John has done a fantastic job of summarizing the panelists’ presentations at the Science Forum. However, I think we need to carefully watch what is claimed as scientific information, especially when that information tends to be uniquely privileged and thus can remove debate from the democratic, public sphere if it becomes a “science” issue. “Science” at its extreme, can become an ever-broadening mantle that can run to personal experiences of scientists, pontification by scientists, and so on.
But what is scientific information, given the variety of fields involved in a complicated field like natural resource management? “Science” can be models, field measurements, interviews with people, GIS exercises, and so on.
Scientific information gets its privileged status from claims of objectivity and physical and biological reality.
So here are some of my impressions, as a scientist and an observer of the science enterprise. First of all, I think modelers cannot be objective about models. No more than botanists can be objective about plants, or wildlife biologists about wildlife. There is an inherent connection between love of a thing and choosing it as a vocation. A good scientist, like a good manager, has a fire in her/his belly for the work. One ecologist notably said “ecosystems are more complex than we think, they are more complex than we can think.” I actually think that that is a paraphrase of J.B.S. Haldane, who said “the universe is queerer than we think, it is queerer than we can think.” How can we believe that they are more complex than we can think, and yet expect managers and the public to put energy into consideration of model outputs without independent empirical evidence that predictions are somewhat accurate?
Role of modeling in forest planning
Nevertheless, the scientists involved in modeling focused on models. Dr. Williams, who runs monitoring programs but is probably not one of the modeling community, focused on monitoring and real world observations, due to uncertainty and the complexity and potential unmodelability of complex systems. I agree with his emphasis on observations. Is that related to the fact we don’t work in models? Does the fire in the belly come as a precursor, or an effect, of working on something like models?
It is the essential conundrum of science – those who know the most have the most inherent conflict of interest in the importance and utility of their work. As the expression goes, if all you have is a hammer…everything looks like a nail.
I think we need to have more serious discussions about the appropriate role of models when there is as much uncertainty as there is about the future. From the science perspective, no doubt, models can synthesize existing information and they are useful to inform scientific understanding. But to then say that they need to be used in planning is a leap. Are they good enough to be better than talking to the public about “we don’t really know, this could happen or that, let’s think through some scenarios?” Are quantitative computer models necessarily better than explaining to the public what scientists currently think about interactions?
If interactions are too complex to predict, then they are too complex to predict- and let’s admit it and use adaptive management. Or use simple, explainable heuristic models. If we are going to use them, then we should wait for 10 years and select the ones with the most predictive value. Weather models were discussed at the Science Forum as a potential approach for the use of models. The problem seems to be that no one in natural resources wants to wait to get the data points. I think we can honor the role of models in increasing scientific understanding without determining that they are predictive enough to be useful in planning.
Sticking to Science
When we invite scientists to speak, we have to be careful about their knowledge claims. Telling stories about their experiences with collaboration isn’t scientific knowledge, it is practitioner experience. In another example, the Precautionary Principle is a human value about how to make decisions under uncertainty. Decision science is, need I say, a separate discipline from biology and ecology. When scientists or scientific organizations advocate for a position like that, in my view, they should separate their science claims from their personal values. Roger Pielke in his book “The Honest Broker” calls these “stealth advocates.” It takes just a minute to add “this isn’t a scientific point of view, it is a value judgment” when you make such a statement , but the power of trust in science and scientists is, indeed, priceless. Ask the climate scientists.
The questions before us are centrally about how we will survive, who will survive, and how we will live. These are questions that climatologists and other scientists can inform but not decide. For their important work, scientists deserve our gratitude, not special political authority. What’s needed today is a politics that seeks authority not from Nature or Science but from a compelling vision of the future that is appropriate for the world we live in and the crises we face.