Horn tooting

One of the things I've been interested in for quite a while is making decisions with poor or no information - what social scientists since Keynes and Knight call uncertainty, meaning that there are no probability distributions available for the outcomes. If we're being honest with ourselves, this characterizes alot of circumstances when dealing with endangered species management. In such circumstances, one possible response is to "satisfice" rather than optimize the management actions.

Earlier this year Max Post van der Burg and I published an article in Ecological Applications Integrating Info-gap Decision Theory With Robust Population Management: A Case Study Using The Mountain Plover" where we used a combination of methods borrowed from robust control theory and satisficing to understand the value of a particular management action to a threatened species. This was a piece of Max's dissertation, and as usual in such things, he did all the hard and important work!

The core idea of "satisficing" is to find a decision that performs good enough, but over the largest possible number of ways of being wrong. In contrast, optimisation focuses on maximizing performance assuming that the system is perfectly understood - i.e. all the parameters are known perfectly and the system model is exactly correct - circumstances that are never true even in the best of times. So an optimal decision will usually outperform a satisficing decision if one's knowledge of the system is perfect, the satisficing decision will continue to do well even if the system model and its parameters are incorrect.

Of course, it is possible that a satisficing strategy is also the optimal strategy, and then we're happiest, but this doesn't seem to happen very often.

Max's contribution was to couple a matrix population model of Mountain Plover with the idea of satisficing to look at how well "nest marking" of Plovers performs as a conservation strategy. The upshot is that even if we are not sure about the life history of this species, nest marking increases the range of "wrongness" under which we will see positive population growth. What we didn't do was evaluate different types of actions against each other - this could easily be done, but was beyond the scope of what we wanted to achieve in the paper.

Population Viability Management

One of the most difficult things to agree on is what the goal of management ought to be - and the more controversial the species the harder this is! Maybe its not controversy, but rather what we ("we" meaning society as a whole) have to give up as a tradeoff to meet perceived goals. For harvested species there are an increasing number of examples in both marine and aquatic systems of coupling population models with management to help resolve uncertainties - the North American waterfowl harvest management plan is the best terrestrial example. In those cases, there is a clear and desirable goal - to be able to continue harvest into the future. Similarly, it is pretty straightforward to work out the ideal goal for an invasive species - zero. Species in need of conservation are trickier - more of them isn't obviously better for society (as food or recreation) even if having none of them is clearly bad. This sets the stage for scientific uncertainty about a species to take on political dimensions - even if everyone agrees we don't want a species to go extinct, ones willingness to accept new management prescriptions is negatively related to how much you personally will have to change behavior as a result. In the most recent issue of Frontiers in Ecology and the Environment, Victoria Bakker and Dan Doak argue that using population models to predict relative extinction risk can help make these tradeoffs - they call it "Population Viability Management" - but their diagrams and arguments are pure Department of Interior Adaptive Management. They give an extended and detailed example using Channel Island Foxes of how PVA models can improve monitoring, guide management actions, and generally make the world a better place. It is a really great review of the recent literature on how population models can be integrated with management decision making.

The only thing I was a bit disappointed by was the way Bakker and Doak skirt past the issue of tradeoffs - although they mention that cost-viability tradeoffs occur, in their example they have chosen not to evaluate them. Any actions that exceed the current available budget are not evaluated. In that sense, the tradeoff IS made, and at a rather extreme level. I agree with their assertion that conducting a full analysis of the ecological risks makes the economic assessment more meaningful - and thus all the more surprising that such ecological assessments are not conducted more often.

They conclude with a reference that I'll have to pursue - about how iterative cycles of explanation and improvement ultimately led to uptake of the recommendations of the model by managers - what they call the "handshake approach".

Bakker, Victoria J. and Daniel F. Doak. 2009. Population viability management: ecological standards to guide adaptive management for rare species. Frontiers in Ecology and the Environment 7:158-165. doi:10.1890/070220