Incorporate recruitment models into stochastic single- and multi-species

Introduction

As a first task the feasibility of an implementation of identified processes and relationships to estimate input variables into medium- to long-term stock projections has been reviewed. Baltic cod and sprat were in focus, but comparison to similar species in other areas enabled a generalised discussion of the findings.

ICES routinely produces medium-term projections of population abundance for a large number of fish populations, including Baltic cod and sprat. Biological inputs for these projections are mean values with random variation based on historical data. Notably one of the major uncertainties in projections of fish population development is a functional relationship between recruitment and any other variable, including

assume a mean recruitment with random variability, or a highly uncertain relationship (i.e. one which explains little variation) between spawner biomass and recruitment. As a result, projections based on these inputs are also highly uncertain.

Recruitment of sprat in the Baltic Sea co-varies with temperature. The temperature-recruitment relationship was integrated into a population projection model used by the Baltic Fisheries Assessment Working group and the expected spawner biomass trend for the next 10 years was predicted as probability distributions for different temperature and exploitation scenarios. Specifically emphasis was given to the probability that SSB falls below the “precautionary approach biomass” (BPA).

Based on established GLM stock-recruitment relationships for cod in Subdivision 25 and sprat in Subdivision 26 (see Task 6.1), medium-term projections were conducted using the ARIMA model predictions of environmental variables. The feedback of recruitment on the spawning stock biomass was modeled by a GLM with SSB as a function of lagged values of recruitment.

Medium-term projections for cod incorporating environmental effects on recruitment (ERE-approach) were run to represent a ten-year period. Five hundred simulations were run for each scenario, where a scenario consisted of an assumed level of fishing mortality and an assumed sequence of environmental variation. The results are summarised in terms of the percentile distributions from these replicate runs in order to give a probabilistic summary of the possible outcomes. Population numbers at ages three and older at the start of the projection period are drawn randomly from log-normal distributions were the mean value is the XSA estimate of survivors at that age from the regular assessment, and the variance is the associated variance of that estimate. Recruitment are drawn from the ERE stock-environment-recruitment model established under Task 6.1. Estimates of weight at age in the catch at the youngest age are derived by randomly selecting a mean value from the observed values at that age over the last three years. For older ages the procedure is to randomly select a growth increment at the appropriate age from the last three years and add this to the most recent observation or estimate of the weight at age of the relevant year-class. Estimates of maturity at age are derived from the estimated catch weights at age using a sigmoid relationship between catch weight and maturity fitted to the observed data.

Multispecies medium- to long-term projections were used to predict different scenarios of stock and catch development with the forecast mode of the 4M programme. Emphasis was given to the impact of predatory interactions (cod cannibalism and cod predation on clupeids) on future stock dynamics as well as the coherence between precautionary biomass (Bpa) and fishing mortality reference points (Fpa), i.e. does fishing at Fpa lead to Bpa under different recruitment scenarios. Four projection scenarios were set-up: i) food suitabilities as estimated by the MSVPA key-run and status quo fishing mortalities in the prediction.

Recruitment estimated from a stochastic Ricker SSB-recruitment relationship, ii) similar to the key-run, but prediction Fs were scaled to Fpa for the three species, iii) high cod stock: stomach content data from 1977 to 1983 as input to the suitability calculation in an alternative MSVPA run, recruitment was estimated from a log-normal distribution fitted to data for the period 1974–1983 and iv) low cod stock: stomach content data from 1984 to 1993 as input to the suitability calculation, recruitment was estimated from a log-normal distribution fitted to the period 1984–1999.

The multispecies production model developed in Task 6.1 was used for medium-term projections of cod, herring and sprat biomass and catches in the central Baltic. Projections were conducted for a range of fishing mortality options and different assumption on environmental conditions, influencing projected

recruitment. Recruitment was predicted from a relationship of recruitment per SSB ratio – environmental relationship. Environmental variables considered are those identified to be statistically significant in the GLM modeling approach in Task 6.1. Different combinations of environmental conditions for cod and sprat were simulated, resulting in both low, both high, low-high, and high-low recruitment. In addition, standard stock-recruitment models (Ricker model for cod and Beverton and Holt model for herring and sprat) were fitted.

These models were used in another series of multispecies medium-term projections (traditional approach). In the projections apart of uncertainty in recruitment, the stochasticity in the initial biomass estimates and growth were introduced.

An Ecosim model was fitted to data covering the period from 1974 to 2000 and projections were run until 2031 under various management schemes. In this 30-year forecasts it was analyzed what is likely to happen if: i) fisheries is managed by status quo fishing pressure, ii) fisheries is managed by precautionary approach, iii) nutrient input is reduced, iv) major recovery of seal populations takes place, v) fisheries is managed by a strategy maximizing the profit, vi) fisheries of clupeids is closed because of the dioxin problem, vii) enacting several management actions and plans at once.

Results and Discussion

Medium- to long-term projections in contrast to short-term predictions depend heavily on the recruitment model employed. In ICES standard projections, recruitment is in general modeled via traditional stock-recruitment relationships. Given that stock-recruitment depends on a combination of environmental conditions, spawning stock characteristics and species interactions, it can be expected that the predictive power of this approach is limited. Consequently, recruitment models need to be expanded to incorporate most important processes affecting the reproductive success. Among the factors and processes to be considered are: i) size, structure and condition of the spawning stock and its viable egg production, ii) temporal and spatial distribution of spawning effort, iii) impact of physical/chemical conditions on fertilisation, egg development, hatching success and larval survival, iv) food availability for larvae and juveniles in terms of quantity and quality, and v) predation pressure on all juvenile life stages. In order to do this, we are faced immediately with two major problems: Various combinations of processes act in different species and even between different stocks of one species. Thus, sound conceptual models of the effects of processes are required for each stock. Secondly, changes in major environmental conditions may prove to be impossible to predict, even a generation time ahead, leading to the conclusion that stochastic approaches may be the only way to proceed. However, if major changes in the environment are likely to happen, e.g. environmentally driven regime shifts, or if typical cycles or general trends can be identified and the impact on specific important processes has been resolved, modeling of corresponding scenarios appears to be important.

In fish stocks exposed at times to adverse abiotic environmental conditions and/or suffering from highly variable food supply, egg production may be highly variable, largely independent of the size of the spawning stock. Thus, the spawning stock biomass as input parameter for stock-recruitment relationships should be replaced by the potential egg production as a function of stock size and structure, utilising relationships between growth, maturation rates and fecundity. In case of limited databases, proxies closely related to the viable egg production may be utilised instead of the estimated populations egg production. If strong relationships exist to major prey species, for which regularly assessments and predictions are conducted,

potential of a stock is substantially affected by fluctuating abiotic environmental conditions, any prediction is limited to a time frame of years equivalent to the recruiting age plus one year at best, while long-term forecasts are restricted to scenario modelling, assuming trends in specific environmental conditions, empirical cycles or random variation.

In addition to the quantity, also the quality of the egg production may be modelled as a function of size/age structure of the spawning stock, spawning experience and nutritional condition of the spawning stock. Atresia is a commonly observed process in fish, which is linked to the nutritional condition of the females. The intensity and thus the impact on the realised egg production is in general not well understood and need to be studied in more detail.

For egg and early larval survival, temperature may be especially important to consider in northern or southern areas of the distribution range, while salinity and oxygen cause problems mainly in stratified systems. Based on established relationships between physical factors and developmental/survival rates, considering information on temporal/spatial distribution of spawning activity, survival until the larval stage may be hindcasted and also predicted given that the environmental conditions are known.

Predation mortality on early life stages is in general not well understood and will hamper predictions if a substantial and variable impact on survival rates occurs. There is a clear necessity of substantial research input, especially with respect to the functional response of predators and the role of temporal/spatial overlap between predator and prey under varying environmental forcing conditions. For larger juveniles the traditional multispecies prediction models offer the possibility to forecast abundance and predation mortality, given that major predators are incorporated in the model and environmental variability does not seriously affect the functional response implemented, an assumption which remains to be tested.

Hatching success and larval activity are again coupled to the quality of spawning products, but also to abiotic environmental conditions during incubation. Larval feeding success is dependent on larval activity and the quantity and quality of available food as well as abiotic environmental conditions affecting capture success (e.g. turbulence, temperature). Although this area has been a focus of recruitment research for the last decades, the complex interplay between various trophodynamic processes at lower trophic levels and abiotic environmental variability made it difficult to develop hindcasting or even prediction models. Advances in hydrodynamic modelling and increased capabilities to include larvae as “intelligent” tracers into the models, and to generate at the same time the abiotic environment are major steps to hindcast distribution pattern, identify potential and actual nursery areas and describe conditions that lead to survival success.

The implementation of advanced coupled hydro- and trophodynamic models considering besides different early life stages, the temporal and spatial heterogeneity in the dynamics of food availability and spatial overlap to predators are major future steps in modelling recruitment processes. These models allow to test suggested environmental indices and to develop new indices to be used as proxies for survival probability (e.g. upwelling indices, transport rates, temperature, zooplankton abundance). However, their predictive time frame will be limited by our ability to forecast large-scale atmospheric forcing conditions, with response times in ocean characteristics being in the best cases some months. Thus application in long-term projections will be restricted to scenario modelling approaches.

As an example, integrating the temperature-recruitment relationship into a population projection model for Baltic sprat used by the Baltic Fisheries Assessment Working group indicate that there is little likelihood that SSB will fall below Bpa in the next 10 years under average or above-average temperatures and with current

fishing mortality rates. This conclusion is a result of the positive influence of temperature on recruitment. If temperatures fall to lower levels and remain low for the next 10 years, the probability that spawner biomass will decrease below Bpa increases. This probability rises even further if fishing mortality rates equivalent to Fpa are permitted (note that status quo F is less than Fpa). Thus, our calculations suggest that fishing at a precautionary level during a cold environment regime may not be sustainable. The effects of climate variability on sprat recruitment may have consequences for predator-prey interactions among the major fish species in the Baltic Sea. Sprat are predators of cod eggs and of calanoid copepods being in juvenile stages the major prey of cod larvae. Thus, a warm environment that favours sprat recruitment could indirectly suppress cod recruitment, delay cod population recovery and promote a regime shift towards clupeid dominance of the Baltic Sea fish community and ecosystem. This situation exists at the present, and it is likely that the warm conditions of recent years have contributed to this shift.

Medium-term projections based on established GLM stock-recruitment relationships for cod in Subdivision 25 and sprat in Subdivision 26 resulted in extremely positive dynamics of cod SSB. The ARIMA model used to predict environmental variables for the projection period, forecasted partly unrealistic hydrographic conditions. For sprat the ARIMA input values are more reasonable, with recruitment driven to a considerable degree by changes in water density. Modelling the spawning stock size with a GLM model has to be considered as a short-cut, as methodology exists to predict the SSB development in dependence of recruitment, fishing mortality, growth and maturation processes, i.e. the multispecies forecast models utilized below.

Medium-term projections for Baltic cod incorporating environmental effects on recruitment were run, reflecting the combination of the three fishing mortality (FStatus quo, Fpa and 0.5xFpa) with four environment scenarios. The four environmental scenarios are based on observed sequences of environmental conditions, in terms of oxygen and food availability. Three of the scenarios take a fixed starting year and assume the same sequence of environmental conditions as were actually observed from that year onward. The fourth scenario takes the environmental conditions as a random variable by assuming a randomly chosen starting year for each run. In conventional medium-term projections, it is assumed that any environmental effects can be regarded as random noise around a fixed stock-recruitment model. Hence there is an implicit assumption that the environment will remain the same during the projection period as it has been during the period for which stock-recruitment observations are available. With the methodology applied here, the assumptions about future environment are made explicit. Even though it may not be possible to predict future environmental conditions with any degree of precision, it is nonetheless instructive to investigate the possible stock development under various possible environmental scenarios. In this respect, it is notable that the scenario run where environmental variation has in effect been incorporated as part of the random variation in the system lead to much higher uncertainty around the projections than under the fixed environment scenarios. The inclusion of environmental factors in medium-term projections allows some inferences to be drawn about the current management plan for the fishery. Under the precautionary approach to fishery management, fishing mortality on this stock should be kept at or below the precautionary value (Fpa). In addition, management should also aim to keep the SSB above Bpa. With the approach to medium-term projections employed here, there is explicit acknowledgement that SSB is not the only contributing factor to recruitment; a situation which has implications for SSB-based reference points, see Task 6.4. It is notable

ensure at least a 50% probability that the spawning stock will increase. This perhaps implies that Fpa should ideally be reduced to below the present value of 0.6 for this stock, although some increase in SSB is apparent at Fpa in the scenario where environment is random. In contrast, only under exceptional environmental conditions will any increase in SSB occur if the stock continues to be exploited at the current level of fishing mortality.

The performed multispecies medium- to long-term projections using the forecast mode of the 4M programme confirmed that in periods of low reproductive success as apparent for the period 1987-1999 even a reduction of the fishing pressure to Fpa does not result in an SSB reaching Bpa. In fact the long-term average SSB is only marginally above Blim. The option of remaining at FStatus quo yielded a SSB being stable well below Blim, but only slightly reduced catches compared to the Fpa option. The high and low cod stock scenario projections clearly demonstrated that high recruitment success is a pre-requisite for an increase in SSB to above Bpa level, independent from the intensive cannibalism associated with this scenario. The low cod stock scenario resembled the key-run prediction with applied Fpa, meaning that this prediction is slightly more optimistic than the key-run under Fstatus quo assumption. This is explainable by the reduced cannibalism but also by the different recruitment model used. The biomass of sprat follows the oscillations in the cod biomass inversely caused by predation. In the high cod stock scenario predation diminishes the sprat biomass to approximately one third of the initial value, while in the low cod stock scenario sprat biomass is more stable.

The multispecies production model was as well sensitive to environmental conditions. Under favourable environmental conditions the cod biomass is almost twofold higher at Fpa than biomass at unfavourable conditions. Fishing at Fstatus quo leads to extinction of biomass at unfavourable environmental conditions but in case of favourable conditions the cod biomass increases above Bpa. The biomass and catch at fishing mortality of F0.1 or lower do not depend much on environmental conditions. So, for low fishing mortality levels the major difference between cod medium-term projections at different environmental conditions is the rate of reaching high levels of biomass. The development of projected biomass and catches of sprat depend on both fishing mortality and environmental conditions for sprat and fishing mortality and environmental conditions for cod, feeding on sprat. Assuming unfavourable environmental conditions for both cod and sprat, exploitation of sprat at Fpa leads to stock extinction, and status quo fishing mortality result as well in low stock sizes, with 50% probability of decreasing below Bpa in medium-term. When cod is fished at Fpa

sprat fishing mortality has to be reduced to 0.2 to be sustainable. At favourable environmental conditions the sprat stock development changes dramatically. Now even fishing mortality of 0.6 leads in medium-term to high stock size and catches. Assuming good environmental conditions for cod and unfavourable for sprat the sustainable stock size can be kept only at very low fishing mortality of sprat. In medium-term at F equal to 0.1 stock biomass approaches Bpa at very low catches, and sprat F has to be reduced to 0.05 to give reasonably stable stock biomass. As it could be expected, the simulations employing standard stock-recruitment relationships, cod and sprat biomass and catches are in between the results of simulations basing on environmentally driven recruitment. Presented medium-term projections should be treated with caution, especially options with favourable cod or sprat environmental conditions, as these options very often produced stock sizes at which modeled recruitment was higher than the maximum observed. When stock

sprat fishing mortality has to be reduced to 0.2 to be sustainable. At favourable environmental conditions the sprat stock development changes dramatically. Now even fishing mortality of 0.6 leads in medium-term to high stock size and catches. Assuming good environmental conditions for cod and unfavourable for sprat the sustainable stock size can be kept only at very low fishing mortality of sprat. In medium-term at F equal to 0.1 stock biomass approaches Bpa at very low catches, and sprat F has to be reduced to 0.05 to give reasonably stable stock biomass. As it could be expected, the simulations employing standard stock-recruitment relationships, cod and sprat biomass and catches are in between the results of simulations basing on environmentally driven recruitment. Presented medium-term projections should be treated with caution, especially options with favourable cod or sprat environmental conditions, as these options very often produced stock sizes at which modeled recruitment was higher than the maximum observed. When stock