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Making science relevant to marine ecosystem-based management
Biological Conservation 144 (2011) 670–671
Contents lists available at ScienceDirect
Biological Conservation journal homepage: www.elsevier.com/locate/biocon
Letter to the Editor Making science relevant to marine ecosystem-based management
Recently, Lester et al. (2010) provided a comprehensive overview of the data, approaches, and dynamics related to ecosystembased management (EBM) on the west coast of the United States. They concluded that ‘‘science is not the bottleneck’’ for EBM in the region. We certainly agree with the authors that our understanding of ecosystems is sufficient to proceed with EBM in this and many jurisdictions. However, framing the adequacy of science as an empirical question to be answered without reference to management objectives gives the impression that a certain minimum of data is necessary for EBM. Although the authors recognize the iterative nature of EBM and the feasibility of starting with little data (e.g., Tallis et al., 2010), this emphasis on data availability risks distracting ecologists from more focused efforts that would better facilitate EBM. We argue that structured decision-making and decision-focused research are the real keys to overcoming several fundamental obstacles, including the disconnect between science and decision-making; insufficient treatment of socialecological systems (SESs); and the scientific tendency towards completeness rather than sufficiency for decision-making. Without a decision context for additional ecosystem science, research tends to produce a disjointed understanding of factors and processes that cannot easily be leveraged in management (Wainger and Boyd, 2009). Such a context can be provided by explicitly relating science to management objectives. Further, by focusing only on the data available and the challenges with understanding ecosystems, we inadvertently promote the decision-making status quo that proof of negative impact is required before exploitation is restrained. Finally, since EBM is intended to be iterative, it is by definition a process that can begin with minimal data. Although documenting the science available in one of the most data-rich jurisdictions in the world is a valuable exercise, concluding on that basis that science is not a bottleneck for EBM fails to make the critical point that EBM must be iterative to deal with new information and unforeseen system behavior. Selecting appropriate management actions depends on the objectives for each particular SES and does not require complete ecological understanding. Thus, instead of starting with the ecosystem and considering everything needed to realistically represent the ecological and social interactions (as might follow from Lester et al.), we propose starting with the decision context and a clear statement of objectives for the SES in question. This naturally leads to a reduced set of required indicators for the development of production functions and highlights necessary data collection efforts. In this fashion, the science required to support Integrated Ecosystem or Social System Assessments, or economic cost-benefit analyses can be greatly reduced. For example, what Lester et al. describe as a ‘‘useful start’’ to understanding the associated social system (spatially explicit maps describing 10 years of consecutive 0006-3207/$ - see front matter Ó 2010 Elsevier Ltd. All rights reserved. doi:10.1016/j.biocon.2010.11.012
trawl activity) may be sufficient or even extraneous in a decision context where trade-offs between fishing and land use practices are the focal point. In EBM, the utility of any data set depends more on how it informs decision-making than the broader question of ecosystem function. Science continues to produce increasingly complex models, working towards the belief articulated by Lester and colleagues that EBM will be facilitated by models that better forecast cumulative impacts and ‘‘improve our ability to predict the ecological and social outcomes of different management and zoning scenarios’’. While we certainly agree with the need for better ecosystem models, the most complex models currently available for marine EBM (e.g., Atlantis) are already so resource intensive that few decision-makers can truly contemplate their development. Furthermore, we are far from the kind of mechanistic understanding of ecosystems and cumulative impacts necessary to make the tactical decisions required to constrain human activities in meaningful ways. Better models will not overcome the challenges we face in defining service production functions and understanding how they respond to natural and human processes. Of course such understanding would be helpful if it can be achieved, but we all agree that EBM cannot and need not wait for such an understanding. We must therefore think strategically about the kind of science needed and be realistic about what science can bring to the table. Perhaps we would best advance EBM by abandoning the idea that we can measure and model our way through this complexity. Our understanding of SES dynamics will always be limited, and obtaining optimal solutions and defensible evidence of negative impacts in these complex systems may well be impossible—especially if the SES components have divergent risk tolerances or objective functions (Arrow’s impossibility theorem). This emphasizes the need for participatory, decision theoretic approaches with the recognition that there are real limits to our understanding, regardless of the data available. Achieving sustainability in SESs requires humility in place of hubris (Guerry, 2005). We must ensure that our heroic attempts at understanding do not inadvertently provide a false sense of security, or reasons to delay action. If, instead of focusing first on understanding the dynamics of SESs we considered how best to inform management objectives, our work as scientists would more directly support the decision-making process, create reasonable expectations for the scientific process, and reduce the time managers wait for necessary information. Surely these outcomes would constitute success and demonstrate the relevance of ecology to marine ecosystem management. References Guerry, A.D., 2005. Icarus and Daedalus: conceptual and tactical lessons for marine ecosystem-based management. Frontiers in Ecology and the Environment 3, 202–211.
Letter to the Editor / Biological Conservation 144 (2011) 670–671 Lester, S.E., McLeod, K.L., Tallis, H., Ruckelshaus, M., Halpern, B.S., Levin, P.S., Chavez, F.P., Pomeroy, C., McCay, B.J., Costello, C., Gaines, S.D., Mace, A.J., Barth, J.A., Fluharty, D.L., Parrish, J.K., 2010. Science in support of ecosystem-based management for the US West Coast and beyond. Biological Conservation 143, 576–587. Tallis, H., Levin, P.S., Ruckelshaus, M., Lester, S.E., McLeod, K.L., Fluharty, D.L., Halpern, B.S., 2010. The many faces of ecosystem-based management: making the process work today in real places. Marine Policy 34, 340–348. Wainger, L.A., Boyd, J.W., 2009. Valuing ecosystem services. In: McLeod, K., Leslie, H. (Eds.), Ecosystem-Based Management for the Oceans. Island Press, Washington, DC. pp. 92–111.
671
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Edward J. Gregr Kai M.A. Chan Institute for Resources, Environment, and Sustainability, University of British Columbia, Aquatic Ecosystem Research Laboratory, 429-2202 Main Mall, Vancouver, BC, Canada V6T 1Z4 ⇑ Tel.: +1 604 612 8324. E-mail address: [email protected] (E.J. Gregr) Available online 10 December 2010
Contents lists available at ScienceDirect
Biological Conservation journal homepage: www.elsevier.com/locate/biocon
Letter to the Editor Making science relevant to marine ecosystem-based management
Recently, Lester et al. (2010) provided a comprehensive overview of the data, approaches, and dynamics related to ecosystembased management (EBM) on the west coast of the United States. They concluded that ‘‘science is not the bottleneck’’ for EBM in the region. We certainly agree with the authors that our understanding of ecosystems is sufficient to proceed with EBM in this and many jurisdictions. However, framing the adequacy of science as an empirical question to be answered without reference to management objectives gives the impression that a certain minimum of data is necessary for EBM. Although the authors recognize the iterative nature of EBM and the feasibility of starting with little data (e.g., Tallis et al., 2010), this emphasis on data availability risks distracting ecologists from more focused efforts that would better facilitate EBM. We argue that structured decision-making and decision-focused research are the real keys to overcoming several fundamental obstacles, including the disconnect between science and decision-making; insufficient treatment of socialecological systems (SESs); and the scientific tendency towards completeness rather than sufficiency for decision-making. Without a decision context for additional ecosystem science, research tends to produce a disjointed understanding of factors and processes that cannot easily be leveraged in management (Wainger and Boyd, 2009). Such a context can be provided by explicitly relating science to management objectives. Further, by focusing only on the data available and the challenges with understanding ecosystems, we inadvertently promote the decision-making status quo that proof of negative impact is required before exploitation is restrained. Finally, since EBM is intended to be iterative, it is by definition a process that can begin with minimal data. Although documenting the science available in one of the most data-rich jurisdictions in the world is a valuable exercise, concluding on that basis that science is not a bottleneck for EBM fails to make the critical point that EBM must be iterative to deal with new information and unforeseen system behavior. Selecting appropriate management actions depends on the objectives for each particular SES and does not require complete ecological understanding. Thus, instead of starting with the ecosystem and considering everything needed to realistically represent the ecological and social interactions (as might follow from Lester et al.), we propose starting with the decision context and a clear statement of objectives for the SES in question. This naturally leads to a reduced set of required indicators for the development of production functions and highlights necessary data collection efforts. In this fashion, the science required to support Integrated Ecosystem or Social System Assessments, or economic cost-benefit analyses can be greatly reduced. For example, what Lester et al. describe as a ‘‘useful start’’ to understanding the associated social system (spatially explicit maps describing 10 years of consecutive 0006-3207/$ - see front matter Ó 2010 Elsevier Ltd. All rights reserved. doi:10.1016/j.biocon.2010.11.012
trawl activity) may be sufficient or even extraneous in a decision context where trade-offs between fishing and land use practices are the focal point. In EBM, the utility of any data set depends more on how it informs decision-making than the broader question of ecosystem function. Science continues to produce increasingly complex models, working towards the belief articulated by Lester and colleagues that EBM will be facilitated by models that better forecast cumulative impacts and ‘‘improve our ability to predict the ecological and social outcomes of different management and zoning scenarios’’. While we certainly agree with the need for better ecosystem models, the most complex models currently available for marine EBM (e.g., Atlantis) are already so resource intensive that few decision-makers can truly contemplate their development. Furthermore, we are far from the kind of mechanistic understanding of ecosystems and cumulative impacts necessary to make the tactical decisions required to constrain human activities in meaningful ways. Better models will not overcome the challenges we face in defining service production functions and understanding how they respond to natural and human processes. Of course such understanding would be helpful if it can be achieved, but we all agree that EBM cannot and need not wait for such an understanding. We must therefore think strategically about the kind of science needed and be realistic about what science can bring to the table. Perhaps we would best advance EBM by abandoning the idea that we can measure and model our way through this complexity. Our understanding of SES dynamics will always be limited, and obtaining optimal solutions and defensible evidence of negative impacts in these complex systems may well be impossible—especially if the SES components have divergent risk tolerances or objective functions (Arrow’s impossibility theorem). This emphasizes the need for participatory, decision theoretic approaches with the recognition that there are real limits to our understanding, regardless of the data available. Achieving sustainability in SESs requires humility in place of hubris (Guerry, 2005). We must ensure that our heroic attempts at understanding do not inadvertently provide a false sense of security, or reasons to delay action. If, instead of focusing first on understanding the dynamics of SESs we considered how best to inform management objectives, our work as scientists would more directly support the decision-making process, create reasonable expectations for the scientific process, and reduce the time managers wait for necessary information. Surely these outcomes would constitute success and demonstrate the relevance of ecology to marine ecosystem management. References Guerry, A.D., 2005. Icarus and Daedalus: conceptual and tactical lessons for marine ecosystem-based management. Frontiers in Ecology and the Environment 3, 202–211.
Letter to the Editor / Biological Conservation 144 (2011) 670–671 Lester, S.E., McLeod, K.L., Tallis, H., Ruckelshaus, M., Halpern, B.S., Levin, P.S., Chavez, F.P., Pomeroy, C., McCay, B.J., Costello, C., Gaines, S.D., Mace, A.J., Barth, J.A., Fluharty, D.L., Parrish, J.K., 2010. Science in support of ecosystem-based management for the US West Coast and beyond. Biological Conservation 143, 576–587. Tallis, H., Levin, P.S., Ruckelshaus, M., Lester, S.E., McLeod, K.L., Fluharty, D.L., Halpern, B.S., 2010. The many faces of ecosystem-based management: making the process work today in real places. Marine Policy 34, 340–348. Wainger, L.A., Boyd, J.W., 2009. Valuing ecosystem services. In: McLeod, K., Leslie, H. (Eds.), Ecosystem-Based Management for the Oceans. Island Press, Washington, DC. pp. 92–111.
671
⇑
Edward J. Gregr Kai M.A. Chan Institute for Resources, Environment, and Sustainability, University of British Columbia, Aquatic Ecosystem Research Laboratory, 429-2202 Main Mall, Vancouver, BC, Canada V6T 1Z4 ⇑ Tel.: +1 604 612 8324. E-mail address: [email protected] (E.J. Gregr) Available online 10 December 2010