Experiments, Mathematics and Theory in Ecology

Friday, March 13, 2009 at 9:50 PM Bookmark and Share
If you check wikipedia or dust off your favorite dictionary and look up the definition of "ecology" you will find something like the following:
Ecology: The branch of biology concerned with the relations between organisms and their environment.
As a branch of biology, and thus a science, you might think that ecologists have centuries old traditions (much like physicists and chemists) - doing controlled experiments in their laboratories or gardens and using the scientific method to test hypotheses and formulate scientific theories. Right?

Well, not quite. History tells us almost the opposite has been the case up until recently... very recently, come to think of it!

I had originally set out to write a single piece, but it got a bit long so I've split it into two parts: the first basically revisits the recent conversation (from the course I TA) that prompted all this, and the second is a bit of a followup heavily seasoned with a few tangents that are likely of interest.

Earlier this week in class, a friend of mine raised a question in class that caught me a little off guard. It made me realized something I had taken overlooked or granted during the past decade or two of my science education: only very, VERY recently did we begin to develop a real understanding of how organisms interact with (and respond to) the world around them. The same could probably be said of knowledge about the natural world!

But on to our example. In lecture this week (for the course "Theoretical Ecology"), we discussed some really nice work that included research done by Dr. Jef Huismann and others, currently at the Institute for Biodiversity and Ecosystem Dynamics at the University of Amsterdam.

During the hot summer months, a lake used for recreation near Amsterdam turns into a smelly, stagnant health hazard due to blooms of toxic cyanobacteria. Understandably, local parks officials wanted to find a way to continue recreational use of this increasingly smelly and toxic body of water without the drastic measures require to stop the actual problem of nutrient pollution (e.g. fertalizers) in the lake.

His group used very controlled laboratory experiments in conjunction with mathematical models of those experimental systems to understand how mixing patterns in water (e.g. due to temperature gradients) influence competition for light among different types of algae under controlled laboratory conditions (think little green beakers). These factors are known to shape the types and numbers of algae you see in small ponds and lakes, and presumably play a role in our lake. (For the philosophically inclined reader, this is using good ol' scientific reductionism being used to lay a conceptual foundation.)

Results from those small scale experiments were then combined with more complicated computer models of the hydrodynamics of an actual lake in order to understand how mixing could be used to control the algal community residing there. With that, they were able to use the models to see how different ways of artificially changing the hydrodynamics in the lake might provide a solution to the problem.

So what was the solution? Based on all the modeling and experimental work, it turned out that a little extra mixing in the right places would cause the good algae to replace the bad. With a few properly placed pumps to bubble the lake, it was returned to its more recreation-friendly state. (More details can be found in Jef's scientific papers, and also in Chapter 7 of the book Harmful Cyanobacteria - if you're interested.)

Along with the many other scientific details uncovered along the way, this is a really cool example of using experimental findings in conjunction with mathematical and/or computer models in order to do exemplary scientific work. The models extend our reasoning and deductive abilities and combined with nice experimental results, lead to a deeper understanding of how algal communities form in these sorts of ponds and lakes.

Much as mathematical models helped Newton understand and describe the laws of motion, Huismann and many other modern day ecologists use similar mathematical models to describe and make predictions about biological systems. But if the math is so similar, why weren't Newton's biologist friends (or at least their grandchildren) doing the same sorts of thing back in the 1700s?? What's so different now that we had to wait 200 years for in order to apply these techniques to biological systems the way Newton and his colleagues applied them to planetary motion?

After the instructor finished talking about Huismann's work (and some of its more technical details), a friend of mine raised his and asked essentially this question: Why didn't someone do this 50 years ago?? It seems so... rudimentary!

Naturally, we looked to the instructor anticipating his response, which was essentially this: Physicists have been using experiments and models to understand and describe natural processes since Galileo (around 1600) - Ecologists (and their biologist and other predecessors) have only been doing it since the early 1900s or later. It just took that long for folks to embrace the idea of doing experiments and using mathematics understand and describe the natural phenomena being observed.

This, admittedly, caught me a little off-guard. I'm sure my thoughts were something like "Wait, what? But, why!?" But in truth, it is an interesting question: why has it taken so long for some of the sciences to gain prominence in recent centuries and (more generally) throughout human history? What walls were broken down recently that unleashed the flood of scientific inquiry we see today?

Well, there are of course a number of ways to answer these questions - certainly many more than I am aware of. Still, I can point to a few of them. Check back for part II of this post in the next couple of days, where I'll try to address some of them.


Posted by: slybird | 3/14/2009 2:11 PM

"After the instructor finished talking about Huismann's work (and some of its more technical details), a friend of mine raised his and asked essentially this question: Why didn't someone do this 50 years ago?? It seems so... rudimentary! "

There are an infinite number of puzzles out there to solve, just waiting for someone to come along and actually ask the right question. If it hasn't been done it's because no one has been motivated to do it.

Of course, that doesn't explain the overall trend towards more rigorous experiments, modeling, and generally just better science. I'd love to hear what you can come up with.

Have you ever read:

John R. Platt (1964) Strong inference: certain systematic methods of scientific thinking may produce much more rapid progress than others. Science 146(3642)

I can email you a pdf if you want, it's a great and funny read.

Just thought I'd also mention, it's great to see you blogging.


Posted by: Paul | 5/13/2010 9:49 PM

Thanks Nick - I found the PDF online (via JSTOR). I'll be sure to give it a read. Here's a link to Part (II).

Original Date: 3/15/2009

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