iPads, aviator glasses, the fake hippy look, Justin Beiber (??). All popular trends of the past few years. At least I think so, not being so trendy myself. 🙂 But if you thought science was immune to trends and trendiness – think again.
On one of my (many) job interviews, I was asked what kind of equipment I was using that was ‘new’ and ‘cutting edge’. The questioner implied that my current techniques were too basic, not Hydrology2.0 enough. She was interested less in the science than in the flashiness of the technique. This seems to be an increasing problem in science, and has the potential to obscure quality research in favour of the ‘gee wow’ factor.
Before I get too far into this argument, let me clarify that I’m no Luddite. I welcome new technologies and the advancements they bring to a range of research areas. What I don’t support is the assumption that science done with these cool gadgets is automatically better than science done without it.
For example, time lapse photography has become a very useful technique used in a range of studies, including tracking animal movements, monitoring plant phenology, and studying glacier retreat and calving. It has added to our understanding of complex processes that occur in our absence. In the case of glacier calving, for example, it has helped determine what drives calving events: tides, weather, or glacier movement.
Parks Canada wildlife camera in Banff National Park
Calving at the Belcher Glacier terminus, Devon Ice Cap (one of our research sites).
Another great technology is LiDar (Light Detection and Ranging). This advanced remote sensing technology, allows us to create very high resolution (~5 m) digital elevation models (DEMs) of the earth’s surface. These DEMs can be used to analyze topographic characteristics and plot watershed boundaries and streamflow patterns. Raw LiDar data can also be used to create high resolution maps of the forest canopy. We have a map of our study site in the Crowsnest Pass that gives the height of each individual tree within a 5 km2 watershed. Not something that could be efficiently done without this technology, and it helps our research immensely.
The biggest problem is that many people think these gadgets automatically collect good data, and forget their own role in the quality of the final dataset. One of my students was at a conference where a presenter proudly noted that their differential GPS system had allowed them to determine <1 cm changes in the position of a cliff face. What they failed to mention was that they hadn’t surveyed their GPS base station into a known coordinate system and given it a permanent marker. So every time they came to resurvey the site, the GPS was placed in a slightly different location. So much for that <1 cm accuracy. Great technology, but only as good as the user.
These tools also don’t do away with the tried and true basic techniques (much as some wish they would): meteorological stations with automated sensors. Manual discharge monitoring in streams. Basic level and rod surveying of stream reaches. Forest mensuration to characterize stand conditions. And many more.
It reminds me of a study that came out last fall in Nature or Science – of course I can’t find it now. It disproved a number of basic theories in ecology based on the results of vegetation plot studies done by research groups around the globe, and then collated and compared. No LiDar, no timelapse photography. No Bayesian analysis (all the rage in hydrology these days) or radioactive tracers. Just manual plant identification and measurement in fixed plots to define species, biomass, density, etc.
In June I’m headed to a big Canadian environmental science conference. There are a lot of interesting presentations on the books, including ones that highlight technology instead of science. This time I think I’ll stick with the good science stuff. Those shiny techno objects blinking and beeping in the corner are only as good as the scientists who use them, and while they can help us do our job – at its heart our science is only as good as we are.