- David Mattson
Fog of Science: The Stealth Advocacy of Grizzly Bear Numbers
Science is a value-laden and often political process. The proximal means for this dis-objectification can be found in the questions asked, the research funded, the results reported, the interpretations featured, the results selectively applied, and the frames foisted upon naïve end-users. Essentially every worthwhile commentator on the scientific enterprise has said as much. The potential quotes abound.
To feature just two, Bill Ascher, Donald McKenna Professor of Government at Claremont-McKenna College noted: “Knowledge generation is a political process…affected by the value systems of institutions, professions, and individuals.” Dan Sarewitz, Professor of Society and Science at Arizona State University, wrote: “Problems of values, assumptions, and ideology…are pervasive across the scientific enterprise.” And so on. Or, as Roger Pielke observed, there is probably no such thing as an objective scientist, other than perhaps for fleeting moments in the early career of budding researchers. But delusions of objectivity among scientists abound nonetheless, with sometimes destructive consequences.
Roger Pielke, a Professor at the University of Colorado, has done what so many scholars do: promulgate a schematic that, in this case, I find to be quite helpful. Roger categorizes what he calls “modes of engagement by scientists and other experts” with policy and politics. He has five types. As I noted just above, he more-or-less dismisses out of hand the ideal of a Pure Scientist. Then there is the Issue Advocate who, with transparency and integrity, features certain interpretations of science to promote a specific policy outcome. I count myself in that group. Or the Science Arbiter, who somewhat ponderously “supports decision-makers by providing answers to questions that can be addressed empirically.” Roger goes on to note that such Arbiters are “…never far from political influences.” And, then, better yet, there is the Honest Broker, who clarifies and expands the scope of options available for deliberation and action.
But there is a fifth category that Roger subjects to special disopprobrium. These are Stealth Issue Advocates. These low-life scientists seek to “…hide behind a façade of science, either pure scientist or science arbiter.” Which, Roger claims, “…is the swiftest route to pathologically politicizing science.” The problem is that most of these researchers end up here, not because of willful malfeasance, but because of self-delusional narratives that they imbibed during their post-graduate indoctrinations (Amen). These are the tricky ones because, at least in my experience, they can’t even begin to engage in a self-reflective conversation.
Which brings me to the self-delusional Stealth Issue Advocates who litter the landscape of Yellowstone’s grizzly bear science. As preface for what follows, I need to note that I struggle with how to broach this topic. There are many dimensions and complexities. There are so many manifestations. And I struggle with how to engage a broader readership not familiar with the nuances of science or scientific practice. But I surmise that most people have a fundamental grasp of human psychology and the foibles of humanity writ large. With that as a premise…
Stealth Advocate Grizzly Bear Scientists
Examples of stealth advocacy by researchers and managers are particularly abundant in the case of Yellowstone’s grizzly bears. Perhaps the most straight-forward examples can be found in how estimates of population size and trend are generated and then represented by technocrats to the attentive public. Estimates of size and trend are central to management controversies primarily because these metrics have been made the determinants of whether Yellowstone’s grizzly bear population is stripped of Endangered Species Act (ESA) protections or not—with status and trends of habitat and foods relegated to the trash bin of deliberations. Parenthetically, the political imperative to remove protections has spawned an environment that rewards agency functionaries who inflate or even fabricate positive population trends.
Stealth Advocacy in Action: Part I
An example? Consider a recent spate of public comments by researchers who work for the Interagency Grizzly Bear Study Team (IGBST), a monopolistic cabal responsible for essentially all the research being fed into management deliberations on behalf of federal and state governments. These comments pertained to trend of the Yellowstone grizzly bear population during the last three years, made relevant by the fact that bear mortality had skyrocketed to unprecedented levels while population size was apparently declining. Yet, when asked by journalists or activists whether the population had, in fact, declined, IGBST researchers intoned that “We cannot conclude the population declined between 2014 and 2016 because confidence intervals for annual estimates overlapped.”
Just the Facts
Before I unpack this rather arcane statement, it’s worth looking at the ostensible facts of the matter. Official estimates of size for Yellowstone’s grizzly bear population for the sequential years 2014, 2015, and 2016 were 757, 717, and 690, respectively. Each estimate has what is called a 95% Confidence Interval. Roughly speaking, this confidence interval encompasses 95% of the estimates we might produce using current methods, and is a means of accounting for the inevitable error that arises from sampling and then estimating a population size, rather than undertaking a comprehensive and exact census. The figure immediately below (Figure 1) shows the relevant series of annual population estimates along with confidence intervals for each. The dashed horizontal line shows the 757 estimate for 2014 as a point of reference.
Figure 1. Estimated numbers of grizzly bears in the Yellowstone ecosystem (red dots) along with 95% Confidence Intervals denoted by the bracketed vertical lines bounding each dot. The dashed line equals the population size estimated for 2014 and is shown as a point of reference.
Stealth Advocacy in Action: Part II
Not surprisingly, the average Joe or Jane is probably confused when he or she looks at these data and then hears the Experts say “We cannot conclude the population declined between 2014 and 2016…” Such was certainly the case with a journalist who called me asking my opinion. He confessed that the numbers sure looked like a decline but, then, who was he to contest profundities emanating from the scientific Sanctum Sanctórum of the IGBST. In nómine Patris, et Filii, et Spíritus Sancti. Amen. My point being that much of the impenetrable scientific mumbo jumbo offered us by scientific experts is not all that different in practice from the Latinic assertions of a Catholic mass: Sicut erat in principo, et nunc, et semper: et in sǽcula sæculórum.
Turning more specifically to the “We cannot conclude…” statement. Why “cannot conclude”? If you can’t conclude that the population is declining, then what can you conclude? Is the IGBST saying they have no clue about what’s going on with population trend? If so, why don’t they emphasize “We can’t conclude the population is increasing” or “We can’t conclude the population is stable”? Or does the IGBST assume that the population is stable to increasing in the absence of overwhelming evidence showing decline? If so, why is the burden to overwhelmingly prove that the population is in decline, rather than proving by the same high standard that the population is stable or increasing? Why has the IGBST not taken a precautionary approach relative to risk of decline? Why did the IGBST chose 95% Confidence Intervals versus 90% or 75% or 50% or…? Given their approach, the choice has major impacts on what you “can” or “cannot” conclude.
My point here is that there is a veritable host of opaque choices embedded in what IGBST scientists have been saying about recent population trends. And all these choices relate to values, preferences, norms…and politics. Not objective science. More egregiously from a conservation standpoint, the IGBST has chosen to take an approach that is anything but precautionary when representing scientific results. Their choice essentially maximizes risk that bear managers will treat the population as if it is stable or increasing when, in fact, it is declining. What a perverse way to manage any population at risk, especially when born of a choice that has absolutely nothing to do with science, as such. More bluntly, the IGBST has been playing politics under the duplicitous guise of scientific objectivity. This kind of stealth advocacy by tax-payer-paid government scientists is quite simply a betrayal of the public’s trust.
And the Trend Is?
So, what has been the recent trend of Yellowstone’s grizzly population? As suggested by my preceding critique, your conclusion depends upon several value-informed choices. The most value-neutral approach to allocating burden of proof is to use weight-of-evidence. You don’t demand overwhelming evidence in support of one conclusion or another. Instead, you tentatively adopt whichever conclusion is better supported by the available evidence, whether by a 51:49, 52:48, 75:25, or 95:05 margin, with the proviso that the greater the weight, the more confident you can be in the adopted conclusion. So, by this frame, does the evidence more strongly support concluding that the population has increased?...or decreased?...or remained stable? De facto, managers end up managing as if the population has done one of these three things, even if scientists were to throw up their hands and say they have no clue.
Having adopted an approach to allocating burden of proof, the next set of value-informed deliberations pertains to the analytic approach adopted and the weight required for settling on a preliminary conclusion. If we were deliberating over two possibilities, increase or decline, the standard would simply be whichever hypothesis was supported by the greater weight of evidence. With three states—increase, decline, or stasis—the standard becomes a bit more subjective and dependent upon the analysis method.
In this instance, I found a simulation model to be the most appropriate analytic approach. Each simulation entailed randomly drawing a population size from a normal distribution within the confidence interval for each annual estimate, repeated for each year 2014 through 2016, and then calculating a growth rate for the 3-year period. Each simulation thus produced a growth rate, which varied with the series of random draws. Once I had compiled enough simulations, I could reliably calculate the proportion that yielded a population increase versus decline, along with the magnitude of each.
What did I find? The result was not subtle. Almost all simulations—93%—showed population decline. Obversely, 7% showed increase. Mean annual growth rate was a negative 5%. The overwhelming weight-of-evidence supports concluding that the population declined between 2014 and 2016. What a contrast with the IGBST’s “We cannot conclude…”.
Stealth Advocacy is Betrayal of Trust
But this is not the entire story. When it comes to allocating burden of proof, different people with a stake in grizzly bear management have different legitimate preferences born of different worldviews. If you are a grizzly bear advocate who does not want to incur the risk of managing Yellowstone’s grizzly bear population as if it were increasing when it is, in fact, in decline, then you may demand that the evidence in support of a population increase be on the order of 75-95%—rather than simply >50%—before adopting this as a premise for management. Conversely, if you loath grizzlies and want to flog them back to within the bounds of Yellowstone National Park, then you may require a 95% likelihood of population decrease before managing as if this were true. Otherwise you might advocate that managers assume the population is stable or increasing. Interesting enough, this is the stance taken by the IGBST given that these researchers assume, by default, that the population is static or on a positive trajectory absent overwhelming evidence that it is in decline.
But this is about values and worldviews, not science. From the perspective of someone who esteems a pluralistic democratic society, such transparent divergences in values are a predictable outcome of legitimately diverse human perspectives and backgrounds.
My fundamental point here pertains to a lack of transparency about values and prejudice on the part of government scientists and managers, promulgated under the guise of purported objectivity and expert prerogative. Which is Stealth Issue Advocacy. Reiterating Roger Pielke, such behavior “…is the swiftest route to pathologically politicizing science.” Government officials bitterly complain about this politicization, with a finger pointed as those who contest their power. But culpability rests squarely with them, whatever their motives. From my perspective, it doesn’t particularly matter whether betrayal of the public trust arises from deliberate duplicity, lack of sel