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Case study 9: Cod fisheries in the Baltic Sea

Introduction - Overview description of the case study

Description of the fishery, stocks and management system

The main fisheries for cod in the Baltic use demersal trawls, high opening trawls (operating both pelagically and demersally), and gillnets. There has been an increase in gillnet fisheries in the 1990s and the share of the total catch of cod taken by gillnets reached 35-50%. However, the size of gillnets fleets decreased in recent years, and the trawl catches dominate the cod fishery, because the share of older and larger cod in the stock decreased. Cod is mainly caught in direct, single species fishery. A small amount of cod is also taken as by-catch in herring, sprat, and flatfish fishery. High cod catches of around 400 thousand tons were observed in first half of 1980s. Next, catches were generally decreasing and in 2000-2001 declined to ca. 90 thousand tons. Substantial underreporting of catches was observed after 1990 – in recent years it was assumed at a level around 35-45% but it is known that this percentage is under-estimated. Since 2001 it has been an attempt to implement new more selective codend (Bacoma) and to increase the mesh size in Baltic cod trawls. The regulations varied following reaction of the industry to the imposed measures. Finally, Bacoma with 110 mm mesh size and minimum landing size of 38 cm were introduced. In 2006 the trawls with 90 degree turned netting were allowed (T90 trawls) by the Council Regulation 2187/2005. They show selective properties similar to Bacoma. Two Baltic cod stocks have been separated on biological grounds: the western stock in ICES Subdivisions 22–24, and the eastern stock in Subdivisions 25–32. They show differences in meristic and morphometric characters, otolith structure, genetic characteristic, and the stock dynamics. The stocks mix in the Arkona and Bornholm Basins. Both stocks are heavily exploited with fishing mortality often exceeding 1.0. This mortality is 3 times higher than the mortalities producing high long-term yield. In 2006, the eastern stock was evaluated by ICES as having reduced reproductive capacity, while the western stock had full reproductive capacity. The estimates of the eastern stock biomass are very imprecise due to large underreporting. Assessment which includes guesstimates of underreported catches indicates that the SSB in 2002-2004 was at level of 70,000 tons, i.e. ca 10% of values recorded in early 1980s. In case of the western stock the biomass in recent years has been at level of 50% of highest observed values. The recruitment to the stocks is very much dependent on environmental conditions, especially in case of the eastern stock for which recruitment abundance depends on the inflows of the North Sea water with characteristic enabling successful spawning. Strong year-classes were born at the end of 1970s and beginning of 1980s which has led to record high stock development in first half of 1980s. Next, year classes were generally weaker as environmental conditions got worse and the spawning stock biomass declined due to strong exploitation.

Up to 2003 the IBSFC (Baltic Commission) managed the Baltic cod in one management unit, covering all Sub-divisions 22–32. However, ICES considers the stocks in Subdivisions 22–24 and Subdivisions 25–32 as separate stocks, and ICES provides assessment and advice on both stock units separately. ICES stressed in its advice that the cod stocks should be managed separately in order to better adapt the exploitation to the present development in the two stocks. Since 2004, the Baltic Fishery Commission has managed two cod stocks separately, following the ICES advice. Both stocks are managed on the TAC basis. IBSFC in 1999, has agreed to implement long-term management plan consistent with precautionary approach. In 2002, a recovery plan for Baltic cod was adopted. In addition to TAC management a suite of technical measures have been implemented. These are:

  1. time and area closure (summer ban, spawning area closure)
  2. minimum landing size
  3. minimum mesh size
  4. limits of cod by-catch in herring and sprat fishery.

However, neither the long-term management plan of IBSFC nor the recovery plan were successfully implemented, mainly due to large underreporting of the catches. As IBSFC was dissolved in 2006, the EC started to develop a multi-annual plan for both cod stocks (western and eastern) and implemented it in 2007. The plan aims at gradual reduction of cod fishing mortality to levels producing high long tern yield and low risk for spawning stock biomass to drop below threshold levels. Simulations showed that fishing mortalities reflecting above goals are at level of 0.6 for western stock and 0.3 for eastern stock. These values are used as target F’s in the plan.

Young cod have been discarded at a level over 90% at age 1 and 30 – 70% at age 2. However, discard does not seem to be a major problem for the stock(s) as it is usually responsible for mortality of less than 1%. Assessment of cod the stocks (especially eastern stock) suffers from two basic shortcomings:
- there are substantial differences in age reading between countries,
- there is substantial underreporting of catches.
In addition, change of survey gear and design may have added some uncertainty to assessment as tuning data had to be re-calculated into new units. The change in survey design is difficult to correct for.

Description of the base case and scenario evaluations

Base case and scenario evaluations in relation to Case Study 9 Approach 1

The base case is defined using standard assumptions of the Baltic Fisheries Assessment WG for the assessment and stock projections.

These are: XSA assessment (Shepherd, 1999), year dependent weight-at-age in the stock, varying by periods maturity-at-age, survey and commercial fleets used for tuning, natural mortality of 0.2 constant over years and ages, and hockey-stick dependence of recruitment on SSB. However, in this Approach 1 the base case is used only for the described below management issue no. 3 (Bias in stock assessment due to underreporting (misreporting)). The base case is not relevant for the management issue no. 1 (Evaluation of alternative assessment models) while for the management issue no. 2 (Effects of implemented technical measures on stock dynamics and management) the work has started right away with development of the full model. In Approach 1 only cod was considered as cod in the Baltic is mainly taken in the directed fishery and cod by-catch in other fisheries is low. The stock was modelled as an age-structured population with varying growth and maturity. Cod cannibalism was not included as it can be substantial only in periods of strong stock increase (e.g. first half of the 1980s) and there are difficulties to quantify it (different models produce very different results). The hockey-stick recruitment sub-model corrected for environmental conditions was used because recruitment to the stock is largely dependent on relatively rare strong inflows of North Sea water and (to lower extent) on spawning stock size. In the fishery operating model two fleets were simulated: trawls and gill-nets. Selectivity at age was considered as the catches of the two fleets have different age structure and changes in mesh size and type of gears were occured after 2000 in Baltic cod fishery. Discarding was included as mesh size regulations and minimum landing size lead to some discarding, which may be substantial for strong year-class. Spatial and temporal structure of the fishery was taken into account to allow modelling management with closed seasons and perhaps areas.

The management procedure will be composed of - assessment model - advice - decision making - implementation error (fishermen adaptation) The standard ICES assessment model is an XSA tuned with survey and commercial CPUEs. Advice is usually provided in terms of fishing mortality and corresponding catch limit (TAC). Decision making model will base on advised TAC changed by some factor. Implementation error has to be included due to substantial underreporting. The way to include it may be also correction of adopted TAC by some factor related to changes in fleet size and TAC.

In the economic model the base case will be an open access. The prices may be constant or depending on landings in other variants of the operating model. The costs will be modeled by quadratic cost function (costs proportional to square of the catches per unit of stock biomass), varying with years and fleets. Fishermen behavior will depend on profits: the effort (or fishing mortality) in given time unit will depend on effort in previous time unit corrected by the term related to the profit and an adjustment parameter (some increase of effort when profit is positive, decrease of effort when profit is negative).

Scenario evaluations (and base case) in relation to Case Study 9 Approach 2

Approach 2 is a bio-economic evaluation and simulation of effort regulation, closed fishing areas and seasons, effect of different levels of compliance in relation to mis-reporting of landings, and effect of different climate driven levels of eastern Baltic cod stock recruitment for the international Baltic cod fisheries.

General

With respect to model development and implementation covering the Baltic examples and case studies under EFIMAS (mainly relating to approach 2under CS9) DTU Aqua has joined forces between the two international EU-FP6 projects EFIMAS and PROTECT, which DTU-Aqua are internationally coordinating, as well as with the Baltic case study of the EU-FP6 CEVIS project, in which DTU-Aqua also is the primary participant and contributor, as well as with a Danish national project. The collaboration has resulted in developing and further development of bio-economic models and tools for management evaluation. These tools, being integrated fleet- and stock based as well as spatial-temporal disaggregated, have been designed to evaluate various aspects of effort management including closed fishing areas and seasons for the cod fisheries in the Baltic Sea. Furthermore, DTU-Aqua has been working together with ICES ACFM and the EU-FP-6 projects BECAUSE and UNCOVER regarding evaluation of eastern Baltic Sea cod multi-annual management strategies. All of these developments and evaluations are connected to the proposals from the EU-Commission regarding management of cod fisheries and stocks in the Baltic Sea. (see: EU Commission 2006. Proposal for a Council Regulation establishing a multi-annual plan for the cod stocks in the Baltic Sea and the fisheries exploiting those stocks. EU Proposal 11984/06 PECHE 238 – COM(2006) 411 final).

Project collaboration has lead to the development of fleet based biological and bio-economic models for evaluation of effort control including closed areas and seasonal closures, evaluation of effects of mis-reporting of cod landings in the Baltic Sea, effect of climate driven different levels of recruitment to the eastern Baltic cod stock, as well as the evaluation of long term based management strategies of the Baltic Sea especially focussing on the international cod fisheries and cod stocks in the Baltic Sea.

Approach 2a

Through the EU-FP6-EFIMAS project DTU-Aqua developed and implemented a spatially-explicit fisheries’ effort reallocation simulation framework for evaluating the effect of various management scenarios on fisheries and stocks (Bastardie et al., 2008). This framework was developed under FLR (Fis¬heries Library in R) (www.efimas.org and http://wiki.difres.dk/efimas/doku.php). The framework has been applied to the international cod fisheries in the Baltic Sea with the purpose of evaluating and comparing the bio-economic consequences of various selected management scenarios comprising various management regimes and environmental circumstances. The simulated management regimes include TAC control compared to effort control in the form of direct effort control as well as indirect effort control through closed areas and seasons. The different environmental scenarios cover situations of favourable conditions for cod-recruitment in connection with a larger inflow of Atlantic seawater into the Baltic Sea compared with low-inflow situations followed by relatively low stock recruitment. The programme includes linkage of a spatio-temporal dis-aggregated biological and fleet-based model (developed by DTU-Aqua) with a superstructure of an economic model (Hoff and Frost 2006) developed by the EFIMAS partner FOI (Institute of Food and Resource Economics). The model framework has been calibrated and implemented to internationally fleet-based and spatially- and temporally-disaggregated landing and fisheries effort-data for cod-fisheries in the Baltic Sea, and installed in a database through the mutual project work. The year 2003 was chosen as the year for model calibration (conditioning), being the latest year having common international fleet-based and spatial-temporal disaggregated data available. The different scenarios have been evaluated, thus producing preliminary results with a model output. The developed simulation frame and the cod fisheries illustration conditioned to 2003 data with the preliminary results of the evaluations provided by the simulation ouputs, are presented in Bastardie et al., (2008). This is also linked to the work in Nielsen et al. (2008, in revision) where data and results from an analysis of fleet-selection, sorting- behaviour and of fleet-efficiency is being presented and has been used in the present modelling.

Approach 2b

Through the collaboration between especially the EU-FP6 PROTECT project and the EU-FP6- EFIMAS project the fleet-based and area-based biological ISIS-Fish Model or Framework which IFREMER in France originally developed (Mahévas and Pelletier, 2004) was implemented with the purpose of evaluating the various management scenarios for closed areas (indirect effort-control) for cod-fisheries in the Baltic Sea. When applying this model, evaluation has taken place as to the effect of closing different areas in the Baltic Sea starting from various scenarios for cod-recruitment based on variable environmental conditions.

The model has applied the same data, for conditioning, calibration and for the starting-point of the evaluations as used for the FLR model-framework under Approach 2a and the TEMAS model-framework under Approach 2c, i.e. the international, spatial-temporal, disaggregated and fleet-based landing and effort-data for the 2003 cod-fisheries in the Baltic Sea. Also, the model has applied the same data and results of Nielsen et al. (2008, in revision) for fleet-selection, sorting-behaviour as well as fleet-efficiency.

Approach 2c

EFIMAS has developed the fleet-based, bio-economic management evaluation-model and framework TEMAS (Ulrich et al. 2007), which in the EFIMAS project is called “Evaluation Frame” (www.efimas.org and http://wiki.difres.dk/efimas/doku.php). This is based on collaboration between EFIMAS, PROTECT and a Danish national project, and the implementation and application to fisheries in the Baltic Sea has focussed especially on international cod fisheries. Regarding the application, the original TEMAS-model, developed through the previous Danish national DFFE-TEMAS project collaborating with the EU-FP5-TECTAC project, has been considerably expanded as to area disaggregates and as to the model capacity in relation to the evaluation of closed seasons and areas and effort regulation. The model is targeted towards bio-economic evaluations of stock- and fleet-based effects on season- and area-divided bases of various effort management scenarios.

The Baltic Sea implementation of the model has been targeted to develop and establish a model framework which can evaluate the effects of effort control in the Baltic Sea, being indirect effort control through closed areas and seasons as well as direct effort control through regulations of sea-days/kW-days and fleet-capacity.

Fleet selectivity, catchability and partial fishing mortality studies

During the project collaboration with EU-FP6-EFIMAS there has been made a number of analyses of international cod fisheries and fleet-division in the Baltic Sea. This has been done in order to identify robust fleet-categorizations and to estimate fleet, area, and seasons based partial fishing mortality, catchabilities and effort taking into consideration the fishery effectiveness (fishing power) of the different fleets against the implicated cod stocks in the Baltic Sea. This has, in addition, comprised analysing the effort allocation compared to fishery-behaviour, catch-combination and composition, fleet economy and other fisheries activities outside this area. Furthermore, the work has analysed and estimated fleet-based selectivity and discard-behaviour in relation to access to resources (the latter targeted towards cod). Finally, the work has analysed and estimated, through BITS surveys the relative availability of cod-resources by length / age group in various areas and quarters. The objective of the work has been the implementation and conditioning of input-data, results and categories including the possible implementation of reference tuning fleets, developed and undergone further development and implemented in the Baltic Sea, in the management evaluation frameworks FLR, Evaluation Frame/TEMAS, and ISIS-Fish.

Other

An evaluation of multi-annual management strategies for cod in the Eastern Baltic Sea was realised though the collaboration with ICES ACFM as well as the EU-FP6 projects: BECAUSE and UNCOVER (Vinther and Köster, 2007). This has been carried out in the light of the proposed management strategies for the cod-stocks in the Baltic Sea by the EU-Commission including evaluation of the adaptive F-approach: reducing fish-mortality by 10% a year until F(4-7) is 0,3. The evaluations have exclusively been stock based and for TAC control, i.e. they do not include direct fleet-based evaluation of effort control and the closing of areas and seasons. This work is presented in Vinther and Köster (2007). This work is not reported under EFIMAS, but the results can be found in: Vinther, M. and Köster, F.W. 2007. Evaluation of harvest control rules for Baltic cod 25-32. Working Document to ICES ACFM May 2007: 28 pp.

Case specific management issues being addressed

1. Evaluation of alternative assessment models
There are significant difficulties in age interpretations of the Baltic cod. Since 1994, ICES has co-ordinated work on consistent interpretations of cod age reading but the progress is very limited (ICES 1994, 1999, 2006). Still two schools of age reading exist: western (Sweden, Denmark, Germany) and eastern (Latvia, Poland, Russia). These differences obviously create the bias at least in absolute estimates of spawning stock size which should be investigated. Some unpublished analyses suggest that the spawning stock biomass estimates may differ by the factor of 2 depending on which methodology of age reading is applied. This in turn would also impact the estimates of reference points and thus the management advice. Another advantage of production/difference models is that they usually allow for errors in the catches while in standard ICES assessment methodology for cod in the Baltic (XSA at present) the catches are treated as exact. This feature of production models is important in light of large underreporting of cod catches. The age independent models (the stock-production or difference models) were used for stock assessment and providing the management advice. It were both classical production models (e.g. Schaefer 1954) and difference models with explicit recruitment sub-model (Horbowy 1992). The commercial CPUE as well as survey data were used for tuning of production and difference models.

2. Effects of implemented technical measures on stock dynamics and management
Apart of the TAC management Baltic cod has for several years been managed with some additional measures such as closed areas, seasons, implemented new mesh sizes and gears (e.g. Bacoma codend). The aim of the closed areas and seasons was both to protect cod during spawning time and to constrain somewhat fishing effort. The relative effects of technical measures are to be evaluated. The evaluation will have to address temporal and spatial distribution of the fisheries to deal with closed season/areas. Also, size structure of the stock and catches will be needed if selectivity effects within technical measures will be modeled.

3. Bias in stock assessment due to underreporting (misreporting)
The decrease in stock size observed in the late 1980s and 1990s has led to decrease in advised and agreed TAC which, thus, became restrictive. This has further led to marked underreporting of cod catches. The share of unallocated catches in the middle 1990s amounted up to 40%. Although many steps has been undertaken to constrain underreporting, it is still significant. The indirect evidence of underreporting is well elucidated from the ratio of survey biomass to the catch based analytical model (XSA) estimate of biomass, which shows some trend in the 1990s and is higher than in the 1980s. It is estimated that the level of underreporting after 2000 was at least 35-45% and some estimates suggests that it may have reached ca. 80%. As a result the stock size is probably underestimated. In consequence, the biological reference points (BRP) used so far may be biased, as they are based on stock-recruitment relationship. The implementation error model will have to simulate the amount of underreported catches which may be included as e.g. certain fraction of adopted TAC or be related to fleet size.

In addition to the above management issues, according to the EFIMAS Project Contract Technical Annex, the effects of management with one or two management/assessment units were to be addressed. However, in the meantime from when the project was applied for and now the Baltic Commission agreed to adapt management to conform to the biological structure of the cod stocks in the Baltic Sea (i.e. to two different stocks). Thus, this management issue is not longer relevant to evaluate and, consequently, the EFIMAS Case Study 9 Group and the WP4 Coordination has decided to omit this from the further analyses under Case Study 9.

Description of approaches for scenario evaluations

Results (summary of scenario evaluations)

1. Evaluation of alternative assessment models

Two approaches in modelling were undertaken. In first (Approach A) the models were fitted to observed data for Baltic cod stock and fishery and used for prediction. In second (Approach B) the models were fitted to data sampled from generated stock, in which different aspects of cod biology and exploitation were simulated, aspects no covered (or partly covered) by applied assessment models. In addition, in that approach the effect of bias in age reading on XSA estimates was analysed.

Approach A

Classical stock-production models (Schaefer, 1954; Fox, 1970; Pella and Tomlinson, 1969) and the difference model (Horbowy, 1992) were used to simulate Baltic cod dynamics. The Schaefer model and the difference model of Horbowy showed satisfactory fit to the data and produced stock dynamics estimates similar to estimates from the standard ICES stock assessment. The models were also used for retrospective stock and catch prediction (similar as ICES short-term prediction) for years 1998-2005. The retrospective predictions of the catches and stock size with the Schaefer and difference model performed similar or better than the standard ICES predictions. An biologically based analytical tool for this evaluation has been produced in R, and simulations with this model were performed. The model was parameterized, showing good correspondence with observed data. Furthermore, the R scripts for the Schaefer and difference models were submitted to the FL-CORE-Group for further incorporation of this into the R/FLR fisheries management evaluation framework.

Approach B

Within this approach the Operating Model was applied for testing the performance of Schaefer and difference models in stock assessment. The cod stock with specific dynamics and harvest rules was generated for years 2005-2024. Next, the data from generated stock needed for assessment were sampled, and assessment with Schaefer and difference models was performed. Finally, obtained results were compared with generated values to see how well the models approximated the stock, given imposed aspects of the generated stock. Sampling from generated data and re-assessing the stock was usually performed in 200 replications. The generated stock included aspects such as sudden pulse in recruitment (simulation of inflow of North Sea water positively affecting cod recruitment), change in selectivity (to take account of changes in fishing gear and mesh size in Baltic cod fishery), and bias in age determination (to investigate the robustness of XSA to age mis-specification).

Conclusions from simulations results

Production/difference models

  • Difference model performed much better that Schafer model
  • For difference model disturbance in recruitment did not create major errors while change in selectivity produced bias in biomass estimates
  • For Schaefer model in all scenarios huge deviations from generated values were observed

XSA and aging bias

  • When catch at age and survey at age bias were the same, estimates of SSB differed very little from generated values. This error was somewhat higher in case of historical fishing mortality, and increased when catch at age and survey at age bias were very different.
  • The age bias had very big effect on stock and F estimates in terminal year
2. Bio-economic evaluation and simulation of effort regulation, closed fishing areas and seasons, effect of different levels of compliance in relation to mis-reporting of landings, and effect of different climate driven levels of eastern Baltic cod stock recruitment for the international Baltic cod fisheries

Approach 2a and 2b

The bio-economic models developed under Approach 2a and 2b (below) point at important key indicators for the cod stocks and fisheries conditions. Ensuring the efficiency of regulations for Baltic Cod required testing some important assumptions about the relationship between where and how much people fished and how the Baltic Cod stock would change as a result. To achieve this, the behaviour of the fishers needed to be integrated into the exercise. It is necessary to understand how fleet behaviour change across both time and space in response to both how the fish move and the implementation of regulations involving area- and season-based restrictions as well as compliance to regulations (i.e. non-compliance or mis-reporting in relation to TAC regulations). Under Approach 2a a simulation frame was developed in R using the FLR open-source platform. The model we developed so it consists of three sub-models: (i) a multi-stock module that considers how the populations of fish stocks in different areas change; (ii) a multi-fleet module taking into account of the heterogeneity of the fishing practices; and, (iii) a management module that could examine both conventional management techniques and permanent or temporary closed areas and seasons. All these components operate on a spatial grid matching underlying data in monthly and spatially dis-aggregated observations. Log-book data has been used to assess fishing patterns and there has been developed some equations suggesting how fishing patterns might change in response to either management measures or fluctuations in the fish stocks. Finally, there has been added an economic description of the fishery to the model. From the results it is possible to consider how economic conditions and indicators for this might have an impact on the displacement of fishing effort, changes in fishing activities or vessel capacity. The model has been used to test various scenarios for the Baltic cod fishery. These included two different ways to design the operating model, two compliance scenarios (including or excluding mis-reporting levels indicated by ICES), two different scenarios of environmental impacts, and three different management strategies. The simulated management regimes evaluated included TAC management, with among other a one-year time lag TAC, compared to effort management in the form of direct effort control as well as indirect effort control through closed areas and seasons (as suggested by EU DG MARE) Also the “F-adaptive approach” suggested and implemented by EU and considered in the ICES Baltic Fisheries Assessment Working Group (ICES WGBFAS) for the recovery of the Baltic Cod was considered. The different environmental scenarios evaluated cover situations of favourable conditions for cod-recruitment (and indicators for this) in connection with a larger inflow of Atlantic seawater into the Baltic Sea compared with low-inflow situations followed by relatively low recruitment. Levels of mis-reporting and indicators for this were also evaluated as significant. Finally, different assumptions about how fishers might behave in response to the above were examined.

The successful implementation of the model as well as the results from the simulations performed with the model is presented in the scientific paper:

Bastardie, F., Nielsen, J.R., and Kraus, G. 2008. Management Strategy Evaluation framework for the Eastern Baltic cod fishery to test robustness of management against environmental conditions and fleet response scenarios. (Submitted ICES J. Mar. Sci.) paper

FOI’s work has been carried out as a collaboration within the EFIMAS and PROTECT projects as well as a Danish national project, in which FOI also participates. FOI has contributed with financial information to DTU-Aqua’s data-models as described in the applications of the FLR (Approach 2a) and Evaluation Frame/TEMAS (Approach 2c) frameworks, and with the AHF model, developed by FOI. The latter having been implemented by DTU-Aqua into the FLR model (see Bastardie et al. (2008)), Furthermore, collaborating with the EU-FP6-PROTECT Project FOI developed a model, BEMCOM, based on FOI’s EMMFID and AHF models, but expanded with a component for stock-dynamics and a component that additionally disaggregates water areas as to the EMMFID model. BEMCOM supplements the TEMAS and ISIS-Fish evaluation frameworks as the model among other can calculate the optimum “paths” for stock- and sea-days-development and dispersion in areas, due to various management initiatives. The latter work still goes on and will be reported during 2008 through the EU-FP6-PROTECT project reports.

Approach 2b

The implementation of the ISIS-Fish model has been successful, and this as well as the results of the evaluations and simulations performed with the model is given in the scientific paper listed below.

Under favorable environmental conditions a simulation without closures showed a stock recovery to levels around Bpa after 18 years, even when the effort was increased to account for illegal landings and discarding. This indicates that the present total effort would be sustainable on the long run under such conditions.

On the contrary, under unfavourable environmental conditions, none of the proposed or implemented closure scenarios was able to recover the stock even to Blim. Such a scenario of consistently low recruitment might be overly pessimistic as even during long stagnation periods, infrequent inflows were observed.

As both population and exploitation models are subject to some uncertainties, the interpretation of SSB and yield should be cautious. Knowing that, our results demonstrated that closed seasons of the entire fishing area had a much larger impact on recovery rates, final stock sizes and yield compared to regionally restricted spawning area closures. A possible reason for the limited impact of spawning closures might reside in the effort reallocation rule implemented in our model.

In summary, our results showed that the ISIS-Fish model for Baltic cod is producing scenarios of stock and yield development in a realistic order of magnitude and comparable to past projections (ICES, 2005). The 1995 closure scenario provided an option to compare simulation results to data from stock assessment during years where the simulation period overlapped with the assessment (ICES, 2005). The comparison yielded a 50% higher SSB of the simulation at the end of the overlap period. The difference might be explained by the lower exploitation rates in the model due to a longer closed season in the simulation compared to the closed seasons implemented in the real world during most of the overlap years. Considering this difference, both estimates correspond well and proof the validity of our model.

Despite the strong and obvious influence of environmental conditions, we further conclude that conditioned on model assumptions for effort reallocation, the reduction of effort and thus fishing mortality as imposed by closed seasons is more efficient at stock recovery rather than reduction of spawner disturbances through the implementation of spatially restricted spawning closures. An effective, traditional management regime may thus be a viable alternative to the MPA design currently implemented in the Baltic Sea

Kraus, G., Pelletier, D., Dubreuil, J., Moellmann, C., Hinrichsen, H.H., Bastardie, F., Vermard, Y., and Mahevas, S. 2008. A model-based evaluation of marine protected areas for fishery management in the case of strong environmental forcing – the example of Eastern Baltic cod (Gadus morhua callarias L.). (Accepted; DTU-Aqua).
Paper with results

Approach 2c

The TEMAS “Evaluation Frame”(EF) of fisheries management regimes (Ulrich, Andersen, Sparre, and Nielsen, 2007) is presented and further developed through model application for the Baltic cod fisheries (Sparre, 2008b), together with the simulation model behind it (Sparre, 2008a,b). The EF executes two parallel simulations of the reference system and the alternative system. Each system comprises an “operational model” which simulates input data to a “management model”. The operational model system simulates the “true world”, whereas the management model simulates the advisory process of ICES combined with the management procedures of EU. The simulations may be executed in deterministic modes as well as in stochastic mode. The management regimes are compared by aid of a suite of “measures of performance”, which are defined by the various groups of stakeholders. Examples are the traditional measures of ICES, the Spawning Stock biomass and the average fishing mortality. Other measures can be bio-economic measures such as the net present value of cash flow, or employment measured in man-years. The EF is demonstrated for marine protected areas (MPA), closed seasons, and restrictions on maximum number of sea days (effort regulation) as management tools for the Baltic cod fisheries. The purpose of these MPAs and effort regulations is the recovery of the Baltic cod stock.

Regrettably, the only obtainable international fishery data for different international fleets in the Baltic Sea to be used in the model (2003 data applied – see Approach 2a), has been for cod fishery leading to only Danish data for Baltic herring and sprat fisheries to be found. Furthermore, as for fisheries outside/beyond the Baltic Sea, the only obtainable data has been for the vessels partly operating in the Baltic Sea for the Danish fisheries and for the Danish fishing fleets and not for the international fisheries. This has made it difficult to obtain meaningful output from the model in the present implementation.

The TEMAS model or Evaluation Frame as well as the application for cod fisheries in the Baltic Sea is reported in Sparre, 2008a; Sparre, 2008b. Sparre (2008a) is a users manual for the TEMAS/Evaluation Frame in its latest developed version for evaluating e.g. different management regimes (TAC management, effort control) and closed areas and seasons in the Baltic Sea with exemplifications from the same, and Sparre (2008b) is the reporting of the implementation of the model for cod fisheries of the Baltic Sea.

Sparre, P. J. 2008a. User’s Manual for the EXCEL Application “TEMAS” or “Evaluation Frame”. DTU-Aqua Report 190-08: 182 pp. ISBN 978-87-7481-077-3.
Users Manual for the TEMAS Evaluation Frame

Sparre, P. J. 2008b. Evaluation Frame for comparison of alternative management regimes using MPA and closed seasons applied to Baltic cod. DTU-Aqua Report 191-08: 298 pp. ISBN 978-87-7481-079-7.
TEMAS Evaluation Frame Baltic Application

Fleet selectivity, sorting behaviour, catchability and partial fishing mortality studies

Fleet based catchabilities and partial fishing mortality has been calculated through analyses of whole fishery selectivity, fishing patterns, and fleet catchability dynamics in international Baltic Sea cod fisheries - from observed spatio-temporal patterns in resource availability and fleet specific selection, relative fishing power, and fisherman sorting behaviour. This work and the results of these analyses area reported in the scientific paper listed below.

Fishery selectivity was analysed for variation when estimated as relative resource outtake by international fishing fleet on a spatio-temporal dis-aggregated scale. Coupled estimates of fleet specific relative effort allocation, gear selection pattern, relative sorting (discard) behaviour, standardized fishing power, and relative resource availability were used. To avoid bias in fleet catchability estimates (and resulting management advice) it has shown necessary to consider significant variation in those factors between fleets, areas, and periods, and to categorize accordingly. Vessels catching Baltic cod were categorized into fleets using an advanced effort allocation model and GIS-analysis considering effort and catch rate stratification as well as importance of landings resulting in spatio-temporal relative effort distribution by fleet. Modelling and ANOVA of fleet-gear selection estimated directly from comparison of research survey catch rates, reflecting resource availability, with fleet specific catch rates including discards from international observer sampling programmes revealed significant spatio-temporal diffe¬rences for important fleets. Modelling and ANOVA of fleet specific sorting behaviour estimated by comparing landings with total catch including discards by vessel and trip showed typically steep sorting ogives. Mainly fish under the minimum legal landing size was discarded. Fleet specific fishing power was estimated from GLM-ANOVA of cod-log-CPUE to obtain relative efficiency between fleets and standardized aggregated effort. It was significantly different between fleets with highest efficiency among large and medium sized otterboard-trawlers. Fisheries management and socio-economic management evaluation should consider those factors and their variation influencing catchability and overall fishing pattern when evaluating effects of spatio-temporal switching behaviour of fleets in response to regulations. This is becoming especially important when calculating, predicting, and distributing fleet specific partial fishing mortality or effort in effort regulation systems.

Nielsen, J.R., Bastardie, F., Nielsen, J.N., and Pedersen, E.M.F. (2008, In revision). Whole fishery selectivity, fishing patterns, and fleet catchability dynamics in international Baltic Sea cod fisheries – from observed spatio-temporal patterns in resource availability and fleet specific selection, relative fishing power, and fisherman sorting behaviour. (In revision) ICES J. Mar. Sci.

Economics

The economic AHF Model (Hoff and Frost, 2006; 2007) and the TEMAS Evaluation Frame (Sparre, 2008a,b) seeks to overcome the problems that arise when different management objectives are chased by using different management rules at the same time. Previous developed models such as the EIAA and the original TEMAS version were able to follow only one objective by one management rule. If, for example, the objective is stock recovery, the EIAA model could be used to analyse what happens economically if quotas were used, and the original TEMAS model could be used to assess what happens economically if sea days were used. The question that naturally arises is what happens if both, quotas and sea days, are used together. Briefly stated, the EIAA calculated the required number of sea days and vessels and hence the costs to catch a given amount (quota) of fish. The original TEMAS version calculated how much fish would be caught given a set amount of sea days and vessels. An obvious, but by far simple, approach to assessing the effect of combining the two management systems is to develop a method that joins the way EIAA and the original TEMAS version work with necessary amendments. The latest version of the TEMAS Evaluation Frame has a solution to the case where both quotas and sea days are used (see Sparre, 2008a,b). The AHF-model (Hoff and Frost, 2006; 2007) is constructed in such a way that if the quotas are more restricting than the number of sea days the model uses the EIAA approach. If sea days are more restricting than the quotas the original TEMAS version approach is used. The AHF-model is designed to switch automatically between the two approaches year by year. To operate in this way will further require a full feed back between fish stocks and fishing effort divided upon sea days and number of vessels. Therefore, the AHF-model includes procedures that determine changes in sea days and number of vessels as a function of the profitability of the fleet segments including the impact of entry exit from profitability reasons and decommissioning grants and the subsequent impact on the fish stocks in terms of fishing mortality.

As the AHF-model is, by and large, a combination of EIAA and the original TEMAS the data requirements are the same as for those models combined. For the North Sea case (see EFIMAS Case Study 2) developments are based on cod and haddock and a limited number of demersal fleet segments. A particular difficult question is to investigate what will happen if one fleet segment is restricted by quotas and another by sea days. The entire process requires careful considerations about causality and recursive procedures as describe below.

The model has been tested in an example for North Sea cod and flatfish, see Hoff and Frost (2006) and under EFIMAS WP4 Case Study 1, and shows satisfactory behaviour. The economic modelling for the North Sea demersal roundfish fisheries case (Case Study 2) has been carried out as part of the general modelling development for the three cases: Baltic Sea cod fisheries, North Sea flatfish fisheries, and North Sea roundfish fisheries. The aim is to construct a consistent model that is generally applicable and in which the economic part has a clear inter-phase to the biological part that estimates stock size fishing mortality etc. by use of XSA. In particular the EIAA and the original TEMAS models have formed basis for development of the general bio-economic model that is capable of taking into account several harvest rules on the output side (TAC) and the input side (effort) without violating causality and the recursive process (Hoff and Frost, 2006). The economic AHF module part is flexible with respect to included species and how the fleet segments are categorized. However, it basically follows the DCR definitions (Commission Regulation (1639/2001) with respect to the fleet, costs and earnings. The application to cod implies that relevant species and fleet segments are included but the basic structure of the model remains the same irrespective the species and fleets that are addressed.

Dissemination

Bastardie, F., Nielsen, J.R., and Kraus, G. 2008. Management Strategy Evaluation framework for the Eastern Baltic cod fishery to test robustness of management against environmental conditions and fleet response scenarios. (Submitted ICES J. Mar. Sci.) submitted paper

EFIMAS ECONOWS Report, Final Version 2008.
Final report ECONOWS 26/06/2008

Hoff, A., and Frost, H. 2006. Economic response to harvest and effort control in fishery. Report no. 185. Institute of Food and Ressource Economics. Copenhagen.
(http://www.foi.life.ku.dk/upload/foi/docs/english/docs_eng/publications_mark2/reports/serialised%20reports/2006/rapport_185%5b1%5d.pdf)
http://www.kvl.foi.dk/upload/foi¬/docs¬/publikationer/rapporter/rapport_185.pdf

Hoff, A. and Frost, H. 2007. Modelling Economic Response to Combined Harvest and Effort Control in Fishery.
http://www.univ-brest.fr/gdr-amure/eafe/eafe_¬conf/2007/¬hoff_frost_¬eafe¬2007.pdf

Horbowy, J. 2005. Cod assessment model with tuning to survey estimates of total mortality. Working paper to the WGBFAS, Hamburg, 12-21 April, 2005

Horbowy, J. 2006. Management of the eastern Baltic cod with stock-production or difference models. Poster to ICES Symposjum on evaluation of management strategies. SFMS 44, Dublin 2006

Horbowy, J. 2007. Two models of cod management – is complex model better ? (in Polish). Conference on “Mathematical models: explanation or over-simplification of ecology”. University of Toruń, June, 2007, Toruń, Poland

Kraus, G., Pelletier, D., Dubreuil, J., Moellmann, C., Hinrichsen, H.H., Bastardie, F., Vermard, Y., and Mahevas, S. 2008. A model-based evaluation of marine protected areas for fishery management in the case of strong environmental forcing – the example of Eastern Baltic cod (Gadus morhua callarias L.). (Accepted; DTU-Aqua).
Paper with results

Kronbak, L., Lindroos M. 2006. An Enforcemen-Coalition Model:Fishermen and Authorities Forming Coalitions. Environmental and Resource Economics, 35: 169-194.

Nielsen, J.R., Bastardie, F., Nielsen, J.N., and Pedersen, E.M.F. (2008, In revision). Whole fishery selectivity, fishing patterns, and fleet catchability dynamics in international Baltic Sea cod fisheries – from observed spatio-temporal patterns in resource availability and fleet specific selection, relative fishing power, and fisherman sorting behaviour. (In revision) ICES J. Mar. Sci.

Pietikäinen, L. 2005. Cod fishery of the European Union and Russia at the Baltic Sea - a game theoretic analysis. Department of Economics and Management, Working Papers no 30, University of Helsinki

Sparre, P. J. 2008a. User’s Manual for the EXCEL Application “TEMAS” or “Evaluation Frame”. DTU-Aqua Report 190-08: 182 pp. ISBN 978-87-7481-077-3.
Users Manual for the TEMAS Evaluation Frame

Sparre, P. J. 2008b. Evaluation Frame for comparison of alternative management regimes using MPA and closed seasons applied to Baltic cod. DTU-Aqua Report 191-08: 298 pp. ISBN 978-87-7481-079-7.
TEMAS Evaluation Frame Baltic Application

Ulrich, C., Andersen, B.S., Sparre, P.J., and Nielsen, J.R. 2007. TEMAS: fleet-based bioeconomic simulation software to evaluate management strategies accounting for fleet behaviour. ICES J. Mar. Sci., 64: 647-651.

Links to Other Work

With respect to Approach 2 there is a cooperation between the EU-FP6-EFIMAS and EU-FP6-PROTECT Projects with respect to evaluating effects of closed areas / closed seasons with the FLR-Model, the ISIS-Fish Model, and the TEMAS Evaluation Framework. Also with respect to EFIMAS Case Study 9 and Case Study 6 (and Case Study 4) there is a cooperation between the EFIMAS and PROTECT projects in relation to application of the ISIS-FISH Simulation Tool (FL-ISIS). The work under Case Study 9 approach 2 has also been done in cooperation with a Danish national government project, and the overall CS9 work has worked together with the ICES WGBFAS Assessment Working Group mainly with respect to Approach 1 but also in close communicaiton with Approach 2.

References

Deriso, R.B. 1980. Harvesting strategies and parameter estimation for an age-structured model. Can. J. Fish. Aquat. Sci. 37:268-282

EFIMAS ECONOWS Report, Final Version 2008.
Final report ECONOWS 26/06/2008

Fox, W.W. 1970. An exponential surplus yield model for optimizing exploited fish populations. Trans. Am. Fish. Soc., 99:80-88

Horbowy, J. 1992. The differential alternative to the Deriso difference production model. ICES J. mar. Sci. 49:167-174

ICES. 1994. Report of the Workshop on Baltic Cod Age Reading. ICES CM 1994/J:5

ICES. 1999. Report of the Study Group on Baltic Cod Age Reading. ICES CM 1999/H:Baltic Committee

ICES. 2006. Report of the Study Group on Aging issues of Baltic Cod. ICES CM 2006/BCC:08

Mahevas, S., and Pelletier, D. 2004. Isis-Fish, a generic and spatially explicit simulation tool for evaluating impact of management measures on fisheries dynamics. Ecological Modelling, 171: 65-84

Pella, J.J., Tomlinson, P.K. 1969. A generalized stock production model. Bull. Inter-Am. Trop. Tuna Comm. 13:419-496

Schaefer, M.B. 1954. Some aspects of the dynamics of populations important to the management of the commercial marine fisheries. Bull. Inter-Am. Trop. Tuna Comm., 1:25-56

Shepherd J.G. 1999. Extended survivors analysis: An improved method for the analysis of catch-at-age data and abundance indices. ICES J. mar. Sci., 56: 584-591

Ulrich, C., Andersen, B.S., Sparre, P.J., and Nielsen, J.R. 2007. TEMAS: fleet-based bioeconomic simulation software to evaluate management strategies accounting for fleet behaviour. ICES J. Mar. Sci., 64: 647-651.

Vinther, M. and Köster, F.W. 2007. Evaluation of harvest control rules for Baltic cod 25-32. Working Document to ICES ACFM May 2007: 28 pp.

See furthermore comprehensive list of references in:

Sparre, P. J. 2008b. Evaluation Frame for comparison of alternative management regimes using MPA and closed seasons applied to Baltic cod. DTU-Aqua Report 191-08: 298 pp. ISBN 978-87-7481-079-7.

and:

Sparre, P. J. 2008a. User’s Manual for the EXCEL Application “TEMAS” or “Evaluation Frame”. DTU-Aqua Report 190-08: 182 pp. ISBN 978-87-7481-077-3.

Acknowledgements

EFIMAS Contribution to the work

The work under this EFIMAS Case Study 9 has mainly been performed under EFIMAS. With respect to Approach 2 there is a cooperation between the EU FP6 EFIMAS, EU FP6 PROTECT and EU FP6 CEVIS Projects with respect to evaluating effects of closed areas / closed seasons with the FLR, ISIS-Fish, and TEMAS Evaluation Frameworks and Models. This cooperation has also included cooperation with a natinal Danish government project. Also with respect to EFIMAS Case Study 9 and Case Study 6 (and Case Study 4) there is a cooperation between the EFIMAS and PROTECT projects in relation to application of the ISIS-FISH Simulation Tool (FL-ISIS). The work under Case Study 9 is also done in Cooperation with the ICES WGBFAS Assessment Working Group mainly with respect to Approach 1 but also in close communicaiton with Approach 2.

Furthermore, we would like to thank for the contribution of fleet based catch and effort data for all Baltic institutes participating in EFIMAS.

Participants

Coordinator: Jan Horbowy (SFI)

Participants: J. Rasmus Nielsen, Francois Bastardie, Gerd Kraus, Per J. Sparre, Eva Maria Pedersen, Jacob Nabe-Nielsen, Ole Vestergaard, Bo S. Andersen, Clara Ulrich Rescan (DTU-AQUA), Ryszard Grzebielec, Magdalena Podolska, Krzysztof Radtke (SFI), Hans Frost, Ayoe Hoff, Jesper Andersen (FOI) Marko Lindroos (Uni Hel), Matti Salminen (FGFRI) Michele Casini (IMR-S), Ivo Sics, Maris Plichs (Latvia), German Institute for Sea Fishery (Hamburg), Dominique Pelletier, Julien Dubreuil, Youen Vermard, Stéphanie Mahevas (IFREMER), Christian Moellmann (Hamburg University), Hans-Harald Hinrichsen (IFM-GEOMAR).

Meeting Documents and Other Case Specific Work - working documents, models, analyses etc.

* Delivery Matrix by April 2006 Case Study 9 Delivery Matrix

 
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