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3.2.3 How other associated and relevant management evaluation frameworks and software are implemented under EFIMAS

As mentioned above the overall fisheries management evaluation tool developed by EFIMAS with help from sister projects is R/FLR which is described in detail in the below sections under the WP3-Chapter. Alongside with this development other bio-economic analysis, simulation and management evaluation tools and frameworks have been further developed, applied and implemented in some case studies as well. These tools have been seeked adapted to the R/FLR concept, and vice versa, and as such they support and complement the overall approach under the EFIMAS Project and its overall purpose.

TEMAS Simulation Tool and Evaluation Frame (EF)

The TEMAS (TEchnical MAnagement measureS evaluation framework) or the EF (Evaluation Frame) is a fleet-based bioeconomic software for evaluation of management strategies accounting for technical measures and fleet behaviour, implemented in Visual Basics with Microsoft Windows EXCEL interface. Focus has been the mixed-fisheries issues, where several fleets can choose between several fishing activities to target different stocks in one or several areas, as well as on evaluation of effort regulation and combinations of TAC and effort regulation. The effort regulation aspects covers both direct effort regulation on fleet capacity and sea days (activity) as well as in-direct effort regulation through closed areas and seasons. The software combines a Management Strategy Evaluation (MSE) framework, using a forward running Operating Model (OM) and a Management Procedure (MP) with a fleet behaviour module simulating both short-term (effort allocation) and long-term (entry/exit) fleet dynamics. The suite of models behind TEMAS can be thought of as extensions to the traditional ICES forecast model. Alternative management scenarios has been compared and evaluated with respect to their bioeconomic consequences and their robustness to parameter uncertainty. The software is generic and user-friendly, and can be run at several space and time scales. (Ulrich, Andersen, Sparre, and Nielsen, 2007. TEMAS: fleet based bio-economic simulation software to evaluate management strategies accounting for fleet behaviour. ICES J. Mar. Sci. 64: 647-651; Sparre 2008a,b (see below); Reports under EFIMAS CS9, Approach 2 at http://wiki.difres.dk/efimas/doku.php?id=efimas1:wp4:cs9:main; Reporting of EFIMAS CS1, Approach 2 at http://wiki.difres.dk/efimas/doku.php?id=efimas1:wp4:cs1:appr2:main).
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

The TEMAS / EF is under EFIMAS applied and implemented under Case Study 1, North Sea flatfish fisheries, Approach 2, and Case Study 9, Baltic Cod Fisheries, Approach 2c. In the North Sea flatfish case study, the focus is made on a detailed description of fleets activity and changes in effort allocation across mesh sizes and target species (“metiers”). The TEMAS model is used to investigate the effects of alternatives assumptions about fleets behaviour and effort re-allocation on stock dynamics and management success.
In the Baltic cod case, the TEMAS Model has been modified to be used to evaluate bio-economic effects of implemented technical measures and fishery closures on stock dynamics and management. Apart from the TAC management Baltic cod has for several years been managed with some additional measures such as closed areas, seasons, and implemented new mesh sizes and gears. The aim of the closed areas and seasons was both to protect cod during spawning and to constrain somewhat fishing effort. The relative effects of technical measures can be evaluated by the TEMAS Model in CS9. The operating model here address temporal and spatial distribution of the fisheries in order to deal with closed season/areas. Also, size structure of the stock and catches are included when selectivity effects within technical measures are modeled. This work is done in cooperation between the EU FP6 EFIMAS and PROTECT Projects. The TEMAS application in the Baltic Sea CS9 has focussed on evaluating effort regulation (both direct and indirect), the adaptive F- and E-regulation approach, as well as combinations of TAC and effort regulation practized today for the internaional Baltic cod fisheries.

Being an integrated software developed in a different environment, TEMAS/EF cannot communicate directly with R/FLR. However, main features from TEMAS (e.g. those dealing with mixed-fisheries and effort allocation) have been implemented under FLR (see for example Case Study 2, Approach 1 with respect to MSE and FCUBE originating from TEMAS.

TEMAS_OM_Flow Chart

The complete operational model, combining biology, technical features, economy and behavioural features, together with it’s links to the management model and the evaluation.

ISIS-Fish Simulation Tool and FL-ISIS

A main issue in the dynamics of mixed fisheries is that of technical interactions, leading to incidental catch and discarding. Technical interactions largely depend on the allocation of fishing effort between métiers and fishing grounds which in turn is tightly linked to economic conditions and to the expected profitability of alternative options for fishing effort allocation. The bio-economic ISIS-Fish fishery model (Mahevas and Pelletier, 2004) has been developed to investigate these issues, and in particular to explore the possibilities of mitigating these interactions through appropriate policy options, through a ISIS-FLR application (Bastardie et al. (Submitted) for Case Study 6 and Case Study 4, and Kraus et al. (Accepted) for Case Study 9). The bio-economic model was developed using and developing (creating) FLR (http://www.flr-project.org) packages as part of the EFIMAS project http://europa.eu.int/comm/research/fp6/ssp/efimas_en.htm). Under CS6 and CS4 ISIS-FLR model defines a set of classes and methods encapsulated in a R package named ‘FLIsis’ which is available for downloading at the FLR web site. The main approach under these case studies were to evaluate technical management measures in relation to the mixed nephrops-hake fisheries in the Bay of Biscay on a spatial scale (see below). Under the CS9 a standard ISIS-Fish approach was used in order to evaluate effects on the eastern Baltic cod stocks of fishing closures (MPA's) and effect of different environmental situations affecting cod recruitment. The ISIS-Fish model is spatially- and seasonally- explicit model. It considers population dynamics, exploitation dynamics, and policies are explicitly modelled building on the fishery model underlying the ISIS-Fish software (http://www.ifremer.fr/isis-fish\). As such the model is a multi-fleet, multi-stock model taking into account of the response of fishermen to a range of management rules through dynamic allocation of fishing effort.

FLISIS: ISIS model: ‘ISIS-FLR’ is a translation of the model underlying the ISIS-Fish software, initially coded in the Java language. ISIS-Fish (’Integration of Spatial Information for FISHeries simulation’) is a freeware for spatially- and seasonally-explicit simulation of the dynamics of multi-stock and multi-fleet interactions under a range of management options (e.g. MPA, catch and effort limitations, technical measures, etc.), already incorporates mixed fisheries, multispecies and economic models. The present model is a translation of ISIS-Fish inside the FLR environment and also incorporates alternative bioeconomic models. ‘ISIS-FLR’ is entirely developed in R using the FLR framework as a toolbox to generate fisheries-related objects from existing FLR classes. However, since the model encompasses the complex structure of mixed fisheries and emphasizes spatial and seasonal aspects, new classes have been defined for handling objects with specific extended properties.

The model is applied to the hake-nephrops fishery in the Bay of Biscay (and the Celtic Sea) under EFIMAS Case Study 6, Approach 2, and Case Study 4, Approach 2. Here the dynamics of the main fleets exploiting hake and nephrops are modelled, and the simulations investigated the consequences of several policy options, including present ones (Total Allowable Catch) and gear technical measures, and alternative options in cluding Marine Protected Areas, closed seasons, and selective devices.

Bastardie F., Pelletier D., Mahevas S., Guyader O., Thebaud O., Sauturtun M., Prellezo R. 2008 ISIS-FLR: An FLR-based bioeconomic operating model for mixed fisheries: framework and application. Submitted ELSEVIER.
submitted paper

The model is, furthermore, applied under the CS9 as a standard ISIS-Fish approach in cooperation with EU-FP6-PROTECT. Here it has been used to evaluate effects on the eastern Baltic cod stocks of fishing closures (MPA's) and effect of different environmental situations affecting cod recruitment.

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

The original ISIS-Fish model is described in:

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

Bayesian Approach

The population of wild Baltic salmon has undergone in the last century a severe decline, due to dam building, overfishing and pollution. The international effort to reverse this decline can claim success in some of the main Baltic rivers where stocks are seen to be recovering, yet some wild stocks remain highly depleted. From a policy perspective there is a desire to identify a management strategy that would have a high probability of safeguarding the stocks while minimizing economic and social hardships of regulation. The difficulty in designing experiments in the real world makes simulation an attractive realm in which to evaluate alternative management regimes. Accordingly, operating models that are designed to simulate a complex bio-economic reality is utilized in EFIMAS Case Study 3. Both structural and parameter model uncertainty is considered by using Bayesian methods that allow one to incorporate information from a variety of sources - both data and expert knowledge. Management procedures for Baltic salmon in a generic simulation framework based on the statistical programming language R are evaluated. Within the scope of the planned simulations, it is possible to explore many factors and scenarios. For example, the ecological effects of changes in the predator population (seals) and in the availability of food (sprat). The simulation-evaluation of harvest control rules is linked to the analysis of socio - economic changes associated with each regulation regime. The goal is to identify those stock rebuilding programs that are most robust to various sources of uncertainty and that are more likely to secure commitment from fishermen. Also the studies concerning Baltic Salmon under Case Study 3 comprise formulation and testing of different management strategies in simulations. The goal has been to identify those that perform better under a range of uncertainties. (Levontin et al., 2007). Other studies introduce a Bayesian probability model for making inferences about the unknown number of individuals in a sample, based on known sample weight and on information provided by subsamples with known weights and corresponding counts (Mäntyniemi et al., submitted), as well as illustrating certain theoretical and practical aspects of Bayesian population dynamics modelling in the context of juvenile salmon population (Mäntyniemi, submitted). See also WP4 Case Study 3 reporting.

Under FLR the FLBayes package has been established (see also section 3.3.2). This package is for running Bayesian interpretations of fisheries models. From this e.g. stock-recruitment relationships and a Shaefer/Pella-Tomlinson surplus production models are implemented as Bayesian models. The main use of the Bayesian stock-recruitment (FLSR package) implementations (see section 3.3.2) is when conditioning operating models on tuned VPA-type assessment results. The stock-recruitment relationship is not estimated at run-time as normally, but afterwards. The Bayesian alternative allows to incorporate the inherent uncertainty in this relationship (both parametric and random uncertainty) into the OM. The Bayesian Pella-Tomlinson surplus production model allows to assess stocks that may be data poor, or lacking in age information, but also serves as an OM in itself, and can be used as a management tool in a larger management procedure in a fully age-based problem.

J. Rasmus Nielsen 2008/09/08 17:34

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