A collective blind spot in measuring natural systems?


A few months ago I got a Fitbit, which for those of you who haven’t heard of it is basically a step counter. I’d been thinking about getting one for a while to help me motivate my exercise and keep my work-life balance somewhat on track. Perhaps symptomatic of not managing the balance, it took me awhile to get around to deciding what to get and actually buying it. Luckily for me, in the mean time, my husband bought one as a present and now I get to obsess about how many steps I take in a day.

The first thing I have learned is that, indeed, 10,000 steps are a lot. Although there is some debate whether 10,000 is really the goal we should all be aiming for, I had sort of assumed that I was a reasonably active person* therefore would be meeting a daily recommendation. Turns out that since I bike as a part of my commute, actually 10,000 steps doesn’t come easy for me. Even on the days when I add in a 30 min jog, I need to do more walking than normal to reach 10,000. The results of this little experiment were sobering and made me re-evaluate my assumptions about my daily activity.

So what does this have to do with ecology? Well, we all have our pet theories and assumptions about how things work. Making up stories (or as we more formally call them: hypotheses) is an incredibly fun and important part of ecology. However, we’ve all had our pet theories and robust hypotheses torn down by actual data. It is a foundation of what we ecologists do. So it isn’t surprising that the act of collecting data can change our perceptions about how things work. We’re pretty comfortable about needing actual data to determine patterns and experiments to tease apart the effects.

But there is something else I’ve noticed about having the Fitbit on. The very fact that I am counting my steps is subtly changing my behaviour. I notice myself thinking more about whether to walk up another set of stairs** or deciding to walk versus bike to our corner store. Of course, this is in part why I wanted to get a step counter in the first place but it has got me thinking about this related issue in ecology.

I think it is safe to say we all agree we need to collect data to test our theories, but we discuss much less often how the act of collecting the data could perturb the system we’re interested in. What if our measuring something alters its behaviour? What does that mean for our science? Of course experimental designs often account for this by controlling as much as possible for our treatments. It is basically why we compare treatments to controls rather than just altering something to see what happens. But the fact remains that our measurements can change the systems we’re studying and we can’t always control for that, especially if taking the measurement itself alters future outcomes. It seems that studies where we measure things multiple times are particularly vulnerable, but also fairly common in ecology (especially whenever you’re interested in fitness).

I’m of course not the first to think of these issues, if I knew more about science history I’m sure I could share lots about the development of the scientific method but alas I do not***. It is at least my impression that animal studies are more explicit about these kinds of effects but as we learn more about plant behaviour (yes, plants definitely behave), there is evidence that we need to think about plant responses to measurements too. For example, studies have looked at the effects of touch on plants (check out this sobering study: pdf) but I rarely see any mention in method sections about how experimenters’ influences were controlled for****. That said, I’m sure that the title of this post is a little strong. I’m guessing that people often think about these issues but just rarely talk about them directly. This could lead to it seeming that studies have not accounted for things that they actually have. However, silence can make it more tough for researchers starting out in a field or new system.

I’m not sure there is much to do about this problem. If me taking flower measurements changes the way the plant behaves, I have to take comfort in the fact that I measure flowers on all the plants in my dataset. The effects I introduce should be uniform and are likely to be small (bees are handling those flowers all the time for example). It is more worrying when I think about things like a hand pollination treatment where handling time for those plants is greater than the ones I leave to be naturally pollinated. I think it is important to keep aware of potential problems in our measurements and address them to the best we can. There are potential dangers in ignoring how our interference effects the patterns we see but we shouldn’t let the possibility cripple our science either. Clearly the benefits of taking measurements far outweigh any biases they introduce and we design experiments for a reason. Imagine where ecology would be if no one took measurements. Good studies tackle questions from multiple angles so that the overall picture isn’t dependent on one test and collectively we are building a picture of how the world works together. So generally I’m not concerned about our field but it is something to think about the next time you take a measurement, whether it is invasive or not.



*I mean I even have a standing desk…but clearly one needs to take it to the next level and go for a walking one🙂

**Even numbers somehow seem nicer and the fitbit counts the flights of stairs I’ve gone up. There is a reason I don’t look at my digital calliper screen when measuring floral traits. That way I know when I get a measurement ending in .00 it isn’t my doing.

***Unfortunately science history is too much of a sidetrack for me to pursue right now but maybe we have some knowledgeable commenters?

****Full disclosure, I rarely discussed potential measurement effects either. It seems we tend towards thinking about these kinds of things when the results are unexpected. I’m trying to be more conscious in my experimental designs and control for things that I can but it could take years of study to know exactly how measurements affect a study system. In the end, I hope that I can reduce the noise around any differences and convince myself that the data are telling me something real about my system.


6 thoughts on “A collective blind spot in measuring natural systems?

  1. Amy – you probably know this paper (http://www.amjbot.org/content/89/9/1401.full) by JC Cahill, about the effects of researcher visitation on plant growth. So a few people have thought about the issue; but if memory serves me right, JC had a hard time publishing that and wondered if people just didn’t want to know!

    And of course we worry about this all the time when trying to measure constitutive plant defences, since handling the plants for measurement purposes can set off induced ones.

  2. Amy, get a walk station. You can easily spin off 10,000 aerobic per day (equals about 3 hours taping on a laptop) while editing, doing email and reading; after 1-2 days on it, your frequency of typos drops to the same as it is sitting on a stationary desk.

    As for the blind spot, science is plastered with them. That is because most people do science not to understand how non-humans function, but in greater part, to achieve some other goal of the thousands people strive for. When people get into how non-humans function, really, observer effects are all over from nano to macro. If plants, insects and frogs could speak YOUR language, you would be deafened by the noise….. But it is SOP for humans (and other species) to ignore the voices of others. By and large raises your fitness to do so, except for the special cases that you elect to perceive. Smile. Dan Janzen.

  3. there is research on this. LOTS from the STS perspective and philosophically. but also from the participant/scientist side. for example, on cage effects (like enclosures for mesocosm studies) and how that impacts plant/insect studies. we just published one in Ag & For Met, Perillo et al 2015

  4. The use of drones in ecology is set to explode, and their effect on the subjects of study is also just coming to light (see links below). A good reminder to keep us on our toes!

    As for the fitbit, I too have found it to be a great motivator. It convinced me to try out a treadmill desk at our office and I am addicted to it! Given, I have always been a pacer, so I know it is not for everyone (I know more than one person who spent a pretty penny on one and barely use it). Problem is that it takes more than one day to really figure out if it can work for you.

    http://www.cell.com/current-biology/abstract/S0960-9822(15)00827-1 and http://www.npr.org/sections/alltechconsidered/2015/08/13/431982136/drones-increase-heart-rates-of-wild-bears-too-much-stress

  5. I think I will treat myself to a treadmill if I get funding to stay where I am (contract is up this year) but it will be worth it if I know I’ll be around for a few more years.

    Thanks all for the extra links! I hadn’t even thought about drones, my focus leaning towards insect cages and touching plants (the link in the post is another from JC Cahill–would love to talk to him about this issue and why he isn’t publishing more in the area).

  6. Amy, that Perillo paper I mentioned above has a table with the findings of previous insect cage study effects on plants/insects, with an eye towards how the observers did (or mostly, did not) account for the effects of their method (cages) on outcomes. I think people ignore it because it’s hard and requires more work. We had to do an entirely separate season-long experiment to our “real” experiment in order to study the cage effects, to even consider, let alone quantify, the impact of our measurement on the organisms in them.

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