Final Report Summary - CAFE (Capacity, F and Effort)
The CAFE project was designed to investigate the links between the fleet capacity, the fishing effort of those fleets and the fishing mortality that results from that effort, so as to facilitate the development of a fishing management strategy.
The effort was considered as the amount of time a given fishing capacity was deployed in a fishery. Therefore, engine power could be seen as a capacity measure and kilowatt hours as the expression of the effort from that capacity. This estimate allowed for capacity and effort to be directly linked within the project. CAFE proved that relating higher capacity and/or effort to higher fish mortality was a common misinterpretation. Thus, the project aimed to test the hypothesis that there was a quantifiable relationship between the capacity and effort by particular fleets and the fishing mortality imposed on the various commercial stocks.
In addition, CAFE tried to identify meaningful measures of capacity with definable and robust links to effort via utilisation. Conventionally, capacity was some combination of the vessel size and its engine power; however many factors could contribute to the fishing power, such as sea-keeping ability, the presence of factory systems and the fishers' behaviour. This approach could ideally be used for a more appropriate fishing management strategy.
Six different case studies were examined, to account for different climatic conditions, both pelagic and demersal fisheries and single and multi-species fisheries. A database was assembled by the involved partners for each specific case. Various alternative analytical approaches were proposed and the partners were able to select among them in order to quantify the relationships between the project parameters in their area. While many of the choices were dependent on the expertise of each involved party, the project also mobilised intellectual transfer between experts so that new approaches could be explored.
After the development of common format databases, an exploratory description of the cases was made and initial analyses were carried out so as to define a set of metrics which would provide the best links between capacity, effort and mortality. During these phase analysts were also able to explore which of the proposed methods better represented each specific case study and fleet. The combination of models and metrics was subsequently employed to quantify the links between the three variables. External factors which affected the fishers' choices were also identified. The modelling approach used both statistical and mathematical modelling techniques.
The models and the understanding gained through them were subsequently used to examine the response of the system to a range of management measures for controlling capacity and effort. A series of simulations were performed to examine the fisheries' response to limitations of capacity, effort or other measures. Several of the models were run using data of different case studies to test the general applicability of the approaches and observe existing differences between individual countries.
The project also examined historical approaches to capacity and effort management worldwide in order to provide the context for the various simulations and to serve as a reference in this management area. In addition, it focused on the investment on fleets, in order to understand the motivation for their development.
CAFE activities were divided in seven interrelated work packages (WPs), one of which was dedicated to project management. The remaining six focused on the following activities:
1. Review of the current practice in measurement of fishing capacity and effort and of methods of applying these to fisheries management.
This WP set out to provide the context and tools for the work carried out in the later WPs. Among its outcomes was that lack of understanding of the production processes in the past was a major factor for overexploitation of fisheries around the world. It also appeared that stochastic approaches could be more adequate for estimating technical efficiency in fisheries, while data envelopment analysis (DEA) was more appropriate for capacity modelling. In addition, in multi-species fisheries, it was proven inappropriate to set total allowable catches on an individual species basis.
2. Compilation of an information database from the case study fisheries, which included both fleet focused and stock focused data.
A common exchange format was constructed in order to define what data should be collected and in which all data would be held. An integrated catch and effort international database was also developed.
3. Definition of appropriate metrics which were most useful in empirical modelling to elucidate the links between the three examined parameters.
A wide range of metrics and analytical methods were explored. It was found that economic metrics may in some cases be more important predicators for fishing mortality than the physical characteristics of the vessel. In terms of effort, the days at sea remained the key determinant. It was also noted that, often, social factors influenced decisions on fishing, and thus modified the stock mortality. This had important implications for effort and capacity management as it suggested that the fleets were often highly adaptable in how they deployed their capacity.
4. Determination of the factors that drove changes in fleets' capacity over time.
Surprisingly profit did not appear to be a key driver for investment and interest rates did not appear to have a major effect. The overall conclusion was that there was no single factor that consistently drove investment in all cases studied. The differences in results were most likely due to differences in the fisheries characteristics, particularly differences in regulatory settings. A methodological report on how to carry relevant analyses was produced.
5. Determination of the factors which controlled how fishing capacity and effort were utilised and allocated and their impacts on fishing mortality.
These factors differed between fisheries; however, some general features were defined, such as the impact of input regulations and economic factors like the fuel cost and the price of fish.
6. Use of the understanding and models developed in the project to explore a number of potential management scenarios and provide recommendations for future capacity and effort based fisheries management.
Broadly, the findings were that, while any reduction would yield some improvement in mortality, the best performing scenarios involved both capacity and effort reduction. The results suggested that managing by controlling mortality would retain a larger, but relatively less efficient, fleet by 2015. The effect of the mesh changes proved difficult to evaluate in the presence of excess capacity.
All models developed as part of the project were potentially valuable for evaluating a range of capacity and effort management measures. In terms of the examined scenarios, results were promising for better understanding of capacity and effort control, even though assumptions had to be made. It appeared that a key concept for further development of the models would be the, as realistic as possible, replication of the dynamics involved in fishers' behaviour and their response to specific management measures.
The effort was considered as the amount of time a given fishing capacity was deployed in a fishery. Therefore, engine power could be seen as a capacity measure and kilowatt hours as the expression of the effort from that capacity. This estimate allowed for capacity and effort to be directly linked within the project. CAFE proved that relating higher capacity and/or effort to higher fish mortality was a common misinterpretation. Thus, the project aimed to test the hypothesis that there was a quantifiable relationship between the capacity and effort by particular fleets and the fishing mortality imposed on the various commercial stocks.
In addition, CAFE tried to identify meaningful measures of capacity with definable and robust links to effort via utilisation. Conventionally, capacity was some combination of the vessel size and its engine power; however many factors could contribute to the fishing power, such as sea-keeping ability, the presence of factory systems and the fishers' behaviour. This approach could ideally be used for a more appropriate fishing management strategy.
Six different case studies were examined, to account for different climatic conditions, both pelagic and demersal fisheries and single and multi-species fisheries. A database was assembled by the involved partners for each specific case. Various alternative analytical approaches were proposed and the partners were able to select among them in order to quantify the relationships between the project parameters in their area. While many of the choices were dependent on the expertise of each involved party, the project also mobilised intellectual transfer between experts so that new approaches could be explored.
After the development of common format databases, an exploratory description of the cases was made and initial analyses were carried out so as to define a set of metrics which would provide the best links between capacity, effort and mortality. During these phase analysts were also able to explore which of the proposed methods better represented each specific case study and fleet. The combination of models and metrics was subsequently employed to quantify the links between the three variables. External factors which affected the fishers' choices were also identified. The modelling approach used both statistical and mathematical modelling techniques.
The models and the understanding gained through them were subsequently used to examine the response of the system to a range of management measures for controlling capacity and effort. A series of simulations were performed to examine the fisheries' response to limitations of capacity, effort or other measures. Several of the models were run using data of different case studies to test the general applicability of the approaches and observe existing differences between individual countries.
The project also examined historical approaches to capacity and effort management worldwide in order to provide the context for the various simulations and to serve as a reference in this management area. In addition, it focused on the investment on fleets, in order to understand the motivation for their development.
CAFE activities were divided in seven interrelated work packages (WPs), one of which was dedicated to project management. The remaining six focused on the following activities:
1. Review of the current practice in measurement of fishing capacity and effort and of methods of applying these to fisheries management.
This WP set out to provide the context and tools for the work carried out in the later WPs. Among its outcomes was that lack of understanding of the production processes in the past was a major factor for overexploitation of fisheries around the world. It also appeared that stochastic approaches could be more adequate for estimating technical efficiency in fisheries, while data envelopment analysis (DEA) was more appropriate for capacity modelling. In addition, in multi-species fisheries, it was proven inappropriate to set total allowable catches on an individual species basis.
2. Compilation of an information database from the case study fisheries, which included both fleet focused and stock focused data.
A common exchange format was constructed in order to define what data should be collected and in which all data would be held. An integrated catch and effort international database was also developed.
3. Definition of appropriate metrics which were most useful in empirical modelling to elucidate the links between the three examined parameters.
A wide range of metrics and analytical methods were explored. It was found that economic metrics may in some cases be more important predicators for fishing mortality than the physical characteristics of the vessel. In terms of effort, the days at sea remained the key determinant. It was also noted that, often, social factors influenced decisions on fishing, and thus modified the stock mortality. This had important implications for effort and capacity management as it suggested that the fleets were often highly adaptable in how they deployed their capacity.
4. Determination of the factors that drove changes in fleets' capacity over time.
Surprisingly profit did not appear to be a key driver for investment and interest rates did not appear to have a major effect. The overall conclusion was that there was no single factor that consistently drove investment in all cases studied. The differences in results were most likely due to differences in the fisheries characteristics, particularly differences in regulatory settings. A methodological report on how to carry relevant analyses was produced.
5. Determination of the factors which controlled how fishing capacity and effort were utilised and allocated and their impacts on fishing mortality.
These factors differed between fisheries; however, some general features were defined, such as the impact of input regulations and economic factors like the fuel cost and the price of fish.
6. Use of the understanding and models developed in the project to explore a number of potential management scenarios and provide recommendations for future capacity and effort based fisheries management.
Broadly, the findings were that, while any reduction would yield some improvement in mortality, the best performing scenarios involved both capacity and effort reduction. The results suggested that managing by controlling mortality would retain a larger, but relatively less efficient, fleet by 2015. The effect of the mesh changes proved difficult to evaluate in the presence of excess capacity.
All models developed as part of the project were potentially valuable for evaluating a range of capacity and effort management measures. In terms of the examined scenarios, results were promising for better understanding of capacity and effort control, even though assumptions had to be made. It appeared that a key concept for further development of the models would be the, as realistic as possible, replication of the dynamics involved in fishers' behaviour and their response to specific management measures.