Is disciplinary consensus a prerequisite for utility?

At a recent meeting relating to an AM program, I commented on the stark absence of social science expertise in the room. That particular program, which I'll not name to protect the not-so-innocent, isn't alone in this lack. Every single program I've been involved with in the last couple of years falls into the same category. One of the meeting participants, an engineer with experience in other AM programs, mentioned that a previous program had invited several sociologists to a meeting, but that the sociologists couldn't agree with each other about what the best way to proceed was. Much laughter - in which I participated, I confess.

Retrospectively however, I realized that I spend most of my time these days in meetings with ecologists who can't agree with each other. Or hydrologists. So obviously these disciplines aren't useful to AM either. Especially not on rivers. Engineers seem to be able to agree with each other at least, so I guess that's the answer - leave it to the engineers.

In fact, this perspective that disciplinary consensus is necessary for utility cuts straight to the heart of the issue - if there is consensus, then there is no uncertainty, and thus no need for AM. The fact that we think ecologists and hydrologists are necessary, but sociologists are not, suggests that we vastly underestimate the complexity of the socio- part of socio-ecological systems. We, rather arrogantly, assume that there should be consensus on how that works, and thus no need to incorporate that expertise into the process.

Whew. Glad I got that off my chest, its been bugging me for weeks!

USACE does AM!

After a long, long, enjoyable holiday break - I'm back.

And what a way to begin the year, with a USACE colonel quoted in public saying they do AM:

"This is adaptive management, making decisions based on science and the performance that's occurring on the ground to assure the resources of the river are being used to their highest priority," said Col. Alvin Lee, chairman of the task force and commander of the corps' New Orleans District.

Nice to see it getting some traction in the higher echelons of decision making. However, at least as outlined in the article, I don't think the closing of the West Bay Diversion project meets the criteria to be AM:

1. The decision isn't iterative (at least not at the scale of a single project).
2. The decision was not influenced by ongoing monitoring, but by a special study.

It is possible to think of AM for projects like the diversion at the scale of multiple projects, where the decision is made each year, or every few years, about whether the project should be maintained or not, based on scheduled monitoring data that is used to determine whether keeping a project open or closed is better meeting the fundamental objectives. In this case, it appears as though the diversion was closed as a result of a study commissioned after the Corps had determined there was a problem. This is fine, but it isn't adaptive management.

There is also a subtle point to be made about whether it is past performance, or expected future performance that is relevant - Col. Lee's quote attributes the decision to "... science and the performance occuring on the ground ...". However, it is in fact the expected future performance, specifically the additional costs of dredging, that sealed the deal:

The Breaux Act Task Force voted to close the controversial project after concluding that its project budget would be on the hook for millions of dollars every three years to dredge a nearby shipping anchorage. The diversion also is now seen as having been built in the wrong location - too close to the mouth of the river - to maximize the use of fresh water and sediment to build new land.

It is not widely appreciated that whenever we make a decision, we must imagine the future consequences of each choice. I suppose you could flip a coin to make a decision without imagining the future consequences of each choice, but I hope that we hold federal agencies to a higher standard! And when you imagine the future consequences, whether you like it or not, you are using a model.

AM at the 70th Midwest F&W meeting

I was just doing a bit of editing of past posts and discovered that I apparently forgot to post this one! Ooops ...

I just got back from the 70th Midwest Fish and Wildlife conference, which is a regional meeting shared among 10 states in the Midwest. I was one of the presenters at a symposium on Adaptive Management organized by the Nebraska Cooperative Fish and Wildlife Research Unit. One of the best things about the symposium was an opportunity to start doing some "introspection" on AM. What works? What doesn't? What are we doing here anyway?

The show was kicked off by Ken Williams, Director of the Cooperative Research Unit program at the USGS. Ken is a powerful and charismatic speaker who always goes at 100 miles an hour through mind blowing concepts. His message was simple, but direct - if anyone tells you there's only one way to do AM they're blowing smoke. OK, I paraphrase, but that's the gist. The essence of AM however defined is "Do, Learn, Do again".

The next speaker was Jamie McFadden, a graduate student from UNL, who is conducting a review of recent published work describing AM in an effort to identify characteristics of successful AM projects. Of course, her first challenge was to figure out how to define success! Her scheme focused on how close projects came to implementation, defined as actually making a management decision - Doing.

Armond Gharmestani of the EPA made some useful points about the relationship between law and AM - in particular pointing out the requirement of current administrative law to do all the planning "up front", which is extremely problematic for AM. In my opinion this is probably the single biggest institutional hurdle to overcome for folks wanting to do AM.

Clint Moore of the USGS presented two examples of collaborative efforts between the USGS and USFWS to implement AM - the AM consultancies and the AM for Refuges cooperative effort. The first is small scale - 2-3 days to lay out a plan that a single refuge manager can implement. The example was of managing burn treatments to maximize species richness on a refuge in Minnesota. The second type of project is intended for projects that span multiple regions and many refuges with a shared management problem, Reed Canary Grass in the example Clint gave. Clint's talk highlighted one of the key problems with implementing projects at that scale - a lack of people with both the time and technical expertise to maintain the AM project once the direct technical support is withdrawn.

Dave Galat from the Missouri Coop Unit gave a talk on the implementation of AM on the Upper Mississippi River. This is an interesting example for me because the UMR AM effort is a USACE habitat restoration project similar to what I am involved in on the Missouri River.

Adaptive Medication

I, like an increasing number of 40+ humans, am taking medication to lower my blood lipids in the hopes this reduces my risk of heart disease. For quite a while now I've been twisting my GP's arm (gently), trying different medications to see if there is one that will fit my personal genotype better. The motivation for this was the recognition that the usual "best" medication - according to randomized studies of large populations, wasn't doing the job for me. It occurred to me that genetic variation among people means that some people will respond better than others (duh.), and hence, the only way to work out what works for me, is, well, Adaptive Medication. Try something new. Test. Try something else. Test. Initially I tried to work out a model of cholesterol synthesis to generate some hypotheses but gave that up. If you think climate scientists are having trouble coming up with good models you should see physiologists. I knew there was a reason I never took biochemistry as an undergrad.

Thus I was intrigued by Pascale Hammond's discussion of how a clinical health care provider works and why this is science. Frankly I couldn't agree more - but the AMed spin raises an interesting point about what happens with all the data generated by those diagnostic tests of differential diagnoses. Unless I give my GP explicit permission, that information is not usable to improve medical understanding. Millions, nay, Billions or Trillions of dollars spent every year testing hypotheses and none of it used to advance the underlying science. I understand that there are privacy issues, but ... but ... this is my potential future longevity that is suffering! Maybe there would be a way for individual patients to "volunteer" to have their diagnoses and test results entered into a global double-blind database in much the same way that gene sequences are.

The black box of risk

I've been interested in the nature of risk and uncertainty for awhile now - this is one of those areas where ecologists are coming late to the game, so I'm playing alot of catchup. I just came across a really nice editorial on the perils of risk modelling in the financial world by Roger Pielke Jr. from earlier this year. Here's a nice quote that I like (for reasons that should be obvious):

The general lesson to take from such experiences is that it is rarely the models that are at fault; it is instead the use of those models in ways that are inappropriate and can lead to flawed decisions, sometimes with very large consequences. Too often the models are treated like black boxes and their use is overlooked as being the domain of technical experts. To make better use of risk models in business decisions, we need to open up the black box and better understand the role of models in decision making. Because of the potential for conflicts of interest, it is important to have independent eyes looking at the models and their use, a role that too often goes overlooked.

Although Roger is talking about hedging investment funds, I think the same could be said for models of risk to endangered species. Building the models is easy - even incorporating risk, error and uncertainty is not difficult. But understanding the outputs of those models demands a certain level of knowledge. And worst of all, we have not worked hard to understand or develop decision making in applied ecology, let alone understand the use of models in decision making. The politicization of climate change science should stand as a warning to us - as the stakes rise the challenges of honestly providing scientific advice and maintaining credibility become much greater.

What do we do about it?

1. Ecological managers at all levels must recognize that they are making decisions.
   
2. Making decisions implies some effort, however implicit, to forecast what will happen in the future after the decision is made.
   
3. We have excellent theoretical tools for forecasting the future of populations and ecosystems (not communities, unfortunately).
4. Ecological managers should be trained in using those tools while making decisions.

As an educator I can try to fix 4 for future managers. The rest of you are on your own!

Staying supple

I spent the morning in the company of a great crew that works on implementing AM for the Central Platte River in Nebraska - the Platte River Recovery Implementation Program. One of the things that is great about the program is the well worked out and detailed governance procedures - although the governing committee gives lots of folks a hard time, it also provides a clear "chain of command", and a place for stakeholders to have their voices heard.

One of the things that's not so good is the lack of flexibility created by those same detailed procedures. Two things in particular that changed after the agreements were signed 1) Phragmites australis spread throughout the central Platte, and 2) Ironoquia plattensis, a new caddisfly species was discovered. Surprise! The future is not like the past. This is exactly the situation that AM should be able to deal with - new information that changes how management actions will play out. Phragmites is problematic because it dramatically changes how the vegetation community will respond to short duration high flow events - it is very resistant to scouring and drowning. It seems as though the reality of Phragmites is settling in, but it took a tremendously long time, and caused much angst. So the key problem is how to design a program that is sufficiently well tied down that people will sign on, but remains flexible enough to deal with new circumstances far outside the scope of the original concept.

Maybe too much to ask, especially when the stakes are high.

Postmortem AM

One of the things that continually amazes me is the extent to which collecting simple data during management activities can be used to refine the management actions. It is one case in which the perfect is sometimes the enemy of the good - when an understandable desire to have the science "done well" prevents the collection of simple data that might be "good enough". In these days of GPS units in phones, it would be great to have the time and location of management actions, at a minimum.

That said, it is always nice when data collected during a management action is well analyzed. There's a nice example of that from the Outer Hebrides, where Thomas Bodey and colleagues used stable isotope analysis on whiskers collected from culled American Minks. The carcasses are in the hand - why not extract information from them, if it will help make the eradication campaign more efficient. The nice thing about an eradication campaign in an archipelago is the clear iterated nature of the decision making - distribution of effort in habitats on new islands provides a nice opportunity to apply lessons learned from previous campaigns.

And in other news, check out Methods.Blog, where Rob Freckleton is collecting samples of new methods in ecology and evolution from across a wide range of journals. He is also the editor of a new journal from Wiley-Blackwell devoted to methods in ecology and evolution. Looks interesting!