Identify and describe causal relationships influencing recruitment and

Introduction

To achieve the first objective, a review and validation of data received from Task 1 to 5 for modelling purpose was conducted. The second major task was to identify critical periods in the reproductive success of cod and sprat and the third task to incorporate identified processes affecting these critical life stages into

The first task included an evaluation of established time series of the stocks’s reproductive effort in terms of spawning stock biomass, female SSB and potential egg production as well as measures of reproductive success in terms of recruitment at age 0 and 1 as established from survey (Task 1) and multispecies modelling activities (Task 5 and 6). Furthermore, alternative multispecies models were constructed and utilized to estimate historic stock dynamics and enable multispecies predictions.

The applicability of Bayesian approaches to estimate parameters of stock recruitment relationships was tested in a meta analysis for 21 cod stocks in the North Atlantic. This meta analysis was also the basis for investigating the carrying capacity of the Baltic and other marine ecosystems for cod recruitment.

The established coupled tropho/hydrodynamic individual based model of drift and feeding was validated and the reliability of results investigated. We tested the sensitivity to perturbations of the model input parameters and we compared an index of observed larval survival originating from main spawning activity 1986-1997 with simulated larval survival probabilities. Finally, we related reproductive success in terms of recruitment to the prey availability of Pseudocalanus elongatus for a longer time series covering the period 1966-1998.

As a first exploratory analysis, an attempt was conducted to identify statistical stock recruitment models for spawning areas with best data coverage, i.e. for cod Subdivision 25 encompassing the spawning area of the Bornholm Basin and for sprat Subdivision 26 encompassing the Gdansk Deep and the southern Gotland Basin. Besides spawning stock biomass an array of environmental variables was considered: quarterly average temperature, salinity, oxygen concentration and density during main spawning time in 25 m depths layers as hydrographic variables, the NAO index in January/February and the BSI index at spawning time as atmospheric forcing conditions reflecting, e.g. transport. An a priori selection of variables was not conducted to enable an objective statistical analysis.

Secondly, an extended exploratory statistical analysis was performed for both species to identify environmental factors affecting reproductive success and recruitment. Specifically abundance or production data for subsequent early life history stages were related to identify critical periods within the recruitment process. Environmental factors showing statistically significant covariance with the survival of one of these critical life stages, were incorporated into stock-recruitment models, separately for individual spawning areas and combined for the Central Baltic. For cod this study has been started within the CORE project and revealed that recruitment depends on egg survival with low oxygen concentration in dwelling depths and predation by clupeids as the major causes for egg mortality. Surviving egg production and larval abundance were weakly correlated, whereas larval abundance was significantly related to year class strength. This indicated that the period between the late egg and the early larval stage is critical for cod recruitment. The statistical model obtained for prediction of cod recruitment at age 0 in Sub-division 25 contained besides egg production, corrected for egg predation by clupeids, the oxygen condition in the reproductive volume and a larval transport index. In the more eastern spawning areas the hydrographic regime did in general not allow successful egg development in the prolonged stagnation period throughout the 1980s. Thus, only relatively simple models based on the egg production by the spawning stock and the reproductive volume were required to achieve a reasonable explanation of recruitment variance. Contrary to cod, the early and late egg stage production of sprat as well as the late egg stage production and larval abundance were significantly related. However, year class strength was largely independent of larval abundance. Thus, the period between the late larval and early juvenile stage appeared to be critical for sprat recruitment. Preliminary models established for Sub-division 25 and 26 are based on the spawning stock biomass as a measure of

egg production, ambient temperature and in the latter area growth anomaly of adult fish throughout the feeding and subsequent winter season. These statistical models explained somewhat less than half of the variance in recruitment, while for Sub-division 28 no significant model could be developed.

The established environmentally sensitive and spatially explicit stock-recruitment relationships for cod and sprat were further explored by predicting year-class strength 1996-1999, not considered in the parameter estimation, and subsequent comparison to updated MSVPA results and survey derived recruitment indices.

Furthermore, an update of these stock recruitment relationships was conducted at the end of the project period considering newest findings from the process analyses sections. These statistical models include oxygen related egg survival for all Sub-divisions and more important identified factors affecting cod larval survival, i.e. nauplii prey availability. Additionally various other physical forcing conditions affecting larval distribution (BSI-index), primary and secondary production (upwelling index) and larval capture success (turbulent velocity) were tested for their explanatory power in explaining larval survival.

For sprat it was investigated more closely how the temperature environment and spawner abundance affect recruitment. Conducted process analyses revealed that low temperature suppresses sprat recruitment and survival, presumably because sprat in the Baltic Sea is located near the northernmost limit of its geographic distribution. Laboratory and field experiments conducted suggest that eggs and larvae suffer increased mortality at low temperatures similar to those which occur in spawning habitats in the Baltic Sea. In addition, low temperature may suppress sprat growth and gonadal development, and via its influence on general hydrographic conditions and food web interactions, affects the potential for sprat egg cannibalism. These observations suggest that temperature is a key variable influencing sprat recruitment and possibly population abundance in the Baltic Sea. We have investigated this possibility by conducting statistical analyses using field estimates of sprat recruitment and water temperature measured at sprat spawning sites during sprat spawning times. As part of the investigation also inter-relationships between recruitment and other climatological and hydrographic variables were analysed. The objective was to evaluate whether large-scale climate variability can be linked via temperature and hydrographic conditions in sprat spawning areas to variations in sprat recruitment.

Coupling the stocks reproductive potential, capturing the stocks contribution to reproduction, with the effective reproductive environment (ERE) should allow determination of an index of reproductive success closely related to recruitment. ERE may be categorised into two components; the abiotic environment (described by e.g. oxygen, salinity, temperature etc.) and the biotic environment (described by e.g. food availability, predator abundance etc.), although these are to some extent interrelated. Following this approach for cod in the eastern Baltic, environmental factors for potential inclusion in the ERE have been selected a priori based on information from process studies under Task 1 to 5. These comprised egg survival in relation to oxygen conditions (oxygen content in the reproductive volume) and larval survival in relation to Pseudocalanus elongatus nauplii abundance. In a second stage appropriate data sets to represent these factors were selected, and then the functional form of the relationship between the factor and egg or larval survival was determined in the light of the mechanism by which the factor operates. Using this approach, it was possible to estimate a series of weightings which represent the extent to which each factor influenced the effective reproduction in each year. These are scaled to between zero (no survival in the relevant year due to the influence of the factor) and one (no influence on recruitment in the relevant year). The intention

part of an annual stock assessment. This application dictates a certain simplicity in the approach, both because of the need to project any environmental predictors which may be used, and in the use of stock and recruitment values estimated by a routine, single-species assessment.

To enable utilization of constructed recruitment models in medium- to long-term projections, environmental scenarios had to be established. This has been achieved by two approaches: i) combining different fragments of the historical time series representing either extreme events such as major inflows, or severe winter situations, or more usual hydrographic situations during stagnation or inflow periods, ii) applying ARIMA (integrated autoregressive moving average processes) models on the compiled time series of environmental data. Longer-term projections are generally used to give a probabalistic indication of the possible future trajectory of a fish stock subject to certain management actions. Typically this will take the form of a series of projections each run assuming a different level of fishing mortality fixed over the prediction period. Comparison of the results of these projections then allows a comparison of the relative probability of achieving a certain objective (e.g. of increasing SSB to above a specified reference value) over this medium-term period. Under the precautionary approach to fishery management, one objective of management of the fishery is to maintain fishing mortality on the stock at or below the precautionary reference level FPA. However, management should also aim to keep the spawning stock biomass above the precautionary reference level BPA. To reflect this situation, two to three different fishing mortality scenarios have been assumed for medium-term projections for the cod and sprat stock as well as medium- to long-term multispecies projections: continuation of fishing mortality at the current level (Fstatus-quo), reduction of F to the precautionary level (FPA), and in some cases reduction of F to half of the precautionary level.

With respect to eutrophication the processes linking nutrient loading to primary production, decomposition of organic matter and consumption rates of oxygen are complex and beyond the scope of this project to quantify. However, scenario simulations based on a mass-balance model accommodating trophic interactions at lower trophic levels and has been applied in a test case in Task 6.3. The full spectrum of interactions between eutrophication and climate change, including also interactions with persistent organic compounds and their potential affect on reproductive success of key species, is complex and cannot be modelled with certainty at the present time. Given the present level of process uncertainty and the likelihood that nutrient loading to the Baltic is not likely to change substantially in the next decade, the status quo situation was considered most representative for at least 10-year fish stock projection scenarios.

Results

To determine the reproductive effort of the cod and sprat stock either as SSB, female SSB or potential egg production by the SSB two major data sources were made available: i) output of analytical age-structured models and ii) international survey results. Due to the relatively short time series of bottom trawl and hydroacoustic surveys, especially not covering periods of maximum reproductive success of cod in the 1970s and early 1980s, analytical stock assessment outputs were used as the major data source, while survey results were used for validation purposes. Analytical stock assessment output is available from the Baltic Fisheries Assessment WG for the period 1966-2001 from an XSA and from MSVPA runs covering 1974-2000 and area dis-aggregated for 1974-1999, the latter two conducted within the project. The reproductive success in terms of recruitment relies essentially on the same data bases, with the MSVPA having the advantage to quantify pre-recruit abundance considering predation mortality by cod. While

standard XSA and area aggregated MSVPA produce very similar results, the area dis-aggregated MSVPA needed validation. This has been accomplished through comparison with various existing and compiled data sets. This allowed the application of the area dis-aggregated MSVPA to spatially resolve the SSB of the different spawning basins thereby allowing the utilisation of area specific reproductive success in recruitment modelling of these stocks.

The traditional MSVPA approach was expanded by a module allowing to model weight- and maturity-at-age in dependence of prey availability. Besides spatial dis-aggregation, missing this feature has been considered as a major disadvantage of the MSVPA approach compared with more modern multispecies models, e.g. the Boreal Migration and Consumption model (BORMICON). Furthermore, a stochastic MSVPA version is presently under development including maximum likelihood functions for commercial catch-at-age observations, CPUE observations, stomach contents observations and a stock-recruitment model. The model operates on historical data for estimation of parameters and their variance. A predictive stochastic model uses these values and input fishing mortalities to estimate effects of various management measures.

Given the successful completion of this task, the performance of the MSVPA is at least comparable to available statistically based multispecies models. Another initiative, i.e. the EU project “Development of structurally detailed statistically testable models of marine populations”, aims at the further development of available statistically based multispecies models. In view of these various efforts presently conducted outside the project, we concentrated on the development of a more simple statistically based model, the multispecies stock production model.

Multispecies production models are generally less data demanding, and may be especially useful when the age structure of the stocks is unknown, or biased as in the case of Baltic cod. The present multispecies stock-production model is derived from the age-structured multispecies model of Andersen and Ursin (1977).

The multispecies interactions in the model are constrained to the impact of the predator stock on the survival of prey components – the growth rate of predator is not affected by prey biomass. The advantage of the approach is that some of the model parameters can be estimated outside the model. The model allows for the estimation of the dynamics of stock biomass and multispecies interactions given catches, predator stomach contents, as well as indices of recruitment and fishing effort. The basic shortcoming of the model, its applicability to fully exploited part of the stocks only, was solved by developing an additional component covering the dynamics of young fish. The model was applied for simulation of the dynamics of the Baltic fish stocks, producing results comparable with those obtained from age-structured assessment models forming also the basis of medium-term multispecies projections.

To address broader issues related to Baltic ecosystem management an Ecopath and Ecosim approach was established, specifically to estimate indices for carrying capacity and multi-decadal fluctuations in cod, herring and sprat biomass. Results of fitting the model to historical time series were then used in medium-term projections incorporating a semi-Bayesian resampling routine, to explicitly consider the numerical uncertainty associated with assumptions and input parameters.

Estimating parameters of stock-recruit relationships of all 21 cod stocks in the North Atlantic revealed in all cases empirical Bayes estimates being biologically reasonable. In contrast, a stock-by-stock analysis occasionally yielded nonsensical parameter estimates (e.g., infinite values). In addition the Bayesian analyses yielded stock-specific parameter estimates with lower variability than when fitting such relationships

investigate the carrying capacity of the Baltic and other marine ecosystems for cod recruitment. These analyses showed that carrying capacities differed significantly among regions, even when standardized for obvious influences such as habitat area and spawner biomass. The differences between regions were significantly negatively correlated with local water temperatures. The performed modelling exercise suggests that Bayesian methods could be especially useful when attempting to derive biological reference points for stocks with highly uncertain recruitment data (e.g., sprat in the Baltic Sea). For these stocks stock-recruit relationships can be determined with significantly less uncertainty if information from other stocks throughout the species range is used in the analysis. The Bayesian analysis and simpler stock-recruit analyses revealed different carrying capacities of the Baltic and other marine ecosystems for cod recruitment. These results have implications for the identification of regime shifts and for evaluating the overall structure and function of the Baltic ecosystem. Identification of the occurrence, onset and persistence of different oceanographic and production regimes is useful when developing medium- to long-term forecasts of stock development under different environmental and fishery scenarios and ultimately the choice of biological reference points and appropriate management strategies.

Reviewing results from conducted process studies revealed most important environmental processes affecting the reproductive success of cod as follows: i) egg production in dependence of ambient hydrographic conditions and food availability, ii) egg developmental success in relation to oxygen concentration and temperature at depths of incubation, iii) in specific areas egg predation by clupeids dependent on predator-prey overlap, iv) larval development in relation to hydrographic processes and food availability, and v) cannibalism on juveniles. For sprat, in contrast to cod, egg production and egg mortality are of less importance for reproductive success. The period between the larval and early juvenile stage appeared to be critical for sprat recruitment. Potential variables identified to affect this life stage were ambient temperature and wind stress. Environmental factors showing statistically significant covariance with the survival of one of these critical life stages, were incorporated into stock-recruitment models separately for individual spawning areas and combined for the Central Baltic, see further below. The development in environmental conditions throughout the last two decades negatively affected the cod population, while the sprat stock benefited from them, despite a developing industrial fishery, resulting in a regime shift from a cod to a sprat dominated system in the Central Baltic.

Investigations on the potential impact of contamination on reproductive success did not reveal any consistent relationships and consequently are not included in any modeling approaches. Eutrophication has several complex influences on marine ecosystems, including effects on productivity and structure of entire food webs. One of the most immediate effects is an increase in primary production rates. Some of this primary production can stimulate production at higher trophic levels and indeed eutrophication may have increased fish production and biomass in the Baltic Sea during the 1950s and 1960s. However in most eutrophied systems a large portion of the phytoplankton production sinks to the seafloor where it is decomposed by the microbial food web. Decomposition of the organic matter on the sea bottom is an oxygen consuming process and can lead to local episodes of hypoxia and anoxia in coastal marine ecosystems. This situation also occurs in the Baltic Sea. In consequence cod and partly also sprat egg habitat (i.e. in and below the halocline of the Baltic Sea) has deteriorated.

The coupled tropho/hydrodynamic modelling study revealed retention and dispersal from the main spawning ground to be a key process influencing cod larval survival, but starvation was found to be important exclusively for first feeding larvae. When Pseudocalanus elongatus nauplii were available in the prey fields, high cod larval survival rates occurred in spring and early summer. When P. elongatus was not available, hatched larvae had only higher survival probabilities later in the year and if transported into shallower coastal regions. Caused by the strong decrease in abundance of P. elongatus during the last two decades, the results of the model runs indicate that larval cod changed from a non-limited to a food limited stage. In this respect, a shift in peak spawning time of cod from spring to summer throughout the last decade ensured a

The coupled tropho/hydrodynamic modelling study revealed retention and dispersal from the main spawning ground to be a key process influencing cod larval survival, but starvation was found to be important exclusively for first feeding larvae. When Pseudocalanus elongatus nauplii were available in the prey fields, high cod larval survival rates occurred in spring and early summer. When P. elongatus was not available, hatched larvae had only higher survival probabilities later in the year and if transported into shallower coastal regions. Caused by the strong decrease in abundance of P. elongatus during the last two decades, the results of the model runs indicate that larval cod changed from a non-limited to a food limited stage. In this respect, a shift in peak spawning time of cod from spring to summer throughout the last decade ensured a