Part 1 of 3 in the Series “Get to know your fry-entists”
It is impossible for a biologist, ecologist, environmental scientist not to think about conservation. The problems our planet is facing are so concrete, so quantifiable, so visible that to ignore them would be to betray the very thing we’ve dedicated our lives to studying. I always chuckle when scientists are portrayed as cold, calculating, and heartless, when the truth is that they’re more committed to understanding their system than any one else. Science is a labor of passion and scientists dig deeply into the inner workings of their world.
So when someone says we don’t care about something, just because we have a more analytical view of how it works, or doesn’t work, I get angry.
There is a flip side to that though, with passion must come temperance. As scientists we are positioned to understand how the world works, but that is not all of science. Unless your discoveries are communicated to society, they mean nothing. In an ideal world, nobody owns knowledge, information is the property of the whole of human society. But this is not an ideal world, and it is up to everyone who does science (and that really is almost everybody) to make sure they disseminate their knowledge to the rest of the world.
So what happens when your knowledge is loaded with the political baggage that is fundamentally and irreversibly associated with conservation biology? Do you trust the data of a climatologist more if they’re active advocates of global warming or temperate, objective observers saying “this is how the system is changing”? On the flip side, do you trust a climatologist who says global warming isn’t happening? Can biased observers give unbiased data?
The answer is yes, but with caveats. An ecologist who’s ravenously opposed to drilling in ANWAR is going to be biased in the same way that someone well paid by a pharmaceutical company is biased. They may be totally objective, doing good, robust science, or they may not, but I would approach either data set with the same level of skepticism and caution. And a policymaker, not well versed in scientific literature, would probably be more skeptical (or less if they agree with the researcher) than I.
So there’s a delicate line that must be tread. On one hand we are deeply passionate about our research, on the other hand, in order to get the best conservation results, we have to present the best objective unbiased data. Conservation asks the questions, but rigorous, critical, unbiased science has the best chance of yielding meaningful results. That means that the best conservation biologists will try their hardest to prove themselves wrong. If you’re looking at a system on the verge of collapse, you’re methods must show that you went out of your way to test the hypothesis that the system is stable, and your data needs to show unequivocally that you could not confirm that hypothesis.
I’m deeply embedded in conservation biology, yet you’ve never heard me advocate within my field precisely for these reasons. My role is to asks questions about the system, figure out how changes, both natural and man-made will affect it, and report the data. The data speaks while the scientist remains silent. That is the only way managers can trust the desicions they make.
So how can a scientist be an advocate? How can we further conservation goals if we remove ourselves from them? We are advocates of Science. Our duty is to make sure people have access to information, can analyze and interpret it for themselves, and are equipped to make those management decisions. We have to ensure that policy makers can see through the deception of global-warming denialists, anti-vaccinationist, creationist, and make those calls. Our highest commitment is to education, everything else flows from that.
Without science advocates fighting for education, bringing science into the public eye, and taking bad science to task, we can’t make good management and conservation decisions. There would be no movement to slow global warming without convincing data. Without rigorous analysis there would be no evidence for ocean acidification. Without the predictive power of unbiased, objective science we can’t anticipate problems and search for solution until it is too late.
~Southern Fried Scientist
Here’s a question: what do we do when people have access to the information, the mental capabilities to comprehend and analyze it, but still choose to believe what they want?
I know someone (close to me), for example. She’s a very smart woman. If she wants to understand something, she’ll actually dig up the scientific papers and read them. She’s particularly interested in is diet and nutrition, and she has read an unbelievable amount on the topic. But when it comes to analyzing the information she reads, she writes off studies that disagree with her beliefs as being biased (“government-funded nonsense”), and instead only believes those that agree with her. It’s not that she has a lack of information, or a lack of the ability to understand the information given – just that she finds reason to fault that which doesn’t agree with her view, and defends her decision to do so fiercely.
How to we ensure that policy makers aren’t the same way? What do we do when simply providing the data isn’t convincing enough? Have we failed somehow, if publishing the papers and getting the information out there doesn’t work?
A good example might be the state of Bluefin Tuna in the Mediterranean. Far as I know, a vast majority of the scientific research suggests that the fishery is on the verge of collapse and that fishing the same quota as we have for the past few years will surely collapse it. Yet even when the policy makers’ scientists tell them this, they set the catch quotas well above what science has deemed sustainable, and fishermen bring in more than the quota allows. It seems to me that the policy makers involved are perfectly informed to the situation, they are just too greedy or too stubborn to listen to the science that disagrees with what they want to do. What do we do as scientists then, when the data isn’t enough to force changes in policy?
Nice post! And I agree it’s a delicate line. I think I shared these identical views as a scientist prior to working directly in conservation. The problem that I see–and perhaps this is what Randy Olson is talking about… and maybe even Mooney (though who the fuck knows what he’s trying to say)–is that as scientists we are trained to do exactly what you describe above: “…to ask questions about the system, figure out how changes, both natural and man-made will affect it, and report the data. The data speaks while the scientist remains silent.”
Problem is, when we just let the data do the talking we are failing at making our data meaningful in a variety of important arenas outside our labs.
Case in point, there’s some ridiculous climate denialist BS that started floating around last week claiming that coral reef scientists are trying to delude policy-makes. Check it out here: http://tinyurl.com/yd8vgan
What is interesting is that each of the statements that they have repeated has a solid basis in the peer-reviewed literature. There is no other real perspective out there with credibility. But as scientists, we have difficulty stating things unequivocally.
But as sientists/conservationists, stating this solidly and unambiguously is what we need to do when it comes to the policymakers because they don’t understand how to deal with scientifically cautious statements/probabilities etc. It seems those who give most scientists headaches (the climate denialists, intelligent design wonks, anti-vacc, etc) prefer scientists who continually waffle in terms of their statements (sounding like “ we will never really know”) and hence have minimal impact on the urgently needed policy development.
You raise some really valid points that get to the nature of science, and unfortunately the lack of scientific thinking outside our camps.
Or policy makers in the Mediterranean serve their constituents, and their constituents aren’t scientists, they’re fishermen. The policy makers may be well informed, but they serve their constituents, who either not informed or have an immediate need for the fishery which overshadows a future need.
Some people are never going to see past their own biases, no matter how well informed they are. The only solution to that is to produce the largest, best educated population possible. You have to teach people to be the most critical of their own views first and not accept only the facts that already agree with their pre-existing biases.
I’ve often said (and just as often been guilty of) – “It’s amazing how many conservationists’ solutions already agree with their values.”
Publishing papers and getting the information out is the Science, actively working to educate is the Activism.
Half of what you’re going to learn in this class is wrong. I’m just not sure which half.
That is the way a grad school professor I had would start each semester. It was a sobering reminder of the changing nature of scientific ‘knowledge’. This professor had the benefit of being 30+ years into his research career, which was long enough to see some of the things scientists thought we ‘knew’ refined and replaced with a new version of ‘what we know’.
The general public has a tough time understanding a point like that, and it can erroneously lead them to statements like ‘you can make statistics say anything you want them to say’. At the same time, scientists as a group risk their credibility in the public arena of ideas if we don’t do a better job of understanding the nature of scientific knowledge.
Along with a strong sense of what public policy should look like given everything we think we understand at the time, scientists need to keep a sort of humble acknowledgment that some large portion of what we know is probably not quite right.
We need to explain that scientists make the best recommendations we can based on what we know. We’ll be wrong some of the time, but no one who lives in modern society can deny that science still has a lot of offer and the other option (making policy without regard for what we think we know) is even worse.
Great post! Look forward to the rest of the series. There is a good book that touches on much of this: The Honest Broker by Roger Pielke. A book I highly recommend for anyone dancing on the precipice between science, policy and advocacy. It describes scientist’s role in policy and politics as being four broad categories: Science arbiter, pure scientist, issue advocate and honest broker. Pielke asserts that issue advocacy has come to dominate the other roles, but the roles need to remain balanced to best serve society.
I’m glad you brought that up. As this series unfurls I think it will become clear that we have all but the honest broker represented among the fry-entists.
I’m totally with you on everything except that last point. Scientists don’t make recommendations, policy makers and advocates make recommendations. The policy maker or advocate may be a scientist, and many scientists are in a good position to make well informed recommendations, but once you cross the line from presenting data to recommending what to do with that data, you’ve entered the realm of advocacy. I do think, while any scientist working in a conservation field is going to make recommendations, we make a distinction between the data and the advocacy.
Scientists themselves tend to acknowledge that they’re always working within a mutable framework (though there are plenty of exceptions), but ensuring that society in general has a solid understanding that science is subject to change is part of being an advocate for science.
As much as we wish it were so, scientists don’t work in a world that’s separate from policy makers. Data by themselves are not as objective as we would like the think.
At the most basic level, the areas of research that are funded and the particular studies and/or scientists who get grants is biased by what someone at a funding agency (like NSF) thinks is important.
Science is done by scientists, studies are designed by people with a perspective, and research is funded based on what policy makers think is important. Data by themselves don’t tell anyone anything. Someone decide why and how to analyze it. There is bias at every step along the way. You can’t erase that by saying ‘I don’t give recommendations’.
Sometimes the simple act of deciding not to fund a particular study can be the most strongest tool a policy maker has. As scientists, we are but pawns in the game. We only think our work is objective.
“I’m deeply embedded in conservation biology, yet you’ve never heard me advocate within my field”
But you know the specifics of your field much better than the typical conservation advocate. I’m all for letting the people who know the most about a subject discuss that subject publicly.
I think you’re making the mistake of assuming a scientists particular field is the central unit of conservation. Effective conservation need to account for many factors, not the least of which is social and economic issues that have nothing to do with my science. For me to go in as someone in a perceived position of special knowledge and say “this is what would would be best” would be sublimely arrogant and to a greater extent misguided.
Much more effective would be to ensure that the people involved know what my data says, knows its strengths and limitations, and are equipped to incorporate that data into a broader framework from which management decisions can be made.
I think whether you realize this or not, you actively practice it, which is why the bulk of your advocacy is showing people how sharks are important to ecosystems and dismantling 20 years of bad science reporting from the media.
Discussing information is not the same as advocating a position.
Which is why people have to be educated to identify those biases and understand the weaknesses inherent in any study. You can’t erase that bias, which is why you have to train people to recognize it.
But the best designed experiments and ecosystem assessments coming from a biased scientist should go out of the way to disprove the hypothesis that the scientist is biased towards. You can see these in the methods, and if those methods aren’t robust, then you have to approach those results with skepticism.
To put it much more succinctly: You should be able to trust the data, even if you can’t trust the scientist.
“Discussing information is not the same as advocating a position.”
Indeed, I don’t often advocate for specific positions (i.e. specific fisheries quotas), and I focus on making sure that people know the basics of shark’s ecological importance.
To me, though, that’s still advocacy. When telling people that sharks are important and many species are threatened with extinction, I’m clearly (though not directly or specifically) calling for protective measures.
“Effective conservation need to account for many factors, not the least of which is social and economic issues that have nothing to do with my science.”
Totally true. Deep sea mining, for example, has to do with the mineralogy of the area, as well as the economics of precious metals. However, you know to a scientific certainty that some proposed mining techniques would be disastrous to deep sea life. Is telling people “x mining technique will cause y ecological devastation” advocacy if you don’t specifically say “therefore we shouldn’t use x mining technique”?
Also, do you think it is a valid role of a scientist to say something like “if the goal is protecting Y ecosystem, then leading scientific research shows that X mining method should not be used”?
This is different from saying “X mining technique causes Y ecological devastation”, and it is different from saying “We shouldn’t use X mining technique”.
I’m just trying to get a sense of “the line” here.
X causes Y is not the same as saying don’t do X. And couching in the terms of ‘devastation’ is becoming an advocate.
Stating “an increase of 100% shark by-catch will cause a 90% reduction in shark populations, which will in turn cause a 30% rise in cownose rays populations, which will subsequently reduce scallop populations to less than 10% ” is much different from saying “doubling you shark bycatch will destroy the ecosystem”
To put it in sharky terms, what is ok for me to say?
“X fishing quota will be bad for Y sharks in Z way”
“If the goal is to benefit Y sharks, X fishing quota will not accomplish this goal”
“We shouldn’t use X fishing quota”
Um, you seem to have forgotten the important one – under my robust experimental/sampling design, the hypothesis that X does not cause Y is not supported.
As an advocate, you can say any of those.
As a scientist and advocate, you can say “these data support this decision”
As a scientist, you can say “this is the data”
If you’re really talking about fishing quotas, then your data are in the past “X fishing quota reduced the population Y amount” if you’re prediction future trendss, why talk about quotas at all? A reduction in X sharks (by over fishing, bycatch, natural disaster, spice worm attack) will have Y effect on the shark population.
You can be an advocate, but if you’re going to do both, you better go out of your way to reject your own hypothesis. Because you know that you will always be biased, you have to ensure that your data are as unbiased as possible.
What about the thought that a particular scientist can, and most will over the course of their careers, depending on the circumstances, professionally act in all four possible roles in The Honest Broker?