Ecosystem-based global fishing policy scenarios

The future of fisheries and marine ecosystems at the global scale, until recently, was often expressed in terms of qualitative storylines with limited quantitative information on how aspects of fisheries such as landings, profits and biodiversity would respond, which constrained the comparing of outcomes across geographic areas. However, the construction of a stratified global model, EcoOcean, has met many of the challenges of quantitatively assessing the future of fisheries under different scenarios. Using the Ecopath with Ecosim (EwE) software, a series of 19 marine ecosystem models representing the 19 FAO areas of the world’s oceans and seas was constructed. The models were populated using global datasets of catches, ex-vessel prices, biomass and distant water fleets from the Sea Around Us Project and the fleet statistics from the Food and Agriculture Organization of the United Nations (FAO). The fleet statistics were used to develop a global database of fishing effort for the five fishing fleets in the model from 1950 to 1998, the last year for which the data are available. Modelling the five fisheries over the 19 FAO areas from 1950 to 2003 resulted in an aggregated global total that was within 10% of the reported total for any given year. This gave some confidence that the models are providing plausible results for different scenarios, in particular for the four scenarios of the Global Environment Outlook 4 and the four scenarios of the International Assessment for Agricultural Science, Technology and Development. This work also provided the opportunity to look at the future of marine biodiversity to 2048, using a depletion index as a proxy for changes in species composition and abundance under the different scenarios. This report presents the background and development of EcoOcean, the model structure, a detailed description of the effort reconstruction, and the underlying datasets that are used to construct and drive the models, especially prices and jobs. The report also discusses the implications of EcoOcean as a policy tool and how it can be further refined to be of wider use and to reduce the uncertainty of the modelled outputs. The application of EcoOcean to GEO4 and the IAASTD resulted in plausible outcomes under the different policy scenarios, and the outcomes differed across geographic areas as well as across scenarios. Some policy scenarios called for increasing landings or profits, rebuilding ecosystems, or a combination of all three with and without subsidies. In cases where effort increased, landings and therefore profits increased; however, any increase in landings was achieved by increases in groups that are not currently fished in large quantities. In many cases increased landings resulted in declining marine trophic levels, and increased depletion risks. a Cite as: Alder, J., Guénette, S. , Beblow, J., Cheung, W. and Christensen, V. 2007. Ecosystem-based global fishing policy scenarios. Fisheries Centre Research Reports 15(7). Fisheries Centre, University of British Columbia [ISSN 1198-6727]. Ecosystem-Based Global Fishing Policy Scenarios, Alder, Guénette, Beblow, Cheung and Christensen 4 INTRODUCTION Recent ecological studies including the recent IPCC2 have focused the world’s attention on the need to consider how future policy can be shaped to address environmental issues. Policy makers have a number of tools at their disposal to make well-reasoned policies that will effect change in the world’s ecosystems, while addressing other issues affecting humankind, especially poverty and economic development as articulated in the Millennium Development Goals (Anonymous, 2007). The global crisis in marine fisheries is included in the suite of issues to be addressed, because the world’s fisheries contributes to food security, as well as assistance in the economic development for many countries, especially so for developing coastal countries (Pauly et al., 2005). One tool that is gaining recognition for this purpose is scenario analysis. It was first used in strategic planning during the cold war (Khan and Weiner, 1967) and was key to the Shell Oil Company coping with the oil crisis of the 1970s (Wack, 1985a, 1985b). Its use assisting in policy formulation in natural resources management and sustainable development sectors, especially at the global scale, emerged in the 1970s (Raskin et al., 2005). There was little development of scenario analysis until late in the 1980s, when concerns over climate change and sustainable development took off. A number of climate change scenarios were thus developed in the 1990s with the IPCC (Raskin, 2000) providing a framework for the further development of scenarios analyses. Development of scenarios within the IPCC area has shaped much of how scenarios are used, reported and evaluated in other studies including the Millennium Ecosystem Assessment, GEO43, IAASTD4, OECD5 and GLOBIO Project6. The development of the global model EcoOcean, which we report on here, was a response to a growing demand for analyses of how, especially fisheries, may impact the future of marine systems for policy making at regional and global scales. In particular, there was a demand for a global oceans model for the United Nations’ Global Environment Outlook 4 (GEO4) and IAASTD as inputs into future scenarios under different policy options. Scenarios as used here can be defined as “plausible, challenging and relevant stories about how the future might unfold which can be told in both words and numbers. They are not forecasts, projections, predictions or recommendations. They are about envisioning future pathways and accounting for critical uncertainties”(Raskin et al., 2005). In this context the EcoOcean model was developed as a tool to explore fisheries and more broadly, marine policy options and not to predict the future. As Peterson et al.(2003) note, predictive modelling works for simulating well-understood systems over the short-term, but as complexity and the modelling time frame increase, predictive power declines. In such systems, the system state is well specified and mathematical algorithms are available to describe relationships used in the quantitative predictions (Raskin, 2005). Much progress has been made in describing such relationships through ecosystem modelling (Christensen and Walters, 2005) and a natural progression has been to bring these models into the field of scenario analysis. While ecosystem modelling has been used extensively for research purposes, it is only now beginning to be used as part of the fisheries policy process, and has yet to be used for large marine regions. As fishery policy moves beyond the objectives for single-species management there is indeed no choice but to adopt more elaborate ecosystem models. Policy choices for ecosystembased fisheries management involve exploring the impact of non-traditional policy choices and our abilities to perform such explorations are severely limited. In the past, we have based comparisons of ecosystem-related policy choices on methods ranging from very simple risk avoidance models, to simple food chain or trophic cascade models, to very complex food web 2 IPCC = Intergovernmental Panel on Climate Change 3 GEO4 = United Nations’ Global Environment Outlook 4 (UNEP 2007) 4 IAASTD = International Assessment for Agricultural Science Technology and Development (Fernandez in press) 5 OECD = Organization for Economic Co-operation and Development 6 GLOBIO = Global Methodology for Mapping Human Impacts on the Biosphere (see www.globio.info) Ecosystem-Based Global Fishing Policy Scenarios, Alder, Guénette, Beblow, Cheung and Christensen 5 models that attempt to explore possible reverberating effects going beyond direct predator-prey interactions. Much of the recent ecosystem modelling work has been aimed mainly at assessing risks of the more complex reverberating effects such as ‘cultivation-depensation’ effects (Walters and Kitchell, 2001), on the assumption that complex interactions are likely to result in counterintuitive responses (Yodzis, 2001) Based on the Ecopath with Ecosim (EwE) approach and software, we developed a new model, EcoOcean, to explore scenarios for the world’s oceans. Christensen and Walters (2004) give a detailed discussion of EwE. The model was constructed using 43 functional groups that are common to the world’s oceans including FAO’s 19 marine statistical areas. The groups were selected with special consideration for exploited fish species, but are intended to jointly include all major groups in the oceans. The fish groups are based on size categories, and feeding and habitat characteristics. Fishing effort is the most important driver for the ecosystem model simulations. The 19 FAO areas were considered large enough to encompass the range of most marine fish and invertebrates as well as accommodating the world’s major fishing fleets. Five major fleet categories, i.e., demersal, distant-water fleet, baitfish tuna (purse seine), tuna longline and small pelagic are used to distinguish different fishing effort based on historical information. This model structure allows for maximum flexibility in meeting different global assessment objectives, while still providing a valid representation of the marine systems. Background Scenario analyses can have quantitative modelling and qualitative narrative components; providing systematic and replicable representations as well as contrasting social visions and descriptions (Raskin et al., 2005). The process of developing scenarios itself often expands people’s perspectives and identifies key issues that might have been missed or dismissed at the initial stages of planning or assessment. Qualitative components help to describe values, behaviours and institutions, while quantitative components provide structure and rigour (Raskin et al., 2005). A review of previous scenarios over the last three decades illustrates the benefits and limits of using models and