Working Packages

Working package 1: Data review

Despite the high quality of most of assessment models, data availability and its quality still limit the forecasting power of those models. Stock assessment models use multiple data as inputs in the modelling processes mainly derived from two different information sources: commercial fisheries and/or research surveys. Both sources include data of total catch, effort by gear, indices of relative abundance (from surveys or from catch per unit effort- cpue), data on fishing gears (e.g. mesh size) and fishing operations, length or age frequency and biological data (e.g. maturity stages, length/weight relationship, age or mortality). These data can provide information on estimated biological and ecosystem processes affecting stock dynamics that have to be parametrized to be included in the model. Sometimes, these parameters can be obtained directly from collected data, for example age-length frequency data from otoliths provide direct information on the growth parameter. However, commonly the modelled processes obtain information indirectly from different data sources, and therefore, the parameters representing these processes (e.g. growth and natural mortality) are usually assumed and fixed in the model. Unfortunately, the lack of reliable direct data on these processes implies the need to formulate uncertain assumptions about the stock what can substantially impact scientific advice. This impact can be even greater in those management systems for which complex decision rules are used to set annual catch limits. Within this context, the overall goal of WP1 will be to review existing information, identify knowledge gaps and improve the quality of models’ inputs by analysing the available datasets. To do so the WP1 will be divided in 4 tasks according to the nature and use of data:

Working package 2: Assessment models

The main goal of WP2 are to develop high quality assessment models with different level of complexity including data-limited models, biomass dynamic models, age-structured models, length-structured models and mixed species structured models. These models will consider the knowledge gaps identified in WP 1. Once these models are validated they will be used to develop alternative indicators and management references (GES, MSY, precautionary). The final models and references will be used to develop Operating models and test management strategies in WP3. To achieve this objective WP2 has defined the following sub-objectives: (1) to develop models able to deal with alternative stock boundaries as well as identifying critical habitats within boundaries; (2) to incorporate new biological and fishery knowledge as well as new abundance indices into improved assessment models; (3) to develop models that incorporate the new knowledge into data-limited stocks; (4) to develop multi-species models considering mixed fisheries interactions and (5) to estimate and propose management references (e.g. MSY, GES, precautionary) from both, data-rich and data-limited models. The final product of this WP will be a set of improved models and their management references to be used in WP 3. To address these goals WP2 is structured in 3 different tasks characterised by an increased level of complexity, from data-limited models, to data-rich models (both for single species) and finally mixed-species models considering interactions between species caught together in the same fishery.

Working package 3: Management Strategy Evaluation

Using FLBEIA as a simulation tool, with accessible outputs and results presented in an interactive interface, will enable the involvement of stakeholders, managers and fishing sector, in decision-making for fisheries management. Management strategy evaluation (MSE) is a simulation based approach that is used to explore the robustness of alternative management options quantifying the trade-offs among different management goals and across a range of management objectives. MSE is then a decision support tool that has seen wide use in fisheries management. Its main application has been in exploring single species harvest strategies, but the method can also be applied to mixed fisheries using the FLBEIA R toolbox http://flbeia.azti.es/. The strength of the MSE approach is that instead of using a single “best” model to find an optimal management solution, multiple candidate models can be assessed for alternative management scenarios. However, given the data, the capacity and computing requirements MSE framework is relatively complex method that is not used to give regular advice (e.g. annual TACs) but to evaluate more permanent regulations such as harvest control rules or management plans. WP3 will contribute to evaluate management strategies for the fisheries in the area. There is an MSE framework developed for Mixed fisheries in the MYFISH (EU VIIFP) project. IMPRESS will use this framework extending the number of species and reconsidering the current Operating model and Management procedures. Alternative MSE will also be developed based on the WP1 and 2 results, this can include data-limited models. The main goal of WP 3 is to build MSEs simulation framework for selected cases from WP2, both single and mixed fisheries. This framework has to be able to incorporate the models and uncertainties identified in previous work (WP1 and 2) to evaluate management strategies suggested by stakeholders. To achieve this objective WP3 has defined the following sub-objectives: (1) to explore the work performed in WP1 and 2 to conditioning the operating model (2) to define the management targets and constraints including Harvest Control Rules (HCR) considering manager and stakeholder and (3) to perform the MSE simulations and evaluate trade-offs among different objectives through analysis of performance statistics.

Working package 4: Synthesis and recommendations

The main objective of this task will be to synthesize all the results obtained by the precedent WPs in order to makes specific recommendations about how input data, assessment methods, and MSE need to be used and how can be effectively improved. These recommendations will be than divulgated as follow:

  • For each CS will be generated policy brief that clearly identify the current issues, the tested alternative solutions and the real improvement that the proposed solutions provided. This will allow to spread in a direct way the project’s results and developed tools to appropriate audiences so that the knowledge and recommendations generated by IMPRESS can be applied and have real and tangible impacts for the fishing management.

  • All the IMPRESS results will be formally presented in specific ICES working groups such as WGHANSA, WGBIE, WGEF, WGCEPH, WGMIX, etc. This will be possible as most of the IMPRESS teams already participate to these meeting as stock coordinator of the stocks considered.

  • The findings achieved in the IMPRESS project, as well as the developed tools will be published in peer-reviewed journal of high impact and in open-access. Similarly, results and recommendations will be presented in international and national conference of fisheries and governance science.

  • All the IMPRESS results will be presented to local fishermen organizations and fisheries advisory bodies (Fisheries Departments in the Autonomic Regions’ governments and Central Spanish government, the International Council for the Exploration of the Sea ICES) during the numerous meetings that the IMPRESS team already have with these stakeholders and national administration.

  • In order to outreach our results we will create a project website and social network profiles where information about the project achievement will be published. The scientific information obtained by the models and MSE simulations will be available through reports, working documents or R-Shiny web application presenting results from the stock assessment models and MSE applications.