Variability of larval Baltic sprat (Sprattus sprattus L.) otolith growth: a modeling approach combining spatially and temporally resolved biotic and abiotic environmental key variables

Plankton sampling was conducted in the Baltic to obtain sprat larvae. Their individual drift patterns were back‐calculated using a hydrodynamic model. The modelled positions along the individual drift trajectories were subsequently used to provide insight into the environmental conditions experienced by the larvae. Autocorrelation analysis revealed that successive otolith increment widths of individual larvae were not independent. Otolith increment width was then modelled using two different generalized additive model (GAM) analyses (with and without autocorrelation), using environmental variables determined for each modelled individual larval position as explanatory variables. The results indicate that otolith growth was not only influenced by the density of potential prey but was controlled by a number of simultaneously acting environmental factors. The final model, not considering autocorrelation, explained more than 80% of the variance of otolith growth, with larval age as a factor variable showing the strongest significant impact on otolith growth. Otolith growth was further explained by statistically significant ambient environmental factors such as temperature, bottom depth, prey density and turbulence. The GAM analysis, taking autocorrelation into account, explained almost 98% of the variability, with the previous otolith increment showing the strongest significant effect. Larval age as well as ambient temperature and prey abundance also had a significant effect. An alternative approach applied individual‐based model (IBM) simulations on larval drift, feeding, growth and survival starting as exogenously feeding larvae at the back‐calculated positions. The IBM results revealed optimal growth conditions for more than 97% of the larvae, with a tendency for our IBM to slightly overestimate larval growth.     

An example of meso‐scale hydrographic features in the central Baltic Sea and their influence on the distribution and vertical migration of sprat,Sprattus sprattus balticus (Schn.)

A wind‐driven meso‐scale pattern of temperature, salinity and oxygen was found along a transect in the northern Bornholm Basin (southern Baltic Sea). Strong winds caused currents along this transect, which shifted cold intermediate water (minimum: 3.6°C) towards the south. The transect was surveyed with a towed CTD‐system and hydroacoustics in parallel to investigate the distribution of sprat, Sprattus sprattus balticus (Schn.) in relation to the observed meso‐scale pattern. In those parts of the transect where the cold intermediate water was observed, sprat were restricted to water layers below the halocline. In other parts of the transect, sprat moved into higher water layers and occupied a wider depth range. The important factor was temperature, which set an upper limit to the vertical sprat distribution. The development of hydrography, as measured in the field, was evaluated with a hydrodynamic model.     

Coupling ecosystem and individual‐based models to simulate the influence of environmental variability on potential growth and survival of larval sprat (Sprattus sprattus L.) in the North Sea

To investigate the impact of changing environmental conditions in the North Sea on the distribution and survival of early life stages of a marine fish species, we employed a suite of coupled model components: (i) an Eulerian coupled hydrodynamic/ecosystem (Nutrients, Phyto‐, Zooplankton, Detritus) model to provide both 3‐D fields of hydrographical properties, and spatially and temporally variable prey fields; (ii) a Lagrangian transport model to simulate temporal changes in cohort distribution; and (iii) an individual‐based model (IBM) to depict foraging, growth and survival of fish early life stages. In this application, the IBM was parameterized for sprat (Sprattus sprattus L.) and included non‐feeding (egg and yolk‐sac larval) stages as well as foraging and growth subroutines for feeding (post‐yolk sac) larvae. Sensitivity analyses indicated that the angle of visual acuity, assimilation efficiency and the maximum food consumption rate were the most critical intrinsic model parameters. As an example, we applied this model system for 1990 in the North Sea. Results included not only information concerning the interplay of temperature and prey availability on larval fish survival and growth but also information on mechanisms underlying larval fish aggregation within frontal zones. The good agreement between modelled and in situ estimates of sprat distribution and growth rates in the German Bight suggested that interconnecting these different models provided an expedient tool to scrutinize basic processes in fish population dynamics.     

Seasonal changes in otolith increment width trajectories and the effect of temperature on the daily growth rate of young sardines

We studied the otolith microstructure and growth of sardine, Sardina pilchardus, in the North Aegean Sea (eastern Mediterranean Sea), using samples of larvae and juveniles that had hatched in winter (November–January) and winter–spring (February–May), respectively. The juveniles had developed during an extended period coinciding with marked pelagic ecosystem changes (from winter, mixed conditions to summer, stratified waters). To examine the relationship between environmental changes and the observed variability in their otolith increment–width trajectories (width‐at‐age), we summarized the shape of trajectories with a four‐parameter set estimated from a growth model fit to each width trajectory. The individual parameter sets were then related to the potential oceanographic conditions that fish experienced during their development, derived from a hydrodynamic–biogeochemical model (POM‐ERSEM), implemented in the sampling area. Substantial seasonal effects were demonstrated on the otolith microstructure (platykurtic versus leptokurtic trajectories in winter‐mixed versus summer‐stratified conditions), which were related to the progressive sea surface warming. In a subsequent step, in order to study the effect of oceanographic conditions on larval and juvenile daily growth rates, a GAM (Generalized Additive Model) analysis of otolith increment widths was carried out, using model‐derived oceanographic parameters and taking into account the ‘inherent otolith growth’, expressed by the explanatory variables ‘previous increment width’ and ‘Age’. Results showed a strong and positive, linear effect of temperature on the growth rate of winter‐caught larvae, whereas in juveniles, which had developed within a wide range of temperatures, an optimum temperature for growth was observed at around 24°C.     

基于耳石微结构的西北太平洋柔鱼群体结构、年龄与生长的研究

根据2007年7—10月在西北太平洋柔鱼传统作业渔场采集的样本,利用耳石微结构对其渔获群体结构、年龄与生长进行了研究。分析认为,雌性个体胴长为200～395 mm,日龄为123～258 d;雄性个体胴长为200～353 mm,日龄为127～274 d。7、8月渔获样本的优势日龄为151～180 d,9月为181～210 d,10月为211～240 d。孵化日期为2006年12月下旬至2007年6月上旬,其中1—4月为高峰期。雌性个体的胴长绝对生长率平均为(1.175±0.127) mm/d,雄性为(0.952±0.213) mm/d。其胴长、体质量与日龄的关系可分别用线性和指数方程来拟合,雌、雄个体胴长和体质量生长存在显著差异。研究认为,传统作业渔场中大多数渔获属冬春生群,7—10月各月优势日龄组呈现出随月变化一致的趋势,进一步印证了柔鱼轮纹为日周期的结论。推测认为,柔鱼孵化后,从产卵场洄游至索饵场需要4～6个月的时间。     

The HELCOM system of a vision,strategic goals and ecological objectives: implementing an ecosystem approach to the management of human activities in the Baltic Sea

• 1. Since signing the Helsinki Convention in 1974, the countries with coasts around the Baltic Sea have striven jointly within the Helsinki Commission (HELCOM) towards the ecological restoration of the Baltic Sea. The European Community signed the revised Convention in 1992.
• 2. Work under HELCOM includes implementing joint recommendations to curb pollution originating from land and marine sources, ensuring safer maritime traffic, and protecting biodiversity, for example, by setting up a network of Baltic Sea protected areas.
• 3. A new concept — the ecosystem approach to the management of human activities — was adopted by the Contracting Parties of HELCOM in 2003 to serve as the new framework for further efforts towards attaining good ecological status of the Baltic Sea.
• 4. Stepwise progress towards the development of quantitative definitions of good ecological status has been made since 2003 to implement the new approach: a common vision reflecting the ecosystem approach was adopted in 2004 and a number of more targeted goals and objectives were agreed in 2006.
• 5. The Contracting Parties to the Helsinki Convention will use the objectives adopted covering eutrophication, impacts of hazardous substances, and the overall status of biodiversity, including the impact of fisheries and shipping, to draft a new set of joint management actions.
• 6. In the future, an agreement under development among the Contracting Parties on indicators with quantitative targets will enable a quantitative assessment of ‘good ecological status’ and progress towards the goals of HELCOM, the Convention on Biological Diversity (CBD), as well European legislation concerning marine environmental protection.

Copyright © 2007 John Wiley & Sons, Ltd.