & Stransky (1999) investigated the short-term effects treme short-term changes in the vertical distribution pattern of a gale on diversity and assemblage patterns of ground fish of species, particularly at depths less than 40 m. Monitoring in the German Bight. We used data from 23 haulseschweizerbartxxx sng-conducted programs should not be conducted in abnormal weather con- during 3 days in July 1990 in Box A where the mean depth was ditions since the data generated will bias assessment estimates. about 40 m. Wind strength up to 50 knots and wave-height were measured at the research platform ”Nordsee”, situated about 15 nm north of the study area. Wave-height was taken Distribution and species assemblages of fish as the mean of the upper third of all waves measured. Catches obtained during the first and second day after the gale and Long term trends in species assemblages catches obtained in previous years were compared using the nonparametric Kolmogorov-Smirnov two-sample test. Diver- The species assemblage in Box A and its long term changes sity indices Hill N1 and Hill N2 (Hill 1973) were calculated were investigated for the period from 1987 to 2005 (Ehrich and compared with the “diverse” module of the PRIMER soft- et al. 2006). As in the entire area of the German EEZ, dab, ware (Clarke & Warwick 1994, Carr 1996) For the analy- plaice and whiting belonged to the five species most frequently sis univariate and multivariate statistical techniques (cluster, caught in Box A. These species as well as horse mackerel and Multi Dimensional Scaling and SIMPER analysis) were used. grey gurnard were present in more than 80% of the hauls. Results showed considerable changes during the gale event Temporal trends in bottom fish assemblages were quantified with a lower range of diversity during the first day after the with multidimensional scaling of the summer data (Q2 and gale compared with the second day, and differences in species Q3 only; pelagic species excluded). The 2-dimensional ordina- composition and abundance (Fig. 21). In general catches of tion of the species similarity matrix revealed a strong shift in flatfishes such as dab, solenette (Buglossidium luteum), plaice the fish assemblage from 1987 to 2005, particularly between (Pleuronectes platessa) and sole (Solea vulgaris) were significant- the period until 1992 and the later years (Fig. 23). Com- ly higher on the first day after the gale than during the fol- parison of abundance indices of selected demersal fish species lowing days or before the gale, whereas catches of the pelagic suggested that in the German Bight (Box A) the previously species like scad (Trachurus trachurus) and mackerel (Scomber (1987 – 1992) more or less gadoid-dominated assemblage, scombrus) were significantly higher on the second day after the characterized by cod and whiting, changed to a flatfish-domi- gale. These changes in the species assemblage were accompa- nated assemblage (1997 – 2005). Between 1993 and 1996 nied by shifts in diversity indices and multivariate description an intermediate situation occurred, when none of these fish of community structure (Fig. 22). Observed differences could groups dominated. During the most recent years, increased be explained by species-specific reactions to higher turbid- abundances of smaller fish species such as solenette (Buglossidi- 41

Fig. 23: MDS ordination of the species similarity matrix based on mean catch of species in Box A for the summer quarters of the years 1987 – 2005. The distance between two data points corresponds to the amount of dissimilarity between the two corresponding species assemblages (Ehrich et al. 2006).

Table 9: Number of hauls per Box and year (summer sampling only, quarters 2 and 3). year A B C D E F H K L M N P

1986 41 1987 29 13 27 80

1988 26 17 25 42 eschweizerbartxxx sng- 1989 36 22 25 24 25 25 1990 36 23 25 17 8 28 1991 50 25 27 26 28 28 27 24 1992 55 24 24 24 28 21 23 19 1993 51 15 11 20 27 23 25 27 1994 49 19 31 39 19 26 27 27 1995 44 19 21 24 21 26 26 24 1996 41 29 23 27 28 26 17 28 1997 35 22 15 19 6 18 25 26 1998 50 19 20 19 17 20 25 23 1999 24 14 23 28 10 27 34 30 20 23 2000 21 16 15 – – – – – – – 8 2001 18 21 23 22 18 24 27 22 24 24 17 2002 19 21 22 21 15 17 17 9 20 21 9 2003 20 21 14 21 15 24 23 24 21 22 9 24 2004 27 21 21 21 19 17 23 17 19 21 15 16 2005 26 21 16 21 14 16 20 14 21 21 20 15 Sum: 657 382 408 536 298 366 339 314 125 132 78 55 Total: 3557 hauls 42

Northern North Sea Boxes Box L 20 Box L Regr Box M Box M Regr 15 Box D Box D Regr

5 n n (southernspecies)

0 1984 1988 1992 1996 2000 2004

Central North Sea Boxes Box B 20 Box B Regr Box C Box C Regr 15 Box H Box H Regr Box K Box K Regr 10 Box P

5 n (southern n species)

0 1984 1988 1992 1996 2000 2004

Soutern North Sea Boxes Box A 20 Box A Regr Box E eschweizerbartxxx sng- Box E Regr Box F 15 Box F Regr Box N

5 n n (southern species)

0 1984 1988 1992 1996 2000 2004 Year

Fig. 24: Presence of southern species in the different Boxes; data from 1986 to 2005. Linear regression lines are inserted for a first visual impression only. Statistical analyses used a GLM as described in the text. Definition of southern component according to Yang (1982) and Ehrich & Stranksy (2001). Total number of species: 89, including 35 northern species [same as 34 in Ehrich & Stransky (2001), additionally: butterfish – Pholis gunnellus], southern species [n = 41, with 6 new records, see text. Removed from original list: “Alosa alosa” as it was a misidentified A. fallax, and Raja brachyura), and an intermediate category with 13 species of undefined origin Gasterosteus( aculeatus removed from original list). um luteum) and scaldfish (Arnoglossus laterna) also contributed General differences between Boxes and changes in the to the typical assemblage of Box A and southern species like southern species component red gurnard (Aspitrigla cuculus), sardine (Sardina pilchardus), anchovy (Engraulis encrasicolus) and striped red mullet (Mullus Ehrich & Stransky (2001) analysed spatial and temporal surmuletus) have appeared more regularly than in the first years changes in the species assemblage of fish in the Boxes, and of the German Small-scale Bottom Trawl Survey (see below). particularly changes in the presence of southern species. The 43

Table 10: Association of Boxes to North Sea water masses and throughout the investigated years 1991 – 2005 (p = 0.013) in groups according to geographical location within the North Sea. which the trend was parallel in both groups (interaction, p = 1) Laevastu (1963). 0.106, n. s.). The absolute numbers of southern species were significantly higher in the Southern Boxes than in the Central Geographical North Sea Water masses1) Boxes Boxes (p = 0.011). location associated Box F lies on the border between Channel water and Eng- lish Coastal water (Fig. 6; Tab. 10). It is this Box, which would Northern North Sea Northern North Sea water L, M first be affected by water masses coming in from the south North Atlantic water D and it is also clearly distinct in its average species composition when assemblages are compared by multidimensional scaling (MDS plots; Ehrich & Stelzenmüller, unpublished data). Central North Sea North Atlantic water B However, the number of southern species observed in Box F (southernmost part) tended to be lower than in Boxes A and E (Fig. 24). Overall, Northern North Sea water H, C the number of southern species was highest in the group of (southernmost part) southern Boxes – water masses “Channel water” and “Con- Central North Sea water P, K tinental Coastal water” according to Laevastu (1963) – than in all the other Boxes, except Box D in the north. Box D is associated with North Atlantic water and has the highest total Southern North Sea Continental Coastal water A, N number of species and in this also a relatively high number of Channel water E southern species. In all other Boxes in the central and northern Channel water F North Sea, the number of southern species did not exceed 10, or remained well below that number. Several southern species have newly appeared in the Boxes within the years 1999 to 2005: reticulated dragonet – Calli- onymus reticulatus, crystal goby – Crystallogobius linearis, white seabream – Diplodus sargus, snake pipefish – Entelurus aequo- reus, straight-nosed pipefish – Nerophis ophidion, and large analysis was based on 1986 to 1999 data from the ten Boxes spotted dogfish –Scyliorhinus stellaris. sampled regularly at the time. We now extended the data set by including the years up to 2005, which also contain data for the Boxes N and P (Tab. 9). In all Boxes except Box C, a trend Geostatistical evaluation of GSBTS data of increasing numbers of southern species could be observed. Fig. 24 groups the Boxes according to their geographic loca- Concept tion and the water masses they are associated with (Tab.eschweizerbartxxx sng- 10). Immigration or intrusion of fish species from southern waters In many fisheries studies including the GSBTS simple (“Lusitanian fauna”, Yang 1982) occurs through the British random sampling designs are employed and often classical Channel, and would therefore primarily be expected in the statistical procedures are used for data evaluation. In these southernmost Boxes. cases observations are assumed to be independent from each The general trends observed by Ehrich & Stransky other. Stochastic independence means that the realisation of (2001) are reaffirmed, with the highest proportions of south- a random variable at one location does not influence realisa- ern species being found in the assemblages of the southern tions at neighbouring locations. If this pre-condition is met, Boxes (Fig. 24). population estimates like means and variances can be derived A repeated measurement analysis of variance (GLM, SPSS directly from the sample values without making any assump- version 13, SPSS Inc.) was used here to test for differences tions about the spatial distribution of the population (Petit- in the number of southern species in the Boxes. Within-sub- gas 2001). However, when random sampling is not carried out ject effects, or repeated measurements, were the years from on a specific spatial scale, any eventually occurring underlying 1991 – 2005, without the year 2000, for which only few sam- spatial structure in the distribution of the organisms can lead ples existed. Between-subjects effects refer to the differences to a bias in calculating such population estimates. Unfortu- between groups of Boxes, where the group “Southern Boxes” nately, it is not possible to detect such a bias a priori, since the consisted of the Boxes A, E, and F, and the group “Central appropriate scale of the spatial distribution of any species of Boxes” of the Boxes B, C, H, and K. The group “Northern interest is generally unknown (Maynou 1998). Boxes” was excluded from the analysis because Box D was the The presence of a spatial structure is indicated by spatial only member of this group with enough repeated measure- autocorrelations between pairs of samples, viz. when the reali- ments (years, see Fig. 24) and hence could not reliably be com- sation of a regionalised variable (e.g. biomass of organisms) at pared with the other two groups. However, in a preliminary one location influences realisations at neighbouring locations. analysis, the estimated marginal means of the model for Box D Thus, when samples are not taken independently of one an- were more similar to those of the Southern Boxes than to those other and when the population sampled is spatially structured, of the Central Boxes. To determine the probability (p-value), the computation of any population parameter like variance epsilon adjustment according to Huynh-Feldt was applied and requires a model of the spatial correlation in the population revealed that the number of southern species in both groups (Matheron 1971). Spatial autocorrelations in a data set can (Southern and Central North Sea Boxes) significantly increased be analysed and modelled mathematically by geostatistics. 44

Geostatistical analysis:

1. Structural analysis 2. Modeling 3. Estimation Empirical variogram Theoretical variogram Kriging

80 80 sill 60 60

40 40 range 20 20

Semivariance Semivariance nugget 0 0

0 5 10 15 0 5 10 15 Distance (km) Distance (km)

Fig. 25: Three steps of a geostatistical analysis. The empirical variogram is derived from a variogram cloud by grouping pairs of observation into distance classes. Secondly, a specific variogram model is estimated which is fully described by the 3 parameters nugget, sill and range. This model is used to obtain interpolations on a regular grid (kriging) leading to a contour map which represents a spatial model of the observed data.

In fisheries, geostatistics is used to optimise sampling strat- regionalised variable of interest (e.g. biomass of organisms) egies (Petitgas 1996, Rivoirard et al. 2000), to estimate (Fig. 25, step 3). More details and modifications of geostatisti- catch data and corresponding variances, taking into account cal analyses are provided in the material and methods sections the existence of spatial structures (Fernandes & Rivoirard of papers dealing with the following case studies. 1999, Rueda & Defeo 2001, Wieland & Rivoirard 2001, Harbitz & Aschan 2003), as well as to map the estimated distributions and spatial patterns of organisms (Maravelias et Case studies al. 1996, Maynou 1998, Fletcher & Sumner 1999, Rueda Meso-scaled investigation on L i m a n d a l i m a n d a & Defeo 2003). ( B o x A ) To avoid potential problems with unjustified assumptions In the context of planning and building offshore wind of stochastic independence of the data, geostatisticaleschweizerbartxxx sng- approach- farms within the inner German Bight, this study provides a es were employed to analyse various GSBTS data sets, espe- method for evaluation of future long-term monitoring data in cially regarding the persistence and changes of spatial patterns order to assess possible effects on fishes (Stelzenmüller et al. of fish populations with time and to assess their influence on 2004). Data collected by the GSBTS during the summer cruis- the estimation of abundance indices at the level of meso-scaled es 1996 – 2000 in a small area of the inner German Bight (Box GSBTS Boxes as defined in section “Survey description”, A) were analysed (see section “Survey description”, p. 15., Tab. p. 15. 1). Geostatistical tools were used to discover characteristics and persistence of spatial structures of two different size classes of the demersal fish species dab, Limanda limanda (Linnaeus Methods 1758), as a measure of natural variability. Spatial autocorrelation was detected in the catch data for both size classes, and For a geostatistical analysis, differences in the realisations of spatial structuring was persistent throughout the time of inves- a regionalised variable (e.g. biomass of organisms) between all tigation (Fig. 26). Both size classes could be characterised by a possible pairs of observations are considered leading to a vario- moderate degree of spatial dependency within the catch rates. gram cloud, which represents the dissimilarity of observations Furthermore, larger dab tend to aggregate in patches 3.2 km with increasing distance of the sampling localities. Because in in diameter, whereas medium-sized dab aggregated in patches this form it is almost impossible to depict a clear pattern, it with average diameters of 1.1 km. The modelled structures is necessary to group observations into distance classes, either were used to calculate the mean cpue of dab within the sur- regarding all directions or only regarding a certain direction. vey area. This kriged mean was compared with the calculated Distance classes and directions are specified through a search arithmetic mean. Furthermore, the geostatistical variance of ellipse, leading to the empirical variogram (Fig. 25; compare the arithmetic mean was compared to the ‘classical’ variance Isaaks & Srivastava 1989, Cressie 1991, Pannatier 1996). (neglecting the spatial structures) showing a reduction of vari- This graph and the fitted model (Fig. 25, step 2) are useful ability of mean catch rates with the geostatistical approach in tools with which to analyse the spatial structure of the region- many cases. The contour plots of biomass index, estimated by alised variable investigated regarding small-scale heterogeneity kriging based on the models fitted to the mean structures for (nugget effect), the strength of spatial structure (sill) and the all years, displayed no locations with persistently increased fish distance beyond which samples become spatially independent biomass index for either size class throughout the years. How- (range). As a result of kriging we obtain a contour plot of the ever, clear differences in aggregation patterns (“patch forma- 45

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Fig. 26: Empirical variograms (semivariograms) of cpue catch data (1996 –1999) for dab size group d2, 9.5–19.5 cm, 2–7 years old (left panel) and d3, >19.5 cm, older than 7 years (right panel) from the German Bight (Box A) with fitted spherical and linear (1977) models (Stelzenmüller et al. 2004). Note that for the structural analysis in 1998 and 2000 of d3 the modulus estimator was used and that Figure 26 (f) varies in scale. tions”) were found for two size classes of dab, demonstrating spatial dependency. For whiting no reduction of the small scale the importance of distinguishing size (age) classes of fish, when variability could be detected; a significant difference in the spa- conducting a spatial analyses. Hence, spatial patterns in fish tial structuring was only found for two different size groups of distributions at the spatial scale of a Box should be taken into whiting. Uncertainty of mean catches of dab and whiting was account when estimating abundance indices. reduced in 2002, while in 2003 this effect of the star survey was less pronounced due to the high local density of the nearby stations. We conclude that the star survey design can be an inexpensive and effective procedure – depending on the species Impact of additional small-scale survey studied and/or the positioning of the nearby stations – when data (Box A) a minimised small-scale variability and a reduction of uncer- Geostatistical tools have been used to investigate the im- tainty in mean biomass of fish are the focus of interest. This pact of additional small scale catch data (star survey design) procedure can help to optimise the spatial analysis of biomass on the spatial analysis of fish, regarding different biological indices as a basis for a stock assessment taking spatial autocor- groups of dab, Limanda limanda and whiting, Merlangius mer- relations into account (Fig. 27). langus (Stelzenmüller et al. 2005b). A standard survey carried out in January (2001 – 2003) in a meso-scaled area in the German Bight (Box A) was modified by additional small-scale Effects of survey scale (Box D) sampling in 2002 and 2003, whereas across one randomly se- Geostatistics were employed to investigate spatial struc- lected station within Box A trawling was carried out several turing of herring, cod, dab, haddock and whiting at differ- times. Adopting the star survey reduced the small-scale vari- ent spatial scales in the northern North Sea (Box D, Stel- ability for medium-sized and male dab, as indicated by lower zenmüller et al. 2005a). Additionally, a structural analysis of values of the nugget effect and an increased resolution of the the maximum water depth was carried out to assess habitat 46

18 18

16 16

14 14 160 24 12 12

10 110 10 17 8 8 North (km) North North (km) North 10 6 60 6

4 4 3 10 2 (a) d2 01 2 (b) d3 01 0 0 0 2 4 6 8 1012141618 0 2 4 6 8 1012141618 East (km) East (km) 18 18

16 16

14 14 160 12 12 24

10 110 10 17 8 8 North (km) North North (km) North 6 60 6 10

4 4 10 3 2 2 (c) d2 02 (d) d3 02 0 0 0 2 4 6 8 1012141618 0 2 4 6 8 1012141618 East (km) East (km) 18 18

16 16

eschweizerbartxxx sng- 14 14

12 24 12 24

10 10 16 17 8 8 North (km) North North (km) North 6 8 6 10

4 4 0 3 2 2 (e) d2 03 (f) d3 03 0 0 0 2 4 6 8 1012141618 0 2 4 6 8 1012141618 East (km) East (km)

Fig. 27: Density of dab biomass (cpue, kg 30min-1) for size group d2, 9.5–19.5 cm, 2 – 7 years old (a, c, e) and d3, > 19.5 cm, older than 7 years (b, d, f) during cruises 2001 – 2003 (with star survey design) within Box A (Stelzenmüller et al. 2005b). Estimations with ordinary kriging based on models fitted to annual structures. For d2 in 2001 and 2002 the model fitted to the generic semivariogram was used for mapping.

associations of fish. Linear, spherical, exponential and Gauss- a high level of habitat association was detected for haddock ian models were fitted to the empirical variograms (semivario- and whiting, while a poor habitat association was found for grams), showing clear spatial autocorrelations. At the smaller cod, dab and herring (Fig. 28). The smaller scale seems to be scale, spatial structuring was weak for haddock, herring and the threshold at which spatial structuring of cpue could have dab, increasing at the larger spatial scale, with the exception marked influence on estimation error. Thus, survey scale is im- of whiting. Mean catch rates, estimated classically and geo- portant when analysing spatial patterns and estimating mean statistically, were in good agreement. Corresponding variances biomass indices, and a sound analysis of relations in spatial were clearly reduced at both spatial scales, when accounting structuring of fish and habitat conditions is essential to derive for spatial distribution of the fish. At the larger survey scale more precise estimates. 47

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Fig. 28: Density maps of cpue [kg 30min-1] of herring, cod, whiting, haddock, dab as well as the maximum depth within the total area, estimated with (universal) point kriging (Stelzenmüller et al. 2005a). Note that the scale differs due to the varying abundance. The smaller area of Box D is displayed in a three-dimensional model of depth. 48

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Fig. 29: Density maps of biomass indices [kg ha-1] for three size classes of dab from the German Bight, Box A (d1, < 9.5 cm, 0 – 2 years old; d2, 9.5–19.5 cm, 2 – 7 years old; d3, > 19.5 cm, older than 7 years), derived with ordinary point kriging using catch data of both the 7 m-beam trawl (n1, left panel) and the cod trawl (n2, right panel) (Stelzenmüller et al. 2006).

Does the type of fishing gear employed fishing gear type on analysing spatial patterns, employing matter? (Box A) geostatistics (Stelzenmüller et al. 2006). In an area equal In the North Sea impact studies are carried out to assess in size to a wind park (with approximately 200 windmills), the effect of offshore windmills on the spatial distributions of a comparative fishing experiment was carried out, where a various fish species, based on data often obtained from differ- 7m-beam trawl and an otter trawl were employed. Structural ent fishing gears. A recent study focused on the spatial analysis analyses showed a presence of spatial autocorrelation in the of three size classes of Limanda limanda (dab) in the German catch data in all cases. The use of an efficient sampling gear led Bight (Box A) and the assessment of the impact of different to an improved resolution of spatial structuring (Fig. 29), but 49 did not necessarily result in a reduction of nugget variability. the most striking patterns is the formation of animal aggre- Ecological parameters derived from a spatial analysis were in gations. Classically, aggregation is viewed as an evolutionary good agreement in case of high abundance and similar gear advantageous property, because it is believed that it increases efficiency. Thus our results show that the type of gear matters, the survival probability of the individual group members (e.g., especially in the case of low species abundance. Therefore, to Pitcher & Parrish 1993, Moore 2001). However, such per- achieve reliable results of a structural analysis and an accurate sistent aggregations of potential prey organisms can also at- spatial assessment of fisheries data, we recommend consider- tract predators. Subsequently, the per-capita mortality of the ation of both, i.e. the abundance of the target species (biologi- aggregated potential prey can increase rapidly (e.g., Connell cal group) and the efficiency of the sampling gear employed. 2000). Such an aggregative behaviour of predators has been mainly documented for avian (Wittenburger & Hunt 1985) and marine mammal predators (Domenici et al. 2000), but Conclusions also for tropic and temperate marine fish (Connell & Gil- landers 1997, Temming et al. 2004). Our results on geostatistical analyses within the framework Hence the question arose whether there are universally of the GSBTS clearly demonstrate the occurrence of spatial au- valid patterns in the key processes that determine the predator- tocorrelations which might hamper the classical estimation of prey interaction between specific predator and prey species. population parameters such as the mean abundance index and The GSBTS offered the ideal platform to answer this ques- its variance. Furthermore, the detected spatial patterns charac- tion and to analyse the two key processes that dominate local terised by the range parameter of the variograms are consistent predator-prey interactions: with time and can thus be regarded as a specific attribute of 1. Spatio-temporal predator-prey overlap (with aggregative the fish population under study, although locations of high response and diurnal feeding rhythms) biomass might change with time. Differences in aggregation 2. Diet selection (with functional response) patterns occurred between sampling seasons (summer vs. winter) and biological groups of fish species (male vs. female; size classes) which can be quantified by the geostatistical analysis. Analysis of key processes that determine local predator- prey interactions Predator-prey interactions fish-fish The analysis presented is based on two surveys in Box D Key processes determining predator-prey interactions during the May-June 1992 and July 1996. In 1996 the survey area was extended in a south-westerly direction. Our understanding of ecosystem functioning is substan- In both surveys the predators whiting and haddock in the tially enhanced through our knowledge of small-scale preda- size range 25 – 29.9cm were analysed, the dominant prey being tor-prey interactions, which is a prerequisite for a reliable ex- sandeel in both situations. Nevertheless, the two feeding situa- trapolation towards large spatio-temporal scales of theeschweizerbartxxx sng- entire tions revealed some major differences which helped to under- system. Besides the pure scientific reasons, trophic interactions stand the dynamics of local predator-prey interactions. between marine fish have an important applied management In 1992 twenty-four trawl hauls were conducted from aspect, as both ecosystem-, multi-species fisheries assessment May 30 to June 1 and 690 stomachs of each predator whiting models need reliable parameterisations of consumption and and haddock (25 – 29.9cm) were analysed. During the 1996 diet selection processes. sampling exercise from July 18 – 22, a total of 35 trawl hauls The key processes affecting trophic interactions in the were conducted and stomachs of 1063 whiting and 1194 had- North Sea fish assemblage were identified in a review on dock were analysed. Further details on the sampling design “North Sea Fish and higher trophic levels” (Floeter & Tem- and the analysis methods were provided in Mergardt & Tem- ming 2003b) and further analysed in Floeter & Temming ming (1997) and Temming et al. (2004). (2003a, 2005) and Floeter (2005): they are (I) diet selection The visual inspection of the spatial distribution of the and (II) spatio-temporal overlap between predator and prey. predator biomass showed no distinct spatial pattern in 3 of Again two processes were identified to govern diet selection: the 4 survey-species combinations (Fig. 30a, b, d), i.e., there prey size and prey species preference, of which prey size was was no gradient or clear separation of sub-areas with low and of higher importance, while spatio-temporal overlap was the high biomass. However, the biomass distribution of whiting most important factor overall (see also Hinz et al. 2005). in the 1996 survey revealed a gradient in south-westerly di- Trawl data from scientific surveys are the main data source rection, which, in combination with their diet composition, available for ecological field investigations. Predation as the triggered the extension of the survey area (Fig. 30c). The spatial dominant biological process structuring marine ecosystems distribution of the mean sandeel prey weight in the stomachs occurs at the level of the individual. However, spatial investiga- of the predators showed in no distinct spatial pattern in the tions at the scale of individual fish are in principle not possible 1992 investigation (Fig. 31a, b, but the 1996 survey revealed from trawl hauls, in which individuals are pooled over several a gradient in south-westerly direction in both predator species kilometres of sampling. Subsequently when working with sur- (Fig. 31c, d). vey data, the key process (II), “spatio-temporal predator - prey If both distribution patterns are combined by calculating overlap” has to be chosen instead of the more detailed process the predation impact as the product of the predator biomass “predator - prey encounter”, which would have been more ac- and the mean weight of sandeel prey in the stomachs at each curate in studies of trophic interactions. trawl station, it can be seen that the predation impact on sand- When analysing spatio-temporal predator – prey overlap eel showed no clear pattern in 1992 (Fig. 32a, b). In 1996 50

Fig. 30: Predator biomass [kg / 30min] distribution in Box D a) 1992 whiting, b) 1992 haddock, c) 1996 whiting, d) 1996 haddock. All predators 25 – 29.9cm, Box D area is depicted by the thin borderline.

eschweizerbartxxx sng-

Fig. 31: Distribution of mean weight of sandeel in stomach of predator [g] in Box D. a) 1992 whiting, b) 1992 haddock, c) 1996 whiting, d) 1996 haddock. All predators 25 – 29.9cm, Box D area is depicted by the thin borderline. 51

Fig. 32: Impact distribution in Box D: Sandeel Impact = predator biomass [kg / 30min] • mean weight of sandeel in stomach of predator [g]. a) 1992 whiting, b) 1992 haddock, c) 1996 whiting, d) 1996 haddock. All predators 25 – 29.9cm, Box D area is depicted by the thin borderline.

the predation impact by both whiting and haddock showedeschweizerbartxxx sng- a The mass of the sandeel fractions in the stomachs as well clear gradient, with values increasing in south-westerly direc- as the mean number of sandeel per stomach increased greatly tion (Fig. 32c, d) during the evening and night hours for both predators, with Apparently, in all four local predator-prey interactions situ- haddock having both higher mass and higher numbers of ation-specific properties of the key processes lead to either dif- sandeels in their stomachs compared to whiting (Fig. 33b). ferent or similar impact pattern. Those situation-specific prop- The frequency of predators with sandeel in their stomachs in- erties will be explored subsequently in greater detail. creased from about 20% in the early evening hours to almost 100% by the end of the night in haddock. The pattern for Diurnal feeding rhythms of whiting and whiting was very similar but on a lower level. If total stomachs haddock in Box D contents from the 7 stations were compared between the two – The 1992 field sampling: In 1992 the 24-hour fishery predators, the difference in stomach content levels is statisti- (24 hauls) revealed that whiting (25 – 29.9cm) were feeding cally significant (Mann-Whitney test, N-whiting = 324, N- on sandeel whereas haddock hardly fed on sandeel and was haddock = 379, p = 0.035 (two tailed)). therefore not analysed for time-of-day effects. The 690 whiting The sandeels found in predator stomachs in the evening stomachs contained 694 sandeel in the size range of 12 – 20cm. hours (19:53 and 21:28 h) were mostly in a progressed stage These rather large sandeels led to a very high mean stomach of digestion. The share of fresh sandeels increased rapidly after content weights (Mergardt & Temming 1997). The results 21:28 h in both predators. indicated a single feeding peak with a maximum feeding be- – Comparison of the 1992 and 1996 feeding situation: In tween 22:00 and 24:00h and minimal food intake between both years 1992 and 1996 whiting and haddock fed on sand- 08:00 and 10:00h. eel during the night. However, the question remains whether – The 1996 field sampling: In 1996, the 35 hauls revealed there was a single feeding peak or 2 feeding peaks at dusk and that whiting and haddock (25 – 29.9cm) were both feeding on down. sandeel (Temming et al. 2004). The analysis of the 1063 whit- The 1992 investigation led to the conclusion that the op- ing and 1194 haddock stomachs revealed that the percentages posite direction of the vertical migration routes of whiting and of empty stomachs decreased from values above 15% in the sandeels reduces the potential times of spatial overlap to two early evening hours to below 3% in the early morning hours in narrow periods during dusk and dawn, from which one would both predators with whiting having higher values throughout expect two feeding peaks. At the time of the year when the in- (Fig. 33a). vestigation was carried out (May/June 1992), dusk and dawn 52

Fig. 33: Percentage of empty stomachs (a) and mean wet mass (g) of the sandeel share in eschweizerbartxxx sng- stomachs (b) in whiting (•) and haddock (°) sampled in the sub area outside of the Box (SW_ OB, see Figs. 30 – 32, 36) plotted with time of day. – Figure from Temming et al. 2004.

2000

1800

1600

1400 y = 61.203x + 358.71 y = 13.578x + 558.03 2 R = 0.031 2 1200 R = 0.0027

1000

800

600 Predator density (N/30min) density Predator 400

200

0 -1.00 1.00 3.00 5.00 7.00 9.00 11.00 Mean sandeel mass in stomach (g)

Fig. 34: 1992 Box D: Aggregative response plot of whiting (black circles) and haddock (open squares) CPUE of predators (25 – 29.9cm) as a function of the average weight of sandeel prey found in the stomachs of the predators (25 – 29.9cm). Linear regression equations were y = 13.578x + 558.03 and y = 61.203x + 358.71 for whiting and haddock with respective R2-values of R2 = 0.0027 and R2 = 0.031. 53

Fig. 35: Frequency distribution of the mean number of days between the food intake of meals (= individual sandeels) derived from the simulation. occurred in the Northern North Sea at 21:30 h (GMT) and size a whiting predator may also be satiated for some days, 02:30 h (GMT), respectively. It was judged as unlikely, how- as the digestion of a 7g sandeel takes around 48 hours for a ever, that two feeding peaks, which are so close together, could 25 – 29.9cm whiting. Thus, such a satiated whiting may have be separated given the limited precision of the back-calcula- no incentive to remain in an area of high prey densities. This tion method, which was applied in Mergardt & Temming may be the reason for not showing an aggregative response in (1997). that particular feeding situation (Fig. 34). For 1996 the conclusion was the same as for 1992: whiting Temming & Mergardt (2002) estimated the mean time and haddock fed on sandeel when vertical migrations crossed between meals in the field from stomach content data and gas- (during night, sandeel borrow, predators ascend). This reduced tric evacuation functions of whiting by applying a simulation the vertical spatial overlap to only a few hours, whereas consid- model to the 1992 data. For the subgroup of whiting with two ering only the horizontal dimension would suggest a completeeschweizerbartxxx sng- sandeels in their stomachs they estimated an average time be- spatial overlap during the entire day. tween the intake of the first and the second sandeel at two days. If the whole population including whiting with empty stom- Aggregative response and diet selection of achs was considered in the simulation model, the average time whiting and haddock in Box D between two meals was estimated as 4 days. This time corre- – The 1992 field sampling: In the 1992 Box D survey it sponds closely to the total evacuation time of a single sandeel, was obvious that whiting was much more successful in preying implying that whiting in this field situation took a new meal on sandeel than haddock, most likely because of the rather at approximately the time, when the old meal was completely large sizes of the available sandeel which was from 12 – 19.9 emptied from the stomach. Thus, in this feeding situation the cm (size distribution of sandeel in whiting stomachs). Whiting average time between meals was 4 days for individual whiting showed very high total stomach content weights with several (Fig. 35) and the average probability of encountering a sandeel station mean values around 10g. was 0.3/day for individual whiting. A visual inspection of the spatial distribution of predator The feeding history of the field situation investigated here biomasses did not show higher whiting biomass levels in areas was unknown. However it can be assumed that feeding condi- of higher sandeel shares in the stomachs (Fig. 30c, d, Fig. 31c, tions are on average much worse than those investigated in d). So, neither whiting nor haddock predators showed aggre- 1992. Daan (1989) and Hislop (1997) summarized the re- gative responses (Fig. 34). This implies that the whiting were sults of a two year round North Sea wide stomach sampling unable to maintain their position in a prey patch over periods exercises (1981 and 1991). Mean stomach content values from of several days. Mergardt & Temming (1997) detected a clear these compilations are only about 1.5%bw (body weight) daily feeding periodicity of whiting with peak feeding around whereas the mean stomach content in the 1992 field situation midnight. They interpreted this as a result of the inverse daily was about 4%. The low average values indicate that quite often vertical migration patterns of sandeel and whiting. According food is not encountered in the field in sufficient amounts. The to this hypothesis whiting can only access sandeel during the specific situation investigated here demonstrates on the other vertical overlap during dusk and dawn. During day- and night hand, that whiting can compensate for periods of low food time whiting and sandeel are separated vertically and individ- availability with extremely intensive food intake in situations ual whiting are most likely unable to avoid being drifted away of high food availability. from a food patch which was previously encountered. Considering the very high stomach contents in the field On the other hand, after feeding 1 – 2 sandeel of that large data of our investigation, one can ask, if the whiting in this 54

eschweizerbartxxx sng-

Fig. 36: 1996 Box D: Prey composition of whiting (a) and haddock (b) stomachs. Diameter of circles represent mean total stomach content in g wet mass. Displayed prey types are sandeel (black), herring (grey), undefined fish prey (hatched) and invertebrates (white). Sub areas NW, NE, SW and SE together are referred to as “Box” while SE_OB is referred to as outside of the Box. – Figure from Temming et al. (2004). 55 specific field situation were feeding at or even above their the stomach content mass being sandeel (Fig. 36a). The other maximum sustainable food intake (Cmax). The analysis revealed relevant prey fish were herring and Norway Pout, accounting that whiting in the investigated field situation with a mean overall for 8.62% and 4.86% of the diets in whiting, respec- stomach content of about 7g were feeding very close to Cmax tively. However, Norway Pout occurred in only 46 whiting as determined experimentally (N. G. Andersen, DIFRES, stomachs (7 in SW_OB, 39 in Box). Herring occurred in only Denmark, pers. comm.). Nevertheless about 50% of these fish 35 whiting stomachs (31 in SW_OB and 4 in Box). The total had stomach contents well above this average, while others had contribution of invertebrates to the whiting diet amounted to little or no food in their stomachs. This shows, that (long term) only 4.49%.

Cmax is neither restricted by the gastric capacity nor by gastric Haddock stomachs revealed a higher share (33.39%) of in- throughput rate. Cmax may instead be adjusted to the maxi- vertebrates in their diet, the fish diet being clearly dominated mum capacity of either absorptive or biochemical processes by sandeel (86.84% of all fish). The spatial distribution of the subsequent to gastric evacuation. In a patchy environment, the sandeel component in the haddock diet resembled closely that gastric capacity must be sufficiently large, to make use of food of whiting: high shares in the south west corner of the Box and concentrations, if they are encountered. Fish in a food patch on stations outside (Fig. 36b). The stomach content mass of will eat in excess of their long time equilibrium needs (Cmax). haddock was positively correlated with the share of sandeel in This enables fish to feed with Cmax on average, even if peri- the diet, as observed in whiting. ods with good food supply are followed by restricted periods Herring and Norway Pout accounted for only 0.68% and without food. Thus, the apparent non-existence of a digestive 1.36% of the fish fraction. Norway pout occurred in only 12 constraint could well be an evolutionary adaptation towards a haddock stomachs (1 in SW_OB, 11 in Box) and herring oc- patchy environment. curred in 4 haddock stomachs (1 in SW_OB and 3 in Box). – The 1996 field sampling: In July 1996 in Box D whiting The sediment samples revealed mostly fine sand from sta- and also haddock were found to feed heavily on sandeel, but tions at the circumference of the Box with median grain sizes the sandeel prey fish were only around half the size of those in varying from 130 to 231 µm (Fig. 37). In the southern part of the 1992 situation, i.e., 6cm (Temming et al. 2004). the Box a band of stations is characterised by medium sands Whiting catch rates varied between 15.7 and 451 kg/30 with median grain sizes between 325 and 382 µm. Outside min. Catches above 100 kg/30 min occurred only in the south of the Box the majority of stations revealed medium sands west corner of the Box and on those stations outside of the with median grain sizes between 254 and 435 µm, the coarsest Box further to the south west (Fig. 30c). The highest catch sediment was found on station 632 outside of the Box. The rates were also obtained on stations outside of the Box with up fraction of very fine sediments varies between 40.9 and 0.3 to 451 kg/30 min. Overall, the mean catch rate of the stations %. Stations with high shares of very fine sediments are found outside of the Box (290.6 kg/30 min) exceeded that of stations more in the northern part of the Box, while lower shares are within the Box (70.4 kg/30 min) by a factor of four. The same found in the SW including the stations outside of the Box, relation exists for the mean numbers of whiting per 30 min where also the station with the least fraction of very fine sedi- in the size class 25 – 29.9 cm, when catch rates in theeschweizerbartxxx Box sng- are ments is located. compared with those from the area outside, the difference be- The trawl catches indicated a strong concentration of whiting highly significant (p=0.001, Mann-Whitney test). ing in the South West part of the investigation area mainly Haddock catch rates varied in a similar range between 51.4 outside of the Box area (SW_OB) while the SW part of the and 485 kg/30 min (Fig. 30d). The catches of haddock were Box shows intermediate densities of whiting. From the smaller more evenly distributed over the entire investigation area with subset of trawl catches that were performed with a fine-mesh high catch rates both, within and outside of the Box. The mean cover over the cod end it appears that the sandeel were also catch rate was higher on the stations located outside of the Box concentrating in the same sub area as the whiting: highest (278.3 kg/30 min) compared to the mean catch rate within the catches in SW_OB, intermediate catches in the SW part (Fig. Box (163.2 kg/30 min) by a factor of 1.7. The catch rates of 36). haddock of the size class 25 – 29.9cm, however, are only 20% High sandeel catches were obtained in the 1996 investiga- higher in the area outside of the Box and this difference is not tion mainly in the evening and night hours in the small area significant (p = 0.442, Mann-Whitney test). outside of the Box. This indicates that the sandeel were mainly Whiting was found to have a significant higher aggrega- accessible to the trawl when they stay close to the bottom in tive response: the regression of whiting abundance of the mean the transition phase between their pelagic and their fully ben- amount of sandeel in the stomachs explains 48% of the vari- thic lifestyle. The tows made on other stations at similar eve- ance, the regression is highly significant (N = 32, r² = 0.48, p < ning and night hours, however, did not reveal any substantial 0.001). If only the night stations are used the explained vari- catches of sandeel. So overall the limited data from the fine- ance increases to 61% (N = 24, r² = 0.61, p < 0.001). The same mesh cod end cover suggest that high concentrations of sand- regression for haddock (all times) explains only 0.7% of the eel were most likely restricted to the small area outside of the variance and is not significant (N = 33, r² = 0.01, p = 0.640). Box, while intermediate concentrations occurred in the SW The dominant prey species of whiting was sandeel, which part of the Box. The limited sediment data would support this occurred in the stomachs from 25 stations (406 stomachs, interpretation: the station with the most suitable median grain 284 in SW_OB, 111 in SW) and accounted overall for 66% size and lowest fraction of very fine sediments is located in the of the stomach contents. Generally, high stomach contents area with highest sandeel catches. Stations with small median (> 1 g) corresponded with pure fish diets (99% fish). Sandeel grain sizes and higher shares of very fine sediments are located dominance was most extreme on stations outside of the Box more in the NE part of the Box. and in the south west corner of the Box with 53% to 93% of It has been demonstrated that sandeel prefer very specific 56

Fig. 37: 1996 Box D: Median grain size and fraction of very fine sediments of the sediment samples. Circle diameter represents median grain size class and the intensity of the grey tone representing the fraction of very fine sediments. The inserted bar graphs indicate a) the catch rates of sandeel in the GOV including the catches from the cod end cover (log(number/30 min), hatched bars) b) the number of sandeels in whiting stomachs (log(mean number/100 stomachs), black bars) and c) the number of sandeels in haddock stomachs (log(mean number/100 stomachs), grey bars). A bold frame around the bar chart indicates night samples. – Figure from Temming et al. (2004). eschweizerbartxxx sng- sediments with medium to coarse sands with median grain siz- which is relatively coarse we cannot deduce the dimensions of es between 0.25 and 2 mm and avoid likewise sediments with these suitable habitat patches. However, it is most likely that gravel or higher silt, clay and very find sand fractions (Reay the limitation of such optimal habitats may be the true cause 1970, Wright et al 2000, Jensen 2001). The ideal combina- for the aggregation of sandeel in the burying phase. tion of the two sediment properties seems to exist only on very This distribution pattern of sandeel was independently limited habitats like exposed edges of sand banks (Hobson confirmed by the presence or absence of sandeel in the stom- 1986, Jensen 2001). Hobson (1986) found that the burying achs of the two predators. If the two distribution patterns of habitat was a rather restricted patch of coarse sand of about predator and prey are viewed together, they basically indicate 0.1 ha that sloped sharply between depth of 5 and 10m. The that whiting aggregate on their sandeel prey. This pattern was area around this patch was floored with either silt, fine sand or less obvious in haddock. gravel with additional rocks. The small area outside of the Box in our investigation, where high sandeel densities were found, Comparison of the 1992 and 1996 feeding differed likewise from the remainder of the investigation area s i t u a t i o n : due to one station having the coarsest sand of the whole area The digestion of a 6cm sandeel may take only a day for a (station 632 with median particle size 435µm). According to 25 – 29.9cm whiting, so that in contrast to the 1992 situation Wright et al. (2000) and Jensen (2001) sandeel densities are the whiting in 1996 may have had greater appetite levels every inversely related to the fraction of very fine sediments. The night. This could be the reason for whiting trying to maintain same station (632) revealed also the smallest fraction of very their position at the sandeel habitat, which was located in a fine sediments (0.3 %) which makes this station most- suit south-westerly direction outside Box D. able as a sandeel habitat. Two of the neighbouring stations and This sandeel habitat with high whiting densities- wasre one station in the SW quadrant in the Box would be the next vealed by extending the sampling outside the Box area in attractive habitats with slightly lower median grain sizes and 1996, which was triggered by an obvious increase in whiting fractions of very fine sediments around 2%. Sandeel -densi catches with sandeels in their stomachs in the south western ties in the cod end cover roughly mirror this spatial pattern, area of the Box. i.e. with highest densities outside of the Box and intermediate The 1996 data revealed that during the above feeding situ- densities in the SW part of the Box. From our station grid ation, haddock were consuming significantly higher amounts 57 of sandeel during the evening and night hours than whiting. the aggregative behaviour of whiting and the diet selection of This result is somewhat surprising, since whiting is - general haddock, or sediment quality affects the distribution of prey ly known to be the more effective piscivore as was the case fish which in turn affects the predator distribution. Eventu- in 1992, while haddock typically feed on benthic organisms ally, the insights gained from the investigation of predator (Jones 1954, Hislop et al. 1997). The most likely explana- prey interactions at the small spatio-temporal scale will trig- tion for the higher efficiency of haddock in 1996 was that the ger new questions. When a scientific fisheries trawl survey is haddock took the small sandeel out of the sediment, as was undertaken, the majority of stations will be characterised as observed by Hobson (1986) for flatfish and sea sculpin, and low intensity feeding situations and only a few stations will that the sandeel in the 1992 feeding situation were too large show a high intensity feeding situation with high stomach for haddock to swallow. content weights and high predator biomasses. This pattern seems to be valid regardless of the spatial and temporal scale of the survey (see section “Analysing predator-prey interactions Conclusions at large and small scales”, p. 67). The remaining question now is - what determines the flux of biomass between the trophic The question when analysing predator-prey interactions levels? Is it the vast number of low intensity feeding situations? was whether there are universally valid patterns in the key pro- Or is the majority of biomass transfer and fish predation mor- cesses that determine the predator-prey interaction between tality occurring in the apparently rare predation hot spots? specific predator and prey species. The investigation of predator-prey interactions at the small spatio-temporal scale revealed that every feeding situa- Sediments and benthos tions seems to have its specific properties, which makes the identification of universally valid patterns in the key processes The GSBTS has been accompanied since 1998 by benthos that determine a relationship between a specific predator and investigations, which have been carried out by the Sencken- its prey species rather difficult. Even in trophic interactions berg Institute in Wilhelmshaven. The epifauna has been sam- between the same species (haddock and whiting preying on pled regularly twice a year in winter (January) and summer sandeel) situation specific properties like prey size or sediment (July/August) (Tab. 11), in summer the Boxes A, B, C, D, L substrate have a dominant influence on the nature of feeding and M, in winter only the Boxes A and N. In 2000, sampling interaction. For example, relative prey size obviously affects did not take place in Boxes D, L and M due to ship problems.

Table 11: Cruise data and information about sampling of infauna, epifauna and sediments in the Boxes A to M from 1998 to 2005.

eschweizerbartxxx sng- Epifauna Infauna Sediment Cruise Year Date Boxes sampled sampling sampling Sampling

WH 197 1998 17.07. – 09.08. A,B,C,D X - -

WH 208 1999 16.07. – 14.08. A, B, C, D, L, M X X X

WH 214 2000 24.02. – 03.03. A X – X

WH 219 2000 06.08. – 19.08. A, B, C X – X

WH 224 2001 02.01. – 09.01. A X – X

WH 230 2001 19.07. – 17.08. A, B, C, D, L, M X – X

WH 235 2002 03.01. – 11.01. A, N X – X

WH 241 2002 19.07. –16.08. A, B, C, D, L, M X – X

WH 247 2003 02.01. –10.01. A, N X – X

WH 254 2003 22.07. –17.08. A, B, C, D, L, M X (Mafcons) X (Mafcons) X

WH 259 2004 05.01. – 12.01. A, N X – –

WH 266 2004 26.07. – 26.08. A, B, C, D, L, M X (Mafcons) X (Mafcons) X

WH 270 2005 04.01. – 11.01. A X – –

WH 277 2005 19.07. – 17.08. A, B, C, D, L, M X – X 58

In addition to the epibenthic sampling, sediment samples were an area sampled of 500 m2. The catch efficiency of the 2 m obtained in most of the years and the infauna was sampled in beam trawl was studied by Reiss et al. (2006), while a com- the summers of 1999, 2003 and 2004 (Tab. 11). parison between the catch efficiency of GOV and 2 m beam trawl was carried out by Ehrich et al. (2004). Infauna was sampled with a 0.1 m2 Van Veen grab paral- Sampling and sample treatment lel to the sampling of epifauna, thus up to 9 grabs were taken per Box. The samples were sieved over 0.5 mm mesh size and Epifauna was sampled with a standardized 2 m beam trawl fixed in 4% buffered formalin. In the lab, the organisms were using a randomised sampling protocol. If possible, nine rep- identified if possible to species level. licates were taken in each Box. The beam trawl was made up Sediment samples were taken from an additional Van of galvanized steel with a chain matt attached to prevent the Veen grab. The samples were stored at –20°C prior to analysis. catch of boulders and to enhance the catch efficiency (Fig. 38). Analyses of mud content (<63 µm) were determined on dried The mesh size of the cod end was 4 mm, the mesh of the outer samples that were sieved with a 500 µm sieve to remove large net 20 mm. A detailed description of the beam construction shell particles. An aliquot of each sample was filled in a Laser is given in Jennings et al. (1999). The beam trawl was fitted Particle Sizer (Analysette 22 Economy; Fritsch) and was au- with a Scanmar depth finding sonar attached to the top of the tomatically homogenized by a stirrer and by ultrasonication. net just behind the steel beam. The depth sonar was used to de- Samples for the analysis of the content of total organic carbon termine the exact time and position of contact with the seabed. (TOC) were freeze-dried, powdered and homogenised. An ali- From the moment of contact with the ground the beam was quot of 10 – 30 mg was combusted at 1010°C in a C/N analy- towed with a speed of about 1.5 to 2 knots for 5 minutes. The ser (vario el) following acidification of the samples with con- ratio of towing warp length to water depth was approximately centrated HCl in a desiccator to remove inorganic carbonates. 3:1. Samples were sieved over 5 mm mesh size and then sorted. The majority of specimens were identified on board. The abundance and wet weight of the epifauna was determined using a Results and discussion motion-compensated marine scale (Pols) with an accuracy of 1 g. Modular species were recorded as present or absent and, Large scale variability of epifaunal communities if possible, weighed. Infauna species were excluded from the in the Boxes analysis because infauna sampling with beam trawl was not reliable. Unidentified species were preserved in a 4% seawater Until 2004, Neumann (2006) found a total of 173 epi- formalin solution for later identification. Abundance and bio- benthic species in 137 beam trawl catches taken in the Boxes mass were standardised to a tow length of 250 m respectively A, C and L. Table 12 presents the six dominant species in these Boxes in terms of mean abundance and percentage of occurrence. Mean total abundance and biomass were the highest in eschweizerbartxxx sng- Box A, dominated by echinoderms with 1138 ind. 500 m-2 and 1114 g wet weight 500 m-2 (Fig. 39), the brittle star Ophiura albida being the most dominant species (1008 ind. 500 m-2, occurrence in 89 % of all hauls) (Tab. 12). Lower total abundances and total biomasses were found in Boxes C and L with 135 ind. 500 m-2 and 939 g wet weight 500 m-2 (Box C) and 387 ind. 500 m-2 and 1057 g wet weight 500 m-2 (Box L), respectively (Neumann 2006). The echinodermata (76 ind. 500 m-2) dominated the taxa in Box C, but were less abundant than in the other Boxes. The sand starAstropecten irregularis (43 ind. 500 m-2) and the common starfish Asterias rubens (8 ind. 500 m-2) were the most abundant species. The mollusca were the dominant group in terms of biomass, of which the common whelk Buccinum undatum and Colus gracilis contributed about 89 % to the biomass in this Box. Similar to Box A, the abundance as well as biomass in Box L were clearly dominated by echinoderms. The sea urchin Echinus acutus (280 individuals 500 m-2) and for a lesser amount the sand star Astropecten irregularis (43 ind. 500 m-2) were the dominant species in terms of the abundance (95 %) within this group (Neumann 2006). The observed differences in the community structure between the three Boxes are in accordance with previous studies on the large sale patterns of epifauna communities, showing a separation between the southern, central and northern North Sea along the 50 m and 100 m depth contour (Frauenheim et al. 1989, Zühlke et al. 2001, Callaway et al. 2002). Since biomass determination of hermit crabs (Paguridae) Fig. 38: The 2-m beam trawl. is difficult, Reiss et al. (2005) published the chela-height vs. 59

Table 12: -2 1600 Mean abundance 500 m and frequency of occurrence in samples of the six dominant species in the Boxes A, C and L. Most abundant species in bold letters. 1200

Abundance Frequency 800 / 500 m² [%]

400 Box A Ophiura albida 1008 100

Mean abundance . Asterias rubens 137 100 0 Box A Box C Box L Liocarcinus holsatus 37 100 Astropecten irregularis 34 100 Crangon allmanni 14 31

1600 Crangon crangon 10 56 All species 1298 – 1200 Box C Astropecten irregularis 43 100 Buccinum undatum 12 100 800 Pagurus bernhardus 12 100

400 Asterias rubens 8 100

Mean biomass . Colus gracilis 7 83

0 Ophiothrix fragilis 7 88 Box A Box C Box L All species 135 –

30 Box L Echinus acutus 280 100 Astropecten irregularis 43 100 25 Asterias rubens 9 59 20 Crangon allmanni 8 96 15 Anapagurus laevis 6 96 Ascidiella aspersa 5 34 10 All species 387 – 5 Species number .

eschweizerbartxxx sng- 0 Box A Box C Box L

others Cnidaria Bryozoa Temporal changes of epifaunal communities in the boxes Crustacea Mollusca Echinodermata Up to now, only little information is available on the tem- Fig. 39: Mean abundance [ind. 500 m-2], mean biomass [g wet wt. poral variability of epifaunal communities in the North Sea 500 m-2] and mean species number [taxa haul-1] for the Boxes A, C (Frauenheim et al. 1989, Hinz et al. 2004, Reiss & Kröncke and L. 2004). Hinz et al. (2004) sampled the epifaunal community in Box A from summer 1998 to winter 2001. The echinoderms body-weight relationship for three hermit crabs Pagurus bern- Ophiura albida and Asterias rubens and the crustacean Pagurus hardus, P. pubescens and P. prideauxi sampled in the Boxes A to bernhardus were the dominant species caught throughout the L. And Reiss et al. (2003) studied the invertebrate associations study period. Overall the species composition of the catches with gastropod shells inhabited by P. bernhardus in some of was relatively consistent while abundances of dominant spe- the Boxes. In total, 51 epizoic species with up to 15 species cies fluctuated considerably between sampling periods. Differ- and 427 individuals per crab were found. Most abundant epi- ences between sampling periods were not only influenced by zoans were obligate associated species such as the polychaete the abundances of dominant species but also by less dominant Circeis amoricani paguri, the cnidaria Hydractinia echinata and species such as Ophiura ophiura, Astropecten irregularis, Corystes the crustacean Trypetesa lampas, as well as sessile epizoans also cassivelaunus, Crangon crangon and Aphorrais pespelicani. The found in hard-bottom habitats such as balanids Balanus cre- abundances of these species varied annually and seasonally in natus and Verrucia stroemia or free living species such as the the assemblage. Clear differences between summer and winter amphipod Gammaropsis nitida. The epizoic community struc- in the species composition, abundance and biomass were iden- tures on shells of the Boxes north of the 50 m contour differ tified. Annual and seasonal changes were most likely linked to from the southern communities on the Dogger Bank and in migratory movements of epifaunal animals into and out of the the German Bight. The northern stations were dominated by area under investigation due to water temperatures. The spatial sessile species, whereas a higher proportion of free living epizo- distribution of the total epifaunal biomass in Box A was cor- ans occurred at the southern stations. related to sediment characteristics. 60

3500 2500 Box A Box A 3000 2000 2500 1500 2000 1500 1000 1000 500

500 Mean biomass . Mean abundance . 0 0 1999 2000 2001 2002 2003 2004 1999 2000 2001 2002 2003 2004

200 Box C 1400 Box C 1200 160 1000 120 800

80 600 400 40 Mean biomass . 200 Mean abundance . 0 0 1999 2000 2001 2002 2003 2004 1999 2000 2001 2002 2003 2004

1000 Box L 1600 1400 Box L 800 1200 600 1000 400 800 600 200 eschweizerbartxxx sng- 400 Mean biomass . Mean abundance . 0 200 1999 2000 2001 2002 2003 2004 0 1999 2000 2001 2002 2003 2004

Cnidaria Crustacea Mollusca Echinodermata Bryozoa

Fig. 40: Mean abundance [ind. 500 m-2] and mean biomass [g wet wt. 500 m-2] in the Boxes A, C and L from 1999 to 2004.

Neumann (2006) studied the temporal variability of epi- above (Fig. 41). In Box C a slight decrease in the abundance faunal communities in the Boxes A to M during the GSBTS of echinodermata, mollusca and crustacea was observed from from 1999 until 2004. In Box A, a trend of decreasing mean 1999 to 2001 (Fig. 40). After 2001 the abundance increased total abundance and biomass is apparent between 1999 and with the highest values in 2002 (175 ind. 500 m-2) and 2004 2004, mainly caused by declining abundance of echinoder- (173 ind. 500 m-2). Echinoderms were the most abundant mata (Fig. 40; Neumann 2006). During this time period, the taxonomic group, also responsible for the temporal pattern, mean abundance of the echinodermata decreased from 3212 whereas the mollusca were dominant in terms of biomass. Like ind. 500 m-2 to 145 ind. 500 m-2, mainly due to the decline of the abundance the biomass decreased from 1999 to 2001, but the brittle star Ophiura albida (2913 ind. 500 m-2 in 1999 to increased towards 2002 (1229 g 500 m-2) and 2004 (1199 g 13. ind. 500 m-2 in 2004). In contrast, the opposite temporal 500 m-2). The MDS reveals a similar pattern to Box A until pattern was found for crustaceans mainly caused by increasing 2002, the communities observed in the following years being abundance of the swimming crab Liocarcinus holsatus, which less dissimilar than in Box A (Fig. 41). The overall similarity of was found in 1999 with a mean abundance of 5 ind. 500 all samples taken in this Box reached 76%, which was higher m-2 and 2004 with 116 ind. 500 m-2. The multidimensional than in the other Boxes (Neumann 2006). Biomass and abun- scaling (MDS) plot confirms the temporal change in- com dance in Box L increased from 1999 to 2004 with maximum munity structure due to the changes in species as described values up to 854 ind. 500 m-2 and 1522 g wet weight 500 m-2, 61

and 2004, infauna was sampled in the Boxes for the EU-Proj- Stress: 0 2003 ect “Managing fisheries to conserve groundfish and -inverte brate species diversity (MAFCONS)”, which studied the effect 2001 of fishing on the benthic diversity (Robinson 2003). As part 2004 of MAFCONS a. small-scale study on the fishing effects on the infauna in Box A showed that univariate parameters such 1999 2002 as mean abundance and mean biomass were not significantly correlated to differences in fishing effort estimated by VMS- data of the Dutch beam-trawl fleet. However, more generally Sieben (2006) found a significant relationship between the 2000 community structure of infauna and fishing effort. Prelimi- Box A nary analyses indicate that small-scale differences in sediment structure and the underlying hydrodynamic regime influenced the small-scale spatial patterns of infauna communities more 2001 Stress: 0 than differences in fishing effort.

Linking stomach contents to prey availability 2002 In 1999, the infauna was sampled simultaneously to the 2004 1999 stomach contents of various demersal fish species in order to 2003 study the food preferences of fish Hinz( et al. 2005). Hinz et al. (2005) found temporal changes in dab condition, percentage of empty stomachs and numbers of ingested prey. In 2000 Box C particular in the winter period 2000 – 2001 dabs were in poor condition and prey items were only rarely found in stomachs. Similarly prey availability decreased in the environment while 2001 Stress: 0 the abundance of dab increased. Thus, temporal changes in the nutritive state were partly thought to be attributed to density-dependence effects. The stomach composition of dabs was mainly dominated by Pariambus typicus and Ophiura albida 2002 while in the winter period only O. albida made a significant contribution to the content. Analysis of prey characteristics in- eschweizerbartxxx sng- dicated that only prey densities in the environment significant- 2004 1999 ly influenced prey choice in dab, while other characteristics such as the position of the prey in the habitat, its palatability or mobility did not have significant effects (Fig. 42). The feed- 2003 ing strategy of dab seemed to be truly opportunistic although Box L there were trends that suggested that buried living fauna was less likely to be ingested which was also observed by previous studies. Fig. 41: Multidimensional scaling (MDS) plots based on fourth-root- transformed epifaunal abundance data for the Boxes A, C and L. Seabirds respectively. After 2002, abundance and biomass decreased to about the level of 1999 (Fig. 40). Again, the echinodermata Introduction dominated the temporal pattern, with the sea urchin Echi- nus acutus and the sand star Astropecten irregularis being the It is well known that several species of seabirds feed on dis- dominant species. The MDS plot revealed that the community cards and offal from fishing vessels throughout many parts of structure in 2004 was more similar to that in 1999 than the the world’s oceans. Experimental studies in the 1980s around previous years (Fig. 41) (Neumann 2006). The data analysis the Shetland Islands have demonstrated in detail which species of the epifaunal communities in the Boxes B, D and M is still participate, to what extent the discharged fish is taken by sea- in progress. birds and that competition occurs among the scavengers (Fur- ness et al. 1988). These studies were transferred to the whole North Sea and further developed in the 1990s (e.g. Garthe & Small scale variability of infaunal communities Hüppop 1994, Garthe et al. 1996), also partly in an EU project (Camphuysen et al. 1995). In this chapter, the methodolo- The infauna study revealed a high small scale variability of gy, some results and major conclusions are reviewed. Although infaunal communities in each Box due to variability in sedi- information on seabird distribution in general would have ment structure as well as patchiness due to biological interac- been very valuable, too, this was not possible in the context tions and competition (Gröning 2005). In the summers 2003 of the GSBTS surveys, when fishing operations were carried 62

Fig. 42: Mean log10 abundance of prey species found in stomachs for the three categorical macrofauna characteristics: a) position in the environment, b) mobility and c) palatability. d) Relationship between macrofauna log10 abundance in the environment and log10 abundance in dab stomachs (Hinz et al. 2005). eschweizerbartxxx sng-

out almost the whole time, as seabirds are attracted by fishing discarding. These subsamples consisted usually of roundfish, activities and such counts can only be done independent of flatfish, offal and benthic invertebrates. However, they were fishing activities (see discussion inGarthe & Hüppop 1994). not always representative with respect to both age and length composition of the general discards although no fish species or length class was favoured overall. Discard samples were Methods identified to species, measured to the nearest cm in length and thrown overboard singly from the stern of the vessel. Attempts Studies of seabirds feeding on discards and offal were car- by seabirds to pick up and swallow the item were recorded, ried out during several WALTHER HERWIG cruises since noting the species and (if possible) age class of the bird and 1991. While periods when the research vessel was steaming whether the item was consumed, dropped or stolen by other were used to assess seabird distribution independent of fishing birds. If it was stolen or dropped, the same notes were made activities (e.g. Camphuysen et al. 1995), fishing periods were for the second and subsequent birds, until the item was finally used to study which seabirds species were attending the vessel lost (sunk) or swallowed. Experimental discarding was usually during the fishing process and to what extent discards were conducted when vessels were stationary as the net was lifted used. Some of the latter studies were carried out during regular and brought on deck, during standard discarding, and also oc- IBTS cruises (e.g. Garthe & Hüppop 1994), while GSBTS casionally during towing or steaming. cruises were particularly useful because of intensive fishing and During each haul the number of birds attending the ves- thus comprehensive data sets. sel (“ship-followers”) was estimated. Ship-followers are defined So-called discard experiments were carried out to quan- as all those birds which were present at least for a short time tify utilization of discards and offal by seabirds and to study behind the vessel from setting out of the net until the end of their feeding behaviour upon such food. At least two observers processing of the haul. Birds passing the ship by were ignored. participated in each of the counts and experiments. For the For calculations, the highest number of individuals per species experiments, fresh subsamples of the catches were taken for and age class counted during that period was used. 63

Table 13: Number of ship-followers attending FRV “Walther Herwig III” during fishing operations in four Boxes in May-June 1994. For each species the mean (and range) is given. Each count refers to a haul and gives the maximum number of ship-followers per species (see Methods).

Box D Box C Box B Box A number of counts (= hauls) 13 17 25 16

Northern fulmar 1405 45 435 13 (Fulmarus glacialis) (80 – 2500) (8 – 91) (50 – 1600) (2 – 50)

Northern gannet 149 0.2 31 0.7 (Sula bassana) (42 – 310) (0 – 1) (0 – 180) (0 – 5)

Great skua 0.9 0 0.3 0 (Stercorarius skua) (0 – 4) (0) (0 – 2) (0)

Black – headed gull 0 0.3 0 0.1 (Larus ridibundus) (0) (0 – 3) (0) (0 – 1)

Common gull 0 0.7 0.1 0.1 (Larus canus) (0) (0 – 5) (0 – 1) (0 – 1)

Lesser black – backed gull 14 13 10 154 (Larus fuscus) (5 – 22) (0 – 40) (0 – 42) (0 – 660)

Herring gull 0.2 0.1 4 5 (Larus argentatus) (0 – 1) (0 – 1) (0 – 24) (0 – 45)

Great black – backed gull 31 4 4 4 (Larus marinus) (10 – 56) (0 – 10) (0 – 15) (0 – 25)

eschweizerbartxxx sng- Black – legged kittiwake 99 3 26 23 (Rissa tridactyla) (11 – 203) (0 – 9) (5 – 100) (3 – 62)

Arctic tern 0 0.1 <0.1 0 (Sterna paradisaea) (0) (0 – 1) (0 – 1) (0)

To derive information on foraging success of seabirds at- ample of the varying abundance of all seabirds attending the tending the fishing process, a foraging success index was cal- boat at different parts of the North Sea, Tab. 13 shows data for culated (for details see Garthe & Hüppop 1998a). Similarly, a four different Boxes sampled in May/June 1994. robbery index was developed to assess interspecific interactions when handling discarded fish Garthe( & Hüppop 1998a). Proportion of discarded fish consumed

Results There are inter-specific differences in discards types taken by birds. The proportion of discarded fish consumed by birds Species and abundance of ship-followers varied between 7 and 96 %, depending on the fish species and their lengths (Garthe & Hüppop 1994). Gadidae and Clupei- During eight IBTS/GSBTS surveys, a total of 22 species dae were taken preferentially. Almost all Norway pout (Trisop- were found to attend the fishing research vessel, of which the terus esmarki) and poor cod (Trisopterus minutus) were eaten most common ones are mentioned in this paper. As an ex- while herring (Clupea harengus), lesser argentine (Argentina 64

(a) Atlantic herring

100%

80%

60%

40%

proportion consumed/lost 20%

0% <10 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 >30 length (cm)

northern gannet large gulls kittiw ake others lost

(b) Haddock

100%

90%

eschweizerbartxxx sng- 80%

70%

60%

50%

40%

30%

proportion consumed/lost 20%

10%

0% <11 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 >34 length (cm)

northern gannet large gulls kittiw ake others lost

Fig. 43: Proportion of (a) Atlantic herring (n = 2696) and (b) haddock (n = 3546) of different lengths thrown over board during experimental discarding (n = 122 experimental sessions) and consumed or lost by seabirds in the North Sea (category “lost” = discards not taken by seabirds). Seabird species were summed into four categories: northern gannet; large gulls (lesser black-backed, herring and greater black-backed); black- legged kittiwake; other species. Only lengths with n ≥ 8 fish offered are shown. 65 sphyraena), whiting (Merlangius merlangus) and haddock (Me- There was also a broad interspecific overlap in prey utilization. lanogrammus aeglefinus) were marginally less eaten. Overall, 85 Some of the variability in the mean lengths and particularly % of all roundfish and 8 % of all flatfish offered were taken by the maximum length of fish chosen by different ship-following birds (Garthe & Hüppop 1994). bird species can be explained by bird morphometrics (Garthe & Hüppop 1994). High percentages of almost all roundfish species were con- Choices of fish length sumed by seabirds. Most of the differences between fish species can be explained by their different natural lengths (and Depending on fish species, seabirds utilized length classes thus the ease for seabirds to swallow them) and their different to different extents (Fig. 43). The proportions of discards con- energy density (Garthe & Hüppop 1994, Camphuysen et al. sumed fell with increasing fish length in experimentally dis- 1995). In contrast to roundfish, especially clupeids and gadids, carded haddock, but not in herring. The proportions of fish flatfish were hardly taken because they are difficult to handle lengths differed substantially between seabirds species/groups, (Hudson 1989, Camphuysen 1994). Since flatfish clearly most obvious for black-legged kittiwake (Rissa tridactyla) at the dominate the discard fraction of beam trawl fisheries, seabirds lower end and northern gannet (Sula bassana) at the high end have to select carefully the few roundfish or have to take the (Fig. 43). less favoured flatfish. The opposite holds true for pelagic and gadid fisheries: there, the amounts of discards are less, but the type of discards available is more appropriate for seabirds. Foraging success Despite the quite different conditions, the figures obtained on research vessels come close to the proportions of discards Scavenging species differed significantly in their foraging consumed by birds at Scottish and Dutch commercial trawlers success (Garthe & Hüppop 1998a). Split by foraging success (Hudson & Furness 1988, Camphuysen 1994) or at shrimp index, Tukey Multiple Comparisons revealed that the northern trawlers in the German Wadden Sea (Berghahn & Rösner gannet was separated from all other species as the most suc- 1992). There is evidence that discard experiments on board cessful species. Foraging success index and body dimensions of commercial trawlers tend to result in slightly lower propor- the birds did not correlate significantly; e.g., black-legged kit- tions of discards consumed when compared to fishery research tiwakes were much more successful than expected from their vessels in the northern North Sea although this did not seem body mass.

Kleptoparasitism

Stealing fish from other birds was frequent during discard eschweizerbartxxx sng- experiments. Fig. 44 demonstrates all interactions observed between the seven most common ship-following species. Northern fulmar (Fulmarus glacialis) was the species with most interactions, stealing many fish from black-legged kittiwakes and loosing many fish to northern gannets and large gulls (Garthe & Hüppop 1998a). The robbery index was highest for the northern gannet (13.9, values not shown in figure), followed by the greater black-backed gull (Larus marinus; 6.7) and the great skua (Stercorarius skua; 4.5). Northern fulmar (0.4), black-headed gull (Larus ridibundus; 0.2) and black- legged kittiwake (0.1) had the lowest values. Interestingly, the species with the highest values (northern gannet, greater black-backed gull, great skua) hardly ever stole fish from each other (Fig. 44). Overall, the kleptoparasitic interactions did not occur randomly between the species involved: the differences between fish stolen and fish lost were highly significant. The bird species order obtained by the robbery index can be well explained by both body mass and body length (Garthe & Hüppop 1998a).

Discussion

Selection and consumption of discards by seabirds Fig. 44: Quantification of interactions between seven bird species. Arrow thickness is equivalent to the number of fish stolen (from Nearly all length classes of offered fish were utilized by dashed = 1 – 2 interactions to the broadest arrows = more than 100 ship-following seabirds due to the broad spectrum of bird sizes interactions), the arrow tips point to the species which stole the fish. and feeding techniques (Garthe & Hüppop 1994, 1998a). [Figure taken from Garthe & Hüppop 1998a] 66 to be the case in the southern North Sea and the western Baltic on board research vessels when taking into account meth- Sea (Garthe 1993, Garthe et al. 1996, Garthe & Scherp odological aspects (Garthe et al. 1996, Garthe & Hüppop 2003). Generally, amounts of discards and frequency of dis- 1998b). The results found by these studies have contributed to carding varies substantially between the different types of fish- several aspects of seabird ecology and marine ecosystem con- eries (Camphuysen et al. 1995). siderations. In spite of some methodological biases the results However, experiments on research vessels will mostly lead can be used to assess utilization of fishery waste by seabirds to an overestimate of consumption percentages because items both qualitatively and (semi-) quantitatively. Studies on re- were mostly discarded one after the other and not only when search vessels are furthermore considered to be a very useful normal discarding takes place. Significant differences in the tool for comparisons between seasons, areas, and over years consumption percentages between single-fish and multiple- to assess possible long-term changes in seabird communities, fish experiments were revealed for some fish species. In order seabird feeding behaviour and seabird-fishery interactions. to correct for this, Garthe & Hüppop (1998b) derived correction factors to be used for large-scale calculations of discard consumption by seabirds. By applying such correction factors The importance of spatial scales to the discard experiments, large-scale calculations on the to- tals of discards consumed by seabirds can be performed when Spatial scales: the relevance of GSBTS survey results for discard availability is sufficiently well-knownGarthe ( et al. interpreting large-scaled abundance and distribution 1996). data from the IBTS

Introduction Foraging success, kleptoparasitism, feeding techniques and competition in scavenging seabirds The problem of scale is an important issue in theoretical ecology (O’Neill 1989, Wiens 1989). A thorough discussion The results demonstrate that scavenging seabird species within the context of Wadden Sea research is provided by Jax utilize discards provided by fisheries throughout the whole et al. (1993). The term scale is used in different ways which North Sea to very different degrees. Whereas the seabird spe- must be clearly distinguished (Zauke & Jax 2001) to describe: cies order obtained by the robbery index can be well explained (1) levels of observations (individual, population, community, by bird body dimensions, the foraging success index cannot guilds, ecosystems) which are in turn dependent on the theo- be explained in this way. Hence, it is obvious that the species’ retical approach under consideration (reductionistic, typologi- techniques of feeding on discards differ in their success. For cal or systemic); (2) taxonomic coverage of a study (taxonomic this reason Garthe & Hüppop (1998a) discuss the different scale); (3) types of observations in a statistical sense (categori- foraging behaviour employed by various species while feeding cal, discrete or continuous data), and finally (4) temporal or on discards. They conclude that the species with the largest spatial scales of a study (spatial grids or sampling intervals). body dimensions, northern gannet, and the specieseschweizerbartxxx sng- with the Further on only spatial scales will be considered. apparently highest flight manoeuvrability, black-legged kitti- Grain and extent of an ecological investigation define the wake, seem to exhibit the best prerequisites for exploiting dis- limits of interpretation of the results, the grain being given by cards. By contrast, northern fulmars forage more successfully the resolution of the spatial grid. For smaller scales no state- on offal rather than discards outcompeting species such as her- ments are possible. The extent determines the area to which ring gull (Larus argentatus) by their high abundance (Hudson interpretations (e.g. the coexistence of species) can be extrapo- & Furness 1989). lated. Too extensive extrapolations presume that ecological Foraging success is also heavily influenced by interactions. processes or patterns are scale-invariant, which is very ques- Kleptoparasitism is an important feeding technique in skuas tionable. Roughgarden et al. (1988) distinguished four levels and gulls (Furness 1987). Camphuysen et al. (1995) found of scale in an ecological field study on larval recruitment in a in feeding experiments that 17 % of all roundfish and 22 % of rocky intertidal. The authors demonstrated that only consider- all flatfish were handled by more than one bird. Most of these ation of all these levels could provide a complete picture of the events can be attributed to stealing fish from each other. The ongoing processes. number of interactions was particularly high for large fish since In the GSBTS, consideration of spatial scales must be these are most difficult to swallow rapidly. Since the robbery taken into account in order to set GSBTS survey data into index is almost perfectly correlated with body measurements perspective with large-scaled fisheries studies as in the IBTS in of the scavengers it is obvious that relatively weak species such the North Sea. as black-legged kittiwake but also northern fulmar and lesser black-backed gull (Larus fuscus) do better by avoiding these interactions (Garthe & Hüppop 1998a). Geostatistical aspects

In geostatistical analyses of any ecological study the scale Conclusions dependence is taken into consideration. Small-scaled variability is, for example, related to the variogram model (nugget effect) Although many quantitative aspects of the study of discard as has been shown in section “Geostatistical evaluation of GS- utilization by seabirds are affected by the design of the experi- BTS data”, p. 43). However, this aspect is also relevant at larger ments, a reasonable simulation of the impact of commercial scales. As shown above, a geostatistical approach was used to fisheries appears possible by conducting discard experiments investigate differences in the spatial distribution patterns of 67 herring, cod, dab, haddock and whiting in relation to habitat median and the IBTS haul showed different, even opposite associations at different spatial scales in the northern North trends. These findings were confirmed by correlation analysis Sea (Stelzenmüller et al. 2005a). This study shows that the (Tab. 14). In 6 of 11 possible cases, the correlation between magnitude of differences in the spatial dimension at both sur- the Box and the IBTS data set was significant. The highest cor- vey scales (“Box D” vs. an extended “Box D” with 30 × 30 km) relation was observed for cod in Box A and whiting in Box D, were sufficient to develop a different spatial structuring of fish while the poorest correlation was found for cod in Box D. The density in both cases. Differences between the spatial model- correlation of biomass trends for whiting was significant in all ling results for both scales were most pronounced for those areas. Overall, the median biomass derived from more than 20 fish species that display a strong association with water depth. hauls in an area of 10×10 nautical miles (Boxes) and from 12 Thus, habitat associations were found to be more pronounced hauls or less in an area of 60×60 nautical miles (4 surrounding at a larger survey scale, indicating that for some species a great Statistical Rectangles) did not follow the same trend (Fig. 46). proportion of variability, calculated from large-scaled survey The correlation analysis (Tab. 15) only showed significant cor- designs (like IBTS), could be due to species-specific aggrega- relations for cod in Box A and D. In some cases, e.g. haddock tion patterns. The influence of a patchy distribution of fish, and whiting in Boxes B and D, the median biomass derived which have a strong habitat association, on the calculation of from the large-scale IBTS data series was consistently lower classical abundance indices was found to be marginal at the than the median biomass derived from the small-scale Box spatial scale of GSBTS Boxes. Conversely, one can expect an data. The within-year range of data inside the Box, however, increasing influence of the spatial distribution pattern of fish was of the same magnitude as the within-year range in the on classical abundance estimates with increasing survey scale, IBTS data in the 4 rectangles, or even higher. making a geostatistical approach necessary to derive unbiased This study suggested that the chance of a randomly chosen results. single haul provides a biomass estimate close to the mean bio- Moreover, Petitgas (2001) applied geostatistical tools to mass of all hauls taken in the area is relatively high and that it analyse the level of coherence of variances between GSBTS is sufficient to take one haul in these areas to get a reasonable and IBTS survey data for cod of age 2 in the second quarter good indication of biomass changes over the years. Thus, the of the years. The small-scaled Box surveys revealed the same sampling effort currently applied to the IBTS appears to be variance as the large-scaled IBTS surveys. Therefore, simula- sufficient in these cases, provided that the focus is on inves- tions were conduced to determine the appropriate sampling tigating changes in biomass over time. The trends in median scheme which allows estimations of the true level of variance biomass, calculated from all hauls in the small Boxes and the from a fish population with a large-scaled spatial pattern and surrounding 4 Statistical Rectangles, were less correlated. One high local heterogeneity. Intensive sampling in a few locations reason for this could be that there are real differences in bio- would result in an over-estimation of population densities, mass between the small and the large area. The goodness-of-fit while allocating more finely resolved sampling effort along a of the observed trends was shown to be influenced by the de- trend led to a lower bias and a better precision of the popu- gree of within-year variation in biomass data. In general, the lation estimates (reduction of standard deviations ofeschweizerbartxxx process sng- small-scale variation was found to be as high as the large-scale mean of up to 50%). variation. Since the large-scale data were obtained by taking just a few hauls within a large area and considering the high variation observed on a small scale, one would expect the large- Comparison of biomass estimates obtained with scale data to be more variable than the small-scale data. On GSBTS and IBTS the other hand, the small-scale data are much more likely to be affected by small-scale fish aggregations than the large-scale Stransky (1998) investigated the differences of biomass data. Therefore, the high small-scale variation is likely not to indices of cod, haddock and whiting derived from GSBTS sur- be apparent in the large-scale data. Thus, the variability of fish veys (1986 – 1997) and IBTS surveys (1991 – 1996). As part of biomass in a small area appears to be underestimated if we this study, the median biomass determined from all hauls in sample in a larger surrounding area to assess between-years each of the Boxes A, B, C and D, was compared with the bio- changes in biomass on a small scale. mass determined from the single haul within the Box that was chosen as an IBTS haul, or – where not required - as a simulated IBTS haul. Secondly, the spread of variation around the Analysing predator-prey interactions median biomass, estimated for all hauls in the Boxes, was com- at large and small scales pared with the spread of variation around the median biomass, estimated for all IBTS hauls in the four Statistical Rectangles The distribution of North Sea fish stocks and their preda- surrounding each Box. The degree of correlation between these tor-prey interactions are traditionally analysed on large spatio- time series was analysed using the Spearman rank correlation temporal scales: in the entire North Sea area, typically 1 – 2 coefficient, the significance of which was tested by a two-tailed trawl hauls are made per quarter and ICES Statistical Rect- t-test. angle (approx. 55 km × 55 km; ICES 2006). From these Inter- In general, the single IBTS haul followed the same trend national North Sea Bottom Trawl Surveys (IBTS) it resulted, as the median of all Box hauls (Fig. 45). There was, however, that once-in-a-while a trawl haul caught extremely high num- no consistently lower or higher biomass observed in one data bers of gadoid predatory fish, whereas average catch-per-unit- series opposed to the other. For cod in Box A, haddock in Box of-efforts (CPUE) were much lower (ICES IBTS Database). B and for whiting in Box D, both trends seem to match each Similarly skewed distributions were observed in gadoid preda- other well. In other cases, e.g. cod in Boxes B and D, the Box tor stomach contents that were sampled on the IBTS cruises 68

eschweizerbartxxx sng-

Fig. 45: Trends in mean biomass of cod, haddock and whiting in the Boxes (solid lines) and biomass values of reported or simulated IBTS hauls (dotted lines). Biomass axes are on a fourth root scale. 69

Table 14: Spearman rank correlation coefficients (r), and significance levels (p), between the medians of cod, haddock and whiting biomass derived from all hauls in the Boxes and from the reported or simulated IBTS hauls lying within a Box. * indicates a significance level of < 0.05, ** indicates a significance level of < 0.01. (–) indicates that sufficient data were not available to allow a correlation analysis.

Box A Box B Box C Box D Species (n = 11 years) (n = 11 years) (n = 11 years) (n = 12 years) r p r p r p r p

Cod 0.945 0.000** 0.373 0.259 0.364 0.272 -0.014 0.966

Haddock (–) (–) 0.825 0.002** 0.337 0.311 0.392 0.208

Whiting 0.852 0.001** 0.673 0.023* 0.770 0.006** 0.916 0.000**

during the years 1981 and 1991, while in some hauls high Generally, in cases where stomach samples were obtained stomach contents were associated with high predator densi- from more than 1 station during the third quarter 1991 in ties (Daan 1989; Hislop et al., 1997). The lack of any infor- an ICES Statistical Rectangle, the full range from very similar mation from the small-scale neighbourhood and the limited to very different mean stomach content weights was obtained sample size of only 5 or 10 pooled stomachs per size group (Fig. 47). Further, only a small number of stations revealed (Robb 1991) made it impossible to analyse the nature of such high stomach content weights, low stomach content weights “outlier” situations in greater detail, and hence no mechanis- seemed to be the rule rather than the exception (Tab. 16). A tic understanding of these predator prey interaction could be more in-depth analysis (not presented here) revealed that high derived. Due to the pooling of samples it was not even clear stomach content weights generally originate from high frac- whether a single predator had taken the observed high prey tions of fish prey in the diet of the predator. numbers. In the situation where multiple hauls in an ICES Statistical Nevertheless, when average stomach contents and diet Rectangle in the third quarter 1991 resulted in similar (usually compositions of specific predator species and age classes are low) values, it may be argued that they are representative for calculated as input data for the single-area North Sea Multi the entire 30 × 30nm Statistical Rectangle and quarter of the Species Virtual Population Analysis (MSVPA; ICES 1997), year. However, the cases were multiple hauls provided very dif- such “feeding hot spots” are quite influential, since theeschweizerbartxxx predator sng- ferent values demonstrate that the local variability in space and numbers are used as a weighting factor during the averaging. over the period of a quarter can be substantial. To down scale the effects of such extreme situations, the square From these results a hypothesis that can be formulated is root of the predator numbers is therefore used as the weight- that a station with low stomach contents is representative for ing factor (Daan 1989). Hence the question arose at which a bigger area and a larger time interval than a station with a spatial and temporal scale such local aggregations of predators high stomach content. This hypothesis can only be tested with on small prey fish in the North Sea occur, and whether a single small-scale studies resolving the neighbouring areas of a single survey station in an area of such an aggregation is representa- station. tive for such a feeding situation. One of the key questions of the small-scale investigations The GSBTS offered the ideal platform to analyse the key was for which dimensions in time and space a single trawl processes that dominate local predator-prey interactions (see station is representative, and whether the representativeness section “Predator-prey interactions fish-fish”, p. 49), and to of single stations varies with the feeding situation. From the answer the key question of the small-scale investigations: large-scale analysis a more specific hypothesis was formulated: – At which spatial and temporal scale do local aggregations a station with low stomach contents is representative for a of fish predators on small prey fish in the North Sea occur larger area and a longer time interval than a station with a high – For which dimensions in time and space is a single trawl stomach content. station representative? These questions were analysed by first using all feeding situ- – Does the representativeness of single stations vary with the ations in which whiting (25 – 30cm) was a dominant predator feeding situation? for a categorization/ categorisation into low, medium and high When analysing key processes determining predator-prey intensity situations, according to their mean stomach content interactions it is useful to compare the insights gained from weights. As a measure for comparison the 1991 third quarter large- and small-scale investigations. North Sea average stomach content weight of 2.76g was taken As the small-scale investigations presented in this review (Tab. 16). All surveys with mean stomach content weights be- are focussing on whiting (25 – 30cm) as the predator, the same low 2g were categorised as low (n = 9), between 2 – 3g as me- species and size class was chosen as an example for a large-scale dium (n = 1) and above 3g as high (n = 2) intensity situation study. The data originate from the third quarter of the interna- (Tab. 17). tionally coordinated 1991 North Sea stomach sampling survey In the next step the station specific mean stomach content (Hislop et al. 1997). weights of the investigated 9 Box surveys were used for a boot- 70

eschweizerbartxxx sng-

Fig. 46: Biomass of cod, haddock and whiting in the 4 Box areas (filled symbols) and in the 4 ICES Statistical Rectangles surrounding each Box area (transparent symbols). Biomass axes are on a fourth root scale. 71

Table 15: Spearman rank correlation coefficients (r), and significance levels ,(p) between the annual medians of cod, haddock and whiting biomass in the Boxes and in the surrounding four ICES Statistical Rectangles. * indicates a significance level of < 0.05, ** indicates a significance level of < 0.01. (–) indicates that sufficient data were not available to allow a correlation analysis.

Box A Box B Box C Box D Species (n = 5 years) (n = 5 years) (n = 5 years) (n = 4 years) r p r p r p r p

Cod 0.886 0.019* 0.314 0.544 0.086 0.872 0.998 0.000**

Haddock (–) (–) 0.543 0.266 0.373 0.449 0.371 0.468

Whiting 0.600 0.208 0.605 0.182 0.543 0.266 0.531 0.292

Table 16: 1991 North Sea IBTS sampling: whiting (25 – 30cm) stomach content weights [g]. North Sea wide statistics of station means. A sample usually contained a number of pooled stomach samples, so the number of (mainly pooled) stomachs is higher than the number of samples.

Quarter 1 Quarter 2 Quarter 3 Quarter 4

N stomachs 1262 3422 3084 2341 N samples 145 273 225 209 Mean 1.25 2.73 2.76 3.21 Median 0.85 2.08 1.79 2.59 Standard Deviation 1.71 2.42 2.87 2.88 CV % 137.22 88.72 104.02 89.61 Minimum 0.00 0.00 0.00 0.00 Maximum 11.25 13.48 20.38 16.57 Percentile 5 0.00 0.19 0.16 0.15 Percentile 10 0.01 0.43 0.38 0.27 eschweizerbartxxx sng- Percentile 25 0.15 0.97 0.98 1.23 Percentile 75 1.67 3.85 3.46 4.28 Percentile 90 3.06 5.97 6.45 6.85 Percentile 95 4.08 7.35 8.24 9.52 strap exercise. The stations of the 9 Box surveys were re-sampled Generally, the detection probability was significantly in- 500-times (with replacement) and from these 500 stations the creasing linearly with the true mean stomach content weight in distributions of mean stomach content weights were obtained. the survey area (Fig. 48), i.e., the higher the feeding intensity From these distributions the probabilities to match the true in the sampled situation, the higher the chance that a single Box survey mean weight of the stomach contents (plus/minus random station is sufficient to capture the area-wide average. x%) when conducting a single random station was calculated, Every single gram increase in the average stomach content assuming a normal distribution. Detection probabilities were weight enhances the detection probability by approx. 5%. calculated for the true mean plus/minus 10%, 25% and 50% The detection probabilities follow an exponential function (Tab. 17). of the coefficient of variation of the station’s mean stomach To reveal any potential relations between the detection content weights (Fig. 49), i.e., the more heterogeneous the sta- probabilities and the level of the feeding situation the detec- tions in a survey area, the lower the probability to capture the tion probabilities were plotted versus the true area-wide mean true area mean by sampling a single random station. stomach content weights (Fig. 48), as well as versus the co- The coefficients of variation of the station’s mean stomach efficient of variation of the station‘s mean stomach content content weights in a survey area decrease exponentially with weights (Fig. 49). the area wide mean stomach content weight (Fig. 50). This The average probability to match the true Box-area-wide means that feeding situations with a high intensity, i.e., high mean stomach content weight plus/minus 10% by conducting average stomach content weights, are more homogenous than a single random station was approx. 10% (range: 6 – 25%), low feeding situations. increasing to approx. 25% (range: 15 – 57%) for plus/minus Finally, we can answer the key questions for which dimen- 25% and further on to 46% (range: 30 – 88%) for plus/minus sions in time and space a single trawl station is representa- 50% (Tab. 17). tive, and whether the representativeness of single stations vary 72

eschweizerbartxxx sng-

Fig. 47: Whiting (25 – 29.9 cm) average stomach content weight [g] of all prey types by haul, third quarter 1991. Data originate from the ICES 1991 International Stomach Sampling. Note that some bars extent into the upper next grid cell.

with the feeding situation. The answer from the small-scale mean plus/minus 50%) for the area of a Box (10 × 10 nm) in investigations of feeding interactions is that a single station homogenous high intensity feeding situations as encountered can be quite representative (90% chance to capture the true in 1992 in Box D, but also that a single station can be hardly 73

Fig. 48: Detection probabilities of true area-wide mean stomach content weights (+/- 10%, 25%, and 50%, respec tively) of whiting (25 – 29.9 cm), in 9 Box surveys as a function of the true area-wide mean stomach content weights. Linear regression for probability of detecting the true mean +/- 25%.

100

90 y = 71.684e-0.0123x R2 = 0.946 80

50 eschweizerbartxxx sng-

Probability to detect mean + / - X % 10

0 0 20 40 60 80 100 120 140 CV data

Fig. 49: Detection probabilities of true area-wide mean stomach content weights (+/- 10%, 25%, and 50%, respectively) of whiting (25 – 29.9 cm) in 9 Box surveys as a function of the coefficients of variation [%] of the station’s mean stomach content weights in each Box survey. Exponential regression for probability of detecting the true mean +/- 25%.

representative for the area of a Box when the feeding situation Conclusions is heterogeneous, which seems to be the case especially in low feeding situations as encountered with WH190 in 1997 Box The key question of the small-scale investigations was for D (30% chance to capture the true mean plus/minus 50%). which dimensions in time and space a single trawl station is Thus, the hypothesis which evolved from the large-scale analy- representative and whether the representativeness of single sta- sis, that a station with low stomach contents is more represen- tions varies with the feeding situation. Generally, encounter tative for a bigger area and a longer time interval than a station processes between predator and prey seem to occur rather on with a high stomach content, has to be rejected. the scale of the individual predator than on the scale of the 74 36 low 530 0.52 0.22 0.63 0.00 3.09 0.02 0.04 0.15 0.82 1.31 1.90 0.56 0.67 6.12 15.21 29.87 123.08 120.86 WH 190 Box D + o.D Box 7 low 108 0.62 0.45 0.52 0.11 1.44 0.11 0.11 0.15 1.09 1.44 1.44 84.38 WH 190 o. Box D o. Box

29 low 422 0.49 0.22 0.67 0.00 3.09 0.01 0.03 0.16 0.55 1.26 2.39 0.49 0.64 6.17 15.34 30.11 135.37 130.19 Box D Box WH 190 22 low 351 0.70 0.36 0.75 0.04 2.58 0.04 0.05 0.16 1.07 2.21 2.53 0.70 0.74 7.49 18.58 36.17 Box B Box 107.32 105.69 WH 188 24 low 496 1.23 0.88 1.02 0.19 3.63 0.21 0.27 0.42 1.71 2.91 3.47 1.22 0.97 82.50 79.20 10.14 24.98 47.58 WH 188 Box D + o.D Box 2 29 low 1.02 1.02 1.06 0.26 1.77 0.26 0.26 0.26 1.77 1.77 1.77 104.60 WH 188 o. Box D o. Box

22 low 467 1.25 0.88 1.04 0.19 3.63 0.21 0.27 0.49 1.81 2.94 3.53 1.36 1.06 9.35 82.75 77.94 23.11 44.32 Box D Box WH 188 34 low 0.85 0.36 1.03 0.06 4.60 0.09 0.13 0.20 1.08 2.61 3.40 0.80 0.98 6.87 1063 17.07 33.37 122.17 122.07 WH 174

eschweizerbartxxx sng- Box D + o.D Box 6 236 2.67 2.61 1.15 1.12 4.60 1.12 1.12 1.86 3.40 4.60 4.60 43.16 medium WH 174 o. Box D o. Box

30cm) stomach content weights [g] from 12 Box surveys. outside o.: the area of Box D, i.e., the extended survey area south-west of – 28 low 827 0.45 0.33 0.39 0.06 1.55 0.08 0.12 0.19 0.59 1.11 1.55 0.47 0.40 9.00 86.56 84.98 22.25 42.80 Box D Box WH 174 28 555 high 3.10 2.46 1.95 0.65 0.81 1.34 1.99 4.05 5.75 8.20 3.06 1.94 62.68 10.11 63.17 12.74 31.14 57.72 Box B Box WH 174 23 690 high 7.31 6.40 2.36 4.50 4.51 4.65 5.26 9.81 7.51 2.33 32.29 11.06 10.80 11.01 30.96 24.59 56.63 88.26 Box D Box WH 124 Descriptive Descriptive statistics and detection probabilities of whiting (25

Table 17: Table 1997. WH 190: November, 1997; WH 188: September, 1996; WH 174: July, 1992; WH 124: May-June, D. Box Cruise Area situation Feeding N stomachs N stations [g] Mean [g] Median Deviation Standard CV [%] [g] Minimum [g] Maximum 5 Percentile 10 Percentile 25 Percentile 75 Percentile 90 Percentile 95 Percentile Bootstrapped mean [g] SD of bootstrap mean CV [%] of bootstrap to detect the mean + / - 10 % Prob. to detect the mean + / - 25 % Prob. to detect the mean + / - 50 % Prob. 75

160

140 y = 119.56e-0.1854x R2 = 0.877 120

100

CV Data 60

0 0.00 1.00 2.00 3.00 4.00 5.00 6.00 7.00 8.00 Mean stomach content weight [g]

Fig. 50: Coefficients of variation [%] of the station’s mean stomach content weights of whiting (25 – 29.9cm) in each Box survey as a function of the true area-wide mean stomach content weights of each of the 9 surveys. area of a Box. These apparently random encounters in space scientific information. The specific design of high-intensity and time lead to a high variability in mean stomach content sampling at the small spatial and temporal scale enables pro- weights of individual predators as well as of station averages. cess studies which can not be conducted in the frame of rou- As long as rare encounters dominate, this feeding situation tine large-scale surveys, as e.g., can be characterised by low average stomach contents coupled – distribution and diurnal migration of fish with a high variability at the small spatial and temporal scale. – predator-prey interactions as consumption, diet selection According to the comparative analysis of the feeding situationseschweizerbartxxx sng- and aggregative behaviour (Tab. 17) this seems to be the rule rather than the exception. – characterisation of fish habitats with respect to biotic and On the other hand, a high density prey patch which is big abiotic parameters enough to persist over a longer period of time, like a cohort – small scale variability of physical and biological parameters of sandeel at a sandeel bank, can make a feeding situation of in general a larger area quite homogenous. This could happen by an ag- – weather effects on fish behaviour and associated gear catch- gregative response of the predators (as whiting in the 1996 Box ability D study, potentially combined with a random dispersal of sati- – comparative fishing experiments for gear calibration and ated predators (as in the 1992 Box D study). These situations selectivity. seem to be rather rare as the share of medium or high feeding In addition to these unique analyses, the GSBTS provides situations was only 25% (3 of 12 Box surveys). This is further- high quality data which enable certain parameters to be cal- more supported by the result that feeding is neither restricted culated with a higher precision and lower costs compared to by the gastric capacity nor by gastric throughput rate. In such calculations from large-scale surveys, e.g., a patchy environment as the North Sea the gastric capacity of – temporal changes on biodiversity and species richness and the predators has obviously evolved to be sufficiently large to – temporal changes in benthos and fish community struc- make use of food concentrations, once they are encountered. tures. These interpretations have also the potential to explain at Furthermore, the GSBTS provides valuable scientific in- first glance the counter-intuitive result that a station with high sight, which is complementary to results from large-scale sur- stomach contents is representative for a bigger area and a larger veys and may help to improve their design, e.g.: time interval than a station with low stomach content. – provision of an alternative fishery-independent time series – independent verification of stock trends obtained by large- scale surveys – geostatistical analyses of spatial autocorrelation has the Scientific value of the GSBTS and demonstrated potential to enhance large-scale survey applications in management CPUE estimates by significantly reducing their variances. The above mentioned aspects are of particular relevance for The GSBTS has established a multi-disciplinary scientific creating advice within the framework of the Common Fisher- survey time series which is globally unique in its design and ies Policy (CFP), and specifically for the implementation of the 76

Table 18: Indicators of ecosystem state (S) and of pressure on the ecosystem (P) as suggested by STECF-SGRN in 2006 (A), and examples of potential further indicators yet unspecified (B), and the potential of the GSBTS survey to provide the required data.

A) Suggested Indicators: Time series data available through the GSBTS:

S Abundance of vulnerable fishes and/ or their conservation sta- Records of occurrence of rare fish species (Higher probability of tus in relation to IUCN (or other) criteria recording than other existing surveys) S Abundance of vulnerable marine mammals, reptiles or seabirds Observation of seabirds in 6 areas of investigation plus observation on transects when steaming from one Box to another S Mean size and mean maximum sizes of bottom dwelling fishes Data available from multiple hauls within same area of investigation S Proportion of sensitive habitats impacted/ protected [Needs specific sampling / new surveys: see SGRN 2006] S Abundance of rare or vulnerable [invertebrate] species or Records of occurrence of rare invertebrate species habitats (Higher probability of recording than other existing surveys) S Age and size of maturity of abundant and/ or commercially Data available for 12 areas of investigation targeted species P Spatial and temporal distribution of fishing effort [Data from commercial fisheries] P Catch and discard rates [Data from commercial fisheries]

B) Further Indicators: Time series data available through the GSBTS:

S Indicators of biodiversity in fish communities Species richness in bottom fish assemblages within 12 areas of investigation S Indicators of predator-prey proportions within fish Field data and process models necessary for robust multi-species communities models

Ecosystems Approach to Fisheries Management (EAFM). Rice & Rochet 2005, ICES 2006c), new indicators need to The process of integration of environmental eschweizerbartxxxprotection sng- re- be evaluated through analyses of their sensitivity to fishing ac- quirements within the CFP should be monitored by means of tivities, the specificity of their response to these activities, and a system based on indicators (EU 2002). the response to time. Long-term data sets with high intensity The Subgroup for Research Needs (SGRN) of the EU Sci- sampling will be needed for this evaluation and may be con- entific, Technical and Economic Committee for Fisheries (EU tributed though the continuation of the GSBTS. 2005, 2006) – as well as the ICES working group for Eco- system Effects of Fisheries (WGECO, ICES 2006b) created synoptic reports which list the data and studies immediately Future perspectives needed within an incremental application of the ecosystems approach envisaged by the European Commission. When facing the substantial data needs of the incremental In this, they identified a suite of indicators of two types, implementation of the Ecological Approach to Fisheries Man- indicators of ecosystem state and pressure indicators, which agement (EAFM) into the Common Fisheries Policy (CFP), quantify the prevailing impact of fisheries activities. The most turning the GSBTS into a true ecosystem survey may provide recent SGRN meeting in June 2006 suggested a series of such a realistic and cost efficient data source complementary to the indicators that are ready for immediate application or that re- routine large-scale IBTS. quire only a small amount of further development. The scientific value of the present 20-year data set of the Through the GSBTS, a platform exists which already in- GSBTS could still be further increased by: cludes a series of investigations that can contribute to fulfilling 1. Combining the survey data with highly resolved data from a substantial part of the recently identified data requirements the commercial fishery to separate the effects of fishing for these indicators (Tab. 18) from natural variability. The GSTBS, as a multi-disciplinary survey, has -the spe 2. Further disciplinary and interdisciplinary analyses of the cial advantage of collecting data for several of these indicators entire data set: So far, the conducted analyses were rather at the same time. This survey would therefore be particularly disciplinary and truly interdisciplinary analyses are still suited for investigating potential synergetic effects when us- missing. Promising examples are: ing more than one indicator at a time, and for any derived – analysis of benthos-fish-bird-community changes over higher-level indicator. It may also be suited for the evaluation time and their relation to historic fisheries impacts of critical characteristics of any newly developed indicator for – coupling of biological and physical habitat characterisa- which it provides data: As it has been pointed out (Rice 2000, tion 77

– enhancement of geostatistical models for the calculation of References unbiased abundance indices from large-scale surveys (Papers directly based on the GSBTS survey results are – calculation of robust correction factors for gear selectivity marked with an asterisk [*]) and weather, current or tide effects on catchability – verification of 3D hydrodynamic model results at the local Adlerstein, S.A. & Ehrich, S. (2002): Effect of deviation from tar- scale through the unique time series of hydrographic and get speed and time of day on catch rates of some abundant species nutrient data. under North Sea international bottom trawl survey protocol con- 3. Collection of accompanying data in order to make the GS- ditions. – ICES Journal of Marine Science, 59: 594 – 603. [*] BTS a true ecosystem survey, i.e. enable it to detect tempo- Adlerstein, S.A. & Ehrich, S. (2003): Patterns in diel variation of ral changes in all major levels of the food web: cod catches in North Sea bottom trawl surveys. – Fisheries Re- – Zooplankton and ichthyoplankton sampling is proposed search, 63 (2): 169 – 178. [*] to be included in order to quantify the availability as food Adlerstein, S.A. & Trumble, R.J. (1993): Management implications source for planktivorous fish species or life stages of fish and of changes in by-catch rates of Pacific halibut and crab species thereby enable process studies on trophic interactions. caused by diel behaviour of groundfish in the Bering Sea. – ICES – Chlorophyll measurements (with probes) are suggested to Marine Science Symposium, 196: 211 – 215. provide information on the potential importance of bot- Aglen, A., Engås, A., Huse, I., Michalsen, K. & Stensholt, B.K. tom-up processes through food supply to the zooplank- (1999): How vertical migration may affect survey results. – ICES ton. Journal of Marine Science, 56: 345 – 360. – Routine stomach sampling to further improve the diet se- Armstrong, F.A.J., Stearns, C.R. & Strickland, J.D.H. (1967): lection process sub-models of currently applied multi-spe- The measurement of upwelling and subsequent biological proc- cies fisheries assessment models. esses by means of the Technicon Autoanalyzer and associated – Routine multi-frequency hydro-acoustic recordings to equipment. – Deep Sea Research, 14: 381 – 389. quantify the abundance of pelagic fish species and life Becker, R.A., Chambers, J.M. & Wilks, A.R. (1988): The New S stages, as well as jellyfish. Language: A Programming Environment for Data Analysis and For the reasons detailed above, we intend to continue Graphics. – Wadsworth & Brooks/Cole Advanced Books & Soft- the GSBTS in its present form, enlarge the number of Boxes ware, Pacific Grove, Ca. to equally cover the North Sea and we propose to extend its Berghahn, R. & Rösner, H.-U. (1992): A method to quantify feed- sampling in the described direction. We wish to invite other ing of seabirds on discard from the shrimp fishery in the North institutions to join us by including their expertise for specific Sea. – Netherlands Journal of Sea Research, 28: 347 – 350. added sampling effort as suggested here. Callaway, R., Alsvag, J., De Boois, I., Cotter, J., Ford, A., Hinz, H., Jennings, S., Kröncke, I., Lancaster, J., Piet, G., Prince, P. & Ehrich, S. (2002): Diversity and community structure of

Acknowledgements eschweizerbartxxx sng- epibenthic invertebrates and fish in the North Sea. – ICES Jour- nal of Marine Science, 59: 1199 – 1214. We are deeply indebted to all the technicians, students and scien- Camphuysen, C.J. (1994): Flatfish selection by Herring Gulls Larus tists which have joined us during the 20 years of cruises and especially argentatus and Lesser Black-backed Gulls Larus fuscus scavenging to the crew members and captains of the vessels for their patience in at commercial beamtrawlers in the southern North Sea. – Neth- fishing for the same fish at the same place for days. erlands Journal of Sea Research, 32: 91 – 98. We thank Ingo Wilhelms for the continuous maintenance and improvement of the survey database and Michael Dethloff for the Camphuysen, C.J., Calvo, B., Durinck, J., Ensor, K., Follestad, development of a data entry program. We also acknowledge the ex- A., Furness, R.W., Garthe, S., Leaper, G., Skov, H., Tasker, cellent technical assistance given by Ilse Büns for carrying out the M.L. & Winter, C.J.N. (1995): Consumption of discards by nutrient analyses and Monika Schütt for handling and plotting the seabirds in the North Sea. – Final report EC DG XIV research nutrient data. contract BIOECO/93/10, NIOZ-rapport 1995 – 5, Netherlands Dr. Dietrich Bürkel and Dr. Uwe Piatkowski provided de- Institute for Sea Research, Texel. tailed comments on the manuscript which are gratefully acknowl- Carr, M.R. (1996): PRIMER User manual (Plymouth Routines in edged. Dr. Joachim Gröger contributed the statistical analysis re- Multivariate Ecological Research). – 43 pp.; Plymouth, U.K. lated to chapter “Representative species composition”, p. 18. (Plymouth Marine Laboratory). The writing of sections “Predator-prey interactions fish-fisch” and “Analysing predator-prey interactions at large and small scales”, Clarke, K.R. & Warwick, R.M. (1994): Change in marine com- was financed by the EU project “BECAUSE – critical interactions munities: an approach to statistical analysis and interpretation. – between species and their implications for a precautionary fisheries Natural Environment Research Council, UK, 144. management in a variable environment – a modelling approach” (EU Connell, S.D. (2000): Is there safety-in-numbers for prey? – Oikos, FP6 TP8.1 502482). 88: 527 – 532. The evaluation of the data series presented in section “Effects of different parameters on the catch”, p. 33”, was supported by the Euro- Connell, S.D. & Gillanders, B.M. (1997): Mortality and abun- pean Commission (DG XIV) under project contract 98/029 (Survey- dance of a schooling reef fish. Proceedings of the 8th Interna- based abundance indices that account for fine scale information for tional Coral Reef Symposium, 1: 1035 – 1038. North Sea stocks – FINE). Cotter, A.J.R. (2001): Intercalibration of North Sea International External funding of the seabird work was obtained from the Eu- Bottom Trawl Surveys by fitting year-class surveys. – ICES Jour- ropean Commission (EC DG XIV: 92/3505; BIOECO/93/10), the nal of Marine Science, 58 (3): 622 – 632. Federal Agency for Nature Conservation (FKZ 808 05 086 and FKZ 802 85 280 - K 1) and the Verein der Freunde und Förder der Inselsta- Cressie, N.A.C. (1991): Statistics for Spatial Data. – 900 pp.; New tion der Vogelwarte Helgoland e.V. York (John Wiley). 78

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Appendix 1

Standard gear on FRC Solea

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