Thank you for the opportunity to appear today.
I'm a retired marine ecologist, and I have an adjunct professorial appointment at the University of Technology in Sydney, although I live in Perth on Australia's west coast.
For the past 20 years, after a previous 20-year career as a marine ecologist in Australia's CSIRO, the national research organization, I have conducted research and given practical science support to governments, businesses, communities, NGOs, UN agencies, and aid agencies in almost all aspects of design and implementation of marine protected areas.
Much of this work has been focused in Australia and the Asia-Pacific countries. My experience ranges from, as we say, “'talking the talk” to “walking the walk” among the science and technical issues, across the full gamut of MPA problems. This of course includes Australia's two major coral reef MPA systems, as well as across to small, community-managed MPAs in the Asia-Pacific.
I'm happy to send in later, Mr. Chair, a personal biography and any other supporting materials you might like.
However, today, by way of opening the discussion, I'd like to introduce you to a couple of concepts I see as being integrating, and then draw your attention to three of the complex issues I have found to be remarkably common across my work in MPA management, irrespective of the size, location, cultural setting, or degree of development that might apply. I'm sure these and many others—and I've already heard some this morning—will be central to the matter of MPAs for Canada. For the remainder of the time, of course, I wish to participate in the Q and A session.
I should also say at the outset that I only have a passing familiarity with the MPA situation in Canada. I was involved briefly in 2015 with round-table workshops on MPA issues in B.C., which were organized by local stakeholders there. If there are questions about Canada-specific issues, I will probably have to abstain, Mr. Chairman.
In terms of concepts, the modern era of MPA design and implementation is based on what is really a simple but in some ways very technical concept, that of spatial optimization. This concept holds that conservation outcomes for species, ecosystems, and the other elements of natural oceans can be achieved by allocating various parts of the oceans to specific forms of management control. Some of these may overlap with each other. We've already heard examples this morning, but they range across the full gamut of human interactions with the ocean.
The process of optimization considers competing requirements for the same parts of the ocean and seeks to resolve the most efficient and effective outcome across those competing demands. This model of MPA design is the same used in many other areas of human endeavour, and is really based on decision science procedures that are simply adapted from use in other sectors. The success of this approach in the oceans relies on the availability of a transparent and inclusive process, the open engagement of all stakeholders and their interests, a clear decision framework, and a willingness for stakeholders to be bound into the collective decision outcomes.
I believe spatial optimization offers a very practical mechanism for stakeholders from all walks of life to engage in a technical process that is defendable and equitable, irrespective of their capacity to engage, and to have confidence that their own expectations are represented in a balanced approach to problem resolution.
I'll take a moment to turn to what I think are three common problems, from my experience with working to implement and design MPAs. The first of these is one that I call confused terminology.
There is a considerable amount of uncertainty invoked in MPA design and management through the use of technical terms that have poor or variable definitions and interpretations across geographic regions, languages, cultures, sectors, and even local contexts. This is not just a matter of a problem of semantics. Some terms actually do have multiple meanings across the different disciplines. Two obvious ones are the term “sustainability” and the term “objectives”.
This question is often confounded by a tendency to flexibly define and apply the terms for tactical purposes, often to service a narrow and specific mission-oriented stakeholder agenda, or to be expressed from a specific sectoral point of view. As a result, I advocate for the adoption and application of a clear framework of terms derived from decision science and analysis. For example, an outcome objective should always be expressed in terms that match the expected achievements of the MPA, such as you might recognize as conservation of species and ecosystems.
The second hurdle is the use of inappropriate underpinning conceptual models. Many of the concepts in the MPA debate are based on models and assumptions, some of which are well tried and tested. However, despite their widespread acceptance for some specific purposes, they may not have been developed and tested for the purposes of MPA design. The most obvious example of this problem is the concept of maximum sustainable yield. Whilst this and other related biomass yield concepts provide the fundamental parameters for fisheries management worldwide, biomass yield of any type is a management parameter that is not highly consistent with the conservation or protection objectives of an MPA or a network, no matter which IUCN management status might be applied. Maximum yield models are not the appropriate underpinning models to achieve the conservation outcomes for fish populations that are usually envisaged by MPA objectives.
As a result, fishing models are rarely appropriate as the main basis for determining scope, scale, and management controls for achieving the conservation outcomes of MPAs. MPAs must apply much higher standards than MSY for fish populations, and use criteria and metrics other than fish biomass yield to provide for the conservation of fish populations and their ecosystem's structure, function, and resilience.
The third hurdle is one that I define as using a decision analysis framework that's effective. After many long years in the theory and practice of MPAs, I have concluded that the science of decision analysis seems to offer the best prospect for achieving good outcomes for all stakeholders, including the ecosystems and the populations that are the target of MPA movements and interests.
In its most elementary construct, a decision analysis framework holds that there is a clear relationship between the setting of outcome-based objectives and defining how such objectives can or should be achieved through management intervention. Both the form of the relationship and the form of any consequent interventions can be derived from within the framework, including the establishment of performance assessment and reporting systems that have direct application for reporting on expected outcomes.
If stakeholders can be motived to contribute freely and fully into a well-designed decision system, I consider that the many issues surrounding MPAs can be resolved into a few remaining highly intractable problems. Such problems can then become the focus of more detailed study and investigations to address the key uncertainties. Even then, there may be issues that remain but they will belong in the realm of politics, not science. Even then, though, science can well inform that debate. In short, trade-offs become explicit, and all parties, if they participate freely, become better informed about the detail and costs of such trade-offs.
The worst-case outcome is that trade-offs of competing objectives are made such that they do not allow substantive benefits for any of the stakeholder interests, and then the MPA system as a whole may become open to contest. The use of popular software optimization packages such as Marxan makes these spatial trade-offs tractable and subject to a number of basic requirements, such as spatial expression of objectives and attributes. I consider such decision support systems as the key element of any pragmatic and modern approach to resolving issues of design and implementing MPAs.
The more complex the EPA problem, the more valuable the decision framework and optimalization approach will prove to be.
Thank you for the opportunity to say these few words and hopefully highlight a few of the commonalities and issues. I'd be happy to take any questions that you might have about anything I've said.