One of the things that kept me going while studying Form 6 maths was the dream that, as soon as I got through STPM, I could kiss the subject goodbye. This averse reaction to mathematics isn't just limited to my personal experience. It is so common that the Quantitative Ecologist John Ollason once said, "Many of our Biology students are refugees from high-school mathematics."
Imagine my dread as I began to realise that there was no escape from all those pesky symbols and equations. As much as ecologists tend to fear anything more than simple arithmetic and the occasional average, the field has gone much further than the mere descriptive natural history that you would find on this site.
Unfortunately my romanticised view of explorers going on adventures and writing occasional vivid descriptions in their field records is how ecology was conducted more than a quarter century ago. Modern ecology is not just about jumping into forests and wrangling animals, it's a science where computers are now a necessity. It's becoming a field where knowing how to swing a parang and how to program a loop are equally important.
Living things are plenty complicated. Groups of living things, even when they are going around minding their own business, are many times more complicated than that. It is the current trend in ecology to try to simplify these complications of the real world into a mathematical model or a few figures or diagrammes.
The problem is that the math required for most of this analysis is incredibly calculation intensive and it is impossible for a human to do it in a reasonable span of time. (It's possible to try doing it manually with a pencil and paper, but it's likely that the animals that you are studying will be extinct by the time you are done).
To put into perspective how much computing power is required, we managed to put people on the moon with the Apollo Guidance Computer, which ran on a 0.001 Ghz processor. My relatively slow computer has a 1.60 GHz processor and is in every way incredibly advanced in comparison, and yet it can take an hour to run a relatively simple Bayesian model.
It may take a couple of days for more complicated datasets or models. The lack of computing power is one of the main reasons why ecology developed so slowly as a field in the late twentieth century. It is the recent and sudden increase in the availability of computing power that is pushing advances in ecology in ways that we never imagined before.
If I had a time machine and went back to Form 6 to warn myself about what ecology has become, it's possible that I wouldn't have been so keen on taking up the study of organisms and the systems that they live in. Despite that, if given a chance I don't think I would waste it on warning my younger self about my current career (Instead I'd tell myself to enjoy video games while I still had time to play them).
Ecology is one of those sciences where you get to cut your own path, both through undergrowth in the forest and in the field of study itself. To be able to discover new things and novel ways of conducting studies. I think that is what keeps me doing what I am doing, despite the need to confront the demon of mathematics that has haunted me for so long.
T.G. Goh is an entomologist based in the Museum of Zoology. He can frequently be seen walking around campus, ruminating on the state of biodiversity; it is from his shortcuts through untarred territories that he gets the inspiration for his columns. You can contact him at firstname.lastname@example.org.