ALBERT

Description: The Eastern Baltic cod abundance started rapidly to increase in the mid-2000s as evidenced by analytical stock assessments, due to increased recruitment and declining fishing mortality. Since 2014, the analytical stock assessment is not available, leaving the present stock status unclear and casting doubts about the magnitude of the recent increase in recruitment. Earlier studies identified main factors impacting on cod reproductive success to be related to the loss of two out of three spawning areas in the 1980s caused by lack of major Baltic inflows with a concurrent reduction in salinity and oxygen. Other important factors include prey availability for first-feeding larvae, egg predation by sprat and herring and cannibalism on juveniles, all in one way or the other related to the prevailing hydrographic conditions. These factors cannot explain increased reproductive success in the last decade, as the period was characterized by an absence of large-scale Baltic inflows since 2003 and persistent anoxic conditions in the bottom water of the deep Baltic basins. This questions the perception of the increased recruitment in later years and challenges our present understanding of cod recruitment dynamics in the Baltic Sea. In this contribution, we review evidence from the recent literature supplemented by information from latest research cruises to elucidate whether cod reproductive success indeed has increased during the last decade, and we suggest the key processes responsible for the recent dynamics in cod recruitment and outline directions for future research.

Description: Bacterial biofilms provide cues for the settlement of marine invertebrates such as coral larvae, and are therefore important for the resilience and recovery of coral reefs. This study aimed to better understand how ocean acidification may affect the community composition and diversity of bacterial biofilms on surfaces under naturally reduced pH conditions. Settlement tiles were deployed at coral reefs in Papua New Guinea along pH gradients created by two CO2 seeps. Biofilms on upper and lower tiles surfaces were sampled 5 and 13 months after deployment. Automated Ribosomal Intergenic Spacer Analysis was used to characterize 240 separate bacterial communities, complemented by amplicon sequencing of the bacterial 16S rRNA gene of 16 samples. Bacterial biofilms consisted predominantly of Alpha-, Gamma-, and Delta-proteobacteria, as well as Cyanobacteria, Flavobacteriia, and Cytophagia, whereas taxa that induce settlement of invertebrate larvae only accounted for a small fraction of the community. Bacterial biofilm composition was heterogeneous, with on average only ∼25% of operational taxonomic units shared between samples. Among the observed environmental parameters, pH was only weakly related to community composition (R2 ∼ 1%), and was unrelated to community richness and evenness. In contrast, biofilms strongly differed between upper and lower tile surfaces (contrasting in light exposure and grazing intensity). There also appeared to be a strong interaction between bacterial biofilm composition and the macroscopic components of the tile community. Our results suggest that on mature settlement surfaces in situ, pH does not have a strong impact on the composition of bacterial biofilms. Other abiotic and biotic factors such as light exposure and interactions with other organisms may be more important in shaping bacterial biofilms on mature surfaces than changes in seawater pH.

Description: Vital processes relevant for exploited stocks, for example growth, predation and recruitment are closely related to the environmental conditions. Here, we present a generic method to include state of the art knowledge on environmental impacts and environmental forecasting into short-term predictions and the formulation of environment-based harvest control rules for exploited stocks. The method consists of three elements: First, the linkage between environmental parameters and stock dynamics, second the short-term prediction of both environment and stock dynamics, and third the scaling of otherwise constant reference values for fishing mortality in accordance with the environmental situation. The method is exemplified for Eastern Baltic cod. Recruitment is treated as dependent on oxygen conditions, and the formulation of the proposed fishing intensity is accounting for the actual oxygen conditions and predicted conditions for the year following the assessment year. Finally, the resulting advice is compared to advice that has been given not accounting for the oxygen conditions.

Description: This manual represents a review of the potential sources and methods to be applied when providing prior information to Bayesian stock assessments and marine risk analysis. The manual is compiled as a product of the EC Framework 7 ECOKNOWS project (www.ecoknows.eu). The manual begins by introducing the basic concepts of Bayesian inference and the role of prior information in the inference. Bayesian analysis is a mathematical formalization of a sequential learning process in a probabilistic rationale. Prior information (also called ”prior knowledge”, ”prior belief”, or simply a ”prior”) refers to any existing relevant knowledge available before the analysis of the newest observations (data) and the information included in them. Prior information is input to a Bayesian statistical analysis in the form of a probability distribution (a prior distribution) that summarizes beliefs about the parameter concerned in terms of relative support for different values. Apart from specifying probable parameter values, prior information also defines how the data are related to the phenomenon being studied, i.e. the model structure. Prior information should reflect the different degrees of knowledge about different parameters and the interrelationships among them. Different sources of prior information are described as well as the particularities important for their successful utilization. The sources of prior information are classified into four main categories: (i) primary data, (ii) literature, (iii) online databases, and (iv) experts. This categorization is somewhat synthetic, but is useful for structuring the process of deriving a prior and for acknowledging different aspects of it. A hierarchy is proposed in which sources of prior information are ranked according to their proximity to the primary observations, so that use of raw data is preferred where possible. This hierarchy is reflected in the types of methods that might be suitable – for example, hierarchical analysis and meta-analysis approaches are powerful, but typically require larger numbers of observations than other methods. In establishing an informative prior distribution for a variable or parameter from ancillary raw data, several steps should be followed. These include the choice of the frequency distribution of observations which also determines the shape of prior distribution, the choice of the way in which a dataset is used to construct a prior, and the consideration related to whether one or several datasets are used. Explicitly modelling correlations between parameters in a hierarchical model can allow more effective use of the available information or more knowledge with the same data. Checking the literature is advised as the next approach. Stock assessment would gain much from the inclusion of prior information derived from the literature and from literature compilers such as FishBase (www.fishbase.org), especially in data-limited situations. The reader is guided through the process of obtaining priors for length–weight, growth, and mortality parameters from FishBase. Expert opinion lends itself to data-limited situations and can be used even in cases where observations are not available. Several expert elicitation tools are introduced for guiding experts through the process of expressing their beliefs and for extracting numerical priors about variables of interest, such as stock–recruitment dynamics, natural mortality, maturation, and the selectivity of fishing gears. Elicitation of parameter values is not the only task where experts play an important role; they also can describe the process to be modelled as a whole. Information sources and methods are not mutually exclusive, so some combination may be used in deriving a prior distribution. Whichever source(s) and method(s) are chosen, it is important to remember that the same data should not be used twice. If the 2 | ICES Cooperative Research Report No. 328 plan is to use the data in the analysis for which the prior distribution is needed, then the same data cannot be used in formulating the prior. The techniques studied and proposed in this manual can be further elaborated and fine-tuned. New developments in technology can potentially be explored to find novel ways of forming prior distributions from different sources of information. Future research efforts should also be targeted at the philosophy and practices of model building based on existing prior information. Stock assessments that explicitly account for model uncertainty are still rare, and improving the methodology in this direction is an important avenue for future research. More research is also needed to make Bayesian analysis of non-parametric models more accessible in practice. Since Bayesian stock assessment models (like all other assessment models) are made from existing knowledge held by human beings, prior distributions for parameters and model structures may play a key role in the processes of collectively building and reviewing those models with stakeholders. Research on the theory and practice of these processes will be needed in the future.

Description: Oxygen minimum zones are increasing, yet the effects of these zones on the genetic composition of marine fish stocks has been neglected. We assessed the combined effects of stock size and structure, and the prevailing oxygen situation, on Eastern Baltic cod (ICES SD25) genetic diversity. For this purpose, we used an integrative long-term otolith sample and data series (1995-2013) to (1) calculate the approximate number of females with surviving eggs in a given year, i.e., contributing to reproduction (n F), and (2) the annually resolved cohort mean allelic richness as proxy of genetic diversity, based on 12 microsatellite markers. Cohort mean allelic richness showed strong year-to-year fluctuations though no permanent decline. Importantly, it was highly correlated with n F, but with an unexpected 1.5 year time lag that may be an artefact of Eastern Baltic cod ageing problems. Our findings indicated that environmental pressure can effect rapid alterations in exploited fish stock genetic composition, and pointed to the importance of large females for Eastern Baltic cod reproduction during stagnation periods. Considering the importance of standing genetic variation for the evolutionary potential of populations, this is relevant for projections of the future state of cod stocks under global change.

Description: A hydrodynamic model coupled with a Lagrangian particle tracking technique was utilized to simulate spatially and temporally resolved long-term environmentally related (i) size of habitat suitable for reproduction, (ii) egg/yolk-sac larval survival, (iii) separation of causes of mortality, and (iv) connectivity between spawning areas of Baltic flounder with pelagic eggs. Information on reproduction habitat requirements and mortality sources were obtained from field or laboratory studies. In our modelling study we only quantified physical processes generating heterogeneity in spatial distribution of eggs and yolk-sac larvae, as e.g. predation is not accounted for. The spatial extent of eggs and larvae represented as modelled particles is primarily determined by oxygen and salinity conditions. The reproduction habitat most suitable was determined for the Gdansk Deep, followed by the Bornholm Basin. Relatively low habitat suitability was obtained for the Arkona Basin and the Gotland Basin. The model runs also showed yolk-sac larval survival to be to a large extent affected by sedimentation. Eggs initially released in the Arkona Basin and Bornholm Basin are strongly affected by sedimentation compared with those released in the Gdansk Deep and Gotland Basin. Highest relative survival of eggs occurred in the Gdansk Deep and in the Bornholm Basin. Relatively low survival rates in the Gotland Basin were attributable to oxygen-dependent mortality. Oxygen content had almost no impact on survival in the Arkona Basin. For all spawning areas mortality caused by lethally low temperatures was only evident after severe winters. Buoyancy of eggs and yolk-sac larvae in relation to topographic features appear as a barrier for the transport of eggs and yolk-sac larvae and potentially limits the connectivity of early life stages between the different spawning areas.