Fishing activities include an integration of biology and economics, a recent new branch within economics that has resulted in a growing interest and use of bio-economic models (BEM) as tools for policy-makers and fishermen to understand the feedback effects between human activity and natural resource dynamics. Using mathematical representations of biological and economic systems known as bio-economic models (BEM), thirteen of these existing European Union models are presented and reviewed. Used in either the Atlantic Ocean of the Mediterranean Sea, the thirteen models (AHF, BIRDMOD, BEMMFISH, COBAS, ECOCORP, ECONMULT, EIAA, EMMFID, FLR, MEFISTO, MOSES, SRRMCF, and TEMAS) help bridge the gap between localized anthropogenic and environmental pressures. A diverse array of models is useful in helping policy-makers and fishermen answer real-life, complex fishery issues. Presello et al (2011) focuses on how BEMs evaluated anthropogenic and biological interrelated components as well as EU policy surrounding fisheries. –Alyshia Silva
R. Prellezo, P. Accadia, J. Anderson, B. Anderson, E. Buisman, A. Little, J. Nielson, Jan Poos, J. Powell, C. Rockmann. 2011. A review of EU bio-economic models for fisheries: The value of a diversity of models. Marine Policy 36, 423–431
There is an obvious and simple relationship between marine resources and users, extracting and fishing result in fish mortality, which is directly affected by biological components (predators, nutrient availability, etc.) and economic components (management, fuel costs, etc.). The need for BEMs and integrated approaches to sustainable fisheries comes from the fact that both economics and biology play a crucial and interrelated role within marine fisheries. BEM incorporates both biological variability as well as human behavioral traits using system dynamics, interactions and feedback mechanisms, key parameters, and data availability as well as their relationships with each other.
The two classifications of BEM are simulation (what if?) and optimization (what’s best?). Simulation models strive to simulate a system of biological and economic components into a scenario to evaluate alternative management strategies or model external variables. In comparison, optimization models are designed to find optimal solutions within a pre-defined objective, such as maximizing revenue, profit, harvest, fleet capacity, welfare, or minimizing day-at-sea costs or ecosystem impacts.
All thirteen of the models that were reviewed except MOSES could conduct simulations, while others models like EIAA, EMMFID, FLR, and SRRMCF can conduct both simulations and optimizations.
Conclusions from these models are also dependent on input (effort, gear restrictions, area closures) and output (quota, catch, composition, maximum landing size). BIRDMOD, BEMMFISH, COBAS, and MOSES solely model input controlled fisheries while the remaining models use both input and output regulated fisheries.
BEMs are intended to reflect the main features of the fishery under analysis including the fact that different management regimes are in force in different areas for different fisheries. However, many of the features of the models are not specific to regions and fisheries, so some aspects of these models, such as algorithms, are generic. None of the models provide a complete biological overview and some are easily driven by routine settings of single-species or multi-species outputs, recruitment relationships, and growth and maturity. There is a trade-off between the generality and complexity of BEMs. SRRMCF, EIAA, ECONMULT, and EMMFID do not have a biological component whereas other models, such as the FLR and BIRDMOD, have as strengths lie in biological components.
The BEMs’ economic components are heterogeneous but rely upon three common mechanisms: fleet and effort dynamics, price dynamics, and cost dynamics. However, approaches to using these mechanisms vary, depending on the purpose of the model, availability of data and their structure, and the features of the fisheries. Optimization or simulation models determine the relevance of the economic component and the approach used for its implementation, especially since both economic and biological data have different availabilities and detail.
Outputs of BEMs are mainly used by policy-makers and it is important that BEM results are standardized and made familiar so that communication between government and fishery experts is at its best. These models are made to assess and compare stocks with sustainable levels with catch capabilities and economic profit, as well as incorporate biological indicators (e.g. sustainable stocks), capacity indicators (e.g. catch capability), economic indicators (short or long term economic goals), and sociological characteristics (e.g. employment), all of which are important to building sustainable fisheries.
The utility of a model depends on the framing of the question being asked. While optimization models consider fixed prices, simulation models adopt elasticity functions to simulate marine dynamics. However, there is room for further integration between biological and economic components, as made clear in the fact that three of the BEMs were purely economic (ECONMULT, EIAA, EMMFID, and SRRMCF) while the remaining nine had both of an economic and biological component. However, all of these models require either economic or biological expertise.