I have been involved with researchers from the University of Melbourne in applying decision theory to a range of protected area management issues faced by Parks Victoria (the managers of Victoria’s terrestrial and marine Protected Areas). In particular we use structured decision making (SDM) to guide managers through a decision process. We believe SDM offers a platform to make more robust, transparent and defensible conservation decisions.
As a part of my PhD research I have applied the principles of SDM and scenario planning to help Parks Victoria explore where to set management thresholds for biological indicators within Victoria’s Marine National Parks. My research is ongoing, but you can read more about it and our other SDM research projects in Decision Point.
Conservation managers often have to make decisions in uncertain and complex situations. One way of dealing with this uncertainty is by modelling the different management alternatives on offer to see what type of results they might yield. The correct use of the appropriate model not only helps in making robust, transparent and defensible conservation decisions, it often generates insights on the nature of system being managed.
There’s no question that when used well, models can deliver good outcomes. But despite their demonstrated benefits, models are often mis-used or not used at all to support conservation decisions. Instead, decisions are frequently based on intuition, personal experience or unaided expert opinion; and this can lead to biased decisions that rest on hidden assumptions and individual agendas.
My colleagues and I recently investigated why models are still not used in many conservation decisions. We found a number of common objections to the use of models in environmental decision-making. In response to these common objections we suggested five practical solutions to help modellers improve the effectiveness and relevance of their work in conservation decision-making.
Our practical solutions include: using a structured decision making (SDM) framework to guide good modeling practice (see Fig 1 for suggested modelling techniques that can be used within a SDM framework); improving the social process of decision-making by including stakeholders, experts and decision-makers in the modelling for decision-making; and, building trust and improving communication between modellers and decision-makers.
Our practical solutions will challenge many modellers as they require skills outside of their core training and experience. However, if the aim is to achieve better conservation outcomes, then it’s definitely worth considering.
The prominent marine scientist, Professor Bob Pressey has recently said what few marine scientists have been brave enough to say about Australia’s new commonwealth marine protected areas (MPAs): they won’t work.
In November 2012, the Australian government established its latest round of commonwealth reserves, upping the area of Australia’s protected marine waters to an impressive 3.1 million sq km.
So why won’t Australia’s commonwealth MPAs work?
Professor Pressey states clearly that the new commonwealth protected areas are in the wrong places. In fact, he refers to these as “residual” places which have been chosen as a political move: the declaration of impressively large areas of marine environment which are considered unsuitable for commercial uses (such as fishing and renewable energy generation). As these areas offer little commercial importance, they are essentially easier to allocate to marine conservation as there is the least opposition from industry.
The primary goal for Australia’s MPAs is for marine biodiversity protection. The new commonwealth protected areas have been declared in remote, deep waters where there are few threats to marine biodiversity. Whilst nearshore waters close to our coastline continue to have a variety of human activities which threaten our marine biodiversity.
The simple message here is that there should be more focus on declaring MPAs in nearshore waters where marine biodiversity is actually threatened.