Faculty of Science 2008

Reproductive aspects of Kattegat cod (Gadus morhua): implications for stock assessment and management

Francesca Vitale

Doctoral thesis

Department of Marine Ecology Swedish Board of Fisheries University of Gothenburg Institute of Marine Research Sven Lovén Centre for Marine Science Turistgatan 5 Kristineberg Marine Research Station SE-453 21 Lysekil, Sweden SE-450 34 Fiskebäckskil, Sweden Akademisk avhandling för filosofie doktorsexamen i Marin Zoologi vid Göteborgs Universitet. Avhandlingen försvaras den 5 juni 2008, kl 10.00 på Sven Lovén Centrum för Marina Vetenskaper - Kristinebergs Marina Forskningsstation, Fiskebäckskil. Examinator: Prof. Mike Thorndyke Fakultetsopponent: Dr. Jonna Tomkiewicz, National Institute of Aquatic Resources, Technical University of Denmark, Kavalergården, 6, DK-2920, Charlottenlund, Denmark.

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CONTENTS

ABSTRACT 3

LIST OF PUBLICATIONS 4

INTRODUCTION 5

REPRODUCTIVE CYCLE 8

Ovarian gross morphology 9

Ovarian cellular development 10

Comparisons between the staging systems 13

Potential energetic proxies of maturity status 15

FECUNDITY 17

SPAWNING AGGREGATIONS 21

CONCLUSIONS AND IMPLICATION FOR MANAGEMENT 24

REFERENCES 26

ACKNOWLEDGEMENTS 39

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Abstract

The Kattegat cod (Gadus morhua) stock has been estimated to be currently at its lowest level since 1971 and the biomass of reproducing fish (spawning stock biomass, SSB) has been reduced by 95%. The whole stock is compressed to a few age classes and the reproduction is mainly dependent on first spawners. Despite rigorous catch limitations, there are no signs of recovery and since the year 2000 this stock has been considered outside safe biological limits. Assessment and management of fish populations currently rely on estimations of SSB, which in turn are based on the proportion of mature fish within age classes in the population (i.e. maturity ogives). A proper identification of mature individuals in the population is thus a crucial step for a precise estimation of SSB, and ultimately for evaluating the status of the stock and establishing harvest levels. In this study the gonadal development of cod in the Kattegat and Sound was studied by investigating ovarian histological structure on a temporal scale. Starting from existing maturity criteria, a modified system based on histological features was developed in order to emphasize crucial steps in the developmental process. Furthermore alternative indicators of maturity status were identified in the gonadosomatic index (GSI) and hepatosomatic index (HSI), representing the ratio of gonad and liver weight to the body weight, respectively. Comparisons between histological and routinely used macroscopical (visual) maturity judgement evidenced consistent discrepancies. The visual analysis consistently overestimates the proportion of mature females in all age classes. The overestimation is more severe for first-time spawners, due to a decreasing error with increasing age. According to present results the female spawning biomass (FSB) of Kattegat cod may have been overestimated by up to 35% for more than 20 years. Fecundity in cod has been shown to be tightly coupled with maternal size, condition and spawning experience, with first-time spawners having a lower reproductive success. In Kattegat cod, just prior to the spawning season fish length explains the largest part of fecundity variability. On the other hand, the maternal condition (HSI and body condition), did not consistently increase the explanatory power provided by fish size alone. However, in order to determine the maternal influence on egg production, the condition of the individual fish should be quantified at an earlier stage of the maturation process, when energy is initially allocated to egg production. SSB, currently used as reproductive potential predictor in stock assessment models, fails to accurately account for the effect that variation in length composition and fish condition has on the stock reproductive output. This leads to an overestimation of the reproductive potential when the stock is dominated by small individuals as is the case of the Kattegat cod stock. Taken together, the overestimation of the stock reproductive success may have led to the implementation of regulating measures far above the stock capacity, masking the need of a more drastic catch control. The use of fishery dependent and independent data shows that cod have been aggregating and spawning in specific areas in the southern Kattegat for more than 25 years, although in considerably reduced numbers over time. It was thus indicated that spawning activity may have also ceased in some areas previously depicted as spawning grounds. These findings were supported by independent samplings of individual physiological and histologically determined maturity status. On the whole, a revision of Kattegat cod stock assessment models and a re-evaluation of the reference points, based on increased stock-specific biological knowledge, is strongly suggested. The use of more accurate methods for estimating individual maturity may integrate and reinforce the routinely used methodology during research surveys. However, a monitoring program based on direct measurements of stock fecundity, and factors influencing it, ought to be considered. The acquired knowledge on the persistence of the spawning aggregations may facilitate the implementation of a more temporally and spatially controlled fishing activity. This thesis represents an insight into the reproductive biology of Kattegat cod, aiming to enhance the accuracy and precision in biological data used for stock assessment and thus assist fishery management decisions.

Keywords: Gadus morhua, fecundity, histology, Kattegat cod, maturity ogives, physiological indices, spawning grounds, SSB, stock assessment, stock management.

Department of Marine Ecology, University of Gothenburg Sven Lovén Centre for Marine Science - Kristineberg Marine Research Station S-450 34 Fiskebäckskil, Sweden

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LIST OF PUBLICATIONS

I. Vitale, F., Cardinale M. and Svedäng, H., 2005. Evaluation of the temporal development of the ovaries in Gadus morhua from the Sound and Kattegat, North Sea. Journal of Fish Biology, 67: 669-683. doi:10.1111/j.0022-1112.2005.00767.x

II. Vitale, F., Svedäng, H and Cardinale, M., 2006. Histological analysis invalidates macroscopically determined maturity ogives of the Kattegat cod (Gadus morhua)and suggests new proxies for estimating maturity status of individual fish. ICES Journal of Marine Science, 63: 485-492. doi:10.1016/j.icesjms.2005.09.001

III. Vitale, F., Thorsen, A. and Kjesbu, O.S. Potential fecundity of Kattegat cod (Gadus morhua) in relation to pre-spawning body size and condition. Manuscript

IV. Vitale, F., Börjesson P., Svedäng H. and Casini M., 2008. The spatial distribution of cod (Gadus morhua L.) spawning grounds in the Kattegat, eastern North Sea.Fisheries Research 90: 36-44. doi: 10.1016/j.fishres.2007.09.023

Publications I, II and IV are reproduced with the permission from the publishers.

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INTRODUCTION

Cod (Gadus morhua) has since the Middle Ages been one of the most socioeconomically important fish species, triggering the development of more and more sophisticated fishing tools for increasing the catches (Kurlansky, 1998). The consequence has been a decline in cod stocks all over the North Atlantic (Myers et al.,1996; Cook et al., 1997; Hutchings, 2000) and not least the stock inhabiting the Kattegat area (Svedäng and Bardon, 2003; Cardinale and Svedäng, 2004). The International Council for the Exploration of the Sea (ICES) including 20 members countries was founded in 1902. The main aim was to promote marine research in North Atlantic (including the adjacent Baltic and North Sea) for evaluating the effects of fishery activity in comparison to natural fluctuations and carry out an international coordination research of the sea. ICES is aimed at estimating and determining safe harvesting limits to prevent the collapse of commercial fish stocks. Scientists must therefore determine the quantity of fish that can be caught without reducing the spawning stock to a level where recruitment to the stock is seriously threatened. In other words, the main goal is to develop harvest control rules for preserving sufficient stock reproductive potential to allow a sustainable exploitation. Fish stocks’ abundance and fishing mortality are presently assessed using age-structured models, such as virtual population analysis (VPA), based on catch, effort and survey data (Pelletier and Laurec, 1992). The harvest is generally regulated through the establishment of annual total allowable catches (TAC). The cod stock in the Kattegat (ICES Subdivision 21) is currently assessed as a separate stock. The assessment relies on survey data from the International Bottom Trawl Survey (IBTS) carried out in the 1st

and 3rd quarters of the year on board of the Swedish R/V Argos, and from the Danish Kattegat Bottom trawl carried out in the 1st and 4th quarters of the year on board of the Danish R/V Havfisken.The demersal fishery in the Kattegat, most exclusively Danish (~70%) and Swedish (~30%), is based on trawling activity and it targets crayfish (Nephrops norvegicus), cod and flatfishes (in particular plaice-Pleuronectes platessa and sole- Solea solea). Back in the 1950s and 1960s there was also a developed fishery on other species such as haddock (Melanogrammus aeglefinus) and pollack (Pollachius pollachius). Due to the decline of these two stocks, cod and, to a small extent whiting (Merlangius merlangus)are presently the only gadoid species fished in the area. Cod is mostly fished during the spawning period in the 1st quarter of the year by a trawl fishery directed on the spawning grounds, historically recognized in the central and southern part of the Kattegat (Pihl and Ulmestrand, 1988; Hagström et al., 1990; Svedäng and Bardon, 2003). In addition, cod are incidentally exploited in the Nephrops fishery, taking place the whole year around in the deeper parts of the Kattegat. In this fishery cod are captured as by-catch species and successively discarded if the allowed quota is surpassed or if the fish is under the allowed catchable size.

The assessment of Kattegat cod has shown a drastic reduction in total biomass and biomass of reproducing fish (spawning stock biomass, SSB) since 1970s (Figure 1), mainly attributable to overfishing. This decline occurred in concomitance with the disappearance of separate spawning aggregations (Svedäng and Bardon, 2003).

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Consequently the number of recruits (1 year-old individuals), despite the significant inflow of eggs and larvae from the Skagerrak-North Sea cod stocks (Cardinale and Svedäng, 2004; Svedäng and Svenson, 2006) is also severely reduced (Figure 1). In accordance, catches have been limited and commercial landings have steadily declined from around 15.000 in 1970 to 876 in 2006, which is the lowest value in the time series. Despite the rigorous catch limitations, the stock has not shown any sign of recovery and at present is considered as severely depleted. Currently, the spawning stock biomass remains at historically low levels, and at the present state the fishery is largely dependent on the strength of incoming year classes (ICES, 2007). The stock has been considered outside safe biological limits since year 2000, and from 2002 and onwards, the ICES Advisory Board has recommended zero catches from the area.

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Figure 1: Time series of (a) Number of recruits (1 year-old individuals), Total biomass and SSB (in tonnes) and (b) commercial landings in Kattegat cod ( in tonnes)(ICES, 2007).

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Stock-recruitment models are important tools for the management of exploited populations (Ricker, 1975). These models represent a fundamental link between the parental population and the number of offspring produced, i.e. recruitment. The relationship between the SSB and the number of recruits is used to determine to what extent a stock may be harvested. Furthermore, annual TACs are determined by using SSB as one of the reference points. Accurate estimates of the SSB thus represent a key factor for evaluating the status of the stock and establishing harvest levels.SSB is calculated as the aggregated weight of mature individuals in each age class. The correct identification of mature individuals in the population is thus the crucial step for a precise estimation of SSB. Histological analyses of reproductive organs are considered the most accurate means for evaluating the degree of individual maturation (Murua et al., 2003; Kjesbu et al., 2003; Tomkiewicz et al., 2003a). However, the assignment of individual maturity status is conventionally based on macroscopical (visual) inspection of the reproductive organs. Therefore the accuracy of SSB estimations is mainly dependent on the ability of the observer to discriminate reproductively active individuals. The subjectivity of this method entails the risk to introduce an error in the estimations of the SSB, distorting the relationship between stock and recruitment (Murawsky et al., 2001). An additional issue concerns the use, in most stock-recruitment models, of the SSB as a proxy of stock reproductive potential, assuming that SSB is proportional to the stock total annual egg production (Marshall et al., 2006 and references therein). This assumption implies that equal biomass weights generate the same reproductive output. An increasing number of studies have challenged this assumption, arguing that demography (Solemdal et al., 1995; Trippel, 1998; Trippel, 1999; Tomkiewicz et al.,2003b), spawner quality (Jørgensen, 1990; Kjesbu et al., 1991; Solemdal et al., 1995; Marshall et al., 1998; Trippel, 1998) and environmental variability (Pörtner et al., 2001; Koops et al., 2003; Lambert et al., 2003) have a strong influence on reproductive success. Furthermore, the SSB estimates are often derived from combined male and female maturity data. Growth, maturation and mortality are known to be sexually dimorphic in many marine fish species, i.e. earlier maturity and shorter lifespan in males (Tomkiewicz et al., 2003b and references therein). Therefore skewed sex-ratio affects the composition of the spawning stocks and compromises the reliability of SSB as a measure of stock reproductive potential. Consequently, concerns about the use of SSB as a suitable proxy for stock reproductive potential have been increasingly raised (Jørgensen, 1990; Kjesbu et al., 1991; MacKenzie et al., 1998; Trippel, 1999; Kraus et al., 2002; Marshall et al., 2003: Köster et al., 2003;). In light of these issues, information about stock structure, spawners’ size at age, sex ratio, proportion of mature at age, fecundity, which all in turn influence offspring number, size and viability are fundamental for accurate estimations of stock reproductive potential. Stock-specific knowledge about fish reproductive biology is therefore an essential tool when managing a stock and represents the basis for the establishment of a sustainable yield. From a management point of view, accurate knowledge about maturity status is important for determining the size at which maturity is first reached, i.e. when the fish can be considered as adult. This information can be used for establishing the minimum size at capture to allow fish to reproduce at least once before being captured. Furthermore, temporal and spatial information on the maturation pattern are essential for identifying spawning grounds and determining the timing of area closure to protect the

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spawning activity. Moreover, understanding the relationships between age/size at maturity or fecundity, food availability and population size is fundamental for predicting the vulnerability of the stock to increasing exploitation pattern and/or changing environmental condition. Therefore investigations of reproductive biology are not only important for understanding stock dynamics, but represent the basis for a correct stock assessment upon which effective management strategies have to rely.

In this thesis, I investigated the temporal development of the ovaries in cod from Kattegat and the Sound and explored possible differences in maturity schedule between the two subpopulations. This led to the development of a histologically based maturity scale where key events for discriminating maturing individuals are emphasized (I). In paper II, the new built histological scale is used in an attempt to validate the conventionally used visual evaluation of ovaries. The detected differences are successively used to reconstruct the historical (1971-2004) female spawning stock biomass (FSB) of Kattegat cod. Furthermore, potential proxies of maturity status are sought among physiological parameters. Paper III examines the potential fecundity in pre-spawning individuals and explores its relationship with the maternal size and condition. In addition, the length-specific potential and relative fecundity and oocyte size are investigated in Kattegat cod and compared to the more healthy Northeast Arctic cod stock (NEAC). In paper IV combined survey and commercial data, together with individual histological maturity and physiological status, are used for detecting putative spawning areas and testing the stability of spawning aggregations. The scope of this thesis was therefore the acquisition of accurate stock-specific information about timing, location and quality of reproductive performances in Kattegat cod in order to improve the assessment and assist the implementation of a more realistic management plan aiming at the recovery of this stock.

REPRODUCTIVE CYCLE

Natural selection favours individuals who efficiently gather energy and matter from the environment and effectively allocate it in order to maximize its fitness. Ideally, a fish would mature early at a large size and produce numerous and large offspring over a long reproductive life span. However, in the real world resources are limited and allocated according to the physiological trade-offs between metabolic needs, survival and reproduction. The energy demand related to reproduction also includes the behavioural aspects linked to it (courtship and migration) beyond the main energy consumption involved in gonadal development. Hence each fish species displays a reproductive strategy (Murua and Saborido-Rey, 2003), which is the overall pattern of reproduction typically shown by individuals in a species, and a reproductive tactic which includes variations in the typical pattern, in response to the environmental fluctuations (Wootton, 1984; Murua et al., 2003). Most of the studies on fish reproduction have focused on females, partly because of the maternal origin of the nourishment in the early life stage and partly because eggs more than sperms represent a limiting factor for the offspring production (Helfman et al.,1997).

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Cod, as all gadoids, is an iteroparous species, which means that spawning occurs more than once during lifetime, in contrast with semelparous species, such as eel (Anguilla anguilla) which have only one breading season and successively die. Fecundity is determinate in cod which implies that the number of eggs that will develop is fixed before the onset of the maturation process (Kjesbu and Kryvi, 1989; Morrison, 1990). Species with indeterminate fecundity show continuous oocytes recruitment during the entire spawning period. Ovaries are paired elongate hollow organs situated ventrally to the swim bladder and consist of several transverse ovigerous folds projecting into the lumen where growing germ cells, i.e. oocytes, originated by meiosis from primordial cells (oogonia), become eggs (oogenesis). The ovarian development in cod is group synchronous showing discrete cohorts of developing oocytes co-existing in the gonad, successively recruited and spawned as discrete groups (i.e. batches) (Kjesbu and Kryvi, 1989). The described pattern can be observed throughout the whole organ due to the homogeneity characteristic of cod ovaries (Kjesbu et al., 1990).The different phases the ovary goes through during the developmental process have been classified and used for building a large number of maturity scales. Individuals are assigned to different stages, according to their maturity status. Maturity scales are an important tool for determining stock specific spawning pattern and for recognising reproductively active individuals. Their accuracy is a crucial prerequisite for a correct estimation of the maturity ogives, (i.e. the proportion of mature individuals at age in the population) and consequently of the SSB.

Ovarian gross morphology

During the maturation process, ovaries undergo different modifications in the gross morphology showing changes in size, vascularisation, consistency and colour. At the beginning, ovaries are small, translucent yellow-reddish structures situated in the posterior part of the abdominal cavity. Following the maturation process, ovaries become larger, firmer, more opaque dark-red/orange and fill most of the cavity. As ripening begins oocytes become increasingly evident through the ovarian surface, at first as opaque granules and successively as transparent eggs as spawning approaches. After the eggs are released the now reddish-grey ovary appears shrunk and contracted, i.e. spent stage, and successively enters the recovering stage (Table 1). The macroscopical (visual) examination of reproductive organs is a low cost and quick method for assessing maturity, allowing the analysis of a large amount of samples. The judgement of the reproductive status based on the gross anatomy of the ovary is therefore ideal for routine monitoring of fish stocks in order to estimate the maturity ogives. Specimens are assigned to one of the different stages included in the used maturity scale according to their external appearance. The maturity scales may vary on a national level as different countries utilize different criteria. The national scale is successively converted into the international conventionally approved staging system before reporting to ICES. The 4-stages maturity scale (ICES, 1999) presented in Table 1, is used during the IBTS performed annually in Kattegat, Skagerrak and North Sea.

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VIRGIN Ovaries small, elongated, whitish, translucent. No signs of development.

Development has obviously started, eggs are becoming MATURING larger and the ovaries are filling more and more of the

body cavity but eggs cannot be extruded with onlymoderate pressure.

SPAWNING Will extrude eggs under moderate pressure to advanced stage of extruding eggs freely with some eggs still in

the gonad.

SPENT Ovaries shrunken with few residual eggs and muchslime. Resting condition, firm, not translucent, showing

no development.

Table 1: Macroscopical maturity scale from the manual for the International Bottom Trawl Surveys (IBTS)

According to the 4-stages scale, only individuals assigned to the first stage are considered immature (juveniles) and therefore have to be excluded form the spawning biomass. The second stage should include all the maturing individuals that are going to finalize their maturation by the forthcoming spawning season. The third stage, i.e. spawning, includes only individuals which are expelling eggs when captured. The last stage, i.e. spent, comprises the individuals that have recently released all the eggs, but also specimens that have already entered a post-spawning condition (resting stage). All the stages from the second and upwards are therefore considered to contribute to the annual reproductive potential of the stock and consequently included as mature in the estimations of the maturity ogives.

Ovarian cellular development

The described modifications of the gross morphology mirror a series of developmental changes on a cellular level identifiable by the means of histological analyses. The general cellular cycle, common to all teleosts (Wallace and Selman, 1981; Tyler and Sumpter, 1996), includes a phase of primary oocyte growth, during which the oocytes increase slightly in size and cytoplasmatic structures, such as the circumnuclear ring (CNR), begin to appear. The following phases include a first proliferation of spherical vesicles (cortical alveoli) followed by a period of yolk accumulation (vitellogenesis). Finally, after the final maturation, hydrated oocytes (now eggs) are ovulated into the ovarian lumen. The ruptured follicles (post-ovulatory follicles, POF) remain in the ovary and persist for a limited time degenerating after spawning. The duration of these structures is however still under discussion and might be species specific. In flounder (Platichthys flesus), POFs have been seen up to 1 month after spawning (Janssen et al.,1995) while in cod, POFs have been recognized up to 9 months after spawning

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(Saborido-Rey and Junquera, 1998; Rideout, 1999). Vitellogenic oocytes that do not complete the maturation undergo a degenerative process called atresia and are successively reabsorbed, while the ovary regenerates. As mentioned above, oocyte cohorts at different developmental stages co-exist in cod ovaries although the first appearance of oocytes showing advanced specific features marks the maturity stage and it is used as stage indicator.

Histological techniques have been increasingly used for investigating the oogenesis of cod from different areas (Kjesbu and Kryvi 1989; Saborido-Rey and Junquera, 1998; Tomkiewicz et al., 2003a, I) and a number of histological maturity scales have been produced. Tomkiewicz and co-workers (2003a) proposed a 10-stages maturity scale for the Baltic cod, subdividing the general classification scheme and adding also some important stages, which show potential disease that may reduce fecundity. The histological analyses of gonadal development in cod from the Kattegat and the Sound brought to the development of a 7-stages maturity scale (I, Table 2).

Small oocytes with a dense basophilic cytoplasm, a central nucleusIMMATURE and few large nucleoli around its edge (perinucleolar stage)

Oogonia are always present but they might not be visible

PREVITELLOGENIC The nucleus increases in size and multiple nucleoli are formed. A weaklyGROWTH stained area called “circumnuclear ring” (CNR) is also present

The circumnuclear ring moves towards the outer part of the cell and ENDOGENOUS gradually disintegrates, while the spherical cortical alveoli appear

VITELLOGENESIS in the superficial half of the cytoplasm. No yolks granules present yet.

Presence of yolk granules. The nucleus, still centrally located, becomesEXOGENOUS irregular. The occurrence of this stage means that the maturation

VITELLOGENESIS process is in progress, and under normal conditions, the individual willdevelop within the current spawning season

FINAL The chorion becomes thicker, the nucleus migrates towards the animalMATURATION pole and the hydration process occurs

SPENT Post-ovulatory follicles (POFs), after oocytes release into the lumen,are distinguishable.

RESTING Oocytes in stage 1 and 2. Some Post-ovulatory structures (POF), still present, show signs of previous spawning

Table 2: Maturity scale based on histological inspection of ovaries (I)

The critical point in maturity studies is to detect the threshold beyond which an individual can be considered as maturing within the present season and unquestionably going to spawn within the next spawning season. In other words, it is particularly important to specify the minimum level of oocyte development necessary for a female

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to be considered mature. According to some studies (Woodhead and Woodhead, 1965; Shirokova, 1977; Holdway and Beamish, 1985), individuals presenting oocytes in the CNR stage (Table 2 stage 2) are likely to mature within the following spawning season. However, ovaries at this stage are always present and the probability of carrying on the maturation process depends on the degree of development in relation to the time of the year in which they are observed (Woodhead and Woodhead, 1965; Holdway and Beamish, 1985; Tomkiewicz et al., 2003a). Further studies (Saborido-Rey and Junquera, 1998; Tomkiewicz et al., 2003a) have identified the threshold between mature and immature fish in the cortical alveoli stage (Table 2, stage 3 and Figure 2a). The content of these alveoli and their role in the fertilization have been investigated in a number of teleosts and it has been shown that they mainly contain endogenously (in situ, within the oocyte) synthesized glycoproteins (Tyler and Sumpter, 1996). This stage is therefore called endogenous vitellogenesis (Burton et al., 1997, I) in contrast with the true (exogenous) vitellogenesis occurring when yolk granules are formed using vitellogenin sequestered from the maternal liver (Tyler and Sumpter, 1996).

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Figure 2: Histological sections of oocytes at the a) endogenous vitellogenesis stage with cortical alveoli (ca) and b) exogenous vitellogenesis with cortical alveoli and yolk granules (yg). Scale bar 100 �m.

The content of cortical alveoli will serve to harden the membrane (vitelline envelope) after ovulation and prevent polyspermy (Kitajima et al., 1994). Thus these structures, often called yolk vesicles, are not to be considered yolk in a strict sense as their contents do not contribute to the embryonic development (Wallace and Selman, 1981). The hepatically derived vitellogenin packed in granules during the true vitellogenesis (Table 2, stage 4 and Figure 2b) is the only precursor of yolk proteins (Tyler, 1991). Furthermore, a number of studies (Burton, 1994; Rideout et al., 2000; Campbell et al.,2006) have provided evidences that fish in cortical alveoli stage can arrest the development and remain reproductively inactive. Therefore the maturity scale presented in paper I aimed to emphasize the passage from the endogenous to the exogenous vitellogenesis as the threshold between immature and mature individuals. An individual showing oocytes with cortical alveoli but no yolk granules has to be considered maturing, but according to the above cited studies, this does not necessarily mean that it

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will be reproductive in the next spawning season. Only fish from the exogenous vitellogenic phase, under normal conditions, ought to be considered spawning within the current spawning season (Burton et al., 1997, Mackie and Lewis, 2001, I) and consequently included in the spawning stock biomass.

Comparisons between the staging systems

Some of the ovarian features cannot always be discriminated by the naked eye during certain phases of the developmental process. Therefore the consistency of this visual method has been increasingly distrusted (Saborido-Rey and Junquera, 1998; Kjesbu et al., 2003, II). While advanced stages (late vitellogenesis and spawning) are easily recognizable and therefore properly judged, the incongruence is encountered for individuals at the beginning of the developmental process. As stated above, the stage 2 in Table 1 should include all the maturing individuals that will eventually spawn during the upcoming spawning season. However, a consistent part of specimens showing initial signs of structural modification are erroneously interpreted as maturing and included in this stage (I). Such a mistake obviously leads to an overestimation of the part of the population contributing to the stock reproductive potential. The comparison between the two staging systems (macroscopical and histological) in Kattegat cod shows in fact a consistent overestimation of the proportion of mature individuals for all age classes but the entity of the estimated bias decreases with increasing age. Consequently larger errors are made when judging first spawners (II). It is therefore obvious that the risk is amplified in stocks such as Kattegat cod, where the SSB is skewed towards younger and smaller individuals.

A further problem encountered when using the macroscopical scale concerns the resting stage, which at the present state is not included in the adopted IBTS macroscopical scale (Table 1). It is important to remark that the term resting may represent a source of confusion because it is often used to refer both to the individuals immediately after the spawning (recovering) as well as to individuals that are omitting spawning (skippers). If the maturity status is observed before the spawning season, these confusions are avoided due to the unlikelihood to find fish in post-spawning condition. The spawning omission appears to be fairly common in cod and it has been estimated that around 30% of cod females tend to skip spawning (Walsh et al., 1986: Rideout et al., 2000; Jørgensen et al., 2006). This phenomenon may occur either by failing to start vitellogenesis (resting) or interrupting it (reabsorbing) or by concluding the process without egg release (retaining). The latter type may occur depending on the conditions encountered during the spawning season (overcrowding, mate availability, pollution) while the first two types (resting and readsorbing) have been often ascribed to low temperature (Woodhead and Woodhead 1965; Federov, 1971) or low condition due to scarcity of food (Burton and Idler, 1987; Rideout et al., 2000; Rideout et al., 2005) prior to the spawning season. The external appearance of the fish may be helpful for identifying females that retain eggs since overripe eggs and scarce intra-ovarian fluid shape the abdomen giving to it a berry-like aspect (Rideout et al., 2005). More difficult is instead the identification of

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females in resting and reabsorbing condition, due to their early stage of development. Gonads in these conditions may be easily confused with late immature or spent, and in the second case the estimation of the spawning stock would be affected.Histology is the most accurate way for identifying non-reproductive individuals, by detecting signs of previous spawning activity (POF) among oocytes in early maturation stage (Tomkiewicz et al., 2003a, Rideout et al., 2005, I). The wall thickness may also be used as criterion for identifying non reproductively active individuals, owing that immature individuals have thinner ovarian wall than the non-reproductive ones (Rideout et al., 2000). However, the presence of POF is the unquestionable sign of previous spawning activity. The occurrence of POFs in non-ripening fish at the time of the year when adult individuals should be ripening (e.g. in December-January in Kattegat cod) suggests that the fish has previously spawned but will not spawn in the upcoming season. The identification of non-reproductive females and their exclusion from the SSB is fundamental, especially for highly exploited stocks. Therefore the inclusion of the resting stage in maturity scales both macroscopical and histological (Tomkiewicz et al., 2003a, I) is crucial and when observed before the onset of spawning, this stage has to be considered as synonymous to a non-reproductive stage.

The occurrence of the different stages and the reliability of the visual inspection are dependent on the time of sampling in relation to the spawning season. Therefore knowledge of the maturation chronology has to be ascertained accurately and on a stock specific level. The temporal ovarian development shows no differences in maturity schedules between cod from Kattegat and the Sound (I). In cod off Newfoundland, females show significant cellular changes more than 7 months before the spawning (Burton et al.,1997) In the Kattegat and the Sound maturing females were found at the earliest in October (i.e. 4 months before the spawning peak), ripening continues until January, spawning peaks in February, and March marks the end of the spawning season (I).When comparing the microscopical and macroscopical staging systems, all age classes showed a convergence towards minimum bias in January, i.e. one month before the spawning peak (II) when the misjudgement is minimized due to the unmistakable advanced stage of the maturity process and to the unlikelihood to find fish in spent or post-spawning condition. Consequently, the reliability of visual judgement is dependent on the time of sampling. Accurate estimations of maturing fish some months before or just after the spawning season can only be assured by using microscopical investigations (Saborido-Rey and Junquera, 1998, Kjesbu et al., 2003, II).Data on individual maturity status for the estimations of the SSB in the Kattegat are annually collected during the surveys performed in February, which hence coincides with the spawning season. A recalculation of the historical female spawning biomass (FSB) for the period 1991-2004, applying the bias obtained from the comparison between the two staging methods, showed a consistent overestimation of the proportion of mature females. The re-estimated FSB was in fact always lower than the historical FSB, evidencing an overestimation ranging between 21 and 35% (II). Hence the histological evaluation of ovarian development has the clear advantage of allowing detailed recording of the maturation development occurring in the ovary. Such information gives the opportunity to obtain unambiguous interpretation of individual maturity status. Estimating the spawning fraction by the means of histological analyses

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is a robust way for obtaining accurate estimates of SSB. Maturity ogives based on macroscopical evaluation, determined during the spawning season, may instead lead to the inclusion of non-reproductive individuals in the SSB estimation. The resulting inflated SSB is prone to mislead the management with serious consequences for the stock.

Potential energetic proxies of maturity status

The use of histology in maturity studies has gained an increasing and unanimous approval as considered more consistent and reliable than macroscopical analysis (Murua et al., 2003; Tomkiewicz et al. 2003a, II). However it is an expensive and time consuming technique and it restricts the analyses to relative small samples. Furthermore the collection of ovaries for histological analyses on board of research vessels implies the handling of harmful substances, i.e. formaldehyde, necessary for the storage. Despite its attested reliability, histology is thus not routinely used and alternative indicators of maturity status, mainly linked to the energy resources, have been often sought. Substantial energy reserves are in fact required for the reproductive process of a fish and the energy expenditures related to reproduction can represent 10-22% of the annual energy budget (Jobling, 1982). In cod, the gonadal maturation, together with all the events associated with reproduction, is mainly promoted by energy gathered and stored during the feeding season rather than ingested during the reproduction. In concomitance with the cessation of feeding during pre-spawning and spawning periods (Kjesbu et al., 1991; Fordham and Trippel, 1999; Lambert and Dutil, 2000) female cod use the stored resources, in form of proteins in the muscle (Eliassen and Vahl, 1982) and fat (lipids) in the liver (Kjesbu et al., 1991), and transfer them to the gonads. Thus the seasonal variations in physiological condition related to reproduction and, in particular gonadosomatic index (GSI, ratio of gonad weight to the body weight), hepatosomatic index (HSI, ratio of liver weight to the body weight) and Fulton’s condition factor (ratio between fish weight and length cubed), have been monitored in different cod stocks (Schwalme and Chouinard, 1999; Lambert and Dutil, 1997a; Lambert and Dutil, 2000, Tomkiewicz et al., 2003a; I; IV). Seasonal pattern of nutrients storage and depletion may differ among cod living in different geographical areas and experiencing different environmental conditions, due to the stock–specific variability in feeding periodicity. Cod in Norwegian coastal fjords (Hop et al., 1992; Hop et al., 1993; Michalsen et al., 2008), in the North Sea and areas west of Scotland (Rae, 1967; Daan, 1973) continue to feed actively during winter (Hislop, 1997). For Kattegat cod, those indices show increasing trends until the spawning starts, when HSI and Fulton’s K values start to decrease again while GSI clearly declines when the spawning is concluded (IV; Figure 3). Similar trends in HSI and K have also been observed in Baltic cod (Tomkiewicz et al., 2003a). However, for some stocks the active consumption of stored resources may occur at an earlier time (Schwalme and Chouinard, 1999; Lambert and Dutil, 2000 and references therein; Mello and Rose, 2005 a and b) possibly due to food-limitations (Jangaard et al., 1967; Hawkins et al.,1985).

15

741 115

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Oct NovDec Jan Feb M

ar

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Figure 3: Monthly trends of bioenergetic indices in Kattegat cod from the period 2002- 2006 (merged years). The sample size is indicated only in the first diagram. Bars represent standard errors.

In paper II a regression tree-model approach was used for testing different variables, as predictors of the maturity status in Kattegat cod. In analogy with stepwise procedure, only variables that significantly contribute to explain the variance are kept in the final model, and accordingly to the parsimony principle, the model are simplified without compromising the goodness of fit. Results showed that the best model with the lowest misclassification rate includes only GSI (which represents the main discriminating factor) and HSI, making these variables useful for tracking the ongoing maturation process. Conversely, total length and Fulton’s condition factor were poor predictors and their use increased the misclassification rate of the model. HSI is thus a more accurate measure of fish condition in cod than Fulton’s condition factor due to the storage of energy in the liver (Lambert and Dutil, 1997b; Marshall, 1999). The proved ability of GSI to reflect the reproductive status is also confirmed in other

16

studies on cod (Burton, 1999; Dahle et al., 2003; Tomkiewicz et al., 2003a) as well as on riverine fishes (Brewer et al., 2008). Due to the use of liver reserves for producing vitellogenin, it is not surprising that there is a relationship between liver condition and maturity (II). Seasonal changes in liver size have been studied in Atlantic cod (Eliassen and Vahl, 1982; Lambert and Dutil, 1997b; Schwalme and Chouinard, 1999; Hansen et al., 2001) and a positive effect of liver condition on the probability of spawning has been demonstrated (Ajiad et al., 1999; Bromley et al., 2000; Morgan, 2004; Morgan and Lilly, 2006). Additionally fat content in the liver has been related to the progress of spawning in female cod (Kjesbu et al., 1991). These findings support the idea of the utility of using HSI in maturity status identification. However, the substantial variation in HSI observed in Baltic cod, probably due to a longer spawning season and therefore higher variation between individual fish compared to the cod in Kattegat (I), rendered it of a little use for maturity status prediction in this stock (Tomkiewicz et al., 2003a).

The condition of the fish, or the quantity of energy stores, may significantly influence the reproductive investment in cod (Kjesbu et al., 1991; Chambers and Waiwood, 1996; Marshall et al., 1999; Lambert and Dutil, 2000; Ouellet et al., 2001). Reduced fecundity (Kjesbu et al., 1991; Marteinsdottir and Steinarsson, 1998; Marshall et al., 1998) or even skipped spawning (Burton and Idler, 1987; Rideout et al., 2000) have been increasingly associated to low conditioned fish. However, the use of bioenergetic index might not be useful for identifying individuals skipping maturity, or more specifically individuals in reabsorbing phase, due to the weight of the atretic oocytes (Rideout et al.,2005) that would nonetheless lead to an increased gonadal weight although in absence of reproduction. While histology is a more reliable technique than physiological indices, the amount of time and the economical cost required may diminish its practical advantage and limit its use. The employ of GSI and HSI, once validated, may be incorporated with other information, such as minimum length at maturity or macroscopical judgement for improving the discrimination between mature and immature individuals (Burton, 1999; Rideout et al., 2005). Hence, considering the modest effort required for the collection of liver and gonad weight, the recording of those additional parameters should be easily included in the routine research sampling procedures for supporting the macroscopical maturity judgement when histological analyses cannot be carried out.

FECUNDITY

Stock assessment models have been traditionally based on the assumption that SSB adequately represented the stock reproductive potential This assumption underlies constancy over time of the SSB and of the stock relative fecundity (number of eggs produced per unity mass), intuitively hard to be valid. Following the decline in stock size and recruitment level experienced by most of the commercially exploited fish stocks, several researches have addressed the question of how changes in population size affect stock-specific reproductive traits. During the past decades an increasing number of studies have evidenced that SSB is not an accurate measure of reproductive potential (Jørgensen, 1990; Kjesbu et al., 1991; MacKenzie et

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al., 1998; Trippel, 1999; Kraus et al., 2002; Marshall et al., 2003; Köster et al., 2003; Marshall et al., 2006), hence the importance of incorporating reproductive biology in stock assessment gained credit. The alternative concept of stock reproductive potential (SRP) was therefore introduced. SRP represents the annual variation in stock’s ability to produce viable eggs and larvae that may eventually recruit to the adult population or fishery (Marshall et al., 1998;; Trippel, 1999; Murawski et al., 2001).Fundamental parameters affecting SRP such as proportion of mature at age, fecundity and offspring size and viability (fertilization and hatching success) have shown to vary with parental age, size, condition and spawning experience (Jørgensen 1990; Kjesbu et al., 1991; Solemdal et al., 1995; Marshall et al., 1998; Trippel, 1998). In North Atlantic cod stocks the severe decline in abundance has been accompanied by substantial reductions in age and size at first sexual maturation (Trippel et al., 1997) and a disproportionate loss of larger, older repeat-spawner (Trippel, 1995) have occurred.Laboratory experiments on cod demonstrated that first-time spawners have a lower reproductive success, breeding for a shorter time and producing fewer and smaller eggs with lower fertilization and hatchings rates (Solemdal et al., 1995; Trippel, 1998; Tomkiewicz et al., 2003b). Furthermore, in multiple spawning fishes, older individuals are likely to produce more batches, within the spawning season, over a longer period than younger ones (Parrish et al., 1986; Lambert, 1990). In addition, the fertilization rate is higher when bigger males are involved in the spawning act (Hutchings et al.,1999). Therefore alterations in the size composition of the breeding stock may conceivably lead to changes in stocks’ reproductive success.

Fecundity estimates do not give information on offspring viability but provides the starting number of potential offspring that can be produced. Fecundity data are therefore essential for assessing an individual’s reproductive potential and consequently providing more reliable estimate of stock recruitment rather than using spawner biomass. Cod, as most of the marine teleosts, produce a large number of small eggs. The estimation of the realized fecundity, i.e. the total number of egg actually spawned, in wild fishes is not an easy task. Some studies have estimated realized fecundity by collecting released eggs from captive fishes reared in tanks (Kjesbu et al., 1991; Trippel et al., 1998; Fordham and Trippel, 1999; Thorsen et al., 2003), while other studies counted the number of developing oocytes, and subsequently subtracting the number of atretic oocytes (Green Walker et al., 1994, Ma et al., 1998; Witthames et al., 2003). However the latter method needs accurate information on the persistence of the atretic stage (Murua et al., 2003) and additionally atresia is not routinely examined. Consequently many studies have concentrated on measurements of potential (i.e. the number of vitellogenic oocytes in the prespawning ovary) or relative (i.e. the number of eggs per unity body mass) fecundity and on the ability of biological and/or environmental factors in explaining their fluctuations. Relationships between fecundity and female age and/or size have been documented in many cod populations (Kjesbu et al., 1998, Marshall et al., 1998; Marteinsdottir et al.,2000, Kraus et al., 2000; Kraus et al., 2002; Marteinsdottir and Begg, 2002; McIntyre and Hutchings, 2003; Yoneda and Wright, 2004; III). Both fish length and weight are significantly correlated with fecundity in cod, although fish length has been usually

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preferred as predictor given the weight large fluctuation during a year cycle (Blanchard et al., 2003; Thorsen et al., 2006). The strength of this relationship varies considerably between populations (Marteinsdottir and Begg, 2002; McIntyre and Hutchings, 2003), geographical areas and years (Lambert et al., 2005), and it becomes weaker when large fish are not included in the sample (Kjesbu et al., 1998).Also in the Kattegat cod, potential fecundity is tightly linked to the fish size but length showed to have a higher predictive power than weight (III). SSB, currently used as reproductive potential predictor in stock assessment models, fails to accurately account for the effect that variation in length composition has on the stock reproductive success. The risk is the overestimation of the reproductive potential when the stock is dominated by small individuals (Marshall et al., 2006) as in the case of the Kattegat cod stock.This stresses the importance of a continuous monitoring of fecundity on a stock-specific level. Despite this awareness and the implementation of easy manageable instruments for direct fecundity measurements (Thorsen and Kjesbu, 2001; Friedland et al., 2005; Klibansky and Juanes, 2007), this kind of data is still not collected on a routine basis (Tomkiewicz et al., 2003b).

Environmental conditions and nutritional status are known to potentially have strong modifying effects on fecundity. Fish condition (Fulton’s K) and also liver index in fish like cod that primarily store energy (lipids) in the liver, are considered reliable proxies for the effect of environmental change on individual energy content and reproductive potential (Kjesbu et al., 1998; Marshall et al., 1999; Lambert and Dutil, 2000). Therefore several studies have been investigating both indices reflecting maternal energy supply as help to predict fecundity variation (Kjesbu et al., 1991; Marshall et al.,1998; Lambert et al., 2003; III). Some studies have shown that yearly averages of lipid energy (Marshall et al., 1999) or food availability (Kraus et al., 2002) can significantly improve predictions of fecundity and egg production. However when the fish condition and egg production were measured on the same fish, i.e. just before the spawning season, the correlation between them was weak, although significant (Kjesbu et al.,1998; Kraus et al., 2000; Marteinsdottir and Begg, 2002; Blanchard et al., 2003; III). In other words condition measured just prior to the start of the spawning season does not increase consistently the predictive power provided by the size alone. These results confirm the existence of a threshold in maturation process where the energy stored can be representatively used as a measure of egg production (Koops et al., 2004; Skjæraasen et al., 2006).In fecundity studies, the timing in relation to the maturation cycle is extremely important. A too early sampling may lead to biased estimations with loss of oocytes not yet recruited to the final stock. On the other hand, sampling too late may lead to the loss of oocytes, as they may have already been released. Late vitellogenesis represents the optimal phase for studying fecundity, minimizing both sources of error. To detect a biologically meaningful influence of maternal condition on egg production, condition should instead be quantified at an earlier stage of the maturation process, when energy is initially allocated to egg production (Koops et al., 2004; Skjæraasen et al., 2006; III).This threshold may be represented by the passage from endogenous to exogenous vitellogenesis during which the lipids stored in the liver are used to build up the yolk reserves in the developing oocytes (I). During this critical time, depending on the individual energetic status, investment in sexual maturation could still be reduced or

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skipped (Skjæraasen et al., 2006). Hence at a later stage, just before the spawning starts, fish size explains the largest part of fecundity variability (III), while fish condition may have a stronger effect in determining recruitment through other mechanisms, such as mate competition, spawning duration, size and number of batches and post-reproductive survival.

Beyond parental influences, variability in egg size and number can also result from adaptations to different local environment. According to life history theory, the optimal trade-off between egg size and number depends on the condition experienced by the offspring (Parker and Begon, 1986) and the quality of the habitat into which offspring will emerge may act as a selective force. In cod, comparative studies have in fact evidenced a decreased size-specific fecundity (Pörtner et al., 2001) with increasing latitude and decreasing temperature (Koops et al., 2003). In paper III potential and relative fecundity are compared between Kattegat cod and Northeast Arctic cod (NEAC) from the main spawning area in Lofoten, caught during the pre-spawning season. Cod in Kattegat show a higher size-specific potential and relative fecundity in addition to a better pre-spawning condition. However, the size of vitellogenic oocytes, which has been shown to represent about 40% of the final egg size in cod (Tyler and Sumpter, 1996), is smaller in specimens belonging to Kattegat stock. The large variability in size-specific fecundity observed between cod stocks (Lambert et al., 2003; Lambert et al., 2005) can be the result of short-term response related to the nutritional status of the fish, food availability, growth and/or environmental temperature (Lambert et al., 2003). Differences in fecundity might also be associated with different life history responses between populations, resulting in different age/size at maturity, reproductive effort, egg size and survival (Roff, 2002).However, caution is needed when comparing fecundity data from geographically separated stocks due to differences in timing of spawning peaks, which may lead to biased results. The stock of vitellogenic oocytes is reduced as the fish approach spawning and consequently fish in early maturation may have considerable larger standing stock of vitellogenic oocytes than fish just prior to spawning (Thorsen et al.,2006). In this case the oocyte diameter of the sampled Kattegat cod was smaller than found for the NEAC. This difference in oocyte size may reflect that the sampled NEAC was closer to spawning than the Kattegat cod. The difference in observed fecundity between the two stocks may therefore to some degree have been influenced by this difference in timing. On the other hand, it cannot be ignored that among the effect of the overexploitation an increased fecundity is often acknowledged (Lambert et al., 2005; Kjesbu et al., 2007), either as a density dependent effect following a release in resources competition (i.e. phenotypic plasticity) or as a selective pressure to maximize reproductive output at an earlier age. Northeast Arctic cod can be considered a relatively healthy stock, highly productive and exposed to much less fishing mortality (Ottersen et al., 2006), while Kattegat cod is suffering a very high fishing pressure and is presently at its lowest historical level (ICES, 2007). The observed difference may therefore mirror the different exploitation pattern experienced by the two stocks.A possible shift towards earlier maturation has previously been evidenced in Kattegat female cod when compared to the cod in the Sound (I). Those two subpopulations have shown marked differences in size structure and abundance (Svedäng et al., 2003;

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Svedäng et al., 2004) likely due to differences in technical regulations, whereas no genetic differences have hitherto been substantiated. Nevertheless the proportion of mature individuals per age class showed to be significantly higher in Kattegat cod, implying an earlier maturation or higher maturation rate. Moreover, in the period 1990-2006, L50 (length at which 50% of the population is mature) has decreased in the Kattegat but not in the Sound, although growth (length-at-age) seems not to differ between the two areas (Svedäng and Vitale, in preparation). These observations seem to be in contradiction with the expectation that the low cod density in Kattegat should decrease intra-specific feeding competition, improving growth (Rindorf et al., 2008). However, these results may suggest that Kattegat cod utilize surplus energy for reproduction rather than investing in growth. Hence an increase in fecundity, reflected in the production of smaller and lower quality eggs, may have occurred in the Kattegat as an effect of the exploitation rate. These outcomes raise therefore concerns about the reliability of SSB estimations used for the management of Kattegat cod. Hence as a consequence of overestimations in SSB due to erroneous maturity judgement (II) and possibly as a consequence of overlooked differences in reproductive output caused by a changed population structure, the resiliency of Kattegat cod stock might have been highly overrated and the actual situation of this stock may be much worse than presently believed.

SPAWNING AGGREGATIONS

Many of the world’s economically important fish species have evolved migratory life histories, showing ontogenetic (between nursery areas and adult populations) and seasonal (between spawning and feeding areas) shifts in distribution (Harden Jones, 1968; Metcalfe et al., 2002). Similarly, cod undertake long seasonal migrations to specific locations forming large short-lived spawning aggregations (Brander, 1975; Brander, 1994; Rose, 1993; Robinchaud and Rose, 2001). Annual movements to spawning grounds have been largely described in cod (Templeman, 1974; Bergstad et al., 1987; Rose, 1993; Bagge et al., 1994; Lawson and Rose, 2000) and a consistent number of genetic, acoustic and tagging studies have evidenced that cod may regularly home to the same spawning ground over long distances year after year, following familiar migratory pathways (Godø, 1984; Green and Wrobleski, 2000; Robinchaud and Rose, 2001; Windle and Rose, 2005; Svedäng et al., 2007).Cod populations exhibit a variety of migratory behaviours which have been recently categorized by Robichaud and Rose (2004) according to degree of migration and philopatry in four groups: (1)“sedentary resident” exhibiting strong year-around site fidelity, (2) “accurate homers” returning to spawn in a specific area, (3) “inaccurate homers” returning to spawn in a much broader area near the original site in subsequent years and (4) “disperser” presenting a random spawning migration pattern within a large area. Interestingly this study showed that the most common strategy among the North Atlantic cod populations is to be sedentary.According to a recent tagging study (Svedäng et al., 2007) also the cod stock in the Kattegat has to be included in the first category, showing a high degree of resident behaviour. Although relying on small scale migratory movements, Kattegat cod seems to have a strong tendency to home to the same location for reproductive purposes

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annually. In paper IV, the stability of the Kattegat cod spawning aggregations has been investigated combining fishery dependent and independent surveys and evidencing that cod has been aggregating and spawning in specific areas for more than 25 years, albeit in drastically reduced numbers. The analyses of data relative to the period 1996-2004 (IV) evidenced two important spawning areas in the southern part of Kattegat, one close to the entrance to the Sound and one off the coast of Falkenberg, confirming previous studies for the period 1981-1990 (Pihl and Ulmestrand, 1988; Hagström et al., 1990) and 1975-1999 (Svedäng and Bardon, 2003, Figure 4).Neighbouring areas, i.e. the bights of Skälderviken and Laholmsbukten, formerly depicted as important spawning areas, did not show any sign of spawning activity during the studied period, confirming the findings from Svedäng and Bardon (2003) who reported the disappearance of spawning aggregations from those two areas after 1990. Whether these results reflect a contraction in spatial distribution or a loss in spawning areas is hard to verify due to the lack of spatial delineation of previous investigations. Additionally a loss of spawning areas seemingly occurred in the northern part of the Kattegat, i.e. the bay of Kungsbackafjorden and north of Lasö, where Hagberg (2005) had identified large spawning aggregations. Only weak signals of spawning activities in these areas were obtained in this study (IV).

Figure 4: Study area. Dashed lines represent the 20m depth contour

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The estimations of spawners’ abundance obtained from the Swedish IBTS surveys in combination with log-book data from the Swedish cod fishery have therefore shown to be a useful tool for detecting spawning areas, providing persistent and precise geographical signals. In order to validate these findings, independent samplings of individual physiological status were carried out in the depicted spawning and non-spawning areas. The liver index (HSI) has been shown to be an unreliable measure of eggs production for individuals in pre-spawning condition (III) while it represents, together with the GSI (Tomkiewicz et al., 2003a) an accurate tool for tracking the ongoing maturation process (Morgan and Lilly, 2006; I). The monthly trends in those indices did not show any significant difference between the assumed spawning and non spawning areas in November and December, which may highlight that individuals start to aggregate approximately one month before the spawning season. From January and onwards individual GSI and HSI values were clearly higher in the assumed spawning areas, evidencing an ongoing maturation process. The energetic pattern together with the significant higher proportion of mature females, recognized by accurate ovarian histological inspection, allowed the precise localization of cod spawning segregation.

Investigations of spawning aggregations and their persistence over time are relevant for understanding the stock structure and consequently the dynamic of the studied population. In case of commercially exploited fish species, the derived increased catchability and vulnerability due to the predictable spatial and temporal associations, makes this knowledge a concern of fishery science. The highest catch rates in many commercial fisheries are in fact achieved by mobile fleets targeting spawning aggregations (Beverton, 1990; Hilborn and Walters, 1992; Hutchings, 1996). The achieved detection of spawning aggregations by the use of commercial landings (IV)clearly confirms that those spatial and temporal aggregations represent a cost-effective way to obtain profits.

The effects of fishing activity in areas where cod spawning takes place at a known time are multifaceted. Beyond the well known consequences of a size selective fishing mortality on the stock structure (Jennings et al, 2001), derived from the removal of larger and more fecund (Solemdal et al., 1995; Trippel, 1998; Tomkiewicz et al.,2003b) individuals from the population, the complex repertoire of cod reproductive behaviours is also strongly impacted. A successful reproduction in cod involves complex mating interactions, including behavioural and acoustic displays by males and mate choice by females (Brawn, 1961a and b; Engen and Folstad, 1999; Hutchings et al., 1999; Nordeide and Foldstad, 2000; Rowe and Hutchings, 2003; Rowe and Hutchings, 2004). The release of gametes is preceded by a sort of ritual “dance”. A final close physical contact (i.e. ventral mount) between the mating pair ensures a synchronized release of eggs and sperms. Reproductive physiology in fish is adversely affected by stress, as for instance the passage of the trawl, causing alterations in reproductive hormones levels, fecundity (Billard et al., 1981; Campbell et al., 1994), eggs’ quality (Kjesbu et al., 1990) and courtship performances, likely disturbing spawning synchronization and eventually decreasing the fertilization rate (Morgan et al., 1997). The production of abnormal larvae has also been observed as one of the effect following a stress (Morgan et al.,

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1999). Furthermore some studies (Morgan and Trippel, 1996; Lawson and Rose, 2000) suggested that males may arrive at the spawning ground first and that females would periodically move onto the grounds to release eggs. The different residence time and activity on the spawning grounds by males and females lead to an unequal distribution and therefore sex ratio on the spawning areas (Robichaud and Rose, 2003) and eventually to a possible differentiated fishing pressure on sexes. Altogether, the stock reproductive potential is both directly and indirectly seriously threatened by the exploitation of spawning grounds.Hence in light of the depleted state of most of the cod populations and the consequent decreased spawning biomass, information on the spatial distribution of the spawning aggregations are not only crucial for elucidating stocks’ structure but represent an useful tool for stock management. A successful management of overexploited stocks, as Kattegat cod, requires an accurate knowledge of location and timing of the spawning activity in order to minimize disturbances and excessive fishing mortality and ensuring successful reproduction, vital for rebuilding stocks to sustainable levels.

CONCLUSIONS AND IMPLICATIONS FOR MANAGEMENT

The drastic decline for more than three decades faced by the cod stock in Kattegat is now undeniable. Although environmental variability is acknowledged among those factors that can play an important role in shaping stocks’ dynamics, in the case of Kattegat cod, overfishing still remains the main cause of the present severe depletion (Cardinale and Svedäng, 2004; ICES, 2007). The objectives of fishery management are many-sided, embracing biological, economic, social and political aspects (Jennings et al., 2001). One of the main biological goals of a management scheme is to promote the recovery of overexploited stocks. This is basically achieved by allowing the stock to produce enough offspring for replacing the adult removal due to fishing activity. The implementation of increasingly restrictive TACs, accordingly to the declining abundance, has had as a main result a decreasing catch data quality (ICES, 2007). Discarding of marketable fish (high-grading) in the cod fishery and of undersized fish in the Nephrops fishery, together with misreporting, most likely contributed to an increased uncontrolled fishing mortality (ICES, 2007), showing that the present management plan is not effective in regulating catches. The last three years assessment of this stock has in fact been unable to estimate fishing mortality due to the uncertainty in catch data.The situation of Kattegat cod could be more alarming, if possible, than what is generally believed. The use of erroneous methodologies (I) for calculating the proportion of mature individuals in the population has led to a consistent overrating of the abundance of females that actually contributed to the reproductive potential for more than 20 years (II). Additionally, SSB, which is considered at an historical low level and far below the safe limit, is at present compressed to a few age classes (2-5 years) and mainly relying on first-spawners (Hutchings and Myers, 1993; Caddy and Agnew, 2003), which in turn result in a lower quantitative and qualitative reproductive output (Solemdal et al., 1995; Trippel, 1998; Tomkiewicz et al., 2003b). The increasing evidence that SSB is not equivalent in terms of egg production (Jørgensen, 1990; Kjesbu et al., 1991; MacKenzie

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et al., 1998; Trippel, 1999; Marshall et al., 2003: Kraus et al., 2002; Köster et al., 2003; Marshall et al., 2006) due to the influence that spawners’ size and condition have on recruitment success, has most likely been overlooked in the assessment analyses. Taken together, the overestimation of the stock reproductive potential may have led to the implementation of regulating measures far above the stock capacity, neglecting potential risks. The false perception of the stock status has probably masked the need of a more drastic catch control and this may partly explain the absence of any sign of recovery.Consequently a revision of Kattegat cod stock assessment models and a re-evaluation of the reference points, based on increased stock-specific biological knowledge, is strongly suggested. The use of more accurate methods, such as histological or bioenergetics analyses, for estimating the individual maturity status might integrate and reinforce the routinely used methodology during research surveys, at least in those cases when there are uncertainties. The observed stock fecundity-length relationship (III) can be used to scale estimates of spawner abundance to population egg production (Murua et al, 2003) and greatly assist the attainment of an improved assessment, although a monitoring program based on direct measurements of stock fecundity, and factors influencing it, ought to be implemented. Furthermore, the acquired knowledge on the persistence of the spawning aggregations (IV) may facilitate the implementation of a more controlled fishing activity during the spawning season. Since the year 2002 scientists have been advocating a total closure of the fishery in Kattegat area, yet remained unheard. Stocks that remain resident within a limited geographic area may be more prone to local extinction but may also be protected in a more efficient way by closing specific area to fishing (Polunin, 2002). The introduction of no-takes area has an obvious clear effect on species abundance. However the results may be comparable to year-around gear restriction, as shown by the remarkable effects that the trawling ban, applied since 1932, has had in the Sound. A total fishing ban on a limited temporal and spatial scale, as represented by spawning closures is also an effective way for protecting a stock. However such a restriction may be less successful and not lead to a decrease in total fishing mortality if it only results in an increase of the fishing effort in adjacent areas or shifted in time, as occurred in the Baltic Sea (Bergström et al., 2007). In the Kattegat as well, the closure during the first quarter of year of the bights of Skälderviken and Laholmsbukten from 2003 did not produce encouraging results (Bergström et al., 2007), which could be due to the fact that the subpopulations in these two areas have yet to recover (IV). Furthermore the closure of such a small portion of the area might not be sufficient for enhancing a recovery. On the whole, the present management scheme in the Kattegat is mainly aimed to improve juvenile survival through supplementary mesh size increase or minimum landing size, resulting in an increased pressure on the few remaining large spawners. Restoring age structure and SSB, based on temporal and spatial limitation of the fishing effort, should instead be opted for, as an appropriate recovery approach in a long-term perspective, auxiliary to conventional controls on exploitation rate and technical measures. However the management of exploited fish stock is not only an ecological but also an economic and social issue of great magnitude. Therefore the implementation of drastic regulative measures has to follow a unanimous consensus apparently difficult to achieve.

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REFERENCES

Ajiad, A., Jakobsen, T. and Nakken, O., 1999. Sexual differences in maturation of northeast Arctic cod. Journal of Northwest Atlantic Fishery Science, 25: 1-15

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Trippel, E.A., Morgan, M.J., Fréchet, A., Rollet, C., Sinclair, A., Annand, C., Beanlands, D. and Brown, L, 1997. Changes in age and length at sexual maturity of Northwest Atlantic cod, haddock and pollock stocks, 1972-1995. Canadian technical Report of Fisheries and Aquatic Science, 2157: 132 pp

Trippel, E.A., 1998. Egg size and viability and seasonal offspring production of young Atlantic cod. Transactions of the American Fisheries Society, 127: 339-359

37

Trippel, E.A., 1999. Estimation of stock reproductive potential: history and challenges for Canadian Atlantic gadoids stock assessment. Journal of Northwest Atlantic Fishery Science, 25: 61-81

Tyler, C.R., 1991. Vitellogenesis in salmonids. In Scott, A.P., Sumpter, J.P., Kime, D.E. and Rolfe, J., eds Proc. Fourth Int. Symp Reproductive Physiology of Fish. Sheffield, UK: Sheffield University Press, pp 295

Tyler, C.R. and Sumpter, J.P., 1996. Oocytes growth and development in teleosts. Reviews in Fish Biology and Fisheries, 6: 287-318.

Wallace, R.A. and Selman, K., 1981. Cellular and dynamic aspects of oocyte growth in teleosts. American Zoologist, 21: 325-343

Walsh, S.J., Wells, R. and Brennan, S., 1986. Histological and visual observation on oogenesis and sexual maturity of Flemish Cap female cod. NAFO Scientific Council Research Document 86/111: 11pp

Whitthames, P.R., Andersson, E., Greenwood, EL.,N., Lyons, B, Fonn, M. and Kjesbu, O.S., 2003. Apoptosis in regressing follicles from Solea solea and Gadus morhua.Fish Physiology and Biochemistry, 28: 91-109

Windle MJS and Rose GA, 2005 Migration route familiarity and homing of transplanted Atlantic cod (Gadus morhua). Fisheries Research, 75:193–199

Woodhead, A. D. and Woodhead, P. J. M., 1965. Seasonal changes in the physiology of the Barents Sea Cod, (Gadus morhua L.) in relation to its environment. Endocrine changes particularly affecting migration and maturation. Special Publication of the International Commission for the Northwest Atlantic Fisheries, 6: 691-715.

Wootton, R.J., 1984. Introduction: Strategies and tactics. In Fish reproduction: strategies and tactics. Edited by G.W. Potts and R.J. Wootton. Academic Press, London, UK, pp 13-33.

Yoneda, M. and Wright, P.J., 2004. Temporal and spatial variation in reproductive investment of Atlantic cod Gadus morhua in the northern North Sea and Scottish west coast. Canadian Journal of Fisheries and Aquatic Sciences, 276: 237-248

38

ACKNOWLEDGEMENTS

Gratitude is the mother of all the virtues (Cicero, Roman orator and philosopher, 106-43 BC). I am deeply grateful to Henrik Svedäng because without him I would never have started (nor concluded) my PhD. Thanks for the leadership, support and for all the great laughs…you definitively made those years much funnier. I would also like to thank Håkan Wennhage for his “short but intense” supervising and his precious help with all the “bureaucratic” aspects. A special thanks goes to Rutger Rosenberg for his valuable assistance during those years. Thanks to all the people at the Institute of Marine Research in Lysekil: to those working on board of Argos and Ancylus for their help in collecting data, despite their unwillingness in using the “lethal” formaldehyde; to Rajlie Sjöberg for all the cod otoliths she has been reading for me in those years also on short notice request; to Joakim Hjelm for his constant understanding and support; to Anne Johansson for her unlimited willingness to help me whenever I needed…thanks to all of you for your love, friendship and for letting me feeling at home since the very first day. I’m also grateful to Merete Fonn, Anders Thorsen and Olav Kjesbu at the Institute of Marine Research in Bergen (Norway) for their priceless teaching and their great hospitality.I would like to express my gratitude to the other members of the “Italienska komplott”, Michele (alias Mikälä) and Max...you have been like brothers to me, supporting and helping me in every single way. There are not enough words for thanking Björn for the joy he brought in my everyday life and for being always so lovely and supporting also during my last (totally hysterical) days, when everybody else would have instead run away. I’m really thankful to Lars Billton from “Brita och Sven Rahmns Stiftelsen” who financed my studies showing a sincere trust in the project and in my work. Further funds were supplied by the University of Rome “La Sapienza”, Italienska Kulturinstitutet “C.M.Lerici”, Kungliga Vetenskaps- och Vitterhetssamhället i Göteborg and Adlerbertska Hospitiestiftelsen. I would like to dedicate this thesis to my family and friends in Italy because this thesis represents one of the reasons why we had to live apart. I want them to know that leaving them was one of the hardest things I ever had to do. A last but important clarification for the Scandinavians: my correct name is Francesca not Fransesca or Franchesca or Franceska or Fransheska…I could list a bunch!

39

I

Evaluation of the temporal development of the ovaries in

Gadus morhua from the Sound and Kattegat, North Sea

F. VITALE*, M. CARDINALE AND H. SVEDANG

National Board of Fisheries, P. O. Box 4-453 21 Lysekil, Sweden

(Received 6 July 2004, Accepted 8 March 2005)

The gonadal development of cod Gadus morhua in the Sound and Kattegat, North Sea, was

studied by investigating their histological structure on a temporal scale by intense sampling from

September 2002 to May 2003. Different age classes were followed and the proportion mature in

each age class within each area was analysed. Based on existing maturity criteria, a modified

system, based on histological features, was developed in order to emphasize the crucial step in the

developmental process, i.e. the passage from endogenous to exogenous vitellogenesis. Only fish

that had attained exogenous vitellogenesis could be considered as being reproductively active in

the forthcoming breeding season (Kjesbu et al., 2003). The histological based maturity scale will

greatly improve the capability of separating mature from immature individuals in the studied

areas, that is fundamental for an accurate and unambiguous estimate of the spawning stock

biomass. Furthermore, the results showed a larger proportion of mature individuals per age class

in the Kattegat stock compared to the Sound stock, which implied an earlier maturity for this

stock. This difference in maturation pattern might have been related to a relaxation of competi-

tion, i.e. enhanced growth rate, as an effect of different levels of exploitation and technical fishing

regulations between the two adjacent areas. # 2005 The Fisheries Society of the British Isles

Key words: cod; histology; maturation timing; oocyte; vitellogenesis.

INTRODUCTION

Fish stocks are currently assessed using age-structured models such as virtualpopulation analysis (VPA), which estimates fishing mortality and stock biomassfrom catch, effort and survey data (Pelletier & Laurec, 1992). For a givenmanagement option within the International Council for the Exploration ofthe Sea (ICES) corresponding annual total allowable catches (TAC) are estab-lished by using estimated spawning stock biomass (SSB) as a reference point.The SSB is defined as the biomass of both sexes contributing to the reproductivepotential of the stock. Thus, accurate estimation of the proportions of spawningfishes within each age class is of vital importance for stock assessment (Marshallet al., 1998; Cardinale & Arrhenius, 2000). These proportions, defined as matur-ity ogives, rely on estimates of sexual maturity (Myers & Barrowman, 1996;Rochet, 2000a).

*Author to whom correspondence should be addressed. Tel.: þ46 0523 18743; fax: þ46 0523 13977;

email: francesca.vitale@fiskeriverket.se

Journal of Fish Biology (2005) 67, 669–683

doi:10.1111/j.1095-8649.2005.00767.x,availableonlineathttp://www.blackwell-synergy.com

669# 2005TheFisheries Society of theBritish Isles

At present, the Kattegat cod Gadus morhua L. population is considered asseverely depleted, as an effect of a prolonged period of high fishing pressure(Svedang & Bardon, 2003; Cardinale & Svedang, 2004; ICES, 2004). The stockdecline coincided with a disappearance of large spawning aggregations in thesouthern part of the Kattegat and survey data have indicated that abundance ofspawning females have dropped to very low levels in the area (Cardinale &Svedang, 2004). Most of the SSB (>95%) is compressed to a few age classes(2–5 years) (ICES, 2004). In such a critical situation, it is important to follow anddescribe the reproductive cycle, as spawning pattern and precise maturity ogivesare essential information for accurate fish stock assessments. It is also importantthat maturation patterns are followed and elucidated in commercial fish speciesthat have faced extreme fishing mortality rates during a considerable long periodof time (Olsen et al., 2004). No such studies on the temporal development andvalidation of maturity schedule for the Kattegat cod population, however, haveever been performed.Estimation of the proportion of mature fishes is highly dependent on the

actual temporal development of the gonads, which is also known to be stock-specific (Rochet, 2000b; ICES, 2004). In order to accurately estimate maturityogives in fish stocks, the maturity staging used must be accurate and unambig-uous. At present, assessment of cod populations within the ICES frameworkrelies on macroscopic scales to estimate the proportion of mature individualswithin each age class (ICES, 2004). There is a great concern about the consis-tency of macroscopic gonadal evaluation, especially with regard to the pre-spawning phase, which is difficult to discriminate macroscopically. Severalstudies, in effect, have indicated that the proportion of mature individuals maybe improperly estimated when using macroscopic scales (Dias et al., 1998; ICES,2004). Imprecision in judgement of maturity stages leads to a biased evaluationof reproductive status, and consequently, estimated maturity ogives mightbecome highly inaccurate. Therefore it appears extremely important to deter-mine at which time of the maturation cycle the discrimination between maturingand non-maturing individuals can be made. Among the alternatives approachesto assess maturity, such as oocyte size frequency distributions, the gonado-somatic index and fat content, histology is considered to be the most reliable(Kjesbu et al., 2003). Histology has shown a greater reliability than traditionalmacroscopic evaluations in separating mature from immature individuals(Murua & Motos, 1998; Saborido-Rey & Junquera, 1998; Tomkiewicz et al.,2003), because through histological studies it is possible to identify at what timethe oocytes start to build up the yolk reserves. The presence of particular yolkproteins (cortical alveoli) within the oocyte has often been considered as the first,decisive step that enables the individual fish to complete the gonadal develop-ment for the following breeding season. Under normal conditions, individuals atthis stage of gonadal development are therefore considered to be maturing(Holdway & Beamish, 1985; Saborido-Rey & Junquera, 1998; Murua et al.,2003). As previous studies have shown, however, interruptions in the spawningcycle of cod may occur, and it is important to consider that premature, as well asadult fish, could postpone gonadal development and spawning, (Burton et al.,1997; Rideout & Burton, 2000). Burton (1994) recorded fish that had beenarrested at this phase of the development (endogenous vitellogenesis). This

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kind of phenomenon is well known in other fish species such as Atlantic salmonSalmo salar L. (Johnston et al., 1987), whose gonadal development has startedbut might be interrupted and postponed during the current spawning season,and sexual maturity is attained at the very earliest in the following spawningseason. Consequently, the presence of reproductively inactive females should beconsidered when estimating maturity ogives for a specific fish stock. In addition,Saborido-Rey & Junquera (1998) have recorded an overestimation of the pro-portion of maturing cod individuals in the pre-spawning season in relation to theestimated proportion of post-spawning fish by the end of the spawning season.This overestimation of mature and maturing fish could the result of a doubtfulinclusion of individuals at the cortical alveoli stage as being considered maturingin the forthcoming spawning season.The principal aim of this study was therefore to develop a histologically based

maturity scale specific for the Kattegat cod. It was recognized that such amaturity scale must provide information about key events taking place, i.e. torecognize the significant step in the developmental process when the individualfish is ‘set in train’ to attain sexual maturity. Therefore only fish that haveattained such a developmental status can be considered as being reproductivelyactive in the forthcoming breeding season. This will improve the capability ofseparating mature from immature individuals and consequently the assessmentand management of this stock.The second aim of the study was to describe the temporal maturation pattern

for different age classes within two studied cod subpopulations in the Kattegatand the Sound by analysing the structural events taking place in the ovaries on atemporal scale. This aspect is considered as crucial for a correct planning of thetimetable of sampling of the maturity ogives to be used for stock assessmentpurposes (ICES, 2004).The cod in the Sound and Kattegat show marked differences in size structure

and abundance, the stock in the Sound being in a less depleted state than the onein the Kattegat (Svedang et al., 2003). This divergence in stock status is probablydue to differences in technical fishing regulations, as towed fishing gears havebeen forbidden since 1932 in the Sound. Although, there is no evidence of geneticsegregation between the two stocks (Knutsen et al., 2003; C. Andre, pers. obs.),the marked differences in size structure (Svedang et al., 2003), together withunpublished information from on-going tagging experiments in the area(H. Svedang, pers. obs.), supported the view of two separated possibly subpo-pulations of cod. Thus, the second aim of the study was to elucidate possibledifferences in maturation timing between the two adjacent subpopulations whosemortality rates and population structure so clearly depart from each other,whereas no genetic differentiation between the stocks has so far been evidenced(Knutsen et al., 2003).

MATERIALS AND METHODS

In order to study the timing of gonadal development prior to the next spawningseason, the proportion of mature individuals within each age class was analysed. Theindividuals were grouped into three age classes: 2, 3 and 4þ years. The oldest age groupincluded all individuals aged �4 years.

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Fish sampling took place on a monthly basis (Table I), from September 2002 to May2003 in the Kattegat and the Sound (Fig. 1), with the exception of April in both areas.Cod were collected on both commercial fishing vessels and Swedish research vessels. Thefish were processed immediately after being taken on board. For each fish, total length(LT) at 0�5 cm below, total wet mass (MT) at the nearest 0�1 g and gutted mass wererecorded. The range in LT varied between 25 and 84 cm. Otoliths (sagittae) were removedfrom all individuals sampled and transversely sectioned through the centre of the nucleus.Therefore, individual age was estimated by a single age reader, counting hyaline zones onsectioned otoliths illuminated from above against a dark background (�15).In order to avoid the tissues from disintegrating, fresh gonads were usually removed

from the fish within an hour after being taken on board. The gonads were weighed andstored in phosphate buffered formaldehyde 3�6% for 14 days before histological analysis.In case of small gonads, the whole gonad was preserved; otherwise a 5 cm long middlecross section of the right lobe was stored. Fixed sections of ovary were dehydratedthrough ascending concentrations of ethanol for a specific duration, embedded throughascending concentrations of historesin and eventually, polymerized into historesin blocksat 4� C. Transverse sections of 2–5 mm in thickness, obtained using a Leica RM2165microtome, were dried at 60� C for a short time before staining with toluidine blue 2%and 1% borax. This procedure ensured staining of structures such as the nucleus, yolkgranules and chorion with different tones of blue. The slides were inspected at differentmagnifications by using a Leica DMR light microscope. Representative stages of oocytedevelopment (Fig. 2) were photographed using a Leica DC 300 photomicroscope camera.

DATA ANALYSIS

The low sample size per age class did not allow month-by-month comparisons to bemade, and as a consequence, the collected material was merged into 2 month periods.The proportion of maturing individuals, as determined by the histological analysis, wasestimated within each age class. A generalized linear model (GLM) procedure was used inorder to estimate the effects of age, month and area (i.e. the Kattegat and Sound) on theproportion of mature individuals. In addition, difference in Fulton’s condition factor (K),K ¼MTLT

�3, was tested for the two areas among immature and mature individualsusing a GLM with age as a factor and month as a covariate. Parsimony and modelselection was evaluated using Akaike information criteria (AIC; Chambers & Hastie,1992). The AIC is computed as: AIC ( p) ¼ nln(SRes p) þ 2p � nln(n), where p is thenumber of parameters, SRes is the residual sum of squares of the model and n is thenumber of observations. The second term in AIC increases with p and it serves as apenalty for the increasing number of parameters in the model. The AIC statistic accountssimultaneously for the d.f. used and the goodness of the fit. More parsimonious modelshave a lower AIC. The error was modelled assuming the binomial distribution (immature

TABLE I. Number of analysed samples (females) per age group and area, combined into 2month periods

Age (years)September to

OctoberNovember toDecember

January toFebruary

March toMay

Kattegat 2 33 25 37 423 25 20 31 274þ 17 15 36 12

Sound 2 7 26 60 253 17 14 14 174þ 6 14 0 8

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against mature individuals). The level of significance was set at 5% for all the statisticaltests used in this study.

Kattegat

Sweden

Copenhagen Sound

12° 50′ 0″ E11° 45′ 0″ E10° 40′ 0″ E

57° 2

0′ 0

″ N

57° 2

0′ 0

″ N

56° 1

5′ 0

″ N

56° 1

5′ 0

″ N

10° 40′ 0″ E 11° 45′ 0″ E 12° 50′ 0″ E

1:860 737

FIG. 1. Study area (., sampling locations).

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RESULTS

HISTOLOGICAL STAGING SYSTEM

The oocytes were present in various states of development throughout thefolds of both ovaries, moving from the wall towards the centre of the organ(luminal epithelium). This pattern could be observed throughout the wholeorgan. This homogeneity of the ovary, documented in previous studies (Kjesbuet al., 1990), enabled just one section to be selected from each ovary, namely, inthis study, a middle cross section of the right lobe. The first developmental stepoccurring in the ovary is the oogonial proliferation. Oogonia are small in sizeand with a single nucleolus. Oogenesis begins with the conversion of oogoniainto oocytes (Kjesbu & Kryvi, 1989). These cells undergo a series of cellularmodifications preceding the ovulation.According to the histological characteristics observed under light microscopy,

seven discrete stages of the developmental process (oogenesis) were identified.

Stage 1: immatureAt this premature stage, the oocytes are small with a dense basophilic (intense

staining) cytoplasm and a central nucleus (germinal vesicle) with few large

pof

ho

n

cnr

mca

yg

(a) (b)

(d)(c)

FIG. 2. Transverse sections of cod ovaries showing oocytes at different stages: (a) primary growth, (b)

endogenous vitellogenesis, (c) exogenous vitellogenesis and (d) spent. n, nucleus; m, nucleolus; ca,

cortical alveolus; cnr, circumnuclear ring; yg, yolk granule; ho, hydrated oocyte; pof, postovulatory

follicle. Scale bar: (a) 25 mm; (b), (c) and (d) 100 mm. Toluidine blue staining.

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nucleoli around its edge (perinucleolar stage). Oogonia are always present(Selman et al., 1993; Coward et al., 2002) but they might be not visible.

Stage 2: primary (previtellogenic) growthThe size of the oocyte increases. This phase is characterized by the nucleus

undergoing major transformation such as an increase in size and the formationof multiple nucleoli, which generate large quantity of ribosomal RNA(Takashima & Hibiya, 1995). The presence of a light area around the nucleus[Fig. 2(a)] shows that cytoplasmatic changes are occurring. This weakly stainedarea is called the ‘circumnuclear ring’ (CNR) (Woodhead & Woodhead, 1965;Morrison, 1990).

Stage 3: endogenous vitellogenesis (cortical alveoli phase)At this stage, oocytes growth occurs when triggered by a gonadotropin surge

(Wallace & Selman, 1981). Prior to vitellogenesis, the ‘circumnuclear ring’ movestowards the outer part of the cell and gradually disintegrates, while the sphericaland transparent vesicles (cortical alveoli) appear in the superficial half of thecytoplasm, which is now more acidophilic (light staining).At this stage there are no yolk granules present in the cytoplasm [Fig. 2(b)].

Stage 4: exogenous vitellogenesisThis phase represents the true vitellogenesis, during which the maternal hepa-

tically derived plasma precursor, vitellogenin (VTG), is packaged into yolkprotein in the form of granules (Wallace, 1978), easily identifiable because oftheir strong reaction to the toluidine blue [Fig. 2(c)]. These bodies, intenselystained, initially appear peripherally, but as they increase in number and size,they tend to spread out together with the cortical alveoli, throughout thecytoplasm. The shape of the nucleus becomes irregular. The occurrence of thisstage means that the maturation process is in progress, and under normalconditions, the individual will develop within the current spawning season. Thenucleus is still centrally located.

Stage 5: final maturationThe final step is marked by thickening of the chorion, the migration of the

nucleus towards the animal pole and by the hydration process. The nucleus,during the final maturation, moves from the centre to the periphery (Nagahama,1983), and eventually breaks down when reaching it. The following water influx(hydrated oocyte) is probably driven by the proteolysis of yolk protein into freeamino acids and consequent osmosis (Craik & Harvey, 1987; Kjesbu & Kryvi,1989).

Stage 6: spentAt ovulation, oocytes are released into the lumen (Wallace & Selman, 1981)

while the ruptured follicles (post-ovulatory follicle) remain within the lamellae.Post-ovulatory follicles (POFs) are short-lived but readily distinguishable[Fig. 2(d)]. At the end of the spawning season, the ovary enters the spent stageand residual vitellogenic oocytes are reabsorbed (Tomkiewicz et al., 2003).

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Stage 7: restingOocytes are in stages 1 and 2. Some post-ovulatory structures, are still present

and show signs of previous spawning (Tomkiewicz et al., 2003).

TEMPORAL DEVELOPMENT BETWEEN AREAS AND AGECLASSES

Reproductively active (i.e. likely to be spawning in the forthcoming season)females were considered to be in stages 4, 5 and 6 while inactive females were instages 1, 2 and 3. The four periods studied showed an increasing percentage ofmature (active) females, with the forthcoming spawning season, in both areas(Table II). The general tendency was represented by a progression of mostlyimmature ovaries in September to October to mostly early developing inNovember to December. Ripe females were commonly observed by the end ofJanuary.In the Kattegat, all 2 year-old females were found immature (i.e. at stage 1 or

2) in September to October, whereas 20% of the females aged 3 years and 29%of the fish aged 4þ years were considered mature (Fig. 3), i.e. had startedexogenous vitellogenesis, the step that almost always leads to full maturationin the forthcoming spawning season. In November to December, the percentageof females aged 2, 3 and 4þ years found with oocytes at stage 4 were 12, 40 and80%, respectively. From the beginning of January and to the beginning ofFebruary, the proportion of sexual mature fish increased even further: 89% ofthe females aged 4þ years or more were ready to release eggs. From Februaryuntil the end of March the proportion of sexual mature females remained high.After having released all the eggs or most of them, the fish progressed into aspent stage.In the Sound, the percentage of reproductively active females aged 3 years in

September to October was 6%. In November to December the percentage ofmature individuals had steadily increased in age groups 3 and 4þ years (29 and43%, respectively). In January to February, the proportion of the studiedfemales in age groups 2, 3 and 4þ years ready to spawn corresponded to 20,43 and 75%, respectively.

TABLE II. Percentage of mature cod females per age group and area, merged into 2month periods

Age (years)September to

OctoberNovember toDecember

January toFebruary

March toMay

Kattegat 2 0 12 24 53 20 40 65 564þ 29 80 89 67

Sound 2 0 0 20 203 6 29 43 294þ 0 43 75 50

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25

20

31

27

17

14

14

17

0·0

0·2

0·4

0·6

0·8

1·0

12

36

15

7

8

3

14

60·0

0·2

0·4

0·6

0·8

1·0

33

25

37

42726

60 25

0·0

0·2

0·4

0·6

0·8

1·0

Sept to Oct Nov to Dec Jan to Feb Mar to May

Sept to Oct Nov to Dec Jan to Feb Mar to May

Sept to Oct Nov to Dec Jan to Feb Mar to May

Pro

port

ion

mat

ure

(a)

(b)

(c)

Month

FIG. 3. Proportion of mature individuals per area ( , Kattegat;&, The Sound) at ages: (a) 2, (b) 3 and (c)

4þ years. Values are means � S.E. The numbers indicate the sample size.

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DATA ANALYSIS

For both studied areas, the percentages of fish at various developmental stageswere calculated for each age class on a 2 month basis from Septemberuntil May (Table II). The initial model was: immature per mature(response) ¼ (intercept) þ age þ month þ area with LT modelled as covariate.The interaction factors were not included in the model. The LT (covariate) wasnot significant and therefore it was excluded from the final model. Results fromthe comparisons between models with different combinations of the predictorsshowed that the model including all the predictors was the best to explain thematurity status of Kattegat cod (Table III). All the analysed predictors (age,month and area) were found significant in the final GLM model (Table III). Agewas the factor explaining most of the variation in mature status. Noteworthy, inevery studied period of time, was that the percentage of reproductively activeindividuals within age group was significantly lower in the Sound area than inthe Kattegat. There was a significant difference in K between the two areasamong immature fish, with Kattegat cod having higher K than the Soundwhile no significant differences were found for mature fish. In both cases,month and age were not significant and therefore excluded from the final model.

DISCUSSION

Cod spawn many times during a single spawning season, i.e. cod femalesrelease eggs in discrete batches (Sorokin, 1957). Consequently, oocytes of vary-ing developmental stages are present within the ovary at the same time. This

TABLE III. Results from the comparisons between models with different combinations ofthe predictors. The information criteria (AIC) were used for generalized linear model(GLM) model selection, with the error modelled assuming the binomial distribution(immature against mature individuals). The Wald statistic is the homologous of the F

statistic of GLM based on the binomial distribution

Variables d.f. AIC P

Age Month Area 6 482�4 <0�001Age Month 5 488�4 <0�001Age Area 3 534�4 <0�001Age 2 541�6 <0�001Month Area 4 584�1 <0�001Month 3 604�1 <0�001Area 1 629�9 <0�001Variables d.f. Wald statistic P

Intercept 1 50�9 <0�001Age 2 84�1 <0�001Month 3 43�6 <0�001Area 1 7�9 <0�005

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asynchronous development of the ovary (Wallace & Selman, 1981), which bringsto a non-simultaneous ripening of eggs destined for spawning, is common inother commercial important marine fishes and the staging system described inthis paper may also apply to those species.Essentially, oocytes in all teleosts undergo the same basic pattern of develop-

ment: primary oocyte growth, cortical alveolus stage, vitellogenesis, maturationand ovulation (Tyler & Sumpter, 1996). The cycle of gonadal developmentdescribed in the present study has been reported for cod from many areas, anda number of different maturity scales, based on histological analyses, have beenproduced. Kjesbu & Kryvi (1989) described four main stages (primary growth,cortical alveoli formation, true vitellogenesis and final maturation). According tosome classification systems, however, some stage has been further subdivided.Recently, a 10 stage microscopical maturity scale has been proposed for theBaltic cod (Tomkiewicz et al., 2003), which includes the usual stages as well aspotential gonadal diseases that can reduce fecundity. In the present work,oogenesis was divided into seven distinct developmental stages, according tocommon histological criteria. The classification maturity scale presented in thisstudy emphasizes the difference between endogenous and exogenous vitellogen-esis, as they are considered as different stages. According to Holdway & Beamish(1985), all oocytes reaching the second stage (when the CNR appears) are likelyto mature within the subsequent reproductive cycle. Ovaries at this stage arealways present, however the probability to carry on the maturation processdepends on the degree of development in relation to the time of the year inwhich they are observed (Woodhead & Woodhead, 1965; Holdway & Beamish,1985; Tomkiewicz et al., 2003). The first structures to emerge within the oocytecytoplasm during the gonadotropin-dependent growth phase are the yolk vesi-cles; also known as ‘intravesicular yolk’ (Marza et al., 1937). These oocytescontain endogenously synthesized glycoproteins, and subsequently they giverise to cortical alveoli; therefore they are not to be considered as yolk in thestrict sense of the word (Wallace & Selman, 1981). The common use of the term‘yolk vesicle’ to describe the cortical alveoli seems inappropriate, because thecontents of these structures do not contribute to embryonic development(Wallace & Selman, 1981).Burton (1994), however, recorded fish that had been arrested at endogenous

vitellogenesis. This vital observation obviously shows that finding ovaries withoocytes at stage 3 does not necessarily imply a fish to be in an active reproductivestate in the forthcoming spawning season. Therefore, only fish containingoocytes which have developed up to the exogenous vitellogenesis phase (stage4) should be considered as sexually mature (Burton et al., 1997), i.e. they arelikely to spawn in the forthcoming season. The unawareness of this concept canlead to an overestimation of the SSB with hazardous consequences for over-exploited species such as cod.Studies on northern cod off the Canadian coast suggest that exogenous

vitellogenesis, leading to ripe gonads and spawning, must have started severalmonths (c. 7 months) before the spawning period (Burton et al., 1997). This isclearly not the case in the Kattegat and Sound, where the first individuals inwhich exogenous vitellogenesis have begun (stage 4), was at the very earliestdetectable in October, i.e. 4 months before the beginning of the spawning season.

DEVE LOPMENT OF COD OVAR I E S 679

# 2005 The Fisheries Society of the British Isles, Journal of Fish Biology 2005, 67, 669–683

A consistent amount of specimens were found to be at stage 4 by November toDecember. Consequently the temporal development of ovaries for cod in theSound and Kattegat seems to be shorter than in cod stocks off the Canadiancoast.The spawning season of most of cod populations takes place from December

until July. Along the Norwegian coast, cod spawning mostly takes place betweenFebruary and April, while the Baltic Sea cod spawns from April to July (Cohenet al., 1990). There are no differences in the spawning timing schedule betweenthe Sound and Kattegat, as in both subpopulations the spawning season starts inJanuary to February and probably finishes by the end of March. The proportionof mature individuals of every studied age group, however, was lower in theSound than in the Kattegat, implying that cod, on average, become mature at anolder age in the Sound. This difference in the maturation pattern might beconsidered as an effect of different levels of exploitation. The cod stock in theKattegat, has probably experienced a higher exploitation rate (Svedang et al.,2003).As an effect of fishing pressure, removing older and larger fishes, fishes might

adjust their life-history traits such as reproduction and growth (Rochet &Trenkel, 2003), either by phenotypic response or by genetic adjustment. Olsenet al. (2004) and Yoneda & Wright (2004) have given support to the hypothesisthat early-maturing genotypes were favoured relative to late-maturing genotypesduring the collapse of northern cod. As no genetic differentiation has been linkedto the two studied sub populations, the higher maturation rate in the KattegatAtlantic cod could thus be due to other factors such as changes in growth rate. Itis known that age at sexual maturation is positively correlated to growth rate orto the accumulation of surplus energy; fishes normally mature at the earliestopportunity (Policansky, 1983; Rowe et al., 1991; Thorpe, 1994; Sandstromet al., 1995; Svedang et al., 1996). The onset, or rather cessation of the inhibitionof the maturation process (Rowe et al., 1991) can act a various stages ofgametogenesis. The division between endogenous and exogenous vitellogenesismight be such a control at which the energetic status of the fish determineswhether the maturation will proceed or not.

The authors thank O.S. Kjesbu and M. Fonn from the Institute of Marine Research inBergen for their precious teaching and advices. The authors are also grateful to the crewon R/V Ancylus and R/V Argos for assistance in the field. Financial support for thisresearch was partially provided through grants from ‘Brita och Sven Rahmns Stiftelse’.

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II

Histological analysis invalidates macroscopically determinedmaturity ogives of the Kattegat cod (Gadus morhua)and suggests new proxies for estimating maturitystatus of individual fish

F. Vitale, H. Svedang, and M. Cardinale

Vitale, F., Svedang, H., and Cardinale, M. 2006. Histological analysis invalidates macro-scopically determined maturity ogives of the Kattegat cod (Gadus morhua) and suggestsnew proxies for estimating maturity status of individual fish. e ICES Journal of MarineScience, 63: 485e492.

Assessment and management of fish populations currently rely on correct estimation of thespawning-stock biomass (SSB), which is based on accurate maturity ogives of the popula-tion. Although maturity ogives are usually calculated through macroscopic evaluation of thegonads, histology is generally considered to be more accurate. Here we show that the mac-roscopic analysis consistently overestimates the proportion of mature females for all ageclasses in Kattegat cod. The resulting bias showed minimum values for all age classes abouta month before the spawning season. Consequently, estimation of the incidence of matura-tion in females several months before or after the spawning season can only be accurateusing histological techniques. Further, the observed bias was used to reconstruct a historicaldata set of maturity ogives of Kattegat cod. The results showed that female spawning bio-mass (FSB) might have been overestimated by up to 35%. However, as histological analysisis considered a laborious procedure, proxies of maturity status were sought. It was indicatedthat the gonadosomatic and hepatosomatic indices may serve as robust proxies for discrim-inating mature females from immature, thus greatly enhancing the accuracy of the macro-scopic maturity evaluation of cod gonads when histological analysis is lacking.

� 2005 International Council for the Exploration of the Sea. Published by Elsevier Ltd. All rights reserved.

Keywords: GSI, HSI, Kattegat cod, maturity ogives, SSB, stock assessment, tree model.

Received 16 March 2005; accepted 14 September 2005.

F. Vitale, H. Svedang, and M. Cardinale: Swedish Board of Fisheries, PO Box 4, 453 21Lysekil, Sweden. Correspondence to F. Vitale: tel: C46 0523 18743; fax: C46 052313977; e-mail: francesca.vitale@fiskeriverket.se.

Introduction

Currently, a total allowable catch (TAC) system is the prin-

cipal instrument to control stock exploitation levels for

Northeast Atlantic commercial fish stocks (ICES, 2005a).

In this context, the biomass of reproducing fish (i.e. spawn-

ing-stock biomass, SSB) is used as one of the reference

points (in concert with the level of fishing mortality) to

evaluate the status of an exploited stock and to establish fu-

ture harvest levels. In order to establish TACs, fishery biol-

ogists usually use age-structured models to estimate SSB.

These models include landings statistics and catch rates

by age class, fishing effort, survey data, and species-specific

biological parameters such as natural mortality, weight, and

proportion of mature individuals at age (Pelletier and Lau-

rec, 1992). Therefore, the proportion of mature fish of all

assessed age classes, usually defined as maturity ogives,

is a crucial variable in the SSB estimation. Errors in esti-

mating maturity ogives will lead to spurious SSB estimates,

distorting the relationship between stock and recruitment

(Murawski et al., 2001), and thereby increasing the vari-

ability of assessment results. This is especially problematic

at low levels of SSB, because the precision in assessment

projections is usually reduced at low stock levels.

Cod in the Kattegat are currently assessed as a separate

stock. Based on all the available information on SSB and

fishing mortality, the stock is at present considered severely

depleted (ICES, 2005b), the effect of a prolonged period of

high fishing pressure (Svedang and Bardon, 2003; Cardi-

nale and Svedang, 2004). According to the ICES assess-

ment in 2005, the Kattegat cod stock has been estimated

to be at its lowest levels since 1971 and around 95% of

1054-3139/$32.00 � 2005 International Council for the Exploration of the Sea. Published by Elsevier Ltd. All rights reserved.

ICES Journal of Marine Science, 63: 485e492 (2006)doi:10.1016/j.icesjms.2005.09.001

the spawning individuals belong to the first four age clas-

ses. Therefore, enhanced accuracy and precision in biolog-

ical data used for stock assessment are of crucial

importance.

For Kattegat cod, maturity ogives are estimated using in-

dividual fish data collected during the first quarter Interna-

tional Bottom Trawl Surveys (IBTS) on board the Swedish

research vessel ‘‘Argos’’. In order to determine the individ-

ual stage of sexual maturation, visual (macroscopic) staging

of reproductive organs is regularly applied. In particular,

maturity stage of cod is currently evaluated using a four-

stage scale (Table 1a), in which each gonad is judged by vi-

sual analysis of external features. However, the subjectivity

and ambiguity of the visual inspection method may lead to

severe misclassifications of fish reproductive status. Several

studies on other cod stocks have shown that histological

analysis of gonadal development is the most accurate meth-

odology to determine the individual stage of sexual matura-

tion, exhibiting more consistent results than visual staging

of reproductive organs (Murua and Motos, 1998; Sabo-

rido-Rey and Junquera, 1998; Kjesbu et al., 2003; Tomkie-

wicz et al., 2003).

In this study, visual staging of sexual maturation of Kat-

tegat cod was evaluated in concert with the newly intro-

duced and validated histological analysis of reproductive

organs (Vitale et al., 2005). By assuming that histological

examinations accurately represent the reproductive status

of individual fish, estimates of the deviation (or error) in us-

ing visual determination of maturity stage were obtained.

Because misclassifications using macroscopic analysis are

even more serious when gonads are sampled several

months prior to spawning (Kjesbu, 1991), we also analysed

the deviation within each age class on a monthly basis. This

result will assist planning of surveys used to estimate matu-

rity ogives of Kattegat cod.

We also include the results of histological analyses in

cod assessment, to estimate the possible error in SSB deter-

mined through visual inspection of gonads. In order to re-

construct the time-series of proportion of mature ogives

in each age class and evaluate the effects of the use of in-

correct maturity ogives on SSB estimation in the past, esti-

mates of deviation in visual staging of reproductive status

were applied to the historical data set of maturity ogives

(ICES, 2005a). In addition, studies on Northeast Arctic

cod showed strong arguments for using female-only spawn-

ing biomass (FSB), rather than SSB, as the independent

variable in stock-recruitment models (ICES, 2004), sug-

gesting that FSB would give a better index of reproductive

potential than SSB. For these reasons, we considered only

the female contribution to the reproductive potential of

the cod stock. Finally, histological analyses are an expen-

sive, laborious, and time-consuming procedure and put

a limit on the number of samples that can be analysed.

Therefore, we explored all available variables in searching

for proxies for estimating maturity status of individual fish.

These alternative criteria may be a way to distinguish

mature from immature females when histological analysis

cannot be performed.

Material and methods

Data collection

Cod in the Kattegat start maturing in November, peaking in

FebruaryeMarch, then enter the spent stage (Vitale et al.,

2005). In order to obtain a good temporal resolution, fish

sampling took place on a monthly basis, from September

2002 to May 2003 (with the exception of April 2003)

both in the Kattegat and the Sound (ICES Subdivisions

21 and 23, respectively), and from December 2003 to Feb-

ruary 2004 only in the Kattegat. Female cod were caught by

commercial fishing vessels and by the Swedish research

vessel ‘‘Argos’’. Sample locations and sample sizes are

shown in Figure 1 and Table 2, respectively. The fish

were processed immediately after capture. For each fish, to-

tal length (TL) to 0.5 cm below, total wet weight (TW), go-

nad (GoW) and liver weight (LW) were measured to the

nearest 0.1 g. The length ranged from 25 cm to 85 cm. Go-

nads were weighed and stored in phosphate-buffered form-

aldehyde 3.6% for 14 days before further preparation for

histological analysis. Fixed sections of ovary were dehy-

drated through ascending concentrations of ethanol, embed-

ded through ascending concentrations of historesin, and

eventually polymerized into historesin blocks at 4(C.Transverse sections of 2e5 mm thick were dried at 60(Cand stained with toluidine blue.

For each fish, we estimated Fulton’s condition factor

(CF) based on total weight as

CFZTW!TL�3!100:

Gonadosomatic (GSI) and hepatosomatic (HSI) indices

were calculated according to the following equations:

GSIZGoW!TW�1!100

HSIZLW!TW�1!100:

Otoliths (sagittae) were removed from all cod sampled

and transversely sectioned through the centre of the nucleus

for age reading. Fish were grouped into four age classes: 2,

3, 4, and 5C. The oldest age group included all cod aged 5

or more.

Sexual maturity of each cod was classified according to

a four-stage macroscopic scale (Table 1a) used in the

IBTS (ICES, 1999), as well using a microscopic scale,

based on histological analysis (Table 1b; Vitale et al.,

2005). The latter classification scheme is a seven-stage

scale that underlines the importance of the passage from en-

dogenous to exogenous vitellogenesis, which coincides

with the beginning of yolk production in the oocytes. These

486 F. Vitale et al.

two stages are hardly discernible by the naked eye and con-

sequently the most susceptible to misclassification. Burton

(1994) recorded fish with arrested maturation at endogenous

vitellogenesis. Therefore, finding ovaries with oocytes in

this phase of development (stage 3) does not necessarily im-

ply that the fish will be active reproductively during the

forthcoming season. Consequently, only fish containing

oocytes which had developed up to the exogenous vitello-

genesis phase (stage 4 and onwards) were considered sexu-

ally mature, i.e. they are likely to spawn in the forthcoming

season. All cod without yolk granules, i.e. from stage 1 to 3,

were classified as immature and judged to remain as such in

the forthcoming spawning season.

Data analysis

Comparison between visual inspection and histological

analysis of female gonads

Fish were classified as either immature or mature both by

visual and histological inspection of the gonads. The matu-

rity status of each was transformed into a binary form, tak-

ing the value ‘‘0’’ for immature and ‘‘1’’ for mature or

maturing individuals both in the histological and the macro-

scopic staging of gonads. Owing to the expected binominal

distribution of data, we used a GLMz (Generalized Linear

Model) with binomial distribution and a logit link function

to test for statistical differences between the proportions of

mature against immature individuals for each age class es-

timated by the two methods (i.e. visual inspection and his-

tological analysis of the gonads). The test was based on the

Wald statistic, which is founded on the binomial distribu-

tion and analogous to the F-statistics of GLM (General Lin-

ear Model).

The deviations in the proportion of mature individuals

per age class, resulting from the comparisons between

visual and histological inspection of the gonads, were

Table 1. (a) Macroscopic scale from the manual for the Inter-

national Bottom Surveys (IBTS) and (b) histological scale from

Vitale et al. (2005).

(a)

Virgin Ovaries small, elongated, whitish,

translucent. No sign of development

Maturing Development has obviously started, eggs are

becoming larger and the ovaries are filling

more and more of the body cavity, but eggs

cannot be extruded with only moderate

pressure

Spawning Will extrude eggs under moderate pressure to

advanced stage of extruding eggs freely with

some eggs still in the gonad

Spent Ovaries shrunken with few residual eggs and

much slime. Resting condition, firm, not

translucent, showing no development

(b)

Immature Small oocytes with a dense basophilic

cytoplasm, a central nucleus, and few large

nucleoli around their edge (perinucleolar

stage). Oogonia are always present but they

might not be visible

Previtellogenic

growth

The nucleus increases in size and multiple

nucleoli are formed. A weakly stained area

called ‘‘circumnuclear ring’’ (CNR) is also

present

Endogenous

vitellogenesis

The circumnuclear ring moves towards the

outer part of the cell and gradually

disintegrates, while the spherical cortical

alveoli appear in the superficial half of the

cytoplasm. No yolk granules present yet

Exogenous

vitellogenesis

Presence of yolk granules. The nucleus, still

centrally located, becomes irregular. The

occurrence of this stage means that the

maturation process is in progress, and under

normal conditions, the individual will

develop within the current spawning season

Final maturation The chorion becomes thicker, the nucleus

migrates towards the animal pole and the

hydration process occurs

Spent Post-ovulatory follicles (POFs), after oocytes

release into the lumen, are distinguishable

Resting Oocytes in stages 1 and 2. Some

post-ovulatory structures, still present, show

signs of previous spawning

Argos samples

Commercial samples

10 11 12 13

Longitude ºE

55

56

57

58

Lat

itude

ºN

Figure 1. Sample locations in the Kattegat and Sound.

487Histological analysis invalidates maturity ogive of the Kattegat cod

considered as an estimate of the bias or deviation from the

visual inspection method. The relative bias per age class

(RBi) was defined by the following equation:

RBiZðMVIi �MHAiÞ=MHAi;

where MVI and MHA are the percentage of mature fish ac-

cording to visual inspection and histological analysis,

respectively.

We also estimated the absolute bias resulting from the

comparison between histological analysis and visual in-

spection of gonads for each age class on a monthly basis.

The absolute bias was calculated as

ABiZMVIi �MHAi:

Re-estimation of historical SSB of the Kattegat cod stock

Maturity ogives represent the proportion of mature or ma-

turing females within each age class and were calculated as:

MOiZMFi=Ni;

where MOi is the maturity ogive, MFi is the number of ma-

ture or maturing females, and Ni is the total number of fe-

males at age i. Because historical maturity ogives (ICES,

2005b) were estimated from cod sampled between January

and March, the RBi per age class to be used for reconstructing

historical maturity ogives was calculated using JanuaryeMarch data only. Between 1971 and 1990, ICES considered

the proportion of mature individuals as constant.

The estimated RBi per age class was applied on the his-

torical data set of maturity ogives as follows:

CMOiZHMOi=ð1CRBiÞ;where CMOi and HMOi are the corrected and the historical

maturity ogives for age i, respectively. RBi for individuals

older than 5 years was assumed equal to those estimated for

5-year-old individuals. The corrected time-series (1971e2004) of female maturity ogives has been used for re-

estimating FSB of the Kattegat cod stock, and this time-

series on FSB is compared with previous estimation of

FSB (ICES, 2005b).

Alternative methods of assessing maturity: a tree-model

application

Owing to the non-linear nature of the relation between matu-

rity status of an individual fish with many morphological and

physiological state variables, we used a tree-regressionmodel

(S-PLUS, 2000) for predicting the best combination of var-

iables to determine the maturity stage of an individual fish in

the absence of histological data. Regression tree models are

based on a recursive partitioning approach, which uses a set

of predictor variables (xi) to generate a single response vari-

able ( yi) [see Cardinale and Arrhenius (2004) for an applica-

tion of themodel in fisheries and for statistical details]. In this

study, the predictors were area (Kattegat, Sound), month

(SeptembereMay), fish length (25e85 cm), fish age

(2e5C), MVI (mature, immature), GSI, HSI, and CF, while

MHA (mature, immature)was the response. In the tree-model

diagram the predicted response (MHA) is at the bottom of the

tree and the predictors come into the system at each node of

the tree. The top node contains the entire samples. Each of the

nodes beneath contains a subset of the sample in the nodes

directly above it. However, a tree model may be more com-

plex than necessary to describe the data. Therefore, after the

initial tree model has been built, a ‘‘tree-pruning approach’’

(for optimizing the number of correct predictions) and

a ‘‘shrink approach’’ (for optimizing internal deviance) are

performed. Those two functions assess the degree to which

a tree can be simplified (i.e. parsimony) without sacrificing

goodness-of-fit. The pruning function achieves parsimonious

Table 2. (top panel) Number of samples histologically analysed per month in 2003e2004 within each age class and (bottom panel) RV

‘‘Argos’’ samples from IBTS collected in JanuaryeMarch for each age class and used for macroscopic estimation of the maturity ogives

within the Baltic Assessment working group.

Age Sep Oct Nov Dec Jan Feb March May

2 18 22 22 31 31 85 30 24

3 11 31 24 49 76 58 13 10

4 1 11 13 16 23 20 4 6

5C 1 6 3 8 17 2 2

Total 30 65 65 99 138 180 49 42

Age 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004

2 69 55 41 68 45 87 100 42 95 55 77 57 47 70 20

3 20 17 96 38 32 67 52 88 32 79 60 75 48 12 74

4 15 10 9 68 11 56 25 18 39 9 34 28 60 7 17

5C 9 7 6 8 25 14 22 15 19 18 10 11 27 7 19

Total 113 89 152 182 113 224 199 163 185 161 181 171 182 96 130

488 F. Vitale et al.

state of the model by reducing the number of nodes and the

number of variables used in the initial model, whereas the

shrink function contracts each node towards its parents.

This is analogous to a stepwise procedure, where only varia-

bles that are significantly contributing to explain the null var-

iance are included in themodel (S-PLUS, 2000). Pruning can

be carried out as guided by the cost-complexity criterion or

simply by stating the desired number of final classes. For

each specific set of variables, we first constructed a so-called

complex model that used all variables and possible nodes.

This will generate a misclassification diagram where mis-

classification (or deviance) rates are indices of the good-

ness-of-fit of the model and analogous to the r2 of

regression models. Misclassification decreases with increas-

ing number of nodes and then levels off. The number of nodes

where misclassification levelled off was used to establish the

desired number of final classes (i.e. pruning approach) in the

final model, i.e. the degree a tree can be simplified without

sacrificing goodness-of-fit. Misclassification rates were

also used to compare between models.

Two different models were tested. The first model (FDC,

fishery-dependent complex model) used fishery-dependent

individual information (i.e. area and month of catch, fish

length, and age) while the second model (FIC, fishery-inde-

pendent complex model) considered fishery-independent

(i.e. survey data) individual information (area and month

of catch, fish length, and age, MVI, GSI, HSI, and CF) as

predictors of maturity stage. The fishery-dependent simpli-

fied model (FDS) and the fishery-independent simplified

model (FIS) are the two simplified models resulting from

the initial FDC and FIC models, respectively. Model vali-

dation was performed using a k-fold cross-validation proce-

dure (see Efron and Tibshirani, 1995). This consists of

randomly dividing the data set into two parts, training

and test data sets. The proportion of tested individuals vs.

the total number of samples used here was 1:3 (445 individ-

uals for training and 222 for testing). Hence, the tree mod-

els were fitted to the training data set, and thereafter the

fitted tree model was used to predict maturity stage (imma-

ture, mature) of the individuals included in the test data set.

Results

Comparison between visual inspectionand histological analysis

There were no statistical differences in the specific RBi per

age class between the two years 2003 and 2004 (General-

ized Linear Model with binomial distribution; pZ 0.18;

nZ 668). Therefore, the 2003 and 2004 data were merged

in the successive analysis. The proportion of mature against

immature individuals was statistically different for the two

methods (i.e. visual inspection and histological analysis of

the gonads) (Wald statisticZ 74.7; p! 0.001). According

to visual inspection of the gonads, the proportions of ma-

ture fish increased from 39% in age class 2 to 100% in

age class 5C (Figure 2). In contrast, the histological

analysis indicated that the proportion of mature fish in-

creased from 24% to 92% for the same age interval. In

other words, the visual inspection method consistently

overestimated the proportion of mature individuals for all

age classes (Figure 2), with RBi increasing with decreasing

age of the fish.

Older cod showed greater monthly variability in bias

than younger ones (Figure 3). On the other hand, all age

classes showed a convergence towards minimum bias in

January (Figure 3).

Re-estimation of historical FSB of the Kattegatcod stock

As a result of the overestimation of the proportion of ma-

ture individuals attributable to the inaccuracies of visual

staging, the re-estimated FSB was by definition always low-

er than the historical FSB of Kattegat cod (Figure 4a). The

re-estimated FSB showed an overestimation that varied be-

tween 21% and 35% of the historical FSB. The difference

between the re-estimated FSB and the historical FSB of

Kattegat cod significantly increases (r2Z 0.31; p! 0.05;

nZ 34) with increasing proportion of first spawners in

the maturity fraction of the population (Figure 4b). This

phenomenon was due to the observed increase in RBi

with decreasing age of the fish (see Figure 2).

Alternative methods in assessing maturity:a tree-model application

Table 3 shows the results for different regression tree mod-

els considered for classification of maturity stage of an in-

dividual fish. Numbers represent the percentages of

misclassification, i.e. the error in the models in relation to

the histological classification considered as the true gonadal

status. Hereafter, we will only refer to the results relative to

the testing models, i.e. the predictive power of the tree

model for estimating maturity stage of an individual fish af-

ter a k-fold cross-validation procedure.

0.0

0.2

0.4

0.6

0.8

1.0

2 3 4 5+0.0

0.2

0.4

0.6

0.8

1.0

Macroscopic

Histological

RBi

RB

i (

)

Figure 2. Comparison between histological and visual staging of

the gonads. Bars represent standard errors. RBi is the relative

bias per age class.

489Histological analysis invalidates maturity ogive of the Kattegat cod

In both initial complex models, i.e. FDC and FIC, a re-

duction in the number of nodes could be obtained without

significantly reducing the predictability of the model (data

not shown). The total misclassification rate of the model

was higher in FDC and FIC than for the corresponding sim-

plified models (FDS and FIS). Moreover, while FDC, FDS,

and FIC used all available variables, the only variables in-

cluded in the FIS model were GSI and HSI. FIS has the

minimum number of nodes and the lowest misclassification

rate. Hence, the use of GSI and HSI significantly increases

the power to predict maturity stage of an individual fish and

led, by comparison, to the most parsimonious model (i.e.

reduced number of nodes).

Discussion

The purpose of this study was to evaluate both existing ma-

turity staging methods and the importance of implementing

accurate and objective maturity determinations, as these are

fundamental to estimating spawning-stock biomass (SSB).

This is especially relevant for assessment and management

of overexploited populations such as the Kattegat cod

stock.

The use of the inaccurate visual inspection method for

determining the proportion of mature cod leads to an over-

estimation of the size of the reproductive part of the stock,

and, perhaps more important, to an increased and unac-

counted uncertainty in stock assessment. The use of histol-

ogy in maturity studies has become more and more

widespread as it is has become more consistent and reliable

(Kjesbu et al., 2003; Murua et al., 2003; Tomkiewicz et al.,

2003). Here we have shown that visual staging of matura-

tion tends to overestimate the gonad maturity status in Kat-

tegat female cod. The decreasing trend in relative bias with

increasing age highlights the fact that the overestimation is

more severe for first spawners.

Moreover, the visual staging method puts some con-

straints on the time when maturity surveys should be per-

formed. Some features of the gonads are not easily

discriminated by the naked eye during certain phases of

the developmental process. In particular, visual inspection

of the gonads and interpretation of gonad development

have been considered as complicated and untrustworthy be-

fore the spawning season (Kjesbu, 1991; Saborido-Rey and

0

2000

4000

6000

8000

10000

12000

14000

16000

18000

20000

1971

1973

1975

1977

1979

1981

1983

1985

1987

1989

1991

1993

1995

1997

1999

2001

2003

0

10

20

30

40

50Macroscopical FSBHistological FSBRBi

a

0.0

0.2

0.4

0.6

0.8

1.0

0 10 20 30 40

b

RB

i (

)

RBi ( )

Figure 4. (a) Relative bias (RBi) between the re-estimated (through

histological analysis) and the historical values of FSB. (b) Rela-

tionship between RBi and the proportion of first spawners in the

stock.

Table 3. Results for different tree models considered. All numbers

are percentages and represent the misclassification rates within

each age class and the total misclassification rate of the model.

Misclassification rate is a proxy of the goodness-of-fit and the

equivalent of r2 for a regression model. The number of nodes indi-

cate the complexity of the model and is associated with the number

of variables used by the model. (Acronyms for models are FDC:

fishery-dependent complex; FDS: fishery-dependent simplified;

FIC: fishery-independent complex, and FIS: fishery-independent

simplified.) n is the number of individuals.

Age FDC FDS FIC FIS

2 23.3 18.6 1.2 2.3

3 31.9 33.3 16.7 12.5

4 33.3 20.8 12.5 12.5

5C 16.7 50 16.7 16.7

Total 27.3 26.3 9.3 8.2

Nodes 55 11 22 4

n 222 222 222 222

0.00

0.25

0.50

0.75

1.00

Sept Oct Nov Dec Jan Feb Mar Apr

Month

AB

i

2

3

4

5+

Median (2-5+)

Figure 3. Monthly trend of the absolute bias (ABi) within age

classes.

490 F. Vitale et al.

Junquera, 1998). Furthermore, when spent gonads progress

to the spent/recovering phase after the spawning season,

there might be a bias towards classifying them as immature.

This is confirmed by the monthly bias trend, which illus-

trates how the risk of misjudgement, when a visual inspec-

tion is used is influenced by the time of year at which

gonads are collected. Hence, the reliability of visual judge-

ment is dependent on the time of sampling, suggesting that

the best time for performing maturity surveys, in order to

obtain reliable results and to reduce the risk of misjudge-

ment, is about a month before the spawning season. In

the case of the Kattegat cod, this corresponds to January.

Consequently, identification of mature/maturing females

several months before or after the spawning season can

only be accurately obtained by histological techniques.

The comparison between the FSB estimated according to

histologically corrected maturity ogives, and the historical

FSB derived from macroscopically estimated maturity

ogives (ICES, 2005b), revealed a consistent overestimation

of the FSB. Moreover, the degree of the overestimation was

significantly positively related to the proportion of first

spawners in the population. Considering that the SSB of ex-

ploited stocks continues to decrease, and the proportion of

first spawners usually increases as the fraction of older cod

becomes smaller, it is valuable to minimize the bias in SSB

estimates. Estimating the spawning fraction by histological

analysis is a robust way of obtaining accurate estimates of

the spawning-stock biomass of exploited stocks. Histology

has the clear advantage of allowing detailed recording of

the reproductive development occurring in ovarian cells,

leading to unambiguous interpretation of maturity status

of an individual fish.

Owing to the energetically expensive processes of matu-

ration and reproduction, considerable energy must be stored

in individual fish before reproduction. In gadoids such as

cod, lipid energy is stored primarily in the liver. Marshall

et al. (1999) found a highly significant, linear relationship

between the total number of eggs produced and total lipid

energy in Barents Sea cod. This makes liver weight, and,

consequently, the hepatosomatic index (HSI) a rapid and

inexpensive measure of spawner quality (Lambert and Dutil,

2000).

According to our results, estimates of GSI and HSI allow

the ongoing maturation process in Kattegat cod to be

tracked. In fact the model considering only GSI and HSI

had a very high classification success (around 95% of the

individuals analysed), making them useful in detailed re-

productive studies. In contrast, models including macro-

scopic evaluation criteria (MVI), TL, and CF had larger

misclassification rates, so these variables were excluded

from the final model. These results partially overlap with

those from previous studies on Baltic cod (Tomkiewicz

et al., 2003), in which TL and GSI supported stage defini-

tions, while CF and HSI were of little use for this purpose.

The contrasting results on the importance of HSI might be

due to different feeding conditions experienced by the two

stocks. Also, the more prolonged spawning season in the

Baltic, continuing for more than six months, naturally leads

to a higher temporal variation in gonad development within

the stock. Maturing Baltic cod that will eventually spawn

during the current spawning season may differ significantly

in energetic status at a certain time during the spawning

season, making indices relating to energetic status inappro-

priate for predicting the outcome of the maturation process.

In conclusion, this study was the first attempt to apply

histological analyses to the assessment of a cod stock and

to estimate the possible error in FSB estimation derived

from the use of visual inspection of the gonads. The results

clearly indicate that visual inspection of the gonads consis-

tently overestimated the reproductive potential of the stock.

This emphasizes the need to find proxies for minimizing the

error in estimating maturity ogives and consequently in as-

sessing the population when histological analysis is not fea-

sible. Therefore, HSI and GSI represent potentially reliable

indices of maturity stage useful to increase precision of vi-

sual maturity evaluation of Kattegat cod females. Improv-

ing the capability of separating mature from immature

individuals, in order to obtain a more correct estimate of

SSB, is fundamental to accurate assessment and manage-

ment of the stock. Recognition of this concept is important

in the context of attaining a sustainable fishery, and ulti-

mately, for the recovery of overexploited fish stocks.

References

Burton, M. P. M. 1994. A critical period for nutritional control ofearly gametogenesis in female winter flounder Pleuronectesamericanus (Pisces, Teleostei). Journal of Zoology, 33:405e415.

Cardinale, M., and Arrhenius, F. 2004. Using otolith weight to esti-mate the age of haddock (Melanogrammus aeglefinus): a treemodel application. Journal of Applied Ichthyology, 20: 470e475.

Cardinale, M., and Svedang, H. 2004. Modelling recruitment andabundance of Atlantic cod, Gadus morhua, in the Kattegat-east-ern Skagerrak (North Sea): evidence of severe depletion due toa prolonged period of high fishing pressure. Fisheries Research,69: 263e282.

Efron, B., and Tibshirani, R.J. 1995. Cross-validation and the boot-strap: estimating the error rate of the predicting rule. TechnicalReport, University of Toronto.

ICES. 1999. Manual for International Bottom Trawl Surveys. ICESCM:1999/D2; Addendum 2.

ICES. 2004. Report of the study group on growth, maturity andcondition in stock projections. ICES CM 2004/D:02.

ICES. 2005a. Report of the ICES Advisory Committee on fisherymanagement. ICES CM 2005/ACFM:12.

ICES. 2005b. Report of the Baltic fisheries assessment workinggroup. ICES CM 2004/ACFM:19.

Kjesbu, O. S. 1991. A simple method for determining the maturitystages of northeast Arctic cod (Gadus morhua L.) by in vitro ex-aminations of oocytes. Sarsia, 754: 335e338.

Kjesbu, O. S., Hunter, J. R., and Witthames, P. R. 2003. Report ofthe working group on modern methods to assess maturity and fe-cundity in warm- and cold-water fish and squids. Fisken ogHavet [Fisken Havet], 12: 1e140.

491Histological analysis invalidates maturity ogive of the Kattegat cod

Lambert, Y., and Dutil, J-D. 2000. Energetic consequences of re-production in Atlantic cod in relation to spawning level of so-matic energy reserves. Canadian Journal of Fisheries andAquatic Science, 57: 815e825.

Marshall, T., Yaragina, N. A., Lambert, Y., and Kjesbu, O. S. 1999.Total lipid energy as proxy for total egg production by fishstocks. Nature, 402: 288e290.

Murawski, S. A., Rago, P. J., and Trippel, E. A. 2001. Impacts ofdemographic variation in spawning characteristics on referencepoints for fishery management. ICES Journal of Marine Science,58: 1002e1014.

Murua, H., and Motos, L. 1998. Reproductive modality and batchfecundity of the European hake (Merluccius merluccius) in theBay of Biscay. Reports of California Cooperative Oceanic Fish-eries Investigations, 39: 196e203.

Murua, H., Kraus, G., Saborido-Rey, F., Witthames, P. R., Thorsen,A., and Junquera, S. 2003. Procedures to estimate fecundity ofmarine fish species in relation to their reproductive strategy.Journal of Northwest Atlantic Fishery Science, 33: 33e54.

Pelletier, D., and Laurec, A. 1992. Management under uncertainty:defining strategies for reducing overexploitation. ICES Journalof Marine Science, 49: 389e401.

Saborido-Rey, F., and Junquera, S. 1998. Histological assessmentof variations in sexual maturity of cod (Gadus morhua) at theFlemish Cap (north-west Atlantic). ICES Journal of MarineScience, 55: 515e521.

S-PLUS. 2000. Guide to Statistics. Data Analysis Products Divi-sion, vol. 1. MathSoft, Seattle, WA.

Svedang, H., and Bardon, G. 2003. Spatial and temporal aspects ofthe decline in cod (Gadus morhua L.) abundance in the Kattegatand eastern Skagerrak. ICES Journal of Marine Science, 60:32e37.

Tomkiewicz, J., Tybjerg, L., and Jespersen, A. 2003. Micro- andmacroscopic characteristic to stage gonadal maturation of femaleBaltic cod. Journal of Fish Biology, 62: 253e275.

Vitale, F., Cardinale, M., and Svedang, H. 2005. Evaluation oftemporal development of ovaries in cod (Gadus morhua) fromthe Sound and Kattegat. Journal of Fish Biology, 67: 669e683.

492 F. Vitale et al.

III

Potential fecundity of Kattegat cod (Gadus morhua) in relation to pre-

spawning body size and condition

F.Vitale1, A. Thorsen2 and O. S. Kjesbu2

1Swedish Board of Fisheries, Institute of Marine Research, PO Box 4, 45321 Lysekil, Sweden 2Institute of Marine Research, PO Box 1870, Nordnes, 5817 Bergen, Norway

The usefulness of spawning stock biomass (SSB) as a proxy for stock reproductive potential in stock-recruitment models has been increasingly undermined. Many investigations have focused on explaining the observed variability in fecundity using fish size and various indices of individual condition. In this study, the relationship between fish size, maternal condition and fecundity was investigated for Kattegat cod during the pre-spawning phase. Results show that in Kattegat cod, just prior the onset of spawning, fish length explains the largest part of fecundity variability. Fulton’s K and HSI measured just before spawning, did not substantially increase the explained variation in fecundity. These finding may corroborate the hypothesis that the energy reserves have to be measured at an earlier stage, i.e. near the start of vitellogenesis, for determining their influence on egg production. Comparisons between Kattegat and North East Arctic cod stock (NEAC) evidenced that females in the Kattegat produce more oocytes (higher size-specific fecundity), although smaller in size, per unit of body mass at a given length than NEAC females. These differences may reflect the fact that the sampled NEAC was closer to spawning than the Kattegat cod, but the adaptations to different environmental conditions and different exploitation rate experienced by the two stocks may also explain the observed divergences. These results emphasize that SSB may fail to accurately account for the length and condition effects on reproductive potential of the stock. Consequently there is a risk of overestimating the reproductive potential when the stock is dominated by small individuals as in the case of Kattegat cod stock. A monitoring program based on direct measurement of Kattegat cod stock fecundity is therefore strongly suggested in order to improve the assessment of this stock and ensure a more sounded management.

Introduction

Estimation of individual reproductive investment is central in many types of fish biology

studies. Reproductive features, namely spawners’ biomass, sex ratio, proportion of mature

females at age, fecundity, egg viability and hatching success, have a large influence on the

reproductive potential of a fish stock and vary among species, stocks, geographical areas and

years (Kjesbu et al., 2007; Marshall et al. 1998; Lambert et al., 2005).

Estimates of individual potential fecundity (i.e. the number of vitellogenic oocytes in the pre-

spawning ovary) are relatively easily obtained in determinate spawners, such as cod (Gadus

morhua), for which the standing stock of oocytes that will develop is fixed prior to the onset

of spawning with no further oocyte recruitment later during the spawning season (Kjesbu et

1

al, 1991). Despite the implementation of manageable methods for direct measurements of

individual fecundity (Thorsen and Kjesbu, 2001; Friedland et al., 2005; Klibansky and

Juanes, 2007) the collection of fecundity data has yet to be formally incorporated into fishery

management.

Nonetheless, most of the stock-recruitment models, currently used in stock assessment,

assume proportionality between the spawning stock biomass (SSB) and the total annual egg

production. Therefore SSB, estimated as the aggregated weight of mature fish in a stock, is

conventionally used as proxy for the stock reproductive potential. This relationship has,

however, been increasingly undermined for many cod stocks (Marshall et al, 1998; Marshall

et al, 1999; Kraus et al., 2002; Köster et al., 2003a; Marshall et al., 2003), as estimates of

SSB neglect the fluctuations in several important reproductive parameters, such as parental

age, condition and spawning experience (MacKenzie et al., 1998; Trippel, 1999; Marshall et

al., 2003; Köster et al., 2003b; Marshall et al., 2006).

Many studies have found a significant relationship between individual egg production and

body size (Kjesbu et al., 1998; Marteinsdottir and Begg, 2002; Lambert et al., 2005).

However the examination of size-specific fecundity in cod has shown a very large variability

between and within stocks (Kjesbu et al., 1991; Lambert et al., 2003; Lambert et al., 2005).

The observed variability can be the result of short-term response related to the nutritional

status of the fish, food availability, growth and/or environmental temperature (Lambert et al.,

2003). Differences in fecundity might also be associated with different life history responses

of population resulting in different age/size at maturity, reproductive effort, egg size and

survival (Roff, 2002).

Several investigations have focussed on explaining the observed variability in fecundity using

various indices of individual condition (Kjesbu et al., 1998; Marshall et al., 1999;

Marteinsdottir and Begg, 2002; Blanchard et al., 2003). Reproduction in fact requires a

substantial energetic investment, which needs to be traded off against growth and metabolic

maintenance. Consequently, the individual energetic state influences egg production and

individuals may skip spawning as a consequence of low condition (Burton and Idler, 1987;

Rideout et al., 2000; Rideout et al., 2005).

Furthermore, stock reproductive potential is affected by the size composition of the stock

owing that large/old spawners produce more and higher quality eggs (Solemdal et al., 1995;

Trippel, 1999; Tomkiewicz et al., 2003) and also that the number of spawning occasions

2

within the spawning season is considerably higher for bigger females than for smaller ones

(Parrish et al., 1986; Lambert, 1990). In addition, the fertilization rate is higher when bigger

males are involved in the spawning act (Hutchings et al., 1999). The Kattegat cod belong to

the cod stocks that have experienced a large decrease in abundance (>90% since 1970) due to

a prolonged exploitation (Cardinale and Svedäng, 2004). As a result the abundance of

spawning cod females in Kattegat has shifted towards fewer and younger age classes (ICES,

2007) and large spawning aggregations in the southern part have disappeared (Svedäng and

Bardon, 2003; Vitale et al., 2008).

This study represents a first attempt to investigate fecundity patterns in the Kattegat stock,

based on measurements of individual potential fecundity (i.e. total egg production) during

three consecutive pre-spawning seasons (2004, 2005 and 2006). The aim is to explore the

relationship between individual body size and potential fecundity and to investigate the ability

of age and energy related indices in describing the observed individual potential fecundity in

Kattegat cod.

Additionally, the size-specific potential and relative fecundity (i.e. number of eggs/unit body

weight) observed in Kattegat cod was compared with the North East Arctic cod (NEAC), two

stocks occurring in different environmental conditions and experiencing two different

exploitation patterns. Results are discussed in terms of different reproductive strategies under

separable ecological, environmental as well as anthropogenic influences.

Material and methods

A total of 233 specimens were caught in Kattegat (ICES SD 21) during the pre-spawning

season in December and January 2004, December and January 2005 and January 2006. For all

collected fish, the total length (L) was recorded to the nearest cm, ranging between 26 and 78

cm. Total wet weight (W), gutted weight (Wgutt), gonad weight (WG) and liver weight (WL)

were also recorded. Age was determined from otoliths and ranged between 2 and 5 years.

Subsamples of the gonads were stored in 3.6% buffered formaldehyde for a minimum of 14

days for histology and fecundity measurements. Histological analyses (see Vitale et al., 2005)

verified that no hydrated oocytes or ovulated eggs were present in the gonads, confirming the

pre-spawning stage of the gonads.

3

Individual Fulton’s somatic condition factor (K), Gonadosomatic and Hepatosomatic (HSI)

indices were calculated, using the following formula:

K=Wgutt*L (-3)*100 (1)

HSI = WL * 100*W(-1) (2)

GSI = WG * 100*W(-1) (3)

The reliability of the exponent in the K equation was verified through annual linear

regressions.

The fecundity was measured using the auto-diametric fecundity method (Thorsen and Kjesbu,

2001), which is based on the principle that the oocyte density is directly proportional to the

oocyte diameter, linked by a power curve relationship.

Only oocytes that were in cortical alveoli or vitellogenic stage were counted and the oocyte

diameter (OD, defined as the average of ellipse major and minor axis) was measured for 200

oocytes per sample. The potential fecundity (Fp) was calculated according to the formula:

Fp= WG (g) * 2.139*1011* OD-2.700 (�m) (4)

within the size interval: 300 � OD � 735 �m

The individual relative fecundity (i.e. number of eggs/unit body mass) was calculated as:

Fr= Fp* W(-1) (5)

A generalized linear model (GLMZ), family gamma and log-link function, was used to test if

there were differences in Fp between samples collected in different months and years. Fp was

set as dependent variable, year and month as factors and L as covariate. GLMZs were run

using SPSS software.

To investigate the relationship between Fp and possible predictors a series of generalized

linear models (GLMZs) with gamma response (Fp) distribution and log-link function were

used. The model was defined accordingly:

Fp ~ ß1*X1 + ß2*X2 + ß3*X3+ ß0

4

where ß0 is the intercept and ß1, ß2 and ß3 are the coefficients for each variable included in the

model.

Owing the autocorrelation between the fish size variables, L and W were never included in

the same model. Therefore, for the first two model runs only size variables (either L or W)

were included as predictors. In the subsequent runs, other predictors (K, HSI and age) were

added one at a time to determine whether they explained a significant amount of variation in

fecundity additional to that attributed to body size alone.

The proportion of explained variation (PEV), equivalent to R2, for each fitted model was

calculated as:

PEV=(null deviance –residual deviance)/null deviance

where null deviance is the explained variation in the response variable before adding a

predictor while residual deviance is the variation in the response variable still not explained

after the addition of a predictor. The statistical analyses were carried out using the r- software

(freely downloaded at www.r-project .org/).

Additional samples of female cod were caught at Andenes (Lofoten) during the pre-spawning

season in early March 2003 and late February 2004 ( see Thorsen et al., 2006). The specimens

were characterized as belonging to the North East Arctic (NEAC) cod stock by using otolith

morphology as stock discriminating factor (Rollefsen, 1934).

Given the large differences in size range between the Kattegat and NEAC cod samples

(Fig.1), data were filtered and only individuals between 54 and 78 cm (34 and 41 specimens

for the Kattegat and the NEAC stocks, respectively) were retained in order to obtain a

comparable size interval. A GLMZ with Fp (or Fr) as dependent variable, month and year as

factors and length as covariate was used for testing potential differences in samples from

different months or years. No significant differences were found so data from different

months and years in these sub-samples were combined.

The individual potential and relative fecundity at length in the two stocks were thus explored

and compared. Furthermore, the average OD, HSI, GSI and Fulton’s K at length was

examined and comparisons between the stocks were made. The differences were tested using

5

t-Test for independent samples performed using Statistica software. Levene’s test was used

for testing the homogeneity of variances.

Results

The first GLMZs revealed a significant (p<0.05) year effect on Fp, while no significant

difference (p>0.05) was detected between months. Specimens collected in different months

were hence merged and the results from the GLMZs for different years are shown in table 1.

Overall, fish size was able to explain the major fraction of the observed variance in fecundity

for all the years analysed. No substantial increase in the explanatory power was observed

when adding fish condition indices to the model built with length alone.

Body size, specifically length more than weight (87%, 81% and 78% against 76% 73% and

73% respectively for 2004, 2005 and 2006), was the best predictor of fecundity in all year

examined explaining more variation, in terms of PEV.

Neither somatic Fulton’s K nor HSI increased the explained variation in fecundity

substantially when added to the fecundity-size (either L or W) models, although significant in

some years. Age was not indicated to be significant and therefore excluded from the models.

In 2004, the K was not significant when included in both fecundity-size models while the

inclusion of HSI to the fecundity-length model corresponded to an increase of 2% in the

explained variance. The addition of HSI to weight-fecundity model increased the explained

variation of 6% although the total explained variation was lower than the model with length

alone.

When considering samples from 2005 an increase of the explained variation by 1% could be

observed after the inclusion of both K and HSI (in separate runs) in the length-fecundity

models. The inclusion of K in the weight-fecundity model resulted in no increase of the PEV,

while an increase on PEV by 1% was detected when adding HSI, although non significant. In

the analyses of samples from 2006, neither K nor HSI were significant.

The results from the comparison between specimens from Kattegat and NEAC cod are shown

in Figure 2, including potential and relative fecundity, oocyte diameter and somatic Fulton’s

K values. Size specific Fp (p<0.05), Fr (p<0.001), K (p<0.001) and oocyte diameters

(p<0.001) differed significantly between the two stocks. No significant differences were

detected in size-specific HSI or GSI. Specimens belonging to the NEAC cod stock showed

6

lower Fp, Fr and Fulton’s K values and a higher oocyte diameter than Kattegat cod in all

length classes.

Discussions

An increasing number of researches have shown that SSB is a rather biased measure of stock

reproductive potential, because it does not take into account stock-specific features that can

produce different number of recruits at the same spawning biomass level (Saborido-Rey et al.,

2004, Marshall et al., 1998; Marshall et al., 2006).

Many studies have concentrated on correlations between indicators of energy reserves and

potential fecundity and different contributive predictive powers have been found for different

species and stocks of the same species, highlighting that the importance of any factor can

differ between species, stocks and geographical areas (see Lambert et al., 2003 for a review).

In this study, potential fecundity of Kattegat cod was shown to be more tightly coupled with

body length (78-87 % of variance explained), than with weight (73-75%). Fish size is without

doubt the factor which at present time has been distinguished as most closely related to

potential fecundity in cod stocks (Kjesbu et al. 1998; Kraus et al. 2000; Marshall et al. 1998).

Although weight is generally more correlated with fecundity, length has often been preferred

(Blanchard et al., 2003; Thorsen et al., 2006) considered that in cod weight can show large

seasonal variations (Eliassen and Vahl, 1982; Lambert and Dutil, 1997b; Schwalme and

Chouinard, 1999). However, the strength of the relationship between potential fecundity and

length varies significantly between stocks (Marteinsdottir and Begg, 2002, Lambert et al.,

2005) reflecting different environmental conditions and stock characteristics. Furthermore the

relationship becomes weaker when large fish are not present (Kjesbu et al., 1998). This

stresses the importance of stock-specific investigations, especially in stocks which are subject

to heavy size-selective fishery which eventually lead to a change in population’s structure in

concomitance with the disappearance of larger and more fecund individuals (Solemdal et al.,

1995; Trippel, 1999; Tomkiewicz et al., 2003).

In cod, Fulton’s K and HSI, mirroring total energy and lipid content respectively (Lambert

and Dutil, 1997 a and b), are often scrutinized for their explanatory power in the observed

fecundity variability (Marteinsdottir and Begg, 2002; Marshall et al.; 1998; Kraus et al.,

2000). For Kattegat cod, the inclusion of Fulton’s K and HSI measured just before spawning,

showed no substantial increase of the explained variation in fecundity, compared to the

7

variation explained by length alone. This result is in accordance with previous studies (Kjesbu

et al., 1998; Lambert and Dutil, 2000; Kraus et al. 2000; Marteinsdottir and Begg, 2002;

Blanchard et al., 2003) in which, despite the fish condition had a significant effect on

fecundity, the explanatory power was generally low. On the contrary, some studies have

shown that yearly averages of lipid energy (Marshall et al., 1999) or food availability (Kraus

et al., 2002) can significantly improve predictions of fecundity and egg production.

Difference in the relative energy investment per egg between stocks and years can influence

the fecundity-length relationship (Lambert et al., 2005). It is well known that fish in poor

condition, because of low food availability or changes of metabolism caused by adverse

temperature, can have reduced fecundity or they can fail completely the maturation process

(Kjesbu et al., 1991; Burton et al., 1997; Marshall et al. 1998). Hence the well-being of a fish

is definitively important but the critical phase for influencing the egg production occurs after

the feeding period, before the onset of maturation processes and the nutritional status may act

as a control mechanism early in the oogenesis (Kraus et al., 2002; Lambert et al., 2003). The

low contribution of K and HSI on fecundity found in our study in and previous investigations

(Kjesbu et al., 1998; Kraus et al., 2000; Marteinsdottir and Begg, 2002) is therefore likely due

to the fact that physiological measurements were taken at a too advanced stage of the

maturation process. In order to detect the influence of maternal condition on fecundity, the

condition is better quantified several months prior to spawning when the stored energy is

initially reallocated to oocyte production (Koops et al., 2004; Skjæraasen et al., 2006). In our

study we were not able to investigate the influence of maternal condition long before the

onset of spawning but we can certainly conclude that two months before spawning, fish

length is the only factor that biologically matters in the assessment of egg production in

Kattegat cod.

This study showed significant differences in oocyte number and size between the Kattegat

and the NEAC cod stocks within the same length interval. Females in the Kattegat produce

more oocytes (higher size-specific fecundity), although smaller in size, per unit of body mass

at a given length than NEAC females. No differences were detected in the HSI but cod in the

Kattegat were in a significantly better pre-spawning condition in term of Fulton’s K.

The different environmental condition experienced by cod in the Barents Sea may partly

explain the larger oocyte size, lower fecundity and lower condition in comparison with

Kattegat cod, confirming previous studies showing a decreased fecundity with increasing

latitude (Pörtner et al., 2001; Lambert et al., 2005) and decreasing temperature (Koops et al.,

2003). The variability in fecundity within the same species can be a result of adaptations to

8

different environmental conditions (Whittames et al., 1995), and the quality of the habitat into

which offspring will emerge may act as a selective force on propagule size (Parker and

Begon, 1986). Any increase in egg size, results in a decrease in egg numbers (Svärdson,

1949) with the optimal trade-off depending on the conditions experienced by the offspring

(Parker and Begon, 1986).

However the timing in fecundity studies is extremely important in relation to the maturation

cycle. Caution is needed when comparing fecundity data from geographically separated

stocks due to differences in spawning peak, and consequently, shifted maturity stages

occurrence will lead to biased results. The stock of vitellogenic oocytes is reduced as the fish

approach spawning and consequently fish in early maturation may have considerable larger

standing stock of vitellogenic oocytes than fish just prior to spawning (Thorsen et al., 2006).

In this case the oocyte diameter of the sampled Kattegat cod was smaller than found for the

NEAC. This difference in oocyte size may reflect that the sampled NEAC was closer to

spawning than the Kattegat cod. The difference in observed fecundity between the two stocks

may therefore to some degree have been influenced by this.

Moreover increased fecundity is often hypothesized to result from increased exploitation of

stock to compensate higher adult mortality and shorter life span (Lambert et al., 2005).

Therefore the differences in reproductive investment between the two stocks observed in the

present study may also be a result of the different exploitation patterns experienced by those

two stocks (Rijnsdorp, 1994; Trippel, 1995; Rochet, 1998). The lack of historical fecundity

data in the Kattegat does, however, preclude a rigorous test of this hypothesis. North East

Arctic cod can be considered a relatively healthy stock, highly productive and exposed to

much less fishing mortality (Ottersen et al., 2006), while Kattegat cod is suffering a very high

fishing pressure and is presently at its lowest historical level (ICES, 2007). As an effect of

size-selected fishery the age composition in Kattegat, as in most Atlantic cod stocks, is

strongly biased towards young fish, and as a consequence, reproduction in largely dependent

on first spawners (Hutchings and Myers, 1993; Caddy and Agnew, 2003).

It has been shown for many fish stocks that first spawners have a lower reproductive success

than repeat spawners due to their smaller size. They produce relatively fewer and smaller

eggs, which are less costly and have a lower quality, viability, fertilization rate and hatching

success (Tomkiewicz et al., 2003 and references therein). Therefore an excessive removal of

older and larger individuals from a stock may be more important than changes in absolute

spawning biomass (Scott et al., 1999).

9

10

The SSB, currently used as fecundity predictor in stock assessment models, fails to accurately

account for the effect that variation in length composition has on reproductive potential of the

stock, and consequently leads to an overestimation of the reproductive potential when the

stock is dominated by small individuals (Marshall et al., 2006) as in the case of Kattegat cod

stock. A previous study has already shown that the biomass of spawner females in Kattegat

cod might have been consistently overestimated for a period of more than 20 years because of

erroneous methods in maturity judgement (Vitale et al., 2006). Regarded as a whole the

resiliency to exploitation of Kattegat cod might have been highly overrated, therefore a re-

examination of the stock-recruitment relationship in this stock is strongly suggested. The

fecundity-length relationship found in this study can be used to scale estimates of spawner

abundance to population eggs production (Murua et al., 2003) and greatly assist the

attainment of an improved assessment of the Kattegat cod stock and hence support the

implementation of an improved and more realistic fishery harvesting strategy.

Considering the reducing effect of a size-selective fishing on the size range of spawning fish

(Jennings et al., 2001) and consequent implications on recruitment success, a continuous

monitoring of the specific reproductive potential on a stock-specific base ought to be

enhanced.

Yea

rn

Mod

elß0

pß0

ß1p

X1

ß2p

Kß3

pH

SIdf

PEV

2004

45Fp

~L8.

14<

0.00

10.

073

<0.

001

440.

87Fp

~W10

.43

<0.

001

0.00

1<

0.00

144

0.76

Fp~L

+K7.

21<

0.00

10.

071

<0.

001

1.27

ns43

0.87

Fp~W

+K9.

66<

0.00

10.

001

<0.

001

0.97

ns43

0.76

Fp~L

+HSI

8.10

<0.

001

0.06

2<

0.00

10.

106

<0.

0143

0.89

Fp~W

+HSI

9.82

<0.

001

0.00

1<

0.00

10.

163

<0.

001

430.

82

Fp~L

+K+H

SI7.

53<

0.00

10.

062

<0.

001

0.78

ns0.

100

<0.

0142

0.89

2005

97Fp

~L8.

57<

0.00

10.

064

<0.

001

960.

81Fp

~W10

.79

<0.

001

0.00

1<

0.00

196

0.73

Fp~L

+K7.

30<

0.00

10.

068

<0.

001

1.23

<0.

0195

0.82

Fp~W

+K10

.96

<0.

001

0.00

1<

0.00

1-0

.19

ns95

0.73

Fp~L

+HSI

8.40

<0.

001

0.06

2<

0.00

10.

063

<0.

0595

0.82

Fp~W

+HSI

10.6

0<

0.00

10.

001

<0.

001

0.05

1ns

950.

74

Fp~L

+K+H

SI7.

27<

0.00

10.

066

<0.

001

1.12

<0.

010.

053

<0.

0594

0.83

2006

87Fp

~L8.

36<

0.00

10.

062

<0.

001

850.

78Fp

~W10

.32

<0.

001

0.00

1<

0.00

185

0.73

Fp~L

+K8.

33<

0.00

10.

062

<0.

001

0.03

ns84

0.78

Fp~W

+K10

.70

<0.

001

0.00

1<

0.00

1-0

.46

ns84

0.73

Fp~L

+HSI

8.25

<0.

001

0.06

3<

0.00

10.

022

ns84

0.78

Fp~W

+HSI

10.3

2<

0.00

10.

001

<0.

001

-0.0

005

ns84

0.73

Fp~L

+K+H

SI8.

26<

0.00

10.

063

<0.

001

-0.0

1ns

0.02

2ns

830.

78

Tabl

e 1:

GLZ

Ms

resu

lts. ß

1 is

the

leng

th (L

) or W

eigh

t (W

) (de

pend

ing

on th

e m

odel

) coe

ffic

ient

. ß2

and

ß3 a

re re

spec

tivel

y th

e Fu

lton’

s K

and

H

SI c

oeff

icie

nts.

n re

pres

ents

the

sam

ple

size

.

11

12

Kattegat NEAC10 20 30 40 50 60 70 80 90 100 110 120

Length (cm)130 140

0

20

40

60

80

100

120

Freq

uenc

y

Figure 1: Length distributions of the samples showing the overlapping size range.

Figu

re 2

: Ave

rage

d po

tent

ial (

Fp)

and

rela

tive

(Fr)

fec

undi

ty, o

ocyt

e di

amet

er (

OD

) an

d Fu

lton’

s K

at g

iven

leng

th in

terv

als

in K

atte

gat a

nd

NEA

C st

ocks

. Bar

s rep

rese

nt st

anda

rd e

rror

s. Th

e sa

mpl

e si

ze is

show

n on

ly in

the

first

gra

ph.

200

400

600

800

54-58

59-63

64-68

69-73

74-78

Leng

th (c

m)

Mean OD (�m)

2

38

129

211

1411

3

0

300

600

900

1200

1500

Fr (n eggs/gram)

0.6

0.81

54-58

59-63

64-68

69-73

74-78

Leng

th (c

m)

Fulton's K (g/cm3)

02468 Fp (millions)

Kat

tega

tN

EAC

13

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19

IV

Available online at www.sciencedirect.com

Fisheries Research 90 (2008) 36–44

The spatial distribution of cod (Gadus morhua L.) spawninggrounds in the Kattegat, eastern North Sea

F. Vitale ∗, P. Borjesson, H. Svedang, M. CasiniSwedish Board of Fisheries, Institute of Marine Research, P.O. Box 4, S-453 21 Lysekil, Sweden

Received 12 April 2007; received in revised form 30 August 2007; accepted 14 September 2007

Abstract

Similar to many other commercial marine fish species, Atlantic cod (Gadus morhua L.) migrate towards specific sites at spawning. Thesetemporal aggregations are generally the most targeted by the commercial fishery. The Kattegat cod has undergone a substantial reduction over thepast 25 years and both stock size and spawning stock biomass have remained at very low levels since the end of the 1990s. There is, therefore, anurgent need to map and document spawning grounds still in use. In the present study, spawning sites of Atlantic cod were identified in the Kattegatusing a combination of commercial and fishery independent data from 1996 to 2004. Moreover, putative spawning and non-spawning areas werealso sampled before and during the reproductive season between 2002 and 2006, and the proportion of mature females together with the individualphysiological status were used to validate and strengthen the spatial analyses.

The spatial analyses identified several spawning areas in the region and two areas in the southeastern part of the Kattegat which appeared tobe the most important. The results showed the presence of cod spawning aggregations, although reduced in size, in areas that have been utilizedfor more than 25 years according to historical information. Some local spawning grounds may have also disappeared. The proportion of maturefemales was higher in putative spawning than in non-spawning areas (p < 0.001) and females from spawning areas had higher gonadosomatic(p < 0.05) and hepatosomatic (p < 0.001) indices than those from non-spawning areas.

Knowledge of stock spatial and temporal distribution is essential in designing recovery strategies for depleted fish populations. The unambiguousstability of the locations of spawning aggregations over time, as shown in this study, represents a useful aid in order to efficiently implement arecovery plan for the collapsing cod stock in this area.© 2007 Elsevier B.V. All rights reserved.

Keywords: Gadus morhua; Kattegat; Spawning grounds; Physiological indices; Stock management

1. Introduction

Many commercially important fish species are highly migra-tory, moving over a life cycle between nursery, feeding andspawning areas (Harden Jones, 1968; Secor, 2005). Atlanticcod is among those species that may seasonally cover longdistances. The persistence of spawning activities over time at cer-tain locations is well documented for many cod stocks: geneticand large-scale tagging studies have shown pre-spawning fishto follow established migratory pathways and to return to thesame locations every year (Brander, 1975; Ruzzante et al.,1999; Green and Wroblewski, 2000; Robichaud and Rose, 2001;Wright et al., 2006).

Information of the spatial distribution of spawning groundsis crucial for studies and inference on stock structures, and

∗ Corresponding author. Tel.: +46 523 18792; fax: +46 523 13977.E-mail address: francesca.vitale@fiskeriverket.se (F. Vitale).

therefore also for fisheries management (Frank and Brickman,2001; Smedbol and Stephenson, 2001). Fishing to a highdegree has traditionally been directed towards various spawn-ing grounds. The temporal and spatial concentration of adultfish may thus increase vulnerability of a stock unit to fish-ing activities. Considering the fact that the highest catch ratesare commonly achieved by mobile fleets targeting spawningaggregations (Hutchings et al., 1999), information on spatialand temporal distribution of spawning grounds is vital, espe-cially for stocks that suffer from prolonged over-exploitation,and whose reproductive capacity may have become seriouslyhampered.

Similar to many other cod stocks, the Kattegat cod is in aseverely depleted state (Svedang and Bardon, 2003; Cardinaleand Svedang, 2004; ICES, 2006). The stock has been consid-ered outside safe biological limits since 2000, and from 2002and onwards, the ICES Advisory Committee for Fisheries Man-agement (ACFM) has recommended a zero take from the area.

0165-7836/$ – see front matter © 2007 Elsevier B.V. All rights reserved.doi:10.1016/j.fishres.2007.09.023

F. Vitale et al. / Fisheries Research 90 (2008) 36–44 37

The Kattegat cod is thus covered by the EC recovery plan whichnonetheless allows a Total Allowable Catch.

Before the decline, spawning cod could be found throughoutthe Kattegat, but the southern part was generally recognized asthe main spawning area, especially the bay of Skalderviken andLaholmsbukten (Pihl and Ulmestrand, 1988; Hagstrom et al.,1990; Svedang and Bardon, 2003). Historically, large spawningaggregations were also observed in the bay of Kungsbackafjor-den and north of Laso (Hagberg, 2005). The stock declinecoincided with the disappearance of large spawning aggrega-tions and the abundance of adult fish in the area has dropped tovery low levels (Cardinale and Svedang, 2004). It is therefore anurgent need to map and document current cod spawning groundsin the Kattegat.

Information on the location of spawning cod has hithertobeen mainly based on research bottom trawl data (Pihl andUlmestrand, 1988; Hagstrom et al., 1990; Hagberg, 2005). Thisinformation, as well as more recent data collected by the Interna-tional Bottom Trawl Survey (IBTS), is limited by low spatial andtemporal coverage. Commercial data on the other hand, can offerhigh coverage but generally suffer from poor spatial resolution.The aim of the present study was to identify putative spawn-ing grounds for cod in the Kattegat by using a combination ofcommercial and research bottom trawl data. The distribution ofreported commercial catches during the spawning season wasused as proxy for adult cod aggregations. It was hence conjec-tured that spawning and non-spawning areas could be depictedby combining the log-book data from the Swedish cod fish-ery with abundance estimates of spawning cod obtained fromsurveys. In order to strengthen and validate our findings, we com-pared maturity status and energetic indices of individual femalesbefore and during the spawning season from the putative spawn-ing and non-spawning areas. Finally, the findings were discussedwith respect to their relevance for fisheries management.

2. Materials and methods

2.1. Spatial analysis

Data on Swedish commercial landings of cod in Kattegat(Fig. 1) from 1996 to 2004 were provided by the Swedish Board

Fig. 1. Map showing the study area. Dashed lines represent the 20 m depthcontour.

of Fisheries. Only data from the first quarter of the year wereused for mapping, as the spawning of cod in Kattegat mainlytakes place from January to March (Vitale et al., 2005). Basedon set position, landings of cod (in kg) from the three major bot-tom trawl fisheries (two cod bottom trawls and one Nephropstrawl) were aggregated in a grid of ∼10 by 10 km (5× 5 nauti-cal miles). These fisheries were selected because of their widespatial coverage and large contribution (80–92%) to the totallandings (Table 1). All squares from which landings had beenreported at least once were included in the analysis. In yearswhen no landings were reported in a specific square, this square

Table 1Data on the Swedish cod fishery in the Kattegat (ICES Subdivision 21) during 1996–2004

Year All year Landings during the 1st quarter

Quota (tonnes) Total landings (tonnes) Total landings (tonnes) Three largest fisheries (tonnes) % of total

1996 2850 2334 1355 1150 851997 3150 3303 1774 1475 831998 2780 2509 1050 843 801999 2590 2540 1326 1150 872000 2567 1568 663 608 922001 2300 1191 603 546 912002 987 744 437 373 852003 852 603 325 297 912004 505 575 389 352 91

Yearly quota and total reported landings obtained from ICES (2006). For the 1st quarter total landings (in tonnes) and landings for the three dominating bottom trawlfisheries are presented (in tonnes and as percentage of total landings).

38 F. Vitale et al. / Fisheries Research 90 (2008) 36–44

Table 2Summary of the International Bottom Trawl Survey (IBTS) data used in the study. Catch and Subsample are expressed in number of fish (N)

Year No. hauls Time of year Catch (N) Subsample (N) No. spawning cod/hour (mean±S.D.)

1996 25 29 January–13 February 4711 565 19.1 ± 27.21997 22 27 January–12 February 2853 519 34.2 ± 57.11998 22 26 January–09 February 6491 543 34.2 ± 77.71999 23 25 January–10 February 4670 553 24.5 ± 37.82000 23 24 January–10 February 3616 508 11.4 ± 152001 22 22 January–08 February 1354 445 7.1 ± 9.22002 22 21 January–07 February 1735 522 19.6 ± 63.32003 22 27 January–12 February 650 272 3.2 ± 7.52004 22 26 January–09 February 1401 508 21.3 ± 52.2

was assigned the value of zero, hence the analysis relied onlyon survey data. Within years, data were standardized to generatedistributions with a mean of zero and a standard deviation of one(0,1).

The spatial distribution of sexual mature or spawning codover the same period of time was based on information gath-ered by the International Bottom Trawl Survey (IBTS; Table 2).To estimate the number of spawning cod caught per hour ineach haul, data on catch per unit effort (CPUE) were combinedwith the proportion of sexually mature, running cod ≥30 cm(obtained from a sub-sample of the catch). Within years, datawere standardized to generate distributions of (0,1).

Spatial interpolation was done using Thiessen polygonsbased on the position of the trawling stations and data weretransferred to the same 10 km× 10 km grid used for the com-mercial landings, excluding those grid cells that did not havetheir centre within a polygon. The shape of the Thiessen poly-gons varied somewhat between years because the number andpositions of trawling stations differed between surveys, how-ever this does not affect the analysis. Putative spawning groundswere depicted by calculating and mapping the arithmetic meanof the two standardized grids based on commercial and fisheryindependent (IBTS) data, respectively.

For the commercial data set, measures of spatial autocorre-lation based on Queen’s connections were computed using theGeoDA software (Anselin, 2004). We used univariate Moran’sI to evaluate if observed data was spatially aggregated withinyears, and pair-wise comparisons (multivariate Moran’s I) toexamine whether these areas persisted over time. The signif-

icance of trends found in the data set was evaluated using arandomisation test. Owing to the small sample size of the IBTSdata, used to generate abundance maps on spawning adults (seeTable 2), no attempt was made to estimate spatial autocorrelationfor this data set or for the combined maps.

2.2. Physiological investigations

Altogether 1089 female cod were collected on board com-mercial trawlers and the Swedish research vessels “Argos” and“Ancylus” between November and January 2002–2006. In 2003samples were also collected in February and March. Total length(LT, cm) to the lowest 0.5 cm, whole body mass (M, g), guttedbody mass (GM, g), liver (ML, g) and gonad mass (MG, g) tothe nearest 0.1 g, were recorded on board. However, gutted bodymass in November–December 2002 and November–December2004 was not recorded, and was therefore calculated by the linearregression (GM = 0.8426×M + 11.676; R2 = 0.993), obtainedfrom the data collected in December 2003 and 2005. Gonads andotoliths (sagittae) were stored and analysed as described in Vitaleet al. (2005). Based on a 7-stage scale for gonadal development(Table 3), females were classified as either immature (stage 1–3)or mature (stage 4–7). Individual age was estimated by count-ing hyaline zones on sectioned otoliths. All age estimates weremade by a single reader.

Based on haul position, each trawl haul was mapped and clas-sified as inside (entirely within black areas) or outside (entirelywithin white areas) a spawning ground according to the averagemap of identified spawning grounds (Fig. 3, upper panel on the

Table 3Histological maturity scale

1. Immature Small oocytes with a dense basophilic cytoplasm, a central nucleus and few large nucleoli around its edge (perinucleolarstage). Oogonia are always present but they might be not visible

2. Previtellogenic growth The nucleus increases in size and multiple nucleoli are formed. A weakly stained area called “circumnuclear ring” (CNR) isalso present

3. Endogenous vitellogenesis The circumnuclear ring moves towards the outer part of the cell and gradually disintegrates, while the spherical corticalalveoli appear in the superficial half of the cytoplasm. No yolks granules present yet

4. Exogenous vitellogenesis Presence of yolk granules. The nucleus, still centrally located, becomes irregular. The occurrence of this stage means thatthe maturation process is in progress, and under normal conditions, the individual will develop within the current spawningseason

5. Final maturation The chorion becomes thicker, the nucleus migrates towards the animal pole and by the hydration process occurs6. Spent Post-ovulatory follicles (POFs), after oocytes release into the lumen, are distinguishable7. Resting Oocytes in stage 1 and 2. Some post-ovulatory structures, still present, show signs of previous spawning

F. Vitale et al. / Fisheries Research 90 (2008) 36–44 39

right). Trawl hauls including grey areas, were not used in thestudy.

The proportion mature per age class, the hepatosomaticindex (HSI = 100×ML×GM−1), the gonadosomatic index(GSI = 100×MG×GM−1) and the Fulton’s condition factor(K = 100×GM×LT

−3) were explored using Generalized Lin-

ear Models (GLZMs). The GLZM can be used to predictresponses for dependent variables which are non-normally dis-tributed and non-linearly related to the predictors. Such a modeldescribes any given model in term of its link function. The testis based on the Wald-statistic, which is analogous to the F statis-tic of General Linear Model (GLM). The proportions of mature

Fig. 2. Spatial distribution of (a) commercial landings of cod (≥30 cm) in kg, in the first quarter of the year (left panel), (b) number of spawning cod (≥30 cm) in theIBTS February survey (middle panel), and (c) putative spawning grounds in the Kattegat (right panel; the arithmetic mean of the standardized value for commercialcatches and IBTS within each square). White grid cells = no reported landings; light grey <0.5 standard deviations above the mean; dark grey = 0.5–1.5 standarddeviations above the mean; black >1.5 standard deviations above the mean. Grid size is approximately 10 km× 10 km (i.e. 5× 5 nautical miles).

40 F. Vitale et al. / Fisheries Research 90 (2008) 36–44

Fig. 2. ( Continued ).

F. Vitale et al. / Fisheries Research 90 (2008) 36–44 41

Fig. 3. Average (upper maps) and standard deviation (lower maps) distribution of (a) commercial landings of cod in the first quarter of the year (left panel) and(b) putative spawning grounds in the Kattegat 1996–2004. White grid cells = no reported landings; Light grey: <0.5 standard deviations above the mean; darkgrey = 0.5–1.5 standard deviations above the mean; black >1.5 standard deviations above the mean. Grid size is approximately 10 km× 10 km (i.e. 5× 5 nauticalmiles).

fish were compared between areas (spawning or non-spawning),using a binomial model with year, month, age and area as cate-gorical predictors and log as link function. Three GLZMs withyear, month, age and area as categorical predictors were alsoemployed to explore GSI-, HSI- and K-values in females belong-ing to the two areas. The GLZMs, with log as link function, weregamma distributed for GSI and HSI and normal distributed forK. The models were expressed as:

Responsex,yλ,ϕ(Prop.mature, GSI, HSI, K)

= c + ψ × year+ δ×month+ σ × age+ ∂ × area+ εwhere c was the model constant and ψ, δ, σ, ∂ were the predic-tors’ specific parameters and ε was a random error. The level ofsignificance for all tests was set at 5%. All the analyses wereperformed using Statistica Software (2004).

3. Results

3.1. Spatial analysis

Data from 1996–2004 clearly indicated that cod catches dur-ing the Swedish bottom trawl fishery were made to a large extentin spatially rather restricted areas in the south eastern part of theKattegat, i.e. either close to the entrance to the Sound, or off thecoast at Falkenberg (Figs. 2 and 3, left panel). In some years,large landings of cod were also reported from Fladen and fromthe northern part of the Kattegat, i.e. north off Laso. Spatial anal-yses confirmed that a positive autocorrelation was present bothwithin years (univariate Moran’s I ranging from 0.20 to 0.48,p < 0.001 for all comparisons) and between years (multivariateMoran’s I ranging from 0.17 to 0.43; p < 0.001 for all compar-isons) (Table 4). The CPUE of spawning cod in the IBTS data

42 F. Vitale et al. / Fisheries Research 90 (2008) 36–44

Table 4Measure of spatial autocorrelation (Moran’s I) computed within and betweenyears

Year 1996 1997 1998 1999 2000 2001 2002 2003 2004

1996 0.30 0.35 0.29 0.32 0.31 0.25 0.23 0.29 0.271997 0.48 0.40 0.43 0.33 0.27 0.25 0.33 0.261998 0.31 0.35 0.27 0.22 0.19 0.25 0.201999 0.41 0.30 0.22 0.17 0.26 0.242000 0.28 0.23 0.24 0.27 0.292001 0.20 0.24 0.25 0.242002 0.29 0.30 0.252003 0.35 0.312004 0.32

All within and between year correlations were significant (p < 0.001, based onrandomization test).

1996–2004 varied with a factor of 10 over the study period, rang-ing from an average of 34.2 spawning fish per hour in 1998 and1999 to 3.2 spawning fish per hour in 2003. However, the occur-rence of spawning fish was not evenly distributed throughoutthe area, but coincided to a large extent with the areas identifiedas hot spots for the commercial landings (Figs. 2 and 3, middlepanel). Put together, these data sources indicate several possiblespawning grounds for cod in the Kattegat (Figs. 2 and 3, rightpanel).

3.2. Physiological investigations

Results from the GLZMs showed higher proportions ofmature, GSI- and HSI-values inside than outside potentialspawning areas (Table 5). No significant difference could bedetected for Fulton’s condition factor. Fig. 4 illustrates themonthly trends of all the investigated variables. The propor-tion of mature females and GSI indicated an increasing trendfrom December to February, followed by a decrease in March

Table 5Results from the GMZLs, testing differences in proportion of mature females,GSI, HIS and K between putative spawning and non-spawning areas

Effect Degr freed Wald statistic p

Proportion of mature Month 4 24.0247 <0.001Year 4 31.6688 <0.001Age 3 151.8890 <0.001Area 1 9.0525 <0.001

GSI Month 4 108.6893 <0.001Year 4 64.3155 <0.001Age 3 312.6589 <0.001Area 1 5.1188 <0.05

HIS Month 4 26.139 <0.001Year 4 27.275 <0.001Age 3 66.015 <0.001Area 1 27.422 <0.001

K Month 4 3.3963 0.49Year 4 6.6541 0.16Age 3 32.5965 <0.001Area 1 0.1984 0.66

Fig. 4. Monthly trends of the investigated physiological parameters and of theproportion of mature individuals in putative spawning (�) and non-spawningareas (©). The vertical bars represent standard errors.

(pooled values from all studied years). From January to March,the proportion of mature females was higher in spawning thanin non-spawning areas. The GSI-values increased more sharplyin the spawning areas during January and February, resulting inlower values in the non-spawning areas also during the declineof the spawning activity in March. Also, HSI-values increasedfrom December to January. After January a decline was observedin both areas, although females from assumed spawning areasexhibited higher HSI values. K showed a stable pattern outsidepotential spawning areas, whereas it decreased from January andonwards inside the spawning grounds, although the differenceswere not significant.

F. Vitale et al. / Fisheries Research 90 (2008) 36–44 43

4. Discussion

This study clearly depicted the location of the major codspawning activities in the Kattegat between 1996 and 2004. Theefficacy of combining commercial landings and fishery inde-pendent survey data was demonstrated by the very persistentand precise geographical signal elicited in the study. Theseresults were further corroborated by independent sampling ofthe physiological status of fish in depicted spawning and non-spawning areas. The combined methodology used in this studythus represents an alternative way of mapping and describ-ing the distribution of spawning localities for commercial fishspecies in relation to more expensive and time-consuming eggsurveys. By using commercial landing data and surveys, eitherin combination or separately, the former spatial distribution ofspawning localities can be elucidated. This might represent theonly opportunity to reconstruct the historical spatial populationstructure.

For the studied period of time, two areas in the south-eastern part of the Kattegat appeared to be most important,one close to the entrance to the Sound and one offthe coast at Falkenberg (Fig. 1). This observation is ingeneral agreement with previous information on locationof spawning aggregations in the Kattegat for the periods1981–1990 (Pihl and Ulmestrand, 1988; Hagstrom et al.,1990), and 1975–1999 (Svedang and Bardon, 2003) andwith the ongoing study on egg distribution (Svedang et al.,2004). In addition, based on survey data only, spawningaggregations were also noted in the deeper parts of the south-western Kattegat (Hagstrom et al., 1990; Fig. 3d, centralpanel).

However, the present diversity of spawning localities in theKattegat was indicated to be reduced in comparison to whatcan be elucidated about the past distribution of spawning activ-ities, i.e. before 1990. Besides the two areas presently indicatedas the main spawning grounds, only weak signals of spawningactivities were obtained in the central and northern parts of Kat-tegat. These areas might no longer be recognized as spawninggrounds, although large spawning aggregations were frequentlyencountered by research surveys in the early part of 20th century(Hagberg, 2005).

Moreover, it was also noted that possibly separate spawn-ing locations may have been abandoned in the bights ofSkalderviken and Laholmsbukten. Svedang and Bardon (2003)depicted rather big spawning aggregations in these areas,which eventually disappeared in the beginning of the 1990s.Unfortunately, earlier information on the location of spawningaggregations in the bights of Laholmsbukten and Skaldervikendid not include any spatial delineation. As these two formerspawning areas were situated rather close to the two majorspawning areas depicted in the present study, it was thereforenot possible to evaluate whether our results reflect a decline innumber of spawning areas or merely a contraction in spatialdistribution.

The inclusion of physiological parameters strengthened theidentification of spawning areas in the study. An unambigu-ous difference was found between individuals at the depicted

spawning and non-spawning grounds in the first quarter of theyear. Seasonal patterns of energy accumulation and depletionin cod, following the cyclic periods of feeding, maturation,migration, reproduction and overwintering, has been describedin several studies (Lambert and Dutil, 1997 and referencestherein). Female cod accumulate mainly energy in the liver inthe form of lipids. Once the maturing is set in train, this energyreserve is successively transferred to the gonads, i.e. during thevitellogenesis. Therefore during the spawning season, cod expe-rience an increase of gonad weight together with a decreasein liver weight, as stored energy is translocated for reproduc-tive purposes (Lambert and Dutil, 1997, 2000; Schwalme andChouinard, 1999). Consequently, the energy requirements andutilisation, constitute a good basis for assessing the reproductivestatus of individuals, and, ultimately, for discriminating betweenspawning and non-spawning grounds. Our results show that theenergetic fluctuation is unequivocally occurring in those individ-uals caught in the assumed spawning grounds from January andonwards, indicating that cod in the Kattegat start to aggregate inJanuary.

Put together, these results showed that cod has contin-ued to aggregate and spawn in specific areas for 25 years ormore, albeit in drastically reduced numbers. This is a goodindication of the persistence of the spatial structure in cod pop-ulations over time and that spawning site fidelity in one way oranother must be transferred from generation to generation (cf.Robichaud and Rose, 2001; Wright et al., 2006; Svedang et al.,2007).

Spatial and temporal fish concentrations are obviously attrac-tive for commercial fishing, as they limit the costs for searchingand harvesting fish shoals. However, in sea areas like the Katte-gat, targeting spawning aggregations may jeopardise the effortsstipulated in the cod recovery plan as the exploitation of thoseareas during the spawning season may represent a considerablepart of the annual fishing mortality (cf. ICES, 2006). More-over, in the spawning areas larger individuals, which producehigher quality and more viable eggs (Trippel et al., 1997) aswell as higher sperm volume (Trippel and Morgan, 1994), aremore common and more easily withdrawn from the populationwith serious consequences for the quality of reproductive output.It is noteworthy that simply performing trawl passages throughthe spawning aggregations could put an extra stress on cod mat-ing behaviour (Brawn, 1961; Hutchings et al., 1999; Nordeideand Foldstad, 2000) and spawning synchronization may be dis-turbed, possibly decreasing the fertilization rates (Morgan et al.,1997).

In conclusion, in order to successfully implement a recoveryplan for an over-exploited fish population, such as the Kattegatcod, accurate knowledge on spatial and temporal distribution ofspawning activity might be crucial. The closure of the identifiedspawning areas could reduce fishing mortality and enhance thechances for successful reproduction, if the recovery is intendedto be favoured by a spatial and temporal management of theoverall fishing effort. The clear-cut persistence of the spawningaggregations over time, as shown in this study, is likely to facil-itate implementation of recovery plans focused on controllingfishing activity during the spawning season.

44 F. Vitale et al. / Fisheries Research 90 (2008) 36–44

Acknowledgements

The authors wish to thank the crews on R/V Ancylus and R/VArgos for the assistance in the field, Massimiliano Cardinalefor his useful advices and three anonymous reviewers whosecriticisms greatly improved the manuscript.

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